Hex | hex is an implementation in c # of the board game hex | Game Engine library

With the first patch for AS Arctic Fox Jetpack Compose previews stopped working.

I'm getting this error for all previews - even older ones, which worked fine a while back:

I have measurements of a quantity (value) at specific points (lon and lat), like the example data below:

ruby '2.7.3' rails (6.1.4.1)

Looks strange:

When I query some (some specific) rows in DB using activerecord and try to assign it to a variable, it raises "nil can't be coerced into Integer"

But when I don't try to assign it to a variable, it works:

There are so many ways to define colour scales within ggplot2. After just loading ggplot2 I count 22 functions beginging with scale_color_* (or scale_colour_*) and same number beginging with scale_fill_*. Is it possible to briefly name the purpose of the functions below? Particularly I struggle with the differences of some of the functions and when to use them.

• scale_*_binned()
• scale_*_brewer()
• scale_*_continuous()
• scale_*_date()
• scale_*_datetime()
• scale_*_discrete()
• scale_*_distiller()
• scale_*_fermenter()
• scale_*_gradient()
• scale_*_gradient2()
• scale_*_gradientn()
• scale_*_grey()
• scale_*_hue()
• scale_*_identity()
• scale_*_manual()
• scale_*_ordinal()
• scale_*_steps()
• scale_*_steps2()
• scale_*_stepsn()
• scale_*_viridis_b()
• scale_*_viridis_c()
• scale_*_viridis_d()

What I tried

I've tried to make some research on the web but the more I read the more I get onfused. To drop some random example: "The default scale for continuous fill scales is scale_fill_continuous() which in turn defaults to scale_fill_gradient()". I do not get what the difference of both functions is. Again, this is just an example. Same is true for scale_color_binned() and scale_color_discrete() where I can not name the difference. And in case of scale_color_date() and scale_color_datetime() the destription says "scale_*_gradient creates a two colour gradient (low-high), scale_*_gradient2 creates a diverging colour gradient (low-mid-high), scale_*_gradientn creates a n-colour gradient." which is nice to know but how is this related to scale_color_date() and scale_color_datetime()? Looking for those functions on the web does not give me very informative sources either. Reading on this topic gets also chaotic because there are tons of color palettes in different packages which are sequential/ diverging/ qualitative plus one can set same color in different ways, i.e. by color name, rgb, number, hex code or palette name. In part this is not directly related to the question about the 2*22 functions but in some cases it is because providing a "wrong" palette results in an error (e.g. the error"Continuous value supplied to discrete scale).

Why I ask this

I need to do many plots for my work and I am supposed to provide some function that returns all kind of plots. The plots are supposed to have similiar layout so that they fit well together. One aspect I need to consider here is that the colour scales of the plots go well together. See here for example, where so many different kind of plots have same colour scale. I was hoping I could use some general function which provides a colour palette to any data, regardless of whether the data is continuous or categorical, whether it is a fill or col easthetic. But since this is not how colour scales are defined in ggplot2 I need to understand what all those functions are good for.

Say I have a signed number coded on an unusual number of bits, for instance 12. How do I convert it efficiently to a standard C value ? The following works but requires an intermediate variable:

I have to store a bunch of UUIDs in integer format in a numpy array. Converting the UUID to integer format (128bits) is not valid since the maximum integer size that can be stored in a numpy array is 64 bits. Therefore I am trying to store the UUID as 6 separate integers using the fields style.

However I am unable to recreate the UUID from the numpy array values. Here is an example of the problem.

I've updated angular cli and created a new project, with routing and scss.

When I run npm install i see:

I'm trying to create a nice graph of indexed prices for a few currencies so I can track relative performance from origin for different projects and price-levels.

Below is my dummy code. I've tried a lot of things but this is as far as I got...

R plot of the orignal code: prices of HEX and BTC

I wish to add other currencies as I go along.

In the end it is just a data frame with multiple columns that all need to start on the same point, the timestamp is irrelevant and I could plot only the series or shift them all to start on the same location.

This is what I'm trying to achieve:

Indexed prices of projects starting at same origin

I try to make an ESDT token issuance transaction using the following Python code