fig | Simple framework for managing hierarchical configurations | Configuration Management library

I have an Rmarkdown with a simple scatter plot (a map for instance), and I would like users to be able to provide some arbitrary x and y coordinates via an input and have those plotted on the graph (in red in the example below). The problem is, I don't have a shiny server so I cannot rely on that option. Is there a implement this, for instance, via javascript or something?

This is what I have:

i am currently working with plotly i have a function called plotChart that takes a dataframe as input and plots a candlestick chart. I am trying to figure out a way to pass a list of dataframes to the function plotChart and use a plotly dropdown menu to show the options on the input list by the stock name. The drop down menu will have the list of dataframe and when an option is clicked on it will update the figure in plotly is there away to do this. below is the code i have to plot a single dataframe

I am trying to achieve a calculation involving geometric progression (split). Is there any effective/efficient way of doing it. The data set has millions of rows. I need the column "Traded_quantity"

turtle = 2 (User defined)

base_quantity = 1 (User defined)

Python 3.9 on Mac running OS 11.6.1. My application involves placing a plot on a frame inside my root window, and I'm struggling to get the plot to take up a larger portion of the window. I thought rcParams in matplotlib.pyplot would take care of this, but I must be overlooking something.

Here's what I have so far:

I have a Rmarkdown document containing some python code chunks using the reticulate library. The code executes output perfectly; however, how would I cross-reference the generated plots in the text using its label? I am using bookdown::pdf_documents2 etc, and have no issue with inline reference of R chunks using the standard \@ref(fig:my-plot).

An MWE would be:

Yesterday I came across the new 3Blue1Brown video about Newton's fractal and I was really mesmerized by his live representation of the fractal. (Here's the video link for anybody interested, it's at 13:40: https://www.youtube.com/watch?v=-RdOwhmqP5s)

I wanted to have a go at it myself and tried to code it in python (I think he uses python too).

I spent a few hours trying to improve my naive implementation and got to a point where I just don't know how could I make it faster.

The code looks like this:

Can one can change the arrows of a figure into an arrow by superimposing arrows on top of the x, y and z axes to create the illusion of the axes being arrows or perhaps directly change the settings of the frames as Matplot lib framing in order to get the same outcome on a 3D plot, showing (x,y,z) with arrows?

Turning this

I'm trying to update below function to report the clusters info via legend:

I have several points on the unit sphere that are distributed according to the algorithm described in https://www.cmu.edu/biolphys/deserno/pdf/sphere_equi.pdf (and implemented in the code below). On each of these points, I have a value that in my particular case represents 1 minus a small error. The errors are in [0, 0.1] if this is important, so my values are in [0.9, 1].

Sadly, computing the errors is a costly process and I cannot do this for as many points as I want. Still, I want my plots to look like I am plotting something "continuous". So I want to fit an interpolation function to my data, to be able to sample as many points as I want.

After a little bit of research I found scipy.interpolate.SmoothSphereBivariateSpline which seems to do exactly what I want. But I cannot make it work properly.

Question: what can I use to interpolate (spline, linear interpolation, anything would be fine for the moment) my data on the unit sphere? An answer can be either "you misused scipy.interpolation, here is the correct way to do this" or "this other function is better suited to your problem".

Sample code that should be executable with numpy and scipy installed: