None of my pcs are respawning after hard mode my house is not damaged in any way it is exactly how I built it but it says someone wants to move in but does not move in it is not infected and there is no invasion going on. Even when no one dies the after hard mode npc won't move in.
I am currently in hard mode and during a blood moon, several of my NPCs including my guide and my healer died. it's been several in game "days" now and they have yet to respawn. Is there a way to check why they aren't respawning?   Is there a list of reasons for the NPCs to not respawn?   Edit in reponse to lunbok's answer:  1. They don't have appropriate housing - There is an in-game housing query function (changes your cursor into a ?) that lets you click on your house to see if it is still a suitable house and I clicked in every room in my house and they are all listed as "This housing is suitable" or "This housing is already occupied".  2. Their spawn conditions aren't met anymore. - This doesn't explain why my guide isn't respawning since they don't need a condition to respawn (other than having a suitable housing which the point above already prove isn't the problem).  3. There's a goblin invasion going on. - Do the invasions last that long? It has been about two reals days and a lot more in-game "days" now. As far as I can tell there shouldn't be an invasion going on.  4. It could be because you built your house in a part of the world that is now corrupted
Is there a way to save composite node presets? Is there any way in Blender to save settings in your compositing node setup. For example say for my shadow catcher I have it setup for a hard shadow for sunlight, and then I also have a setting for diffuse light shadow for indoors. Is there any way I can save these settings individually so I can quickly switch to them rather than having to individually change the nodes every time. For some of the apps I've developed (then proceeded to forget about), I've been writing plain SQL, primarily for MySQL.  Though I have used ORMs in python like , I didn't stick with them for long.  Usually it was either the documentation or complexity (from my point of view) holding me back.  I see it like this: use an ORM for portability, plain SQL if it's just going to be using one type of database. I'm really looking for advice on when to use an ORM or SQL when developing an app that needs database support.  Thinking about it, it would be far better to just use a lightweight wrapper to handle database inconsistencies vs. using an ORM. Shadows along edges of mesh in 3D View How do we prove that this set is not manifold? Does excessive markup affect SEO? Why has Earth's core not become solid? How to export variable for use with sudo? On Slackware, using sbopkg permits one to build a package from source. Repos is not big as Debian, but it's nice.  Some software can use environment variables, for example on the VICE c64 emulator, if the variable FFMPEG is set to yes, it will enable ffmpeg recording the emulator.  I tried to use  $ export FFMPEG=yes; sudo sbopkg -B -i vice   but ffmpeg is disabled.  Instead I had to use  $ su - $ export FFMPEG=yes $ sbopkg -B -i vice   which works.  How to use environment variables with sudo? How can I generate irregular grid containing minimum n points? Given a large (~ 1 million) sample of unevenly distributed points - is it possible to generate irregular grid (in size, but could also be irregular in shape if that is possible?) that will contain specified minimum amount of n points?   It is of less importance for me if genereted 'cells' of such grid contain exactly n number of points or at least n points.  I'm aware of solutions like  in ArcGIS or  in QGIS/mmgis however they will all create regular grids which will result in an output with empty cells (smaller problem - I could simply discard them) or cells with count of points less than n (bigger problem since I'd need a solution to aggregate those cells, probably using some tools from ?).  I've been googling around to no avail and am open to both commercial (ArcGIS &amp; extensions) or free (Python, PostGIS, R) solutions. ... and why ?  Assuming $X_1$,$X_2$ are independent random-variables with mean $\mu_1,\mu_2$ and variance $\sigma^2_1,\sigma^2_2$ respectively. My basic statistics book tells me that the distribution of the $X_1-X_2$ has the following properties:    $E(X_1-X_2)=\mu_1-\mu_2$ $Var(X_1-X_2)=\sigma^2_1 +\sigma^2_2$   Now let's say $X_1$, $X_2$  are t-distributions with $n_1-1$, $n_2-2$ degrees of freedom. What is the distribution of $X_1-X_2$ ?   This question has been edited: The original question was "What are the degrees of freedom of the difference of two t-distributions ?". mpiktas has already pointed out that this makes no sense since $X_1-X_2$ is not t-distributed, no matter how approximately normal $X_1,X_2$ (i.e. high df) may be. PostGIS Geometry Query returns "Error: Operation on mixed SRID geometries" only for certain values Order of nested random effects in lme4 I just fit a model in lme4, and I'm wondering what the heck I fit...  I have individuals id, and each is measured pass/fail on items that can be described using two factors, f1 and f2. My theory says that id and f2 can interact. So I want to compare these models:  # f2 doesn't matter m1 &lt;- lmer(pass ~ f1 + (1|id), family="binomial")  # f2 is a fixed effect, doesn't interact with individuals m2 &lt;- lmer(pass ~ f1 + f2 + (1|id), family="binomial")  # f2 is a nested random effect, interacting with individuals m3 &lt;- lmer(pass ~ f1 + (1|f2/id), family="binomial")   First, am I right that there's a random effect of each level of f2, and each individual's level of f2 is partially pooled, depending on the number of observations for that individual?  Second, does it make sense to fit f2 as a fixed effect with random individuals nested within each level of f2? How does one write that?  Third, what's this, with f2 and id reversed in the formula? I typed it by accident, but now I want to understand it.  m3weird &lt;- lmer(pass ~ f1 + (1|id/f2), family="binomial") Compute the limit of $\sqrt{1-a}\sum\limits_{n=0}^{+\infty} a^{n^2}$ when $a\to1^-$ I need some suggestions, hints for the limit when $a \to 1^{-}$ of $$\sqrt{\,1 - a\,}\,\sum_{n = 0}^{\infty}a^{n^{2}}.$$ The situation is my  has been enchanted with .  The creature has      when it dies, return it to his owner’s hand   The enchantment says     When enchanted creature dies, return that card to the battlefield under your control with a +1/+1 counter on it.   Who gets the creature? Me or my rival?  Does the creature ability trigger before or after enchantment? Is it possible to use a laptop as an external monitor? I need to create a multi-monitor setup for my desktop computer but I have no additional monitors with me right now, aside from my laptop. Is it possible to use my laptop screen as an external monitor?  Note that I am not trying to connect a monitor to my laptop, rather, I am trying to connect my laptop screen to a desktop video card (if this is possible). SQL Join Differences What's difference between inner join and outer join (left join,right join), and which has the best performance of them?  Thanks! How to prove $(-3) \times (-4) = 12$? How to logically understand the multiplication of two integers ?  Eg:  3 x 4 = 12 (is understandable)  -3 x4 = -12 (is also somewhat understandable)  But , 3 x -4 = -12 (is NOT understandable)  -3 x -4 = 12 (is also NOT understandable)  Now , at this we must assume that commutative property may not be true .  What is the logical explanation for something being multiplied negative times ? Calculate posterior distribution (gamma-prior, poisson-likelihood) I want to calculate the posterior distribution given a gamma-prior and a poisson likelihood. The task is from a textbook and I just have the solutions (without a walkthrough). Please find all given information in the following:  Given information:  $m$ countries each with a population of $n_i$; $y_i$ is the number of people having a disease; $y_i$ is a poisson random variable with mean $\frac{n_i*\lambda}{100}$  The prior distribution for $\lambda$: $\lambda \sim Gamma(a_0,b_0)$  Task:  Show that the posterior distribution is also a gamma distribution with $a_m = a_0 + \sum_{i = 1}^{m}y_i$ and $b_m = b_0 + \sum_{i = 1}^{m} \frac{n_i}{100}$  My solution:  $Posterior \propto Likelihood \times Prior$  $p(\theta|y) \propto \prod_{i=1}^{m}(\theta^{y_i}e^{-\theta})\times \theta^{a_0-1}e^{-b_0\theta}$  $p(\theta|y) \propto \theta^{\sum_{i = 1}^{m}y_i}e^{-m\theta}\times \theta^{a_0-1}e^{-b_0\theta}$  $p(\theta|y) \propto \theta^{\sum_{i = 1}^{m}y_i+a_0-1}e^{-\theta(m+b_0)}$  $a_m = a_0 + \sum_{i = 1}^{m}y_i$  $b_m = b_0 + m \neq b_0 + \sum_{i = 1}^{m} \frac{n_i}{100}$  I think I am doing a mistake, because I don't know how to incorporate the information that the mean of $y_i$ is given as $\frac{n_i*\lambda}{100}$. Or do I just have to transform $b_m$ somehow? Can someone may give me a hint?   Thank you already in advance!  Edit 1: Considering first advices  $Likelihood: p(y | \theta) \propto \prod_{i=1}^{m}(\frac{n_i\lambda}{100})^{y_i}e^{-\frac{n_i\lambda}{100}}$  $\propto \prod_{i = 1}^{m} ((\frac{n_i}{100})^{y_i})\lambda^{\sum_{i=1}^{m}y_i}e^{-\lambda\sum_{i=1}^{m}\frac{n_i}{100}}$  $\propto \lambda^{\sum_{i=1}^{m}y_i}e^{-\lambda\sum_{i=1}^{m}\frac{n_i}{100}}$  Is the transformation of $\prod_{i=1}^{m}$ I did from the first to the second step correct? I need to calculate the SQRT of  $x$ to $y$ decimal places. I'm dealing with $128$-bit precision, giving a limit of $28$ decimal places. Obviously, if $\,y &gt; 28$, the , which I'm currently using, becomes futile, as it simply doesn't offer $y$ decimal places.  My question to you is, can I calculate the Square Root digit-by-digit? For example, calculating the $n$-th digit, assuming I already have digit $\,n - 1$. I'm well aware this may be impossible, as I've not found any such method through Google yet, just checking here before I give up in search of arbitrary precision methods. The primitive types (number, string, etc.) are passed by value, but objects are unknown, because they can be both passed-by-value (in case we consider that a variable holding an object is in fact a reference to the object) and passed-by-reference (when we consider that the variable to the object holds the object itself).  Although it doesn't really matter at the end, I want to know what is the correct way to present the arguments passing conventions. Is there an excerpt from JavaScript specification, which defines what should be the semantics regarding this? Does "Root A" follow the fact about Takatsuki and the One-Eyed Owl? In Root A, Takatsuki does seem to be fascinated by Kaneki's name, but,      I didn't at all expect her to be the One-Eyed Owl.   I just looked her up on the  and it says that       she is the One Eyed-Owl as well as the horror novelist.   Is this true only in the manga or is it also true in Root A?