hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c4a3b7fd35e583f4df4df37c10b28021b5e84c76
| 184
|
py
|
Python
|
tensorboard/acceptance/__init__.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 296
|
2020-03-16T19:55:00.000Z
|
2022-01-10T19:46:05.000Z
|
tensorboard/acceptance/__init__.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 57
|
2020-03-17T11:15:57.000Z
|
2021-07-10T14:42:27.000Z
|
tensorboard/acceptance/__init__.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 38
|
2020-03-17T21:06:05.000Z
|
2022-02-08T03:19:34.000Z
|
from .test_tensorboard_rest_api import TestTensorboardRestAPI
from .test_tensorboard_server import TestTensorboardServer
from .test_tensorboard_endpoints import TestTensorboardEndpoint
| 61.333333
| 63
| 0.923913
| 19
| 184
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| 0.578947
| 0.147239
| 0.349693
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| 0
| 0
|
0
| 5
|
c4b0cff3a089b5a105c23dc4c0935c7ecd2fb0ae
| 70
|
py
|
Python
|
checkout/orders/__init__.py
|
accelero-cloud/tutorials
|
9a9580e60bc216bf45ec0011f6d9b6b14d5a8d03
|
[
"Apache-2.0"
] | 2
|
2019-08-09T16:15:40.000Z
|
2020-01-12T09:46:28.000Z
|
checkout/orders/__init__.py
|
accelero-cloud/tutorials
|
9a9580e60bc216bf45ec0011f6d9b6b14d5a8d03
|
[
"Apache-2.0"
] | 2
|
2021-03-31T18:48:41.000Z
|
2021-12-13T19:49:46.000Z
|
checkout/orders/__init__.py
|
accelero-cloud/tutorials
|
9a9580e60bc216bf45ec0011f6d9b6b14d5a8d03
|
[
"Apache-2.0"
] | null | null | null |
from checkout.orders.order_service import Order, AuthorisationRequest
| 35
| 69
| 0.885714
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|
0
| 5
|
c4daf560e5af757855362756ff7ad96e183b2138
| 11,798
|
py
|
Python
|
pystratis/api/node/tests/test_node.py
|
TjadenFroyda/pyStratis
|
9cc7620d7506637f8a2b84003d931eceb36ac5f2
|
[
"MIT"
] | 8
|
2021-06-30T20:44:22.000Z
|
2021-12-07T14:42:22.000Z
|
pystratis/api/node/tests/test_node.py
|
TjadenFroyda/pyStratis
|
9cc7620d7506637f8a2b84003d931eceb36ac5f2
|
[
"MIT"
] | 2
|
2021-07-01T11:50:18.000Z
|
2022-01-25T18:39:49.000Z
|
pystratis/api/node/tests/test_node.py
|
TjadenFroyda/pyStratis
|
9cc7620d7506637f8a2b84003d931eceb36ac5f2
|
[
"MIT"
] | 4
|
2021-07-01T04:36:42.000Z
|
2021-09-17T10:54:19.000Z
|
import pytest
import ast
from pytest_mock import MockerFixture
from pystratis.api.node import Node
from pystratis.api.node.responsemodels import *
from pystratis.api import FullNodeState, FeatureInitializationState, LogRule
from pystratis.core.networks import StraxMain, CirrusMain
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_status_no_publish(mocker: MockerFixture, network):
data = {
'agent': 'nodeagent',
'version': 'nodeversion',
'externalAddress': '[::0.0.0.0]',
'network': network.name,
'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS',
'processId': '0',
'consensusHeight': 10,
'blockStoreHeight': 10,
'bestPeerHeight': 10,
'inboundPeers': [
{
'version': 1,
'remoteSocketEndpoint': '[::0.0.0.0]',
'tipHeight': 10
}
],
'outboundPeers': [
{
'version': 1,
'remoteSocketEndpoint': '[::0.0.0.0]',
'tipHeight': 10
}
],
'featuresData': [
{
'namespace': 'node.feature',
'state': FeatureInitializationState.Initialized
}
],
'dataDirectoryPath': '/my/data/dir',
'runningTime': 'a long time',
'difficulty': 100000.0000,
'protocolVersion': 123,
'testnet': False,
'relayFee': 0,
'state': FullNodeState.Initialized,
'inIbd': False,
'headerHeight': 1
}
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.status(publish=False)
assert response == StatusModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_status_publish(mocker: MockerFixture, network):
data = {
'agent': 'nodeagent',
'version': 'nodeversion',
'externalAddress': '[::0.0.0.0]',
'network': network.name,
'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS',
'processId': '0',
'consensusHeight': 10,
'blockStoreHeight': 10,
'bestPeerHeight': 10,
'inboundPeers': [
{
'version': 1,
'remoteSocketEndpoint': '[::0.0.0.0]',
'tipHeight': 10
}
],
'outboundPeers': [
{
'version': 1,
'remoteSocketEndpoint': '[::0.0.0.0]',
'tipHeight': 10
}
],
'featuresData': [
{
'namespace': 'node.feature',
'state': FeatureInitializationState.Initialized
}
],
'dataDirectoryPath': '/my/data/dir',
'runningTime': 'a long time',
'difficulty': 100000.0000,
'protocolVersion': 123,
'testnet': False,
'relayFee': 0,
'state': FullNodeState.Initialized,
'inIbd': False,
'headerHeight': 1
}
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.status(publish=True)
assert response == StatusModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_get_blockheader(mocker: MockerFixture, network, generate_uint256):
data = {
'version': 1,
'merkleroot': generate_uint256,
'nonce': 0,
'bits': 'bits',
'previousblockhash': generate_uint256,
'time': 1,
}
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.get_blockheader(
block_hash=generate_uint256,
is_json_format=True
)
assert response == BlockHeaderModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_get_raw_transaction_verbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256):
trxid = generate_uint256
data = generate_coinbase_transaction(trxid)
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.get_raw_transaction(trxid=trxid, verbose=True)
assert response == TransactionModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_get_raw_transaction_nonverbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256):
trxid = generate_uint256
data = generate_coinbase_transaction(trxid)
hexified_data = bytes(str(data), 'ascii').hex()
mocker.patch.object(Node, 'get', return_value=hexified_data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.get_raw_transaction(trxid=trxid, verbose=False)
assert response == hexified_data
unserialized_response = ast.literal_eval(bytes.fromhex(hexified_data).decode('ascii'))
assert data == unserialized_response
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_decode_raw_transaction(mocker: MockerFixture, network, generate_uint256, generate_coinbase_transaction):
trxid = generate_uint256
data = generate_coinbase_transaction(trxid)
hexified_data = bytes(str(data), 'ascii').hex()
mocker.patch.object(Node, 'post', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.decode_raw_transaction(raw_hex=hexified_data)
assert response == TransactionModel(**data)
# noinspection PyUnresolvedReferences
node.post.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_validate_address(mocker: MockerFixture, network, generate_p2pkh_address):
address = generate_p2pkh_address(network=network)
data = {
'isvalid': True,
'address': address,
'scriptPubKey': 'a scriptPubKey',
'isscript': False,
'iswitness': False
}
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.validate_address(address=address)
assert response == ValidateAddressModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_get_txout(mocker: MockerFixture, network, generate_uint256, generate_hexstring, generate_p2pkh_address):
data = {
'bestblock': generate_uint256,
'confirmations': 1,
'value': 5,
'scriptPubKey': {
'asm': generate_hexstring(128),
'hex': generate_hexstring(128),
'type': 'pubkey',
'reqSigs': 1,
"addresses": [
generate_p2pkh_address(network=network)
]
},
'coinbase': False
}
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.get_txout(trxid=generate_uint256, vout=0, include_mempool=False)
assert response == GetTxOutModel(**data)
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_get_txout_proof(mocker: MockerFixture, network, generate_uint256, generate_hexstring):
data = generate_hexstring(128)
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.get_txout_proof(
txids=[
generate_uint256,
generate_uint256
],
block_hash=generate_uint256
)
assert response == data
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_shutdown(mocker: MockerFixture, network):
data = None
mocker.patch.object(Node, 'post', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
node.shutdown()
# noinspection PyUnresolvedReferences
node.post.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_stop(mocker: MockerFixture, network):
data = None
mocker.patch.object(Node, 'post', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
node.stop()
# noinspection PyUnresolvedReferences
node.post.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_log_levels(mocker: MockerFixture, network):
data = None
mocker.patch.object(Node, 'put', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
node.log_levels(log_rules=[LogRule(rule_name='TestRule', log_level='Debug', filename='filename')])
# noinspection PyUnresolvedReferences
node.put.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_log_rules(mocker: MockerFixture, network):
data = [
{
'ruleName': 'TestRule',
'logLevel': 'Debug',
'filename': 'filename'
}
]
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.log_rules()
assert response == [LogRule(**x) for x in data]
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_async_loops(mocker: MockerFixture, network):
data = [
{
'loopName': 'Loop1',
'status': 'Running'
}
]
mocker.patch.object(Node, 'get', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.async_loops()
assert response == [AsyncLoopsModel(**x) for x in data]
# noinspection PyUnresolvedReferences
node.get.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_rewind(mocker: MockerFixture, network):
data = "Rewind flag set, please restart the node."
mocker.patch.object(Node, 'put', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
response = node.rewind(height=2)
assert isinstance(response, str)
# noinspection PyUnresolvedReferences
node.put.assert_called_once()
@pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain'])
def test_delete_datafolder_chain(mocker: MockerFixture, network):
data = None
mocker.patch.object(Node, 'delete', return_value=data)
node = Node(network=network, baseuri=mocker.MagicMock())
node.delete_datafolder_chain()
# noinspection PyUnresolvedReferences
node.delete.assert_called_once()
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| 121
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|
0
| 5
|
c4e9c3ba14a1425fb2bb7e78afee5ef252184d66
| 3,704
|
py
|
Python
|
pycoax/examples/40_eab.py
|
lowobservable/coax
|
9714fdfb418dff56357b9a35d2da3a91b8a60ffe
|
[
"0BSD"
] | 21
|
2020-05-11T19:46:29.000Z
|
2022-02-09T01:32:41.000Z
|
pycoax/examples/40_eab.py
|
lowobservable/coax-interface
|
614f8a5f448b1f7e8298ced2585c178f4d7f435d
|
[
"0BSD"
] | null | null | null |
pycoax/examples/40_eab.py
|
lowobservable/coax-interface
|
614f8a5f448b1f7e8298ced2585c178f4d7f435d
|
[
"0BSD"
] | 5
|
2020-07-20T08:05:10.000Z
|
2022-01-30T13:57:05.000Z
|
#!/usr/bin/env python
import sys
from itertools import chain
from common import open_example_serial_interface
from coax import read_feature_ids, parse_features, Feature, LoadAddressCounterHi, LoadAddressCounterLo, WriteData, EABWriteAlternate, EABLoadMask
def get_features(interface):
commands = read_feature_ids()
ids = interface.execute(commands)
return parse_features(ids, commands)
def eab_alternate_zip(regen_buffer, eab_buffer):
return bytes(chain(*zip(regen_buffer, eab_buffer)))
with open_example_serial_interface() as interface:
features = get_features(interface)
if Feature.EAB not in features:
sys.exit('No EAB feature found.')
eab_address = features[Feature.EAB]
print(f'EAB feature found at address {eab_address}')
# Protected Normal
interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(80)])
regen_buffer = bytes.fromhex('e0 08 00 af 91 8e 93 84 82 93 84 83 00 ad 8e 91 8c 80 8b 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09')
interface.execute(WriteData(regen_buffer))
# Protected Intense
interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(160)])
regen_buffer = bytes.fromhex('e8 08 00 af 91 8e 93 84 82 93 84 83 00 a8 8d 93 84 8d 92 84 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09')
interface.execute(WriteData(regen_buffer))
# Normal EFA
interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(64)])
regen_buffer = bytes.fromhex('e0 08 00 ad 8e 91 8c 80 8b 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0')
eab_buffer = bytes.fromhex('00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00')
interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))
# Blink EFA
interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(144)])
regen_buffer = bytes.fromhex('e0 08 00 a1 8b 88 8d 8a 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0')
eab_buffer = bytes.fromhex('40 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00')
interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))
# Reverse EFA
interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(224)])
regen_buffer = bytes.fromhex('e0 08 00 b1 84 95 84 91 92 84 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0')
eab_buffer = bytes.fromhex('80 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00')
interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))
# Underline EFA
interface.execute([LoadAddressCounterHi(2), LoadAddressCounterLo(48)])
regen_buffer = bytes.fromhex('e0 08 00 b4 8d 83 84 91 8b 88 8d 84 00 a4 a5 a0 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0')
eab_buffer = bytes.fromhex('c0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00')
interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))
| 49.386667
| 185
| 0.718952
| 745
| 3,704
| 3.502013
| 0.143624
| 0.351092
| 0.43005
| 0.530471
| 0.717133
| 0.664622
| 0.595631
| 0.528938
| 0.518973
| 0.518973
| 0
| 0.299033
| 0.218143
| 3,704
| 74
| 186
| 50.054054
| 0.601865
| 0.027538
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| 0.263158
| 0.43032
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| 1
| 0.052632
| false
| 0
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| 0.026316
| 0.210526
| 0.026316
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| null | 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
c4fab5fadfd556ed33d5c8cd6a4689c230aa1b08
| 54
|
py
|
Python
|
src/client/__init__.py
|
kyehyukahn/scp-prototype
|
4e92b47ab82068a154c407c22e8c396196a31942
|
[
"Apache-2.0"
] | 1
|
2018-04-10T11:00:59.000Z
|
2018-04-10T11:00:59.000Z
|
src/client/__init__.py
|
kyehyukahn/scp-prototype
|
4e92b47ab82068a154c407c22e8c396196a31942
|
[
"Apache-2.0"
] | null | null | null |
src/client/__init__.py
|
kyehyukahn/scp-prototype
|
4e92b47ab82068a154c407c22e8c396196a31942
|
[
"Apache-2.0"
] | null | null | null |
from .client import send_message, MessageInfo # noqa
| 27
| 53
| 0.796296
| 7
| 54
| 6
| 1
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| 0
| 0
| 0
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| 0.148148
| 54
| 1
| 54
| 54
| 0.913043
| 0.074074
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| true
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| 1
| 0
| 1
| 0
|
0
| 5
|
f21c03303c0e86780d94fa0daa72a6287b00df39
| 3,721
|
py
|
Python
|
stubs/workspaces.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
stubs/workspaces.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
stubs/workspaces.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
from . import AWSObject, AWSProperty
from .validators import *
from .constants import *
# -------------------------------------------
class WorkSpacesWorkspace(AWSObject):
"""# AWS::WorkSpaces::Workspace - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html",
"Properties": {
"BundleId": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-bundleid",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Conditional"
},
"DirectoryId": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-directoryid",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Conditional"
},
"RootVolumeEncryptionEnabled": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-rootvolumeencryptionenabled",
"PrimitiveType": "Boolean",
"Required": false,
"UpdateType": "Conditional"
},
"UserName": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-username",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Immutable"
},
"UserVolumeEncryptionEnabled": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-uservolumeencryptionenabled",
"PrimitiveType": "Boolean",
"Required": false,
"UpdateType": "Conditional"
},
"VolumeEncryptionKey": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-volumeencryptionkey",
"PrimitiveType": "String",
"Required": false,
"UpdateType": "Conditional"
}
}
}
"""
resource_type = "AWS::WorkSpaces::Workspace"
props = {
'BundleId': (basestring, True, 'Conditional', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-bundleid'),
'DirectoryId': (basestring, True, 'Conditional', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-directoryid'),
'RootVolumeEncryptionEnabled': (boolean, False, 'Conditional', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-rootvolumeencryptionenabled'),
'UserName': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-username'),
'UserVolumeEncryptionEnabled': (boolean, False, 'Conditional', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-uservolumeencryptionenabled'),
'VolumeEncryptionKey': (basestring, False, 'Conditional', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-workspaces-workspace.html#cfn-workspaces-workspace-volumeencryptionkey')
}
| 56.378788
| 228
| 0.685837
| 318
| 3,721
| 8.022013
| 0.144654
| 0.201098
| 0.056056
| 0.086633
| 0.798902
| 0.78283
| 0.699726
| 0.699726
| 0.699726
| 0.699726
| 0
| 0.000964
| 0.163934
| 3,721
| 65
| 229
| 57.246154
| 0.819029
| 0.604945
| 0
| 0
| 0
| 0.461538
| 0.715458
| 0.05472
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.230769
| 0
| 0.461538
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
4807de81e5cd93efaec1325cded4f4d3e15bd5c9
| 93
|
py
|
Python
|
aaem_summaries/components/transmission/__init__.py
|
gina-alaska/alaska_affordable_energy_model
|
96fed0137152985ce280ea37e0affec131e3087f
|
[
"MIT-feh"
] | 1
|
2022-01-23T07:18:36.000Z
|
2022-01-23T07:18:36.000Z
|
aaem_summaries/components/transmission/__init__.py
|
gina-alaska/alaska_affordable_energy_model
|
96fed0137152985ce280ea37e0affec131e3087f
|
[
"MIT-feh"
] | 5
|
2017-07-14T21:56:46.000Z
|
2017-07-14T21:59:15.000Z
|
aaem_summaries/components/transmission/__init__.py
|
gina-alaska/alaska_affordable_energy_model
|
96fed0137152985ce280ea37e0affec131e3087f
|
[
"MIT-feh"
] | 2
|
2020-04-28T18:12:55.000Z
|
2021-01-13T01:56:57.000Z
|
"""
__init__.py
summary for
Transmission Line in a community
"""
from summary import *
| 11.625
| 32
| 0.698925
| 12
| 93
| 5.083333
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.215054
| 93
| 7
| 33
| 13.285714
| 0.835616
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
4818f40bb2961d309e93cce19f1650592ac0d462
| 123
|
py
|
Python
|
src/aceinna/bootstrap/__init__.py
|
lihaiyong827/python-openimu
|
f1c536ba4182aaeabd87b63c08ebd92f97e8dbb4
|
[
"Apache-2.0"
] | 41
|
2018-07-20T17:30:33.000Z
|
2022-02-24T08:17:39.000Z
|
src/aceinna/bootstrap/__init__.py
|
lihaiyong827/python-openimu
|
f1c536ba4182aaeabd87b63c08ebd92f97e8dbb4
|
[
"Apache-2.0"
] | 52
|
2018-06-25T22:15:14.000Z
|
2022-03-10T07:30:56.000Z
|
src/aceinna/bootstrap/__init__.py
|
lihaiyong827/python-openimu
|
f1c536ba4182aaeabd87b63c08ebd92f97e8dbb4
|
[
"Apache-2.0"
] | 31
|
2018-12-19T00:10:08.000Z
|
2022-03-19T02:14:03.000Z
|
import sys
import os
import traceback
from .default import Default
from .cli import CommandLine
from .loader import Loader
| 17.571429
| 28
| 0.829268
| 18
| 123
| 5.666667
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146341
| 123
| 7
| 29
| 17.571429
| 0.971429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
482f35fcca776fd3b82f536d756e301830e31fbf
| 83
|
py
|
Python
|
libs/models/__init__.py
|
tonyngjichun/pspnet-pytorch
|
75297aa4fdb4f7a712ef9185be1ec805044f8328
|
[
"MIT"
] | 56
|
2017-12-07T12:29:14.000Z
|
2021-05-14T16:45:59.000Z
|
libs/models/__init__.py
|
tonyngjichun/pspnet-pytorch
|
75297aa4fdb4f7a712ef9185be1ec805044f8328
|
[
"MIT"
] | 7
|
2017-12-26T09:00:23.000Z
|
2019-01-14T03:55:56.000Z
|
libs/models/__init__.py
|
tonyngjichun/pspnet-pytorch
|
75297aa4fdb4f7a712ef9185be1ec805044f8328
|
[
"MIT"
] | 16
|
2017-12-20T00:36:51.000Z
|
2020-12-31T07:41:06.000Z
|
from __future__ import absolute_import
from .resnet import *
from .pspnet import *
| 20.75
| 38
| 0.807229
| 11
| 83
| 5.636364
| 0.545455
| 0.322581
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144578
| 83
| 3
| 39
| 27.666667
| 0.873239
| 0
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| null | 1
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| null | 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
4866676df99cb56da6528e0c45d5fc2aef3aec92
| 13,162
|
py
|
Python
|
tools/harness/tests/compiler-rt_builtins.py
|
Harvard-PRINCESS/barrelfish-trunk-mirror
|
1c98195d123046d985bb3952a591297c2ef6fdf9
|
[
"MIT"
] | 4
|
2017-09-16T01:23:48.000Z
|
2017-09-22T08:02:47.000Z
|
tools/harness/tests/compiler-rt_builtins.py
|
Harvard-PRINCESS/barrelfish-trunk-mirror
|
1c98195d123046d985bb3952a591297c2ef6fdf9
|
[
"MIT"
] | null | null | null |
tools/harness/tests/compiler-rt_builtins.py
|
Harvard-PRINCESS/barrelfish-trunk-mirror
|
1c98195d123046d985bb3952a591297c2ef6fdf9
|
[
"MIT"
] | 1
|
2020-03-06T15:48:10.000Z
|
2020-03-06T15:48:10.000Z
|
##########################################################################
# Copyright (c) 2009, ETH Zurich.
# All rights reserved.
#
# This file is distributed under the terms in the attached LICENSE file.
# If you do not find this file, copies can be found by writing to:
# ETH Zurich D-INFK, Haldeneggsteig 4, CH-8092 Zurich. Attn: Systems Group.
##########################################################################
import tests
from common import TestCommon
from results import PassFailMultiResult
class CompilerRTBuiltinsAbstract(TestCommon):
def get_finish_string(self):
return "usleeptest_done"
def process_data(self, testdir, rawiter):
# the test passed if no error occurred
errors = []
for line in rawiter:
if "error in" in line:
errors.append(line)
if line.startswith("Assertion failed on core"):
errors.append(line)
return PassFailMultiResult(self.name, errors)
# lists of tests to run for compiler-rt
vector_fp_tests = [
"compiler-rt/test/builtins/Unit/adddf3vfp_test",
"compiler-rt/test/builtins/Unit/addsf3vfp_test",
"compiler-rt/test/builtins/Unit/divdf3vfp_test",
"compiler-rt/test/builtins/Unit/divsf3vfp_test",
"compiler-rt/test/builtins/Unit/eqdf2vfp_test",
"compiler-rt/test/builtins/Unit/eqsf2vfp_test",
"compiler-rt/test/builtins/Unit/extebdsfdf2vfp_test",
"compiler-rt/test/builtins/Unit/fixdfsivfp_test",
"compiler-rt/test/builtins/Unit/fixsfsivfp_test",
"compiler-rt/test/builtins/Unit/fixunsdfsivfp_test",
"compiler-rt/test/builtins/Unit/fixunssfsivfp_test",
"compiler-rt/test/builtins/Unit/floatsidfvfp_test",
"compiler-rt/test/builtins/Unit/floatsisfvfp_test",
"compiler-rt/test/builtins/Unit/floatunssidfvfp_test",
"compiler-rt/test/builtins/Unit/floatunssisfvfp_test",
"compiler-rt/test/builtins/Unit/gedf2vfp_test",
"compiler-rt/test/builtins/Unit/gesf2vfp_test",
"compiler-rt/test/builtins/Unit/gtdf2vfp_test",
"compiler-rt/test/builtins/Unit/gtsf2vfp_test",
"compiler-rt/test/builtins/Unit/ledf2vfp_test",
"compiler-rt/test/builtins/Unit/lesf2vfp_test",
"compiler-rt/test/builtins/Unit/ltdf2vfp_test",
"compiler-rt/test/builtins/Unit/ltsf2vfp_test",
"compiler-rt/test/builtins/Unit/muldf3vfp_test",
"compiler-rt/test/builtins/Unit/mulsf3vfp_test",
"compiler-rt/test/builtins/Unit/nedf2vfp_test",
"compiler-rt/test/builtins/Unit/negdf2vfp_test",
"compiler-rt/test/builtins/Unit/negsf2vfp_test",
"compiler-rt/test/builtins/Unit/nesf2vfp_test",
"compiler-rt/test/builtins/Unit/subdf3vfp_test",
"compiler-rt/test/builtins/Unit/subsf3vfp_test",
"compiler-rt/test/builtins/Unit/truncdfsf2vfp_test",
"compiler-rt/test/builtins/Unit/unorddf2vfp_test",
"compiler-rt/test/builtins/Unit/unordsf2vfp_test",
]
@tests.add_test
class CompilerRTBuiltinsVfp(CompilerRTBuiltinsAbstract):
name = 'compiler-rt-vfp'
def get_modules(self, build, machine):
modules = super(CompilerRTBuiltinsVfp, self).get_modules(build, machine)
for m in vector_fp_tests:
modules.add_module(m)
modules.add_module("usleeptest", [ "5" ])
return modules
fp_tests = [
"compiler-rt/test/builtins/Unit/absvdi2_test",
"compiler-rt/test/builtins/Unit/absvsi2_test",
"compiler-rt/test/builtins/Unit/absvti2_test",
"compiler-rt/test/builtins/Unit/addtf3_test",
"compiler-rt/test/builtins/Unit/addvdi3_test",
"compiler-rt/test/builtins/Unit/addvsi3_test",
"compiler-rt/test/builtins/Unit/addvti3_test",
"compiler-rt/test/builtins/Unit/ashldi3_test",
"compiler-rt/test/builtins/Unit/ashlti3_test",
"compiler-rt/test/builtins/Unit/ashrdi3_test",
"compiler-rt/test/builtins/Unit/ashrti3_test",
"compiler-rt/test/builtins/Unit/bswapdi2_test",
"compiler-rt/test/builtins/Unit/bswapsi2_test",
# "compiler-rt/test/builtins/Unit/clear_cache_test",
"compiler-rt/test/builtins/Unit/clzdi2_test",
"compiler-rt/test/builtins/Unit/clzsi2_test",
"compiler-rt/test/builtins/Unit/clzti2_test",
"compiler-rt/test/builtins/Unit/cmpdi2_test",
"compiler-rt/test/builtins/Unit/cmpti2_test",
"compiler-rt/test/builtins/Unit/comparedf2_test",
"compiler-rt/test/builtins/Unit/comparesf2_test",
"compiler-rt/test/builtins/Unit/ctzdi2_test",
"compiler-rt/test/builtins/Unit/ctzsi2_test",
"compiler-rt/test/builtins/Unit/ctzti2_test",
"compiler-rt/test/builtins/Unit/divdc3_test",
"compiler-rt/test/builtins/Unit/divdi3_test",
"compiler-rt/test/builtins/Unit/divmodsi4_test",
"compiler-rt/test/builtins/Unit/divsc3_test",
"compiler-rt/test/builtins/Unit/divsi3_test",
# "compiler-rt/test/builtins/Unit/divtc3_test",
"compiler-rt/test/builtins/Unit/divtf3_test",
"compiler-rt/test/builtins/Unit/divti3_test",
"compiler-rt/test/builtins/Unit/divxc3_test",
# "compiler-rt/test/builtins/Unit/enable_execute_stack_test",
"compiler-rt/test/builtins/Unit/eqtf2_test",
"compiler-rt/test/builtins/Unit/extenddftf2_test",
# "compiler-rt/test/builtins/Unit/extendhfsf2_test",
"compiler-rt/test/builtins/Unit/extendsftf2_test",
"compiler-rt/test/builtins/Unit/ffsdi2_test",
"compiler-rt/test/builtins/Unit/ffsti2_test",
"compiler-rt/test/builtins/Unit/fixdfdi_test",
"compiler-rt/test/builtins/Unit/fixdfti_test",
"compiler-rt/test/builtins/Unit/fixsfdi_test",
"compiler-rt/test/builtins/Unit/fixsfti_test",
"compiler-rt/test/builtins/Unit/fixtfdi_test",
"compiler-rt/test/builtins/Unit/fixtfsi_test",
"compiler-rt/test/builtins/Unit/fixtfti_test",
# this errors on 0X1P+64
#"compiler-rt/test/builtins/Unit/fixunsdfdi_test",
"compiler-rt/test/builtins/Unit/fixunsdfsi_test",
"compiler-rt/test/builtins/Unit/fixunsdfti_test",
# this errors on 0X1P+64
#"compiler-rt/test/builtins/Unit/fixunssfdi_test",
"compiler-rt/test/builtins/Unit/fixunssfsi_test",
"compiler-rt/test/builtins/Unit/fixunssfti_test",
"compiler-rt/test/builtins/Unit/fixunstfdi_test",
"compiler-rt/test/builtins/Unit/fixunstfsi_test",
"compiler-rt/test/builtins/Unit/fixunstfti_test",
"compiler-rt/test/builtins/Unit/fixunsxfdi_test",
"compiler-rt/test/builtins/Unit/fixunsxfsi_test",
"compiler-rt/test/builtins/Unit/fixunsxfti_test",
"compiler-rt/test/builtins/Unit/fixxfdi_test",
"compiler-rt/test/builtins/Unit/fixxfti_test",
"compiler-rt/test/builtins/Unit/floatdidf_test",
"compiler-rt/test/builtins/Unit/floatdisf_test",
"compiler-rt/test/builtins/Unit/floatditf_test",
"compiler-rt/test/builtins/Unit/floatdixf_test",
"compiler-rt/test/builtins/Unit/floatsitf_test",
"compiler-rt/test/builtins/Unit/floattidf_test",
"compiler-rt/test/builtins/Unit/floattisf_test",
"compiler-rt/test/builtins/Unit/floattixf_test",
"compiler-rt/test/builtins/Unit/floatundidf_test",
"compiler-rt/test/builtins/Unit/floatundisf_test",
"compiler-rt/test/builtins/Unit/floatunditf_test",
"compiler-rt/test/builtins/Unit/floatundixf_test",
"compiler-rt/test/builtins/Unit/floatunsitf_test",
"compiler-rt/test/builtins/Unit/floatuntidf_test",
"compiler-rt/test/builtins/Unit/floatuntisf_test",
"compiler-rt/test/builtins/Unit/floatuntixf_test",
# "compiler-rt/test/builtins/Unit/gcc_personality_test",
"compiler-rt/test/builtins/Unit/getf2_test",
"compiler-rt/test/builtins/Unit/gttf2_test",
"compiler-rt/test/builtins/Unit/letf2_test",
"compiler-rt/test/builtins/Unit/lshrdi3_test",
"compiler-rt/test/builtins/Unit/lshrti3_test",
"compiler-rt/test/builtins/Unit/lttf2_test",
"compiler-rt/test/builtins/Unit/moddi3_test",
"compiler-rt/test/builtins/Unit/modsi3_test",
"compiler-rt/test/builtins/Unit/modti3_test",
"compiler-rt/test/builtins/Unit/muldc3_test",
"compiler-rt/test/builtins/Unit/muldi3_test",
"compiler-rt/test/builtins/Unit/mulodi4_test",
"compiler-rt/test/builtins/Unit/mulosi4_test",
"compiler-rt/test/builtins/Unit/muloti4_test",
"compiler-rt/test/builtins/Unit/mulsc3_test",
"compiler-rt/test/builtins/Unit/multc3_test",
"compiler-rt/test/builtins/Unit/multf3_test",
"compiler-rt/test/builtins/Unit/multi3_test",
"compiler-rt/test/builtins/Unit/mulvdi3_test",
"compiler-rt/test/builtins/Unit/mulvsi3_test",
"compiler-rt/test/builtins/Unit/mulvti3_test",
"compiler-rt/test/builtins/Unit/mulxc3_test",
"compiler-rt/test/builtins/Unit/negdi2_test",
"compiler-rt/test/builtins/Unit/negti2_test",
"compiler-rt/test/builtins/Unit/negvdi2_test",
"compiler-rt/test/builtins/Unit/negvsi2_test",
"compiler-rt/test/builtins/Unit/negvti2_test",
"compiler-rt/test/builtins/Unit/netf2_test",
"compiler-rt/test/builtins/Unit/paritydi2_test",
"compiler-rt/test/builtins/Unit/paritysi2_test",
"compiler-rt/test/builtins/Unit/parityti2_test",
"compiler-rt/test/builtins/Unit/popcountdi2_test",
"compiler-rt/test/builtins/Unit/popcountsi2_test",
"compiler-rt/test/builtins/Unit/popcountti2_test",
"compiler-rt/test/builtins/Unit/powidf2_test",
"compiler-rt/test/builtins/Unit/powisf2_test",
"compiler-rt/test/builtins/Unit/powitf2_test",
"compiler-rt/test/builtins/Unit/powixf2_test",
"compiler-rt/test/builtins/Unit/subtf3_test",
"compiler-rt/test/builtins/Unit/subvdi3_test",
"compiler-rt/test/builtins/Unit/subvsi3_test",
"compiler-rt/test/builtins/Unit/subvti3_test",
# "compiler-rt/test/builtins/Unit/trampoline_setup_test",
# "compiler-rt/test/builtins/Unit/truncdfhf2_test",
"compiler-rt/test/builtins/Unit/truncdfsf2_test",
# "compiler-rt/test/builtins/Unit/truncsfhf2_test",
"compiler-rt/test/builtins/Unit/trunctfdf2_test",
"compiler-rt/test/builtins/Unit/trunctfsf2_test",
"compiler-rt/test/builtins/Unit/ucmpdi2_test",
"compiler-rt/test/builtins/Unit/ucmpti2_test",
"compiler-rt/test/builtins/Unit/udivdi3_test",
"compiler-rt/test/builtins/Unit/udivmoddi4_test",
"compiler-rt/test/builtins/Unit/udivmodsi4_test",
"compiler-rt/test/builtins/Unit/udivmodti4_test",
"compiler-rt/test/builtins/Unit/udivsi3_test",
"compiler-rt/test/builtins/Unit/udivti3_test",
"compiler-rt/test/builtins/Unit/umoddi3_test",
"compiler-rt/test/builtins/Unit/umodsi3_test",
"compiler-rt/test/builtins/Unit/umodti3_test",
"compiler-rt/test/builtins/Unit/unordtf2_test",
]
def get_modules_tpl(ts, self, build, machine):
'''Function template for get_modules() for each compiler-rt test case'''
modules = super(CompilerRTBuiltinsAbstract, self).get_modules(build, machine)
for m in ts:
if machine.name.startswith("panda") and \
(m.endswith("floatdisf_test") or m.endswith("floatdidf_test")):
# Skip failing test on pandaboard
continue
modules.add_module(m)
modules.add_module("usleeptest", [ "5" ])
return modules
def chunker(seq, size):
'''Helper function: this takes a sequence `seq` and splits it up into
`size`-sized chunks, except for the last chunk which is just the <= size
long remainder of the sequence'''
return (seq[pos:pos+size] for pos in xrange(0, len(seq), size))
# generate test-cases with <=CHUNK_SIZE compiler-rt tests each
CHUNK_SIZE=35
# array just to keep the class objects somewhere
compiler_rt_tests_classes = []
for i, ts in enumerate(chunker(fp_tests, CHUNK_SIZE)):
# append new class to our array
compiler_rt_tests_classes.append(
# this is essentially the decorator @tests.add_test
tests.add_test(
# type is the (built-in) base-class for python classes, here we
# construct classes by calling its constructor
# signature of type constructor:
# type(classname, baseclass tuple, dict with methods/attributes)
type('CompilerRTBuiltins%d' % (i+1),
(CompilerRTBuiltinsAbstract,),
{ 'name': 'compiler-rt-fp%d' % (i+1),
# partially bind the get_modules() template to select the
# right set of tests. Note the ts=ts in the lambda
# arguments, this prevents python's default late-binding
# for closure arguments.
'get_modules':
lambda s, b, m, ts=ts: get_modules_tpl(ts, s, b, m)})))
| 50.429119
| 81
| 0.677557
| 1,637
| 13,162
| 5.316433
| 0.219914
| 0.205676
| 0.278295
| 0.434793
| 0.618178
| 0.618178
| 0.039067
| 0.031483
| 0.02413
| 0.02413
| 0
| 0.013682
| 0.183711
| 13,162
| 260
| 82
| 50.623077
| 0.796351
| 0.136226
| 0
| 0.038095
| 0
| 0
| 0.655416
| 0.640376
| 0
| 0
| 0
| 0
| 0.004762
| 1
| 0.02381
| false
| 0.009524
| 0.014286
| 0.004762
| 0.07619
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
6f801ba5e156e09ae80a405057d4699d1492e731
| 7,182
|
py
|
Python
|
barry/convert.py
|
jyotiska/barry
|
53f3b3f8c070cbc5b2d9dcadebe9f776d170b6ed
|
[
"MIT"
] | null | null | null |
barry/convert.py
|
jyotiska/barry
|
53f3b3f8c070cbc5b2d9dcadebe9f776d170b6ed
|
[
"MIT"
] | null | null | null |
barry/convert.py
|
jyotiska/barry
|
53f3b3f8c070cbc5b2d9dcadebe9f776d170b6ed
|
[
"MIT"
] | null | null | null |
from exceptions import BarryFileException, BarryConversionException, BarryExportException, BarryDFException
import pandas as pd
import requests
from StringIO import StringIO
def detect_file_extension(filename):
"""Extract and return the extension of a file given a filename.
Args:
filename (str): name of the file
Returns:
str: extension of the file
Raises:
BarryFileException: if extension not present in filename
"""
if filename is None:
raise BarryFileException("Input file name cannot be None")
split_filename = filename.split(".")
if len(split_filename) > 1:
return str(split_filename[-1]).lower()
else:
raise BarryFileException("Could not determine input file type from file extension")
def xls_to_df(filename, skip_rows, skip_header, columns):
"""Converts a XLS file to Pandas dataframe.
Args:
filename (str): name of the file
skip_rows (int): number of rows to skip from top
skip_header (bool): whether to skip header
columns (list or None): list of column names
Returns:
dataframe: a pandas dataframe
Raises:
BarryConversionException: if file cannot be converted to dataframe
"""
try:
# Check if columns names has been passed
if columns is not None and len(columns) > 0:
skip_header = 0
# Check if header needs to be skipped
if skip_header is True:
skip_header = None
else:
skip_header = 0
return pd.read_excel(filename, skiprows=skip_rows, header=skip_header, names=columns)
except Exception as e:
raise BarryConversionException("Could not convert file %s to dataframe" % (filename))
def xlsx_to_df(filename, skip_rows, skip_header, columns):
"""Converts a XLSX file to Pandas dataframe.
Args:
filename (str): name of the file
skip_rows (int): number of rows to skip from top
skip_header (bool): whether to skip header
columns (list or None): list of column names
Returns:
dataframe: a pandas dataframe
Raises:
BarryConversionException: if file cannot be converted to dataframe
"""
try:
# Check if columns names has been passed
if columns is not None and len(columns) > 0:
skip_header = 0
# Check if header needs to be skipped
if skip_header is True:
skip_header = None
else:
skip_header = 0
return pd.read_excel(filename, skiprows=skip_rows, header=skip_header, names=columns)
except Exception as e:
raise BarryConversionException("Could not convert file %s to dataframe" % (filename))
def csv_to_df(filename, skip_rows, skip_header, columns):
"""Converts a CSV file to Pandas dataframe.
Args:
filename (str): name of the file
skip_rows (int): number of rows to skip from top
skip_header (bool): whether to skip header
columns (list or None): list of column names
Returns:
dataframe: a pandas dataframe
Raises:
BarryConversionException: if file cannot be converted to dataframe
"""
try:
# Check if columns names has been passed
if columns is not None and len(columns) > 0:
skip_header = 0
# Check if header needs to be skipped
if skip_header is True:
skip_header = None
else:
skip_header = 0
return pd.read_csv(filename, skiprows=skip_rows, header=skip_header, names=columns)
except Exception as e:
raise BarryConversionException("Could not convert file %s to dataframe" % (filename))
def url_to_df(url, skip_rows, skip_header, columns):
"""Converts a CSV from HTTP URL to Pandas dataframe.
Args:
url (str): http url of the csv
skip_rows (int): number of rows to skip from top
skip_header (bool): whether to skip header
columns (list or None): list of column names
Returns:
dataframe: a pandas dataframe
Raises:
BarryConversionException: if file cannot be converted to dataframe
"""
try:
# Check if columns names has been passed
if columns is not None and len(columns) > 0:
skip_header = 0
# Check if header needs to be skipped
if skip_header is True:
skip_header = None
else:
skip_header = 0
url_content = requests.get(url).content
return pd.read_csv(StringIO(url_content), skiprows=skip_rows, header=skip_header, names=columns)
except Exception as e:
raise BarryConversionException("Could not convert file %s to dataframe" % (filename))
def df_to_xls(df, out_filename):
"""Writes a Pandas dataframe to a XLS file.
Args:
df (dataframe): dataframe to be written to file
filename (str): name of the file
Raises:
BarryExportException: if file cannot be converted to dataframe
"""
try:
df.to_excel(out_filename)
except Exception as e:
raise BarryExportException("Could not write dataframe to file %s" % (out_filename))
def df_to_xlsx(df, out_filename):
"""Writes a Pandas dataframe to a XLS file.
Args:
df (dataframe): dataframe to be written to file
filename (str): name of the file
Raises:
BarryExportException: if file cannot be converted to dataframe
"""
try:
df.to_excel(out_filename)
except Exception as e:
raise BarryExportException("Could not write dataframe to file %s" % (out_filename))
def df_to_json(df, out_filename):
"""Writes a Pandas dataframe to a JSON file.
Args:
df (dataframe): dataframe to be written to file
filename (str): name of the file
Raises:
BarryExportException: if file cannot be converted to dataframe
"""
try:
df.to_json(out_filename)
except Exception as e:
raise BarryExportException("Could not write dataframe to file %s" % (out_filename))
def df_to_csv(df, out_filename):
"""Writes a Pandas dataframe to a CSV file.
Args:
df (dataframe): dataframe to be written to file
filename (str): name of the file
Raises:
BarryExportException: if file cannot be converted to dataframe
"""
try:
df.to_csv(out_filename)
except Exception as e:
raise BarryExportException("Could not write dataframe to file %s" % (out_filename))
def sort_df(df, sort_column, ascending):
"""Sort a DataFrame with the column name passed in ascending/descending order.
Args:
df (dataframe): dataframe that needs to be sorted
sort_column (str): column to be sorted on
ascending (bool): sort order, ascending if True, descending if False
Returns:
dataframe: a pandas dataframe
Raises:
BarryDFException: if there is any error while sorting the dataframe
"""
try:
return df.sort(columns=sort_column, ascending=ascending)
except Exception as e:
raise BarryDFException("Could not sort dataframe on columns %s" % (sort_column))
| 31.362445
| 107
| 0.657059
| 946
| 7,182
| 4.895349
| 0.114165
| 0.0691
| 0.017491
| 0.034982
| 0.764414
| 0.759447
| 0.751242
| 0.745195
| 0.736558
| 0.720147
| 0
| 0.002696
| 0.276942
| 7,182
| 228
| 108
| 31.5
| 0.889081
| 0.441938
| 0
| 0.670732
| 0
| 0
| 0.116022
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.121951
| false
| 0
| 0.04878
| 0
| 0.243902
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
6f86e19366559629464f6c94fe703e3f9d6154c1
| 956
|
py
|
Python
|
lessons/terminal.report.py
|
thepros847/python_programiing
|
d177f79d0d1f21df434bf3f8663ae6469fcf8357
|
[
"MIT"
] | null | null | null |
lessons/terminal.report.py
|
thepros847/python_programiing
|
d177f79d0d1f21df434bf3f8663ae6469fcf8357
|
[
"MIT"
] | null | null | null |
lessons/terminal.report.py
|
thepros847/python_programiing
|
d177f79d0d1f21df434bf3f8663ae6469fcf8357
|
[
"MIT"
] | null | null | null |
#students exams data entries for terminal report card
print("Westside Educational Complex--End Of second Terminal Report--Class-KKJA--Name:Theodora Obaa Yaa Gyarbeng")
while True:
student_score = float(input ("Enter the student score:"))
if student_score >= 1.0 and student_score <= 39.9:
print("student_score is F9", "fail")
elif student_score >= 40 and student_score <= 49.9:
print("student_score is E8", "pass" )
elif student_score >= 50 and student_score <= 59.9:
print("student_score is D7", "credit")
elif student_score >= 60 and student_score <= 69.9:
print("student_score is C4", "good")
elif student_score >= 70 and student_score <= 79.9:
print("student_score is B2", "very_good")
elif student_score >= 80 and student_score <= 100:
print("student_score is A1", "excellent")
else:
print("student_score is invalid entry")
student = []
| 39.833333
| 113
| 0.654812
| 133
| 956
| 4.548872
| 0.473684
| 0.416529
| 0.196694
| 0.219835
| 0.165289
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049046
| 0.232218
| 956
| 23
| 114
| 41.565217
| 0.775204
| 0.054393
| 0
| 0
| 0
| 0
| 0.341463
| 0.036585
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.055556
| 0
| 0
| 0
| 0.444444
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
|
0
| 5
|
6fc09d38fc6e352436484c44be3ed1f477d458b5
| 109
|
py
|
Python
|
servermn/core/__init__.py
|
masterhung0112/servermn
|
d518f2fa394bb3e22c29e74802357c2aa054f392
|
[
"Unlicense"
] | null | null | null |
servermn/core/__init__.py
|
masterhung0112/servermn
|
d518f2fa394bb3e22c29e74802357c2aa054f392
|
[
"Unlicense"
] | null | null | null |
servermn/core/__init__.py
|
masterhung0112/servermn
|
d518f2fa394bb3e22c29e74802357c2aa054f392
|
[
"Unlicense"
] | null | null | null |
def init():
# Set locale environment
# Set config
# Set user and group
# init logger
pass
| 18.166667
| 28
| 0.59633
| 14
| 109
| 4.642857
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.33945
| 109
| 6
| 29
| 18.166667
| 0.902778
| 0.587156
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
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| 0
| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| 1
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
6ff24a30aea978a6baf63da8c2c0d8819e5f801c
| 19
|
py
|
Python
|
beeline/version.py
|
noam-stein/beeline-python
|
a5ae7b30d9abebc681524f1087c404fb2e2b915f
|
[
"Apache-2.0"
] | null | null | null |
beeline/version.py
|
noam-stein/beeline-python
|
a5ae7b30d9abebc681524f1087c404fb2e2b915f
|
[
"Apache-2.0"
] | null | null | null |
beeline/version.py
|
noam-stein/beeline-python
|
a5ae7b30d9abebc681524f1087c404fb2e2b915f
|
[
"Apache-2.0"
] | null | null | null |
VERSION = '2.11.2'
| 9.5
| 18
| 0.578947
| 4
| 19
| 2.75
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0.157895
| 19
| 1
| 19
| 19
| 0.4375
| 0
| 0
| 0
| 0
| 0
| 0.315789
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
b512b2de6527126b947a320b79c117609580ec75
| 114
|
py
|
Python
|
pyquil/__init__.py
|
ftripier/pyquil
|
573d5ae64bbc594917ad46885fca0d8f5f3fe0e9
|
[
"Apache-2.0"
] | null | null | null |
pyquil/__init__.py
|
ftripier/pyquil
|
573d5ae64bbc594917ad46885fca0d8f5f3fe0e9
|
[
"Apache-2.0"
] | null | null | null |
pyquil/__init__.py
|
ftripier/pyquil
|
573d5ae64bbc594917ad46885fca0d8f5f3fe0e9
|
[
"Apache-2.0"
] | null | null | null |
__version__ = "2.1.0.dev0"
from pyquil.quil import Program
from pyquil.api import list_quantum_computers, get_qc
| 22.8
| 53
| 0.807018
| 19
| 114
| 4.473684
| 0.842105
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039604
| 0.114035
| 114
| 4
| 54
| 28.5
| 0.80198
| 0
| 0
| 0
| 0
| 0
| 0.087719
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
82ff0515b3da6ec57b02cf613a0fd6672311351d
| 150
|
py
|
Python
|
src/posts/templatetags/urlify.py
|
thunderoy/blogger
|
8102d11c04fbc98a31298ebfdb75023e9207109f
|
[
"MIT"
] | null | null | null |
src/posts/templatetags/urlify.py
|
thunderoy/blogger
|
8102d11c04fbc98a31298ebfdb75023e9207109f
|
[
"MIT"
] | null | null | null |
src/posts/templatetags/urlify.py
|
thunderoy/blogger
|
8102d11c04fbc98a31298ebfdb75023e9207109f
|
[
"MIT"
] | null | null | null |
from urllib.parse import quote
from django import template
register = template.Library()
@register.filter
def urlify(value):
return quote(value)
| 18.75
| 30
| 0.78
| 20
| 150
| 5.85
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14
| 150
| 8
| 31
| 18.75
| 0.906977
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.333333
| 0.166667
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
d2025b2a20a97cda599aa94a7ddf6c498a1acbae
| 121
|
py
|
Python
|
treeviz_test.py
|
larsga/sprake
|
32598651b2fb514b18aab4f82ffba89d606a7b74
|
[
"Apache-2.0"
] | 1
|
2022-01-26T08:50:33.000Z
|
2022-01-26T08:50:33.000Z
|
treeviz_test.py
|
larsga/sprake
|
32598651b2fb514b18aab4f82ffba89d606a7b74
|
[
"Apache-2.0"
] | null | null | null |
treeviz_test.py
|
larsga/sprake
|
32598651b2fb514b18aab4f82ffba89d606a7b74
|
[
"Apache-2.0"
] | null | null | null |
from sprake import treeviz
# we don't actually have any meaningful tests that we can do, but at least
# we can do this
| 20.166667
| 74
| 0.752066
| 23
| 121
| 3.956522
| 0.826087
| 0.10989
| 0.153846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214876
| 121
| 5
| 75
| 24.2
| 0.957895
| 0.719008
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
d2045b61e5e8006918d4654b503671b6d4cfdf28
| 303
|
py
|
Python
|
source/bluetooth/test_search_serial_port.py
|
Takahiro55555/CameraSystem
|
53a77b7a7bd0c34b486d73af8ef2a49201a0bdaa
|
[
"MIT"
] | 1
|
2019-12-03T05:28:35.000Z
|
2019-12-03T05:28:35.000Z
|
source/bluetooth/test_search_serial_port.py
|
Takahiro55555/CameraSystem
|
53a77b7a7bd0c34b486d73af8ef2a49201a0bdaa
|
[
"MIT"
] | 88
|
2019-07-01T09:11:35.000Z
|
2021-09-08T01:13:16.000Z
|
source/bluetooth/test_search_serial_port.py
|
Takahiro55555/CameraSystem
|
53a77b7a7bd0c34b486d73af8ef2a49201a0bdaa
|
[
"MIT"
] | 5
|
2019-05-22T06:44:38.000Z
|
2019-09-18T05:20:30.000Z
|
"""
@file: test_search_serial_port.py
@author: Futa HIRAKOBA
@brief: search_serial_port.pyのをテストするプログラム
"""
from search_serial_port import search_com_ports, search_enabled_com_port
def test_search_com_ports():
search_com_ports()
def test_search_enabled_com_port():
search_enabled_com_port()
| 18.9375
| 72
| 0.808581
| 44
| 303
| 5.022727
| 0.386364
| 0.135747
| 0.217195
| 0.271493
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108911
| 303
| 15
| 73
| 20.2
| 0.818519
| 0.323432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
d22021e322a81ec24f4d2957e1994d21c7ec3963
| 52
|
py
|
Python
|
interrogatio/shortcuts/__init__.py
|
ffaraone/interrogatio
|
8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1
|
[
"BSD-3-Clause"
] | 5
|
2019-02-19T13:10:39.000Z
|
2022-03-04T19:11:04.000Z
|
interrogatio/shortcuts/__init__.py
|
ffaraone/interrogatio
|
8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1
|
[
"BSD-3-Clause"
] | 11
|
2020-03-24T16:58:41.000Z
|
2021-12-14T10:19:17.000Z
|
interrogatio/shortcuts/__init__.py
|
ffaraone/interrogatio
|
8b66e7fe73d14bfda38cc2eb3aecb3291e4afda1
|
[
"BSD-3-Clause"
] | 2
|
2019-05-31T08:36:26.000Z
|
2020-12-18T17:58:50.000Z
|
from interrogatio.shortcuts.dialogs import * # noqa
| 52
| 52
| 0.807692
| 6
| 52
| 7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 52
| 1
| 52
| 52
| 0.913043
| 0.076923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
d2213ea96c7a47974d92d29c00540c2195a53bed
| 69
|
py
|
Python
|
vivid/__init__.py
|
blacktanktop/vivid
|
e85837bcd86575f8a275517250dd026aac3e451f
|
[
"BSD-2-Clause-FreeBSD"
] | 39
|
2020-05-13T18:13:25.000Z
|
2022-03-02T10:46:53.000Z
|
vivid/__init__.py
|
blacktanktop/vivid
|
e85837bcd86575f8a275517250dd026aac3e451f
|
[
"BSD-2-Clause-FreeBSD"
] | 29
|
2020-05-13T18:04:09.000Z
|
2022-02-27T04:43:18.000Z
|
vivid/__init__.py
|
blacktanktop/vivid
|
e85837bcd86575f8a275517250dd026aac3e451f
|
[
"BSD-2-Clause-FreeBSD"
] | 3
|
2020-05-13T19:17:01.000Z
|
2020-10-28T21:29:42.000Z
|
from .core import BaseBlock
from .runner import Runner, create_runner
| 34.5
| 41
| 0.84058
| 10
| 69
| 5.7
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115942
| 69
| 2
| 41
| 34.5
| 0.934426
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
d25543f2eb84e1a829ecf2a781633ed4850daa4c
| 599
|
py
|
Python
|
examples/ec2/tests/config.py
|
dabble-of-devops-biodeploy/terraform-aws-batch
|
9d075163821f81f33d6be767820d1db20b45eb8e
|
[
"Apache-2.0"
] | 3
|
2021-12-07T18:10:16.000Z
|
2022-02-04T09:15:31.000Z
|
examples/ec2/tests/config.py
|
dabble-of-devops-biodeploy/terraform-aws-batch
|
9d075163821f81f33d6be767820d1db20b45eb8e
|
[
"Apache-2.0"
] | null | null | null |
examples/ec2/tests/config.py
|
dabble-of-devops-biodeploy/terraform-aws-batch
|
9d075163821f81f33d6be767820d1db20b45eb8e
|
[
"Apache-2.0"
] | 1
|
2022-02-22T01:48:38.000Z
|
2022-02-22T01:48:38.000Z
|
DATA_S3 = "bioanalyze-ec2-test-nf-rnaseq-06o3qdtm7v"
JOB_S3 = DATA_S3
# These come from the terraform code in auto-deployment/terraform
ECR = "dabbleofdevops/nextflow-rnaseq-tutorial"
COMPUTE_ENVIRONMENT = "bioanalyze-ec2-test-nf-rnaseq"
JOB_DEF_NAME = "bioanalyze-ec2-test-nf-rnaseq"
JOB_QUEUE_NAME = "bioanalyze-ec2-test-nf-rnaseq-default-job-queue"
JOB_ROLE = "arn:aws:iam::018835827632:role/bioanalyze-ec2-test-nf-rnaseq-batch_execution_role"
SECRET_NAME = "bioanalyze-ec2-test-nf-rnaseq"
SECRET_ARN = "arn:aws:secretsmanager:us-east-1:018835827632:secret:bioanalyze-ec2-test-nf-rnaseq-Zg7kMY"
| 49.916667
| 104
| 0.806344
| 91
| 599
| 5.164835
| 0.450549
| 0.193617
| 0.253191
| 0.282979
| 0.410638
| 0.251064
| 0
| 0
| 0
| 0
| 0
| 0.071174
| 0.06177
| 599
| 12
| 104
| 49.916667
| 0.765125
| 0.105175
| 0
| 0
| 0
| 0.222222
| 0.715888
| 0.715888
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
963e0a388ab593079d1ff2e77544ecf12fa56919
| 112
|
py
|
Python
|
reqto/__init__.py
|
DovaX/reqto
|
4d3cc03535297fb0d5c946632e9de6a3a1ec5420
|
[
"MIT"
] | null | null | null |
reqto/__init__.py
|
DovaX/reqto
|
4d3cc03535297fb0d5c946632e9de6a3a1ec5420
|
[
"MIT"
] | null | null | null |
reqto/__init__.py
|
DovaX/reqto
|
4d3cc03535297fb0d5c946632e9de6a3a1ec5420
|
[
"MIT"
] | null | null | null |
from reqto.core.reqto import get, post, delete, put, patch, head
__all__=[get, post, delete, put, patch, head]
| 28
| 64
| 0.723214
| 18
| 112
| 4.277778
| 0.611111
| 0.181818
| 0.337662
| 0.415584
| 0.649351
| 0.649351
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 112
| 4
| 65
| 28
| 0.802083
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
967705c9e8a9fd17fb6a029cb268db7aef64d726
| 198
|
py
|
Python
|
treasurehunt/views.py
|
code-haven/Django-treasurehunt-demo
|
c22aa88486d57fa97363d9d57dbbb7bc68a8ddd4
|
[
"MIT"
] | 1
|
2017-04-30T05:46:40.000Z
|
2017-04-30T05:46:40.000Z
|
treasurehunt/views.py
|
code-haven/Django-treasurehunt-demo
|
c22aa88486d57fa97363d9d57dbbb7bc68a8ddd4
|
[
"MIT"
] | null | null | null |
treasurehunt/views.py
|
code-haven/Django-treasurehunt-demo
|
c22aa88486d57fa97363d9d57dbbb7bc68a8ddd4
|
[
"MIT"
] | null | null | null |
from django.views.generic import View
from django.http import HttpResponse
from django.shortcuts import render
def index(request):
return render(request, 'treasurehunt/treasurehunt_index.html')
| 33
| 66
| 0.823232
| 26
| 198
| 6.230769
| 0.615385
| 0.185185
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106061
| 198
| 6
| 66
| 33
| 0.915254
| 0
| 0
| 0
| 0
| 0
| 0.180905
| 0.180905
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.6
| 0.2
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
96929dbf83193019e408fa5ab401d32d84324a98
| 104
|
py
|
Python
|
python/torch_mlir/eager_mode/__init__.py
|
burntfalafel/torch-mlir-internal
|
d3ef58450fc94e9337dc0434fa3af6dd7b54b37f
|
[
"Apache-2.0"
] | 2
|
2022-02-16T21:56:00.000Z
|
2022-02-20T17:34:47.000Z
|
python/torch_mlir/eager_mode/__init__.py
|
burntfalafel/torch-mlir-internal
|
d3ef58450fc94e9337dc0434fa3af6dd7b54b37f
|
[
"Apache-2.0"
] | null | null | null |
python/torch_mlir/eager_mode/__init__.py
|
burntfalafel/torch-mlir-internal
|
d3ef58450fc94e9337dc0434fa3af6dd7b54b37f
|
[
"Apache-2.0"
] | null | null | null |
import os
EAGER_MODE_DEBUG = os.environ.get("EAGER_MODE_DEBUG", 'False').lower() in ('true', '1', 't')
| 26
| 92
| 0.673077
| 17
| 104
| 3.882353
| 0.764706
| 0.272727
| 0.424242
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010753
| 0.105769
| 104
| 3
| 93
| 34.666667
| 0.698925
| 0
| 0
| 0
| 0
| 0
| 0.259615
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
96be495bd3261e63c1a53206e1ecae309a118594
| 387
|
py
|
Python
|
container_service_extension/pksclient/api/__init__.py
|
tschoergez/container-service-extension
|
e1fbaf7e9c242a416d3f580880c1051286847cfd
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null |
container_service_extension/pksclient/api/__init__.py
|
tschoergez/container-service-extension
|
e1fbaf7e9c242a416d3f580880c1051286847cfd
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null |
container_service_extension/pksclient/api/__init__.py
|
tschoergez/container-service-extension
|
e1fbaf7e9c242a416d3f580880c1051286847cfd
|
[
"BSD-2-Clause",
"BSD-3-Clause"
] | null | null | null |
from __future__ import absolute_import
# flake8: noqa
# import apis into api package
from container_service_extension.pksclient.api.cluster_api import ClusterApi
from container_service_extension.pksclient.api.plans_api import PlansApi
from container_service_extension.pksclient.api.profile_api import ProfileApi
from container_service_extension.pksclient.api.users_api import UsersApi
| 38.7
| 76
| 0.881137
| 52
| 387
| 6.230769
| 0.423077
| 0.160494
| 0.246914
| 0.358025
| 0.506173
| 0.506173
| 0
| 0
| 0
| 0
| 0
| 0.002809
| 0.080103
| 387
| 9
| 77
| 43
| 0.907303
| 0.105943
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
738a85e82da68aa322a25cf87d2adf64e784db74
| 2,056
|
py
|
Python
|
data/kbqa/parse_kbqa.py
|
UKPLab/TWEAC-qa-agent-selection
|
ed4f0cafa87aefd4820cca0d7f4881d2de99a9f0
|
[
"MIT"
] | 9
|
2021-04-16T12:45:45.000Z
|
2022-01-29T10:52:52.000Z
|
data/kbqa/parse_kbqa.py
|
UKPLab/TWEAC-qa-agent-selection
|
ed4f0cafa87aefd4820cca0d7f4881d2de99a9f0
|
[
"MIT"
] | 1
|
2021-11-25T04:16:25.000Z
|
2021-11-25T09:54:29.000Z
|
data/kbqa/parse_kbqa.py
|
UKPLab/TWEAC-qa-agent-selection
|
ed4f0cafa87aefd4820cca0d7f4881d2de99a9f0
|
[
"MIT"
] | 3
|
2021-04-16T12:43:41.000Z
|
2021-11-25T04:21:43.000Z
|
import json
import os
def qald(in_folder, out_folder):
train = json.load(open(os.path.join(in_folder, "qald-7-train-en-wikidata.json")))
test = json.load(open(os.path.join(in_folder, "qald-7-test-en-wikidata-withoutanswers.json")))
train_q = []
test_q = []
for qs in train["questions"]:
for q in qs["question"]:
train_q.append(q["string"])
split_idx = int(len(train_q)*0.75)
dev_q = train_q[split_idx:]
train_q = train_q[:split_idx]
for qs in test["questions"]:
for q in qs["question"]:
test_q.append(q["string"])
for qs, split in zip([train_q, dev_q, test_q], ["train", "dev", "test"]):
os.makedirs(os.path.join(out_folder, split), exist_ok=True)
with open(os.path.join(out_folder, split, "qald-7.txt"), "w", encoding="utf-8") as f:
for q in qs:
f.write(q+"\n")
def websqp(in_folder, out_folder):
train = json.load(open(os.path.join(in_folder, "WebQSP.train.json"), encoding="utf-8"))
test = json.load(open(os.path.join(in_folder, "WebQSP.test.json"), encoding="utf-8"))
train_q = []
test_q = []
for q in train["Questions"]:
train_q.append(q["RawQuestion"])
split_idx = int(len(train_q)*0.75)
dev_q = train_q[split_idx:]
train_q = train_q[:split_idx]
for q in test["Questions"]:
test_q.append(q["RawQuestion"])
for qs, split in zip([train_q, dev_q, test_q], ["train", "dev", "test"]):
os.makedirs(os.path.join(out_folder, split), exist_ok=True)
with open(os.path.join(out_folder, split, "webqsp.txt"), "w", encoding="utf-8") as f:
for q in qs:
f.write(q+"\n")
if __name__ == "__main__":
qald(r"C:\Users\Gregor\Documents\Programming\square-skill-selector\data\kbqa\qald", r"C:\Users\Gregor\Documents\Programming\square-skill-selector\data\kbqa")
websqp(r"C:\Users\Gregor\Documents\Programming\square-skill-selector\data\kbqa\WebQSP\data", r"C:\Users\Gregor\Documents\Programming\square-skill-selector\data\kbqa")
| 38.792453
| 170
| 0.634728
| 326
| 2,056
| 3.843558
| 0.196319
| 0.067039
| 0.063847
| 0.067039
| 0.762969
| 0.740623
| 0.700718
| 0.700718
| 0.700718
| 0.660814
| 0
| 0.007798
| 0.189202
| 2,056
| 53
| 170
| 38.792453
| 0.743851
| 0
| 0
| 0.487805
| 0
| 0.04878
| 0.273213
| 0.177443
| 0
| 0
| 0
| 0
| 0
| 1
| 0.04878
| false
| 0
| 0.04878
| 0
| 0.097561
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
73c590592e5f6c7d80e9e638ac61992cbf513263
| 49
|
py
|
Python
|
test/fixtures/python/analysis/main1.py
|
matsubara0507/semantic
|
67899f701abc0f1f0cb4374d8d3c249afc33a272
|
[
"MIT"
] | 8,844
|
2019-05-31T15:47:12.000Z
|
2022-03-31T18:33:51.000Z
|
test/fixtures/python/analysis/main1.py
|
matsubara0507/semantic
|
67899f701abc0f1f0cb4374d8d3c249afc33a272
|
[
"MIT"
] | 401
|
2019-05-31T18:30:26.000Z
|
2022-03-31T16:32:29.000Z
|
test/fixtures/python/analysis/main1.py
|
matsubara0507/semantic
|
67899f701abc0f1f0cb4374d8d3c249afc33a272
|
[
"MIT"
] | 504
|
2019-05-31T17:55:03.000Z
|
2022-03-30T04:15:04.000Z
|
import a as b
import b.c as e
b.foo(1)
e.baz(1)
| 8.166667
| 15
| 0.632653
| 15
| 49
| 2.066667
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.22449
| 49
| 5
| 16
| 9.8
| 0.763158
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
fb4743a6ee0568d1f98e6dec89a2138670b26a6f
| 9,921
|
py
|
Python
|
aqme/qdesc.py
|
patonlab/aqme
|
080d8e85ee905718ddf78f7fdee2ee308a293ad1
|
[
"MIT"
] | null | null | null |
aqme/qdesc.py
|
patonlab/aqme
|
080d8e85ee905718ddf78f7fdee2ee308a293ad1
|
[
"MIT"
] | null | null | null |
aqme/qdesc.py
|
patonlab/aqme
|
080d8e85ee905718ddf78f7fdee2ee308a293ad1
|
[
"MIT"
] | null | null | null |
#####################################################.
# This file stores all the functions #
# used for genrating all parameters #
#####################################################.
from rdkit.Chem import AllChem as Chem
from rdkit.Chem import rdMolTransforms
import os
import pandas as pd
from aqme.csearch import getDihedralMatches
def get_data(rdkit_mols,min_mols,dft_mols,lot,bs,name_mol,args,type_csearch,type_min,w_dir_initial):
geom_data = pd.DataFrame()
for j, mol_j in enumerate(rdkit_mols):
name = mol_j.GetProp('_Name')
name_dft= '_'.join(mol_j.GetProp('_Name').split())+'_'+type_min
geom_data.at[j,'Name'] = name
if len(args.dihedral) != 0:
for d,dh in enumerate(args.dihedral):
dihedral_rdkit = rdMolTransforms.GetDihedralDeg(mol_j.GetConformer(),dh[0],dh[1],dh[2],dh[3])
geom_data.at[j,args.geom_par_name+'-Dihedral-'+type_csearch+'-'+str(dh[0])+'-'+str(dh[1])+'-'+str(dh[2])+'-'+str(dh[3])] = dihedral_rdkit
if len(args.angle) != 0:
for a,an in enumerate(args.angle):
angle_rdkit = rdMolTransforms.GetAngleDeg(mol_j.GetConformer(),an[0],an[1],an[2])
geom_data.at[j,args.geom_par_name+'-Angle-'+type_csearch+'-'+str(an[0])+'-'+str(an[1])+'-'+str(an[2])] = angle_rdkit
if len(args.bond) != 0:
for b,bd in enumerate(args.angle):
bond_rdkit = rdMolTransforms.GetBondLength(mol_j.GetConformer(),bd[0],bd[1])
geom_data.at[j,args.geom_par_name+'-Bond-'+type_csearch+'-'+str(bd[0])+'-'+str(bd[1])] = bond_rdkit
if min_mols is not None:
if type_min =='ani' or type_min=='xtb':
for i, mol_i in enumerate(min_mols):
if mol_i.GetProp('_Name') == name+' '+type_min:
if len(args.dihedral) != 0:
for d,dh in enumerate(args.dihedral):
dihedral_min = rdMolTransforms.GetDihedralDeg(mol_i.GetConformer(),dh[0],dh[1],dh[2],dh[3])
geom_data.at[j,args.geom_par_name+'-Dihedral-'+type_min+'-'+str(dh[0])+'-'+str(dh[1])+'-'+str(dh[2])+'-'+str(dh[3])] = dihedral_min
if len(args.angle) != 0:
for a,an in enumerate(args.angle):
angle_min = rdMolTransforms.GetAngleDeg(mol_i.GetConformer(),an[0],an[1],an[2])
geom_data.at[j,args.geom_par_name+'-Angle-'+type_min+'-'+str(an[0])+'-'+str(an[1])+'-'+str(an[2])] = angle_min
if len(args.bond) != 0:
for b,bd in enumerate(args.angle):
bond_min = rdMolTransforms.GetBondLength(mol_i.GetConformer(),bd[0],bd[1])
if dft_mols is not None:
if type_min =='ani' or type_min=='xtb':
for i, mol_i in enumerate(dft_mols):
if mol_i.GetProp('_Name').split('/')[-1].split('.log')[0] == name_dft:
if len(args.dihedral) != 0:
for d,dh in enumerate(args.dihedral):
dihedral_min = rdMolTransforms.GetDihedralDeg(mol_i.GetConformer(),dh[0],dh[1],dh[2],dh[3])
geom_data.at[j,args.geom_par_name+'-Dihedral-'+lot+'-'+bs+'-'+str(dh[0])+'-'+str(dh[1])+'-'+str(dh[2])+'-'+str(dh[3])] = dihedral_min
if len(args.angle) != 0:
for a,an in enumerate(args.angle):
angle_min = rdMolTransforms.GetAngleDeg(mol_i.GetConformer(),an[0],an[1],an[2])
geom_data.at[j,args.geom_par_name+'-Angle-'+lot+'-'+bs+'-'+str(an[0])+'-'+str(an[1])+'-'+str(an[2])] = angle_min
if len(args.bond) != 0:
for b,bd in enumerate(args.angle):
bond_min = rdMolTransforms.GetBondLength(mol_i.GetConformer(),bd[0],bd[1])
geom_data.at[j,args.geom_par_name+'-Bond-'+lot+'-'+bs+'-'+str(bd[0])+'-'+str(bd[1])] = bond_min
return geom_data
def calculate_parameters(sdf_rdkit,sdf_ani,sdf_xtb,qm_files,args,log,w_dir_initial,name_mol,lot,bs):
#creating folder for all molecules to write geom parameter
folder = w_dir_initial + '/QSTAT/geom_parameters'
try:
os.makedirs(folder)
os.chdir(folder)
except OSError:
if os.path.isdir(folder):
os.chdir(folder)
else:
raise
#get mol objects
dft_mols= []
rdkit_mols = Chem.SDMolSupplier(sdf_rdkit, removeHs=False)
if args.rot_dihedral:
args.dihedral = getDihedralMatches(rdkit_mols[0], args.heavyonly,log)
if sdf_ani is not None:
ani_mols = Chem.SDMolSupplier(sdf_ani, removeHs=False)
if sdf_xtb is not None:
xtb_mols = Chem.SDMolSupplier(sdf_xtb, removeHs=False)
ob_compat = True
try:
import openbabel as ob
except (ModuleNotFoundError,AttributeError):
ob_compat = False
log.write('\nx Open Babel is not installed correctly, it is not possible to get molecular descriptors')
if ob_compat:
obConversion = ob.OBConversion()
obConversion.SetInAndOutFormats("log", "mol")
ob_mol = ob.OBMol()
for file in qm_files:
if str(bs).find('/') > -1:
obConversion.ReadFile(ob_mol, args.path + str(lot) + '-' + str(bs).split('/')[0] +'/success/output_files/'+file)
obConversion.WriteFile(ob_mol, args.path + str(lot) + '-' + str(bs).split('/')[0] +'/success/output_files/'+file.split('.')[0]+'.mol')
obConversion.CloseOutFile()
dft_mols.append(Chem.MolFromMolFile(args.path + str(lot) + '-' + str(bs).split('/')[0] +'/success/output_files/'+file.split('.')[0]+'.mol', removeHs=False))
else:
obConversion.ReadFile(ob_mol, args.path + str(lot) + '-' + str(bs) +'/success/output_files/'+file)
obConversion.WriteFile(ob_mol, args.path + str(lot) + '-' + str(bs) +'/success/output_files/'+file.split('.')[0]+'.mol')
obConversion.CloseOutFile()
dft_mols.append(Chem.MolFromMolFile(args.path + str(lot) + '-' + str(bs) +'/success/output_files/'+file.split('.')[0]+'.mol', removeHs=False))
if os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/rdkit/'+name_mol+'_rdkit.sdf'):
geom_data = get_data(rdkit_mols,xtb_mols,dft_mols,lot,bs,name_mol,args,'rdkit','xtb',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-rdkit-xtb.csv',index=False)
if os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/rdkit/'+name_mol+'_rdkit.sdf'):
geom_data = get_data(rdkit_mols,ani_mols,dft_mols,lot,bs,name_mol,args,'rdkit','ani',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-rdkit-ani.csv',index=False)
##########
if os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/summ/'+name_mol+'_summ.sdf'):
geom_data = get_data(rdkit_mols,xtb_mols,dft_mols,lot,bs,name_mol,args,'summ','xtb',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-summ-xtb.csv',index=False)
if os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/summ/'+name_mol+'_summ.sdf'):
geom_data = get_data(rdkit_mols,ani_mols,dft_mols,lot,bs,name_mol,args,'summ','ani',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-summ-ani.csv',index=False)
#############
if os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/fullmonte/'+name_mol+'_fullmonte.sdf'):
geom_data = get_data(rdkit_mols,xtb_mols,dft_mols,lot,bs,name_mol,args,'fullmonte','xtb',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-fullmonte-xtb.csv',index=False)
if os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf') and os.path.exists(w_dir_initial+'/CSEARCH/fullmonte/'+name_mol+'_fullmonte.sdf'):
geom_data = get_data(rdkit_mols,ani_mols,dft_mols,lot,bs,name_mol,args,'fullmonte','ani',w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-fullmonte-ani.csv',index=False)
############
if os.path.exists(w_dir_initial+'/CSEARCH/summ/'+name_mol+'_summ.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf'):
geom_data = get_data(rdkit_mols,None,dft_mols,lot,bs,name_mol,args,'summ',None,w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-summ.csv',index=False)
if os.path.exists(w_dir_initial+'/CSEARCH/rdkit/'+name_mol+'_rdkit.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf') :
geom_data = get_data(rdkit_mols,None,dft_mols,lot,bs,name_mol,args,'rdkit',None,w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-rdkit.csv',index=False)
if os.path.exists(w_dir_initial+'/CSEARCH/fullmonte/'+name_mol+'_fullmonte.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/xtb/'+name_mol+'_xtb.sdf') and not os.path.exists(w_dir_initial+'/CSEARCH/ani/'+name_mol+'_ani.sdf') :
geom_data = get_data(rdkit_mols,None,dft_mols,lot,bs,name_mol,args,'rdkit',None,w_dir_initial)
geom_data.to_csv(name_mol+'-all-geom-data-with-fullmonte.csv',index=False)
| 65.269737
| 238
| 0.603467
| 1,424
| 9,921
| 3.985253
| 0.095506
| 0.051806
| 0.063965
| 0.048106
| 0.755771
| 0.752423
| 0.745022
| 0.739383
| 0.733921
| 0.723877
| 0
| 0.00928
| 0.217922
| 9,921
| 151
| 239
| 65.701987
| 0.722129
| 0.01774
| 0
| 0.297521
| 0
| 0
| 0.132632
| 0.046676
| 0
| 0
| 0
| 0
| 0
| 1
| 0.016529
| false
| 0
| 0.049587
| 0
| 0.07438
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
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| null | 0
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| 0
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| 0
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| 0
| 0
| 0
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| 0
| 0
|
0
| 5
|
fb5ffc354d2d854524531b1d4f70227336db8f87
| 238
|
py
|
Python
|
src/ikazuchi/errors.py
|
t2y/ikazuchi
|
7023111e92fa47360c50cfefd1398c554475f2c6
|
[
"Apache-2.0"
] | null | null | null |
src/ikazuchi/errors.py
|
t2y/ikazuchi
|
7023111e92fa47360c50cfefd1398c554475f2c6
|
[
"Apache-2.0"
] | null | null | null |
src/ikazuchi/errors.py
|
t2y/ikazuchi
|
7023111e92fa47360c50cfefd1398c554475f2c6
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
class IkazuchiError(Exception):
""" ikazuchi root exception """
pass
class TranslatorError(IkazuchiError):
""" ikazuchi translator exception """
pass
class NeedApiKeyError(TranslatorError): pass
| 19.833333
| 44
| 0.693277
| 21
| 238
| 7.857143
| 0.571429
| 0.157576
| 0.218182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005128
| 0.180672
| 238
| 11
| 45
| 21.636364
| 0.841026
| 0.327731
| 0
| 0.4
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| true
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| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
fb7be7756110402e4a2ea628f2c6bc51fd0dd0f4
| 139
|
py
|
Python
|
manager.py
|
thangbk2209/pretraining_auto_scaling_ng
|
0b98b311c75ec4b87b3e8168f93eeb53ed0d16f5
|
[
"MIT"
] | null | null | null |
manager.py
|
thangbk2209/pretraining_auto_scaling_ng
|
0b98b311c75ec4b87b3e8168f93eeb53ed0d16f5
|
[
"MIT"
] | null | null | null |
manager.py
|
thangbk2209/pretraining_auto_scaling_ng
|
0b98b311c75ec4b87b3e8168f93eeb53ed0d16f5
|
[
"MIT"
] | null | null | null |
"""
Author: bkc@data_analysis
Project: autoencoder_ng
Created: 7/29/20 10:51
Purpose: START SCRIPT FOR AUTOENCODER_NG PROJECT
"""
| 19.857143
| 50
| 0.726619
| 20
| 139
| 4.9
| 0.85
| 0.265306
| 0
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| 0
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| 0
| 0.078261
| 0.172662
| 139
| 6
| 51
| 23.166667
| 0.773913
| 0.877698
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
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| null | true
| 0
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| null | null | null | 1
| 0
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| 0
| 0
| 0
|
0
| 5
|
fb89161fb05f2325ee9a0854f9561e3db343bc07
| 89
|
py
|
Python
|
cwl_airflow_parser/operators/__init__.py
|
lrodri29/cwl-airflow-parser
|
3854022fc7a5c62cfd92e93fdb7a97d528918239
|
[
"Apache-2.0"
] | 14
|
2018-05-01T01:31:07.000Z
|
2019-09-02T15:41:06.000Z
|
cwl_airflow_parser/operators/__init__.py
|
lrodri29/cwl-airflow-parser
|
3854022fc7a5c62cfd92e93fdb7a97d528918239
|
[
"Apache-2.0"
] | 1
|
2018-08-06T17:28:51.000Z
|
2018-08-27T16:05:10.000Z
|
cwl_airflow_parser/operators/__init__.py
|
lrodri29/cwl-airflow-parser
|
3854022fc7a5c62cfd92e93fdb7a97d528918239
|
[
"Apache-2.0"
] | 8
|
2018-08-06T16:47:31.000Z
|
2020-05-12T20:21:01.000Z
|
from .cwljobdispatcher import CWLJobDispatcher
from .cwljobgatherer import CWLJobGatherer
| 44.5
| 46
| 0.898876
| 8
| 89
| 10
| 0.5
| 0
| 0
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| 0
| 0.078652
| 89
| 2
| 47
| 44.5
| 0.97561
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
fb9503385f519e775914f1b2f2d3dd6a4f2477ad
| 15,037
|
py
|
Python
|
Machine Learning Summer School 2019 (London, UK)/tutorials/mcmc/2 - markov_chain_monte_carlo.py
|
xuedong/rlss2019
|
d7468c2fcf269d8afd6fb0f44993aa9797867944
|
[
"MIT"
] | null | null | null |
Machine Learning Summer School 2019 (London, UK)/tutorials/mcmc/2 - markov_chain_monte_carlo.py
|
xuedong/rlss2019
|
d7468c2fcf269d8afd6fb0f44993aa9797867944
|
[
"MIT"
] | null | null | null |
Machine Learning Summer School 2019 (London, UK)/tutorials/mcmc/2 - markov_chain_monte_carlo.py
|
xuedong/rlss2019
|
d7468c2fcf269d8afd6fb0f44993aa9797867944
|
[
"MIT"
] | null | null | null |
############################################################
# Copyright 2019 Michael Betancourt
# Licensed under the new BSD (3-clause) license:
#
# https://opensource.org/licenses/BSD-3-Clause
############################################################
############################################################
#
# Initial setup
#
############################################################
import matplotlib.pyplot as plot
import scipy.stats as stats
import numpy
import math
light = "#DCBCBC"
light_highlight = "#C79999"
mid = "#B97C7C"
mid_highlight = "#A25050"
dark = "#8F2727"
dark_highlight = "#7C0000"
green = "#00FF00"
# To facilitate the computation of Markov chain Monte Carlo estimators
# let's define a _Welford accumulator_ that computes empirical summaries
# of a sample in a single pass
def welford_summary(x, L = 100):
summary = [0] * (L + 1)
for n in range(len(x)):
delta = x[n] - summary[0]
summary[0] += delta / (n + 1)
for l in range(L):
if n > l:
summary[l + 1] += delta * (x[n - l] - summary[0])
norm = 1.0 / (len(x) - 1)
for l in range(L): summary[l + 1] *= norm
return summary
# We can then use the Welford accumulator output to compute the
# Markov chain Monte Carlo estimators and their properties
def compute_mcmc_stats(x, L = 20):
summary = welford_summary(x, L)
mean = summary[0]
var = summary[1]
acov = summary[1:(L + 1)]
# Compute the effective sample size
rho_hat_s = [0] * L
rho_hat_s[1] = acov[1] / var
# First we transform our autocovariances into Geyer's initial positive sequence
max_s = 1
for s in [ 2 * i + 1 for i in range((L - 1) / 2) ]:
rho_hat_even = acov[s + 1] / var
rho_hat_odd = acov[s + 2] / var;
max_s = s + 2
if rho_hat_even + rho_hat_odd > 0:
rho_hat_s[s + 1] = rho_hat_even
rho_hat_s[s + 2] = rho_hat_odd
else:
break
# Then we transform this output into Geyer's initial monotone sequence
for s in [ 2 * i + 3 for i in range((max_s - 2)/ 2) ]:
if rho_hat_s[s + 1] + rho_hat_s[s + 2] > rho_hat_s[s - 1] + rho_hat_s[s]:
rho_hat_s[s + 1] = 0.5 * (rho_hat_s[s - 1] + rho_hat_s[s])
rho_hat_s[s + 2] = rho_hat_s[s + 1]
ess = len(x) / (1.0 + 2 * sum(rho_hat_s))
return [mean, math.sqrt(var / ess), math.sqrt(var), ess]
# To generate our samples we'll use numpy's pseudo random number
# generator which needs to be seeded to achieve reproducible
# results
numpy.random.seed(seed=8675309)
# To ensure accurate results let's generate pretty large samples
N = 10000
# To see how results scale with dimension we'll consider
# behavior one thorugh ten dimensions
Ds = [ n + 1 for n in range(10) ]
idxs = [ idx for idx in range(Ds[-1]) for r in range(2) ]
plot_Ds = [ D + delta for D in Ds for delta in [-0.5, 0.5]]
############################################################
#
# How does the Random Walk Metropolis algorithm perform
# on a target distribution with a two-dimensional Gaussian
# density function?
#
############################################################
# Target density
def target_lpdf(x):
return - 0.5 * ( (x[0] - 1)**2 + (x[1] + 1)**2 ) \
- 0.5 * 2 * math.log(6.283185307179586)
# Tune proposal density
sigma = 1.4
# A place to store our Markov chain
# D columns for the parameters and one extra column
# for the Metropolis acceptance probability
D = 2
mcmc_samples = [[0] * (D + 1) for _ in range(N)]
# Randomly seed the initial state
mcmc_samples[0][0] = stats.norm.rvs(0, 3)
mcmc_samples[0][1] = stats.norm.rvs(0, 3)
mcmc_samples[0][2] = 1
for n in range(1, N):
x0 = [ mcmc_samples[n - 1][0], mcmc_samples[n - 1][1]]
xp = [ stats.norm.rvs(x0[0], sigma), stats.norm.rvs(x0[1], sigma) ]
# Compute acceptance probability
accept_prob = 1
if target_lpdf(xp) < target_lpdf(x0):
accept_prob = math.exp(target_lpdf(xp) - target_lpdf(x0))
mcmc_samples[n][D] = accept_prob
# Apply Metropolis correction
u = stats.uniform.rvs(0, 1)
if accept_prob > u:
mcmc_samples[n][0] = xp[0]
mcmc_samples[n][1] = xp[1]
else:
mcmc_samples[n][0] = x0[0]
mcmc_samples[n][1] = x0[1]
# Compute MCMC estimator statistics, leaving
# out the first 100 samples as warmup
compute_mcmc_stats([ s[0] for s in mcmc_samples[100:] ])
compute_mcmc_stats([ s[1] for s in mcmc_samples[100:] ])
# Plot convergence of MCMC estimators for each parameter
stride = 250
M = N / stride
iters = [ stride * (i + 1) for i in range(N / stride) ]
x1_mean = [0] * M
x1_se = [0] * M
x2_mean = [0] * M
x2_se = [0] * M
for m in range(M):
running_samples = [ s[0] for s in mcmc_samples[100:iters[m]] ]
mcmc_stats = compute_mcmc_stats(running_samples)
x1_mean[m] = mcmc_stats[0]
x1_se[m] = mcmc_stats[1]
running_samples = [ s[1] for s in mcmc_samples[100:iters[m]] ]
mcmc_stats = compute_mcmc_stats(running_samples)
x2_mean[m] = mcmc_stats[0]
x2_se[m] = mcmc_stats[1]
plot.fill_between(iters,
[ x1_mean[m] - 2 * x1_se[m] for m in range(M) ],
[ x1_mean[m] + 2 * x1_se[m] for m in range(M) ],
facecolor=light, color=light)
plot.plot(iters, x1_mean, color=dark)
plot.plot([iters[0], iters[-1]], [1, 1], color='grey', linestyle='--')
plot.gca().set_xlim([0, N])
plot.gca().set_xlabel("Iteration")
plot.gca().set_ylim([-2, 2])
plot.gca().set_ylabel("Monte Carlo Estimator")
plot.show()
plot.fill_between(iters,
[ x2_mean[m] - 2 * x2_se[m] for m in range(M) ],
[ x2_mean[m] + 2 * x2_se[m] for m in range(M) ],
facecolor=light, color=light)
plot.plot(iters, x2_mean, color=dark)
plot.plot([iters[0], iters[-1]], [-1, -1], color='grey', linestyle='--')
plot.gca().set_xlim([0, N])
plot.gca().set_xlabel("Iteration")
plot.gca().set_ylim([-2, 2])
plot.gca().set_ylabel("Monte Carlo Estimator")
plot.show()
############################################################
#
# How does the Random Walk Metropolis algorithm perform
# on a target distribution with a funnel density function?
#
############################################################
# Target density
def target_lpdf(x):
return - 0.5 * ( x[0]**2 + x[1]**2 + ( (x[2] - x[0]) / math.exp(x[1]) )**2 ) \
- 0.5 * 3 * math.log(6.283185307179586) - 0.5 * x[2]
# Tune proposal density
sigma = 1.4
# A place to store our Markov chain
# D columns for the parameters and one extra column
# for the Metropolis acceptance probability
D = 3
mcmc_samples = [[0] * (D + 1) for _ in range(N)]
# Randomly seed the initial state
mcmc_samples[0][0] = stats.norm.rvs(0, 3)
mcmc_samples[0][1] = stats.norm.rvs(0, 3)
mcmc_samples[0][2] = stats.norm.rvs(0, 3)
mcmc_samples[0][3] = 1
for n in range(1, N):
x0 = [ mcmc_samples[n - 1][0],
mcmc_samples[n - 1][1],
mcmc_samples[n - 1][2]]
xp = [ stats.norm.rvs(x0[0], sigma),
stats.norm.rvs(x0[1], sigma),
stats.norm.rvs(x0[2], sigma) ]
# Compute acceptance probability
accept_prob = 1
if target_lpdf(xp) < target_lpdf(x0):
accept_prob = math.exp(target_lpdf(xp) - target_lpdf(x0))
mcmc_samples[n][D] = accept_prob
# Apply Metropolis correction
u = stats.uniform.rvs(0, 1)
if accept_prob > u:
mcmc_samples[n][0] = xp[0]
mcmc_samples[n][1] = xp[1]
mcmc_samples[n][2] = xp[2]
else:
mcmc_samples[n][0] = x0[0]
mcmc_samples[n][1] = x0[1]
mcmc_samples[n][2] = x0[2]
# Compute MCMC estimator statistics, leaving
# out the first 100 samples as warmup
compute_mcmc_stats([ s[0] for s in mcmc_samples[100:] ])
compute_mcmc_stats([ s[1] for s in mcmc_samples[100:] ])
compute_mcmc_stats([ s[2] for s in mcmc_samples[100:] ])
# Plot convergence of MCMC estimators for each parameter
stride = 250
M = N / stride
iters = [ stride * (i + 1) for i in range(N / stride) ]
mu_mean = [0] * M
mu_se = [0] * M
log_tau_mean = [0] * M
log_tau_se = [0] * M
for m in range(M):
running_samples = [ s[0] for s in mcmc_samples[100:iters[m]] ]
mcmc_stats = compute_mcmc_stats(running_samples)
mu_mean[m] = mcmc_stats[0]
mu_se[m] = mcmc_stats[1]
running_samples = [ s[1] for s in mcmc_samples[100:iters[m]] ]
mcmc_stats = compute_mcmc_stats(running_samples)
log_tau_mean[m] = mcmc_stats[0]
log_tau_se[m] = mcmc_stats[1]
plot.fill_between(iters,
[ mu_mean[m] - 2 * mu_se[m] for m in range(M) ],
[ mu_mean[m] + 2 * mu_se[m] for m in range(M) ],
facecolor=light, color=light)
plot.plot(iters, mu_mean, color=dark)
plot.plot([iters[0], iters[-1]], [0, 0], color='grey', linestyle='--')
plot.gca().set_xlim([0, N])
plot.gca().set_xlabel("Iteration")
plot.gca().set_ylim([-1, 1])
plot.gca().set_ylabel("Monte Carlo Estimator")
plot.show()
plot.fill_between(iters,
[ log_tau_mean[m] - 2 * log_tau_se[m] for m in range(M) ],
[ log_tau_mean[m] + 2 * log_tau_se[m] for m in range(M) ],
facecolor=light, color=light)
plot.plot(iters, log_tau_mean, color=dark)
plot.plot([iters[0], iters[-1]], [0, 0], color='grey', linestyle='--')
plot.gca().set_xlim([0, N])
plot.gca().set_xlabel("Iteration")
plot.gca().set_ylim([-1, 8])
plot.gca().set_ylabel("Monte Carlo Estimator")
plot.show()
############################################################
#
# How does the effective sample size of a Random Walk
# Metropolis Markov chain vary with the dimension of
# the target distribution?
#
############################################################
def target_lpdf(x):
return - 0.5 * sum([ x_n**2 for x_n in x ]) \
- 0.5 * len(x) * math.log(6.283185307179586)
############################################################
# First let's use a constant Markov transition
############################################################
accept_prob_means = [0] * len(Ds)
accept_prob_ses = [0] * len(Ds)
ave_eff_sample_sizes = [0] * len(Ds)
# Tune proposal density
sigma = 1.4
for D in Ds:
# A place to store our Markov chain
# D columns for the parameters and one extra column
# for the Metropolis acceptance probability
mcmc_samples = [[0] * (D + 1) for _ in range(N)]
# Seeding the initial state with an exact sample
# from the target distribution ensures that we
# start in the typical set and avoid having to
# worry about warmup.
for d in range(D):
mcmc_samples[0][d] = stats.norm.rvs(0, 3)
mcmc_samples[0][D] = 1
for n in range(1, N):
x0 = [ mcmc_samples[n - 1][d] for d in range(D) ]
xp = [ stats.norm.rvs(x0[d], sigma) for d in range(D) ]
# Compute acceptance probability
accept_prob = 1
if target_lpdf(xp) < target_lpdf(x0):
accept_prob = math.exp(target_lpdf(xp) - target_lpdf(x0))
mcmc_samples[n][D] = accept_prob
# Apply Metropolis correction
u = stats.uniform.rvs(0, 1)
if accept_prob > u:
mcmc_samples[n][0:D] = xp
else:
mcmc_samples[n][0:D] = x0
# Estimate average acceptance probability
# Compute MCMC estimator statistics
mcmc_stats = compute_mcmc_stats([ s[D] for s in mcmc_samples])
accept_prob_means[D - 1] = mcmc_stats[0]
accept_prob_ses[D - 1] = mcmc_stats[1]
# Estimate effective sample size
eff_sample_sizes = [ compute_mcmc_stats([ s[d] for s in mcmc_samples])[3] \
for d in range(D) ]
ave_eff_sample_sizes[D - 1] = sum(eff_sample_sizes) / D
f, axarr = plot.subplots(1, 2)
axarr[0].set_title("")
axarr[0].fill_between(plot_Ds,
[ accept_prob_means[idx] - 2 * accept_prob_ses[idx] for idx in idxs ],
[ accept_prob_means[idx] + 2 * accept_prob_ses[idx] for idx in idxs ],
facecolor=dark, color=dark)
axarr[0].plot(plot_Ds, [ accept_prob_means[idx] for idx in idxs], color=dark_highlight)
axarr[0].set_xlim([Ds[0], Ds[-1]])
axarr[0].set_xlabel("Dimension")
axarr[0].set_ylim([0, 1])
axarr[0].set_ylabel("Average Acceptance Probability")
axarr[1].set_title("")
axarr[1].plot(plot_Ds, [ ave_eff_sample_sizes[idx] / N for idx in idxs],
color=dark_highlight)
axarr[1].set_xlim([Ds[0], Ds[-1]])
axarr[1].set_xlabel("Dimension")
axarr[1].set_ylim([0, 0.3])
axarr[1].set_ylabel("Average Effective Sample Size Per Iteration")
plot.show()
############################################################
# Now let's use an (approximately) optimally tuned Markov
# transition for each dimension
############################################################
accept_prob_means = [0] * len(Ds)
accept_prob_ses = [0] * len(Ds)
ave_eff_sample_sizes = [0] * len(Ds)
# Approximately optimal proposal tuning
opt_sigmas = [2.5, 1.75, 1.5, 1.2, 1.15, 1.0, 0.95, 0.85, 0.8, 0.75]
# Tune proposal density
sigma = 1.4
for D in Ds:
# A place to store our Markov chain
# D columns for the parameters and one extra column
# for the Metropolis acceptance probability
mcmc_samples = [[0] * (D + 1) for _ in range(N)]
# Seeding the initial state with an exact sample
# from the target distribution ensures that we
# start in the typical set and avoid having to
# worry about warmup.
for d in range(D):
mcmc_samples[0][d] = stats.norm.rvs(0, 3)
mcmc_samples[0][D] = 1
for n in range(1, N):
x0 = [ mcmc_samples[n - 1][d] for d in range(D) ]
xp = [ stats.norm.rvs(x0[d], opt_sigmas[D - 1]) for d in range(D) ]
# Compute acceptance probability
accept_prob = 1
if target_lpdf(xp) < target_lpdf(x0):
accept_prob = math.exp(target_lpdf(xp) - target_lpdf(x0))
mcmc_samples[n][D] = accept_prob
# Apply Metropolis correction
u = stats.uniform.rvs(0, 1)
if accept_prob > u:
mcmc_samples[n][0:D] = xp
else:
mcmc_samples[n][0:D] = x0
# Estimate average acceptance probability
# Compute MCMC estimator statistics
mcmc_stats = compute_mcmc_stats([ s[D] for s in mcmc_samples])
accept_prob_means[D - 1] = mcmc_stats[0]
accept_prob_ses[D - 1] = mcmc_stats[1]
# Estimate effective sample size
eff_sample_sizes = [ compute_mcmc_stats([ s[d] for s in mcmc_samples])[3] \
for d in range(D) ]
ave_eff_sample_sizes[D - 1] = sum(eff_sample_sizes) / D
f, axarr = plot.subplots(1, 2)
axarr[0].set_title("")
axarr[0].fill_between(plot_Ds,
[ accept_prob_means[idx] - 2 * accept_prob_ses[idx] for idx in idxs ],
[ accept_prob_means[idx] + 2 * accept_prob_ses[idx] for idx in idxs ],
facecolor=dark, color=dark)
axarr[0].plot(plot_Ds, [ accept_prob_means[idx] for idx in idxs], color=dark_highlight)
axarr[0].set_xlim([Ds[0], Ds[-1]])
axarr[0].set_xlabel("Dimension")
axarr[0].set_ylim([0, 1])
axarr[0].set_ylabel("Average Acceptance Probability")
axarr[1].set_title("")
axarr[1].plot(plot_Ds, [ ave_eff_sample_sizes[idx] / N for idx in idxs],
color=dark_highlight)
axarr[1].set_xlim([Ds[0], Ds[-1]])
axarr[1].set_xlabel("Dimension")
axarr[1].set_ylim([0, 0.3])
axarr[1].set_ylabel("Average Effective Sample Size Per Iteration")
plot.show()
| 31.524109
| 92
| 0.608499
| 2,404
| 15,037
| 3.656406
| 0.111065
| 0.066325
| 0.03413
| 0.01479
| 0.783845
| 0.758362
| 0.753925
| 0.747895
| 0.744937
| 0.736405
| 0
| 0.044709
| 0.201237
| 15,037
| 476
| 93
| 31.590336
| 0.68712
| 0.209084
| 0
| 0.621429
| 0
| 0
| 0.0342
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.017857
| false
| 0
| 0.014286
| 0.010714
| 0.05
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
fb99379467ad51c39cd5405a13aedf9d925212e0
| 40
|
py
|
Python
|
test.py
|
probot1511/test_repo
|
9dee2d2eb1c44c09d04d91861b3f9bd2b63c4e0f
|
[
"MIT"
] | null | null | null |
test.py
|
probot1511/test_repo
|
9dee2d2eb1c44c09d04d91861b3f9bd2b63c4e0f
|
[
"MIT"
] | null | null | null |
test.py
|
probot1511/test_repo
|
9dee2d2eb1c44c09d04d91861b3f9bd2b63c4e0f
|
[
"MIT"
] | 1
|
2022-01-31T19:24:49.000Z
|
2022-01-31T19:24:49.000Z
|
print("RUnning!!!")
print("Updated!!!")
| 13.333333
| 19
| 0.6
| 4
| 40
| 6
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05
| 40
| 2
| 20
| 20
| 0.631579
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
83b0ae650bd55397213c23d819dd2927624d8665
| 121
|
py
|
Python
|
common/utils/__init__.py
|
jl1990/alpha-zero-general
|
6a1549f9cd1b2ebdffee30f8de1be9cbefecd5f4
|
[
"MIT"
] | null | null | null |
common/utils/__init__.py
|
jl1990/alpha-zero-general
|
6a1549f9cd1b2ebdffee30f8de1be9cbefecd5f4
|
[
"MIT"
] | null | null | null |
common/utils/__init__.py
|
jl1990/alpha-zero-general
|
6a1549f9cd1b2ebdffee30f8de1be9cbefecd5f4
|
[
"MIT"
] | null | null | null |
"""Useful utils
"""
from .eval import *
from .misc import *
# progress bar
from .progress.progress.bar import Bar as Bar
| 17.285714
| 45
| 0.719008
| 18
| 121
| 4.833333
| 0.5
| 0.252874
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.165289
| 121
| 6
| 46
| 20.166667
| 0.861386
| 0.214876
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
860369b74b7a50328a72400a0fc52d3fc97e9d16
| 80
|
py
|
Python
|
route/link.py
|
moluwole/Bast_skeleton
|
9e58c1c0da3085b377896aab1e3007689c328c1c
|
[
"MIT"
] | 3
|
2018-08-04T21:11:35.000Z
|
2018-08-24T04:47:16.000Z
|
route/link.py
|
moluwole/Bast_skeleton
|
9e58c1c0da3085b377896aab1e3007689c328c1c
|
[
"MIT"
] | 1
|
2018-08-24T20:57:36.000Z
|
2018-08-24T20:57:36.000Z
|
route/link.py
|
moluwole/Bast_skeleton
|
9e58c1c0da3085b377896aab1e3007689c328c1c
|
[
"MIT"
] | 2
|
2018-08-05T19:14:16.000Z
|
2018-08-15T08:13:50.000Z
|
from bast import Route
route = Route()
route.get('/', 'HelloController.index')
| 16
| 39
| 0.7125
| 10
| 80
| 5.7
| 0.7
| 0.526316
| 0.526316
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 80
| 4
| 40
| 20
| 0.814286
| 0
| 0
| 0
| 0
| 0
| 0.275
| 0.2625
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f7af8bb0d4f3220811a9ca15ffd7c866a271a05f
| 24
|
py
|
Python
|
opensecrets/__init__.py
|
ndanielsen/py-opensecrets
|
b362d993fdcff6fc6a0d33ec2db75fb1da418a84
|
[
"MIT"
] | 1
|
2018-02-15T03:59:13.000Z
|
2018-02-15T03:59:13.000Z
|
opensecrets/__init__.py
|
ndanielsen/py-opensecrets
|
b362d993fdcff6fc6a0d33ec2db75fb1da418a84
|
[
"MIT"
] | 11
|
2018-02-14T16:23:17.000Z
|
2018-04-05T16:14:49.000Z
|
opensecrets/__init__.py
|
ndanielsen/py-opensecrets
|
b362d993fdcff6fc6a0d33ec2db75fb1da418a84
|
[
"MIT"
] | null | null | null |
from .crpapi import CRP
| 12
| 23
| 0.791667
| 4
| 24
| 4.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 24
| 1
| 24
| 24
| 0.95
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f7b55905ea97e096b70cfda1b4ce991e067b06eb
| 151
|
py
|
Python
|
data/windows/dr16/mask.py
|
dnidever/apogee
|
83ad7496a0b4193df9e2c01b06dc36cb879ea6c1
|
[
"BSD-3-Clause"
] | 5
|
2019-04-11T13:35:24.000Z
|
2019-11-14T06:12:51.000Z
|
data/windows/dr16/mask.py
|
dnidever/apogee
|
83ad7496a0b4193df9e2c01b06dc36cb879ea6c1
|
[
"BSD-3-Clause"
] | null | null | null |
data/windows/dr16/mask.py
|
dnidever/apogee
|
83ad7496a0b4193df9e2c01b06dc36cb879ea6c1
|
[
"BSD-3-Clause"
] | 5
|
2018-09-20T22:07:43.000Z
|
2021-01-15T07:13:38.000Z
|
from apogee.aspcap import aspcap
from apogee.aspcap import mask
els=aspcap.elems()
for el in els[0]: mask.mkmask(el,globalmask='mask_v02_aspcap.txt')
| 25.166667
| 66
| 0.788079
| 26
| 151
| 4.5
| 0.576923
| 0.17094
| 0.273504
| 0.376068
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022059
| 0.099338
| 151
| 5
| 67
| 30.2
| 0.838235
| 0
| 0
| 0
| 0
| 0
| 0.125828
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f7bde64d861ea84f6a0483cdddf17127e95c800d
| 67
|
py
|
Python
|
keras_retinanet/backend/__init__.py
|
mj-haghighi/keras-retinanet
|
644c2f8da799889a2a3f6cc833478256cbe32c23
|
[
"Apache-2.0"
] | null | null | null |
keras_retinanet/backend/__init__.py
|
mj-haghighi/keras-retinanet
|
644c2f8da799889a2a3f6cc833478256cbe32c23
|
[
"Apache-2.0"
] | null | null | null |
keras_retinanet/backend/__init__.py
|
mj-haghighi/keras-retinanet
|
644c2f8da799889a2a3f6cc833478256cbe32c23
|
[
"Apache-2.0"
] | null | null | null |
# from .backend import * # noqa: F401,F403
from .sbackend import *
| 33.5
| 43
| 0.701493
| 9
| 67
| 5.222222
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109091
| 0.179104
| 67
| 2
| 44
| 33.5
| 0.745455
| 0.597015
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
f7c31602d3ba09f1a3970f8ce071305eb086135d
| 74
|
py
|
Python
|
Crypto-hardRSA/flag.py
|
JSW2020/hsctf-2019-freshmen
|
5282d6d51153aadd62f42673aa3d487f8d7ef45b
|
[
"MIT"
] | 16
|
2019-12-09T15:53:08.000Z
|
2021-12-07T00:34:30.000Z
|
Crypto-hardRSA/flag.py
|
JSW2020/hsctf-2019-freshmen
|
5282d6d51153aadd62f42673aa3d487f8d7ef45b
|
[
"MIT"
] | null | null | null |
Crypto-hardRSA/flag.py
|
JSW2020/hsctf-2019-freshmen
|
5282d6d51153aadd62f42673aa3d487f8d7ef45b
|
[
"MIT"
] | 7
|
2019-12-09T11:53:52.000Z
|
2021-11-14T04:09:04.000Z
|
flag = "flag{b3453333-9da9-49ae-b4ed-0017c392d58e}"
e1 = 65537
e2 = 368273
| 24.666667
| 51
| 0.743243
| 11
| 74
| 5
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.515152
| 0.108108
| 74
| 3
| 52
| 24.666667
| 0.318182
| 0
| 0
| 0
| 0
| 0
| 0.56
| 0.56
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f7dd193790b7ae7797daf8c7c2f3ca9a0623ed89
| 405
|
py
|
Python
|
tests/test_plugins/pytester_example_dir/test_file_1.py
|
MORSECorp/snappiershot
|
acb6a8d01d4496abe0f2fe83c7e7af9cf77aac8e
|
[
"Apache-2.0"
] | 27
|
2020-10-15T18:36:25.000Z
|
2022-03-02T19:11:44.000Z
|
tests/test_plugins/pytester_example_dir/test_file_1.py
|
MORSECorp/snappiershot
|
acb6a8d01d4496abe0f2fe83c7e7af9cf77aac8e
|
[
"Apache-2.0"
] | 33
|
2020-10-15T15:03:37.000Z
|
2022-03-24T21:00:34.000Z
|
tests/test_plugins/pytester_example_dir/test_file_1.py
|
MORSECorp/snappiershot
|
acb6a8d01d4496abe0f2fe83c7e7af9cf77aac8e
|
[
"Apache-2.0"
] | 5
|
2020-10-15T16:30:00.000Z
|
2022-03-30T15:07:28.000Z
|
""" This is a test file used for testing the pytest plugin. """
def test_function_passed(snapshot):
""" The snapshot for this function is expected to exist. """
snapshot.assert_match(3 + 4j)
def test_function_new(snapshot):
""" The snapshot for this function is expected to exist, but only one assertion is expected. """
snapshot.assert_match(3 + 4j)
snapshot.assert_match(3 + 4j)
| 31.153846
| 100
| 0.708642
| 60
| 405
| 4.666667
| 0.45
| 0.107143
| 0.203571
| 0.214286
| 0.6
| 0.364286
| 0.364286
| 0.364286
| 0.364286
| 0.364286
| 0
| 0.018349
| 0.192593
| 405
| 12
| 101
| 33.75
| 0.83792
| 0.491358
| 0
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.6
| 1
| 0.4
| false
| 0.2
| 0
| 0
| 0.4
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
7912e94c22f794944d84a76c7ea337e0f1d42d27
| 83
|
py
|
Python
|
maths2.py
|
tavleensasan/Tav
|
7d9d041cf0ed13c2fe581dc8e40c93721ae4de73
|
[
"MIT"
] | null | null | null |
maths2.py
|
tavleensasan/Tav
|
7d9d041cf0ed13c2fe581dc8e40c93721ae4de73
|
[
"MIT"
] | null | null | null |
maths2.py
|
tavleensasan/Tav
|
7d9d041cf0ed13c2fe581dc8e40c93721ae4de73
|
[
"MIT"
] | null | null | null |
def multiple(first,second):
return first * second
def add(x,y):
return x+y
| 16.6
| 27
| 0.662651
| 14
| 83
| 3.928571
| 0.571429
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.216867
| 83
| 4
| 28
| 20.75
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
791a74027f2dc3fbe44b27f9c9f0523352b4d029
| 149
|
py
|
Python
|
datahub/activity_feed/apps.py
|
Staberinde/data-hub-api
|
3d0467dbceaf62a47158eea412a3dba827073300
|
[
"MIT"
] | 6
|
2019-12-02T16:11:24.000Z
|
2022-03-18T10:02:02.000Z
|
datahub/activity_feed/apps.py
|
Staberinde/data-hub-api
|
3d0467dbceaf62a47158eea412a3dba827073300
|
[
"MIT"
] | 1,696
|
2019-10-31T14:08:37.000Z
|
2022-03-29T12:35:57.000Z
|
datahub/activity_feed/apps.py
|
Staberinde/data-hub-api
|
3d0467dbceaf62a47158eea412a3dba827073300
|
[
"MIT"
] | 9
|
2019-11-22T12:42:03.000Z
|
2021-09-03T14:25:05.000Z
|
from django.apps import AppConfig
class ActivityFeedConfig(AppConfig):
"""App config for activity_feed."""
name = 'datahub.activity_feed'
| 18.625
| 39
| 0.738255
| 17
| 149
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| 0.823529
| 0.222222
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| 0
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| 0
| 0
| 0
| 0.161074
| 149
| 7
| 40
| 21.285714
| 0.864
| 0.194631
| 0
| 0
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| 0
| 0.184211
| 0.184211
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
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| 0
| null | 1
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| 0
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| 1
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
f719f32c0de53ae35c0223c63678dbad415c2f11
| 22
|
py
|
Python
|
__init__.py
|
andy-96/GFPGAN
|
0ed1214760170cc27fdfd60da1f64a0699a28cf4
|
[
"BSD-3-Clause"
] | null | null | null |
__init__.py
|
andy-96/GFPGAN
|
0ed1214760170cc27fdfd60da1f64a0699a28cf4
|
[
"BSD-3-Clause"
] | null | null | null |
__init__.py
|
andy-96/GFPGAN
|
0ed1214760170cc27fdfd60da1f64a0699a28cf4
|
[
"BSD-3-Clause"
] | null | null | null |
from .gfpgan import *
| 11
| 21
| 0.727273
| 3
| 22
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.181818
| 22
| 1
| 22
| 22
| 0.888889
| 0
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| 0
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| 0
| 0
| 0
| 1
| 0
| true
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| 0
| null | 0
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| 0
| 0
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| 0
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| 1
| 0
| 0
| 0
|
0
| 5
|
f72f3f991d29cfcde8c404665347a2b2067bd01a
| 3,145
|
py
|
Python
|
tests/test_game_map.py
|
brittleshinpass/mossbread
|
6a225e5d11fdf1957d1bfe74c5a76d105561e12e
|
[
"MIT"
] | 1
|
2020-05-30T19:45:58.000Z
|
2020-05-30T19:45:58.000Z
|
tests/test_game_map.py
|
brittleshinpass/mossbread
|
6a225e5d11fdf1957d1bfe74c5a76d105561e12e
|
[
"MIT"
] | null | null | null |
tests/test_game_map.py
|
brittleshinpass/mossbread
|
6a225e5d11fdf1957d1bfe74c5a76d105561e12e
|
[
"MIT"
] | null | null | null |
import pytest
from array import array
from game_map import GameMap
from tests.conftest import get_relative_path
sample_map_data = tuple(
reversed(
(
array("I", (0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0)),
array("I", (0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0)),
array("I", (1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1)),
array("I", (1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1)),
array("I", (1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)),
array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)),
array("I", (1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1)),
array("I", (0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0)),
array("I", (0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0)),
)
)
)
def test_game_map_from_file(sample_game_map, sample_tiles):
assert sample_game_map.map_data == sample_map_data
assert sample_game_map.width == 21
assert sample_game_map.height == 21
assert sample_game_map.tile_data == sample_tiles
# Assert map is read right-up
assert sample_game_map.get(16, 2) == 0
assert sample_game_map.get(16, 18) == 1
def test_game_map_get_out_of_bounds(sample_game_map):
with pytest.raises(AssertionError):
sample_game_map.get(-1, 0)
sample_game_map.get(0, -1)
sample_game_map.get(-1, -1)
sample_game_map.get(21, 0)
sample_game_map.get(0, 21)
sample_game_map.get(21, 21)
def test_game_map_load_mapfile_nonrectangular():
with pytest.raises(AssertionError):
GameMap.load_mapfile(get_relative_path("fixtures/map_nonrectangular.csv"))
def test_game_map_traversable(sample_game_map):
assert sample_game_map.traversable(2, 2)
assert not sample_game_map.traversable(1, 1)
assert sample_game_map.traversable(16, 2)
assert not sample_game_map.traversable(16, 18)
| 46.25
| 88
| 0.475994
| 678
| 3,145
| 2.103245
| 0.070796
| 0.280505
| 0.315568
| 0.322581
| 0.629032
| 0.504208
| 0.445302
| 0.396914
| 0.391304
| 0.388499
| 0
| 0.219334
| 0.302703
| 3,145
| 67
| 89
| 46.940299
| 0.430917
| 0.008585
| 0
| 0.333333
| 0
| 0
| 0.016688
| 0.009949
| 0
| 0
| 0
| 0
| 0.222222
| 1
| 0.074074
| false
| 0
| 0.074074
| 0
| 0.148148
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f7309823f58463b82e823f3fd4ecc77467f835fd
| 11,759
|
py
|
Python
|
pml/engineer_tests.py
|
gatapia/py_ml_utils
|
844d8b62a7c5cc0a80f4f62c0bfda092aac57ade
|
[
"MIT"
] | 183
|
2015-01-11T13:01:01.000Z
|
2022-02-08T04:45:33.000Z
|
pml/engineer_tests.py
|
gatapia/py_ml_utils
|
844d8b62a7c5cc0a80f4f62c0bfda092aac57ade
|
[
"MIT"
] | 13
|
2015-05-12T17:39:42.000Z
|
2018-07-29T18:01:38.000Z
|
pml/engineer_tests.py
|
gatapia/py_ml_utils
|
844d8b62a7c5cc0a80f4f62c0bfda092aac57ade
|
[
"MIT"
] | 166
|
2015-01-28T18:05:55.000Z
|
2022-02-08T04:45:34.000Z
|
from __future__ import print_function, absolute_import
import unittest, math
import pandas as pd
import numpy as np
from . import *
class T(base_pandas_extensions_tester.BasePandasExtensionsTester):
def test_concat(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'c_2': ['d', 'e', 'f']})
df.engineer('concat(c_1, c_2)')
self.assertTrue(np.array_equal(df['c_concat(c_1,c_2)'].values,
np.array(['ad', 'be', 'cf'], 'object')))
def test_concat_3_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'c_2': ['d', 'e', 'f'], 'c_3': ['h', 'i', 'j']})
df.engineer('concat(c_3, c_1, c_2)')
self.assertTrue(np.array_equal(df['c_concat(c_3,c_1,c_2)'].values,
np.array(['had', 'ibe', 'jcf'], 'object')))
def test_concat_with_numerical_col(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3]})
df.engineer('concat(c_1,n_2)')
self.assertTrue(np.array_equal(df['c_concat(c_1,n_2)'].values,
np.array(['a1', 'b2', 'c3'], 'object')))
def test_concat_with_numerical_col_3_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6]})
df.engineer('concat(n_3,c_1,n_2)')
self.assertTrue(np.array_equal(df['c_concat(n_3,c_1,n_2)'].values,
np.array(['4a1', '5b2', '6c3'], 'object')))
def test_multiplication(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('mult(n_2, n_3)')
self.assertTrue(np.array_equal(df['n_mult(n_2,n_3)'].values,
np.array([4, 10, 18], long)))
def test_multiplication_3_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('mult(n_2, n_3, n_4)')
self.assertTrue(np.array_equal(df['n_mult(n_2,n_3,n_4)'].values,
np.array([4*7, 80, 18*9], long)))
def test_square_on_whole_data_frame(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('pow(2)')
np.testing.assert_array_equal(df.values,
np.array([
['a', 1, 4, 7, 1*1, 4*4, 7*7],
['b', 2, 5, 8, 2*2, 5*5, 8*8],
['c', 3, 6, 9, 3*3, 6*6, 9*9],
], 'object'))
def test_square_on_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('pow(n_3, 2)')
np.testing.assert_array_equal(df.values,
np.array([
['a', 1, 4, 7, 4*4],
['b', 2, 5, 8, 5*5],
['c', 3, 6, 9, 6*6],
], 'object'))
def test_log_on_whole_data_frame(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('lg()')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 1, 4, 7, math.log(1), math.log(4), math.log(7)],
['b', 2, 5, 8, math.log(2), math.log(5), math.log(8)],
['c', 3, 6, 9, math.log(3), math.log(6), math.log(9)],
], 'object')))
def test_log_on_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('lg(n_3)')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 1, 4, 7, math.log(4)],
['b', 2, 5, 8, math.log(5)],
['c', 3, 6, 9, math.log(6)],
], 'object')))
def test_sqrt_on_whole_data_frame(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('sqrt()')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 1, 4, 7, math.sqrt(1), math.sqrt(4), math.sqrt(7)],
['b', 2, 5, 8, math.sqrt(2), math.sqrt(5), math.sqrt(8)],
['c', 3, 6, 9, math.sqrt(3), math.sqrt(6), math.sqrt(9)],
], 'object')))
def test_sqrt_on_cols(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('sqrt(n_3)')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 1, 4, 7, math.sqrt(4)],
['b', 2, 5, 8, math.sqrt(5)],
['c', 3, 6, 9, math.sqrt(6)],
], 'object')))
def test_rolling_sum_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_sum(n_1,3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 35, 40, 30, 29, 48], df['n_' + col])
def test_rolling_mean_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_mean(n_1,3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 11.66, 13.33, 10, 9.66, 16], df['n_' + col], rtol=1e-3)
def test_rolling_median_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_median(n_1,3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 12, 13, 13, 12, 12], df['n_' + col])
def test_rolling_min_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_min(n_1,3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 10, 12, 2, 2, 2], df['n_' + col])
def test_rolling_max_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_max(n_1,3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 13, 15, 15, 15, 34], df['n_' + col])
def test_rolling_std_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_std(n_1,3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 1.528, 1.528, 7, 6.807, 16.371], df['n_' + col], rtol=1e-3)
def test_rolling_var_on_single_col(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34]})
col = 'rolling_var(n_1,3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 2.333, 2.333, 49, 46.333, 268], df['n_' + col], rtol=1e-3)
# Multiple Columns
def test_rolling_sum_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_sum(3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 35, 40, 30, 29, 48], df['n_rolling_sum(n_1,3)'])
np.testing.assert_array_equal([np.nan, np.nan, 6, 10, 10, 9, 8], df['n_rolling_sum(n_2,3)'])
def test_rolling_mean_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_mean(3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 11.66, 13.33, 10, 9.66, 16], df['n_rolling_mean(n_1,3)'], rtol=1e-3)
np.testing.assert_allclose([np.nan, np.nan, 2, 3.333, 3.333, 3, 2.666], df['n_rolling_mean(n_2,3)'], rtol=1e-3)
def test_rolling_median_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_median(3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 12, 13, 13, 12, 12], df['n_rolling_median(n_1,3)'])
np.testing.assert_array_equal([np.nan, np.nan, 2, 3, 3, 2, 2], df['n_rolling_median(n_2,3)'])
def test_rolling_min_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_min(3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 10, 12, 2, 2, 2], df['n_rolling_min(n_1,3)'])
np.testing.assert_array_equal([np.nan, np.nan, 1, 2, 2, 2, 2], df['n_rolling_min(n_2,3)'])
def test_rolling_max_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_max(3)'
df.engineer(col)
np.testing.assert_array_equal([np.nan, np.nan, 13, 15, 15, 15, 34], df['n_rolling_max(n_1,3)'])
np.testing.assert_array_equal([np.nan, np.nan, 3, 5, 5, 5, 4], df['n_rolling_max(n_2,3)'])
def test_rolling_std_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_std(3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 1.528, 1.528, 7, 6.807, 16.371], df['n_rolling_std(n_1,3)'], rtol=1e-3)
np.testing.assert_allclose([np.nan, np.nan, 1, 1.528, 1.528, 1.732, 1.1547], df['n_rolling_std(n_2,3)'], rtol=1e-3)
def test_rolling_var_on_multi_cols(self):
df = pd.DataFrame({'n_1': [10, 12, 13, 15, 2, 12, 34], 'n_2': [1, 2, 3, 5, 2, 2, 4]})
col = 'rolling_var(3)'
df.engineer(col)
np.testing.assert_allclose([np.nan, np.nan, 2.333, 2.333, 49, 46.333, 268], df['n_rolling_var(n_1,3)'], rtol=1e-3)
np.testing.assert_allclose([np.nan, np.nan, 1, 2.333, 2.333, 3, 1.333], df['n_rolling_var(n_2,3)'], rtol=1e-3)
def test_method_chaining(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'c_2':['d', 'e', 'f'],
'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.\
engineer('concat(c_1, c_2)').\
engineer('concat(c_1, n_2)').\
engineer('mult(n_2, n_3)').\
engineer('lg(n_2)').\
engineer('pow(n_3, 2)')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 'd', 1, 4, 7, 'ad', 'a1', 4, math.log(1), 4*4],
['b', 'e', 2, 5, 8, 'be', 'b2', 10, math.log(2), 5*5],
['c', 'f', 3, 6, 9, 'cf', 'c3', 18, math.log(3), 6*6]
], 'object')))
def test_chaining_single_call_semi_col_sep(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'c_2':['d', 'e', 'f'],
'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('concat(c_1, c_2);concat(c_1, n_2);mult(n_2, n_3);lg(n_2);pow(n_3, 2)')
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 'd', 1, 4, 7, 'ad', 'a1', 4, math.log(1), 4*4],
['b', 'e', 2, 5, 8, 'be', 'b2', 10, math.log(2), 5*5],
['c', 'f', 3, 6, 9, 'cf', 'c3', 18, math.log(3), 6*6]
], 'object')))
def test_chaining_single_with_arr_arg(self):
df = pd.DataFrame({'c_1':['a', 'b', 'c'], 'c_2':['d', 'e', 'f'],
'n_2': [1, 2, 3], 'n_3': [4, 5, 6], 'n_4': [7, 8, 9]})
df.engineer('concat(c_1, c_2);concat(c_1, n_2);mult(n_2, n_3);lg(n_2);pow(n_3, 2)'.split(';'))
self.assertTrue(np.array_equal(df.values,
np.array([
['a', 'd', 1, 4, 7, 'ad', 'a1', 4, math.log(1), 4*4],
['b', 'e', 2, 5, 8, 'be', 'b2', 10, math.log(2), 5*5],
['c', 'f', 3, 6, 9, 'cf', 'c3', 18, math.log(3), 6*6]
], 'object')))
def test_long_method_chains(self):
df1 = pd.DataFrame({'n_1': [1, 2, 3], 'n_2': [4, 5, 6]})
df2 = pd.DataFrame({'n_1': [1, 2, 3], 'n_2': [4, 5, 6]})
df1.engineer('mult(lg(mult(n_1, n_2)), lg(pow(n_1, 3)))')
df2.engineer('mult(n_1,n_2);pow(n_1,3)')
df2.engineer('lg(pow(n_1,3));lg(mult(n_1, n_2))')
df2.engineer('mult(lg(mult(n_1,n_2)),lg(pow(n_1, 3)))')
np.testing.assert_array_equal(df1.columns.values.sort(), df2.columns.values.sort());
np.testing.assert_array_equal(df1['n_mult(n_1,n_2)'].values, df2['n_mult(n_1,n_2)'].values);
np.testing.assert_array_equal(df1['n_pow(n_1,3)'], df2['n_pow(n_1,3)']);
np.testing.assert_array_equal(df1['n_lg(pow(n_1,3))'], df2['n_lg(pow(n_1,3))']);
np.testing.assert_array_equal(df1['n_lg(mult(n_1,n_2))'], df2['n_lg(mult(n_1,n_2))']);
np.testing.assert_array_equal(df1['n_mult(lg(mult(n_1,n_2)),lg(pow(n_1,3)))'], df2['n_mult(lg(mult(n_1,n_2)),lg(pow(n_1,3)))']);
| 46.478261
| 133
| 0.541628
| 2,231
| 11,759
| 2.651277
| 0.060063
| 0.018935
| 0.039222
| 0.083347
| 0.878107
| 0.819104
| 0.762637
| 0.716653
| 0.695858
| 0.679459
| 0
| 0.114777
| 0.208691
| 11,759
| 252
| 134
| 46.662698
| 0.520903
| 0.001361
| 0
| 0.362791
| 0
| 0.009302
| 0.158586
| 0.03116
| 0
| 0
| 0
| 0
| 0.195349
| 1
| 0.139535
| false
| 0
| 0.023256
| 0
| 0.167442
| 0.004651
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f732fdf1128b31b7b49d386c93aa86199f8cc84f
| 109
|
py
|
Python
|
examples/etcc.py
|
t-pimpisa/pythainlp17
|
cc6bc4991dfffd68953dcdb26fd99c22d60a4c1f
|
[
"Apache-2.0"
] | null | null | null |
examples/etcc.py
|
t-pimpisa/pythainlp17
|
cc6bc4991dfffd68953dcdb26fd99c22d60a4c1f
|
[
"Apache-2.0"
] | null | null | null |
examples/etcc.py
|
t-pimpisa/pythainlp17
|
cc6bc4991dfffd68953dcdb26fd99c22d60a4c1f
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from pythainlp.tokenize import etcc
print(etcc.etcc("คืนความสุข")) # /คืน/ความสุข
| 18.166667
| 46
| 0.642202
| 22
| 109
| 3.363636
| 0.727273
| 0.054054
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010638
| 0.137615
| 109
| 5
| 47
| 21.8
| 0.734043
| 0.311927
| 0
| 0
| 0
| 0
| 0.138889
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
f78b62473ace335a7a8a2b3f902ea2441941d851
| 26,116
|
py
|
Python
|
python/dgllife/model/pretrain/__init__.py
|
VIGNESHinZONE/dgl-lifesci
|
9a892fd0935a7d8ab125530f54ce1e2a38b2377a
|
[
"Apache-2.0"
] | null | null | null |
python/dgllife/model/pretrain/__init__.py
|
VIGNESHinZONE/dgl-lifesci
|
9a892fd0935a7d8ab125530f54ce1e2a38b2377a
|
[
"Apache-2.0"
] | null | null | null |
python/dgllife/model/pretrain/__init__.py
|
VIGNESHinZONE/dgl-lifesci
|
9a892fd0935a7d8ab125530f54ce1e2a38b2377a
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
#
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
#
# pylint: disable= no-member, arguments-differ, invalid-name
#
# Utilities for using pre-trained models.
import torch
from dgl.data.utils import _get_dgl_url, download
from .moleculenet import *
from .generative_models import *
from .property_prediction import *
from .reaction import *
__all__ = ['load_pretrained']
url = {**moleculenet_url, **generative_url, **property_url, **reaction_url}
def download_and_load_checkpoint(model_name, model, model_postfix,
local_pretrained_path='pre_trained.pth', log=True):
"""Download pretrained model checkpoint
The model will be loaded to CPU.
Parameters
----------
model_name : str
Name of the model
model : nn.Module
Instantiated model instance
model_postfix : str
Postfix for pretrained model checkpoint
local_pretrained_path : str
Local name for the downloaded model checkpoint
log : bool
Whether to print progress for model loading
Returns
-------
model : nn.Module
Pretrained model
"""
url_to_pretrained = _get_dgl_url(model_postfix)
local_pretrained_path = '_'.join([model_name, local_pretrained_path])
download(url_to_pretrained, path=local_pretrained_path, log=log)
checkpoint = torch.load(local_pretrained_path, map_location='cpu')
model.load_state_dict(checkpoint['model_state_dict'])
if log:
print('Pretrained model loaded')
return model
# pylint: disable=I1101
def load_pretrained(model_name, log=True):
"""Load a pretrained model
Parameters
----------
model_name : str
Currently supported options include
* ``'GCN_Tox21'``: A GCN-based model for molecular property prediction on Tox21
* ``'GAT_Tox21'``: A GAT-based model for molecular property prediction on Tox21
* ``'Weave_Tox21'``: A Weave model for molecular property prediction on Tox21
* ``'AttentiveFP_Aromaticity'``: An AttentiveFP model for predicting number of
aromatic atoms on a subset of Pubmed
* ``'DGMG_ChEMBL_canonical'``: A DGMG model trained on ChEMBL with a canonical
atom order
* ``'DGMG_ChEMBL_random'``: A DGMG model trained on ChEMBL for molecule generation
with a random atom order
* ``'DGMG_ZINC_canonical'``: A DGMG model trained on ZINC for molecule generation
with a canonical atom order
* ``'DGMG_ZINC_random'``: A DGMG model pre-trained on ZINC for molecule generation
with a random atom order
* ``'JTNN_ZINC'``: A JTNN model pre-trained on ZINC for molecule generation
* ``'wln_center_uspto'``: A WLN model pre-trained on USPTO for reaction prediction
* ``'wln_rank_uspto'``: A WLN model pre-trained on USPTO for candidate product ranking
* ``'gin_supervised_contextpred'``: A GIN model pre-trained with supervised learning
and context prediction
* ``'gin_supervised_infomax'``: A GIN model pre-trained with supervised learning
and deep graph infomax
* ``'gin_supervised_edgepred'``: A GIN model pre-trained with supervised learning
and edge prediction
* ``'gin_supervised_masking'``: A GIN model pre-trained with supervised learning
and attribute masking
* ``'GCN_canonical_BACE'``: A GCN model trained on BACE with canonical
featurization for atoms
* ``'GCN_attentivefp_BACE'``: A GCN model trained on BACE with attentivefp
featurization for atoms
* ``'GAT_canonical_BACE'``: A GAT model trained on BACE with canonical
featurization for atoms
* ``'GAT_attentivefp_BACE'``: A GAT model trained on BACE with attentivefp
featurization for atoms
* ``'Weave_canonical_BACE'``: A Weave model trained on BACE with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_BACE'``: A Weave model trained on BACE with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_BACE'``: An MPNN model trained on BACE with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_BACE'``: An MPNN model trained on BACE with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_BACE'``: An AttentiveFP model trained on BACE with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_BACE'``: An AttentiveFP model trained on BACE with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_BACE'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on BACE
* ``'gin_supervised_infomax_BACE'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on BACE
* ``'gin_supervised_edgepred_BACE'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on BACE
* ``'gin_supervised_masking_BACE'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on BACE
* ``'NF_canonical_BACE'``: An NF model trained on BACE with canonical
featurization for atoms
* ``'GCN_canonical_BBBP'``: A GCN model trained on BBBP with canonical
featurization for atoms
* ``'GCN_attentivefp_BBBP'``: A GCN model trained on BBBP with attentivefp
featurization for atoms
* ``'GAT_canonical_BBBP'``: A GAT model trained on BBBP with canonical
featurization for atoms
* ``'GAT_attentivefp_BBBP'``: A GAT model trained on BBBP with attentivefp
featurization for atoms
* ``'Weave_canonical_BBBP'``: A Weave model trained on BBBP with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_BBBP'``: A Weave model trained on BBBP with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_BBBP'``: An MPNN model trained on BBBP with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_BBBP'``: An MPNN model trained on BBBP with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_BBBP'``: An AttentiveFP model trained on BBBP with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_BBBP'``: An AttentiveFP model trained on BBBP with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_BBBP'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on BBBP
* ``'gin_supervised_infomax_BBBP'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on BBBP
* ``'gin_supervised_edgepred_BBBP'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on BBBP
* ``'gin_supervised_masking_BBBP'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on BBBP
* ``'NF_canonical_BBBP'``: An NF model pre-trained on BBBP with canonical
featurization for atoms
* ``'GCN_canonical_ClinTox'``: A GCN model trained on ClinTox with canonical
featurization for atoms
* ``'GCN_attentivefp_ClinTox'``: A GCN model trained on ClinTox with attentivefp
featurization for atoms
* ``'GAT_canonical_ClinTox'``: A GAT model trained on ClinTox with canonical
featurization for atoms
* ``'GAT_attentivefp_ClinTox'``: A GAT model trained on ClinTox with attentivefp
featurization for atoms
* ``'Weave_canonical_ClinTox'``: A Weave model trained on ClinTox with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_ClinTox'``: A Weave model trained on ClinTox with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_ClinTox'``: An MPNN model trained on ClinTox with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_ClinTox'``: An MPNN model trained on ClinTox with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_ClinTox'``: An AttentiveFP model trained on ClinTox with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_BACE'``: An AttentiveFP model trained on ClinTox with
attentivefp featurization for atoms and bonds
* ``'GCN_canonical_ESOL'``: A GCN model trained on ESOL with canonical
featurization for atoms
* ``'GCN_attentivefp_ESOL'``: A GCN model trained on ESOL with attentivefp
featurization for atoms
* ``'GAT_canonical_ESOL'``: A GAT model trained on ESOL with canonical
featurization for atoms
* ``'GAT_attentivefp_ESOL'``: A GAT model trained on ESOL with attentivefp
featurization for atoms
* ``'Weave_canonical_ESOL'``: A Weave model trained on ESOL with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_ESOL'``: A Weave model trained on ESOL with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_ESOL'``: An MPNN model trained on ESOL with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_ESOL'``: An MPNN model trained on ESOL with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_ESOL'``: An AttentiveFP model trained on ESOL with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_ESOL'``: An AttentiveFP model trained on ESOL with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_ESOL'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on ESOL
* ``'gin_supervised_infomax_ESOL'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on ESOL
* ``'gin_supervised_edgepred_ESOL'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on ESOL
* ``'gin_supervised_masking_ESOL'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on ESOL
* ``'GCN_canonical_FreeSolv'``: A GCN model trained on FreeSolv with canonical
featurization for atoms
* ``'GCN_attentivefp_FreeSolv'``: A GCN model trained on FreeSolv with attentivefp
featurization for atoms
* ``'GAT_canonical_FreeSolv'``: A GAT model trained on FreeSolv with canonical
featurization for atoms
* ``'GAT_attentivefp_FreeSolv'``: A GAT model trained on FreeSolv with attentivefp
featurization for atoms
* ``'Weave_canonical_FreeSolv'``: A Weave model trained on FreeSolv with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_FreeSolv'``: A Weave model trained on FreeSolv with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_FreeSolv'``: An MPNN model trained on FreeSolv with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_FreeSolv'``: An MPNN model trained on FreeSolv with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_FreeSolv'``: An AttentiveFP model trained on FreeSolv with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_FreeSolv'``: An AttentiveFP model trained on FreeSolv with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_FreeSolv'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on FreeSolv
* ``'gin_supervised_infomax_FreeSolv'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on FreeSolv
* ``'gin_supervised_edgepred_FreeSolv'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on FreeSolv
* ``'gin_supervised_masking_FreeSolv'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on FreeSolv
* ``'GCN_canonical_HIV'``: A GCN model trained on HIV with canonical
featurization for atoms
* ``'GCN_attentivefp_HIV'``: A GCN model trained on HIV with attentivefp
featurization for atoms
* ``'GAT_canonical_HIV'``: A GAT model trained on BACE with canonical
featurization for atoms
* ``'GAT_attentivefp_HIV'``: A GAT model trained on BACE with attentivefp
featurization for atoms
* ``'Weave_canonical_HIV'``: A Weave model trained on HIV with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_HIV'``: A Weave model trained on HIV with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_HIV'``: An MPNN model trained on HIV with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_HIV'``: An MPNN model trained on HIV with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_HIV'``: An AttentiveFP model trained on HIV with canonical
featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_HIV'``: An AttentiveFP model trained on HIV with attentivefp
featurization for atoms and bonds
* ``'gin_supervised_contextpred_HIV'``: A GIN model pre-trained with supervised learning
and context prediction, and fine-tuned on HIV
* ``'gin_supervised_infomax_HIV'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on HIV
* ``'gin_supervised_edgepred_HIV'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on HIV
* ``'gin_supervised_masking_HIV'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on HIV
* ``'NF_canonical_HIV'``: An NF model trained on HIV with canonical
featurization for atoms
* ``'GCN_canonical_Lipophilicity'``: A GCN model trained on Lipophilicity with canonical
featurization for atoms
* ``'GCN_attentivefp_Lipophilicity'``: A GCN model trained on Lipophilicity with
attentivefp featurization for atoms
* ``'GAT_canonical_Lipophilicity'``: A GAT model trained on Lipophilicity with canonical
featurization for atoms
* ``'GAT_attentivefp_Lipophilicity'``: A GAT model trained on Lipophilicity with
attentivefp featurization for atoms
* ``'Weave_canonical_Lipophilicity'``: A Weave model trained on Lipophilicity with
canonical featurization for atoms and bonds
* ``'Weave_attentivefp_Lipophilicity'``: A Weave model trained on Lipophilicity with
attentivefp featurization for atoms and bonds
* ``'MPNN_canonical_Lipophilicity'``: An MPNN model trained on Lipophilicity with
canonical featurization for atoms and bonds
* ``'MPNN_attentivefp_Lipophilicity'``: An MPNN model trained on Lipophilicity with
attentivefp featurization for atoms and bonds
* ``'AttentiveFP_canonical_Lipophilicity'``: An AttentiveFP model trained on
Lipophilicity with canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_Lipophilicity'``: An AttentiveFP model trained on
Lipophilicity with attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_Lipophilicity'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on Lipophilicity
* ``'gin_supervised_infomax_Lipophilicity'``: A GIN model pre-trained with supervised
learning and infomax, and fine-tuned on Lipophilicity
* ``'gin_supervised_edgepred_Lipophilicity'``: A GIN model pre-trained with supervised
learning and edge prediction, and fine-tuned on Lipophilicity
* ``'gin_supervised_masking_Lipophilicity'``: A GIN model pre-trained with supervised
learning and masking, and fine-tuned on Lipophilicity
* ``'GCN_canonical_MUV'``: A GCN model trained on MUV with canonical
featurization for atoms
* ``'GCN_attentivefp_MUV'``: A GCN model trained on MUV with attentivefp
featurization for atoms
* ``'GAT_canonical_MUV'``: A GAT model trained on MUV with canonical
featurization for atoms
* ``'GAT_attentivefp_MUV'``: A GAT model trained on MUV with attentivefp
featurization for atoms
* ``'Weave_canonical_MUV'``: A Weave model trained on MUV with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_MUV'``: A Weave model trained on MUV with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_MUV'``: An MPNN model trained on MUV with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_MUV'``: An MPNN model trained on MUV with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_MUV'``: An AttentiveFP model trained on MUV with canonical
featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_MUV'``: An AttentiveFP model trained on MUV with attentivefp
featurization for atoms and bonds
* ``'gin_supervised_contextpred_MUV'``: A GIN model pre-trained with supervised learning
and context prediction, and fine-tuned on MUV
* ``'gin_supervised_infomax_MUV'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on MUV
* ``'gin_supervised_edgepred_MUV'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on MUV
* ``'gin_supervised_masking_MUV'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on MUV
* ``'GCN_canonical_PCBA'``: A GCN model trained on PCBA with canonical
featurization for atoms
* ``'GCN_attentivefp_PCBA'``: A GCN model trained on PCBA with attentivefp
featurization for atoms
* ``'GAT_canonical_PCBA'``: A GAT model trained on PCBA with canonical
featurization for atoms
* ``'GAT_attentivefp_PCBA'``: A GAT model trained on PCBA with attentivefp
featurization for atoms
* ``'Weave_canonical_PCBA'``: A Weave model trained on PCBA with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_PCBA'``: A Weave model trained on PCBA with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_PCBA'``: An MPNN model trained on PCBA with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_PCBA'``: An MPNN model trained on PCBA with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_PCBA'``: An AttentiveFP model trained on PCBA with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_PCBA'``: An AttentiveFP model trained on PCBA with
attentivefp featurization for atoms and bonds
* ``'GCN_canonical_SIDER'``: A GCN model trained on SIDER with canonical
featurization for atoms
* ``'GCN_attentivefp_SIDER'``: A GCN model trained on SIDER with attentivefp
featurization for atoms
* ``'GAT_canonical_SIDER'``: A GAT model trained on SIDER with canonical
featurization for atoms
* ``'GAT_attentivefp_SIDER'``: A GAT model trained on SIDER with attentivefp
featurization for atoms
* ``'Weave_canonical_SIDER'``: A Weave model trained on SIDER with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_SIDER'``: A Weave model trained on SIDER with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_SIDER'``: An MPNN model trained on SIDER with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_SIDER'``: An MPNN model trained on SIDER with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_SIDER'``: An AttentiveFP model trained on SIDER with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_SIDER'``: An AttentiveFP model trained on SIDER with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_SIDER'``: A GIN model pre-trained with supervised learning
and context prediction, and fine-tuned on SIDER
* ``'gin_supervised_infomax_SIDER'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on SIDER
* ``'gin_supervised_edgepred_SIDER'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on SIDER
* ``'gin_supervised_masking_SIDER'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on SIDER
* ``'NF_canonical_SIDER'``: An NF model trained on SIDER with canonical
featurization for atoms
* ``'GCN_canonical_Tox21'``: A GCN model trained on Tox21 with canonical
featurization for atoms
* ``'GCN_attentivefp_Tox21'``: A GCN model trained on Tox21 with attentivefp
featurization for atoms
* ``'GAT_canonical_Tox21'``: A GAT model trained on Tox21 with canonical
featurization for atoms
* ``'GAT_attentivefp_Tox21'``: A GAT model trained on Tox21 with attentivefp
featurization for atoms
* ``'Weave_canonical_Tox21'``: A Weave model trained on Tox21 with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_Tox21'``: A Weave model trained on Tox21 with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_Tox21'``: An MPNN model trained on Tox21 with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_Tox21'``: An MPNN model trained on Tox21 with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_Tox21'``: An AttentiveFP model trained on Tox21 with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_Tox21'``: An AttentiveFP model trained on Tox21 with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_Tox21'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on Tox21
* ``'gin_supervised_infomax_Tox21'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on Tox21
* ``'gin_supervised_edgepred_Tox21'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on Tox21
* ``'gin_supervised_masking_Tox21'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on Tox21
* ``'NF_canonical_Tox21'``: An NF model trained on Tox21 with canonical
featurization for atoms
* ``'GCN_canonical_ToxCast'``: A GCN model trained on ToxCast with canonical
featurization for atoms
* ``'GCN_attentivefp_ToxCast'``: A GCN model trained on ToxCast with attentivefp
featurization for atoms
* ``'GAT_canonical_ToxCast'``: A GAT model trained on ToxCast with canonical
featurization for atoms
* ``'GAT_attentivefp_ToxCast'``: A GAT model trained on ToxCast with attentivefp
featurization for atoms
* ``'Weave_canonical_ToxCast'``: A Weave model trained on ToxCast with canonical
featurization for atoms and bonds
* ``'Weave_attentivefp_ToxCast'``: A Weave model trained on ToxCast with attentivefp
featurization for atoms and bonds
* ``'MPNN_canonical_ToxCast'``: An MPNN model trained on ToxCast with canonical
featurization for atoms and bonds
* ``'MPNN_attentivefp_ToxCast'``: An MPNN model trained on ToxCast with attentivefp
featurization for atoms and bonds
* ``'AttentiveFP_canonical_ToxCast'``: An AttentiveFP model trained on ToxCast with
canonical featurization for atoms and bonds
* ``'AttentiveFP_attentivefp_ToxCast'``: An AttentiveFP model trained on ToxCast with
attentivefp featurization for atoms and bonds
* ``'gin_supervised_contextpred_ToxCast'``: A GIN model pre-trained with supervised
learning and context prediction, and fine-tuned on ToxCast
* ``'gin_supervised_infomax_ToxCast'``: A GIN model pre-trained with supervised learning
and infomax, and fine-tuned on ToxCast
* ``'gin_supervised_edgepred_ToxCast'``: A GIN model pre-trained with supervised learning
and edge prediction, and fine-tuned on ToxCast
* ``'gin_supervised_masking_ToxCast'``: A GIN model pre-trained with supervised learning
and masking, and fine-tuned on ToxCast
* ``'NF_canonical_ToxCast'``: An NF model trained on ToxCast with canonical
featurization for atoms and bonds
log : bool
Whether to print progress for model loading
Returns
-------
model
"""
if model_name not in url:
raise RuntimeError("Cannot find a pretrained model with name {}".format(model_name))
for func in [create_moleculenet_model, create_generative_model,
create_property_model, create_reaction_model]:
model = func(model_name)
if model is not None:
break
return download_and_load_checkpoint(model_name, model, url[model_name], log=log)
| 59.219955
| 98
| 0.689501
| 3,192
| 26,116
| 5.495614
| 0.052318
| 0.068236
| 0.102155
| 0.099875
| 0.883879
| 0.876012
| 0.868772
| 0.815129
| 0.698894
| 0.503819
| 0
| 0.003991
| 0.242074
| 26,116
| 440
| 99
| 59.354545
| 0.882237
| 0.889531
| 0
| 0
| 0
| 0
| 0.087349
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.074074
| false
| 0
| 0.222222
| 0
| 0.37037
| 0.037037
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f797e5f31f0f4940006d8b4a1e545eb141db847d
| 10,703
|
py
|
Python
|
tests/sentry/integrations/cloudflare/test_webhook.py
|
jianyuan/sentry
|
ceb8389c54d29f80b27703bb76c3880d923a3a5a
|
[
"BSD-3-Clause"
] | 1
|
2017-10-18T19:40:14.000Z
|
2017-10-18T19:40:14.000Z
|
tests/sentry/integrations/cloudflare/test_webhook.py
|
Munyola/sentry
|
ab8923b2801d7d72d6903e0d9180584817bb1b9a
|
[
"BSD-3-Clause"
] | 1
|
2021-02-24T04:32:19.000Z
|
2021-02-24T04:32:19.000Z
|
tests/sentry/integrations/cloudflare/test_webhook.py
|
Munyola/sentry
|
ab8923b2801d7d72d6903e0d9180584817bb1b9a
|
[
"BSD-3-Clause"
] | 2
|
2021-01-26T09:53:39.000Z
|
2022-03-22T09:01:47.000Z
|
from __future__ import absolute_import
from hashlib import sha256
import hmac
import json
import six
from sentry import options
from sentry.models import ApiToken, ProjectKey
from sentry.testutils import TestCase
UNSET = object()
class BaseWebhookTest(TestCase):
def setUp(self):
super(BaseWebhookTest, self).setUp()
self.user = self.create_user(is_superuser=False)
self.org = self.create_organization(owner=None)
self.team = self.create_team(organization=self.org)
self.create_member(organization=self.org, user=self.user, role='owner', teams=[self.team])
self.project = self.create_project(name='a', team=self.team)
self.token = ApiToken.objects.create(
user=self.user,
token='55838c83b3ec4e3ebc24c10c7bd071ffb1dc91161d3d49aeaedd9bd35d84bbe2',
)
self.key = ProjectKey.objects.get_or_create(project=self.project)[0]
def post_webhook(self, data, signature=UNSET, variant=UNSET, key=None):
if key is None:
key = options.get('cloudflare.secret-key')
if not isinstance(data, six.string_types):
body = json.dumps(data)
else:
body = data
if signature is UNSET:
signature = hmac.new(
key=key.encode('utf-8'),
msg=body.encode('utf-8'),
digestmod=sha256,
).hexdigest()
if variant is UNSET:
variant = '1'
headers = {
'HTTP_X_SIGNATURE_HMAC_SHA256_HEX': signature,
'HTTP_X_SIGNATURE_KEY_VARIANT': variant,
}
return self.client.post(
'/extensions/cloudflare/webhook/',
body,
content_type='application/json',
**headers
)
class CloudflareWebhookTest(BaseWebhookTest):
def test_missing_signature(self):
resp = self.post_webhook(
{'event': 'test'},
signature=None,
)
assert resp.status_code == 400
def test_invalid_signature(self):
resp = self.post_webhook(
{'event': 'test'},
signature='a' * 40,
)
assert resp.status_code == 400
def test_invalid_json(self):
resp = self.post_webhook('a')
assert resp.status_code == 400
def test_missing_variant(self):
resp = self.post_webhook(
{'event': 'test'},
variant=None,
)
assert resp.status_code == 400
def test_invalid_variant(self):
resp = self.post_webhook(
{'event': 'test'},
variant='fizzbuz',
)
assert resp.status_code == 400
def test_invalid_signature_with_test_variant(self):
resp = self.post_webhook(
{'event': 'test'},
variant='test',
)
assert resp.status_code == 400
def test_invalid_app_id_test_variant(self):
resp = self.post_webhook(
{'event': 'test', 'app': {'id': 'buzz'}},
variant='test',
key='test-key',
)
assert resp.status_code == 400
def test_valid_test_variant(self):
resp = self.post_webhook(
{'event': 'test', 'app': {'id': 'local'}, 'install': {}},
variant='test',
key='test-key',
)
assert resp.status_code == 200
class PreviewWebhookTest(BaseWebhookTest):
def test_empty(self):
webhook_data = json.loads(self.load_fixture('cloudflare/preview-webhook.json'))
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data == {
'install': webhook_data['install'],
'proceed': True,
}
def test_prefills_data(self):
webhook_data = json.loads(self.load_fixture(
'cloudflare/preview-webhook-authenticated.json'))
webhook_data['install']['options']['organization'] = six.text_type(self.org.id)
resp = self.post_webhook(data=webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['schema']['properties']['organization']['enumNames'] == {
six.text_type(self.org.id): self.org.slug,
}
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == [
six.text_type(self.project.id)]
assert resp.data['install']['schema']['properties']['project']['enumNames'] == {
six.text_type(self.project.id): self.project.slug,
}
assert resp.data['install']['options']['project'] == six.text_type(self.project.id)
assert resp.data['install']['schema']['properties']['dsn']['enum'] == [
self.key.get_dsn(public=True)]
assert resp.data['install']['options']['dsn'] == six.text_type(
self.key.get_dsn(public=True))
def test_multiple_projects(self):
project2 = self.create_project(name='b', team=self.team)
webhook_data = json.loads(self.load_fixture(
'cloudflare/preview-webhook-authenticated.json'))
webhook_data['install']['options']['organization'] = six.text_type(self.org.id)
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == [
six.text_type(self.project.id), six.text_type(project2.id)]
assert resp.data['install']['options']['project'] == six.text_type(self.project.id)
assert resp.data['install']['schema']['properties']['dsn']['enum'] == [
self.key.get_dsn(public=True)]
assert resp.data['install']['options']['dsn'] == six.text_type(
self.key.get_dsn(public=True))
def test_no_projects(self):
self.project.delete()
webhook_data = json.loads(self.load_fixture(
'cloudflare/preview-webhook-authenticated.json'))
webhook_data['install']['options']['organization'] = six.text_type(self.org.id)
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == []
assert 'dsn' not in resp.data['install']['schema']['properties']
class OptionChangeAccountWebhookTest(BaseWebhookTest):
def test_without_authentication(self):
webhook_data = json.loads(self.load_fixture(
'cloudflare/option-change-account-webhook.json'))
del webhook_data['authentications']
resp = self.post_webhook(webhook_data)
assert resp.status_code == 401, resp.content
def test_prefills_data(self):
webhook_data = json.loads(self.load_fixture(
'cloudflare/option-change-account-webhook.json'))
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == [
six.text_type(self.project.id)]
assert resp.data['install']['options']['project'] == six.text_type(self.project.id)
assert resp.data['install']['schema']['properties']['dsn']['enum'] == [
self.key.get_dsn(public=True)]
assert resp.data['install']['options']['dsn'] == six.text_type(
self.key.get_dsn(public=True))
def test_with_invalid_organization_selected(self):
webhook_data = json.loads(self.load_fixture(
'cloudflare/option-change-account-webhook.json'))
webhook_data['install']['options']['organization'] = -1
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == [
six.text_type(self.project.id)]
assert resp.data['install']['options']['project'] == six.text_type(self.project.id)
assert resp.data['install']['schema']['properties']['dsn']['enum'] == [
self.key.get_dsn(public=True)]
assert resp.data['install']['options']['dsn'] == six.text_type(
self.key.get_dsn(public=True))
def test_with_existing_project_selected_and_no_keys(self):
project2 = self.create_project(name='b', team=self.team)
# kill the automatically generated keys
ProjectKey.objects.filter(project=project2).delete()
webhook_data = json.loads(self.load_fixture(
'cloudflare/option-change-account-webhook.json'))
webhook_data['install']['options']['organization'] = six.text_type(self.org.id)
webhook_data['install']['options']['project'] = six.text_type(project2.id)
resp = self.post_webhook(webhook_data)
assert resp.status_code == 200, resp.content
assert resp.data['proceed']
assert resp.data['install']['schema']['properties']['organization']['enum'] == [
six.text_type(self.org.id)]
assert resp.data['install']['options']['organization'] == six.text_type(self.org.id)
assert resp.data['install']['schema']['properties']['project']['enum'] == [
six.text_type(self.project.id), six.text_type(project2.id)]
assert resp.data['install']['options']['project'] == six.text_type(project2.id)
assert resp.data['install']['schema']['properties']['dsn']['enum'] == []
assert 'dsn' not in resp.data['install']['options']
| 41.484496
| 98
| 0.613566
| 1,226
| 10,703
| 5.21044
| 0.116639
| 0.08923
| 0.089856
| 0.115059
| 0.747495
| 0.738103
| 0.729962
| 0.721822
| 0.700063
| 0.612085
| 0
| 0.012589
| 0.22816
| 10,703
| 257
| 99
| 41.645914
| 0.760683
| 0.003457
| 0
| 0.527778
| 0
| 0
| 0.183327
| 0.04895
| 0
| 0
| 0
| 0
| 0.273148
| 1
| 0.083333
| false
| 0
| 0.037037
| 0
| 0.143519
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e3aa556fa11d4a3e0d7e99f07a6cd0ab4a4331f6
| 7,607
|
py
|
Python
|
test/integration/test_build.py
|
DahlitzFlorian/wily
|
069c26bff9741b49420e3cfd7b0954ac9b88cc3f
|
[
"Apache-2.0"
] | null | null | null |
test/integration/test_build.py
|
DahlitzFlorian/wily
|
069c26bff9741b49420e3cfd7b0954ac9b88cc3f
|
[
"Apache-2.0"
] | null | null | null |
test/integration/test_build.py
|
DahlitzFlorian/wily
|
069c26bff9741b49420e3cfd7b0954ac9b88cc3f
|
[
"Apache-2.0"
] | null | null | null |
"""
Tests for the wily build command.
All of the following tests will use a click CLI runner to fully simulate the CLI.
Many of the tests will depend on a "builddir" fixture which is a compiled wily cache.
TODO : Test build + build with extra operator
"""
import pathlib
import pytest
from click.testing import CliRunner
from git import Repo, Actor
from mock import patch
import wily.__main__ as main
from wily.archivers import ALL_ARCHIVERS
def test_build_not_git_repo(tmpdir):
"""
Test that build defaults to filesystem in a non-git directory
"""
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(main.cli, ["--path", tmpdir, "build", "test.py"])
assert result.exit_code == 0, result.stdout
cache_path = tmpdir / ".wily"
assert cache_path.exists()
index_path = tmpdir / ".wily" / "filesystem" / "index.json"
assert index_path.exists()
def test_build_invalid_path(tmpdir):
"""
Test that build fails with a garbage path
"""
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(main.cli, ["--path", "/fo/v/a", "build", "test.py"])
assert result.exit_code == 1, result.stdout
def test_build_no_target(tmpdir):
"""
Test that build fails with no target
"""
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(main.cli, ["--path", tmpdir, "build"])
assert result.exit_code == 2, result.stdout
def test_build_crash(tmpdir):
"""
Test that build works in a basic repository.
"""
repo = Repo.init(path=tmpdir)
tmppath = pathlib.Path(tmpdir)
# Write a test file to the repo
with open(tmppath / "test.py", "w") as test_txt:
test_txt.write("import abc")
with open(tmppath / ".gitignore", "w") as test_txt:
test_txt.write(".wily/")
index = repo.index
index.add(["test.py", ".gitignore"])
author = Actor("An author", "[email protected]")
committer = Actor("A committer", "[email protected]")
index.commit("basic test", author=author, committer=committer)
import wily.commands.build
with patch.object(
wily.commands.build.Bar, "finish", side_effect=RuntimeError("arggh")
) as bar_finish:
runner = CliRunner()
result = runner.invoke(main.cli, ["--path", tmpdir, "build", "test.py"])
assert bar_finish.called_once
assert result.exit_code == 1, result.stdout
with patch("wily.commands.build.logger") as logger:
logger.level = "DEBUG"
with patch.object(
wily.commands.build.Bar, "finish", side_effect=RuntimeError("arggh")
) as bar_finish:
runner = CliRunner()
result = runner.invoke(
main.cli, ["--debug", "--path", tmpdir, "build", "test.py"]
)
assert bar_finish.called_once
assert result.exit_code == 1, result.stdout
def test_build(tmpdir):
"""
Test that build works in a basic repository.
"""
repo = Repo.init(path=tmpdir)
tmppath = pathlib.Path(tmpdir)
# Write a test file to the repo
with open(tmppath / "test.py", "w") as test_txt:
test_txt.write("import abc")
with open(tmppath / ".gitignore", "w") as test_txt:
test_txt.write(".wily/")
index = repo.index
index.add(["test.py", ".gitignore"])
author = Actor("An author", "[email protected]")
committer = Actor("A committer", "[email protected]")
commit = index.commit("basic test", author=author, committer=committer)
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(
main.cli, ["--debug", "--path", tmpdir, "build", "test.py"]
)
assert result.exit_code == 0, result.stdout
cache_path = tmpdir / ".wily"
assert cache_path.exists()
index_path = tmpdir / ".wily" / "git" / "index.json"
assert index_path.exists()
rev_path = tmpdir / ".wily" / "git" / commit.name_rev.split(" ")[0] + ".json"
assert rev_path.exists()
def test_build_twice(tmpdir):
"""
Test that build works when run twice.
"""
repo = Repo.init(path=tmpdir)
tmppath = pathlib.Path(tmpdir)
# Write a test file to the repo
with open(tmppath / "test.py", "w") as test_txt:
test_txt.write("import abc")
with open(tmppath / ".gitignore", "w") as test_txt:
test_txt.write(".wily/")
index = repo.index
index.add(["test.py", ".gitignore"])
author = Actor("An author", "[email protected]")
committer = Actor("A committer", "[email protected]")
commit = index.commit("basic test", author=author, committer=committer)
runner = CliRunner()
result = runner.invoke(main.cli, ["--debug", "--path", tmpdir, "build", "test.py"])
assert result.exit_code == 0, result.stdout
cache_path = tmpdir / ".wily"
assert cache_path.exists()
index_path = tmpdir / ".wily" / "git" / "index.json"
assert index_path.exists()
rev_path = tmpdir / ".wily" / "git" / commit.name_rev.split(" ")[0] + ".json"
assert rev_path.exists()
# Write a test file to the repo
with open(tmppath / "test.py", "w") as test_txt:
test_txt.write("import abc\nfoo = 1")
index.add(["test.py"])
commit2 = index.commit("basic test", author=author, committer=committer)
result = runner.invoke(main.cli, ["--debug", "--path", tmpdir, "build", "test.py"])
assert result.exit_code == 0, result.stdout
cache_path = tmpdir / ".wily"
assert cache_path.exists()
index_path = tmpdir / ".wily" / "git" / "index.json"
assert index_path.exists()
rev_path = tmpdir / ".wily" / "git" / commit.name_rev.split(" ")[0] + ".json"
assert rev_path.exists()
rev_path2 = tmpdir / ".wily" / "git" / commit2.name_rev.split(" ")[0] + ".json"
assert rev_path2.exists()
def test_build_no_commits(tmpdir):
"""
Test that build fails cleanly with no commits
"""
repo = Repo.init(path=tmpdir)
runner = CliRunner()
result = runner.invoke(
main.cli, ["--debug", "--path", tmpdir, "build", tmpdir, "--skip-ignore-check"]
)
assert result.exit_code == 1, result.stdout
def test_build_dirty_repo(builddir):
"""
Test that build fails cleanly with a dirty repo
"""
tmppath = pathlib.Path(builddir)
with open(tmppath / "test.py", "w") as test_txt:
test_txt.write("import abc\nfoo = 1")
runner = CliRunner()
result = runner.invoke(main.cli, ["--debug", "--path", builddir, "build", builddir])
assert result.exit_code == 1, result.stdout
def test_build_no_git_history(tmpdir):
repo = Repo.init(path=tmpdir)
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(main.cli, ["--path", tmpdir, "build", "src/test.py"])
assert result.exit_code == 1, result.stdout
archivers = {name for name in ALL_ARCHIVERS.keys()}
@pytest.mark.parametrize("archiver", archivers)
def test_build_archiver(gitdir, archiver):
"""
Test the build against each type of archiver
"""
with patch("wily.logger") as logger:
runner = CliRunner()
result = runner.invoke(
main.cli, ["--path", gitdir, "build", "src/test.py", "-a", archiver]
)
assert result.exit_code == 0, result.stdout
cache_path = gitdir / ".wily"
assert cache_path.exists()
index_path = gitdir / ".wily" / archiver / "index.json"
assert index_path.exists()
| 31.962185
| 88
| 0.625739
| 986
| 7,607
| 4.725152
| 0.135903
| 0.062245
| 0.046362
| 0.056665
| 0.784932
| 0.758747
| 0.721399
| 0.707448
| 0.685984
| 0.656793
| 0
| 0.003749
| 0.228474
| 7,607
| 237
| 89
| 32.097046
| 0.790083
| 0.102274
| 0
| 0.718121
| 0
| 0
| 0.15098
| 0.013317
| 0
| 0
| 0
| 0.004219
| 0.187919
| 1
| 0.067114
| false
| 0
| 0.087248
| 0
| 0.154362
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e3f8f7b3257c5bd12d8d3490e725fe8a7a51ecb9
| 388
|
py
|
Python
|
frappe/patches/v7_0/desktop_icons_hidden_by_admin_as_blocked.py
|
anandpdoshi/frappe
|
b3546f1ebcac3480eccf5d19371ca534e7ce79bb
|
[
"MIT"
] | null | null | null |
frappe/patches/v7_0/desktop_icons_hidden_by_admin_as_blocked.py
|
anandpdoshi/frappe
|
b3546f1ebcac3480eccf5d19371ca534e7ce79bb
|
[
"MIT"
] | null | null | null |
frappe/patches/v7_0/desktop_icons_hidden_by_admin_as_blocked.py
|
anandpdoshi/frappe
|
b3546f1ebcac3480eccf5d19371ca534e7ce79bb
|
[
"MIT"
] | 5
|
2016-06-20T08:48:11.000Z
|
2018-12-12T09:42:31.000Z
|
import frappe
def execute():
# all icons hidden in standard are "blocked"
# this is for the use case where the admin wants to remove icon for everyone
# in 7.0, icons may be hidden by default, but still can be shown to the user
# e.g. Accounts, Stock etc, so we need a new property for blocked
frappe.db.sql('update `tabDesktop Icon` set blocked = 1 where standard=1 and hidden=1')
| 43.111111
| 88
| 0.737113
| 71
| 388
| 4.028169
| 0.746479
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015974
| 0.193299
| 388
| 9
| 88
| 43.111111
| 0.897764
| 0.659794
| 0
| 0
| 0
| 0
| 0.546875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
540b37aa828992718d326e40cc3e8c5c7baaf141
| 67
|
py
|
Python
|
nadl/__init__.py
|
siAyush/nadl
|
8aa698231e1d198bf823a58c84f139f6f93bc7df
|
[
"MIT"
] | 7
|
2021-05-18T11:16:49.000Z
|
2021-05-30T20:25:12.000Z
|
nadl/__init__.py
|
siAyush/nadl
|
8aa698231e1d198bf823a58c84f139f6f93bc7df
|
[
"MIT"
] | null | null | null |
nadl/__init__.py
|
siAyush/nadl
|
8aa698231e1d198bf823a58c84f139f6f93bc7df
|
[
"MIT"
] | 1
|
2022-03-02T19:52:25.000Z
|
2022-03-02T19:52:25.000Z
|
from nadl.tensor import Tensor
from nadl.parameter import Parameter
| 33.5
| 36
| 0.865672
| 10
| 67
| 5.8
| 0.5
| 0.275862
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104478
| 67
| 2
| 36
| 33.5
| 0.966667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
583a4439342b3be3a1f5a61fbbd79630bf4f80cd
| 409
|
py
|
Python
|
cords/selectionstrategies/SL/__init__.py
|
krishnatejakk/AUTOMATA
|
fd0cf58058e39660f88d9d6b4101e30a497f6ce2
|
[
"MIT"
] | null | null | null |
cords/selectionstrategies/SL/__init__.py
|
krishnatejakk/AUTOMATA
|
fd0cf58058e39660f88d9d6b4101e30a497f6ce2
|
[
"MIT"
] | null | null | null |
cords/selectionstrategies/SL/__init__.py
|
krishnatejakk/AUTOMATA
|
fd0cf58058e39660f88d9d6b4101e30a497f6ce2
|
[
"MIT"
] | 1
|
2022-03-16T05:55:12.000Z
|
2022-03-16T05:55:12.000Z
|
from .craigstrategy import CRAIGStrategy
from .dataselectionstrategy import DataSelectionStrategy
from .glisterstrategy import GLISTERStrategy
from .randomstrategy import RandomStrategy
from .submodularselectionstrategy import SubmodularSelectionStrategy
from .gradmatchstrategy import GradMatchStrategy
from .fixedweightstrategy import FixedWeightStrategy
from .adapweightsstrategy import AdapWeightsStrategy
| 51.125
| 68
| 0.904645
| 32
| 409
| 11.5625
| 0.3125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075795
| 409
| 8
| 69
| 51.125
| 0.978836
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
58672ac219aa158da24cd5ab42129bffccff6013
| 2,429
|
py
|
Python
|
tests/fixtures/test_abstracts/content_03_expected.py
|
elifesciences/elife-tools
|
ee345bf0e6703ef0f7e718355e85730abbdfd117
|
[
"MIT"
] | 9
|
2015-04-16T08:13:31.000Z
|
2020-05-18T14:03:06.000Z
|
tests/fixtures/test_abstracts/content_03_expected.py
|
elifesciences/elife-tools
|
ee345bf0e6703ef0f7e718355e85730abbdfd117
|
[
"MIT"
] | 310
|
2015-02-11T00:30:09.000Z
|
2021-07-14T23:58:50.000Z
|
tests/fixtures/test_abstracts/content_03_expected.py
|
elifesciences/elife-tools
|
ee345bf0e6703ef0f7e718355e85730abbdfd117
|
[
"MIT"
] | 9
|
2015-02-04T01:21:28.000Z
|
2021-06-15T12:50:47.000Z
|
expected = [
{
"abstract_type": None,
"content": "RET can be activated in cis or trans by its co-receptors and ligands in vitro, but the physiological roles of trans signaling are unclear. Rapidly adapting (RA) mechanoreceptors in dorsal root ganglia (DRGs) express Ret and the co-receptor Gfr\u03b12 and depend on Ret for survival and central projection growth. Here, we show that Ret and Gfr\u03b12 null mice display comparable early central projection deficits, but Gfr\u03b12 null RA mechanoreceptors recover later. Loss of Gfr\u03b11, the co-receptor implicated in activating RET in trans, causes no significant central projection or cell survival deficit, but Gfr\u03b11;Gfr\u03b12 double nulls phenocopy Ret nulls. Finally, we demonstrate that GFR\u03b11 produced by neighboring DRG neurons activates RET in RA mechanoreceptors. Taken together, our results suggest that trans and cis RET signaling could function in the same developmental process and that the availability of both forms of activation likely enhances but not diversifies outcomes of RET signaling.",
"full_content": "<p>RET can be activated in <italic>cis</italic> or <italic>trans</italic> by its co-receptors and ligands <italic>in vitro</italic>, but the physiological roles of <italic>trans</italic> signaling are unclear. Rapidly adapting (RA) mechanoreceptors in dorsal root ganglia (DRGs) express <italic>Ret</italic> and the co-receptor <italic>Gfr\u03b12</italic> and depend on <italic>Ret</italic> for survival and central projection growth. Here, we show that <italic>Ret</italic> and <italic>Gfr\u03b12</italic> null mice display comparable early central projection deficits, but <italic>Gfr\u03b12</italic> null RA mechanoreceptors recover later. Loss of <italic>Gfr\u03b11</italic>, the co-receptor implicated in activating RET <italic>in trans</italic>, causes no significant central projection or cell survival deficit, but <italic>Gfr\u03b11;Gfr\u03b12</italic> double nulls phenocopy <italic>Ret</italic> nulls. Finally, we demonstrate that GFR\u03b11 produced by neighboring DRG neurons activates RET in RA mechanoreceptors. Taken together, our results suggest that <italic>trans</italic> and <italic>cis</italic> RET signaling could function in the same developmental process and that the availability of both forms of activation likely enhances but not diversifies outcomes of RET signaling.</p>",
},
]
| 303.625
| 1,326
| 0.792096
| 361
| 2,429
| 5.3241
| 0.277008
| 0.037461
| 0.027055
| 0.032778
| 0.736733
| 0.668054
| 0.640999
| 0.559834
| 0.559834
| 0.49948
| 0
| 0.026807
| 0.139975
| 2,429
| 7
| 1,327
| 347
| 0.89325
| 0
| 0
| 0
| 0
| 0.285714
| 0.967888
| 0.096336
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
5871c92a8c31f58780367e72dd645d194490519d
| 266
|
py
|
Python
|
HalleyComet/bit/models.py
|
ryanduan/Halley_Comet
|
bd3263e4575c820dd14c265c2c0d4b6b44197682
|
[
"Apache-2.0"
] | null | null | null |
HalleyComet/bit/models.py
|
ryanduan/Halley_Comet
|
bd3263e4575c820dd14c265c2c0d4b6b44197682
|
[
"Apache-2.0"
] | null | null | null |
HalleyComet/bit/models.py
|
ryanduan/Halley_Comet
|
bd3263e4575c820dd14c265c2c0d4b6b44197682
|
[
"Apache-2.0"
] | null | null | null |
from django.db import models
class Url(models.Model):
long_url = models.CharField(max_length=200)
short_url = models.CharField(max_length=100)
visit_time = models.DateTimeField(auto_now_add=True)
def __unicode__(self):
return self.long_url
| 26.6
| 56
| 0.740602
| 38
| 266
| 4.868421
| 0.684211
| 0.145946
| 0.194595
| 0.227027
| 0.291892
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027149
| 0.169173
| 266
| 9
| 57
| 29.555556
| 0.809955
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.142857
| 0.142857
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
587a404ecb9909eff07171e4499fcb5702d3abd5
| 78
|
py
|
Python
|
samples/ast/test.py
|
Ryoich/python_zero
|
fe4a5fd8b11c8c059d82b797cd1668f96d54e541
|
[
"CC-BY-4.0"
] | 203
|
2018-12-14T10:16:33.000Z
|
2022-03-10T07:23:34.000Z
|
samples/ast/test.py
|
Ryoich/python_zero
|
fe4a5fd8b11c8c059d82b797cd1668f96d54e541
|
[
"CC-BY-4.0"
] | 39
|
2019-06-21T12:28:03.000Z
|
2022-01-17T10:41:53.000Z
|
samples/ast/test.py
|
Ryoich/python_zero
|
fe4a5fd8b11c8c059d82b797cd1668f96d54e541
|
[
"CC-BY-4.0"
] | 29
|
2018-12-30T06:48:59.000Z
|
2022-03-10T07:43:42.000Z
|
def func(a, b):
return a + b
def func2(a):
print(a)
print("Hello")
| 8.666667
| 16
| 0.538462
| 14
| 78
| 3
| 0.571429
| 0.095238
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017857
| 0.282051
| 78
| 8
| 17
| 9.75
| 0.732143
| 0
| 0
| 0
| 0
| 0
| 0.064103
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0
| 0.2
| 0.6
| 0.4
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
545268aad6cd438a8b86741579655c5f5b28ba41
| 249
|
py
|
Python
|
test/test_i18n.py
|
timgates42/uliweb
|
80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1
|
[
"BSD-2-Clause"
] | 202
|
2015-01-12T08:10:48.000Z
|
2021-11-08T09:04:32.000Z
|
test/test_i18n.py
|
timgates42/uliweb
|
80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1
|
[
"BSD-2-Clause"
] | 30
|
2015-01-01T09:07:17.000Z
|
2021-06-03T12:58:45.000Z
|
test/test_i18n.py
|
timgates42/uliweb
|
80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1
|
[
"BSD-2-Clause"
] | 58
|
2015-01-12T03:28:54.000Z
|
2022-01-14T01:58:08.000Z
|
from uliweb.i18n import ugettext_lazy as _
def test_1():
"""
>>> x = _('Hello')
>>> print repr(x)
ugettext_lazy('Hello')
"""
def test_1():
"""
>>> x = _('Hello {0}')
>>> print x.format('name')
Hello name
"""
| 16.6
| 42
| 0.48996
| 30
| 249
| 3.833333
| 0.566667
| 0.208696
| 0.13913
| 0.156522
| 0.243478
| 0
| 0
| 0
| 0
| 0
| 0
| 0.028409
| 0.293173
| 249
| 15
| 43
| 16.6
| 0.625
| 0.481928
| 0
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.666667
| true
| 0
| 0.333333
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
54607def7c2c2dd5026968fee33155a24a8770a7
| 155
|
py
|
Python
|
satyrus/sat/types/__init__.py
|
lucasvg/Satyrus3-FinalProject-EspTopsOTM
|
024785752abdc46e3463d8c94df7c3da873c354d
|
[
"MIT"
] | null | null | null |
satyrus/sat/types/__init__.py
|
lucasvg/Satyrus3-FinalProject-EspTopsOTM
|
024785752abdc46e3463d8c94df7c3da873c354d
|
[
"MIT"
] | null | null | null |
satyrus/sat/types/__init__.py
|
lucasvg/Satyrus3-FinalProject-EspTopsOTM
|
024785752abdc46e3463d8c94df7c3da873c354d
|
[
"MIT"
] | null | null | null |
from .array import Array
from .string import String
from .problem import Constraint, Loop
from .main import SatType, Var, Number
from .expr import Expr
| 31
| 39
| 0.780645
| 23
| 155
| 5.26087
| 0.521739
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.167742
| 155
| 5
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0
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547f16545ac590cbce83d8fc70ff6fbb32f028e2
| 16,628
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py
|
Python
|
code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py
|
factset/enterprise-sdk
|
3fd4d1360756c515c9737a0c9a992c7451d7de7e
|
[
"Apache-2.0"
] | 6
|
2022-02-07T16:34:18.000Z
|
2022-03-30T08:04:57.000Z
|
code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py
|
factset/enterprise-sdk
|
3fd4d1360756c515c9737a0c9a992c7451d7de7e
|
[
"Apache-2.0"
] | 2
|
2022-02-07T05:25:57.000Z
|
2022-03-07T14:18:04.000Z
|
code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py
|
factset/enterprise-sdk
|
3fd4d1360756c515c9737a0c9a992c7451d7de7e
|
[
"Apache-2.0"
] | null | null | null |
"""
FactSet Funds API
FactSet Mutual Funds data offers over 50 fund- and share class-specific data points for mutual funds listed in the United States. <p>FactSet Mutual Funds Reference provides fund-specific reference information as well as FactSet's proprietary classification system. It includes but is not limited to the following coverage * Fund descriptions * A seven-tier classification system * Leverage information * Fees and expenses * Portfolio managers FactSet Mutual Funds Time Series provides quantitative data items on a historical basis. It includes but is not limited to the following coverage * Net asset value * Fund flows * Assets under management * Total return # noqa: E501
The version of the OpenAPI document: 1.0.0
Contact: [email protected]
Generated by: https://openapi-generator.tech
"""
import re # noqa: F401
import sys # noqa: F401
from fds.sdk.FactSetFunds.model_utils import ( # noqa: F401
ApiTypeError,
ModelComposed,
ModelNormal,
ModelSimple,
cached_property,
change_keys_js_to_python,
convert_js_args_to_python_args,
date,
datetime,
file_type,
none_type,
validate_get_composed_info,
OpenApiModel
)
from fds.sdk.FactSetFunds.exceptions import ApiAttributeError
class Classifications(ModelNormal):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
Attributes:
allowed_values (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
with a capitalized key describing the allowed value and an allowed
value. These dicts store the allowed enum values.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
discriminator_value_class_map (dict): A dict to go from the discriminator
variable value to the discriminator class name.
validations (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
that stores validations for max_length, min_length, max_items,
min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum,
inclusive_minimum, and regex.
additional_properties_type (tuple): A tuple of classes accepted
as additional properties values.
"""
allowed_values = {
}
validations = {
}
@cached_property
def additional_properties_type():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
"""
return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501
_nullable = False
@cached_property
def openapi_types():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
"""
return {
'fsym_id': (str,), # noqa: E501
'request_id': (str,), # noqa: E501
'asset_class': (str,), # noqa: E501
'category_class': (str,), # noqa: E501
'economic_development_class': (str,), # noqa: E501
'focus_class': (str,), # noqa: E501
'geographic_class': (str,), # noqa: E501
'niche_class': (str,), # noqa: E501
'region_class': (str,), # noqa: E501
}
@cached_property
def discriminator():
return None
attribute_map = {
'fsym_id': 'fsymId', # noqa: E501
'request_id': 'requestId', # noqa: E501
'asset_class': 'assetClass', # noqa: E501
'category_class': 'categoryClass', # noqa: E501
'economic_development_class': 'economicDevelopmentClass', # noqa: E501
'focus_class': 'focusClass', # noqa: E501
'geographic_class': 'geographicClass', # noqa: E501
'niche_class': 'nicheClass', # noqa: E501
'region_class': 'regionClass', # noqa: E501
}
read_only_vars = {
}
_composed_schemas = {}
@classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs): # noqa: E501
"""Classifications - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
fsym_id (str): FactSet Security Identifier. Six alpha-numeric characters, excluding vowels, with a -S suffix (XXXXXX-S), resolved from the requestId of the Fund requested.. [optional] # noqa: E501
request_id (str): The requested Id sent as input.. [optional] # noqa: E501
asset_class (str): Returns the asset class description from FactSet's fund classification system. Asset class designates the fund's underlying holding type, e.g. equity, fixed-income, etc.. [optional] # noqa: E501
category_class (str): Returns the asset class category description from FactSet's fund classification system. The asset class category is the first-tier subcategory within the fund's asset class, e.g. size & style, sector, precious metals, etc.. [optional] # noqa: E501
economic_development_class (str): Returns the fund's economic development description from FactSet's fund classification system. This description refers to the development level for the fund's geographic region of focus, e.g. developed, emerging, etc.. [optional] # noqa: E501
focus_class (str): Returns the fund's focus description from FactSet's fund classification system. The fund's focus is the second-tier subcategory within the fund's asset class, e.g. small cap, energy, etc.. [optional] # noqa: E501
geographic_class (str): Returns the fund's specific geography description from FactSet's fund classification system. Specific geography refers to the fund's particular geographic focus within the region, e.g. Chile, BRICs, etc.. [optional] # noqa: E501
niche_class (str): Returns the fund's niche description from FactSet's fund classification system. The fund's niche is the third-tier subcategory with the fund's asset class, e.g. growth, coal, etc.. [optional] # noqa: E501
region_class (str): Returns the fund's region description from FactSet's fund classification system. Refers to the broad regional exposure of the fund's holdings, e.g. Latin America, Asia-Pacific, etc.. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
self = super(OpenApiModel, cls).__new__(cls)
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
return self
required_properties = set([
'_data_store',
'_check_type',
'_spec_property_naming',
'_path_to_item',
'_configuration',
'_visited_composed_classes',
])
@convert_js_args_to_python_args
def __init__(self, *args, **kwargs): # noqa: E501
"""Classifications - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
fsym_id (str): FactSet Security Identifier. Six alpha-numeric characters, excluding vowels, with a -S suffix (XXXXXX-S), resolved from the requestId of the Fund requested.. [optional] # noqa: E501
request_id (str): The requested Id sent as input.. [optional] # noqa: E501
asset_class (str): Returns the asset class description from FactSet's fund classification system. Asset class designates the fund's underlying holding type, e.g. equity, fixed-income, etc.. [optional] # noqa: E501
category_class (str): Returns the asset class category description from FactSet's fund classification system. The asset class category is the first-tier subcategory within the fund's asset class, e.g. size & style, sector, precious metals, etc.. [optional] # noqa: E501
economic_development_class (str): Returns the fund's economic development description from FactSet's fund classification system. This description refers to the development level for the fund's geographic region of focus, e.g. developed, emerging, etc.. [optional] # noqa: E501
focus_class (str): Returns the fund's focus description from FactSet's fund classification system. The fund's focus is the second-tier subcategory within the fund's asset class, e.g. small cap, energy, etc.. [optional] # noqa: E501
geographic_class (str): Returns the fund's specific geography description from FactSet's fund classification system. Specific geography refers to the fund's particular geographic focus within the region, e.g. Chile, BRICs, etc.. [optional] # noqa: E501
niche_class (str): Returns the fund's niche description from FactSet's fund classification system. The fund's niche is the third-tier subcategory with the fund's asset class, e.g. growth, coal, etc.. [optional] # noqa: E501
region_class (str): Returns the fund's region description from FactSet's fund classification system. Refers to the broad regional exposure of the fund's holdings, e.g. Latin America, Asia-Pacific, etc.. [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
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| 0.011829
| 0.318739
| 16,628
| 288
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| 57.736111
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| 0.44186
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| 0.173398
| 0.041553
| 0
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| 1
| 0.03876
| false
| 0.015504
| 0.031008
| 0.007752
| 0.162791
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| 0
|
0
| 5
|
49b0052d2675e4f9dc69452f3b5d084691e4a664
| 19,202
|
py
|
Python
|
tests/tests/test_api_management.py
|
MaciejTe/useradm
|
4962000db94bc7d9e80b81c4389f6f769d0d062a
|
[
"Apache-2.0"
] | 8
|
2017-02-27T08:58:08.000Z
|
2020-05-25T14:37:24.000Z
|
tests/tests/test_api_management.py
|
MaciejTe/useradm
|
4962000db94bc7d9e80b81c4389f6f769d0d062a
|
[
"Apache-2.0"
] | 263
|
2016-11-17T15:02:26.000Z
|
2022-03-31T10:04:09.000Z
|
tests/tests/test_api_management.py
|
MaciejTe/useradm
|
4962000db94bc7d9e80b81c4389f6f769d0d062a
|
[
"Apache-2.0"
] | 25
|
2016-11-16T15:45:38.000Z
|
2020-12-19T09:56:16.000Z
|
#!/usr/bin/python
# Copyright 2021 Northern.tech AS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from common import (
init_users,
init_users_f,
init_users_mt,
init_users_mt_f,
cli,
api_client_mgmt,
mongo,
make_auth,
)
import bravado
import pytest
import tenantadm
class TestManagementApiPostUsersBase:
def _do_test_ok(self, api_client_mgmt, init_users, new_user, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
_, r = api_client_mgmt.create_user(new_user, auth)
assert r.status_code == 201
users = api_client_mgmt.get_users(auth)
assert len(users) == len(init_users) + 1
found_user = [u for u in users if u.email == new_user["email"]]
assert len(found_user) == 1
found_user = found_user[0]
def _do_test_fail_unprocessable_entity(
self, api_client_mgmt, init_users, new_user, tenant_id=None
):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
try:
api_client_mgmt.create_user(new_user, auth)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 422
class TestManagementApiPostUsers(TestManagementApiPostUsersBase):
def test_ok(self, api_client_mgmt, init_users):
new_user = {"email": "[email protected]", "password": "asdf1234zxcv"}
self._do_test_ok(api_client_mgmt, init_users, new_user)
def test_fail_malformed_body(self, api_client_mgmt):
new_user = {"foo": "bar"}
try:
api_client_mgmt.create_user(new_user)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
def test_fail_no_password(self, api_client_mgmt):
new_user = {"email": "foobar"}
try:
api_client_mgmt.create_user(new_user)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
def test_fail_no_email(self, api_client_mgmt):
new_user = {"password": "asdf1234zxcv"}
try:
api_client_mgmt.create_user(new_user)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
def test_fail_not_an_email(self, api_client_mgmt):
new_user = {"email": "foobar", "password": "asdf1234zxcv"}
try:
api_client_mgmt.create_user(new_user)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
def test_fail_pwd_too_short(self, api_client_mgmt):
new_user = {"email": "[email protected]", "password": "asdf"}
try:
api_client_mgmt.create_user(new_user)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 422
def test_fail_duplicate_email(self, api_client_mgmt, init_users):
new_user = {"email": "[email protected]", "password": "asdf"}
self._do_test_fail_unprocessable_entity(api_client_mgmt, init_users, new_user)
class TestManagementApiPostUsersEnterprise(TestManagementApiPostUsersBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok(self, tenant_id, api_client_mgmt, init_users_mt):
new_user = {"email": "[email protected]", "password": "asdf1234zxcv"}
with tenantadm.run_fake_create_user(new_user):
self._do_test_ok(
api_client_mgmt, init_users_mt[tenant_id], new_user, tenant_id
)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_fail_duplicate_email(self, tenant_id, api_client_mgmt, init_users_mt):
new_user = {"email": "[email protected]", "password": "asdf1234zxcv"}
with tenantadm.run_fake_create_user(new_user, 422):
self._do_test_fail_unprocessable_entity(
api_client_mgmt, init_users_mt[tenant_id], new_user, tenant_id
)
class TestManagementApiGetUserBase:
def _do_test_ok(self, api_client_mgmt, init_users, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
for u in init_users:
found = api_client_mgmt.get_user(u.id, auth)
assert found.id == u.id
assert found.email == u.email
assert found.created_ts == u.created_ts
assert found.updated_ts == u.updated_ts
def _do_test_fail_not_found(self, api_client_mgmt, init_users, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
try:
not_found = api_client_mgmt.get_user("madeupid", auth)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 404
class TestManagementApiGetUser(TestManagementApiGetUserBase):
def test_ok(self, api_client_mgmt, init_users):
self._do_test_ok(api_client_mgmt, init_users)
def test_fail_not_found(self, api_client_mgmt, init_users):
self._do_test_fail_not_found(api_client_mgmt, init_users)
class TestManagementApiGetUserEnterprise(TestManagementApiGetUserBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok(self, tenant_id, api_client_mgmt, init_users_mt):
self._do_test_ok(api_client_mgmt, init_users_mt[tenant_id], tenant_id)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_fail_not_found(self, tenant_id, api_client_mgmt, init_users_mt):
self._do_test_fail_not_found(
api_client_mgmt, init_users_mt[tenant_id], tenant_id
)
class TestManagementApiGetUsersBase:
def _do_test_ok(self, api_client_mgmt, init_users, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
users = api_client_mgmt.get_users(auth)
assert len(users) == len(init_users)
def _do_test_no_users(self, api_client_mgmt, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
users = api_client_mgmt.get_users(auth)
assert len(users) == 0
class TestManagementApiGetUsersOk(TestManagementApiGetUsersBase):
def test_ok(self, api_client_mgmt, init_users):
self._do_test_ok(api_client_mgmt, init_users)
class TestManagementApiGetUsersNoUsers(TestManagementApiGetUsersBase):
def test_no_users(self, api_client_mgmt):
self._do_test_no_users(api_client_mgmt)
class TestManagementApiGetUsersEnterprise(TestManagementApiGetUsersBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok(self, tenant_id, api_client_mgmt, init_users_mt):
self._do_test_ok(api_client_mgmt, init_users_mt[tenant_id], tenant_id)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_no_users(self, tenant_id, api_client_mgmt, init_users_mt):
self._do_test_no_users(api_client_mgmt, "non_existing_tenant_id")
class TestManagementApiDeleteUserBase:
def _do_test_ok(self, api_client_mgmt, init_users, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
rsp = api_client_mgmt.delete_user(init_users[0]["id"], auth)
assert rsp.status_code == 204
users = api_client_mgmt.get_users(auth)
assert len(users) == len(init_users) - 1
found = [u for u in users if u.id == init_users[0]["id"]]
assert len(found) == 0
def _do_test_not_found(self, api_client_mgmt, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
rsp = api_client_mgmt.delete_user("nonexistent_id", auth)
assert rsp.status_code == 204
class TestManagementApiDeleteUser(TestManagementApiDeleteUserBase):
def test_ok(self, api_client_mgmt, init_users):
self._do_test_ok(api_client_mgmt, init_users)
def test_not_found(self, api_client_mgmt, init_users):
self._do_test_not_found(api_client_mgmt)
class TestManagementApiDeleteUserEnterprise(TestManagementApiDeleteUserBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok(self, tenant_id, api_client_mgmt, init_users_mt):
with tenantadm.run_fake_delete_user(
tenant_id, init_users_mt[tenant_id][0]["id"]
):
self._do_test_ok(api_client_mgmt, init_users_mt[tenant_id], tenant_id)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_not_found(self, tenant_id, api_client_mgmt):
with tenantadm.run_fake_delete_user():
self._do_test_not_found(api_client_mgmt, tenant_id)
class TestManagementApiPutUserBase:
def _do_test_ok_email(
self, api_client_mgmt, init_users, user, update, tenant_id=None
):
_, r = api_client_mgmt.login(user.email, "correcthorsebatterystaple")
assert r.status_code == 200
token = r.text
auth = {"Authorization": "Bearer " + token}
# test update
_, r = api_client_mgmt.update_user(user.id, update, auth)
assert r.status_code == 204
# get/verify users
users = api_client_mgmt.get_users(auth)
assert len(users) == len(init_users)
found = [u for u in users if u.email == update["email"]]
assert len(found) == 1
def _do_test_ok_email_or_pass(
self, api_client_mgmt, init_users, user, update, tenant_id=None
):
_, r = api_client_mgmt.login(user.email, "correcthorsebatterystaple")
assert r.status_code == 200
token = r.text
auth = {"Authorization": "Bearer " + token}
# test update
_, r = api_client_mgmt.update_user(user.id, update, auth)
assert r.status_code == 204
# get/verify users
users = api_client_mgmt.get_users(auth)
assert len(users) == len(init_users)
# find the user via (new?) email
email = user.email
new_email = update.get("email", None)
if new_email != None and new_email != user.email:
email = new_email
found = [u for u in users if u.email == email]
assert len(found) == 1
# try if login still works
_, r = api_client_mgmt.login(email, update["password"])
assert r.status_code == 200
def _do_test_fail_not_found(
self, api_client_mgmt, init_users, update, tenant_id=None
):
_, r = api_client_mgmt.login(init_users[0].email, "correcthorsebatterystaple")
assert r.status_code == 200
token = r.text
auth = {"Authorization": "Bearer " + token}
try:
_, r = api_client_mgmt.update_user("madeupid", update, auth)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 404
def _do_test_fail_bad_update(self, api_client_mgmt, init_users, tenant_id=None):
try:
_, r = api_client_mgmt.update_user(init_users[0].id, {"foo": "bar"})
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
def _do_test_fail_unprocessable_entity(
self, api_client_mgmt, init_users, user, update, tenant_id=None
):
_, r = api_client_mgmt.login(user.email, "correcthorsebatterystaple")
assert r.status_code == 200
token = r.text
auth = {"Authorization": "Bearer " + token}
try:
_, r = api_client_mgmt.update_user(user.id, update, auth)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 422
class TestManagementApiPutUser(TestManagementApiPutUserBase):
def test_ok_email(self, api_client_mgmt, init_users_f):
update = {"email": "[email protected]"}
self._do_test_ok_email(api_client_mgmt, init_users_f, init_users_f[0], update)
def test_ok_pass(self, api_client_mgmt, init_users_f):
update = {
"current_password": "correcthorsebatterystaple",
"password": "secretpassword123",
}
self._do_test_ok_email_or_pass(
api_client_mgmt, init_users_f, init_users_f[0], update
)
def test_ok_email_and_pass(self, api_client_mgmt, init_users_f):
update = {
"email": "[email protected]",
"current_password": "correcthorsebatterystaple",
"password": "secretpassword123",
}
self._do_test_ok_email_or_pass(
api_client_mgmt, init_users_f, init_users_f[0], update
)
def test_fail_password_mismatch(self, api_client_mgmt, init_users_f):
update = {"current_password": "dummy", "password": "secretpassword123"}
self._do_test_fail_unprocessable_entity(
api_client_mgmt, init_users_f, init_users_f[0], update
)
def test_fail_not_found(self, api_client_mgmt, init_users_f):
update = {"email": "[email protected]", "password": "secretpassword123"}
self._do_test_fail_not_found(api_client_mgmt, init_users_f, update)
def test_fail_bad_update(self, api_client_mgmt, init_users_f):
self._do_test_fail_bad_update(api_client_mgmt, init_users_f)
def test_fail_duplicate_email(self, api_client_mgmt, init_users_f):
update = {"email": init_users_f[1].email, "password": "secretpassword123"}
self._do_test_fail_unprocessable_entity(
api_client_mgmt, init_users_f, init_users_f[0], update
)
class TestManagementApiPutUserEnterprise(TestManagementApiPutUserBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok_email(self, api_client_mgmt, init_users_mt_f, tenant_id):
user = init_users_mt_f[tenant_id][0]
update = {"email": "[email protected]"}
with tenantadm.run_fake_update_user(tenant_id, user.id, update):
self._do_test_ok_email(
api_client_mgmt, init_users_mt_f[tenant_id], user, update, tenant_id
)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok_pass(self, api_client_mgmt, init_users_mt_f, tenant_id):
user = init_users_mt_f[tenant_id][1]
with tenantadm.run_fake_get_tenants(tenant_id):
update = {
"password": "secretpassword123",
"current_password": "correcthorsebatterystaple",
}
self._do_test_ok_email_or_pass(
api_client_mgmt, init_users_mt_f[tenant_id], user, update, tenant_id
)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok_email_and_pass(self, api_client_mgmt, init_users_mt_f, tenant_id):
user = init_users_mt_f[tenant_id][2]
update = {
"email": "[email protected]",
"current_password": "correcthorsebatterystaple",
"password": "secretpassword123",
}
with tenantadm.run_fake_update_user(tenant_id, user.id, update):
self._do_test_ok_email_or_pass(
api_client_mgmt, init_users_mt_f[tenant_id], user, update, tenant_id
)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_fail_not_found(self, api_client_mgmt, init_users_mt_f, tenant_id):
user = init_users_mt_f[tenant_id][3]
update = {
"email": "[email protected]",
"current_password": "correcthorsebatterystaple",
"password": "secretpassword123",
}
with tenantadm.run_fake_update_user(tenant_id, user.id, update, 404):
self._do_test_fail_not_found(
api_client_mgmt, init_users_mt_f[tenant_id], update, tenant_id
)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_fail_bad_update(self, api_client_mgmt, init_users_mt_f, tenant_id):
self._do_test_fail_bad_update(api_client_mgmt, init_users_mt_f[tenant_id])
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_fail_duplicate_email(self, api_client_mgmt, init_users_mt_f, tenant_id):
user = init_users_mt_f[tenant_id][0]
update = {
"email": init_users_mt_f[tenant_id][1].email,
"password": "secretpassword123",
}
with tenantadm.run_fake_update_user(tenant_id, user.id, update, 422):
self._do_test_fail_unprocessable_entity(
api_client_mgmt, init_users_mt_f[tenant_id], user, update, tenant_id
)
class TestManagementApiSettingsBase:
def _do_test_ok(self, api_client_mgmt, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
# nonempty
self._set_and_verify(
{"foo": "foo-val", "bar": "bar-val"}, api_client_mgmt, auth
)
# empty
self._set_and_verify({}, api_client_mgmt, auth)
def _do_test_no_settings(self, api_client_mgmt, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
found = api_client_mgmt.get_settings(auth)
assert found.json() == {}
def _set_and_verify(self, settings, api_client_mgmt, auth):
r = api_client_mgmt.post_settings(settings, auth)
assert r.status_code == 201
found = api_client_mgmt.get_settings(auth)
assert found.json() == settings
def _do_test_fail_bad_request(self, api_client_mgmt, tenant_id=None):
auth = None
if tenant_id is not None:
auth = make_auth("foo", tenant_id)
try:
r = api_client_mgmt.post_settings("asdf", auth)
except bravado.exception.HTTPError as e:
assert e.response.status_code == 400
class TestManagementApiSettings(TestManagementApiSettingsBase):
def test_ok(self, api_client_mgmt):
self._do_test_ok(api_client_mgmt)
def test_no_settings(self, api_client_mgmt):
self._do_test_no_settings(api_client_mgmt)
def test_bad_request(self, api_client_mgmt):
self._do_test_fail_bad_request(api_client_mgmt)
class TestManagementApiSettingsEnterprise(TestManagementApiSettingsBase):
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_ok(self, api_client_mgmt, init_users_mt_f, tenant_id):
self._do_test_ok(api_client_mgmt, tenant_id)
@pytest.mark.parametrize("tenant_id", ["tenant1id", "tenant2id"])
def test_bad_request(self, api_client_mgmt, tenant_id):
self._do_test_fail_bad_request(api_client_mgmt, tenant_id)
| 38.327345
| 86
| 0.672638
| 2,538
| 19,202
| 4.701734
| 0.078014
| 0.093522
| 0.135088
| 0.091176
| 0.797871
| 0.775916
| 0.752367
| 0.727646
| 0.685243
| 0.664628
| 0
| 0.012778
| 0.229716
| 19,202
| 500
| 87
| 38.404
| 0.793996
| 0.037809
| 0
| 0.541333
| 0
| 0
| 0.085564
| 0.015986
| 0
| 0
| 0
| 0
| 0.101333
| 1
| 0.149333
| false
| 0.088
| 0.010667
| 0
| 0.210667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
49b03158777693b6348d205c910ad771b55e53ea
| 1,167
|
py
|
Python
|
scripts/convert_to_bed.py
|
Lila14/multimds
|
e54642e0ae47592321352f931f534881ca57d888
|
[
"MIT"
] | 1
|
2019-10-29T12:33:57.000Z
|
2019-10-29T12:33:57.000Z
|
scripts/convert_to_bed.py
|
Lila14/multimds
|
e54642e0ae47592321352f931f534881ca57d888
|
[
"MIT"
] | null | null | null |
scripts/convert_to_bed.py
|
Lila14/multimds
|
e54642e0ae47592321352f931f534881ca57d888
|
[
"MIT"
] | null | null | null |
import os
chrom_bins = {}
with open("GSE88952_Sc_Su.32000.bed") as in_file:
for line in in_file:
line = line.strip().split()
chrom_bins[line[3]] = "{}\t{}\t{}".format(line[0], line[1], line[2])
in_file.close()
if not os.path.isfile("ctrl_32kb.bed"):
with open("ctrl_32kb.bed", "w") as out_file:
with open("ctrl_32kb_matrix.txt") as in_file:
for line in in_file:
line = line.strip().split()
bin1 = line[0]
chrom_string1 = chrom_bins[bin1]
bin2 = line[1]
chrom_string2 = chrom_bins[bin2]
if float(line[3]) != 0:
out_file.write("\t".join((chrom_string1, chrom_string2, line[3])))
out_file.write("\n")
in_file.close()
out_file.close()
if not os.path.isfile("galactose_32kb.bed"):
with open("galactose_32kb.bed", "w") as out_file:
with open("galactose_32kb_matrix.txt") as in_file:
for line in in_file:
line = line.strip().split()
bin1 = line[0]
chrom_string1 = chrom_bins[bin1]
bin2 = line[1]
chrom_string2 = chrom_bins[bin2]
if float(line[3]) != 0:
out_file.write("\t".join((chrom_string1, chrom_string2, line[3])))
out_file.write("\n")
in_file.close()
out_file.close()
| 29.175
| 71
| 0.652956
| 193
| 1,167
| 3.735751
| 0.227979
| 0.074896
| 0.094313
| 0.04577
| 0.787795
| 0.787795
| 0.787795
| 0.728155
| 0.658807
| 0.658807
| 0
| 0.053998
| 0.174807
| 1,167
| 39
| 72
| 29.923077
| 0.694704
| 0
| 0
| 0.714286
| 0
| 0
| 0.129392
| 0.041988
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.028571
| 0
| 0.028571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
49bc8549c7944e60a8f4b2d3ccdc16b4d5329c4f
| 890
|
py
|
Python
|
SwitchTracer/universal/exceptions/__init__.py
|
IzayoiRin/VirtualVeyonST
|
d0c4035dba81d02135ad54f4c5a5d463e95f7925
|
[
"MIT"
] | null | null | null |
SwitchTracer/universal/exceptions/__init__.py
|
IzayoiRin/VirtualVeyonST
|
d0c4035dba81d02135ad54f4c5a5d463e95f7925
|
[
"MIT"
] | null | null | null |
SwitchTracer/universal/exceptions/__init__.py
|
IzayoiRin/VirtualVeyonST
|
d0c4035dba81d02135ad54f4c5a5d463e95f7925
|
[
"MIT"
] | null | null | null |
class UniErrors(Exception):
pass
class SetupErrors(UniErrors):
pass
class SettingErrors(UniErrors):
pass
class ConfigureSyntaxErrors(UniErrors):
pass
class NoLocationErrors(UniErrors):
pass
class ImportedErrors(UniErrors):
pass
class KernelWaresSettingsErrors(UniErrors):
pass
class RegisterErrors(UniErrors):
pass
class ResoluterErrors(UniErrors):
pass
class VolumeErrors(UniErrors):
pass
class ConnectionErrors(UniErrors):
pass
class RedisOperationErrors(UniErrors):
pass
class SerializerSettingErrors(UniErrors):
pass
class SerializerValidationErrors(UniErrors):
pass
class ParserSettingErrors(UniErrors):
pass
class ContentTypeErrors(UniErrors):
pass
class IllegalParametersErrors(UniErrors):
pass
class CodingErrors(UniErrors):
pass
class AppRuntimeErrors(UniErrors):
pass
| 11.866667
| 44
| 0.746067
| 76
| 890
| 8.736842
| 0.289474
| 0.243976
| 0.460843
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.189888
| 890
| 74
| 45
| 12.027027
| 0.920943
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0.026316
| 0
| 0.526316
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
49ee2e293e1b411f588dd752ab4762901a62db20
| 7,801
|
py
|
Python
|
src/tools/nuscenes-devkit/prediction/tests/test_mtp_loss.py
|
jie311/TraDeS
|
896491a159abe65f61c6ad05662cda6e28d137a6
|
[
"MIT"
] | 475
|
2021-03-13T16:33:36.000Z
|
2022-03-30T06:00:39.000Z
|
src/tools/nuscenes-devkit/prediction/tests/test_mtp_loss.py
|
jie311/TraDeS
|
896491a159abe65f61c6ad05662cda6e28d137a6
|
[
"MIT"
] | 50
|
2021-03-17T04:48:20.000Z
|
2022-03-08T13:55:32.000Z
|
src/tools/nuscenes-devkit/prediction/tests/test_mtp_loss.py
|
jie311/TraDeS
|
896491a159abe65f61c6ad05662cda6e28d137a6
|
[
"MIT"
] | 98
|
2021-03-14T12:12:49.000Z
|
2022-03-19T16:19:13.000Z
|
import math
import unittest
import torch
from nuscenes.prediction.models import mtp
class TestMTPLoss(unittest.TestCase):
"""
Test each component of MTPLoss as well as the
__call__ method.
"""
def test_get_trajectories_and_modes(self):
loss_n_modes_5 = mtp.MTPLoss(5, 0, 0)
loss_n_modes_1 = mtp.MTPLoss(1, 0, 0)
xy_pred = torch.arange(60).view(1, -1).repeat(1, 5).view(-1, 60)
mode_pred = torch.arange(5).view(1, -1)
prediction_bs_1 = torch.cat([xy_pred.reshape(1, -1), mode_pred], dim=1)
prediction_bs_2 = prediction_bs_1.repeat(2, 1)
# Testing many modes with batch size 1.
traj, modes = loss_n_modes_5._get_trajectory_and_modes(prediction_bs_1)
self.assertTrue(torch.allclose(traj, xy_pred.unsqueeze(0).reshape(1, 5, 30, 2)))
self.assertTrue(torch.allclose(modes, mode_pred))
# Testing many modes with batch size > 1.
traj, modes = loss_n_modes_5._get_trajectory_and_modes(prediction_bs_2)
self.assertTrue(torch.allclose(traj, xy_pred.repeat(1, 2).unsqueeze(0).reshape(2, 5, 30, 2)))
self.assertTrue(torch.allclose(modes, mode_pred.repeat(2, 1)))
xy_pred = torch.arange(60).view(1, -1).repeat(1, 1).view(-1, 60)
mode_pred = torch.arange(1).view(1, -1)
prediction_bs_1 = torch.cat([xy_pred.reshape(1, -1), mode_pred], dim=1)
prediction_bs_2 = prediction_bs_1.repeat(2, 1)
# Testing one mode with batch size 1.
traj, modes = loss_n_modes_1._get_trajectory_and_modes(prediction_bs_1)
self.assertTrue(torch.allclose(traj, xy_pred.unsqueeze(0).reshape(1, 1, 30, 2)))
self.assertTrue(torch.allclose(modes, mode_pred))
# Testing one mode with batch size > 1.
traj, modes = loss_n_modes_1._get_trajectory_and_modes(prediction_bs_2)
self.assertTrue(torch.allclose(traj, xy_pred.repeat(1, 2).unsqueeze(0).reshape(2, 1, 30, 2)))
self.assertTrue(torch.allclose(modes, mode_pred.repeat(2, 1)))
def test_angle_between_trajectories(self):
def make_trajectory(last_point):
traj = torch.zeros((12, 2))
traj[-1] = torch.Tensor(last_point)
return traj
loss = mtp.MTPLoss(0, 0, 0)
# test angle is 0.
self.assertEqual(loss._angle_between(make_trajectory([0, 0]), make_trajectory([0, 0])), 0.)
self.assertEqual(loss._angle_between(make_trajectory([15, 15]), make_trajectory([15, 15])), 0.)
# test angle is 15.
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 1]),
make_trajectory([math.sqrt(3)/2, 0.5])), 15., places=4)
# test angle is 30.
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 0]),
make_trajectory([math.sqrt(3)/2, 0.5])), 30., places=4)
# test angle is 45.
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 1]),
make_trajectory([0, 1])), 45., places=4)
# test angle is 90.
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 1]),
make_trajectory([-1, 1])), 90., places=4)
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 0]),
make_trajectory([0, 1])), 90., places=4)
# test angle is 180.
self.assertAlmostEqual(loss._angle_between(make_trajectory([1, 0]),
make_trajectory([-1, 0])), 180., places=4)
self.assertAlmostEqual(loss._angle_between(make_trajectory([0, 1]),
make_trajectory([0, -1])), 180., places=4)
self.assertAlmostEqual(loss._angle_between(make_trajectory([3, 1]),
make_trajectory([-3, -1])), 180., places=4)
def test_compute_best_mode_nothing_below_threshold(self):
angles = [(90, 0), (80, 1), (70, 2)]
target = None
traj = None
loss = mtp.MTPLoss(3, 0, 5)
self.assertTrue(loss._compute_best_mode(angles, target, traj) in {0, 1, 2})
loss = mtp.MTPLoss(3, 0, 65)
self.assertTrue(loss._compute_best_mode(angles, target, traj) in {0, 1, 2})
def test_compute_best_mode_only_one_below_threshold(self):
angles = [(30, 1), (3, 0), (25, 2)]
target = torch.ones((1, 6, 2))
trajectory = torch.zeros((3, 6, 2))
loss = mtp.MTPLoss(3, 0, 5)
self.assertEqual(loss._compute_best_mode(angles, target, trajectory), 0)
def test_compute_best_mode_multiple_below_threshold(self):
angles = [(2, 2), (4, 1), (10, 0)]
target = torch.ones((1, 6, 2))
trajectory = torch.zeros((3, 6, 2))
trajectory[1] = 1
loss = mtp.MTPLoss(3, 0, 5)
self.assertEqual(loss._compute_best_mode(angles, target, trajectory), 1)
def test_compute_best_mode_only_one_mode(self):
angles = [(25, 0)]
target = torch.ones((1, 6, 2))
trajectory = torch.zeros((1, 6, 2))
loss = mtp.MTPLoss(1, 0, 5)
self.assertEqual(loss._compute_best_mode(angles, target, trajectory), 0)
trajectory[0] = 1
self.assertEqual(loss._compute_best_mode(angles, target, trajectory), 0)
def test_loss_single_mode(self):
targets = torch.zeros((16, 1, 30, 2))
targets[:, :, :, 1] = torch.arange(start=0, end=3, step=0.1)
predictions = torch.ones((16, 61))
predictions[:, :60] = targets[0, 0, :, :].reshape(-1, 60)
predictions[:, 60] = 1/10
loss = mtp.MTPLoss(1, 1, angle_threshold_degrees=20)
# Only regression loss in single mode case.
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()),
0, places=4)
# Now the best mode differs by 1 from the ground truth.
# Smooth l1 loss subtracts 0.5 from l1 norm if diff >= 1.
predictions[:, :60] += 1
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()), 0.5,
places=4)
# In this case, one element has perfect regression, the others are off by 1.
predictions[1, :60] -= 1
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()),
(15/16)*0.5,
places=4)
def test_loss_many_modes(self):
targets = torch.zeros((16, 1, 30, 2))
targets[:, :, :, 1] = torch.arange(start=0, end=3, step=0.1)
predictions = torch.ones((16, 610))
predictions[:, 540:600] = targets[0, 0, :, :].reshape(-1, 60)
predictions[:, -10:] = 1/10
loss = mtp.MTPLoss(10, 1, angle_threshold_degrees=20)
# Since one mode exactly matches gt, loss should only be classification error.
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()),
-math.log(1/10), places=4)
# Now the best mode differs by 1 from the ground truth.
# Smooth l1 loss subtracts 0.5 from l1 norm if diff >= 1.
predictions[:, 540:600] += 1
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()),
-math.log(1/10) + 0.5,
places=4)
# In this case, one element has perfect regression, the others are off by 1.
predictions[1, 540:600] -= 1
self.assertAlmostEqual(float(loss(predictions, targets).detach().numpy()),
-math.log(1/10) + (15/16)*0.5,
places=4)
| 42.396739
| 106
| 0.58313
| 1,034
| 7,801
| 4.22824
| 0.135397
| 0.067246
| 0.036597
| 0.045746
| 0.810156
| 0.758463
| 0.748399
| 0.705627
| 0.679094
| 0.663769
| 0
| 0.071326
| 0.282912
| 7,801
| 183
| 107
| 42.628415
| 0.710225
| 0.104089
| 0
| 0.350877
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.263158
| 1
| 0.078947
| false
| 0
| 0.035088
| 0
| 0.131579
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 0
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|
0
| 5
|
3f978f4cb297bf98d9722f54f27227c0fe655e28
| 120,882
|
py
|
Python
|
tests/parsers/test_pwscf.py
|
jgaff/pif-dft
|
0fcc136560973f0f99cd257108cdfbc497207e4f
|
[
"Apache-2.0"
] | null | null | null |
tests/parsers/test_pwscf.py
|
jgaff/pif-dft
|
0fcc136560973f0f99cd257108cdfbc497207e4f
|
[
"Apache-2.0"
] | null | null | null |
tests/parsers/test_pwscf.py
|
jgaff/pif-dft
|
0fcc136560973f0f99cd257108cdfbc497207e4f
|
[
"Apache-2.0"
] | null | null | null |
import unittest
from dfttopif.parsers.pwscf import PwscfParser
from ..test_pif import unpack_example, delete_example
from pypif.obj.common.value import Value
import os
import shutil
class TestPWSCFParser(unittest.TestCase):
def get_parser(self,name):
'''Get a PwscfParser for a certain test'''
unpack_example(os.path.join('examples', 'pwscf', name+'.tar.gz'))
return PwscfParser.generate_from_directory(name)
def test_Au_nscf(self):
"""Test that a NSCF calculation is even parseable"""
# Parse the results
parser = self.get_parser('Au.nscf')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
def test_NaF(self):
# Parse the results
parser = self.get_parser('NaF.scf')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
strc = parser.get_output_structure()
self.assertEquals(2.2713025676424632, strc.cell[0][2])
self.assertEquals(['F', 'Na'], strc.get_chemical_symbols())
self.assertEquals('FNa', parser.get_composition())
# Test the density
self.assertAlmostEqual(2.975233747, parser.get_density().scalars[0].value)
self.assertEqual("g/(cm^3)", parser.get_density().units)
cutoff = parser.get_cutoff_energy()
self.assertEquals(50.0, cutoff.scalars[0].value)
self.assertEquals('Ry', cutoff.units)
self.assertTrue(parser.is_converged().scalars[0].value)
energy = parser.get_total_energy()
self.assertEquals(-143.96084355, energy.scalars[0].value)
self.assertEquals('Ry', energy.units)
self.assertEquals(-83.49879681, parser.get_one_electron_energy_contribution().scalars[0].value)
self.assertEquals(48.83409529, parser.get_hartree_energy_contribution().scalars[0].value)
self.assertEquals(-23.86775310, parser.get_xc_energy_contribution().scalars[0].value)
self.assertEquals(-85.42838893, parser.get_ewald_energy_contribution().scalars[0].value)
self.assertEquals(None, parser.uses_SOC())
self.assertEquals(None, parser.is_relaxed())
self.assertEquals('SLA PW PBE PBE', parser.get_xc_functional().scalars[0].value)
self.assertEquals(['f_pbe_v1.4.uspp.F.UPF','Na_pbe_v1.uspp.F.UPF'], list(map(lambda x: x.value, parser.get_pp_name().scalars)))
self.assertEquals(3456, parser.get_KPPRA().scalars[0].value)
self.assertEquals('5.4.0', parser.get_version_number())
self.assertEquals(None, parser.get_U_settings())
self.assertEquals(None, parser.get_vdW_settings())
self.assertEquals(None, parser.get_pressure())
self.assertEquals(None, parser.get_stresses())
self.assertEquals(None, parser.get_band_gap())
self.assertEquals(None, parser.get_dos())
# Delete the data
delete_example('NaF.scf')
def test_TiO2(self):
# Parse the results
parser = self.get_parser('TiO2.vcrelax')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
strc = parser.get_output_structure()
self.assertEquals(3.7373367889445048, strc.cell[0][0])
self.assertEquals(['Ti', 'Ti', 'Ti', 'Ti', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O'], strc.get_chemical_symbols())
self.assertEquals('O8Ti4', parser.get_composition())
cutoff = parser.get_cutoff_energy()
self.assertEquals(50.0, cutoff.scalars[0].value)
self.assertEquals('Ry', cutoff.units)
self.assertTrue(parser.is_converged().scalars[0].value)
energy = parser.get_total_energy()
self.assertAlmostEqual(-724.67999404, energy.scalars[0].value)
self.assertEquals('Ry', energy.units)
self.assertEquals(None, parser.uses_SOC())
self.assertTrue(isinstance(parser.is_relaxed(), Value))
self.assertEquals('SLA PZ NOGX NOGC', parser.get_xc_functional().scalars[0].value)
self.assertEquals(['Ti.pz-sp-van_ak.UPF', 'O.pz-van_ak.UPF'], list(map(lambda x: x.value, parser.get_pp_name().scalars)))
self.assertEquals(4800, parser.get_KPPRA().scalars[0].value)
self.assertEquals('4.3.2', parser.get_version_number())
self.assertEquals(None, parser.get_U_settings())
self.assertEquals(None, parser.get_vdW_settings())
pressure = parser.get_pressure()
self.assertEquals(-2.34, pressure.scalars[0].value)
self.assertEquals('kbar', pressure.units)
stresses = parser.get_stresses()
self.assertEquals([[-2.32, 0.0, 0.0], [0.0, -2.32, 0.0], [0.0, 0.0, -2.36]],
list(map(lambda x: list(map(lambda y: y.value, x)), stresses.matrices[0])))
self.assertEquals('kbar', stresses.units)
self.assertEquals(None, parser.get_band_gap())
self.assertAlmostEqual(0.000141, parser.get_total_force().scalars[0].value)
self.assertAlmostEqual(0.00005032, parser.get_forces().vectors[11][2].value)
# Test energy contribution terms (from the end of the calculation)
self.assertAlmostEqual(-317.64355286, parser.get_one_electron_energy_contribution().scalars[0].value)
self.assertAlmostEqual(200.00443558, parser.get_hartree_energy_contribution().scalars[0].value)
self.assertAlmostEqual(-112.62810014, parser.get_xc_energy_contribution().scalars[0].value)
self.assertAlmostEqual(-494.41277661, parser.get_ewald_energy_contribution().scalars[0].value)
# Delete the data
delete_example('TiO2.vcrelax')
def test_VS2(self):
# Parse the results
parser = self.get_parser('VS2.scf')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
strc = parser.get_output_structure()
self.assertEquals(1.5862881841690908, strc.cell[0][0])
self.assertEquals(2.7475322138658069, strc.cell[1][1])
self.assertEquals(39.999449897411992, strc.cell[2][2])
self.assertEquals(['V', 'S', 'S'], strc.get_chemical_symbols())
self.assertEquals('S2V', parser.get_composition())
cutoff = parser.get_cutoff_energy()
self.assertEquals(56.0, cutoff.scalars[0].value)
self.assertEquals('Ry', cutoff.units)
self.assertTrue(parser.is_converged().scalars[0].value)
energy = parser.get_total_energy()
self.assertEquals(-68.80612326, energy.scalars[0].value)
self.assertEquals('Ry', energy.units)
self.assertEquals(None, parser.uses_SOC())
self.assertEquals(None, parser.is_relaxed())
self.assertEquals('SLA PW PBE PBE', parser.get_xc_functional().scalars[0].value)
self.assertEquals(['V.pbe-n-van.UPF', 'S.pbe-van_bm.UPF'], list(map(lambda x: x.value, parser.get_pp_name().scalars)))
self.assertEquals(768, parser.get_KPPRA().scalars[0].value)
self.assertEquals('4.3.2', parser.get_version_number())
self.assertEquals(None, parser.get_U_settings())
self.assertEquals(None, parser.get_vdW_settings())
self.assertEquals(None, parser.get_pressure())
self.assertEquals(None, parser.get_stresses())
self.assertEquals(0, parser.get_band_gap().scalars[0].value)
dos = parser.get_dos()
self.assertEquals([-14.3248, -14.3198, -14.314799999999998, -14.3098, -14.3048, -14.299800000000001, -14.294799999999999, -14.2898, -14.2848, -14.279799999999998, -14.274799999999999, -14.2698, -14.264800000000001, -14.259799999999998, -14.2548, -14.2498, -14.244799999999998, -14.239799999999999, -14.2348, -14.229800000000001, -14.224799999999998, -14.2198, -14.2148, -14.209800000000001, -14.204799999999999, -14.1998, -14.1948, -14.189799999999998, -14.1848, -14.1798, -14.174800000000001, -14.169799999999999, -14.1648, -14.1598, -14.154799999999998, -14.149799999999999, -14.1448, -14.139800000000001, -14.134799999999998, -14.1298, -14.1248, -14.119799999999998, -14.114799999999999, -14.1098, -14.104800000000001, -14.099799999999998, -14.0948, -14.0898, -14.084800000000001, -14.079799999999999, -14.0748, -14.0698, -14.064799999999998, -14.0598, -14.0548, -14.049800000000001, -14.044799999999999, -14.0398, -14.0348, -14.029799999999998, -14.024799999999999, -14.0198, -14.014800000000001, -14.009799999999998, -14.0048, -13.9998, -13.994799999999998, -13.989799999999999, -13.9848, -13.979800000000001, -13.974799999999998, -13.9698, -13.9648, -13.959800000000001, -13.954799999999999, -13.9498, -13.9448, -13.939799999999998, -13.9348, -13.9298, -13.924800000000001, -13.919799999999999, -13.9148, -13.9098, -13.904799999999998, -13.899799999999999, -13.8948, -13.889800000000001, -13.884799999999998, -13.8798, -13.8748, -13.869799999999998, -13.864799999999999, -13.8598, -13.854800000000001, -13.849799999999998, -13.8448, -13.8398, -13.834800000000001, -13.829799999999999, -13.8248, -13.8198, -13.814799999999998, -13.8098, -13.8048, -13.799800000000001, -13.794799999999999, -13.7898, -13.7848, -13.779799999999998, -13.774799999999999, -13.7698, -13.764800000000001, -13.759799999999998, -13.7548, -13.7498, -13.744799999999998, -13.739799999999999, -13.7348, -13.729800000000001, -13.724799999999998, -13.7198, -13.7148, -13.709800000000001, -13.704799999999999, -13.6998, -13.6948, -13.689799999999998, -13.6848, -13.6798, -13.674800000000001, -13.669799999999999, -13.6648, -13.6598, -13.654799999999998, -13.649799999999999, -13.6448, -13.639800000000001, -13.634799999999998, -13.6298, -13.6248, -13.619799999999998, -13.614799999999999, -13.6098, -13.604800000000001, -13.599799999999998, -13.5948, -13.5898, -13.584800000000001, -13.579799999999999, -13.5748, -13.5698, -13.564799999999998, -13.5598, -13.5548, -13.549800000000001, -13.544799999999999, -13.5398, -13.5348, -13.529799999999998, -13.524799999999999, -13.5198, -13.514800000000001, -13.509799999999998, -13.5048, -13.4998, -13.494799999999998, -13.489799999999999, -13.4848, -13.479800000000001, -13.474799999999998, -13.4698, -13.4648, -13.459800000000001, -13.454799999999999, -13.4498, -13.4448, -13.439799999999998, -13.4348, -13.4298, -13.424800000000001, -13.419799999999999, -13.4148, -13.4098, -13.404799999999998, -13.399799999999999, -13.3948, -13.389800000000001, -13.384799999999998, -13.3798, -13.3748, -13.369799999999998, -13.364799999999999, -13.3598, -13.354800000000001, -13.349799999999998, -13.3448, -13.3398, -13.334800000000001, -13.329799999999999, -13.3248, -13.3198, -13.314799999999998, -13.3098, -13.3048, -13.299800000000001, -13.294799999999999, -13.2898, -13.2848, -13.279799999999998, -13.274799999999999, -13.2698, -13.264800000000001, -13.259799999999998, -13.2548, -13.2498, -13.244799999999998, -13.239799999999999, -13.2348, -13.229800000000001, -13.224799999999998, -13.2198, -13.2148, -13.209800000000001, -13.204799999999999, -13.1998, -13.1948, -13.189799999999998, -13.1848, -13.1798, -13.174800000000001, -13.169799999999999, -13.1648, -13.1598, -13.154799999999998, -13.149799999999999, -13.1448, -13.139800000000001, -13.134799999999998, -13.1298, -13.1248, -13.119799999999998, -13.114799999999999, -13.1098, -13.104800000000001, -13.099799999999998, -13.0948, -13.0898, -13.084800000000001, -13.079799999999999, -13.0748, -13.0698, -13.064799999999998, -13.0598, -13.0548, -13.049800000000001, -13.044799999999999, -13.0398, -13.0348, -13.029799999999998, -13.024799999999999, -13.0198, -13.014800000000001, -13.009799999999998, -13.0048, -12.9998, -12.994799999999998, -12.989799999999999, -12.9848, -12.979800000000001, -12.974799999999998, -12.9698, -12.9648, -12.959800000000001, -12.954799999999999, -12.9498, -12.9448, -12.939799999999998, -12.9348, -12.9298, -12.924800000000001, -12.919799999999999, -12.9148, -12.9098, -12.904799999999998, -12.899799999999999, -12.8948, -12.889800000000001, -12.884799999999998, -12.8798, -12.8748, -12.869799999999998, -12.864799999999999, -12.8598, -12.854800000000001, -12.849799999999998, -12.8448, -12.8398, -12.834800000000001, -12.829799999999999, -12.8248, -12.8198, -12.814799999999998, -12.8098, -12.8048, -12.799800000000001, -12.794799999999999, -12.7898, -12.7848, -12.779799999999998, -12.774799999999999, -12.7698, -12.764800000000001, -12.759799999999998, -12.7548, -12.7498, -12.744799999999998, -12.739799999999999, -12.7348, -12.729800000000001, -12.724799999999998, -12.7198, -12.7148, -12.709800000000001, -12.704799999999999, -12.6998, -12.6948, -12.689799999999998, -12.6848, -12.6798, -12.674800000000001, -12.669799999999999, -12.6648, -12.6598, -12.654799999999998, -12.649799999999999, -12.6448, -12.639800000000001, -12.634799999999998, -12.6298, -12.6248, -12.619799999999998, -12.614799999999999, -12.6098, -12.604800000000001, -12.599799999999998, -12.5948, -12.5898, -12.584800000000001, -12.579799999999999, -12.5748, -12.5698, -12.564799999999998, -12.5598, -12.5548, -12.549800000000001, -12.544799999999999, -12.5398, -12.5348, -12.529799999999998, -12.524799999999999, -12.5198, -12.514800000000001, -12.509799999999998, -12.5048, -12.4998, -12.494799999999998, -12.489799999999999, -12.4848, -12.479800000000001, -12.474799999999998, -12.4698, -12.4648, -12.459800000000001, -12.454799999999999, -12.4498, -12.4448, -12.439799999999998, 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self.assertEquals([-4.957e-05, -8.501e-05, -0.0001428, -0.0002347, -0.0003778, -0.0005949, -0.0009164, -0.00138, -0.002032, -0.002921, -0.004097, -0.005601, -0.007451, -0.009628, -0.01205, -0.01455, -0.01686, -0.01856, -0.01913, -0.01787, -0.01402, -0.006742, 0.004777, 0.02122, 0.04303, 0.07032, 0.1028, 0.1397, 0.1798, 0.2217, 0.2637, 0.3041, 0.3417, 0.3754, 0.405, 0.4307, 0.4535, 0.4743, 0.4945, 0.5149, 0.536, 0.5575, 0.5781, 0.5962, 0.6094, 0.6155, 0.6125, 0.5994, 0.5763, 0.5447, 0.5074, 0.4682, 0.4316, 0.4025, 0.3849, 0.3817, 0.3946, 0.423, 0.4649, 0.5165, 0.5728, 0.6285, 0.6783, 0.7177, 0.7433, 0.7534, 0.7473, 0.7259, 0.6912, 0.6457, 0.5923, 0.5341, 0.4742, 0.4156, 0.3613, 0.3144, 0.2781, 0.2553, 0.2487, 0.2603, 0.2912, 0.3412, 0.4083, 0.4891, 0.5786, 0.6705, 0.758, 0.8342, 0.8928, 0.9293, 0.9407, 0.9267, 0.889, 0.8315, 0.7597, 0.68, 0.5986, 0.5214, 0.4528, 0.3957, 0.3512, 0.3189, 0.2974, 0.2847, 0.2787, 0.2781, 0.2822, 0.2912, 0.3061, 0.3283, 0.3593, 0.4, 0.4506, 0.5102, 0.5769, 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0.02285, -0.01946, -0.04335, -0.04704, -0.02897, 0.01207, 0.07668, 0.1646, 0.2741, 0.4023, 0.5445, 0.6943, 0.8441, 0.9854, 1.109, 1.208, 1.275, 1.305, 1.297, 1.25, 1.169, 1.06, 0.9299, 0.7873, 0.641, 0.4988, 0.3674, 0.2516, 0.1545, 0.07729, 0.01941, -0.02084, -0.04602, -0.05912, -0.06318, -0.06104, -0.05513, -0.04739, -0.03928, -0.03178, -0.02553, -0.02088, -0.01796, -0.01681, -0.01737, -0.01948, -0.0229, -0.02724, -0.03193, -0.03611, -0.03864, -0.03803, -0.03254, -0.02023, 0.0008609, 0.03244, 0.07569, 0.131, 0.1977, 0.2738, 0.356, 0.44, 0.5206, 0.5922, 0.6495, 0.6879, 0.7044, 0.6975, 0.6677, 0.6174, 0.5504, 0.4718, 0.3869, 0.301, 0.2188, 0.1439, 0.07879, 0.02484, -0.01761, -0.04891, -0.06969, -0.08063, -0.08208, -0.07399, -0.05585, -0.02682, 0.01406, 0.06754, 0.1338, 0.2123, 0.3012, 0.3977, 0.4979, 0.5971, 0.69, 0.7715, 0.8367, 0.882, 0.9049, 0.9043, 0.8808, 0.8364, 0.7742, 0.6982, 0.6129, 0.5227, 0.4319, 0.3442, 0.2628, 0.1897, 0.1265, 0.07369, 0.03123, -0.001444, -0.02522, -0.04114, -0.05019, -0.05319, -0.05069, -0.04294, -0.02991, -0.01145, 0.01264, 0.04237, 0.07739, 0.1169, 0.1594, 0.2031, 0.2454, 0.2838, 0.3156, 0.3384, 0.3505, 0.3509, 0.3396, 0.3176, 0.2866, 0.2489, 0.2072, 0.1641, 0.1221, 0.08303, 0.04831, 0.01865, -0.005761, -0.0251, -0.03974, -0.05001, -0.05602, -0.05751, -0.05375, -0.04361, -0.02563, 0.001723, 0.03982, 0.08947, 0.1507, 0.2223, 0.302, 0.3861, 0.4699, 0.548, 0.6151, 0.666, 0.6966, 0.7046, 0.6891, 0.6516, 0.5949, 0.5235, 0.4427, 0.358, 0.2747, 0.1973, 0.1292, 0.07248, 0.02814, -0.003917, -0.02454, -0.0351, -0.0372, -0.03248, -0.02249, -0.008625, 0.007888, 0.02594, 0.0445, 0.06259, 0.07925, 0.09359, 0.1048, 0.1124, 0.1158, 0.115, 0.1102, 0.102, 0.09092, 0.07801, 0.06416, 0.05029, 0.0372, 0.0255, 0.0156, 0.007694, 0.001772, -0.002319, -0.004839, -0.006102, -0.006431, -0.006129, -0.00545, -0.004594, -0.003706, -0.002877, -0.002158, -0.001568, -0.001106, -0.000758, -0.0005059, -0.0003289, -0.0002085, -0.000129, -7.784e-05],
list(map(lambda x: x.value, dos.scalars)))
# Delete the data
delete_example('VS2.scf')
def test_pw_vdw(self):
# Parse the results
parser = self.get_parser('pw_vdw')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
strc = parser.get_output_structure()
self.assertEquals(2.46596598034, strc.cell[0][0])
self.assertEquals(2.1355881881239482, strc.cell[1][1])
self.assertEquals(6.4115115488840004, strc.cell[2][2])
self.assertEquals(['C', 'C', 'C', 'C'], strc.get_chemical_symbols())
self.assertEquals('C4', parser.get_composition())
cutoff = parser.get_cutoff_energy()
self.assertEquals(45.0, cutoff.scalars[0].value)
self.assertEquals('Ry', cutoff.units)
self.assertTrue(parser.is_converged().scalars[0].value)
energy = parser.get_total_energy()
self.assertEquals(-44.61813252, energy.scalars[0].value)
self.assertEquals('Ry', energy.units)
self.assertEquals(None, parser.uses_SOC())
self.assertEquals(None, parser.is_relaxed())
self.assertEquals('SLA PW PBX PBC', parser.get_xc_functional().scalars[0].value)
self.assertEquals(['C.pbe-mt_gipaw.UPF'], list(map(lambda x: x.value, parser.get_pp_name().scalars)))
self.assertEquals(4, parser.get_KPPRA().scalars[0].value)
self.assertEquals('6.0', parser.get_version_number())
self.assertEquals(None, parser.get_U_settings())
self.assertEquals('Tkatchenko-Scheffler', parser.get_vdW_settings().scalars[0].value)
pressure = parser.get_pressure()
self.assertEquals(188.77, pressure.scalars[0].value)
self.assertEquals('kbar', pressure.units)
stresses = parser.get_stresses()
self.assertEquals([[185.91, -1.88, 0.0], [-1.88, 183.74, 0.0], [0.0, 0.0, 196.65]],
list(map(lambda x: list(map(lambda y: y.value, x)), stresses.matrices[0])))
self.assertEquals('kbar', stresses.units)
self.assertEquals(None, parser.get_band_gap())
# Delete the data
delete_example('pw_vdw')
def test_pw_ldaU(self):
# Parse the results
parser = self.get_parser('pw_lda+U')
# Test the settings
self.assertEquals('PWSCF', parser.get_name())
strc = parser.get_output_structure()
self.assertEquals(2.1669808346549999, strc.cell[0][0])
self.assertEquals(4.3339616693099998, strc.cell[1][1])
self.assertEquals(['O', 'O', 'Fe', 'Fe'], strc.get_chemical_symbols())
self.assertEquals('Fe2O2', parser.get_composition())
cutoff = parser.get_cutoff_energy()
self.assertEquals(30.0, cutoff.scalars[0].value)
self.assertEquals('Ry', cutoff.units)
self.assertTrue(parser.is_converged().scalars[0].value)
energy = parser.get_total_energy()
self.assertEquals(-174.47156021, energy.scalars[0].value)
self.assertEquals('Ry', energy.units)
self.assertEquals(None, parser.uses_SOC())
self.assertEquals(None, parser.is_relaxed())
self.assertEquals('SLA PZ NOGX NOGC', parser.get_xc_functional().scalars[0].value)
self.assertEquals(['O.pz-rrkjus.UPF', 'Fe.pz-nd-rrkjus.UPF', 'Fe.pz-nd-rrkjus.UPF'], list(map(lambda x: x.value, parser.get_pp_name().scalars)))
self.assertEquals(32, parser.get_KPPRA().scalars[0].value)
self.assertEquals('6.0', parser.get_version_number())
U_settings = parser.get_U_settings()
self.assertEquals('Simplified', U_settings.Type)
self.assertEquals({'Fe2': {'J': 0.0, 'U': 4.3, 'L': 2.0}, 'Fe1': {'J': 0.0, 'U': 4.3, 'L': 2.0}}, U_settings.Values)
self.assertEquals(None, parser.get_vdW_settings())
self.assertEquals(None, parser.get_pressure())
self.assertEquals(None, parser.get_stresses())
self.assertEquals(None, parser.get_band_gap())
# Delete the data
delete_example('pw_lda+U')
if __name__ == '__main__':
unittest.main()
| 470.357977
| 65,484
| 0.668983
| 22,823
| 120,882
| 3.533453
| 0.184507
| 0.019121
| 0.006287
| 0.006535
| 0.072305
| 0.069342
| 0.063216
| 0.05993
| 0.056768
| 0.051684
| 0
| 0.666697
| 0.101843
| 120,882
| 256
| 65,485
| 472.195313
| 0.076079
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| 0.004593
| 0.000174
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| 0.703911
| 1
| 0.039106
| false
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| 0.03352
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| 0
| 0
|
0
| 5
|
3fe105950fe7c097a0cf82f9fd41aa14438e8996
| 66
|
py
|
Python
|
qymel/core/__init__.py
|
hal1932/QyMEL
|
4fdf2409aaa34516f021a37aac0f011fe6ea6073
|
[
"MIT"
] | 6
|
2019-12-23T05:20:29.000Z
|
2021-01-30T21:17:32.000Z
|
qymel/core/__init__.py
|
hal1932/QyMEL
|
4fdf2409aaa34516f021a37aac0f011fe6ea6073
|
[
"MIT"
] | null | null | null |
qymel/core/__init__.py
|
hal1932/QyMEL
|
4fdf2409aaa34516f021a37aac0f011fe6ea6073
|
[
"MIT"
] | 1
|
2020-03-05T08:17:44.000Z
|
2020-03-05T08:17:44.000Z
|
# coding: utf-8
from .force_reload import *
from .scopes import *
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| 27
| 0.727273
| 10
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0
| 5
|
3fe5513bca482d43a59c15049895c9303427b971
| 85
|
py
|
Python
|
engines/__init__.py
|
mukeran/simple_sandbox
|
a2a97d13d814548f313871f0bd5c48f65b1a6180
|
[
"MIT"
] | null | null | null |
engines/__init__.py
|
mukeran/simple_sandbox
|
a2a97d13d814548f313871f0bd5c48f65b1a6180
|
[
"MIT"
] | null | null | null |
engines/__init__.py
|
mukeran/simple_sandbox
|
a2a97d13d814548f313871f0bd5c48f65b1a6180
|
[
"MIT"
] | null | null | null |
from .watcher import FileWatcher
from .fpm_sniffer import FPMSniffer, FPMSnifferMode
| 28.333333
| 51
| 0.858824
| 10
| 85
| 7.2
| 0.8
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0
| 5
|
3ff942a422edefd4743417af8a01150a5a71f98a
| 10,122
|
py
|
Python
|
scripts/create_fluseverity_figs_v2/export_zOR_classif_swap.py
|
eclee25/flu-SDI-exploratory-age
|
2f5a4d97b84d2116e179e85fe334edf4556aa946
|
[
"MIT"
] | 3
|
2018-03-29T23:02:43.000Z
|
2020-08-10T12:01:50.000Z
|
scripts/create_fluseverity_figs_v2/export_zOR_classif_swap.py
|
eclee25/flu-SDI-exploratory-age
|
2f5a4d97b84d2116e179e85fe334edf4556aa946
|
[
"MIT"
] | null | null | null |
scripts/create_fluseverity_figs_v2/export_zOR_classif_swap.py
|
eclee25/flu-SDI-exploratory-age
|
2f5a4d97b84d2116e179e85fe334edf4556aa946
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 10/14/14
###Function: Export zOR retrospective and early warning classifications into csv file format (SDI and ILINet, national and regional for SDI)
### Use nation-level peak-based retrospective classification for SDI region analysis
# 10/14/14 swap OR age groups
###Import data: R_export/OR_zip3_week_outpatient_cl.csv, R_export/allpopstat_zip3_season_cl.csv
#### These data were cleaned with data_extraction/clean_OR_hhsreg_week_outpatient.R and exported with OR_zip3_week.sql
#### allpopstat_zip3_season_cl.csv includes child, adult, and other populations; popstat_zip3_season_cl.csv includes only child and adult populations
###Command Line: python export_zOR_classif_swap.py
##############################################
### notes ###
# Incidence per 100,000 is normalized by total population by second calendar year of the flu season
### packages/modules ###
import csv
## local modules ##
import functions_v2 as fxn
### data structures ###
### called/local plotting parameters ###
nw = fxn.gp_normweeks # number of normalization weeks in baseline period
### functions ###
def print_dict_to_file(dic, filename):
with open(filename, 'w+') as fwriter:
fwriter.write("season,mn_retro,mn_early\n")
for key, value in dic.items():
fwriter.write("%s,%s,%s\n" % (key, value[0], value[1]))
def print_dict_to_file2(dic, filename):
with open(filename, 'w+') as fwriter:
fwriter.write("season,region,mn_retro,mn_early\n")
for key, value in dic.items():
fwriter.write("%s,%s,%s,%s\n" % (key[0], key[1], value[0], value[1]))
def print_dict_to_file3(dic, filename):
with open(filename, 'w+') as fwriter:
fwriter.write('season,state,mn_retro,mn_early\n')
for key, value in dic.items():
fwriter.write("%s,%s,%s,%s\n" % (key[0], key[1], value[0], value[1]))
##############################################
# SDI NATIONAL
# national files
incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/OR_allweeks_outpatient.csv','r')
incid = csv.reader(incidin, delimiter=',')
popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/totalpop_age.csv', 'r')
pop = csv.reader(popin, delimiter=',')
thanksin=open('/home/elee/Dropbox/My_Bansal_Lab/Clean_Data_for_Import/ThanksgivingWeekData_cl.csv', 'r')
thanksin.readline() # remove header
thanks=csv.reader(thanksin, delimiter=',')
# dict_wk[week] = seasonnum, dict_incid[week] = ILI cases per 10,000 in US population in second calendar year of flu season, dict_OR[week] = OR
d_wk, d_incid, d_OR = fxn.week_OR_processing(incid, pop)
d_zOR = fxn.week_zOR_processing(d_wk, d_OR)
# d_incid53ls[seasonnum] = [ILI wk 40 per 100000, ILI wk 41 per 100000,...], d_OR53ls[seasonnum] = [OR wk 40, OR wk 41, ...], d_zOR53ls[seasonnum] = [zOR wk 40, zOR wk 41, ...]
d_incid53ls, d_OR53ls, d_zOR53ls = fxn.week_plotting_dicts(d_wk, d_incid, d_OR, d_zOR)
# d_classifzOR[seasonnum] = (mean retrospective zOR, mean early warning zOR)
d_classifzOR = fxn.classif_zOR_processing(d_wk, d_incid53ls, d_zOR53ls, thanks)
# ##############################################
# # ILINet NATIONAL
# # national files
# incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/CDC_Source/Import_Data/all_cdc_source_data.csv','r')
# incidin.readline() # remove header
# incid = csv.reader(incidin, delimiter=',')
# popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/Census/Import_Data/totalpop_age_Census_98-14.csv', 'r')
# pop = csv.reader(popin, delimiter=',')
# thanksin=open('/home/elee/Dropbox/My_Bansal_Lab/Clean_Data_for_Import/ThanksgivingWeekData_cl.csv', 'r')
# thanksin.readline() # remove header
# thanks=csv.reader(thanksin, delimiter=',')
# # dict_wk[week] = seasonnum, dict_incid[week] = ILI cases per 10,000 in US population in second calendar year of flu season, dict_OR[week] = OR
# d_wk, d_incid, d_OR = fxn.ILINet_week_OR_processing(incid, pop)
# d_zOR = fxn.week_zOR_processing(d_wk, d_OR)
# # d_incid53ls[seasonnum] = [ILI wk 40 per 100000, ILI wk 41 per 100000,...], d_OR53ls[seasonnum] = [OR wk 40, OR wk 41, ...], d_zOR53ls[seasonnum] = [zOR wk 40, zOR wk 41, ...]
# d_incid53ls, d_OR53ls, d_zOR53ls = fxn.week_plotting_dicts(d_wk, d_incid, d_OR, d_zOR)
# # d_ILINet_classifzOR[seasonnum] = (mean retrospective zOR, mean early warning zOR)
# d_ILINet_classifzOR = fxn.classif_zOR_processing(d_wk, d_incid53ls, d_zOR53ls, thanks)
##############################################
# SDI REGION: region-level peak-basesd retrospective classification
# regional files
reg_incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/R_export/OR_zip3_week_outpatient_cl.csv', 'r')
reg_incidin.readline()
regincid = csv.reader(reg_incidin, delimiter=',')
reg_popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/R_export/allpopstat_zip3_season_cl.csv','r')
reg_popin.readline()
regpop = csv.reader(reg_popin, delimiter=',')
# national files
incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/OR_allweeks_outpatient.csv','r')
incid = csv.reader(incidin, delimiter=',')
popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/totalpop_age.csv', 'r')
pop = csv.reader(popin, delimiter=',')
thanksin=open('/home/elee/Dropbox/My_Bansal_Lab/Clean_Data_for_Import/ThanksgivingWeekData_cl.csv', 'r')
thanksin.readline() # remove header
thanks=csv.reader(thanksin, delimiter=',')
# dict_wk[week] = seasonnum, dict_incid[week] = ILI cases per 10,000 in US population in second calendar year of flu season, dict_OR[week] = OR
d_wk, d_incid, d_OR = fxn.week_OR_processing(incid, pop)
d_zOR = fxn.week_zOR_processing(d_wk, d_OR)
# d_incid53ls[seasonnum] = [ILI wk 40 per 100000, ILI wk 41 per 100000,...], d_OR53ls[seasonnum] = [OR wk 40, OR wk 41, ...], d_zOR53ls[seasonnum] = [zOR wk 40, zOR wk 41, ...]
d_incid53ls, d_OR53ls, d_zOR53ls = fxn.week_plotting_dicts(d_wk, d_incid, d_OR, d_zOR)
_, d_zip3_reg, d_incid_reg, d_OR_reg = fxn.week_OR_processing_region(regincid, regpop)
# dict_zOR_reg[(week, hhsreg)] = zOR
d_zOR_reg = fxn.week_zOR_processing_region(d_wk, d_OR_reg)
# dict_incid53ls_reg[(seasonnum, region)] = [ILI wk 40, ILI wk 41,...], dict_OR53ls_reg[(seasonnum, region)] = [OR wk 40, OR wk 41, ...], dict_zOR53ls_reg[(seasonnum, region)] = [zOR wk 40, zOR wk 41, ...]
d_incid53ls_reg, d_OR53ls_reg, d_zOR53ls_reg = fxn.week_plotting_dicts_region(d_wk, d_incid_reg, d_OR_reg, d_zOR_reg)
# dict_classifindex[seasonnum] = (index of first retro period week, index of first early warning period week)
d_classifindex = fxn.classif_zOR_index(d_wk, d_incid53ls, d_incid53ls_reg, 'region', thanks)
# d_classifzOR_reg[(seasonnum, region)] = (mean retrospective zOR, mean early warning zOR)
d_classifzOR_reg = fxn.classif_zOR_region_processing(d_classifindex, d_wk, d_zOR53ls_reg)
##############################################
# SDI STATE: state-level peak-basesd retrospective classification
# import same files as regional files
reg_incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/R_export/OR_zip3_week_outpatient_cl.csv', 'r')
reg_incidin.readline()
regincid = csv.reader(reg_incidin, delimiter=',')
reg_popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/R_export/allpopstat_zip3_season_cl.csv','r')
reg_popin.readline()
regpop = csv.reader(reg_popin, delimiter=',')
# national files
incidin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/OR_allweeks_outpatient.csv','r')
incid = csv.reader(incidin, delimiter=',')
popin = open('/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/SQL_export/totalpop_age.csv', 'r')
pop = csv.reader(popin, delimiter=',')
thanksin=open('/home/elee/Dropbox/My_Bansal_Lab/Clean_Data_for_Import/ThanksgivingWeekData_cl.csv', 'r')
thanksin.readline() # remove header
thanks=csv.reader(thanksin, delimiter=',')
# dict_wk[week] = seasonnum, dict_incid[week] = ILI cases per 10,000 in US population in second calendar year of flu season, dict_OR[week] = OR
d_wk, d_incid, d_OR = fxn.week_OR_processing(incid, pop)
d_zOR = fxn.week_zOR_processing(d_wk, d_OR)
# d_incid53ls[seasonnum] = [ILI wk 40 per 100000, ILI wk 41 per 100000,...], d_OR53ls[seasonnum] = [OR wk 40, OR wk 41, ...], d_zOR53ls[seasonnum] = [zOR wk 40, zOR wk 41, ...]
d_incid53ls, d_OR53ls, d_zOR53ls = fxn.week_plotting_dicts(d_wk, d_incid, d_OR, d_zOR)
_, d_zip3_reg, d_incid_state, d_OR_state = fxn.week_OR_processing_state(regincid, regpop)
# dict_zOR_state[(week, state)] = zOR
d_zOR_state = fxn.week_zOR_processing_state(d_wk, d_OR_state)
# dict_incid53ls_state[(seasonnum, state)] = [ILI wk 40, ILI wk 41,...], dict_OR53ls_reg[(seasonnum, state)] = [OR wk 40, OR wk 41, ...], dict_zOR53ls_state[(seasonnum, state)] = [zOR wk 40, zOR wk 41, ...]
d_incid53ls_state, d_OR53ls_state, d_zOR53ls_state = fxn.week_plotting_dicts_state(d_wk, d_incid_state, d_OR_state, d_zOR_state)
# dict_classifindex[seasonnum] = (index of first retro period week, index of first early warning period week)
d_classifindex = fxn.classif_zOR_index_state(d_wk, d_incid53ls, d_incid53ls_state, 'state', thanks)
# d_classifzOR_state[(seasonnum, state)] = (mean retrospective zOR, mean early warning zOR)
d_classifzOR_state = fxn.classif_zOR_state_processing(d_classifindex, d_wk, d_zOR53ls_state)
##############################################
print d_classifzOR
print d_classifzOR_reg
fn1 = '/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/Py_export/SDI_national_classifications_%s_swap.csv' %(nw)
print_dict_to_file(d_classifzOR, fn1)
# fn2 = '/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/Py_export/ILINet_national_classifications_%s_swap.csv' %(nw)
# print_dict_to_file(d_ILINet_classifzOR, fn2)
fn3 = '/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/Py_export/SDI_regional_classifications_%sreg_swap.csv' %(nw)
print_dict_to_file2(d_classifzOR_reg, fn3)
fn4 = '/home/elee/Dropbox/Elizabeth_Bansal_Lab/SDI_Data/explore/Py_export/SDI_state_classifications_%sst_swap.csv' %(nw)
print_dict_to_file3(d_classifzOR_state, fn4)
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0
| 5
|
b79b4b3441162b8ce9025428d639fcec36693cf3
| 42
|
py
|
Python
|
tests/__init__.py
|
chasefinch/amp-renderer
|
a226140d8a8a6f8c21c073e394b672cf75c8671e
|
[
"Apache-2.0"
] | 13
|
2020-08-19T18:37:01.000Z
|
2021-12-10T17:33:14.000Z
|
tests/__init__.py
|
chasefinch/amp-renderer
|
a226140d8a8a6f8c21c073e394b672cf75c8671e
|
[
"Apache-2.0"
] | 5
|
2020-08-24T18:31:12.000Z
|
2022-02-07T17:36:59.000Z
|
tests/__init__.py
|
chasefinch/amp-renderer
|
a226140d8a8a6f8c21c073e394b672cf75c8671e
|
[
"Apache-2.0"
] | null | null | null |
"""Tests for the AMP Renderer project."""
| 21
| 41
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0
| 5
|
b7a964ee74b74803fefa91500045e19a16c2244a
| 85,945
|
py
|
Python
|
regions.py
|
greggy/python-ipgeobase
|
593e4dc7e55e0c90a1979e586f03c013f6ac057a
|
[
"BSD-3-Clause"
] | 1
|
2017-11-12T11:26:25.000Z
|
2017-11-12T11:26:25.000Z
|
regions.py
|
greggy/python-ipgeobase
|
593e4dc7e55e0c90a1979e586f03c013f6ac057a
|
[
"BSD-3-Clause"
] | null | null | null |
regions.py
|
greggy/python-ipgeobase
|
593e4dc7e55e0c90a1979e586f03c013f6ac057a
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
REGIONS = {'USRI': 'Rhode Island', 'UY02': 'Canelones', 'KR21': 'Ulsan-gwangyoksi', 'KR20': 'Kyongsang-namdo', 'KM02': 'Grande Comore', 'KM03': 'Moheli', 'CO22': 'Putumayo', 'BN18': 'Zou', 'BN17': 'Plateau', 'BN16': 'Oueme', 'BN15': 'Tutong', 'BN14': 'Littoral', 'BN13': 'Donga', 'BN12': 'Kouffo', 'BN11': 'Collines', 'BN10': 'Temburong', 'KP09': 'Kangwon-do', 'KP08': 'Kaesong-si', 'KP07': 'Hwanghae-bukto', 'KP06': 'Hwanghae-namdo', 'KP01': 'Chagang-do', 'KP03': 'Hamgyong-namdo', 'IS40': 'Norourland Eystra', 'CO28': 'Tolima', 'TH77': 'Amnat Charoen', 'CO29': 'Valle del Cauca', 'TH76': 'Udon Thani', 'IS44': 'Vestfiroir', 'IS45': 'Vesturland', 'MK80': 'Plasnica', 'MK81': 'Podares', 'MK82': 'Prilep', 'MK83': 'Probistip', 'MK84': 'Radovis', 'MK85': 'Rankovce', 'MK86': 'Resen', 'MK87': 'Rosoman', 'MK88': 'Rostusa', 'MK89': 'Samokov', 'NG23': 'Kaduna', 'NG22': 'Cross River', 'SZ05': 'Praslin', 'SZ04': 'Shiselweni', 'SZ03': 'Manzini', 'SZ02': 'Lubombo', 'SZ01': 'Hhohho', 'NG26': 'Benue', 'BG41': 'Gabrovo', 'BG40': 'Dobrich', 'BG43': 'Khaskovo', 'BG42': 'Grad Sofiya', 'BG45': 'Kyustendil', 'BG44': 'Kurdzhali', 'BG47': 'Montana', 'BG46': 'Lovech', 'BG49': 'Pernik', 'BG48': 'Pazardzhik', 'NG24': 'Katsina', 'DO19': 'Salcedo', 'KH18': 'Svay Rieng', 'KH19': 'Takeo', 'KH12': 'Pursat', 'KH13': 'Preah Vihear', 'KH10': 'Mondulkiri', 'KH11': 'Phnum Penh', 'KH16': 'Siem Reap', 'KH17': 'Stung Treng', 'KH14': 'Prey Veng', 'KH15': 'Ratanakiri Kiri', 'GN15': 'Kerouane', 'GN16': 'Kindia', 'GN17': 'Kissidougou', 'GN10': 'Forecariah', 'GN11': 'Fria', 'GN12': 'Gaoual', 'GN13': 'Gueckedou', 'GN18': 'Koundara', 'GN19': 'Kouroussa', 'GBR1': 'Ballymoney', 'GBR3': 'Belfast', 'GBR2': 'Banbridge', 'GBR5': 'Castlereagh', 'GBR4': 'Carrickfergus', 'GBR7': 'Cookstown', 'GBR6': 'Coleraine', 'GBR9': 'Down', 'GBR8': 'Craigavon', 'CZ87': 'Plzensky kraj', 'CZ86': 'Pardubicky kraj', 'CZ85': 'Moravskoslezsky kraj', 'CZ84': 'Olomoucky kraj', 'CZ83': 'Liberecky kraj', 'CZ82': 'Kralovehradecky kraj', 'CZ81': 'Karlovarsky kraj', 'CZ80': 'Vysocina', 'CZ89': 'Ustecky kraj', 'CZ88': 'Stredocesky kraj', 'MD87': 'Soroca', 'MD86': 'Soldanesti', 'MD85': 'Singerei', 'MD84': 'Riscani', 'MD83': 'Rezina', 'MD81': 'Ocnita', 'MD80': 'Nisporeni', 'VN55': 'Binh Thuan', 'MD89': 'Straseni', 'MD88': 'Stefan-Voda', 'CN09': 'Henan', 'CN08': 'Heilongjiang', 'CN03': 'Jiangxi', 'CN02': 'Zhejiang', 'CN01': 'Anhui', 'CN07': 'Fujian', 'CN06': 'Qinghai', 'CN05': 'Jilin', 'CN04': 'Jiangsu', 'DE04': 'Hamburg', 'VN50': 'Vinh Phu', 'PE09': 'Huancavelica', 'PE08': 'Cusco', 'PE01': 'Amazonas', 'PE03': 'Apurimac', 'PE02': 'Ancash', 'PE05': 'Ayacucho', 'PE04': 'Arequipa', 'PE07': 'Callao', 'PE06': 'Cajamarca', 'AE02': 'Ajman', 'DE08': 'Rheinland-Pfalz', 'AE01': 'Abu Dhabi', 'AE06': 'Sharjah', 'AE07': 'Umm Al Quwain', 'GY19': 'Upper Takutu-Upper Essequibo', 'GY18': 'Upper Demerara-Berbice', 'AE04': 'Fujairah', 'AF08': 'Ghazni', 'GY13': 'East Berbice-Corentyne', 'GY12': 'Demerara-Mahaica', 'GY11': 'Cuyuni-Mazaruni', 'GY10': 'Barima-Waini', 'GY17': 'Potaro-Siparuni', 'GY16': 'Pomeroon-Supenaam', 'GY15': 'Mahaica-Berbice', 'GY14': 'Essequibo Islands-West Demerara', 'BI10': 'Bururi', 'BI11': 'Cankuzo', 'BI12': 'Cibitoke', 'BI13': 'Gitega', 'BI14': 'Karuzi', 'BI15': 'Kayanza', 'BI16': 'Kirundo', 'BI17': 'Makamba', 'BI18': 'Muyinga', 'BI19': 'Ngozi', 'IE02': 'Cavan', 'USSC': 'South Carolina', 'AF02': 'Badghis', 'USSD': 'South Dakota', 'IE06': 'Donegal', 'IE04': 'Cork', 'MK93': 'Sopotnica', 'MK92': 'Sopiste', 'MK91': 'Sipkovica', 'MK90': 'Saraj', 'MK97': 'Staro Nagoricane', 'MK96': 'Star Dojran', 'MK95': 'Staravina', 'MK94': 'Srbinovo', 'MK99': 'Struga', 'MK98': 'Stip', 'CD01': 'Bandundu', 'KG01': 'Bishkek', 'CD05': 'Katanga', 'CD04': 'Kasai-Oriental', 'CD06': 'Kinshasa', 'SD32': 'Bahr al Ghazal', 'LB02': 'Al Janub', 'LB03': 'Liban-Nord', 'LB01': 'Beqaa', 'LB06': 'Liban-Sud', 'LB07': 'Nabatiye', 'LB04': 'Beyrouth', 'LB05': 'Mont-Liban', 'LB08': 'Beqaa', 'LB09': 'Liban-Nord', 'KH05': 'Kampong Thum', 'KH04': 'Kampong Speu', 'KH07': 'Kandal', 'KH06': 'Kampot', 'KH01': 'Batdambang', 'KH03': 'Kampong Chhnang', 'KH02': 'Kampong Cham', 'KH09': 'Kracheh', 'KH08': 'Koh Kong', 'PT02': 'Aveiro', 'PT03': 'Beja', 'PT04': 'Braga', 'PT05': 'Braganca', 'PT06': 'Castelo Branco', 'PT07': 'Coimbra', 'PT08': 'Evora', 'PT09': 'Faro', 'GN07': 'Dinguiraye', 'GN06': 'Dalaba', 'GN05': 'Dabola', 'GN04': 'Conakry', 'GN03': 'Boke', 'GN02': 'Boffa', 'GN01': 'Beyla', 'GN09': 'Faranah', 'SI17': 'Crnomelj', 'SI16': 'Crna na Koroskem', 'SK06': 'Trencin', 'SK07': 'Trnava', 'SK04': 'Nitra', 'SK05': 'Presov', 'SK02': 'Bratislava', 'SK03': 'Kosice', 'SK01': 'Banska Bystrica', 'SK08': 'Zilina', 'GBW5': 'South Lanarkshire', 'MX27': 'Tabasco', 'CN32': 'Sichuan', 'CN33': 'Chongqing', 'CN30': 'Guangdong', 'CN31': 'Hainan', 'BH17': 'Al Janubiyah', 'VE18': 'Portuguesa', 'VE19': 'Sucre', 'VE11': 'Falcon', 'VE12': 'Guarico', 'VE13': 'Lara', 'VE14': 'Merida', 'VE15': 'Miranda', 'VE16': 'Monagas', 'VE17': 'Nueva Esparta', 'BH16': 'Al Asimah', 'NE07': 'Zinder', 'MX10': 'Durango', 'MX11': 'Guanajuato', 'MX12': 'Guerrero', 'MX13': 'Hidalgo', 'MX14': 'Jalisco', 'MX15': 'Mexico', 'MX16': 'Michoacan de Ocampo', 'MX17': 'Morelos', 'MX18': 'Nayarit', 'MX19': 'Nuevo Leon', 'DZ55': 'Tipaza', 'BI02': 'Bujumbura', 'BI09': 'Bubanza', 'CV10': 'Sao Nicolau', 'CV11': 'Sao Vicente', 'CV13': 'Mosteiros', 'CV14': 'Praia', 'CV15': 'Santa Catarina', 'CV16': 'Santa Cruz', 'CV17': 'Sao Domingos', 'CV18': 'Sao Filipe', 'CV19': 'Sao Miguel', 'PHB8': 'Cotabato', 'PHB9': 'Dagupan', 'PHB3': 'Calbayog', 'ER01': 'Anseba', 'ER03': "Debubawi K'eyih Bahri", 'ER02': 'Debub', 'ER05': "Ma'akel", 'ER04': 'Gash Barka', 'ER06': "Semenawi K'eyih Bahri", 'NE08': 'Niamey', 'TH80': 'Sa Kaeo', 'PHB5': 'Canlaon', 'TD08': 'Logone Occidental', 'TD09': 'Logone Oriental', 'TD04': 'Chari-Baguirmi', 'TD05': 'Guera', 'TD06': 'Kanem', 'TD07': 'Lac', 'TD01': 'Batha', 'TD02': 'Biltine', 'TD03': 'Borkou-Ennedi-Tibesti', 'LB11': 'Baalbek-Hermel', 'LB10': 'Aakk', 'PT13': 'Leiria', 'PT11': 'Guarda', 'PT10': 'Madeira', 'PT17': 'Porto', 'PT16': 'Portalegre', 'PT14': 'Lisboa', 'PT19': 'Setubal', 'PT18': 'Santarem', 'GN32': 'Kankan', 'GN33': 'Koubia', 'GN30': 'Coyah', 'GN31': 'Dubreka', 'GN36': 'Lola', 'GN37': 'Mandiana', 'GN34': 'Labe', 'GN35': 'Lelouma', 'GN38': 'Nzerekore', 'GN39': 'Siguiri', 'MW22': 'Salima', 'ES56': 'Catalonia', 'ES55': 'Castilla y Leon', 'JM14': 'Saint Thomas', 'ES54': 'Castilla-La Mancha', 'JP47': 'Okinawa', 'MW26': 'Balaka', 'JM16': 'Westmoreland', 'ES52': 'Aragon', 'CN21': 'Ningxia', 'CN20': 'Nei Mongol', 'CN23': 'Shanghai', 'CN22': 'Beijing', 'CN25': 'Shandong', 'CN24': 'Shanxi', 'CN26': 'Shaanxi', 'CN29': 'Yunnan', 'CN28': 'Tianjin', 'JM11': 'Saint Elizabeth', 'LT59': 'Marijampoles Apskritis', 'LT58': 'Klaipedos Apskritis', 'JM12': 'Saint James', 'VE03': 'Apure', 'VE02': 'Anzoategui', 'VE01': 'Amazonas', 'JP41': 'Tottori', 'LT57': 'Kauno Apskritis', 'LT56': 'Alytaus Apskritis', 'VE05': 'Barinas', 'VE04': 'Aragua', 'FRB2': 'Lorraine', 'FRB1': 'Limousin', 'VN54': 'Binh Dinh', 'FRB6': 'Picardie', 'FRB7': 'Poitou-Charentes', 'EC08': 'El Oro', 'EC09': 'Esmeraldas', 'FRB4': 'Nord-Pas-de-Calais', 'EC01': 'Galapagos', 'EC02': 'Azuay', 'EC03': 'Bolivar', 'EC04': 'Canar', 'EC05': 'Carchi', 'EC06': 'Chimborazo', 'EC07': 'Cotopaxi', 'MX03': 'Baja California Sur', 'MX02': 'Baja California', 'MX01': 'Aguascalientes', 'MX07': 'Coahuila de Zaragoza', 'MX06': 'Chihuahua', 'MX05': 'Chiapas', 'MX04': 'Campeche', 'CAPE': 'Prince Edward Island', 'MX09': 'Distrito Federal', 'MX08': 'Colima', 'SI66': 'Loski Potok', 'SI64': 'Logatec', 'ZM07': 'Southern', 'ZM06': 'North-Western', 'SI62': 'Ljubno', 'ZM05': 'Northern', 'PA06': 'Herrera', 'PA01': 'Bocas del Toro', 'UG90': 'Mukono', 'CV02': 'Brava', 'CV01': 'Boa Vista', 'KY08': 'Western', 'ZM01': 'Western', 'CV05': 'Paul', 'CV04': 'Maio', 'KY04': 'South Town', 'KY05': 'Spot Bay', 'KY06': 'Stake Bay', 'CV08': 'Sal', 'KY01': 'Creek', 'KY02': 'Eastern', 'KY03': 'Midland', 'US44': 'Rhode Island', 'MZ03': 'Inhambane', 'US47': 'Tennessee', 'US40': 'Oklahoma', 'US41': 'Oregon', 'US42': 'Pennsylvania', 'IQ08': 'Dahuk', 'IQ09': 'Dhi Qar', 'IQ06': 'Babil', 'IQ07': 'Baghdad', 'IQ04': 'Al Qadisiyah', 'IQ05': 'As Sulaymaniyah', 'IQ02': 'Al Basrah', 'LA14': 'Xiangkhoang', 'IQ01': 'Al Anbar', 'TD14': 'Tandjile', 'TD13': 'Salamat', 'TD12': 'Ouaddai', 'TD11': 'Moyen-Chari', 'TD10': 'Mayo-Kebbi', 'GT22': 'Zacapa', 'GT21': 'Totonicapan', 'GT20': 'Suchitepequez', 'GBA8': 'Blackburn with Darwen', 'GBA9': 'Blackpool', 'PT22': 'Viseu', 'PT23': 'Azores', 'PT20': 'Viana do Castelo', 'PT21': 'Vila Real', 'GN29': 'Yomou', 'GN28': 'Tougue', 'EE10': 'Parnu', 'GN25': 'Pita', 'GN27': 'Telimele', 'GN21': 'Macenta', 'GBA2': 'Barnet', 'GN23': 'Mamou', 'GN22': 'Mali', 'GR47': 'Dhodhekanisos', 'GBA3': 'Barnsley', 'GR46': 'Lasithi', 'GBA4': 'Bath and North East Somerset', 'GBA5': 'Bedfordshire', 'GR44': 'Rethimni', 'GBA6': 'Bexley', 'GBA7': 'Birmingham', 'AD08': 'Escaldes-Engordany', 'AD03': 'Encamp', 'AD02': 'Canillo', 'AD07': 'Andorra la Vella', 'AD06': 'Sant Julia de Loria', 'AD05': 'Ordino', 'AD04': 'La Massana', 'CG08': 'Plateaux', 'LY57': 'Gharyan', 'CG01': 'Bouenza', 'CG06': 'Likouala', 'CG07': 'Niari', 'CG04': 'Kouilou', 'CG05': 'Lekoumou', 'VN44': 'Dac Lac', 'VN45': 'Dong Nai', 'LT64': 'Utenos Apskritis', 'LT65': 'Vilniaus Apskritis', 'LT62': 'Taurages Apskritis', 'LT63': 'Telsiu Apskritis', 'LT60': 'Panevezio Apskritis', 'LT61': 'Siauliu Apskritis', 'VN49': 'Song Be', 'JP28': 'Nara', 'JP29': 'Niigata', 'JP24': 'Miyagi', 'JP25': 'Miyazaki', 'JP26': 'Nagano', 'JP27': 'Nagasaki', 'JP20': 'Kochi', 'JP21': 'Kumamoto', 'JP22': 'Kyoto', 'JP23': 'Mie', 'EC19': 'Tungurahua', 'EC18': 'Pichincha', 'EC13': 'Los Rios', 'EC12': 'Loja', 'EC11': 'Imbabura', 'EC10': 'Guayas', 'EC17': 'Pastaza', 'EC15': 'Morona-Santiago', 'EC14': 'Manabi', 'SI04': 'Bohinj', 'SI05': 'Borovnica', 'SI06': 'Bovec', 'SI07': 'Brda', 'SI01': 'Ajdovscina', 'SI02': 'Beltinci', 'SI03': 'Bled', 'MX32': 'Zacatecas', 'SI09': 'Brezovica', 'MX30': 'Veracruz-Llave', 'MX31': 'Yucatan', 'DO18': 'Puerto Plata', 'PHA9': 'Cabanatuan', 'PHA8': 'Butuan', 'PHA7': 'Batangas City', 'PHA6': 'Basilan City', 'PHA5': 'Bais', 'PHA4': 'Baguio', 'PHA3': 'Bago', 'PHA2': 'Bacolod', 'PHA1': 'Angeles', 'JP42': 'Toyama', 'BI21': 'Ruyigi', 'BI20': 'Rutana', 'BI23': 'Mwaro', 'BI22': 'Muramvya', 'PA10': 'Veraguas', 'MZ10': 'Manica', 'MZ11': 'Maputo', 'IQ18': 'Salah ad Din', 'PH29': 'Ilocos Sur', 'IQ11': 'Arbil', 'IQ10': 'Diyala', 'IQ13': "At Ta'mim", 'IQ12': "Karbala'", 'IQ15': 'Ninawa', 'IQ14': 'Maysan', 'IQ17': 'An Najaf', 'IQ16': 'Wasit', 'TJ02': 'Khatlon', 'TJ03': 'Sughd', 'TJ01': 'Kuhistoni Badakhshon', 'GT12': 'Peten', 'GT13': 'Quetzaltenango', 'GT10': 'Jalapa', 'GT11': 'Jutiapa', 'GT16': 'Sacatepequez', 'GT17': 'San Marcos', 'GT14': 'Quiche', 'GT15': 'Retalhuleu', 'GT18': 'Santa Rosa', 'GT19': 'Solola', 'PSWE': 'West Bank', 'PY23': 'Alto Paraguay', 'PY21': 'Nueva Asuncion', 'PY20': 'Chaco', 'QA06': 'Ar Rayyan', 'QA04': 'Al Khawr', 'QA05': 'Al Wakrah Municipality', 'QA02': 'Al Ghuwariyah', 'QA03': 'Al Jumaliyah', 'QA01': 'Ad Dawhah', 'QA08': 'Madinat ach Shamal', 'QA09': 'Umm Salal', 'GBU5': 'East Dunbartonshire', 'UY03': 'Cerro Largo', 'UY01': 'Artigas', 'UY06': 'Flores', 'UY07': 'Florida', 'UY04': 'Colonia', 'UY05': 'Durazno', 'UY08': 'Lavalleja', 'UY09': 'Maldonado', 'CH10': 'Inner-Rhoden', 'GBU6': 'East Lothian', 'CH11': 'Luzern', 'CG14': 'Cuvette-Ouest', 'CG11': 'Pool', 'CG10': 'Sangha', 'CG13': 'Cuvette', 'CG12': 'Brazzaville', 'UA24': "Volyns'ka Oblast'", 'UA25': "Zakarpats'ka Oblast'", 'UA26': "Zaporiz'ka Oblast'", 'UA27': "Zhytomyrs'ka Oblast'", 'UA20': "Sevastopol'", 'UA21': "Sums'ka Oblast'", 'UA22': "Ternopil's'ka Oblast'", 'UA23': "Vinnyts'ka Oblast'", 'IT20': 'Veneto', 'US11': 'District of Columbia', 'VE21': 'Trujillo', 'VE20': 'Tachira', 'VE23': 'Zulia', 'VE22': 'Yaracuy', 'VE25': 'Distrito Federal', 'VN52': 'Ho Chi Minh', 'VN51': 'Ha Noi', 'VE26': 'Vargas', 'VN59': 'Ha Tay', 'VN58': 'Ha Giang', 'LY62': 'Yafran', 'JP39': 'Tokushima', 'JP38': 'Tochigi', 'JP37': 'Shizuoka', 'JP36': 'Shimane', 'JP35': 'Shiga', 'JP34': 'Saitama', 'JP33': 'Saga', 'JP32': 'Osaka', 'JP31': 'Okayama', 'JP30': 'Oita', 'MX29': 'Tlaxcala', 'MX28': 'Tamaulipas', 'SI15': 'Crensovci', 'SI14': 'Cerkno', 'SI13': 'Cerknica', 'SI12': 'Cerklje na Gorenjskem', 'SI11': 'Celje', 'MX21': 'Puebla', 'MX20': 'Oaxaca', 'MX23': 'Quintana Roo', 'MX22': 'Queretaro de Arteaga', 'MX25': 'Sinaloa', 'MX24': 'San Luis Potosi', 'SI19': 'Divaca', 'MX26': 'Sonora', 'LY60': 'Surt', 'MD61': 'Basarabeasca', 'MD60': 'Balti', 'MD63': 'Briceni', 'KN10': 'Saint Paul Charlestown', 'KN11': 'Saint Peter Basseterre', 'KN12': 'Saint Thomas Lowland', 'MD62': 'Bender', 'KN15': 'Trinity Palmetto Point', 'PHB2': 'Cagayan de Oro', 'MD65': 'Cantemir', 'PHB1': 'Cadiz', 'PHB6': 'Cavite City', 'PHB7': 'Cebu City', 'PHB4': 'Caloocan', 'MD64': 'Cahul', 'CI75': 'Bafing', 'CI74': 'Agneby', 'CI77': 'Denguele', 'CI76': 'Bas-Sassandra', 'CI79': 'Fromager', 'CI78': 'Dix-Huit Montagnes', 'FRB5': 'Pays de la Loire', 'EC24': 'Orellana', 'EC22': 'Sucumbios', 'EC23': 'Napo', 'EC20': 'Zamora-Chinchipe', 'CV20': 'Tarrafal', 'KW02': 'Al Kuwayt', 'KW01': 'Al Ahmadi', 'KW07': 'Al Farwaniyah', 'KW05': 'Al Jahra', 'CH19': 'Thurgau', 'KW08': 'Hawalli', 'KW09': 'Mubarak al Kabir', 'PA09': 'San Blas', 'PA08': 'Panama', 'ZM09': 'Lusaka', 'ZM08': 'Copperbelt', 'PA05': 'Darien', 'PA04': 'Colon', 'PA07': 'Los Santos', 'ZM04': 'Luapula', 'ZM03': 'Eastern', 'ZM02': 'Central', 'PA03': 'Cocle', 'PA02': 'Chiriqui', 'MZ01': 'Cabo Delgado', 'US45': 'South Carolina', 'US46': 'South Dakota', 'MZ02': 'Gaza', 'MZ05': 'Sofala', 'MZ04': 'Maputo', 'MZ07': 'Niassa', 'MZ06': 'Nampula', 'MZ09': 'Zambezia', 'MZ08': 'Tete', 'US48': 'Texas', 'US49': 'Utah', 'GD05': 'Saint Mark', 'GD04': 'Saint John', 'GD06': 'Saint Patrick', 'GD01': 'Saint Andrew', 'GD03': 'Saint George', 'GD02': 'Saint David', 'IS09': 'Eyjafjardarsysla', 'IS05': 'Austur-Hunavatnssysla', 'IS06': 'Austur-Skaftafellssysla', 'IS07': 'Borgarfjardarsysla', 'IS03': 'Arnessysla', 'AU02': 'New South Wales', 'AU03': 'Northern Territory', 'AU01': 'Australian Capital Territory', 'AU06': 'Tasmania', 'AU07': 'Victoria', 'AU04': 'Queensland', 'AU05': 'South Australia', 'AU08': 'Western Australia', 'BO09': 'Tarija', 'BM10': 'Southampton', 'BM11': 'Warwick', 'GT09': 'Izabal', 'GT08': 'Huehuetenango', 'GT05': 'El Progreso', 'GT04': 'Chiquimula', 'GT07': 'Guatemala', 'GT06': 'Escuintla', 'GT01': 'Alta Verapaz', 'GT03': 'Chimaltenango', 'GT02': 'Baja Verapaz', 'PY19': 'Canindeyu', 'PY12': 'Misiones', 'PY13': 'Neembucu', 'PY10': 'Guaira', 'PY11': 'Itapua', 'PY16': 'Presidente Hayes', 'PY17': 'San Pedro', 'PY15': 'Paraguari', 'QA11': 'Jariyan al Batnah', 'QA10': 'Al Wakrah', 'QA12': "Umm Sa'id", 'AF41': 'Daykondi', 'AF40': 'Parvan', 'AF42': 'Panjshir', 'GBY1': 'Flintshire', 'GBY2': 'Gwynedd', 'GBY3': 'Merthyr Tydfil', 'GBY4': 'Monmouthshire', 'GBY5': 'Neath Port Talbot', 'GBY6': 'Newport', 'GBY7': 'Pembrokeshire', 'GBY8': 'Powys', 'GBY9': 'Rhondda Cynon Taff', 'UY19': 'Treinta y Tres', 'UY18': 'Tacuarembo', 'UY15': 'Salto', 'UY14': 'Rocha', 'UY17': 'Soriano', 'UY16': 'San Jose', 'UY11': 'Paysandu', 'UY10': 'Montevideo', 'UY13': 'Rivera', 'UY12': 'Rio Negro', 'CL16': 'Arica y Parinacota', 'CL17': 'Los Rios', 'CL14': 'Los Lagos', 'CL15': 'Tarapaca', 'SN14': 'Saint-Louis', 'SN15': 'Matam', 'CL10': 'Magallanes y de la Antartica Chilena', 'CL11': 'Maule', 'BZ01': 'Belize', 'BZ02': 'Cayo', 'BZ03': 'Corozal', 'BZ04': 'Orange Walk', 'BZ05': 'Stann Creek', 'BZ06': 'Toledo', 'CASK': 'Saskatchewan', 'RU87': 'Yamal-Nenets', 'RU86': 'Voronezh', 'RU85': 'Vologda', 'RU84': 'Volgograd', 'RU83': 'Vladimir', 'VN67': 'Ninh Binh', 'VN64': 'Quang Tri', 'VN65': 'Nam Ha', 'VN68': 'Ninh Thuan', 'VN69': 'Phu Yen', 'RU89': 'Yevrey', 'RU88': "Yaroslavl'", 'JP08': 'Fukushima', 'JP09': 'Gifu', 'JP02': 'Akita', 'JP03': 'Aomori', 'JP01': 'Aichi', 'JP06': 'Fukui', 'JP07': 'Fukuoka', 'JP04': 'Chiba', 'JP05': 'Ehime', 'SI22': 'Dol pri Ljubljani', 'SI20': 'Dobrepolje', 'SI26': 'Duplek', 'SI27': 'Gorenja Vas-Poljane', 'SI24': 'Dornava', 'SI25': 'Dravograd', 'SI28': 'Gorisnica', 'SI29': 'Gornja Radgona', 'GBE4': 'Essex', 'GBE5': 'Gateshead', 'GBE6': 'Gloucestershire', 'GBE7': 'Greenwich', 'GBE1': 'East Riding of Yorkshire', 'GBE2': 'East Sussex', 'GBE3': 'Enfield', 'GBE8': 'Hackney', 'GBE9': 'Halton', 'KN03': 'Saint George Basseterre', 'KN02': 'Saint Anne Sandy Point', 'KN01': 'Christ Church Nichola Town', 'KN07': 'Saint John Figtree', 'KN06': 'Saint John Capisterre', 'KN05': 'Saint James Windward', 'KN04': 'Saint George Gingerland', 'KN09': 'Saint Paul Capisterre', 'KN08': 'Saint Mary Cayon', 'CI88': 'Sud-Bandama', 'CI89': 'Sud-Comoe', 'CI84': 'Moyen-Cavally', 'CI85': 'Moyen-Comoe', 'CI86': "N'zi-Comoe", 'CI87': 'Savanes', 'CI80': 'Haut-Sassandra', 'CI81': 'Lacs', 'CI82': 'Lagunes', 'CI83': 'Marahoue', 'NG16': 'Ogun', 'AZ18': 'Fuzuli', 'AZ19': 'Gadabay', 'NG11': 'Federal Capital Territory', 'US56': 'Wyoming', 'US55': 'Wisconsin', 'US54': 'West Virginia', 'US53': 'Washington', 'US51': 'Virginia', 'US50': 'Vermont', 'PHC5': 'Dumaguete', 'PHC4': 'Dipolog', 'PHC7': 'Gingoog', 'PHC6': 'General Santos', 'PHC1': 'Danao', 'PHC3': 'Davao City', 'PHC2': 'Dapitan', 'CO38': 'Magdalena', 'PHC9': 'Iloilo City', 'SN12': 'Ziguinchor', 'SN13': 'Louga', 'TH48': 'Chanthaburi', 'TH49': 'Trat', 'TH44': 'Chachoengsao', 'TH45': 'Prachin Buri', 'IS15': 'Kjosarsysla', 'TH47': 'Rayong', 'TH40': 'Krung Thep', 'TH41': 'Phayao', 'TH42': 'Samut Prakan', 'IS10': 'Gullbringusysla', 'BM07': "Saint George's", 'BM06': 'Saint George', 'BM05': 'Pembroke', 'BM04': 'Paget', 'BM03': 'Hamilton', 'BM02': 'Hamilton', 'BM01': 'Devonshire', 'BM09': 'Smiths', 'BM08': 'Sandys', 'SIK5': 'Preddvor', 'USDC': 'District of Columbia', 'PY05': 'Caazapa', 'PY04': 'Caaguazu', 'PY07': 'Concepcion', 'PY06': 'Central', 'PY01': 'Alto Parana', 'PY03': 'Boqueron', 'PY02': 'Amambay', 'PY08': 'Cordillera', 'AF30': 'Balkh', 'AF31': 'Jowzjan', 'AF32': 'Samangan', 'AF33': 'Sar-e Pol', 'AF34': 'Konar', 'AF35': 'Laghman', 'AF36': 'Paktia', 'AF37': 'Khowst', 'AF38': 'Nurestan', 'AF39': 'Oruzgan', 'GBX3': 'Bridgend', 'GBX2': 'Blaenau Gwent', 'GBX1': 'Isle of Anglesey', 'ML10': 'Kidal', 'GBX6': 'Ceredigion', 'GBX5': 'Cardiff', 'GBX4': 'Caerphilly', 'GBX9': 'Denbighshire', 'GBX8': 'Conwy', 'AM08': "Syunik'", 'AM09': 'Tavush', 'AM02': 'Ararat', 'AM03': 'Armavir', 'AM01': 'Aragatsotn', 'AM06': 'Lorri', 'AM07': 'Shirak', 'AM04': "Geghark'unik'", 'AM05': "Kotayk'", 'CL09': 'Los Lagos', 'CL08': "Libertador General Bernardo O'Higgins", 'SN09': 'Fatick', 'SN03': 'Diourbel', 'SN01': 'Dakar', 'CL02': 'Aisen del General Carlos Ibanez del Campo', 'SN07': 'Thies', 'CL04': 'Araucania', 'SN05': 'Tambacounda', 'CL06': 'Bio-Bio', 'SN10': 'Kaolack', 'UA08': "Khersons'ka Oblast'", 'UA09': "Khmel'nyts'ka Oblast'", 'USMN': 'Minnesota', 'UA02': "Chernihivs'ka Oblast'", 'UA03': "Chernivets'ka Oblast'", 'UA01': "Cherkas'ka Oblast'", 'UA06': "Ivano-Frankivs'ka Oblast'", 'UA07': "Kharkivs'ka Oblast'", 'UA04': "Dnipropetrovs'ka Oblast'", 'UA05': "Donets'ka Oblast'", 'SN11': 'Kolda', 'VN62': 'Khanh Hoa', 'VN79': 'Hai Duong', 'VN78': 'Da Nang', 'VN63': 'Kon Tum', 'VN75': 'Tra Vinh', 'VN74': 'Thua Thien', 'VN77': 'Vinh Long', 'VN76': 'Tuyen Quang', 'VN71': 'Quang Ngai', 'VN60': 'Ha Tinh', 'VN73': 'Soc Trang', 'VN72': 'Quang Tri', 'VN61': 'Hoa Binh', 'VN66': 'Nghe An', 'RU82': 'Ust-Orda Buryat', 'JP15': 'Ishikawa', 'JP14': 'Ibaraki', 'JP17': 'Kagawa', 'JP16': 'Iwate', 'JP11': 'Hiroshima', 'RU81': "Ul'yanovsk", 'JP13': 'Hyogo', 'JP12': 'Hokkaido', 'IL03': 'HaZafon', 'IL02': 'HaMerkaz', 'IL01': 'HaDarom', 'RU80': 'Udmurt', 'JP19': 'Kanagawa', 'JP18': 'Kagoshima', 'IL05': 'Tel Aviv', 'IL04': 'Hefa', 'SI39': 'Ivancna Gorica', 'SI38': 'Ilirska Bistrica', 'SI35': 'Hrpelje-Kozina', 'SI34': 'Hrastnik', 'SI37': 'Ig', 'SI36': 'Idrija', 'SI31': 'Gornji Petrovci', 'SI30': 'Gornji Grad', 'SI32': 'Grosuplje', 'EE20': 'Viljandimaa', 'GBD6': 'Dorset', 'GBD5': 'Doncaster', 'GBD4': 'Devon', 'GBD3': 'Derbyshire', 'GBD2': 'Derby', 'GBD1': 'Darlington', 'GBD9': 'Ealing', 'GBD8': 'Durham', 'BR01': 'Acre', 'BR02': 'Alagoas', 'BR03': 'Amapa', 'BR04': 'Amazonas', 'BR05': 'Bahia', 'BR06': 'Ceara', 'BR07': 'Distrito Federal', 'BR08': 'Espirito Santo', 'CI92': 'Zanzan', 'CI91': 'Worodougou', 'CI90': 'Vallee du Bandama', 'PK03': 'North-West Frontier', 'PK02': 'Balochistan', 'IT10': 'Marche', 'IT11': 'Molise', 'IT12': 'Piemonte', 'IT13': 'Puglia', 'IT14': 'Sardegna', 'IT15': 'Sicilia', 'IT16': 'Toscana', 'IT17': 'Trentino-Alto Adige', 'IT18': 'Umbria', 'IT19': "Valle d'Aosta", 'PHD1': 'Iriga', 'PHD2': 'La Carlota', 'PHD3': 'Laoag', 'PHD4': 'Lapu-Lapu', 'PHD5': 'Legaspi', 'PHD6': 'Lipa', 'PHD7': 'Lucena', 'PHD8': 'Mandaue', 'PHD9': 'Manila', 'PK08': 'Islamabad', 'BB01': 'Christ Church', 'IS28': 'Skagafjardarsysla', 'IS29': 'Snafellsnes- og Hnappadalssysla', 'BB04': 'Saint James', 'BB05': 'Saint John', 'TH59': 'Ranong', 'TH58': 'Chumphon', 'TH57': 'Prachuap Khiri Khan', 'IS23': 'Rangarvallasysla', 'TH55': 'Samut Sakhon', 'TH54': 'Samut Songkhram', 'TH53': 'Nakhon Pathom', 'TH52': 'Ratchaburi', 'TH51': 'Suphan Buri', 'TH50': 'Kanchanaburi', 'BT20': 'Thimphu', 'BT21': 'Tongsa', 'BT22': 'Wangdi Phodrang', 'CR07': 'Puntarenas', 'CR06': 'Limon', 'CR04': 'Heredia', 'CR03': 'Guanacaste', 'CR02': 'Cartago', 'CR01': 'Alajuela', 'CR08': 'San Jose', 'HN02': 'Choluteca', 'HN03': 'Colon', 'HN01': 'Atlantida', 'HN06': 'Cortes', 'HN07': 'El Paraiso', 'HN04': 'Comayagua', 'HN05': 'Copan', 'HN08': 'Francisco Morazan', 'HN09': 'Gracias a Dios', 'GL01': 'Nordgronland', 'GL03': 'Vestgronland', 'GL02': 'Ostgronland', 'ET50': 'Hareri Hizb', 'ET51': 'Oromiya', 'ET52': 'Sumale', 'ET53': 'Tigray', 'ET54': 'YeDebub Biheroch Bihereseboch na Hizboch', 'AF23': 'Kandahar', 'AF27': 'Vardak', 'IE29': 'Westmeath', 'AF24': 'Kondoz', 'IE24': 'Roscommon', 'IE25': 'Sligo', 'IE26': 'Tipperary', 'IE27': 'Waterford', 'IE20': 'Mayo', 'IE21': 'Meath', 'IE22': 'Monaghan', 'IE23': 'Offaly', 'ML07': 'Koulikoro', 'ML06': 'Sikasso', 'ML05': 'Segou', 'ML04': 'Mopti', 'ML03': 'Kayes', 'AM10': "Vayots' Dzor", 'ML01': 'Bamako', 'ML09': 'Gao', 'ML08': 'Tombouctou', 'UA15': "L'vivs'ka Oblast'", 'UA14': "Luhans'ka Oblast'", 'UA17': "Odes'ka Oblast'", 'UA16': "Mykolayivs'ka Oblast'", 'UA11': 'Krym', 'UA10': "Kirovohrads'ka Oblast'", 'UA13': "Kyyivs'ka Oblast'", 'UA12': 'Kyyiv', 'GBV9': 'Orkney', 'UA19': "Rivnens'ka Oblast'", 'UA18': "Poltavs'ka Oblast'", 'GBV8': 'North Lanarkshire', 'GBV5': 'Midlothian', 'GBV4': 'Inverclyde', 'VN09': 'Dong Thap', 'VN01': 'An Giang', 'VN03': 'Ben Tre', 'VN05': 'Cao Bang', 'NG56': 'Nassarawa', 'MV41': 'Meemu', 'MV40': 'Maale', 'MV43': 'Noonu', 'PL80': 'Podkarpackie', 'SI49': 'Komen', 'PL82': 'Pomorskie', 'MV42': 'Gnaviyani', 'PL84': 'Swietokrzyskie', 'PL85': 'Warminsko-Mazurskie', 'PL86': 'Wielkopolskie', 'PL87': 'Zachodniopomorskie', 'SI40': 'Izola-Isola', 'MV45': 'Shaviyani', 'SI42': 'Jursinci', 'SI44': 'Kanal', 'SI45': 'Kidricevo', 'SI46': 'Kobarid', 'MV44': 'Raa', 'MV47': 'Vaavu', 'MV46': 'Thaa', 'GBG2': 'Isle of Wight', 'GBG3': 'Islington', 'GBG1': 'Hounslow', 'GBG6': 'Kingston upon Hull', 'GBG7': 'Kingston upon Thames', 'GBG4': 'Kensington and Chelsea', 'GBG5': 'Kent', 'GBG8': 'Kirklees', 'GBG9': 'Knowsley', 'MKC3': 'Zelino', 'BR13': 'Maranhao', 'BR11': 'Mato Grosso do Sul', 'MKC2': 'Zelenikovo', 'BR17': 'Paraiba', 'BR16': 'Para', 'BR15': 'Minas Gerais', 'BR14': 'Mato Grosso', 'FJ04': 'Rotuma', 'FJ05': 'Western', 'BR18': 'Parana', 'FJ01': 'Central', 'FJ02': 'Eastern', 'FJ03': 'Northern', 'MKC6': 'Zrnovci', 'PH08': 'Batanes', 'PH09': 'Batangas', 'PH04': 'Aklan', 'PH05': 'Albay', 'PH06': 'Antique', 'PH07': 'Bataan', 'PH01': 'Abra', 'PH02': 'Agusan del Norte', 'PH03': 'Agusan del Sur', 'IT03': 'Calabria', 'IT02': 'Basilicata', 'IT01': 'Abruzzi', 'IT07': 'Lazio', 'IT06': 'Friuli-Venezia Giulia', 'IT05': 'Emilia-Romagna', 'IT04': 'Campania', 'IT09': 'Lombardia', 'IT08': 'Liguria', 'PHE3': 'Olongapo', 'PHE2': 'Naga', 'PHE1': 'Marawi', 'PHE7': 'Pagadian', 'PHE6': 'Ozamis', 'PHE5': 'Oroquieta', 'PHE4': 'Ormoc', 'PHE9': 'Pasay', 'PHE8': 'Palayan', 'TH68': 'Songkhla', 'TH69': 'Pattani', 'TH62': 'Phuket', 'TH63': 'Krabi', 'TH60': 'Surat Thani', 'TH61': 'Phangnga', 'TH66': 'Phatthalung', 'TH67': 'Satun', 'TH64': 'Nakhon Si Thammarat', 'TH65': 'Trang', 'MS01': 'Saint Anthony', 'MS02': 'Saint Georges', 'MS03': 'Saint Peter', 'VE24': 'Dependencias Federales', 'SIB3': 'Sentilj', 'DE12': 'Mecklenburg-Vorpommern', 'DE13': 'Sachsen', 'DE10': 'Schleswig-Holstein', 'DE11': 'Brandenburg', 'DE16': 'Berlin', 'DE14': 'Sachsen-Anhalt', 'DE15': 'Thuringen', 'MU20': 'Savanne', 'MU21': 'Agalega Islands', 'MU22': 'Cargados Carajos', 'MU23': 'Rodrigues', 'HN18': 'Yoro', 'HN15': 'Olancho', 'HN14': 'Ocotepeque', 'HN17': 'Valle', 'HN16': 'Santa Barbara', 'HN11': 'Islas de la Bahia', 'HN10': 'Intibuca', 'HN13': 'Lempira', 'HN12': 'La Paz', 'IS35': 'Vestur-Hunavatnssysla', 'IS34': 'Vestur-Bardastrandarsysla', 'IS37': 'Vestur-Skaftafellssysla', 'IS36': 'Vestur-Isafjardarsysla', 'IS31': 'Sudur-Mulasysla', 'IS30': 'Strandasysla', 'IS32': 'Sudur-Tingeyjarsysla', 'HT03': 'Nord-Ouest', 'USFL': 'Florida', 'USFM': 'Federated States of Micronesia', 'ET49': 'Gambela Hizboch', 'ET48': 'Dire Dawa', 'ZW10': 'Harare', 'ET47': 'Binshangul Gumuz', 'ET46': 'Amara', 'ET45': 'Afar', 'ET44': 'Adis Abeba', 'AF18': 'Nangarhar', 'AF19': 'Nimruz', 'AF17': 'Lowgar', 'AF14': 'Kapisa', 'AF13': 'Kabol', 'AF10': 'Helmand', 'AF11': 'Herat', 'GBZ1': 'Swansea', 'GBZ3': 'Vale of Glamorgan', 'GBZ2': 'Torfaen', 'GBZ4': 'Wrexham', 'AO08': 'Huambo', 'AO09': 'Huila', 'AO01': 'Benguela', 'AO02': 'Bie', 'AO03': 'Cabinda', 'AO04': 'Cuando Cubango', 'AO05': 'Cuanza Norte', 'AO06': 'Cuanza Sul', 'AO07': 'Cunene', 'TO03': 'Vava', 'NP08': 'Lumbini', 'NP09': 'Mahakali', 'NP06': 'Karnali', 'NP07': 'Kosi', 'NP04': 'Gandaki', 'NP05': 'Janakpur', 'NP02': 'Bheri', 'NP03': 'Dhawalagiri', 'NP01': 'Bagmati', 'VN13': 'Hai Phong', 'UG84': 'Kitgum', 'UG85': 'Kyenjojo', 'UG86': 'Mayuge', 'UG87': 'Mbale', 'UG80': 'Kaberamaido', 'UG81': 'Kamwenge', 'UG82': 'Kanungu', 'UG83': 'Kayunga', 'UG88': 'Moroto', 'UG89': 'Mpigi', 'SI53': 'Kranjska Gora', 'SI52': 'Kranj', 'SI51': 'Kozje', 'SI50': 'Koper-Capodistria', 'SI57': 'Lasko', 'SI55': 'Kungota', 'SI54': 'Krsko', 'GBF9': 'Hillingdon', 'GBF8': 'Hertford', 'EE08': 'Laane-Virumaa', 'EE09': 'Narva', 'GBF5': 'Hartlepool', 'GBF4': 'Harrow', 'GBF7': 'Herefordshire', 'GBF6': 'Havering', 'GBF1': 'Hammersmith and Fulham', 'EE03': 'Ida-Virumaa', 'GBF3': 'Haringey', 'GBF2': 'Hampshire', 'BR28': 'Sergipe', 'BR29': 'Goias', 'BR26': 'Santa Catarina', 'BR27': 'Sao Paulo', 'BR24': 'Rondonia', 'BR25': 'Roraima', 'BR22': 'Rio Grande do Norte', 'BR23': 'Rio Grande do Sul', 'BR20': 'Piaui', 'BR21': 'Rio de Janeiro', 'SI76': 'Mislinja', 'PH19': 'Catanduanes', 'PH18': 'Capiz', 'PH17': 'Camiguin', 'PH16': 'Camarines Sur', 'PH15': 'Camarines Norte', 'PH14': 'Cagayan', 'PH13': 'Bulacan', 'PH12': 'Bukidnon', 'PH11': 'Bohol', 'PH10': 'Benguet', 'US08': 'Colorado', 'US09': 'Connecticut', 'CH25': 'Zurich', 'CH24': 'Zug', 'CH23': 'Vaud', 'CH22': 'Valais', 'CH21': 'Uri', 'CH20': 'Ticino', 'US01': 'Alabama', 'US02': 'Alaska', 'US04': 'Arizona', 'US05': 'Arkansas', 'US06': 'California', 'NA25': 'Kavango', 'PHF8': 'Silay', 'PHF9': 'Surigao', 'PHF6': 'San Jose', 'PHF7': 'San Pablo', 'PHF4': 'San Carlos', 'PHF5': 'San Carlos', 'PHF2': 'Quezon City', 'PHF3': 'Roxas', 'PHF1': 'Puerto Princesa', 'LA02': 'Champasak', 'NA21': 'Windhoek', 'USGA': 'Georgia', 'NA20': 'Karasburg', 'NA23': 'Hereroland Oos', 'USGU': 'Guam', 'BT06': 'Chhukha', 'BT07': 'Chirang', 'BT05': 'Bumthang', 'BT08': 'Daga', 'BT09': 'Geylegphug', 'KZ14': 'Qyzylorda', 'KZ15': 'East Kazakhstan', 'KZ16': 'North Kazakhstan', 'KZ17': 'Zhambyl', 'KZ10': 'South Kazakhstan', 'KZ11': 'Pavlodar', 'KZ12': 'Qaraghandy', 'KZ13': 'Qostanay', 'LU02': 'Grevenmacher', 'PHC8': 'Iligan', 'TH75': 'Ubon Ratchathani', 'IS41': 'Norourland Vestra', 'IS42': 'Suourland', 'IS43': 'Suournes', 'TH71': 'Ubon Ratchathani', 'TH70': 'Yala', 'TH73': 'Nakhon Phanom', 'TH72': 'Yasothon', 'TH79': 'Nong Bua Lamphu', 'TH78': 'Mukdahan', 'ZW05': 'Mashonaland West', 'ZW04': 'Mashonaland East', 'ZW07': 'Matabeleland South', 'ZW06': 'Matabeleland North', 'ZW01': 'Manicaland', 'ZW03': 'Mashonaland Central', 'ZW02': 'Midlands', 'ZW09': 'Bulawayo', 'ZW08': 'Masvingo', 'FM02': 'Pohnpei', 'FM01': 'Kosrae', 'DE05': 'Hessen', 'IS17': 'Myrasysla', 'DE07': 'Nordrhein-Westfalen', 'DE06': 'Niedersachsen', 'DE01': 'Baden-Wurttemberg', 'DE03': 'Bremen', 'DE02': 'Bayern', 'NR08': 'Denigomodu', 'DE09': 'Saarland', 'TH46': 'Chon Buri', 'NR09': 'Ewa', 'AF09': 'Ghowr', 'SC20': 'Pointe La Rue', 'SC21': 'Port Glaud', 'AF01': 'Badakhshan', 'IE03': 'Clare', 'AF03': 'Baghlan', 'IE01': 'Carlow', 'AF05': 'Bamian', 'IE07': 'Dublin', 'AF07': 'Faryab', 'AF06': 'Farah', 'VN39': 'Lang Son', 'TH43': 'Nakhon Nayok', 'AO19': 'Bengo', 'AO18': 'Lunda Sul', 'AO13': 'Namibe', 'AO12': 'Malanje', 'AO17': 'Lunda Norte', 'AO16': 'Zaire', 'AO15': 'Uige', 'AO14': 'Moxico', 'TW04': "T'ai-wan", 'TW03': "T'ai-pei", 'TW02': 'Kao-hsiung', 'TW01': 'Fu-chien', 'NP11': 'Narayani', 'NP10': 'Mechi', 'NP13': 'Sagarmatha', 'NP12': 'Rapti', 'NP14': 'Seti', 'EG05': 'Al Gharbiyah', 'SIA7': 'Rogaska Slatina', 'SIA6': 'Rogasovci', 'SIA3': 'Radovljica', 'SIA2': 'Radlje ob Dravi', 'SIA1': 'Radenci', 'SIA8': 'Rogatec', 'CAMB': 'Manitoba', 'EG03': 'Al Buhayrah', 'JP46': 'Yamanashi', 'JM15': 'Trelawny', 'JP44': 'Yamagata', 'JP45': 'Yamaguchi', 'JM10': 'Saint Catherine', 'JP43': 'Wakayama', 'JP40': 'Tokyo', 'JM13': 'Saint Mary', 'UG97': 'Yumbe', 'UG96': 'Wakiso', 'UG95': 'Soroti', 'UG94': 'Sironko', 'UG93': 'Rukungiri', 'UG92': 'Pader', 'UG91': 'Nakapiripirit', 'SI61': 'Ljubljana', 'SI68': 'Lukovica', 'EE19': 'Valgamaa', 'EE18': 'Tartumaa', 'VN24': 'Long An', 'VN23': 'Lam Dong', 'VN20': 'Ho Chi Minh', 'VN21': 'Kien Giang', 'EE11': 'Parnumaa', 'GBA1': 'Barking and Dagenham', 'EE13': 'Raplamaa', 'EE12': 'Polvamaa', 'EE15': 'Sillamae', 'EE14': 'Saaremaa', 'EE17': 'Tartu', 'EE16': 'Tallinn', 'BR31': 'Tocantins', 'BR30': 'Pernambuco', 'IR43': 'Khorasan-e Shemali', 'PH28': 'Ilocos Norte', 'RUCI': 'Chechnya Republic', 'PH22': 'Basilan', 'PH23': 'Eastern Samar', 'PH20': 'Cavite', 'PH21': 'Cebu', 'PH26': 'Davao Oriental', 'PH27': 'Ifugao', 'PH24': 'Davao', 'PH25': 'Davao del Sur', 'CH12': 'Neuchatel', 'CH13': 'Nidwalden', 'US19': 'Iowa', 'US18': 'Indiana', 'CH16': 'Schaffhausen', 'CH17': 'Schwyz', 'CH14': 'Obwalden', 'CH15': 'Sankt Gallen', 'US13': 'Georgia', 'US12': 'Florida', 'CH18': 'Solothurn', 'US10': 'Delaware', 'US17': 'Illinois', 'US16': 'Idaho', 'US15': 'Hawaii', 'PHG8': 'Aurora', 'PHG1': 'Tacloban', 'PHG3': 'Tagbilaran', 'PHG2': 'Tagaytay', 'PHG5': 'Toledo', 'PHG4': 'Tangub', 'PHG7': 'Zamboanga', 'PHG6': 'Trece Martires', 'BT11': 'Lhuntshi', 'BT10': 'Ha', 'BT13': 'Paro', 'BT12': 'Mongar', 'BT15': 'Punakha', 'BT14': 'Pemagatsel', 'BT17': 'Samdrup', 'BT16': 'Samchi', 'BT19': 'Tashigang', 'BT18': 'Shemgang', 'KZ07': 'West Kazakhstan', 'KZ06': 'Atyrau', 'KZ05': 'Astana', 'KZ04': 'Aqtobe', 'KZ03': 'Aqmola', 'KZ02': 'Almaty City', 'KZ01': 'Almaty', 'KZ09': 'Mangghystau', 'KZ08': 'Bayqonyr', 'KR19': 'Taejon-jikhalsi', 'TH01': 'Mae Hong Son', 'TH02': 'Chiang Mai', 'TH03': 'Chiang Rai', 'TH04': 'Nan', 'TH05': 'Lamphun', 'TH06': 'Lampang', 'TH07': 'Phrae', 'TH08': 'Tak', 'TH09': 'Sukhothai', 'FM04': 'Yap', 'TN28': 'Madanin', 'TN29': 'Gabes', 'TN22': 'Siliana', 'TN23': 'Sousse', 'TN27': 'Ben Arous', 'UG52': 'Mbarara', 'DK18': 'Midtjylland', 'DK19': 'Nordjylland', 'DK17': 'Hovedstaden', 'UG50': 'Masindi', 'DZ24': 'Jijel', 'DZ25': 'Laghouat', 'NG50': 'Rivers', 'NG51': 'Sokoto', 'DZ20': 'Blida', 'CH08': 'Glarus', 'NG54': 'Ekiti', 'NG55': 'Gombe', 'IE15': 'Laois', 'IE14': 'Leitrim', 'IE16': 'Limerick', 'IE11': 'Kerry', 'IE10': 'Galway', 'IE13': 'Kilkenny', 'IE12': 'Kildare', 'IE19': 'Louth', 'IE18': 'Longford', 'SIB2': 'Sencur', 'HT09': 'Nord', 'SIB1': 'Semic', 'SIB6': 'Sevnica', 'SIB7': 'Sezana', 'SIB4': 'Sentjernej', 'USDE': 'Delaware', 'SIB8': 'Skocjan', 'SIB9': 'Skofja Loka', 'HT06': 'Artibonite', 'HT07': 'Centre', 'LR21': 'Gbarpolu', 'JM09': 'Saint Ann', 'JM08': 'Saint Andrew', 'JM07': 'Portland', 'JM04': 'Manchester', 'JM02': 'Hanover', 'JM01': 'Clarendon', 'AO20': 'Luanda', 'SI71': 'Medvode', 'VN80': 'Ha Nam', 'SI73': 'Metlika', 'SI72': 'Menges', 'SI74': 'Mezica', 'SI77': 'Moravce', 'VN81': 'Hung Yen', 'SI79': 'Mozirje', 'SI78': 'Moravske Toplice', 'VN82': 'Nam Dinh', 'GBO9': 'Waltham Forest', 'VN84': 'Quang Nam', 'LU01': 'Diekirch', 'LU03': 'Luxembourg', 'VN85': 'Thai Nguyen', 'VN86': 'Vinh Puc Province', 'VN87': 'Can Tho', 'FM03': 'Chuuk', 'VN30': 'Quang Ninh', 'VN33': 'Tay Ninh', 'VN32': 'Son La', 'VN35': 'Thai Binh', 'VN34': 'Thanh Hoa', 'VN37': 'Tien Giang', 'VN89': 'Lai Chau', 'NR04': 'Anibare', 'NR05': 'Baiti', 'NR06': 'Boe', 'NR07': 'Buada', 'NR01': 'Aiwo', 'NR02': 'Anabar', 'NR03': 'Anetan', 'EG08': 'Al Jizah', 'EG09': 'Al Minufiyah', 'EG04': 'Al Fayyum', 'GBO6': 'Trafford', 'EG06': 'Al Iskandariyah', 'EG07': "Al Isma'iliyah", 'EG01': 'Ad Daqahliyah', 'EG02': 'Al Bahr al Ahmar', 'GBO7': 'Wakefield', 'PH35': 'Lanao del Sur', 'PH34': 'Lanao del Norte', 'PH37': 'Leyte', 'PH36': 'La Union', 'PH31': 'Isabela', 'PH30': 'Iloilo', 'PH33': 'Laguna', 'PH32': 'Kalinga-Apayao', 'PH39': 'Masbate', 'PH38': 'Marinduque', 'US26': 'Michigan', 'US27': 'Minnesota', 'US24': 'Maryland', 'US25': 'Massachusetts', 'US22': 'Louisiana', 'US23': 'Maine', 'US20': 'Kansas', 'US21': 'Kentucky', 'US28': 'Mississippi', 'US29': 'Missouri', 'NG52': 'Bayelsa', 'NG53': 'Ebonyi', 'DZ26': 'Mascara', 'DZ27': "M'sila", 'CH09': 'Graubunden', 'DZ21': 'Bouira', 'DZ22': 'Djelfa', 'DZ23': 'Guelma', 'CH05': 'Bern', 'CH04': 'Basel-Stadt', 'CH07': 'Geneve', 'CH06': 'Fribourg', 'CH01': 'Aargau', 'DZ29': 'Oum el Bouaghi', 'CH03': 'Basel-Landschaft', 'CH02': 'Ausser-Rhoden', 'VE08': 'Cojedes', 'USAK': 'Alaska', 'USAL': 'Alabama', 'USAA': 'Armed Forces Americas', 'USAE': 'Armed Forces Europe', 'USAZ': 'Arizona', 'USAS': 'American Samoa', 'USAR': 'Arkansas', 'USAP': 'Armed Forces Pacific', 'ES51': 'Andalucia', 'MU13': 'Flacq', 'MU12': 'Black River', 'MU15': 'Moka', 'MU14': 'Grand Port', 'MU17': 'Plaines Wilhems', 'MU16': 'Pamplemousses', 'MU19': 'Riviere du Rempart', 'MU18': 'Port Louis', 'TH13': 'Phichit', 'TH12': 'Phitsanulok', 'TH11': 'Kamphaeng Phet', 'TH10': 'Uttaradit', 'TH17': 'Nong Khai', 'TH16': 'Nakhon Sawan', 'TH15': 'Uthai Thani', 'TH14': 'Phetchabun', 'TH18': 'Loei', 'TN39': 'Manouba', 'TN38': 'Aiana', 'TN33': 'Sidi Bou Zid', 'TN32': 'Sfax', 'TN31': 'Kebili', 'TN37': 'Zaghouan', 'TN36': 'Tunis', 'TN35': 'Tozeur', 'TN34': 'Tataouine', 'TG25': 'Plateaux', 'TG24': 'Maritime', 'TG26': 'Savanes', 'TG23': 'Kara', 'TG22': 'Centrale', 'NG25': 'Anambra', 'YE24': 'Lahij', 'YE25': 'Ta', 'YE20': "Al Bayda'", 'YE21': 'Al Jawf', 'YE22': 'Hajjah', 'YE23': 'Ibb', 'TR58': 'Sivas', 'CZ52': 'Hlavni mesto Praha', 'MM08': 'Mandalay', 'MM09': 'Pegu', 'MM06': 'Kayah State', 'MM07': 'Magwe', 'MM04': 'Kachin State', 'MM05': 'Karan State', 'MM02': 'Chin State', 'MM03': 'Irrawaddy', 'MM01': 'Rakhine State', 'VE06': 'Bolivar', 'RS01': 'Kosovo', 'RS02': 'Vojvodina', 'SIC9': 'Store', 'SIC8': 'Starse', 'SIC5': 'Smarje pri Jelsah', 'SIC4': 'Slovenske Konjice', 'SIC7': 'Sostanj', 'SIC6': 'Smartno ob Paki', 'SIC1': 'Skofljica', 'HT15': 'Nippes', 'TR54': 'Sakarya', 'TO01': 'Ha', 'GBX7': 'Carmarthenshire', 'SE08': 'Jonkopings Lan', 'SE09': 'Kalmar Lan', 'AR24': 'Tucuman', 'AR23': 'Tierra del Fuego', 'AR22': 'Santiago del Estero', 'AR21': 'Santa Fe', 'AR20': 'Santa Cruz', 'SE02': 'Blekinge Lan', 'SE03': 'Gavleborgs Lan', 'SE05': 'Gotlands Lan', 'SE06': 'Hallands Lan', 'SE07': 'Jamtlands Lan', 'SI88': 'Osilnica', 'SI89': 'Pesnica', 'SI84': 'Nova Gorica', 'SI86': 'Odranci', 'SI87': 'Ormoz', 'SI80': 'Murska Sobota', 'SI81': 'Muta', 'SI82': 'Naklo', 'SI83': 'Nazarje', 'GBC6': 'Cornwall', 'GBC7': 'Coventry', 'GBC4': 'Camden', 'GBC5': 'Cheshire', 'GBC2': 'Calderdale', 'GBC3': 'Cambridgeshire', 'GBC1': 'Bury', 'MD58': 'Stinga Nistrului', 'MD59': 'Anenii Noi', 'GBC8': 'Croydon', 'GBC9': 'Cumbria', 'NR14': 'Yaren', 'NR13': 'Uaboe', 'NR12': 'Nibok', 'NR11': 'Meneng', 'NR10': 'Ijuw', 'EG19': "Bur Sa'id", 'EG18': 'Bani Suwayf', 'EG17': 'Asyut', 'EG16': 'Aswan', 'EG15': 'As Suways', 'EG14': 'Ash Sharqiyah', 'EG13': 'Al Wadi al Jadid', 'EG12': 'Al Qalyubiyah', 'EG11': 'Al Qahirah', 'EG10': 'Al Minya', 'ZA10': 'North-West', 'PH41': 'Mindoro Oriental', 'PH42': 'Misamis Occidental', 'PH43': 'Misamis Oriental', 'PH44': 'Mountain', 'PH45': 'Negros Occidental', 'PH46': 'Negros Oriental', 'PH47': 'Nueva Ecija', 'PH48': 'Nueva Vizcaya', 'PH49': 'Palawan', 'JO12': 'At Tafilah', 'JO13': 'Az Zarqa', 'JO10': 'Al Mafraq', 'JO11': 'Amman Governorate', 'JO16': 'Amman', 'JO14': 'Irbid', 'NG05': 'Lagos', 'US31': 'Nebraska', 'US30': 'Montana', 'US33': 'New Hampshire', 'US32': 'Nevada', 'US35': 'New Mexico', 'US34': 'New Jersey', 'US37': 'North Carolina', 'US36': 'New York', 'US39': 'Ohio', 'US38': 'North Dakota', 'DZ37': 'Annaba', 'DZ36': 'Ain Temouchent', 'DZ35': 'Ain Defla', 'DZ34': 'Adrar', 'DZ33': 'Tebessa', 'NG48': 'Ondo', 'DZ31': 'Skikda', 'DZ30': 'Sidi Bel Abbes', 'NG45': 'Abia', 'NG44': 'Yobe', 'NG47': 'Enugu', 'NG46': 'Bauchi', 'NG41': 'Kogi', 'NG40': 'Kebbi', 'DZ39': 'Bordj Bou Arreridj', 'DZ38': 'Bechar', 'CL01': 'Valparaiso', 'CL03': 'Antofagasta', 'CL05': 'Atacama', 'CL07': 'Coquimbo', 'AE05': 'Ras Al Khaimah', 'BO05': 'Oruro', 'BO04': 'La Paz', 'BO07': 'Potosi', 'BO06': 'Pando', 'BO01': 'Chuquisaca', 'TH28': 'Buriram', 'TH29': 'Surin', 'TH26': 'Chaiyaphum', 'TH27': 'Nakhon Ratchasima', 'TH24': 'Maha Sarakham', 'TH25': 'Roi Et', 'TH22': 'Khon Kaen', 'TH23': 'Kalasin', 'TH20': 'Sakon Nakhon', 'TH21': 'Nakhon Phanom', 'TN06': 'Jendouba', 'TN02': 'Kasserine', 'TN03': 'Kairouan', 'SIL3': 'Ruse', 'NA27': 'Namaland', 'MV37': 'Haa Dhaalu', 'MW04': 'Chitipa', 'MW05': 'Thyolo', 'MW06': 'Dedza', 'MW07': 'Dowa', 'MW02': 'Chikwawa', 'MW03': 'Chiradzulu', 'MW08': 'Karonga', 'MW09': 'Kasungu', 'TR82': 'Cankiri', 'TR83': 'Gaziantep', 'TR80': 'Sirnak', 'TR81': 'Adana', 'TR86': 'Ardahan', 'TR87': 'Bartin', 'TR84': 'Kars', 'TR85': 'Zonguldak', 'TR88': 'Igdir', 'TR89': 'Karabuk', 'SD44': 'Central Equatoria State', 'MM11': 'Shan State', 'MM10': 'Sagaing', 'MM13': 'Mon State', 'MM12': 'Tenasserim', 'MM14': 'Rangoon', 'MM17': 'Yangon', 'BF15': 'Bam', 'BF19': 'Boulkiemde', 'NG37': 'Edo', 'SL01': 'Eastern', 'SL03': 'Southern', 'SL02': 'Northern', 'SL04': 'Western Area', 'SID8': 'Velike Lasce', 'SID1': 'Sveti Jurij', 'SID2': 'Tolmin', 'SID3': 'Trbovlje', 'SID4': 'Trebnje', 'SID5': 'Trzic', 'SID6': 'Turnisce', 'SID7': 'Velenje', 'DZ51': 'Relizane', 'AR12': 'La Rioja', 'AR13': 'Mendoza', 'AR10': 'Jujuy', 'AR11': 'La Pampa', 'AR16': 'Rio Negro', 'AR17': 'Salta', 'LY61': 'Tarabulus', 'AR15': 'Neuquen', 'SE12': 'Kronobergs Lan', 'AR18': 'San Juan', 'AR19': 'San Luis', 'SE16': 'Ostergotlands Lan', 'SE15': 'Orebro Lan', 'SE14': 'Norrbottens Lan', 'SI99': 'Radece', 'SI98': 'Racam', 'SI97': 'Puconci', 'SI94': 'Postojna', 'SI92': 'Podcetrtek', 'SI91': 'Pivka', 'VN70': 'Quang Binh', 'GBB1': 'Bolton', 'GBB3': 'Bracknell Forest', 'GBB2': 'Bournemouth', 'GBB5': 'Brent', 'GBB4': 'Bradford', 'GBB7': 'Bristol', 'GBB6': 'Brighton and Hove', 'GBB9': 'Buckinghamshire', 'GBB8': 'Bromley', 'RU18': 'Evenk', 'RU19': 'Ingush', 'RU14': 'Chita', 'RU15': 'Chukot', 'RU16': 'Chuvashia', 'RU17': 'Dagestan', 'RU10': 'Bryansk', 'RU11': 'Buryat', 'RU12': 'Chechnya', 'RU13': 'Chelyabinsk', 'EG22': 'Matruh', 'EG23': 'Qina', 'EG20': 'Dumyat', 'EG21': 'Kafr ash Shaykh', 'EG26': "Janub Sina'", 'EG27': "Shamal Sina'", 'EG24': 'Suhaj', 'ZA03': 'Free State', 'ZA02': 'KwaZulu-Natal', 'ZA01': 'North-Western Province', 'PH50': 'Pampanga', 'PH57': 'North Cotabato', 'PH56': 'Maguindanao', 'PH55': 'Samar', 'PH54': 'Romblon', 'ZA09': 'Limpopo', 'ZA08': 'Northern Cape', 'JO09': 'Al Karak', 'JO07': 'Ma', 'JO02': "Al Balqa'", 'TZ22': 'Zanzibar North', 'RO28': 'Neamt', 'AZ38': 'Qabala', 'AZ39': 'Qax', 'AZ34': 'Naftalan', 'AZ35': 'Naxcivan', 'AZ36': 'Neftcala', 'AZ37': 'Oguz', 'AZ30': 'Lankaran', 'AZ31': 'Lerik', 'AZ32': 'Masalli', 'JP10': 'Gumma', 'DZ03': 'Batna', 'DZ01': 'Alger', 'DZ06': 'Medea', 'DZ07': 'Mostaganem', 'DZ04': 'Constantine', 'VC05': 'Saint Patrick', 'VC04': 'Saint George', 'NG32': 'Oyo', 'VC06': 'Grenadines', 'VC01': 'Charlotte', 'NG35': 'Adamawa', 'VC03': 'Saint David', 'VC02': 'Saint Andrew', 'USCT': 'Connecticut', 'IL06': 'Yerushalayim', 'USCA': 'California', 'USCO': 'Colorado', 'ZA07': 'Mpumalanga', 'ZA06': 'Gauteng', 'ZA05': 'Eastern Cape', 'TH39': 'Pathum Thani', 'TH38': 'Nonthaburi', 'TH31': 'Narathiwat', 'TH30': 'Sisaket', 'TH33': 'Sing Buri', 'TH32': 'Chai Nat', 'TH35': 'Ang Thong', 'TH34': 'Lop Buri', 'TH37': 'Saraburi', 'TH36': 'Phra Nakhon Si Ayutthaya', 'TN10': 'Qafsah', 'TN15': 'Al Mahdia', 'VN53': 'Ba Ria-Vung Tau', 'TN17': 'Bajah', 'TN16': 'Al Munastir', 'TN19': 'Nabeul', 'TN18': 'Bizerte', 'LC10': 'Vieux-Fort', 'LC11': 'Praslin', 'DK21': 'Syddanmark', 'DK20': 'Sjelland', 'MW17': 'Nkhata Bay', 'MW16': 'Ntcheu', 'MW15': 'Mzimba', 'MW13': 'Mchinji', 'MW12': 'Mangochi', 'MW11': 'Lilongwe', 'MW19': 'Nsanje', 'MW18': 'Nkhotakota', 'TR91': 'Osmaniye', 'TR90': 'Kilis', 'TR93': 'Duzce', 'TR92': 'Yalova', 'YE08': 'Al Hudaydah', 'YE02': 'Adan', 'YE03': 'Al Mahrah', 'YE01': 'Abyan', 'YE06': 'Al Ghaydah', 'YE04': 'Hadramawt', 'YE05': 'Shabwah', 'CZ78': 'Jihomoravsky kraj', 'CZ79': 'Jihocesky kraj', 'BF20': 'Ganzourgou', 'BF21': 'Gnagna', 'BF28': 'Kouritenga', 'GBQ1': 'Wirral', 'SIE9': 'Zavrc', 'SIE3': 'Vodice', 'SIE2': 'Vitanje', 'SIE1': 'Vipava', 'SIE7': 'Zagorje ob Savi', 'SIE6': 'Vuzenica', 'SIE5': 'Vrhnika', 'SE26': 'Stockholms Lan', 'SE27': 'Skane Lan', 'SE24': 'Vasternorrlands Lan', 'SE25': 'Vastmanlands Lan', 'SE22': 'Varmlands Lan', 'SE23': 'Vasterbottens Lan', 'SE21': 'Uppsala Lan', 'SE28': 'Vastra Gotaland', 'LY52': 'Awbari', 'LY53': 'Az Zawiyah', 'LY50': 'Al Khums', 'LY51': 'An Nuqat al Khams', 'AR09': 'Formosa', 'AR08': 'Entre Rios', 'LY54': 'Banghazi', 'LY55': 'Darnah', 'AR05': 'Cordoba', 'AR04': 'Chubut', 'AR07': 'Distrito Federal', 'AR06': 'Corrientes', 'AR01': 'Buenos Aires', 'AR03': 'Chaco', 'AR02': 'Catamarca', 'NE03': 'Dosso', 'NE02': 'Diffa', 'NE01': 'Agadez', 'CA08': 'Ontario', 'CA09': 'Prince Edward Island', 'LR22': 'River Gee', 'NE04': 'Maradi', 'CA04': 'New Brunswick', 'CA05': 'Newfoundland and Labrador', 'CA07': 'Nova Scotia', 'CA01': 'Alberta', 'CA02': 'British Columbia', 'CA03': 'Manitoba', 'GBD7': 'Dudley', 'GBM8': 'Southwark', 'GBM9': 'Staffordshire', 'MD78': 'Ialoveni', 'EE21': 'Vorumaa', 'GBM4': 'Southampton', 'GBM5': 'Southend-on-Sea', 'GBM6': 'South Gloucestershire', 'GBM7': 'South Tyneside', 'MD72': 'Dubasari', 'GBM1': 'Slough', 'GBM2': 'Solihull', 'GBM3': 'Somerset', 'RU09': 'Belgorod', 'RU08': 'Bashkortostan', 'RU07': "Astrakhan'", 'RU06': "Arkhangel'sk", 'RU05': 'Amur', 'RU04': 'Altaisky krai', 'RU03': 'Gorno-Altay', 'RU02': 'Aginsky Buryatsky AO', 'RU01': 'Adygeya', 'PH68': 'Quirino', 'PH69': 'Siquijor', 'PH66': 'Zamboanga del Sur', 'PH67': 'Northern Samar', 'PH64': 'Zambales', 'PH65': 'Zamboanga del Norte', 'PH62': 'Surigao del Sur', 'PH63': 'Tarlac', 'PH60': 'Sulu', 'PH61': 'Surigao del Norte', 'CO24': 'Risaralda', 'CO25': 'San Andres y Providencia', 'CO26': 'Santander', 'CO27': 'Sucre', 'CO20': 'Narino', 'CO21': 'Norte de Santander', 'AZ29': 'Lankaran', 'AZ28': 'Lacin', 'AZ27': 'Kurdamir', 'AZ26': 'Kalbacar', 'AZ25': 'Ismayilli', 'AZ24': 'Imisli', 'AZ23': 'Haciqabul', 'AZ22': 'Goycay', 'AZ21': 'Goranboy', 'AZ20': 'Ganca', 'NG29': 'Kano', 'NG28': 'Imo', 'DZ19': 'Biskra', 'DZ18': 'Bejaia', 'DZ15': 'Tlemcen', 'DZ14': 'Tizi Ouzou', 'NG21': 'Akwa Ibom', 'NG27': 'Borno', 'DZ10': 'Saida', 'DZ13': 'Tiaret', 'DZ12': 'Setif', 'NA05': 'Grootfontein', 'FI14': 'Eastern Finland', 'FI15': 'Western Finland', 'FI13': 'Southern Finland', 'VU10': 'Malakula', 'VU11': 'Paama', 'VU12': 'Pentecote', 'VU13': 'Sanma', 'VU14': 'Shepherd', 'VU15': 'Tafea', 'VU16': 'Malampa', 'VU17': 'Penama', 'NG57': 'Zamfara', 'HT13': 'Sud-Est', 'HT12': 'Sud', 'HT11': 'Ouest', 'HT10': 'Nord-Est', 'BA02': 'Republika Srpska', 'BA01': 'Federation of Bosnia and Herzegovina', 'SIC2': 'Slovenj Gradec', 'USLA': 'Louisiana', 'LC09': 'Soufriere', 'LC08': 'Micoud', 'LC03': 'Castries', 'LC02': 'Dauphin', 'LC01': 'Anse-la-Raye', 'LC07': 'Laborie', 'LC06': 'Gros-Islet', 'LC05': 'Dennery', 'LC04': 'Choiseul', 'ES57': 'Extremadura', 'MW23': 'Zomba', 'MW20': 'Ntchisi', 'MW21': 'Rumphi', 'ES53': 'Canarias', 'MW27': 'Likoma', 'MW24': 'Blantyre', 'MW25': 'Mwanza', 'MW28': 'Machinga', 'MW29': 'Mulanje', 'ES59': 'Pais Vasco', 'ES58': 'Galicia', 'YE15': 'Sa', 'YE14': "Ma'rib", 'YE16': 'San', 'YE11': 'Dhamar', 'YE10': 'Al Mahwit', 'MN19': 'Uvs', 'UG29': 'Bushenyi', 'BF34': 'Passore', 'BF36': 'Sanguie', 'BF33': 'Oudalan', 'MN13': 'Hovsgol', 'AL50': 'Tirane', 'AL51': 'Vlore', 'HR20': 'Zagrebacka', 'HR21': 'Grad Zagreb', 'LY49': 'Al Jabal al Akhdar', 'LY48': 'Al Fatih', 'LY45': 'Zlitan', 'LY47': 'Ajdabiya', 'LY41': 'Tarhunah', 'LY42': 'Tubruq', 'CA14': 'Nunavut', 'CA13': 'Northwest Territories', 'CA12': 'Yukon Territory', 'CA11': 'Saskatchewan', 'CA10': 'Quebec', 'FR99': 'Basse-Normandie', 'FR98': 'Auvergne', 'FR97': 'Aquitaine', 'MD69': 'Criuleni', 'MD68': 'Cimislia', 'GBL9': 'Sheffield', 'GBL8': 'Sefton', 'GBL7': 'Sandwell', 'GBL6': 'Shropshire', 'GBL5': 'Salford', 'GBL4': 'Rutland', 'GBL3': 'Rotherham', 'GBL2': 'Rochdale', 'GBL1': 'Richmond upon Thames', 'MD66': 'Calarasi', 'RU38': 'Krasnodar', 'RU39': 'Krasnoyarsk', 'SIF2': 'Ziri', 'SIF3': 'Zrece', 'SIF1': 'Zelezniki', 'RU32': 'Khanty-Mansiy', 'RU33': 'Kirov', 'RU30': 'Khabarovsk', 'RU31': 'Khakass', 'RU36': 'Koryak', 'RU37': 'Kostroma', 'RU34': 'Komi', 'RU35': 'Komi-Permyak', 'RW12': 'Kigali', 'RW13': 'Nord', 'RW11': 'Est', 'RW14': 'Ouest', 'RW15': 'Sud', 'BO08': 'Santa Cruz', 'MO01': 'Ilhas', 'PH71': 'Sultan Kudarat', 'PH70': 'South Cotabato', 'PH72': 'Tawitawi', 'CO37': 'Caldas', 'CO36': 'Boyaca', 'CO35': 'Bolivar', 'CO34': 'Distrito Especial', 'CO33': 'Cundinamarca', 'CO32': 'Casanare', 'CO31': 'Vichada', 'CO30': 'Vaupes', 'AZ12': 'Beylaqan', 'AZ13': 'Bilasuvar', 'AZ10': 'Balakan', 'AZ11': 'Barda', 'AZ16': 'Daskasan', 'AZ17': 'Davaci', 'AZ14': 'Cabrayil', 'AZ15': 'Calilabad', 'WS02': 'Aiga-i-le-Tai', 'WS03': 'Atua', 'WS06': 'Va', 'WS07': 'Gagaifomauga', 'WS04': 'Fa', 'WS05': 'Gaga', 'WS08': 'Palauli', 'WS09': 'Satupa', 'USMT': 'Montana', 'USMS': 'Mississippi', 'USMP': 'Northern Mariana Islands', 'USMO': 'Missouri', 'FI06': 'Lapland', 'FI01': 'Aland', 'USMH': 'Marshall Islands', 'USME': 'Maine', 'USMD': 'Maryland', 'USMA': 'Massachusetts', 'FI08': 'Oulu', 'PK07': 'Northern Areas', 'PK06': 'Azad Kashmir', 'PK05': 'Sindh', 'PK04': 'Punjab', 'RO38': 'Vaslui', 'RO39': 'Valcea', 'PK01': 'Federally Administered Tribal Areas', 'RO34': 'Suceava', 'RO35': 'Teleorman', 'RO36': 'Timis', 'RO37': 'Tulcea', 'RO30': 'Prahova', 'RO31': 'Salaj', 'RO32': 'Satu Mare', 'RO33': 'Sibiu', 'IR38': 'Qazvin', 'IR39': 'Qom', 'MD51': 'Gagauzia', 'IR34': 'Markazi', 'IR35': 'Mazandaran', 'IR36': 'Zanjan', 'IR37': 'Golestan', 'IR30': 'Khorasan', 'IR31': 'Yazd', 'IR32': 'Ardabil', 'IR33': 'East Azarbaijan', 'MD57': 'Chisinau', 'BB02': 'Saint Andrew', 'BB03': 'Saint George', 'NO20': 'Vestfold', 'BB06': 'Saint Joseph', 'BB07': 'Saint Lucy', 'BB08': 'Saint Michael', 'BB09': 'Saint Peter', 'IS20': 'Nordur-Mulasysla', 'IS21': 'Nordur-Tingeyjarsysla', 'BF59': 'Koulpelogo', 'ES60': 'Comunidad Valenciana', 'MK47': 'Konce', 'MW30': 'Phalombe', 'MK48': 'Kondovo', 'MK49': 'Konopiste', 'BF48': 'Bougouriba', 'BF49': 'Boulgou', 'SC22': 'Saint Louis', 'SC23': 'Takamaka', 'BF40': 'Soum', 'BF42': 'Tapoa', 'BF44': 'Zoundweogo', 'BF45': 'Bale', 'BF46': 'Banwa', 'BF47': 'Bazega', 'AL49': 'Shkoder', 'AL48': 'Lezhe', 'AL47': 'Kukes', 'AL46': 'Korce', 'AL45': 'Gjirokaster', 'AL44': 'Fier', 'AL43': 'Elbasan', 'AL42': 'Durres', 'AL41': 'Diber', 'AL40': 'Berat', 'LK10': 'Kandy', 'LK11': 'Kegalla', 'LK12': 'Kurunegala', 'LK14': 'Matale', 'LK15': 'Matara', 'LK16': 'Moneragala', 'LK17': 'Nuwara Eliya', 'LK18': 'Polonnaruwa', 'LK19': 'Puttalam', 'LV18': 'Limbazu', 'CF11': 'Ouaka', 'CF12': 'Ouham', 'CF13': 'Ouham-Pende', 'CF14': 'Cuvette-Ouest', 'CF15': 'Nana-Grebizi', 'CF16': 'Sangha-Mbaere', 'CF17': 'Ombella-Mpoko', 'CF18': 'Bangui', 'LY30': 'Murzuq', 'LY34': 'Sabha', 'LR01': 'Bong', 'LR06': 'Maryland', 'LR07': 'Monrovia', 'LR04': 'Grand Cape Mount', 'LR05': 'Lofa', 'LR09': 'Nimba', 'CANB': 'New Brunswick', 'RU25': 'Kaluga', 'RU24': 'Kalmyk', 'GBO8': 'Walsall', 'VN83': 'Phu Tho', 'RU21': 'Ivanovo', 'RU20': 'Irkutsk', 'RU23': 'Kaliningrad', 'RU22': 'Kabardin-Balkar', 'GBO2': 'Telford and Wrekin', 'GBO3': 'Thurrock', 'GBO1': 'Tameside', 'RU29': 'Kemerovo', 'RU28': 'Karelia', 'GBO4': 'Torbay', 'GBO5': 'Tower Hamlets', 'SIG4': 'Dobrova-Horjul-Polhov Gradec', 'SIG7': 'Domzale', 'CANL': 'Newfoundland', 'PH40': 'Mindoro Occidental', 'RW09': 'Kigali', 'ZA11': 'Western Cape', 'RW07': 'Kibungo', 'RW06': 'Gitarama', 'RW01': 'Butare', 'GA01': 'Estuaire', 'GA02': 'Haut-Ogooue', 'GA03': 'Moyen-Ogooue', 'GA04': 'Ngounie', 'GA05': 'Nyanga', 'GA06': 'Ogooue-Ivindo', 'GA07': 'Ogooue-Lolo', 'GA08': 'Ogooue-Maritime', 'GA09': 'Woleu-Ntem', 'TT08': 'Saint George', 'TT09': 'Saint Patrick', 'TT04': 'Nariva', 'TT05': 'Port-of-Spain', 'TT06': 'Saint Andrew', 'TT07': 'Saint David', 'TT01': 'Arima', 'TT02': 'Caroni', 'TT03': 'Mayaro', 'CANS': 'Nova Scotia', 'AZ05': 'Agstafa', 'AZ04': 'Agdas', 'AZ07': 'Ali Bayramli', 'AZ06': 'Agsu', 'AZ01': 'Abseron', 'AZ03': 'Agdam', 'AZ02': 'Agcabadi', 'AZ09': 'Baki', 'AZ08': 'Astara', 'CO02': 'Antioquia', 'CO03': 'Arauca', 'CO01': 'Amazonas', 'CO06': 'Boyaca Department', 'CO07': 'Caldas Department', 'CO04': 'Atlantico', 'CO05': 'Bolivar Department', 'CO08': 'Caqueta', 'CO09': 'Cauca', 'WS11': 'Vaisigano', 'WS10': 'Tuamasaga', 'GQ03': 'Annobon', 'GQ04': 'Bioko Norte', 'GQ05': 'Bioko Sur', 'GQ06': 'Centro Sur', 'GQ07': 'Kie-Ntem', 'GQ08': 'Litoral', 'GQ09': 'Wele-Nzas', 'TZ24': 'Rukwa', 'TZ25': 'Zanzibar Urban', 'TZ26': 'Arusha', 'TZ27': 'Manyara', 'TZ20': 'Pemba South', 'TZ21': 'Zanzibar Central', 'RO29': 'Olt', 'TZ23': 'Dar es Salaam', 'RO27': 'Mures', 'RO26': 'Mehedinti', 'RO25': 'Maramures', 'RO23': 'Iasi', 'RO22': 'Ialomita', 'RO21': 'Hunedoara', 'RO20': 'Harghita', 'IR29': 'Kerman', 'IR28': 'Esfahan', 'IR27': 'Zanjan', 'IR26': 'Tehran', 'IR25': 'Semnan', 'IR24': 'Markazi', 'IR23': 'Lorestan', 'IR22': 'Bushehr', 'IR21': 'Zanjan', 'LY56': 'Ghadamis', 'USNY': 'New York', 'USNV': 'Nevada', 'USNJ': 'New Jersey', 'USNH': 'New Hampshire', 'USNM': 'New Mexico', 'USNC': 'North Carolina', 'USND': 'North Dakota', 'USNE': 'Nebraska', 'VU18': 'Shefa', 'NO18': 'Troms', 'NO19': 'Vest-Agder', 'NO16': 'Sor-Trondelag', 'NO17': 'Telemark', 'NO14': 'Rogaland', 'NO15': 'Sogn og Fjordane', 'NO12': 'Oslo', 'NO13': 'Ostfold', 'NO10': 'Nord-Trondelag', 'NO11': 'Oppland', 'NG49': 'Plateau', 'MK44': 'Kisela Voda', 'MK45': 'Klecevce', 'MK46': 'Kocani', 'BF58': 'Kossi', 'MK40': 'Karbinci', 'MK41': 'Karpos', 'MK42': 'Kavadarci', 'MK43': 'Kicevo', 'BF53': 'Kadiogo', 'BF52': 'Ioba', 'BF51': 'Houet', 'BF50': 'Gourma', 'BF57': 'Kompienga', 'BF56': 'Komondjari', 'BF55': 'Komoe', 'BF54': 'Kenedougou', 'BY03': "Hrodzyenskaya Voblasts'", 'BY02': "Homyel'skaya Voblasts'", 'BY01': "Brestskaya Voblasts'", 'BY07': "Vitsyebskaya Voblasts'", 'BY06': "Mahilyowskaya Voblasts'", 'BY05': "Minskaya Voblasts'", 'BY04': 'Minsk', 'LK03': 'Badulla', 'LK02': 'Anuradhapura', 'LK01': 'Amparai', 'LK07': 'Hambantota', 'LK06': 'Galle', 'LK04': 'Batticaloa', 'LK09': 'Kalutara', 'CANT': 'Northwest Territories', 'CANU': 'Nunavut', 'PSGZ': 'Gaza', 'NG43': 'Taraba', 'NG42': 'Osun', 'CF03': 'Haute-Kotto', 'CF02': 'Basse-Kotto', 'CF01': 'Bamingui-Bangoran', 'CF07': 'Lobaye', 'CF06': 'Kemo', 'CF05': 'Haut-Mbomou', 'CF04': 'Mambere-Kadei', 'CF09': 'Nana-Mambere', 'CF08': 'Mbomou', 'KI01': 'Gilbert Islands', 'KI02': 'Line Islands', 'KI03': 'Phoenix Islands', 'HR08': 'Licko-Senjska', 'HR09': 'Medimurska', 'HR06': 'Koprivnicko-Krizevacka', 'HR07': 'Krapinsko-Zagorska', 'HR04': 'Istarska', 'HR05': 'Karlovacka', 'HR02': 'Brodsko-Posavska', 'HR03': 'Dubrovacko-Neretvanska', 'HR01': 'Bjelovarsko-Bilogorska', 'RU50': 'Nenets', 'LR19': 'Grand Gedeh', 'LR18': 'River Cess', 'VN92': 'Dien Bien', 'LR14': 'Montserrado', 'LR17': 'Margibi', 'LR11': 'Grand Bassa', 'LR10': 'Sino', 'LR13': 'Maryland', 'LR12': 'Grand Cape Mount', 'GBN5': 'Suffolk', 'GBN4': 'Stoke-on-Trent', 'GBN7': 'Surrey', 'GBN6': 'Sunderland', 'GBN1': 'St. Helens', 'GBN3': 'Stockton-on-Tees', 'GBN2': 'Stockport', 'GBN9': 'Swindon', 'GBN8': 'Sutton', 'VN93': 'Hau Giang', 'RU51': 'Nizhegorod', 'VN91': 'Dak Nong', 'VN90': 'Lao Cai', 'RU54': 'Omsk', 'RU55': 'Orenburg', 'RU56': 'Orel', 'RU57': 'Penza', 'RU58': "Perm'", 'RU59': "Primor'ye", 'SIH4': 'Jesenice', 'SIH6': 'Kamnik', 'SIH7': 'Kocevje', 'SH01': 'Ascension', 'SH03': 'Tristan da Cunha', 'SH02': 'Saint Helena', 'LI22': 'River Gee', 'LI21': 'Gbarpolu', 'TT12': 'Victoria', 'TT11': 'Tobago', 'TT10': 'San Fernando', 'AZ70': 'Zaqatala', 'AZ71': 'Zardab', 'BS30': 'Kemps Bay', 'BS31': 'Marsh Harbour', 'BS32': 'Nichollstown and Berry Islands', 'BS33': 'Rock Sound', 'CO19': 'Meta', 'DZ43': 'El Oued', 'DZ40': 'Boumerdes', 'DZ41': 'Chlef', 'CO15': 'Guainia', 'CO14': 'Guaviare', 'CO17': 'La Guajira', 'CO16': 'Huila', 'CO11': 'Choco', 'CO10': 'Cesar', 'DZ48': 'Mila', 'DZ49': 'Naama', 'USOH': 'Ohio', 'USOK': 'Oklahoma', 'RO18': 'Galati', 'RO19': 'Gorj', 'USOR': 'Oregon', 'RO12': 'Caras-Severin', 'RO13': 'Cluj', 'RO10': 'Bucuresti', 'RO11': 'Buzau', 'RO16': 'Dambovita', 'RO17': 'Dolj', 'RO14': 'Constanta', 'RO15': 'Covasna', 'IR18': 'Semnan Province', 'IR19': 'Markazi', 'IR12': 'Kerman', 'IR13': 'Bakhtaran', 'IR10': 'Ilam', 'IR11': 'Hormozgan', 'IR16': 'Kordestan', 'IR17': 'Mazandaran', 'IR15': 'Khuzestan', 'NA14': 'Outjo', 'NA15': 'Owambo', 'NA16': 'Rehoboth', 'NA17': 'Swakopmund', 'NA10': 'Maltahohe', 'NA11': 'Okahandja', 'NA12': 'Omaruru', 'NA13': 'Otjiwarongo', 'NA18': 'Tsumeb', 'VE09': 'Delta Amacuro', 'BH08': 'Al Mintaqah al Gharbiyah', 'BH09': 'Mintaqat Juzur Hawar', 'BH02': 'Al Manamah', 'BH01': 'Al Hadd', 'BH06': 'Sitrah', 'BH05': 'Jidd Hafs', 'BD86': 'Sylhet', 'BD84': 'Chittagong', 'BD85': 'Barisal', 'BD82': 'Khulna', 'BD83': 'Rajshahi', 'BD81': 'Dhaka', 'AF26': 'Takhar', 'NO09': 'Nordland', 'NO08': 'More og Romsdal', 'VU09': 'Epi', 'VU08': 'Efate', 'NO01': 'Akershus', 'VE07': 'Carabobo', 'NO02': 'Aust-Agder', 'NO05': 'Finnmark', 'NO04': 'Buskerud', 'NO07': 'Hordaland', 'NO06': 'Hedmark', 'KN13': 'Saint Thomas Middle Island', 'AF29': 'Paktika', 'AF28': 'Zabol', 'ES07': 'Islas Baleares', 'SY04': 'Ar Raqqah', 'SY05': "As Suwayda'", 'SY06': 'Dar', 'SY07': 'Dayr az Zawr', 'SY01': 'Al Hasakah', 'SY02': 'Al Ladhiqiyah', 'SY03': 'Al Qunaytirah', 'SY08': 'Rif Dimashq', 'SY09': 'Halab', 'BF66': 'Nayala', 'BF67': 'Noumbiel', 'BF64': 'Namentenga', 'BF65': 'Naouri', 'BF62': 'Loroum', 'BF63': 'Mouhoun', 'BF60': 'Kourweogo', 'BF61': 'Leraba', 'BF68': 'Oubritenga', 'BF69': 'Poni', 'MK57': 'Kumanovo', 'MK56': 'Kukurecani', 'MK55': 'Kuklis', 'MK54': 'Krusevo', 'MK53': 'Krivogastani', 'MK52': 'Kriva Palanka', 'MK51': 'Kratovo', 'SC09': 'Bel Air', 'SC06': 'Baie Lazare', 'SC07': 'Baie Sainte Anne', 'SC04': 'Anse Louis', 'SC05': 'Anse Royale', 'SC02': 'Anse Boileau', 'SC03': 'Anse Etoile', 'MK59': 'Lipkovo', 'MK58': 'Labunista', 'LK36': 'Western', 'LK34': 'Southern', 'LK35': 'Uva', 'LK32': 'North Western', 'LK33': 'Sabaragamuwa', 'LK30': 'North Central', 'LK31': 'Northern', 'AM11': 'Yerevan', 'LY13': "Ash Shati'", 'HR19': 'Zadarska', 'HR18': 'Vukovarsko-Srijemska', 'HR11': 'Pozesko-Slavonska', 'HR10': 'Osjecko-Baranjska', 'HR13': 'Sibensko-Kninska', 'HR12': 'Primorsko-Goranska', 'HR15': 'Splitsko-Dalmatinska', 'HR14': 'Sisacko-Moslavacka', 'HR17': 'Viroviticko-Podravska', 'HR16': 'Varazdinska', 'GBI1': 'Luton', 'GBI2': 'Manchester', 'GBI3': 'Medway', 'GBI4': 'Merton', 'GBI5': 'Middlesbrough', 'GBI6': 'Milton Keynes', 'GBI7': 'Newcastle upon Tyne', 'GBI8': 'Newham', 'GBI9': 'Norfolk', 'RU43': 'Lipetsk', 'ID10': 'Yogyakarta', 'RU41': 'Kursk', 'RU40': 'Kurgan', 'RU47': 'Moskva', 'RU46': 'Mordovia', 'RU45': 'Mariy-El', 'RU44': 'Magadan', 'RU49': 'Murmansk', 'RU48': 'Moscow City', 'ID12': 'Kalimantan Selatan', 'ID13': 'Kalimantan Tengah', 'SII9': 'Luce', 'SII7': 'Loska Dolina', 'SII6': 'Ljutomer', 'SII5': 'Litija', 'SII3': 'Lenart', 'SII2': 'Kuzma', 'CAON': 'Ontario', 'LI10': 'Triesenberg', 'LI11': 'Vaduz', 'DZ46': 'Illizi', 'DZ47': 'Khenchela', 'DZ44': 'El Tarf', 'DZ45': 'Ghardaia', 'CD12': 'Sud-Kivu', 'CD10': 'Maniema', 'CD11': 'Nord-Kivu', 'DZ42': 'El Bayadh', 'BS35': 'San Salvador and Rum Cay', 'AZ63': 'Xizi', 'SV10': 'San Salvador', 'AZ61': 'Xankandi', 'AZ60': 'Xacmaz', 'AZ67': 'Yevlax', 'AZ66': 'Yardimli', 'AZ65': 'Xocavand', 'AZ64': 'Xocali', 'AZ69': 'Zangilan', 'AZ68': 'Yevlax', 'SV12': 'San Vicente', 'BS23': 'New Providence', 'BS22': 'Harbour Island', 'DZ53': 'Tamanghasset', 'DZ52': 'Souk Ahras', 'BS27': "Governor's Harbour", 'BS26': 'Fresh Creek', 'BS25': 'Freeport', 'BS24': 'Acklins and Crooked Islands', 'BS29': 'High Rock', 'BS28': 'Green Turtle Cay', 'CO12': 'Cordoba', 'BO03': 'El Beni', 'GBU8': 'Edinburgh', 'BO02': 'Cochabamba', 'GBU9': 'Falkirk', 'RO05': 'Bihor', 'RO04': 'Bacau', 'RO07': 'Botosani', 'MY09': 'Pulau Pinang', 'RO01': 'Alba', 'RO03': 'Arges', 'RO02': 'Arad', 'MY02': 'Kedah', 'MY03': 'Kelantan', 'MY01': 'Johor', 'MY06': 'Pahang', 'MY07': 'Perak', 'MY04': 'Melaka', 'MY05': 'Negeri Sembilan', 'TZ02': 'Pwani', 'TZ03': 'Dodoma', 'TZ06': 'Kilimanjaro', 'TZ07': 'Lindi', 'TZ04': 'Iringa', 'TZ05': 'Kigoma', 'TZ08': 'Mara', 'TZ09': 'Mbeya', 'BH15': 'Al Muharraq', 'NA06': 'Kaokoland', 'AT09': 'Wien', 'NA04': 'Gobabis', 'BH11': 'Al Mintaqah al Wusta', 'BH10': 'Al Mintaqah ash Shamaliyah', 'NA01': 'Bethanien', 'BH12': 'Madinat', 'AT03': 'Niederosterreich', 'AT02': 'Karnten', 'AT01': 'Burgenland', 'BH19': 'Al Wusta', 'BH18': 'Ash Shamaliyah', 'AT05': 'Salzburg', 'NA08': 'Keetmanshoop', 'GW06': 'Cacheu', 'GW07': 'Tombali', 'GW04': 'Oio', 'GW05': 'Bolama', 'GR50': 'Khios', 'GR51': 'Lesvos', 'GW01': 'Bafata', 'USHI': 'Hawaii', 'IR05': 'Kohkiluyeh va Buyer Ahmadi', 'IR04': 'Sistan va Baluchestan', 'IR07': 'Fars', 'IR01': 'Azarbayjan-e Bakhtari', 'IR03': 'Chahar Mahall va Bakhtiari', 'IR09': 'Hamadan', 'IR08': 'Gilan', 'TR28': 'Giresun', 'TR24': 'Erzincan', 'TR25': 'Erzurum', 'TR26': 'Eskisehir', 'TR20': 'Denizli', 'TR21': 'Diyarbakir', 'TR22': 'Edirne', 'TR23': 'Elazig', 'SI47': 'Kobilje', 'SY14': 'Tartus', 'SY13': 'Dimashq', 'SY12': 'Idlib', 'SY11': 'Hims', 'SY10': 'Hamah', 'ID41': 'Sulawesi Barat', 'ID40': 'Kepulauan Riau', 'BF71': 'Seno', 'BF70': 'Sanmatenga', 'BF73': 'Sourou', 'BF72': 'Sissili', 'BF75': 'Yagha', 'BF74': 'Tuy', 'BF77': 'Ziro', 'BF76': 'Yatenga', 'DO14': 'Maria Trinidad Sanchez', 'DO15': 'Monte Cristi', 'DO16': 'Pedernales', 'DO17': 'Peravia', 'DO10': 'La Altagracia', 'DO11': 'Elias Pina', 'DO12': 'La Romana', 'MK62': 'Makedonska Kamenica', 'MK63': 'Makedonski Brod', 'MK60': 'Lozovo', 'MK61': 'Lukovo', 'MK66': 'Miravci', 'MK67': 'Mogila', 'MK64': 'Mavrovi Anovi', 'MK65': 'Meseista', 'SC11': 'Cascade', 'SC10': 'Bel Ombre', 'MK68': 'Murtino', 'MK69': 'Negotino', 'SC15': 'La Digue', 'SC14': "Grand' Anse", 'SC17': 'Mont Buxton', 'SC16': 'La Riviere Anglaise', 'NI18': 'Region Autonoma Atlantico Sur', 'NI14': 'Rio San Juan', 'NI15': 'Rivas', 'NI16': 'Zelaya', 'NI17': 'Autonoma Atlantico Norte', 'NI10': 'Managua', 'NI11': 'Masaya', 'NI12': 'Matagalpa', 'NI13': 'Nueva Segovia', 'LK29': 'Central', 'LK28': 'Vavuniya', 'LK21': 'Trincomalee', 'LK20': 'Ratnapura', 'LK23': 'Colombo', 'LK25': 'Jaffna', 'LK24': 'Gampaha', 'LK27': 'Mullaittivu', 'LK26': 'Mannar', 'CM04': 'Est', 'CM05': 'Littoral', 'LY03': 'Al Aziziyah', 'LY05': 'Al Jufrah', 'LY08': 'Al Kufrah', 'SO05': 'Galguduud', 'GBH3': 'Leeds', 'GBH2': 'Lancashire', 'GBH1': 'Lambeth', 'GBH7': 'Lincolnshire', 'GBH6': 'Lewisham', 'GBH5': 'Leicestershire', 'GBH4': 'Leicester', 'GBH9': 'London', 'GBH8': 'Liverpool', 'RU78': "Tyumen'", 'RU79': 'Tuva', 'RU76': 'Tula', 'RU77': "Tver'", 'RU74': 'Taymyr', 'RU75': 'Tomsk', 'RU72': 'Tambovskaya oblast', 'RU73': 'Tatarstan', 'RU70': "Stavropol'", 'RU71': 'Sverdlovsk', 'SIJ9': 'Piran', 'SIJ2': 'Maribor', 'SIJ1': 'Majsperk', 'SIJ7': 'Novo Mesto', 'SIJ5': 'Miren-Kostanjevica', 'LI01': 'Balzers', 'AE03': 'Dubai', 'LI03': 'Gamprin', 'LI02': 'Eschen', 'LI05': 'Planken', 'LI04': 'Mauren', 'LI07': 'Schaan', 'LI06': 'Ruggell', 'LI09': 'Triesen', 'LI08': 'Schellenberg', 'KG02': 'Chuy', 'KG03': 'Jalal-Abad', 'UG28': 'Bundibugyo', 'CD02': 'Equateur', 'KG06': 'Talas', 'KG07': 'Ysyk-Kol', 'KG04': 'Naryn', 'KG05': 'Osh', 'CD09': 'Orientale', 'CD08': 'Bas-Congo', 'KG08': 'Osh', 'KG09': 'Batken', 'UG26': 'Apac', 'AZ58': 'Tovuz', 'AZ59': 'Ucar', 'AZ56': 'Susa', 'AZ57': 'Tartar', 'AZ54': 'Sumqayit', 'AZ55': 'Susa', 'AZ52': 'Samux', 'AZ53': 'Siyazan', 'AZ50': 'Samaxi', 'AZ51': 'Samkir', 'MC03': 'Monte-Carlo', 'BS18': 'Ragged Island', 'BS16': 'Mayaguana', 'BS15': 'Long Island', 'BS13': 'Inagua', 'BS10': 'Exuma', 'KY07': 'West End', 'MO02': 'Macau', 'MY15': 'Labuan', 'MY14': 'Kuala Lumpur', 'MY17': 'Putrajaya', 'MY16': 'Sabah', 'MY11': 'Sarawak', 'MY13': 'Terengganu', 'MY12': 'Selangor', 'USIA': 'Iowa', 'USID': 'Idaho', 'USIN': 'Indiana', 'USIL': 'Illinois', 'PH53': 'Rizal', 'TZ19': 'Kagera', 'TZ18': 'Tanga', 'TZ15': 'Shinyanga', 'TZ14': 'Ruvuma', 'TZ17': 'Tabora', 'TZ16': 'Singida', 'TZ11': 'Mtwara', 'TZ10': 'Morogoro', 'TZ13': 'Pemba North', 'TZ12': 'Mwanza', 'NA32': 'Kunene', 'NA33': 'Ohangwena', 'NA30': 'Hardap', 'NA31': 'Karas', 'NA36': 'Omusati', 'NA37': 'Oshana', 'NA34': 'Okavango', 'NA35': 'Omaheke', 'LA17': 'Louangphrabang', 'NA38': 'Oshikoto', 'NA39': 'Otjozondjupa', 'LA13': 'Xaignabouri', 'LA10': 'Savannakhet', 'LA11': 'Vientiane', 'BJ08': 'Atakora', 'BJ09': 'Atlanyique', 'BJ07': 'Alibori', 'GW11': 'Bissau', 'GW10': 'Gabu', 'GR45': 'Iraklion', 'GW12': 'Biombo', 'GR43': 'Khania', 'GR42': 'Lakonia', 'GR41': 'Arkadhia', 'GR40': 'Messinia', 'GR49': 'Kikladhes', 'GR48': 'Samos', 'USVI': 'Virgin Islands', 'CO18': 'Magdalena Department', 'ES27': 'La Rioja', 'ES29': 'Madrid', 'TR39': 'Kirklareli', 'TR38': 'Kayseri', 'TR37': 'Kastamonu', 'TR35': 'Izmir', 'TR34': 'Istanbul', 'TR33': 'Isparta', 'TR32': 'Mersin', 'TR31': 'Hatay', 'PL81': 'Podlaskie', 'PL83': 'Slaskie', 'NZE9': 'Canterbury', 'NZE8': 'Bay of Plenty', 'NZE7': 'Auckland', 'DO09': 'Independencia', 'DO08': 'Espaillat', 'TH56': 'Phetchaburi', 'DO06': 'Duarte', 'DO05': 'Distrito Nacional', 'DO04': 'Dajabon', 'DO03': 'Barahona', 'DO02': 'Baoruco', 'DO01': 'Azua', 'MK79': 'Petrovec', 'MK78': 'Pehcevo', 'MK75': 'Orasac', 'MK74': 'Ohrid', 'MK77': 'Oslomej', 'MK76': 'Orizari', 'MK71': 'Novaci', 'MK70': 'Negotino-Polosko', 'MK73': 'Oblesevo', 'MK72': 'Novo Selo', 'RU52': 'Novgorod', 'NI09': 'Madriz', 'NI08': 'Leon', 'NI07': 'Jinotega', 'NI06': 'Granada', 'NI05': 'Esteli', 'NI04': 'Chontales', 'NI03': 'Chinandega', 'NI02': 'Carazo', 'NI01': 'Boaco', 'RU53': 'Novosibirsk', 'IQ03': 'Al Muthanna', 'HU41': 'Salgotarjan', 'HU40': 'Zalaegerszeg', 'HU43': 'Erd', 'HU42': 'Szekszard', 'GBK8': 'Redbridge', 'GBK9': 'Redcar and Cleveland', 'GBK6': 'Portsmouth', 'GBK7': 'Reading', 'GBK4': 'Plymouth', 'GBK5': 'Poole', 'GBK2': 'Oxfordshire', 'GBK3': 'Peterborough', 'GBK1': 'Oldham', 'RU69': 'Smolensk', 'RU68': 'North Ossetia', 'SIK7': 'Ptuj', 'RU61': 'Rostov', 'RU60': 'Pskov', 'RU63': 'Sakha', 'RU62': "Ryazan'", 'RU65': 'Samara', 'RU64': 'Sakhalin', 'RU67': 'Saratov', 'RU66': 'Saint Petersburg City', 'SA08': 'Al Qasim', 'SA09': 'Al Qurayyat', 'SA05': 'Al Madinah', 'SA06': 'Ash Sharqiyah', 'SA02': 'Al Bahah', 'SA03': 'Al Jawf', 'SO20': 'Woqooyi Galbeed', 'SO21': 'Awdal', 'SO22': 'Sool', 'CAAB': 'Alberta', 'UG37': 'Kampala', 'UG36': 'Kalangala', 'UG31': 'Hoima', 'UG30': 'Gulu', 'UG33': 'Jinja', 'UG39': 'Kapchorwa', 'UG38': 'Kamuli', 'AZ49': 'Salyan', 'AZ48': 'Saki', 'AZ41': 'Qobustan', 'AZ40': 'Qazax', 'AZ43': 'Qubadli', 'AZ42': 'Quba', 'AZ45': 'Saatli', 'AZ44': 'Qusar', 'AZ47': 'Saki', 'AZ46': 'Sabirabad', 'BS05': 'Bimini', 'BS06': 'Cat Island', 'MA46': 'Fes-Boulemane', 'MA47': 'Marrakech-Tensift-Al Haouz', 'MA45': 'Grand Casablanca', 'MA48': 'Meknes-Tafilalet', 'MA49': 'Rabat-Sale-Zemmour-Zaer', 'VU07': 'Torba', 'VU06': 'Aoba', 'VU05': 'Ambrym', 'LA09': 'Saravan', 'LA08': 'Phongsali', 'NA29': 'Erongo', 'NA28': 'Caprivi', 'LA01': 'Attapu', 'NA24': 'Hereroland Wes', 'LA03': 'Houaphan', 'NA26': 'Mariental', 'LA05': 'Louang Namtha', 'LA04': 'Khammouan', 'LA07': 'Oudomxai', 'NA22': 'Damaraland', 'MR12': 'Inchiri', 'MR10': 'Guidimaka', 'MR11': 'Tiris Zemmour', 'BJ18': 'Zou', 'BJ13': 'Donga', 'BJ12': 'Kouffo', 'BJ11': 'Collines', 'BJ10': 'Borgou', 'BJ17': 'Plateau', 'BJ16': 'Oueme', 'BJ15': 'Mono', 'BJ14': 'Littoral', 'CU08': 'Cienfuegos', 'CU09': 'Granma', 'CU01': 'Pinar del Rio', 'CU02': 'Ciudad de la Habana', 'CU03': 'Matanzas', 'CU04': 'Isla de la Juventud', 'CU05': 'Camaguey', 'CU07': 'Ciego de Avila', 'GE04': 'Ajaria', 'GE05': 'Akhalgoris Raioni', 'GE06': "Akhalk'alak'is Raioni", 'GE07': "Akhalts'ikhis Raioni", 'GE01': 'Abashis Raioni', 'GE02': 'Abkhazia', 'GE03': 'Adigenis Raioni', 'GE08': 'Akhmetis Raioni', 'GE09': 'Ambrolauris Raioni', 'ES31': 'Murcia', 'ES32': 'Navarra', 'ES34': 'Asturias', 'ES39': 'Cantabria', 'TR08': 'Artvin', 'TR09': 'Aydin', 'TR02': 'Adiyaman', 'TR03': 'Afyonkarahisar', 'TR07': 'Antalya', 'TR04': 'Agri', 'TR05': 'Amasya', 'USMI': 'Michigan', 'DO32': 'Monte Plata', 'DO33': 'San Cristobal', 'DO30': 'La Vega', 'DO31': 'Monsenor Nouel', 'DO36': 'San Jose de Ocoa', 'DO37': 'Santo Domingo', 'DO34': 'Distrito Nacional', 'DO35': 'Peravia', 'MK08': 'Bogdanci', 'MK09': 'Bogomila', 'MK01': 'Aracinovo', 'MK02': 'Bac', 'MK03': 'Belcista', 'MK04': 'Berovo', 'MK05': 'Bistrica', 'MK06': 'Bitola', 'MK07': 'Blatec', 'CABC': 'British Columbia', 'RU27': 'Karachay-Cherkess', 'NZF6': 'Northland', 'NZF7': 'Otago', 'NZF4': 'Marlborough', 'NZF5': 'Nelson', 'NZF2': "Hawke's Bay", 'NZF3': 'Manawatu-Wanganui', 'NZF1': 'Gisborne', 'VN46': 'Dong Thap', 'NZF8': 'Southland', 'NZF9': 'Taranaki', 'HU38': 'Tatabanya', 'HU39': 'Veszprem', 'AR14': 'Misiones', 'HU30': 'Kaposvar', 'HU31': 'Kecskemet', 'HU32': 'Nagykanizsa', 'HU33': 'Nyiregyhaza', 'HU34': 'Sopron', 'HU35': 'Szekesfehervar', 'HU36': 'Szolnok', 'HU37': 'Szombathely', 'GBJ9': 'Nottinghamshire', 'GBJ8': 'Nottingham', 'GBJ1': 'Northamptonshire', 'GBJ3': 'North Lincolnshire', 'GBJ2': 'North East Lincolnshire', 'GBJ5': 'North Tyneside', 'GBJ4': 'North Somerset', 'GBJ7': 'North Yorkshire', 'GBJ6': 'Northumberland', 'SIL1': 'Ribnica', 'DM10': 'Saint Paul', 'DM11': 'Saint Peter', 'SIL7': 'Sentjur pri Celju', 'SIL8': 'Slovenska Bistrica', 'SA19': 'Tabuk', 'SA17': 'Jizan', 'SA16': 'Najran', 'SA15': 'Al Hudud ash Shamaliyah', 'SA14': 'Makkah', 'SA13': "Ha'il", 'SD40': 'Al Wahadah State', 'SA10': 'Ar Riyad', 'UG40': 'Kasese', 'UG41': 'Kibale', 'UG42': 'Kiboga', 'UG43': 'Kisoro', 'UG45': 'Kotido', 'UG46': 'Kumi', 'UG47': 'Lira', 'CL12': 'Region Metropolitana', 'MA51': 'Doukkala-Abda', 'MA50': 'Chaouia-Ouardigha', 'MA53': 'Guelmim-Es Smara', 'MA52': 'Gharb-Chrarda-Beni Hssen', 'MA55': 'Souss-Massa-Dr', 'MA54': 'Oriental', 'MA57': 'Tanger-Tetouan', 'MA56': 'Tadla-Azilal', 'MA59': 'La', 'MA58': 'Taza-Al Hoceima-Taounate', 'CL13': 'Tarapaca', 'USKY': 'Kentucky', 'USKS': 'Kansas', 'MR09': 'Tagant', 'MR08': 'Dakhlet Nouadhibou', 'MR01': 'Hodh Ech Chargui', 'MR03': 'Assaba', 'MR02': 'Hodh El Gharbi', 'MR05': 'Brakna', 'MR04': 'Gorgol', 'MR07': 'Adrar', 'MR06': 'Trarza', 'BB11': 'Saint Thomas', 'BB10': 'Saint Philip', 'CU13': 'Las Tunas', 'CU12': 'Holguin', 'CU11': 'La Habana', 'CU10': 'Guantanamo', 'CU16': 'Villa Clara', 'CU15': 'Santiago de Cuba', 'CU14': 'Sancti Spiritus', 'GE17': "Dedop'listsqaros Raioni", 'GE16': "Ch'okhatauris Raioni", 'GE15': "Ch'khorotsqus Raioni", 'GE14': "Chiat'ura", 'GE13': 'Borjomis Raioni', 'GE12': 'Bolnisis Raioni', 'GE11': "Baghdat'is Raioni", 'GE10': 'Aspindzis Raioni', 'GE19': "Dushet'is Raioni", 'GE18': 'Dmanisis Raioni', 'TR15': 'Burdur', 'TR14': 'Bolu', 'TR17': 'Canakkale', 'TR16': 'Bursa', 'TR11': 'Bilecik', 'TR10': 'Balikesir', 'TR13': 'Bitlis', 'TR12': 'Bingol', 'TR19': 'Corum', 'BE10': 'Brabant Wallon', 'BE11': 'Brussels Hoofdstedelijk Gewest', 'BE12': 'Vlaams-Brabant', 'SC08': 'Beau Vallon', 'USTN': 'Tennessee', 'MK50': 'Kosel', 'DO25': 'Santiago', 'DO24': 'San Pedro De Macoris', 'DO27': 'Valverde', 'DO26': 'Santiago Rodriguez', 'DO21': 'Sanchez Ramirez', 'DO20': 'Samana', 'DO23': 'San Juan', 'DO29': 'Hato Mayor', 'DO28': 'El Seibo', 'SC01': 'Anse aux Pins', 'MK19': 'Cesinovo', 'MK18': 'Centar Zupa', 'MK13': 'Cair', 'MK12': 'Brvenica', 'MK11': 'Bosilovo', 'MK10': 'Bogovinje', 'MK17': 'Centar', 'MK16': 'Cegrane', 'MK15': 'Caska', 'MK14': 'Capari', 'BG33': 'Mikhaylovgrad', 'BG38': 'Blagoevgrad', 'BG39': 'Burgas', 'NZG1': 'Waikato', 'ID11': 'Kalimantan Barat', 'NZG3': 'West Coast', 'NZG2': 'Wellington', 'ID14': 'Kalimantan Timur', 'ID15': 'Lampung', 'ID16': 'Maluku', 'ID17': 'Nusa Tenggara Barat', 'ID18': 'Nusa Tenggara Timur', 'ID19': 'Riau', 'GBU4': 'East Ayrshire', 'SV11': 'Santa Ana', 'HU29': 'Hodmezovasarhely', 'SV13': 'Sonsonate', 'SV14': 'Usulutan', 'GBU1': 'Clackmannanshire', 'GBU2': 'Dumfries and Galloway', 'GBU3': 'Dundee City', 'HU23': 'Veszprem', 'HU22': 'Vas', 'HU21': 'Tolna', 'HU20': 'Jasz-Nagykun-Szolnok', 'HU27': 'Dunaujvaros', 'HU26': 'Bekescsaba', 'HU25': 'Gyor', 'HU24': 'Zala', 'MKC4': 'Zitose', 'DM09': 'Saint Patrick', 'DM08': 'Saint Mark', 'DM05': 'Saint John', 'DM04': 'Saint George', 'DM07': 'Saint Luke', 'DM06': 'Saint Joseph', 'DM03': 'Saint David', 'DM02': 'Saint Andrew', 'SD30': 'Ash Shamaliyah', 'SD31': 'Ash Sharqiyah', 'SA20': 'Al Jawf', 'SD33': 'Darfur', 'SD34': 'Kurdufan', 'SD35': 'Upper Nile', 'SO02': 'Banaadir', 'SO03': 'Bari', 'SO01': 'Bakool', 'SO06': 'Gedo', 'SO07': 'Hiiraan', 'SO04': 'Bay', 'CM07': 'Nord-Ouest', 'CM08': 'Ouest', 'CM09': 'Sud-Ouest', 'SO08': 'Jubbada Dhexe', 'SO09': 'Jubbada Hoose', 'PH51': 'Pangasinan', 'LV28': 'Talsu', 'LV29': 'Tukuma', 'LV20': 'Madonas', 'LV21': 'Ogres', 'LV22': 'Preilu', 'LV23': 'Rezekne', 'LV24': 'Rezeknes', 'LV25': 'Riga', 'LV26': 'Rigas', 'LV27': 'Saldus', 'MC01': 'La Condamine', 'MC02': 'Monaco', 'IR42': 'Khorasan-e Razavi', 'UG56': 'Mubende', 'UG59': 'Ntungamo', 'UG58': 'Nebbi', 'PH59': 'Southern Leyte', 'PH58': 'Sorsogon', 'PG18': 'Sandaun', 'PG19': 'Enga', 'PG10': 'East New Britain', 'PG11': 'East Sepik', 'PG12': 'Madang', 'PG13': 'Manus', 'PG14': 'Morobe', 'PG15': 'New Ireland', 'PG16': 'Western Highlands', 'PG17': 'West New Britain', 'RO41': 'Calarasi', 'RO40': 'Vrancea', 'RO43': 'Ilfov', 'RO42': 'Giurgiu', 'GR18': 'Thesprotia', 'GR19': 'Preveza', 'GR10': 'Grevena', 'GR11': 'Kozani', 'GR12': 'Imathia', 'GR13': 'Thessaloniki', 'GR14': 'Kavala', 'GR15': 'Khalkidhiki', 'GR16': 'Pieria', 'GR17': 'Ioannina', 'USTX': 'Texas', 'GE22': 'Goris Raioni', 'GE23': 'Gurjaanis Raioni', 'GE20': 'Gardabanis Raioni', 'GE21': 'Gori', 'GE26': 'Kaspis Raioni', 'GE27': 'Kharagaulis Raioni', 'GE24': 'Javis Raioni', 'GE25': "K'arelis Raioni", 'IR41': 'Khorasan-e Janubi', 'IR40': 'Yazd', 'GE28': 'Khashuris Raioni', 'GE29': 'Khobis Raioni', 'TR60': 'Tokat', 'TR61': 'Trabzon', 'TR62': 'Tunceli', 'TR63': 'Sanliurfa', 'TR64': 'Usak', 'TR65': 'Van', 'TR66': 'Yozgat', 'TR68': 'Ankara', 'TR69': 'Gumushane', 'BE09': 'West-Vlaanderen', 'BE08': 'Oost-Vlaanderen', 'BE07': 'Namur', 'BE06': 'Luxembourg', 'BE05': 'Limburg', 'BE04': 'Liege', 'BE03': 'Hainaut', 'BE01': 'Antwerpen', 'UZ14': 'Toshkent', 'UZ12': 'Surkhondaryo', 'UZ13': 'Toshkent', 'UZ10': 'Samarqand', 'UZ11': 'Sirdaryo', 'AZ33': 'Mingacevir', 'NG39': 'Jigawa', 'MK26': 'Dobrusevo', 'MK27': 'Dolna Banjica', 'MK24': 'Demir Hisar', 'MK25': 'Demir Kapija', 'MK22': 'Delcevo', 'MK23': 'Delogozdi', 'MK20': 'Cucer-Sandevo', 'MK21': 'Debar', 'MV38': 'Kaafu', 'MV39': 'Lhaviyani', 'MK28': 'Dolneni', 'MK29': 'Dorce Petrov', 'NG30': 'Kwara', 'NG31': 'Niger', 'DZ09': 'Oran', 'NG36': 'Delta', 'GM04': 'Upper River', 'GM05': 'Western', 'GM07': 'North Bank', 'GM01': 'Banjul', 'GM02': 'Lower River', 'GM03': 'Central River', 'CAQC': 'Quebec', 'ID03': 'Bengkulu', 'ID02': 'Bali', 'ID01': 'Aceh', 'ID07': 'Jawa Tengah', 'ID06': 'Jawa Barat', 'ID05': 'Jambi', 'ID04': 'Jakarta Raya', 'CO23': 'Quindio', 'ID09': 'Papua', 'ID08': 'Jawa Timur', 'SV03': 'Chalatenango', 'GBT6': 'Aberdeenshire', 'GBT5': 'Aberdeen City', 'GBT4': 'Strabane', 'GBT3': 'Omagh', 'GBT2': 'North Down', 'GBT1': 'Newtownabbey', 'RU42': 'Leningrad', 'SV09': 'San Miguel', 'SV08': 'Morazan', 'GBT9': 'Scottish Borders', 'GBT8': 'Argyll and Bute', 'MV34': 'Gaafu Alifu', 'MV35': 'Gaafu Dhaalu', 'SIN5': 'Zalec', 'SIN2': 'Videm', 'SIN3': 'Vojnik', 'MKA9': 'Vasilevo', 'SD28': "Al Istiwa'iyah", 'MKA3': 'Suto Orizari', 'MKA2': 'Studenicani', 'MKA1': 'Strumica', 'MKA7': 'Topolcani', 'MKA6': 'Tetovo', 'MKA5': 'Tearce', 'MKA4': 'Sveti Nikole', 'CM13': 'Nord', 'CM12': 'Extreme-Nord', 'CM11': 'Centre', 'CM10': 'Adamaoua', 'SO19': 'Togdheer', 'SO18': 'Nugaal', 'CM14': 'Sud', 'SO14': 'Shabeellaha Hoose', 'SO16': 'Woqooyi Galbeed', 'SO11': 'Nugaal', 'SO10': 'Mudug', 'SO13': 'Shabeellaha Dhexe', 'SO12': 'Sanaag', 'LV33': 'Ventspils', 'LV32': 'Ventspils', 'LV31': 'Valmieras', 'LV30': 'Valkas', 'UG69': 'Katakwi', 'UG66': 'Bugiri', 'UG67': 'Busia', 'UG65': 'Adjumani', 'UG60': 'Pallisa', 'UG61': 'Rakai', 'FRA7': 'Haute-Normandie', 'FRA6': 'Franche-Comte', 'FRA5': 'Corse', 'FRA4': 'Champagne-Ardenne', 'FRA3': 'Centre', 'FRA2': 'Bretagne', 'HU10': 'Hajdu-Bihar', 'HU11': 'Heves', 'FRA9': 'Languedoc-Roussillon', 'FRA8': 'Ile-de-France', 'PG09': 'Eastern Highlands', 'PG08': 'Chimbu', 'PG03': 'Milne Bay', 'PG02': 'Gulf', 'PG01': 'Central', 'PG07': 'North Solomons', 'PG06': 'Western', 'PG05': 'Southern Highlands', 'PG04': 'Northern', 'IN30': 'Arunachal Pradesh', 'IN31': 'Mizoram', 'IN32': 'Daman and Diu', 'VN47': 'Kien Giang', 'IN34': 'Bihar', 'IN35': 'Madhya Pradesh', 'IN36': 'Uttar Pradesh', 'IN37': 'Chhattisgarh', 'IN38': 'Jharkhand', 'IN39': 'Uttarakhand', 'USUT': 'Utah', 'VN43': 'An Giang', 'MD67': 'Causeni', 'OM04': 'Ash Sharqiyah', 'OM05': 'Az Zahirah', 'OM06': 'Masqat', 'OM07': 'Musandam', 'OM01': 'Ad Dakhiliyah', 'OM02': 'Al Batinah', 'OM03': 'Al Wusta', 'OM08': 'Zufar', 'GR09': 'Kastoria', 'GR08': 'Florina', 'PHH2': 'Quezon', 'PHH3': 'Negros Occidental', 'GR03': 'Xanthi', 'GR02': 'Rodhopi', 'GR01': 'Evros', 'GR07': 'Pella', 'GR06': 'Kilkis', 'GR05': 'Serrai', 'GR04': 'Drama', 'GE39': 'Ninotsmindis Raioni', 'GE38': "Mts'khet'is Raioni", 'GE35': 'Marneulis Raioni', 'GE34': 'Lentekhis Raioni', 'GE37': 'Mestiis Raioni', 'GE36': 'Martvilis Raioni', 'GE31': "K'ut'aisi", 'GE30': 'Khonis Raioni', 'GE33': "Lanch'khut'is Raioni", 'GE32': 'Lagodekhis Raioni', 'TR73': 'Nigde', 'TR72': 'Mardin', 'TR71': 'Konya', 'TR70': 'Hakkari', 'TR77': 'Bayburt', 'TR76': 'Batman', 'TR75': 'Aksaray', 'TR74': 'Siirt', 'TR79': 'Kirikkale', 'TR78': 'Karaman', 'IE31': 'Wicklow', 'IE30': 'Wexford', 'UZ09': 'Qoraqalpoghiston', 'UZ08': 'Qashqadaryo', 'UZ01': 'Andijon', 'KM01': 'Anjouan', 'UZ03': 'Farghona', 'UZ02': 'Bukhoro', 'UZ05': 'Khorazm', 'UZ04': 'Jizzakh', 'UZ07': 'Nawoiy', 'UZ06': 'Namangan', 'BW10': 'Southern', 'BW11': 'North-West', 'MK31': 'Dzepciste', 'MK30': 'Drugovo', 'MK33': 'Gevgelija', 'MK32': 'Gazi Baba', 'MK35': 'Gradsko', 'MK34': 'Gostivar', 'MK37': 'Izvor', 'MK36': 'Ilinden', 'MK39': 'Kamenjane', 'MK38': 'Jegunovce', 'RU26': 'Kamchatka', 'ID38': 'Sulawesi Selatan', 'ID39': 'Irian Jaya Barat', 'ID36': 'Papua', 'ID37': 'Riau', 'ID34': 'Gorontalo', 'ID35': 'Kepulauan Bangka Belitung', 'ID32': 'Sumatera Selatan', 'ID33': 'Banten', 'ID30': 'Jawa Barat', 'ID31': 'Sulawesi Utara', 'GBW2': 'Renfrewshire', 'GBW3': 'Shetland Islands', 'GBW1': 'Perth and Kinross', 'GBW6': 'Stirling', 'GBW7': 'West Dunbartonshire', 'GBW4': 'South Ayrshire', 'AZ62': 'Xanlar', 'GBW8': 'Eilean Siar', 'GBW9': 'West Lothian', 'MKB6': 'Vranestica', 'MKB7': 'Vrapciste', 'MKB4': 'Vinica', 'MKB5': 'Vitoliste', 'MKB2': 'Velesta', 'MKB3': 'Vevcani', 'MKB1': 'Veles', 'MKB8': 'Vratnica', 'MKB9': 'Vrutok', 'LV06': 'Daugavpils', 'LV07': 'Daugavpils', 'LV04': 'Bauskas', 'LV05': 'Cesu', 'LV02': 'Aluksnes', 'LV03': 'Balvu', 'LV01': 'Aizkraukles', 'LV08': 'Dobeles', 'LV09': 'Gulbenes', 'UG79': 'Kabarole', 'UG78': 'Iganga', 'DZ50': 'Ouargla', 'UG71': 'Masaka', 'UG70': 'Luwero', 'UG73': 'Nakasongola', 'UG72': 'Moyo', 'UG74': 'Sembabule', 'UG77': 'Arua', 'UG76': 'Tororo', 'HU01': 'Bacs-Kiskun', 'FRB3': 'Midi-Pyrenees', 'HU03': 'Bekes', 'HU02': 'Baranya', 'HU05': 'Budapest', 'HU04': 'Borsod-Abauj-Zemplen', 'HU07': 'Debrecen', 'HU06': 'Csongrad', 'HU09': 'Gyor-Moson-Sopron', 'HU08': 'Fejer', 'FRB8': "Provence-Alpes-Cote d'Azur", 'FRB9': 'Rhone-Alpes', 'DZ54': 'Tindouf', 'GBT7': 'Angus', 'SV02': 'Cabanas', 'DZ56': 'Tissemsilt', 'SV01': 'Ahuachapan', 'CAYT': 'Yukon Territory', 'SV07': 'La Union', 'SV06': 'La Paz', 'SV05': 'La Libertad', 'SI08': 'Brezice', 'SV04': 'Cuscatlan', 'IN23': 'Punjab', 'IN22': 'Puducherry', 'IN21': 'Orissa', 'IN20': 'Nagaland', 'IN26': 'Tripura', 'IN25': 'Tamil Nadu', 'IN24': 'Rajasthan', 'IN29': 'Sikkim', 'IN28': 'West Bengal', 'NZ10': 'Chatham Islands', 'TN14': 'El Kef', 'GR36': 'Argolis', 'GR37': 'Korinthia', 'GR34': 'Evvoia', 'GR35': 'Attiki', 'GR32': 'Fokis', 'GR33': 'Voiotia', 'GR30': 'Evritania', 'GR31': 'Aitolia kai Akarnania', 'GR38': 'Akhaia', 'GR39': 'Ilia', 'USVT': 'Vermont', 'GE48': 'Samtrediis Raioni', 'GE49': 'Senakis Raioni', 'USVA': 'Virginia', 'GE40': 'Onis Raioni', 'GE41': "Ozurget'is Raioni", 'GE42': "P'ot'i", 'GE43': 'Qazbegis Raioni', 'GE44': 'Qvarlis Raioni', 'GE45': "Rust'avi", 'GE46': "Sach'kheris Raioni", 'GE47': 'Sagarejos Raioni', 'TR48': 'Mugla', 'TR49': 'Mus', 'TR46': 'Kahramanmaras', 'TR44': 'Malatya', 'TR45': 'Manisa', 'TR43': 'Kutahya', 'TR40': 'Kirsehir', 'TR41': 'Kocaeli', 'SD29': 'Al Khartum', 'MKA8': 'Valandovo', 'BW09': 'South-East', 'BW08': 'North-East', 'BW05': 'Kgatleng', 'BW04': 'Kgalagadi', 'BW06': 'Kweneng', 'BW01': 'Central', 'BW03': 'Ghanzi', 'VN88': 'Dak Lak', 'SD27': 'Al Wusta', 'ID29': 'Maluku Utara', 'ID28': 'Maluku', 'ID21': 'Sulawesi Tengah', 'ID20': 'Sulawesi Selatan', 'ID23': 'Sulawesi Utara', 'ID22': 'Sulawesi Tenggara', 'ID25': 'Sumatera Selatan', 'ID24': 'Sumatera Barat', 'ID26': 'Sumatera Utara', 'AG01': 'Barbuda', 'AG03': 'Saint George', 'AG04': 'Saint John', 'AG05': 'Saint Mary', 'AG06': 'Saint Paul', 'AG07': 'Saint Peter', 'AG08': 'Saint Philip', 'AG09': 'Redonda', 'GBV7': 'North Ayrshire', 'GBV6': 'Moray', 'GBV1': 'Fife', 'MY08': 'Perlis', 'GBV3': 'Highland', 'GBV2': 'Glasgow City', 'RO06': 'Bistrita-Nasaud', 'CV07': 'Ribeira Grande', 'MKC1': 'Zajas', 'KE01': 'Central', 'KE02': 'Coast', 'KE03': 'Eastern', 'MKC5': 'Zletovo', 'KE05': 'Nairobi Area', 'KE06': 'North-Eastern', 'KE07': 'Nyanza', 'KE08': 'Rift Valley', 'KE09': 'Western', 'LV11': 'Jelgava', 'LV10': 'Jekabpils', 'LV13': 'Jurmala', 'LV12': 'Jelgavas', 'LV15': 'Kuldigas', 'LV14': 'Kraslavas', 'LV17': 'Liepajas', 'LV16': 'Liepaja', 'LV19': 'Ludzas', 'RO09': 'Brasov', 'RO08': 'Braila', 'MN25': 'Orhon', 'MN24': 'Govisumber', 'MN23': 'Darhan-Uul', 'MN22': 'Erdenet', 'MN21': 'Bulgan', 'MN20': 'Ulaanbaatar', 'FRC1': 'Alsace', 'ST01': 'Principe', 'ST02': 'Sao Tome', 'BG50': 'Pleven', 'IN18': 'Meghalaya', 'IN19': 'Karnataka', 'IN16': 'Maharashtra', 'IN17': 'Manipur', 'IN14': 'Lakshadweep', 'IN12': 'Jammu and Kashmir', 'IN13': 'Kerala', 'IN10': 'Haryana', 'IN11': 'Himachal Pradesh', 'HU16': 'Pest', 'USWY': 'Wyoming', 'HU17': 'Somogy', 'USWV': 'West Virginia', 'HU14': 'Nograd', 'HU15': 'Pecs', 'USWI': 'Wisconsin', 'BG58': 'Sofiya', 'HU12': 'Komarom-Esztergom', 'TM02': 'Balkan', 'USWA': 'Washington', 'HU13': 'Miskolc', 'KR18': 'Kwangju-jikhalsi', 'FRA1': 'Bourgogne', 'KR14': 'Kyongsang-bukto', 'KR15': 'Taegu-jikhalsi', 'KR16': 'Cholla-namdo', 'KR17': "Ch'ungch'ong-namdo", 'KR10': 'Pusan-jikhalsi', 'KR11': "Seoul-t'ukpyolsi", 'KR12': "Inch'on-jikhalsi", 'KR13': 'Kyonggi-do', 'PG20': 'National Capital', 'HU18': 'Szabolcs-Szatmar-Bereg', 'HU19': 'Szeged', 'GR21': 'Larisa', 'GR20': 'Arta', 'GR23': 'Kardhitsa', 'GR22': 'Trikala', 'GR25': 'Kerkira', 'GR24': 'Magnisia', 'GR27': 'Kefallinia', 'GR26': 'Levkas', 'GR29': 'Fthiotis', 'GR28': 'Zakinthos', 'GE59': 'Tsalkis Raioni', 'GE58': 'Tsalenjikhis Raioni', 'GE53': "T'erjolis Raioni", 'GE52': "T'elavis Raioni", 'GE51': "T'bilisi", 'GE50': 'Sighnaghis Raioni', 'GE57': "Ts'ageris Raioni", 'GE56': 'Tqibuli', 'GE55': "T'ianet'is Raioni", 'GE54': "T'et'ritsqaros Raioni", 'TR59': 'Tekirdag', 'NA07': 'Karibib', 'BH14': 'Madinat Hamad', 'TR50': 'Nevsehir', 'TR53': 'Rize', 'TR52': 'Ordu', 'TR55': 'Samsun', 'TO02': 'Tongatapu', 'TR57': 'Sinop', 'AT08': 'Vorarlberg', 'NA03': 'Boesmanland', 'NA02': 'Caprivi Oos', 'BH13': 'Ar Rifa', 'AT07': 'Tirol', 'AT06': 'Steiermark', 'NA09': 'Luderitz', 'MV05': 'Laamu', 'AT04': 'Oberosterreich', 'MV01': 'Seenu', 'GBQ8': 'Armagh', 'GBQ9': 'Ballymena', 'GBU7': 'East Renfrewshire', 'GBQ2': 'Wokingham', 'GBQ3': 'Wolverhampton', 'GBQ4': 'Worcestershire', 'GBQ5': 'York', 'GBQ6': 'Antrim', 'GBQ7': 'Ards', 'EE06': 'Kohtla-Jarve', 'EE07': 'Laanemaa', 'EE04': 'Jarvamaa', 'MN18': 'Tov', 'EE05': 'Jogevamaa', 'MN12': 'Hovd', 'EE02': 'Hiiumaa', 'MN10': 'Govi-Altay', 'MN11': 'Hentiy', 'MN16': 'Selenge', 'MN17': 'Suhbaatar', 'MN14': 'Omnogovi', 'MN15': 'Ovorhangay', 'GW02': 'Quinara', 'EE01': 'Harjumaa', 'SB10': 'Central', 'SB11': 'Western', 'SB12': 'Choiseul', 'SB13': 'Rennell and Bellona', 'MV36': 'Haa Alifu', 'IN09': 'Gujarat', 'IN01': 'Andaman and Nicobar Islands', 'IN03': 'Assam', 'IN02': 'Andhra Pradesh', 'IN05': 'Chandigarh', 'BS34': 'Sandy Point', 'IN07': 'Delhi', 'IN06': 'Dadra and Nagar Haveli', 'CY04': 'Nicosia', 'CY05': 'Limassol', 'CY06': 'Paphos', 'IN33': 'Goa', 'CY01': 'Famagusta', 'CY02': 'Kyrenia', 'CY03': 'Larnaca', 'MV30': 'Alifu', 'MG04': 'Toamasina', 'MG05': 'Antananarivo', 'MG06': 'Toliara', 'MG01': 'Antsiranana', 'MG02': 'Fianarantsoa', 'MG03': 'Mahajanga', 'KR06': 'Kangwon-do', 'KR05': "Ch'ungch'ong-bukto", 'KR03': 'Cholla-bukto', 'KR01': 'Cheju-do', 'MV31': 'Baa', 'SR14': 'Nickerie', 'SR15': 'Para', 'SR16': 'Paramaribo', 'SR17': 'Saramacca', 'SR10': 'Brokopondo', 'SR11': 'Commewijne', 'SR12': 'Coronie', 'SR13': 'Marowijne', 'SR18': 'Sipaliwini', 'SR19': 'Wanica', 'MV32': 'Dhaalu', 'MV33': 'Faafu ', 'GE64': 'Zugdidis Raioni', 'GE62': "Zestap'onis Raioni", 'GE63': 'Zugdidi', 'GE60': 'Tsqaltubo', 'GE61': 'Vanis Raioni', 'USPR': 'Puerto Rico', 'USPW': 'Palau', 'USPA': 'Pennsylvania', 'GH10': 'Upper East', 'GH11': 'Upper West', 'GBS7': 'Magherafelt', 'BG63': 'Vidin', 'BG62': 'Veliko Turnovo', 'BG61': 'Varna', 'BG60': 'Turgovishte', 'GBS4': 'Limavady', 'BG65': 'Yambol', 'BG64': 'Vratsa', 'GBS5': 'Lisburn', 'SM04': 'Faetano', 'SM05': 'Fiorentino', 'GBP9': 'Windsor and Maidenhead', 'GBP8': 'Wiltshire', 'GBP3': 'Warwickshire', 'GBP2': 'Warrington', 'GBP1': 'Wandsworth', 'GBS1': 'Dungannon', 'GBP7': 'Wigan', 'GBP6': 'West Sussex', 'GBP5': 'Westminster', 'GBP4': 'West Berkshire', 'DJ01': 'Ali Sabieh', 'DJ06': 'Dikhil', 'DJ07': 'Djibouti', 'DJ04': 'Obock', 'DJ05': 'Tadjoura', 'DJ08': 'Arta', 'LY58': 'Misratah', 'LY59': 'Sawfajjin', 'KH30': 'Pailin', 'NL02': 'Friesland', 'NL03': 'Gelderland', 'NL01': 'Drenthe', 'NL06': 'Noord-Brabant', 'NL07': 'Noord-Holland', 'NL04': 'Groningen', 'NL05': 'Limburg', 'NL08': 'Overijssel', 'NL09': 'Utrecht', 'MN05': 'Darhan', 'MN07': 'Dornogovi', 'MN06': 'Dornod', 'MN01': 'Arhangay', 'MN03': 'Bayan-Olgiy', 'MN02': 'Bayanhongor', 'LR20': 'Lofa', 'MN09': 'Dzavhan', 'MN08': 'Dundgovi', 'NE06': 'Tahoua', 'NE05': 'Niamey', 'JM17': 'Kingston', 'CH26': 'Jura', 'SB07': 'Isabel', 'SB06': 'Guadalcanal', 'SB03': 'Malaita', 'SB09': 'Temotu', 'SB08': 'Makira', 'PE23': 'Tacna', 'PE22': 'San Martin', 'PE21': 'Puno', 'PE20': 'Piura', 'PE25': 'Ucayali', 'PE24': 'Tumbes', 'MD79': 'Leova', 'MD76': 'Glodeni', 'PL79': 'Opolskie', 'PL78': 'Mazowieckie', 'MD77': 'Hincesti', 'PL75': 'Lubelskie', 'PL74': 'Lodzkie', 'PL77': 'Malopolskie', 'PL76': 'Lubuskie', 'MD74': 'Falesti', 'PL73': 'Kujawsko-Pomorskie', 'PL72': 'Dolnoslaskie', 'MD75': 'Floresti', 'MD73': 'Edinet', 'MD70': 'Donduseni', 'BF78': 'Zondoma', 'MD71': 'Drochia', 'SC19': 'Plaisance', 'BN08': 'Belait', 'BN09': 'Brunei and Muara', 'SC18': 'Mont Fleuri', 'BN07': 'Alibori', 'KP12': "P'yongyang-si", 'KP13': 'Yanggang-do', 'KP11': "P'yongan-bukto", 'KP17': 'Hamgyong-bukto', 'KP14': "Namp'o-si", 'KP15': "P'yongan-namdo", 'KP18': 'Najin Sonbong-si', 'SC13': "Grand' Anse", 'SC12': 'Glacis', 'GH01': 'Greater Accra', 'GH03': 'Brong-Ahafo', 'GH02': 'Ashanti', 'GH05': 'Eastern', 'GH04': 'Central', 'GH06': 'Northern', 'GH09': 'Western', 'GH08': 'Volta', 'BG56': 'Sliven', 'BG57': 'Smolyan', 'BG54': 'Shumen', 'BG55': 'Silistra', 'BG52': 'Razgrad', 'BG53': 'Ruse', 'RU90': 'Permskiy Kray', 'BG51': 'Plovdiv', 'TM05': 'Mary', 'TM04': 'Lebap', 'TM01': 'Ahal', 'TM03': 'Dashoguz', 'BG59': 'Stara Zagora', 'SE18': 'Sodermanlands Lan', 'HU28': 'Eger', 'RU91': 'Krasnoyarskiy Kray', 'CN11': 'Hunan', 'HT14': "Grand' Anse", 'KH29': 'Batdambang', 'KH25': 'Banteay Meanchey', 'NL15': 'Overijssel', 'NL16': 'Flevoland', 'NL11': 'Zuid-Holland', 'NL10': 'Zeeland', 'LS18': 'Quthing', 'LS19': 'Thaba-Tseka', 'LS10': 'Berea', 'LS11': 'Butha-Buthe', 'LS12': 'Leribe', 'LS13': 'Mafeteng', 'LS14': 'Maseru', 'LS15': 'Mohales Hoek', 'LS16': 'Mokhotlong', 'LS17': 'Qachas Nek', 'GBS6': 'Derry', 'SM01': 'Acquaviva', 'SM02': 'Chiesanuova', 'SM03': 'Domagnano', 'GBS2': 'Fermanagh', 'GBS3': 'Larne', 'SM06': 'Borgo Maggiore', 'SM07': 'San Marino', 'SM08': 'Monte Giardino', 'SM09': 'Serravalle', 'GBS8': 'Moyle', 'GBS9': 'Newry and Mourne', 'CZ90': 'Zlinsky kraj', 'MD90': 'Taraclia', 'MD91': 'Telenesti', 'MD92': 'Ungheni', 'CN18': 'Guizhou', 'CN19': 'Liaoning', 'CN10': 'Hebei', 'SE10': 'Dalarnas Lan', 'CN12': 'Hubei', 'CN13': 'Xinjiang', 'CN14': 'Xizang', 'CN15': 'Gansu', 'CN16': 'Guangxi', 'PE18': 'Moquegua', 'PE19': 'Pasco', 'PE16': 'Loreto', 'PE17': 'Madre de Dios', 'PE14': 'Lambayeque', 'PE15': 'Lima', 'PE12': 'Junin', 'PE13': 'La Libertad', 'PE10': 'Huanuco', 'PE11': 'Ica'}
| 21,486.25
| 85,919
| 0.602339
| 9,765
| 85,945
| 5.301382
| 0.841065
| 0.003709
| 0.000386
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09857
| 0.109617
| 85,945
| 3
| 85,920
| 28,648.333333
| 0.577923
| 0.000244
| 0
| 0
| 0
| 0
| 0.622111
| 0.004097
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
b7b6ad2f30eeeef89f8be32e1b423aba5b40b98c
| 51
|
py
|
Python
|
src/deep_dialog/usersims/__init__.py
|
Yuqing2018/tcbot_python3
|
583ce1b670f7c67669ff437e69eb09832e784da6
|
[
"MIT"
] | null | null | null |
src/deep_dialog/usersims/__init__.py
|
Yuqing2018/tcbot_python3
|
583ce1b670f7c67669ff437e69eb09832e784da6
|
[
"MIT"
] | null | null | null |
src/deep_dialog/usersims/__init__.py
|
Yuqing2018/tcbot_python3
|
583ce1b670f7c67669ff437e69eb09832e784da6
|
[
"MIT"
] | null | null | null |
from .usersim_rule import *
from .realUser import *
| 25.5
| 27
| 0.784314
| 7
| 51
| 5.571429
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137255
| 51
| 2
| 28
| 25.5
| 0.886364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
4d054d1c9024db142794eb18e583cbea3e61dd43
| 125
|
py
|
Python
|
apps/work_order/admin.py
|
joewen85/devops_study
|
6bbfbac7e70f295ef6068393bd9cf7d418ab4417
|
[
"Apache-2.0"
] | null | null | null |
apps/work_order/admin.py
|
joewen85/devops_study
|
6bbfbac7e70f295ef6068393bd9cf7d418ab4417
|
[
"Apache-2.0"
] | null | null | null |
apps/work_order/admin.py
|
joewen85/devops_study
|
6bbfbac7e70f295ef6068393bd9cf7d418ab4417
|
[
"Apache-2.0"
] | 1
|
2020-10-28T09:12:47.000Z
|
2020-10-28T09:12:47.000Z
|
from django.contrib import admin
# Register your models here.
from .models import WorkOrder
admin.site.register(WorkOrder)
| 17.857143
| 32
| 0.808
| 17
| 125
| 5.941176
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128
| 125
| 6
| 33
| 20.833333
| 0.926606
| 0.208
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
4d26e4038ffff6b5c711d810347580c7c6e22de3
| 44
|
py
|
Python
|
Python/Tutorial - 2/strings.py
|
JC2295/FCC_Tutorial_Projects
|
990e1221b2177acb9e4db0264adab518620404a0
|
[
"MIT"
] | null | null | null |
Python/Tutorial - 2/strings.py
|
JC2295/FCC_Tutorial_Projects
|
990e1221b2177acb9e4db0264adab518620404a0
|
[
"MIT"
] | null | null | null |
Python/Tutorial - 2/strings.py
|
JC2295/FCC_Tutorial_Projects
|
990e1221b2177acb9e4db0264adab518620404a0
|
[
"MIT"
] | null | null | null |
print("One")
print("Two")
print("Three")
| 6.285714
| 14
| 0.590909
| 6
| 44
| 4.333333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 44
| 6
| 15
| 7.333333
| 0.684211
| 0
| 0
| 0
| 0
| 0
| 0.255814
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
4d360ecaf65d937ea0be727ba4568099673793e8
| 41
|
py
|
Python
|
eyap/utils/ghtools/__init__.py
|
emin63/eyap
|
783bdede298e63bbafee81b50cd1e899c43f5847
|
[
"BSD-3-Clause"
] | null | null | null |
eyap/utils/ghtools/__init__.py
|
emin63/eyap
|
783bdede298e63bbafee81b50cd1e899c43f5847
|
[
"BSD-3-Clause"
] | 2
|
2017-07-17T03:50:32.000Z
|
2017-08-05T02:39:36.000Z
|
eyap/utils/ghtools/__init__.py
|
emin63/eyap
|
783bdede298e63bbafee81b50cd1e899c43f5847
|
[
"BSD-3-Clause"
] | null | null | null |
"""Additional GitHub specific tools.
"""
| 13.666667
| 36
| 0.707317
| 4
| 41
| 7.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121951
| 41
| 2
| 37
| 20.5
| 0.805556
| 0.804878
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
4d4284d5a0b58c47616dd4e99223550ab8085447
| 166
|
py
|
Python
|
src/core/command.py
|
cfmcdonald-78/Hexcrawler
|
79ca4ab9327abf08de1743612c23eb89aa53a2b9
|
[
"MIT"
] | null | null | null |
src/core/command.py
|
cfmcdonald-78/Hexcrawler
|
79ca4ab9327abf08de1743612c23eb89aa53a2b9
|
[
"MIT"
] | null | null | null |
src/core/command.py
|
cfmcdonald-78/Hexcrawler
|
79ca4ab9327abf08de1743612c23eb89aa53a2b9
|
[
"MIT"
] | 1
|
2021-12-01T01:38:12.000Z
|
2021-12-01T01:38:12.000Z
|
'''
Created on Jul 19, 2012
@author: Chris
'''
class Command(object):
def validate(self, game):
pass
def execute(self, game):
pass
| 12.769231
| 29
| 0.554217
| 20
| 166
| 4.6
| 0.8
| 0.173913
| 0.26087
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053571
| 0.325301
| 166
| 13
| 30
| 12.769231
| 0.767857
| 0.23494
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.4
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
4d5f2fae7694343130816ebc7bceb8f26a914a6d
| 79
|
py
|
Python
|
The Core/At the Crossroads/willYou.py
|
shanemichaelarcaro/codesignal
|
69b0460dbc163091dc115634bbb730da5caf65a9
|
[
"MIT"
] | null | null | null |
The Core/At the Crossroads/willYou.py
|
shanemichaelarcaro/codesignal
|
69b0460dbc163091dc115634bbb730da5caf65a9
|
[
"MIT"
] | null | null | null |
The Core/At the Crossroads/willYou.py
|
shanemichaelarcaro/codesignal
|
69b0460dbc163091dc115634bbb730da5caf65a9
|
[
"MIT"
] | null | null | null |
def willYou(young, beautiful, loved):
return loved != (young and beautiful)
| 39.5
| 41
| 0.721519
| 10
| 79
| 5.7
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164557
| 79
| 2
| 41
| 39.5
| 0.863636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
4da96c829ebc724feb06739ebe6a1d31d5dda9bf
| 49
|
py
|
Python
|
while.py
|
egriswol/astr-119-hw-1
|
e290355de8f48b9def3fdacf4779ac4a3c51a003
|
[
"MIT"
] | null | null | null |
while.py
|
egriswol/astr-119-hw-1
|
e290355de8f48b9def3fdacf4779ac4a3c51a003
|
[
"MIT"
] | 1
|
2018-10-18T17:49:41.000Z
|
2018-10-18T17:49:41.000Z
|
while.py
|
egriswol/astr-119-hw-1
|
e290355de8f48b9def3fdacf4779ac4a3c51a003
|
[
"MIT"
] | 1
|
2018-10-18T01:31:32.000Z
|
2018-10-18T01:31:32.000Z
|
i = 0
while (i<119):
print(i)
i+=10
| 7
| 14
| 0.408163
| 9
| 49
| 2.222222
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206897
| 0.408163
| 49
| 6
| 15
| 8.166667
| 0.482759
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
4de518de130a1d423998bfe32aad3a8e89b7b784
| 171
|
py
|
Python
|
rllib/algorithms/maddpg/__init__.py
|
willfrey/ray
|
288a81b42ef0186ab4db33b30191614a7bdb69f6
|
[
"Apache-2.0"
] | null | null | null |
rllib/algorithms/maddpg/__init__.py
|
willfrey/ray
|
288a81b42ef0186ab4db33b30191614a7bdb69f6
|
[
"Apache-2.0"
] | null | null | null |
rllib/algorithms/maddpg/__init__.py
|
willfrey/ray
|
288a81b42ef0186ab4db33b30191614a7bdb69f6
|
[
"Apache-2.0"
] | 1
|
2019-09-24T16:24:49.000Z
|
2019-09-24T16:24:49.000Z
|
from ray.rllib.algorithms.maddpg.maddpg import (
MADDPGConfig,
MADDPGTrainer,
DEFAULT_CONFIG,
)
__all__ = ["MADDPGConfig", "MADDPGTrainer", "DEFAULT_CONFIG"]
| 21.375
| 61
| 0.730994
| 16
| 171
| 7.4375
| 0.6875
| 0.420168
| 0.537815
| 0.638655
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152047
| 171
| 7
| 62
| 24.428571
| 0.82069
| 0
| 0
| 0
| 0
| 0
| 0.22807
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
1289e9a1e3edba91a08623829d6f72757cbc5c8d
| 136
|
py
|
Python
|
example/geometry/admin.py
|
emelianovss-yandex-praktikum/07_pyplus_django_2
|
09bda00f9c8e9fd1ff0f3a483ecb210041d19a48
|
[
"MIT"
] | null | null | null |
example/geometry/admin.py
|
emelianovss-yandex-praktikum/07_pyplus_django_2
|
09bda00f9c8e9fd1ff0f3a483ecb210041d19a48
|
[
"MIT"
] | null | null | null |
example/geometry/admin.py
|
emelianovss-yandex-praktikum/07_pyplus_django_2
|
09bda00f9c8e9fd1ff0f3a483ecb210041d19a48
|
[
"MIT"
] | 2
|
2021-11-27T08:06:35.000Z
|
2021-11-27T13:52:41.000Z
|
from django.contrib import admin
from geometry.models import Shape
@admin.register(Shape)
class AdminShape(admin.ModelAdmin):
...
| 17
| 35
| 0.772059
| 17
| 136
| 6.176471
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132353
| 136
| 7
| 36
| 19.428571
| 0.889831
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
128e53da4b600437f498e3a40b34bc75e174bc07
| 117
|
py
|
Python
|
marshmallow_helpers/__init__.py
|
hilearn/marsh-enum
|
2003ed850b076cd9d29a340ee44abe1c73aadc66
|
[
"MIT"
] | null | null | null |
marshmallow_helpers/__init__.py
|
hilearn/marsh-enum
|
2003ed850b076cd9d29a340ee44abe1c73aadc66
|
[
"MIT"
] | null | null | null |
marshmallow_helpers/__init__.py
|
hilearn/marsh-enum
|
2003ed850b076cd9d29a340ee44abe1c73aadc66
|
[
"MIT"
] | null | null | null |
from .enum_field import EnumField, RegisteredEnum # noqa
from .marsh_schema import attr_with_schema, derive # noqa
| 39
| 58
| 0.811966
| 16
| 117
| 5.6875
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136752
| 117
| 2
| 59
| 58.5
| 0.90099
| 0.076923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 0
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| null | 0
| 0
| 0
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| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
12932d615b9cdc4848ccdf491cf3ec6f30e667d0
| 6,968
|
py
|
Python
|
creel_portal/api/filters/FN024_Filter.py
|
AdamCottrill/CreelPortal
|
5ec867c4f11b4231c112e8209116b6b96c2830ec
|
[
"MIT"
] | null | null | null |
creel_portal/api/filters/FN024_Filter.py
|
AdamCottrill/CreelPortal
|
5ec867c4f11b4231c112e8209116b6b96c2830ec
|
[
"MIT"
] | null | null | null |
creel_portal/api/filters/FN024_Filter.py
|
AdamCottrill/CreelPortal
|
5ec867c4f11b4231c112e8209116b6b96c2830ec
|
[
"MIT"
] | null | null | null |
import django_filters
from ...models import FN024
from .filter_utils import NumberInFilter, ValueInFilter
class FN024SubFilter(django_filters.FilterSet):
"""A fitlerset that allows us to select subsets of net set objects by
net set attributes."""
prd = ValueInFilter(field_name="prd")
prd__not = ValueInFilter(field_name="prd", exclude=True)
prdtm0 = django_filters.TimeFilter(field_name="prdtm0", help_text="format: HH:MM")
prdtm0__gte = django_filters.TimeFilter(
field_name="prdtm0", lookup_expr="gte", help_text="format: HH:MM"
)
prdtm0__lte = django_filters.TimeFilter(
field_name="prdtm0", lookup_expr="lte", help_text="format: HH:MM"
)
prdtm1 = django_filters.TimeFilter(field_name="prdtm1", help_text="format: HH:MM")
prdtm1__gte = django_filters.TimeFilter(
field_name="prdtm1", lookup_expr="gte", help_text="format: HH:MM"
)
prdtm1__lte = django_filters.TimeFilter(
field_name="prdtm1", lookup_expr="lte", help_text="format: HH:MM"
)
prd_dur__gte = django_filters.NumberFilter(field_name="prd_dur", lookup_expr="gte")
prd_dur__lte = django_filters.NumberFilter(field_name="prd_dur", lookup_expr="lte")
class Meta:
model = FN024
fields = [
"prd",
"prdtm0",
"prdtm1",
"prd_dur",
]
class FN024Filter(FN024SubFilter):
"""Extends the FN024SubFilter to include additional fields that
are associated with parent objects.
"""
# FN011 ATTRIBUTES
year = django_filters.CharFilter(
field_name="daytype__season__creel__year", lookup_expr="exact"
)
year__gte = django_filters.NumberFilter(
field_name="daytype__season__creel__year", lookup_expr="gte"
)
year__lte = django_filters.NumberFilter(
field_name="daytype__season__creel__year", lookup_expr="lte"
)
year__gt = django_filters.NumberFilter(
field_name="daytype__season__creel__year", lookup_expr="gt"
)
year__lt = django_filters.NumberFilter(
field_name="daytype__season__creel__year", lookup_expr="lt"
)
prj_date0 = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date0", help_text="format: yyyy-mm-dd"
)
prj_date0__gte = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date0",
lookup_expr="gte",
help_text="format: yyyy-mm-dd",
)
prj_date0__lte = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date0",
lookup_expr="lte",
help_text="format: yyyy-mm-dd",
)
prj_date1 = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date1", help_text="format: yyyy-mm-dd"
)
prj_date1__gte = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date1",
lookup_expr="gte",
help_text="format: yyyy-mm-dd",
)
prj_date1__lte = django_filters.DateFilter(
field_name="daytype__season__creel__prj_date1",
lookup_expr="lte",
help_text="format: yyyy-mm-dd",
)
prj_cd = ValueInFilter(field_name="daytype__season__creel__prj_cd")
prj_cd__not = ValueInFilter(
field_name="daytype__season__creel__prj_cd", exclude=True
)
prj_cd__like = django_filters.CharFilter(
field_name="daytype__season__creel__prj_cd", lookup_expr="icontains"
)
prj_cd__not_like = django_filters.CharFilter(
field_name="daytype__season__creel__prj_cd",
lookup_expr="icontains",
exclude=True,
)
prj_cd__endswith = django_filters.CharFilter(
field_name="daytype__season__creel__prj_cd", lookup_expr="endswith"
)
prj_cd__not_endswith = django_filters.CharFilter(
field_name="daytype__season__creel__prj_cd",
lookup_expr="endswith",
exclude=True,
)
prj_nm__like = django_filters.CharFilter(
field_name="daytype__season__creel__prj_nm", lookup_expr="icontains"
)
prj_nm__not_like = django_filters.CharFilter(
field_name="daytype__season__creel__prj_nm",
lookup_expr="icontains",
exclude=True,
)
prj_ldr = django_filters.CharFilter(
field_name="daytype__season__creel__prj_ldr__username", lookup_expr="iexact"
)
contmeth = ValueInFilter(field_name="daytype__season__creel__contmeth")
contmeth__not = ValueInFilter(
field_name="daytype__season__creel__contmeth", exclude=True
)
lake = ValueInFilter(field_name="daytype__season__creel__lake__abbrev")
lake__not = ValueInFilter(
field_name="daytype__season__creel__lake__abbrev", exclude=True
)
ssn_date0 = django_filters.DateFilter(
field_name="daytype__season__ssn_date0", help_text="format: yyyy-mm-dd"
)
ssn_date0__gte = django_filters.DateFilter(
field_name="daytype__season__ssn_date0",
lookup_expr="gte",
help_text="format: yyyy-mm-dd",
)
ssn_date0__lte = django_filters.DateFilter(
field_name="daytype__season__ssn_date0",
lookup_expr="lte",
help_text="format: yyyy-mm-dd",
)
ssn_date1 = django_filters.DateFilter(
field_name="daytype__season__ssn_date1", help_text="format: yyyy-mm-dd"
)
ssn_date1__gte = django_filters.DateFilter(
field_name="daytype__season__ssn_date1",
lookup_expr="gte",
help_text="format: yyyy-mm-dd",
)
ssn_date1__lte = django_filters.DateFilter(
field_name="daytype__season__ssn_date1",
lookup_expr="lte",
help_text="format: yyyy-mm-dd",
)
ssn = ValueInFilter(field_name="daytype__season__ssn")
ssn__not = ValueInFilter(field_name="daytype__season__ssn", exclude=True)
ssn__like = django_filters.CharFilter(
field_name="daytype__season__ssn", lookup_expr="icontains"
)
ssn__not_like = django_filters.CharFilter(
field_name="daytype__season__ssn", lookup_expr="icontains", exclude=True
)
ssn_des = ValueInFilter(field_name="daytype__season__ssn_des")
ssn_des__not = ValueInFilter(field_name="daytype__season__ssn_des", exclude=True)
ssn_des__like = django_filters.CharFilter(
field_name="daytype__season__ssn_des", lookup_expr="icontains"
)
ssn_des__not_like = django_filters.CharFilter(
field_name="daytype__season__ssn_des", lookup_expr="icontains", exclude=True
)
dtp = ValueInFilter(field_name="daytype__dtp")
dtp__not = ValueInFilter(field_name="daytype__dtp", exclude=True)
dtp_nm__like = django_filters.CharFilter(
field_name="daytype__dtp_nm", lookup_expr="icontains"
)
dtp_nm__not_like = django_filters.CharFilter(
field_name="daytype__dtp_nm", lookup_expr="icontains", exclude=True
)
class Meta:
model = FN024
fields = [
"prd",
"prdtm0",
"prdtm1",
"prd_dur",
]
| 33.180952
| 87
| 0.695896
| 840
| 6,968
| 5.180952
| 0.104762
| 0.107537
| 0.154412
| 0.192096
| 0.844899
| 0.824449
| 0.768612
| 0.715533
| 0.565257
| 0.492188
| 0
| 0.011542
| 0.204219
| 6,968
| 209
| 88
| 33.339713
| 0.773309
| 0.028846
| 0
| 0.266272
| 0
| 0
| 0.252707
| 0.14934
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.017751
| 0
| 0.349112
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
12c35e34c837e4d87b7e6155a3d32986c86a463f
| 88
|
py
|
Python
|
__init__.py
|
sbalen/TrafficSignsDataset
|
39ae40a0d307ee83af57f70eed43c38bc5d25233
|
[
"Apache-2.0"
] | 1
|
2021-05-05T14:23:34.000Z
|
2021-05-05T14:23:34.000Z
|
__init__.py
|
sbalen/TrafficSignsDataset
|
39ae40a0d307ee83af57f70eed43c38bc5d25233
|
[
"Apache-2.0"
] | null | null | null |
__init__.py
|
sbalen/TrafficSignsDataset
|
39ae40a0d307ee83af57f70eed43c38bc5d25233
|
[
"Apache-2.0"
] | null | null | null |
"""TrafficSignDataset dataset."""
from .TrafficSignsDataset import Trafficsignsdataset
| 22
| 52
| 0.829545
| 6
| 88
| 12.166667
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.079545
| 88
| 3
| 53
| 29.333333
| 0.901235
| 0.306818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
12f7704aea2bda946e46a42c6fdb1b32ab8e104a
| 39
|
py
|
Python
|
pixiv_spider/__init__.py
|
Uzukidd/Pixiv-spider
|
10d21bf8f1e0ec0b0792383ae9e8ae55e77efd17
|
[
"MIT"
] | 1
|
2021-11-12T19:16:56.000Z
|
2021-11-12T19:16:56.000Z
|
pixiv_spider/__init__.py
|
Uzukidd/Pixiv-web-crawler
|
10d21bf8f1e0ec0b0792383ae9e8ae55e77efd17
|
[
"MIT"
] | null | null | null |
pixiv_spider/__init__.py
|
Uzukidd/Pixiv-web-crawler
|
10d21bf8f1e0ec0b0792383ae9e8ae55e77efd17
|
[
"MIT"
] | null | null | null |
# from pixiv_web_crawler import Getters
| 39
| 39
| 0.871795
| 6
| 39
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.914286
| 0.948718
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
4201d4e01f67d6a8af781c7b4dac4cc684c59e89
| 117
|
py
|
Python
|
src/iranlowo/corpus/__init__.py
|
Niger-Volta-LTI/iranlowo
|
0046b61105ffadfff21dd8b37754b9d95177fbf8
|
[
"MIT"
] | 17
|
2019-07-05T20:30:35.000Z
|
2022-02-28T10:00:24.000Z
|
src/iranlowo/corpus/__init__.py
|
Olamyy/iranlowo
|
1feb123988a8afac3ac53c7acfb72df862c4bc18
|
[
"MIT"
] | 17
|
2019-07-06T09:10:10.000Z
|
2020-11-13T08:30:37.000Z
|
src/iranlowo/corpus/__init__.py
|
ruohoruotsi/iranlowo
|
0046b61105ffadfff21dd8b37754b9d95177fbf8
|
[
"MIT"
] | 7
|
2019-07-01T01:59:07.000Z
|
2020-11-27T17:12:46.000Z
|
from .corpus import Corpus, DirectoryCorpus
from .loaders import OweLoader, YorubaBlogCorpus, BBCCorpus, BibeliCorpus
| 58.5
| 73
| 0.854701
| 12
| 117
| 8.333333
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.094017
| 117
| 2
| 73
| 58.5
| 0.943396
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
420b2687d1f426ed1eefef8109dac3c6ae18bab7
| 261
|
py
|
Python
|
workshop/serializers.py
|
shivammaniharsahu/django_api
|
6ffb3d9f70f30f5fd3ae06ec00a6dd7c7783a797
|
[
"bzip2-1.0.6"
] | null | null | null |
workshop/serializers.py
|
shivammaniharsahu/django_api
|
6ffb3d9f70f30f5fd3ae06ec00a6dd7c7783a797
|
[
"bzip2-1.0.6"
] | null | null | null |
workshop/serializers.py
|
shivammaniharsahu/django_api
|
6ffb3d9f70f30f5fd3ae06ec00a6dd7c7783a797
|
[
"bzip2-1.0.6"
] | null | null | null |
from rest_framework import serializers
from .models import Register
class RegisterSerializer(serializers.HyperlinkedModelSerializer):
class Meta:
model = Register
fields = ('id', 'name', 'email', 'contact', 'password', 'confirm_password')
| 29
| 83
| 0.724138
| 25
| 261
| 7.48
| 0.76
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 261
| 8
| 84
| 32.625
| 0.865741
| 0
| 0
| 0
| 0
| 0
| 0.16092
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.166667
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
422b18d573ebb1cb612e410eb429acc8c41c02ef
| 224
|
py
|
Python
|
btc_tracker_engine/helper_functions.py
|
metalerk/4btc
|
ee9ec1a6fcea1b489bd8afa9c3a25c025e022cb0
|
[
"MIT"
] | null | null | null |
btc_tracker_engine/helper_functions.py
|
metalerk/4btc
|
ee9ec1a6fcea1b489bd8afa9c3a25c025e022cb0
|
[
"MIT"
] | null | null | null |
btc_tracker_engine/helper_functions.py
|
metalerk/4btc
|
ee9ec1a6fcea1b489bd8afa9c3a25c025e022cb0
|
[
"MIT"
] | null | null | null |
def rate_diff_percentage(previous_rate, current_rate, percentage=False):
diff_percentage = (current_rate - previous_rate) / previous_rate
if percentage:
return diff_percentage * 100
return diff_percentage
| 44.8
| 72
| 0.772321
| 27
| 224
| 6.037037
| 0.37037
| 0.343558
| 0.196319
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016129
| 0.169643
| 224
| 5
| 73
| 44.8
| 0.860215
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
422b4572706867cc810fb195c7e12772e8a93c86
| 324
|
py
|
Python
|
nngeometry/object/__init__.py
|
amyami187/nngeometry
|
cb516da3f7a019e148f48ff3ef3bed0cdae0d184
|
[
"MIT"
] | 103
|
2020-03-19T08:47:29.000Z
|
2022-03-29T00:54:38.000Z
|
nngeometry/object/__init__.py
|
amyami187/nngeometry
|
cb516da3f7a019e148f48ff3ef3bed0cdae0d184
|
[
"MIT"
] | 29
|
2021-01-07T13:39:20.000Z
|
2022-03-29T14:52:21.000Z
|
nngeometry/object/__init__.py
|
amyami187/nngeometry
|
cb516da3f7a019e148f48ff3ef3bed0cdae0d184
|
[
"MIT"
] | 11
|
2020-11-09T01:07:12.000Z
|
2022-03-29T00:54:41.000Z
|
from .pspace import (PMatDense, PMatBlockDiag, PMatDiag,
PMatLowRank, PMatImplicit,
PMatKFAC, PMatEKFAC, PMatQuasiDiag)
from .vector import (PVector, FVector)
from .fspace import (FMatDense,)
from .map import (PushForwardDense, PushForwardImplicit,
PullBackDense)
| 40.5
| 56
| 0.66358
| 26
| 324
| 8.269231
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.265432
| 324
| 7
| 57
| 46.285714
| 0.903361
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.571429
| 0
| 0.571429
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
4248c96a6cf8583046ad1cd239d37aa7ac5e5d96
| 740
|
py
|
Python
|
terrascript/resource/ddelnano/mikrotik.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 507
|
2017-07-26T02:58:38.000Z
|
2022-01-21T12:35:13.000Z
|
terrascript/resource/ddelnano/mikrotik.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 135
|
2017-07-20T12:01:59.000Z
|
2021-10-04T22:25:40.000Z
|
terrascript/resource/ddelnano/mikrotik.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 81
|
2018-02-20T17:55:28.000Z
|
2022-01-31T07:08:40.000Z
|
# terrascript/resource/ddelnano/mikrotik.py
# Automatically generated by tools/makecode.py (24-Sep-2021 15:21:43 UTC)
import terrascript
class mikrotik_bgp_instance(terrascript.Resource):
pass
class mikrotik_bgp_peer(terrascript.Resource):
pass
class mikrotik_dhcp_lease(terrascript.Resource):
pass
class mikrotik_dns_record(terrascript.Resource):
pass
class mikrotik_pool(terrascript.Resource):
pass
class mikrotik_scheduler(terrascript.Resource):
pass
class mikrotik_script(terrascript.Resource):
pass
__all__ = [
"mikrotik_bgp_instance",
"mikrotik_bgp_peer",
"mikrotik_dhcp_lease",
"mikrotik_dns_record",
"mikrotik_pool",
"mikrotik_scheduler",
"mikrotik_script",
]
| 17.209302
| 73
| 0.754054
| 85
| 740
| 6.258824
| 0.364706
| 0.285714
| 0.302632
| 0.315789
| 0.406015
| 0
| 0
| 0
| 0
| 0
| 0
| 0.019231
| 0.156757
| 740
| 42
| 74
| 17.619048
| 0.833333
| 0.152703
| 0
| 0.291667
| 1
| 0
| 0.195513
| 0.033654
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.291667
| 0.041667
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
426e9a71b5a0425ef77735be32bb8398f28a2e1e
| 45
|
py
|
Python
|
ceefax/fonts/size7extracondensed/__init__.py
|
mscroggs/CEEFAX
|
8e7a075de1809064b77360da24ebbbaa409c3bf2
|
[
"MIT"
] | 1
|
2020-03-28T15:53:22.000Z
|
2020-03-28T15:53:22.000Z
|
ceefax/fonts/size7extracondensed/__init__.py
|
mscroggs/CEEFAX
|
8e7a075de1809064b77360da24ebbbaa409c3bf2
|
[
"MIT"
] | 1
|
2021-02-05T13:43:52.000Z
|
2021-02-05T13:43:52.000Z
|
ceefax/fonts/size7extracondensed/__init__.py
|
mscroggs/CEEFAX
|
8e7a075de1809064b77360da24ebbbaa409c3bf2
|
[
"MIT"
] | null | null | null |
from .default import size7extracondensedfont
| 22.5
| 44
| 0.888889
| 4
| 45
| 10
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02439
| 0.088889
| 45
| 1
| 45
| 45
| 0.95122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
427b0f2bb086452498a9bfd3a4dc95c14c7879d6
| 127
|
py
|
Python
|
src/tarski/fstrips/contingent/__init__.py
|
phoeft670/tarski
|
7d955e535fbbca012bfd1a12402b97febc6b35b9
|
[
"Apache-2.0"
] | 29
|
2018-11-26T20:31:04.000Z
|
2021-12-29T11:08:40.000Z
|
src/tarski/fstrips/contingent/__init__.py
|
phoeft670/tarski
|
7d955e535fbbca012bfd1a12402b97febc6b35b9
|
[
"Apache-2.0"
] | 101
|
2018-06-07T13:10:01.000Z
|
2022-03-11T11:54:00.000Z
|
src/tarski/fstrips/contingent/__init__.py
|
phoeft670/tarski
|
7d955e535fbbca012bfd1a12402b97febc6b35b9
|
[
"Apache-2.0"
] | 18
|
2018-11-01T22:44:39.000Z
|
2022-02-28T04:57:15.000Z
|
from .problem import ContingentProblem as Problem
from .. action import Action
from .sensor import Sensor
from . import errors
| 25.4
| 49
| 0.811024
| 17
| 127
| 6.058824
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149606
| 127
| 4
| 50
| 31.75
| 0.953704
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
42abdb34b5121a34132a5ff61f5b37cf1ca828bc
| 53
|
py
|
Python
|
scripts/rnn/gru/__init__.py
|
bfeng/CryptoGRU
|
65f6fe9eba981fea65fc665ff16938bf3a593001
|
[
"MIT"
] | 1
|
2022-01-12T03:18:55.000Z
|
2022-01-12T03:18:55.000Z
|
scripts/rnn/gru/__init__.py
|
bfeng/CryptoGRU
|
65f6fe9eba981fea65fc665ff16938bf3a593001
|
[
"MIT"
] | null | null | null |
scripts/rnn/gru/__init__.py
|
bfeng/CryptoGRU
|
65f6fe9eba981fea65fc665ff16938bf3a593001
|
[
"MIT"
] | null | null | null |
from .grucell import MyGRUCell
from .gru import MyGRU
| 26.5
| 30
| 0.830189
| 8
| 53
| 5.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132075
| 53
| 2
| 31
| 26.5
| 0.956522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
35fbe8e8b4f1e1aa102f85306945ce878960b4de
| 52
|
py
|
Python
|
tests/conftest.py
|
grintor/Hello-Wolrd-CI
|
1f1b8c40f55d0b35cd73601ed90567a84abf03db
|
[
"Apache-2.0"
] | null | null | null |
tests/conftest.py
|
grintor/Hello-Wolrd-CI
|
1f1b8c40f55d0b35cd73601ed90567a84abf03db
|
[
"Apache-2.0"
] | null | null | null |
tests/conftest.py
|
grintor/Hello-Wolrd-CI
|
1f1b8c40f55d0b35cd73601ed90567a84abf03db
|
[
"Apache-2.0"
] | null | null | null |
# see: https://stackoverflow.com/a/34520971/3238695
| 26
| 51
| 0.769231
| 7
| 52
| 5.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.306122
| 0.057692
| 52
| 1
| 52
| 52
| 0.510204
| 0.942308
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
c40ce4ea8967938d11ba63e971d617289f172e0d
| 22
|
py
|
Python
|
Python/SCRIPT PYTHON/Hello.py
|
guimaraesalves/material-python
|
d56b6b24ae35a67d394b43cb1ef4420805c7bd9b
|
[
"MIT"
] | null | null | null |
Python/SCRIPT PYTHON/Hello.py
|
guimaraesalves/material-python
|
d56b6b24ae35a67d394b43cb1ef4420805c7bd9b
|
[
"MIT"
] | null | null | null |
Python/SCRIPT PYTHON/Hello.py
|
guimaraesalves/material-python
|
d56b6b24ae35a67d394b43cb1ef4420805c7bd9b
|
[
"MIT"
] | null | null | null |
print ("Hello Word!")
| 11
| 21
| 0.636364
| 3
| 22
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 22
| 1
| 22
| 22
| 0.736842
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
6748094d5dca0ac93c047a1471d4c4dfa641d3ad
| 112
|
py
|
Python
|
0702 In-Place Move Zeros to End of List.py
|
ansabgillani/binarysearchcomproblems
|
12fe8632f8cbb5058c91a55bae53afa813a3247e
|
[
"MIT"
] | 1
|
2020-12-29T21:17:26.000Z
|
2020-12-29T21:17:26.000Z
|
0702 In-Place Move Zeros to End of List.py
|
ansabgillani/binarysearchcomproblems
|
12fe8632f8cbb5058c91a55bae53afa813a3247e
|
[
"MIT"
] | null | null | null |
0702 In-Place Move Zeros to End of List.py
|
ansabgillani/binarysearchcomproblems
|
12fe8632f8cbb5058c91a55bae53afa813a3247e
|
[
"MIT"
] | 4
|
2021-09-09T17:42:43.000Z
|
2022-03-18T04:54:03.000Z
|
class Solution:
def solve(self, nums):
return [num for num in nums if num != 0] + [0]*nums.count(0)
| 28
| 68
| 0.598214
| 19
| 112
| 3.526316
| 0.684211
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036145
| 0.258929
| 112
| 3
| 69
| 37.333333
| 0.771084
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
67525ed3e9b1efee9050769baa49e34f54d058e4
| 7,215
|
py
|
Python
|
tests/st/fallback/control_flow/test_fallback_010_if_in_if.py
|
httpsgithu/mindspore
|
c29d6bb764e233b427319cb89ba79e420f1e2c64
|
[
"Apache-2.0"
] | 1
|
2022-02-23T09:13:43.000Z
|
2022-02-23T09:13:43.000Z
|
tests/st/fallback/control_flow/test_fallback_010_if_in_if.py
|
949144093/mindspore
|
c29d6bb764e233b427319cb89ba79e420f1e2c64
|
[
"Apache-2.0"
] | null | null | null |
tests/st/fallback/control_flow/test_fallback_010_if_in_if.py
|
949144093/mindspore
|
c29d6bb764e233b427319cb89ba79e420f1e2c64
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
""" test graph fallback control flow if in if scenario"""
import pytest
import numpy as np
from mindspore import Tensor, ms_function, context
context.set_context(mode=context.GRAPH_MODE)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_1():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(1)
y = Tensor(2)
if x > Tensor(0):
if y > Tensor(1):
return y + 1
return x + 1
return x + y
res = control_flow_if_in_if()
assert res == 3
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_2():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(1)
y = Tensor(0)
if x > Tensor(0):
if y > Tensor(1):
return y + 1
return x + 1
return x + y
res = control_flow_if_in_if()
assert res == 2
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_3():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(-2)
y = Tensor(-3)
if x > Tensor(0):
if y > Tensor(1):
return y + 1
return x + 1
return x + y
res = control_flow_if_in_if()
assert res == -5
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_4():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = np.array([1, 2, 3, 4, 5])
y = x % 2
z = Tensor(y)
if (x >= y).all():
if sum(z) > Tensor(2):
z = Tensor(x) + 1
return z
res = control_flow_if_in_if()
assert np.all(res.asnumpy() == np.array([2, 3, 4, 5, 6]))
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_5():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = list([1, 2, 3, 4])
if max(x) >= 4:
y = Tensor(sum(x) + max(x))
if y < Tensor(10):
return y
return y - 10
return x
res = control_flow_if_in_if()
assert res == 4
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_else_in_if_else_1():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(10)
y = Tensor(7)
if x - y > Tensor(np.array([0])):
x = x - Tensor(3)
if x - y > Tensor(0):
x = x - Tensor(4)
else:
x = x + Tensor(4)
x = x * 2
return x - 1
res = control_flow_if_in_if()
assert res == 21
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_else_in_if_else_2():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(10)
y = Tensor(7)
if x - y > Tensor(np.array([10])):
x = x - Tensor(3)
if x - y > Tensor(0):
x = x - Tensor(4)
else:
x = x + Tensor(4)
x = x * 2
else:
if x > Tensor(15):
m = np.array([1, 2, 3, 4, 5])
elif x < Tensor(-10):
return Tensor(sum(np.array([5, 4, 3, 2, 1])))
else:
m = np.array([-1, -2, -3, -4, -5])
x = Tensor(sum(m))
return x - 1
res = control_flow_if_in_if()
assert res == -16
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_multi_conds():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = np.array([1, 2, 3, 4])
y = np.array([4, 5, 6])
if max(x) <= min(y) and sum(x) == 10:
x += 3
if max(x) <= max(y):
m = Tensor(10)
elif min(x) != max(y) or x.size > y.size:
m = Tensor(20)
else:
m = Tensor(0)
else:
m = Tensor(1)
return m
res = control_flow_if_in_if()
assert res == 20
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_if_in_if_multi_conds_2():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_if_in_if():
x = Tensor(10)
y = Tensor(2)
if x > y and x % y == Tensor(0):
x -= Tensor(3)
if x < y:
m = Tensor(10)
elif x > y or x % y == Tensor(0):
m = Tensor(20)
else:
m = x + y
else:
m = Tensor(0)
return m
res = control_flow_if_in_if()
assert res == 20
| 27.43346
| 78
| 0.595981
| 1,015
| 7,215
| 4.02266
| 0.129064
| 0.110213
| 0.11903
| 0.069802
| 0.773206
| 0.752143
| 0.749204
| 0.742591
| 0.729121
| 0.729121
| 0
| 0.035101
| 0.289258
| 7,215
| 262
| 79
| 27.538168
| 0.761115
| 0.214137
| 0
| 0.688525
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04918
| 1
| 0.098361
| false
| 0
| 0.016393
| 0
| 0.213115
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
675926d38ebca3605bde9778baaa7d1ff647176f
| 95
|
py
|
Python
|
pickle_storage/tests/__init__.py
|
PyUnchained/pickle_storage
|
c0a978701ae59a9feeb3e14026ff0b2353b2e7f5
|
[
"MIT"
] | null | null | null |
pickle_storage/tests/__init__.py
|
PyUnchained/pickle_storage
|
c0a978701ae59a9feeb3e14026ff0b2353b2e7f5
|
[
"MIT"
] | null | null | null |
pickle_storage/tests/__init__.py
|
PyUnchained/pickle_storage
|
c0a978701ae59a9feeb3e14026ff0b2353b2e7f5
|
[
"MIT"
] | null | null | null |
# import os
# os.environ.setdefault('PICKLE_STORAGE_SETTINGS', 'pickle_storage.tests.settings')
| 47.5
| 83
| 0.810526
| 12
| 95
| 6.166667
| 0.666667
| 0.351351
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 95
| 2
| 83
| 47.5
| 0.822222
| 0.957895
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
67607806f4f757a440672ca409795cb6fc24a8c8
| 97
|
py
|
Python
|
src/__init__.py
|
PY-GZKY/fconversion
|
f1da069ac258444c8a6b2a5fe77d0e1295a0d4e4
|
[
"Apache-2.0"
] | 1
|
2022-02-11T09:39:08.000Z
|
2022-02-11T09:39:08.000Z
|
src/__init__.py
|
PY-GZKY/fconversion
|
f1da069ac258444c8a6b2a5fe77d0e1295a0d4e4
|
[
"Apache-2.0"
] | null | null | null |
src/__init__.py
|
PY-GZKY/fconversion
|
f1da069ac258444c8a6b2a5fe77d0e1295a0d4e4
|
[
"Apache-2.0"
] | null | null | null |
from .file_core import FileEngine
from src.utils.utils import *
from .version import __version__
| 24.25
| 33
| 0.824742
| 14
| 97
| 5.357143
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.123711
| 97
| 3
| 34
| 32.333333
| 0.882353
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
6785ebdaa0a0f8a5a088b840a1b64f1e5c59a6a9
| 6,046
|
py
|
Python
|
src/config/svc-monitor/svc_monitor/tests/test_port_tuple.py
|
UbuntuEvangelist/contrail-controller
|
4e8a992230f8f8e91e4f753e19b5442d9e1b446d
|
[
"Apache-2.0"
] | null | null | null |
src/config/svc-monitor/svc_monitor/tests/test_port_tuple.py
|
UbuntuEvangelist/contrail-controller
|
4e8a992230f8f8e91e4f753e19b5442d9e1b446d
|
[
"Apache-2.0"
] | null | null | null |
src/config/svc-monitor/svc_monitor/tests/test_port_tuple.py
|
UbuntuEvangelist/contrail-controller
|
4e8a992230f8f8e91e4f753e19b5442d9e1b446d
|
[
"Apache-2.0"
] | 18
|
2017-01-12T09:28:44.000Z
|
2019-04-18T20:47:42.000Z
|
import mock
from mock import patch
import unittest
from vnc_api.vnc_api import *
from svc_monitor.port_tuple import PortTupleAgent
from svc_monitor.config_db import *
import test_common_utils as test_utils
class PortTupleTest(unittest.TestCase):
def setUp(self):
InstanceIpSM._cassandra = mock.MagicMock()
InstanceIpSM._cassandra.object_read = test_utils.iip_db_read
ServiceInstanceSM._cassandra = mock.MagicMock()
ServiceInstanceSM._cassandra.object_read = test_utils.si_db_read
VirtualMachineInterfaceSM._cassandra = mock.MagicMock()
VirtualMachineInterfaceSM._cassandra.object_read = test_utils.vmi_db_read
self.mocked_vnc = mock.MagicMock()
self.mocked_vnc.fq_name_to_id = test_utils.get_vn_id_for_fq_name
self.mocked_vnc.instance_ip_create = test_utils.iip_create
self.pt_agent = PortTupleAgent(
svc_mon=mock.MagicMock(), vnc_lib=self.mocked_vnc,
cassandra=mock.MagicMock(), config_section=mock.MagicMock(),
logger=mock.MagicMock())
def tearDown(self):
ServiceTemplateSM.reset()
ServiceInstanceSM.reset()
InstanceIpSM.reset()
del InstanceIpSM._cassandra
ServiceInstanceSM.reset()
del ServiceInstanceSM._cassandra
VirtualMachineInterfaceSM.reset()
del VirtualMachineInterfaceSM._cassandra
def test_single_vm_port_tuple_create(self):
test_utils.create_test_project('fake-domain:fake-project')
test_utils.create_test_virtual_network('fake-domain:fake-project:public-vn')
test_utils.create_test_virtual_network('fake-domain:fake-project:fake-vn-uuid')
st = test_utils.create_test_st(name='fake-st-uuid',
intf_list=[['right', True], ['left', True]], version='2')
si = test_utils.create_test_si(name='fake-si-uuid', count=1,
intf_list=['public-vn', 'fake-vn-uuid'])
si.service_template = 'fake-st-uuid'
pt = test_utils.create_test_port_tuple(
'fake-domain:fake-project:fake-si-uuid:fake-port-tuple',
'fake-si-uuid')
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-left', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'left'
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-right', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'right'
self.pt_agent.update_port_tuple(pt_id='fake-port-tuple')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-left',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-right',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('service-instance',
'fake-si-uuid', 'instance-ip', 'fake-iip-uuid', None, 'ADD',
ServiceInterfaceTag('left'))
self.mocked_vnc.ref_update.assert_any_call('service-instance',
'fake-si-uuid', 'instance-ip', 'fake-iip-uuid', None, 'ADD',
ServiceInterfaceTag('right'))
def test_two_vm_port_tuple_create(self):
test_utils.create_test_project('fake-domain:fake-project')
test_utils.create_test_virtual_network('fake-domain:fake-project:public-vn')
test_utils.create_test_virtual_network('fake-domain:fake-project:fake-vn-uuid')
st = test_utils.create_test_st(name='fake-st-uuid',
intf_list=[['right', True], ['left', True]], version='2')
si = test_utils.create_test_si(name='fake-si-uuid', count=1,
intf_list=['public-vn', 'fake-vn-uuid'])
si.service_template = 'fake-st-uuid'
pt = test_utils.create_test_port_tuple(
'fake-domain:fake-project:fake-si-uuid:fake-port-tuple1',
'fake-si-uuid')
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-left1', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'left'
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-right1', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'right'
self.pt_agent.update_port_tuple(pt_id='fake-port-tuple1')
si.service_template = 'fake-st-uuid'
pt = test_utils.create_test_port_tuple(
'fake-domain:fake-project:fake-si-uuid:fake-port-tuple2',
'fake-si-uuid')
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-left2', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'left'
vmi = test_utils.create_test_vmi('fake-domain:fake-project:fake-vmi-uuid-right2', pt)
vmi.params = {}
vmi.params['service_interface_type'] = 'right'
self.pt_agent.update_port_tuple(pt_id='fake-port-tuple2')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-left1',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-right1',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-left2',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('instance-ip',
'fake-iip-uuid', 'virtual-machine-interface', 'fake-vmi-uuid-right2',
None, 'ADD')
self.mocked_vnc.ref_update.assert_any_call('service-instance',
'fake-si-uuid', 'instance-ip', 'fake-iip-uuid', None, 'ADD',
ServiceInterfaceTag('left'))
self.mocked_vnc.ref_update.assert_any_call('service-instance',
'fake-si-uuid', 'instance-ip', 'fake-iip-uuid', None, 'ADD',
ServiceInterfaceTag('right'))
| 48.368
| 93
| 0.664406
| 782
| 6,046
| 4.886189
| 0.121483
| 0.058885
| 0.074588
| 0.094478
| 0.737765
| 0.715781
| 0.715781
| 0.715781
| 0.715781
| 0.715781
| 0
| 0.003309
| 0.200298
| 6,046
| 124
| 94
| 48.758065
| 0.78697
| 0
| 0
| 0.554545
| 0
| 0
| 0.27605
| 0.148528
| 0
| 0
| 0
| 0
| 0.090909
| 1
| 0.036364
| false
| 0
| 0.063636
| 0
| 0.109091
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
67a4b479d6f75f2f17d3b85691a149733addfde8
| 7,560
|
py
|
Python
|
tests/test_data_gateway/test_dummy_serial.py
|
aerosense-ai/data-gateway
|
019b8e4a114e16d363a3167171a457cefdbf004f
|
[
"Apache-2.0"
] | null | null | null |
tests/test_data_gateway/test_dummy_serial.py
|
aerosense-ai/data-gateway
|
019b8e4a114e16d363a3167171a457cefdbf004f
|
[
"Apache-2.0"
] | 34
|
2021-12-20T14:51:57.000Z
|
2022-03-30T16:47:04.000Z
|
tests/test_data_gateway/test_dummy_serial.py
|
aerosense-ai/data-gateway
|
019b8e4a114e16d363a3167171a457cefdbf004f
|
[
"Apache-2.0"
] | null | null | null |
import random
import unittest
from serial.serialutil import SerialException
from data_gateway.dummy_serial import DummySerial, constants, exceptions, random_bytes, random_string
from tests.base import BaseTestCase
class DummySerialTest(BaseTestCase):
def setUp(self):
"""Set up the test environment:
1. Create a random serial port name.
2. Create a random baud rate.
"""
self.random_serial_port = random_string()
self.random_baudrate = random_string(5, constants.NUMBERS)
def test_write_closed_port(self):
"""Tests writing-to a closed DummySerial port."""
rand_write_len1 = random.randint(0, 1024)
rand_write_len2 = random.randint(0, 1024)
rand_write_str1 = random_string(rand_write_len1).encode()
rand_write_str2 = random_string(rand_write_len2).encode()
ds_instance = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_str1: rand_write_str2}
)
self.assertTrue(ds_instance._isOpen) # pylint: disable=W0212
ds_instance.close()
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
with self.assertRaises(SerialException):
ds_instance.write(rand_write_str1)
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
def test_write_and_read_to_closed_port(self):
"""Tests writing-to and reading-from a closed DummySerial port."""
rand_write_len1 = random.randint(0, 1024)
rand_write_len2 = random.randint(0, 1024)
rand_write_str1 = random_string(rand_write_len1).encode()
rand_write_str2 = random_string(rand_write_len2).encode()
ds_instance = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_str1: rand_write_str2}
)
self.assertTrue(ds_instance._isOpen) # pylint: disable=W0212
ds_instance.write(rand_write_str1)
ds_instance.close()
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
with self.assertRaises(SerialException):
ds_instance.read(rand_write_len2)
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
def test_repr_port(self):
"""Tests describing a DummySerial port."""
rand_write_len1 = random.randint(0, 1024)
rand_write_len2 = random.randint(0, 1024)
rand_write_str1 = random_string(rand_write_len1).encode()
rand_write_str2 = random_string(rand_write_len2).encode()
ds_instance = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_str1: rand_write_str2}
)
self.assertTrue(self.random_serial_port in str(ds_instance))
def test_open_port(self):
"""Tests opening an already-open DummySerial port."""
rand_write_len1 = random.randint(0, 1024)
rand_write_len2 = random.randint(0, 1024)
rand_write_str1 = random_string(rand_write_len1).encode()
rand_write_str2 = random_string(rand_write_len2).encode()
ds_instance = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_str1: rand_write_str2}
)
self.assertTrue(ds_instance._isOpen) # pylint: disable=W0212
with self.assertRaises(SerialException):
ds_instance.open()
ds_instance.close()
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
ds_instance.open()
self.assertTrue(ds_instance._isOpen) # pylint: disable=W0212
def test_close(self):
"""Tests closing a DummySerial port."""
rand_write_len1 = random.randint(0, 1024)
rand_write_len2 = random.randint(0, 1024)
rand_write_str1 = random_string(rand_write_len1).encode()
rand_write_str2 = random_string(rand_write_len2).encode()
ds_instance = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_str1: rand_write_str2}
)
self.assertTrue(ds_instance._isOpen) # pylint: disable=W0212
self.assertFalse(ds_instance.close())
self.assertFalse(ds_instance._isOpen) # pylint: disable=W0212
def test_write_and_read_no_data_present(self): # pylint: disable=C0103
"""Tests writing and reading with an unspecified response."""
rand_write_len1 = random.randint(256, 1024)
rand_read_len2 = random.randint(1, 16) # give it some order of magnitudes less
rand_write_bytes1 = random_bytes(rand_write_len1)
ds_instance = DummySerial(port=self.random_serial_port, baudrate=self.random_baudrate)
ds_instance.write(rand_write_bytes1)
while 1:
ds_instance.read(rand_read_len2) # discard this data
if not ds_instance.in_waiting:
empty_data = ds_instance.read(rand_read_len2)
break
self.assertEqual(constants.NO_DATA_PRESENT, empty_data)
def test_writing_non_bytes_data_raises_type_error(self):
"""Ensures that errors are raised if attempting to write non-bytes data"""
rand_write_len = random.randint(256, 1024)
rand_write_string = random_string(rand_write_len)
ds = DummySerial(port=self.random_serial_port, baudrate=self.random_baudrate)
with self.assertRaises(TypeError):
ds.write(rand_write_string)
def test_negative_read_size(self):
"""Ensures that errors are raised if attempting to access more or less data than in the buffer"""
rand_write_len = random.randint(256, 1024)
rand_write_bytes = random_bytes(rand_write_len)
ds = DummySerial(port=self.random_serial_port, baudrate=self.random_baudrate)
ds.write(rand_write_bytes)
with self.assertRaises(exceptions.DSIOError):
ds.read(-1)
def test_timeout_with_large_read_size(self):
"""Ensures that errors are raised if attempting to access more or less data than in the buffer"""
rand_write_len = random.randint(256, 1024)
rand_write_bytes = random_bytes(rand_write_len)
ds = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_bytes: rand_write_bytes}
)
ds.write(rand_write_bytes)
result = ds.read(rand_write_len + 2)
self.assertEqual(len(result), rand_write_len)
def test_partial_read(self):
"""Ensures that errors are raised if attempting to access more or less data than in the buffer"""
rand_write_len = random.randint(256, 1024)
rand_write_bytes = random_bytes(rand_write_len)
ds = DummySerial(
port=self.random_serial_port, baudrate=self.random_baudrate, responses={rand_write_bytes: rand_write_bytes}
)
ds.write(rand_write_bytes)
result = ds.read(rand_write_len - 2)
self.assertEqual(len(result), rand_write_len - 2)
self.assertEqual(ds.in_waiting, 2)
def test_write_bytearray(self):
"""Ensures that errors are raised if attempting to access more or less data than in the buffer"""
rand_write_len = random.randint(256, 1024)
rand_write_bytearray = bytearray(random_bytes(rand_write_len))
ds = DummySerial(
port=self.random_serial_port,
baudrate=self.random_baudrate,
)
ds.write(rand_write_bytearray)
if __name__ == "__main__":
unittest.main()
| 41.538462
| 119
| 0.694577
| 968
| 7,560
| 5.103306
| 0.130165
| 0.13664
| 0.039474
| 0.052632
| 0.762753
| 0.749798
| 0.717409
| 0.717409
| 0.704251
| 0.687045
| 0
| 0.034261
| 0.220106
| 7,560
| 181
| 120
| 41.767956
| 0.803596
| 0.15
| 0
| 0.543307
| 0
| 0
| 0.001264
| 0
| 0
| 0
| 0
| 0
| 0.173228
| 1
| 0.094488
| false
| 0
| 0.03937
| 0
| 0.141732
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
67da024b54f0853f0965d1f566e700aad7c2a74c
| 152
|
py
|
Python
|
pbt/population/__init__.py
|
automl/HPO_for_RL
|
d82c7ddd6fe19834c088137570530f11761d9390
|
[
"Apache-2.0"
] | 9
|
2021-06-22T08:54:19.000Z
|
2022-03-28T09:10:59.000Z
|
pbt/population/__init__.py
|
automl/HPO_for_RL
|
d82c7ddd6fe19834c088137570530f11761d9390
|
[
"Apache-2.0"
] | null | null | null |
pbt/population/__init__.py
|
automl/HPO_for_RL
|
d82c7ddd6fe19834c088137570530f11761d9390
|
[
"Apache-2.0"
] | null | null | null |
from .trial import Trial, NoTrial
from .member import Member
from .population import Population
__all__ = ['Trial', 'NoTrial', 'Member', 'Population']
| 25.333333
| 54
| 0.75
| 18
| 152
| 6.111111
| 0.388889
| 0.218182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131579
| 152
| 5
| 55
| 30.4
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0.184211
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
db2cccb8706be958cee0c18ee9e554aac314a720
| 348
|
py
|
Python
|
grpr2-ch/maci/policies/__init__.py
|
saarcohen30/GrPR2-CH
|
ba8c32f5b4caeebfc93ca30fa1fcc8223176183f
|
[
"MIT"
] | null | null | null |
grpr2-ch/maci/policies/__init__.py
|
saarcohen30/GrPR2-CH
|
ba8c32f5b4caeebfc93ca30fa1fcc8223176183f
|
[
"MIT"
] | null | null | null |
grpr2-ch/maci/policies/__init__.py
|
saarcohen30/GrPR2-CH
|
ba8c32f5b4caeebfc93ca30fa1fcc8223176183f
|
[
"MIT"
] | null | null | null |
from .nn_policy import NNPolicy
# from .gmm import GMMPolicy
# from .latent_space_policy import LatentSpacePolicy
from .uniform_policy import UniformPolicy
# from .gaussian_policy import GaussianPolicy
from .stochastic_policy import StochasticNNPolicy, StochasticNNConditionalPolicy
from .deterministic_policy import DeterministicNNPolicy
| 38.666667
| 81
| 0.850575
| 36
| 348
| 8.027778
| 0.527778
| 0.249135
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117816
| 348
| 8
| 82
| 43.5
| 0.941368
| 0.347701
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
e1f30a4f4d1925bf5687b7cf412adf4bd33cee9b
| 84
|
py
|
Python
|
docs/ResearchSession/manage.py
|
VoIlAlex/pytorchresearch
|
c4f08cd0ec6b78788e682005c099aef4582640cb
|
[
"MIT"
] | 1
|
2020-12-13T20:25:27.000Z
|
2020-12-13T20:25:27.000Z
|
docs/ResearchSession/manage.py
|
VoIlAlex/pytorchresearch
|
c4f08cd0ec6b78788e682005c099aef4582640cb
|
[
"MIT"
] | null | null | null |
docs/ResearchSession/manage.py
|
VoIlAlex/pytorchresearch
|
c4f08cd0ec6b78788e682005c099aef4582640cb
|
[
"MIT"
] | null | null | null |
from backbone import entry_point
if __name__ == '__main__':
entry_point.main()
| 16.8
| 32
| 0.738095
| 11
| 84
| 4.727273
| 0.727273
| 0.384615
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 84
| 4
| 33
| 21
| 0.742857
| 0
| 0
| 0
| 0
| 0
| 0.095238
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
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