inferno | A Rust port of FlameGraph | Monitoring library

I have scoured the Internet trying to find a solution and somehow I still can't find a simple, straightforward answer. Maybe it's much more complicated ? I have read Advanced R by Hadley Wickham on lexical scoping but it somehow doesn't help. Maybe I haven't asked the right question, but the answer seems so simple. There's even a chapter in R inferno (Chapter 5.3, Chapter 6) telling me what to do, without really getting into the details while warning against global assignment.

Currently what I'm doing is using Global Assignment which apparently is a disaster. I don't know how to fix my pipeline.

This might have been answered, but I can't quite find the right group of words to search for to find the answer to the problem I'm having.

Situation: I have a several data frames that could be plugged into a function. The function requires that I name the data frame so that it can take the shape.

Inputted x, y, and z coordinates will output three graphs: an x-z graph sliding along the y axis, an x-y graph sliding along the z axis, and a y-z graph sliding along the x axis. I position the lines based on the percent by which the user has slid its corresponding coordinate on the slider tool. See below (don't be alarmed by how the coronal and transverse views are switched):

However, as you can see, the y-coordinate is low, so the line is out of the bounds of the figure. The issue is the lines are positioned relative to the window rather than relative to the plot. Therefore, I would like to get the size of the figure within the window to correct for this issue. I have not found any documentation on how to find the dimensions of a figure within a window as opposed to the whole window—how would I approach this? Thank you! See my code below to see how each individual plot is visualized:

I have XML that I'd like to transform with XSL to view in a browser.

I have made the default namespace in my XML http://www.tei-c.org/ns/1.0. To avoid using prefixes in the XML and XSL, I added xpath-default-namespace="http://www.tei-c.org/ns/1.0" to my xsl:stylesheet element. I still seem to need prefixes in my xpaths, however, since xpaths with no prefixes do not work.

What am I missing? Shouldn't the xpath-default-namespace attribute ensure that I can use the default namespace in my xpaths, thus avoiding the need to prefix the (default) namespace?

I am hosting the XML and XSL on my own web server (Debian Bullseye, Apache, Raspberry Pi). Could there be an issue with the packages I have installed? For example, I have libxslt1.1 installed, which only "supports" XSLT 1.0 (which doesn't include the xpath-default-namespace attribute). But shouldn't the XML be transformed by the browser, and not by my server?

The XML

According to matplotlib's colormap documentation, the lightness values of their default colormaps are not constant. However, I would like to create a colormap from the HSL color space that has a constant lightness. How can I do that?

I get that generally, it's not that hard to create your own colormaps, but I don't know how to do this while satisfying the lightness criterion. Maybe this can be done by reverse-engineering the code from the colormap documentation?

I think I found a way to do that, based on this post. First of all, working in the HSL color space turned out to be not the best idea for my overal goal, so I switched to HSV instead. With that, I can load the preferred colormap from matplotlib, create a set of RGB colors from it, transform them into HSV, set their color value constant, transform them back into RGB and finally create a colormap from them again (which I can then use for a 2d histogram e.g.).

I need a colormap in HSV with a constant color value because then I can uniquely map colors to the RGB space from the pallet that is spanned by hue and saturation. This in turn would allow me to create a 2d histogram where I could color-code both the counts (via the saturation) and a third variable (via the hue).

In the MWE below for example (slightly changed from here), with a colormap with constant color value, in each bin I could use the saturation to indicate the number of counts (e.g. the lighter the color, the lower the number), and use the hue to indicate the the average z value. This would allow me to essentially combine the two plots below into one. (There is also this tutorial on adding alpha values to a 2d histogram, but this wouldn't work in this case I think.)

Currently, you still need both plots to get the full picture, because without the histogram for example, you wouldn't be able to tell how significant a certain z value in a bin might be, as the same color is used independently of how many data points contributed to it (so judging by the color, a bin with only one data point might look just as significant as a bin with the same color but that contains many more data points; thus there is a bias in favor of outliers).

I have a csv file with some data. Here is the example of data from it (from R Studio):

and result of data.frame(df):

I already figured out how to save a video animation and zooming a picture with matplotlib. I want now to merge the two things and understand how to introduce zoom in an animation: reading some documentation I noticed it's not straightforward for just a picture, I expect to be the same or worse for a video.

In the following I write a simple working code, relating to that you can find on the first link

I want to create color legend using linear gradient > https://bl.ocks.org/HarryStevens/6eb89487fc99ad016723b901cbd57fde . But how can I pass my d3 colors here because its in the form like d3.scaleSequential(d3.interpolateViridis).domain([0,1]). In linear gradient the colors are passed as below :

Same question asked on the plotly community forum.

I am creating a dash app which utilizes plotly-dash density_mapbox and I would like to disable the ability for the user to zoom, as it effects the radius of the heatmap and misrepresents this particular dataset, in my opinion.

Setting scrollZoom = False in the config of dcc.Graph works as intended on desktop--the user can't zoom but can pan and move around, and interact with the graph. However, on mobile devices scrollZoom = False doesn't appear to do anything--the user can still zoom in and out.

staticPlot = True was a recommended solution, but that will not work because I'd like for the datapoints to be viewable on hover. Making the graph static removes all interaction.

Below is the sample code with sample dataset.