Heatmap generation in Python using different heat intensity - python

I am trying to generate a Hit map of a scatter plot using matplotlib's hist2d. Can I change the heat level intensity for that? I looks like heat color gets changes linearly. I want to do it exponentially? Is there any other tool in python other than matplotlib's hist2d that I can use.

I think you probably want to use color normalization

Related

How can I visualize data using RPM-Order Plots with python

One of my projects needs order analysis of vibration signals with Python instead of Matlab, they want to visualize data using colormap which usually has frequency on the horizontal axis and rotational speed on the vertical axis. Just like this picture:
How can I do this?

Change the heat map so each column has it's shading adjusted independently?

My Seaborn heat map as of now
Is there a way to make the legend shade lighter or darker based on each feature's max and min, instead of grabbing them from the whole dataframe? Or is there a better way to go about visualizing this?

Layering a heatmap onto a map from a data array

I am trying to generate a heatmap (if possible layered on top of a map of my area of interest). I have an array of data (Sea surface temperatures) for the Mediterranean Sea and I would like to generate a heatmap (red for hotter, blue for colder regions) and if possible layer this onto a map (such as google maps or similar) in order to make my data more readable. Are there any packages that can help me with this/does anyone know where I could look to find some sample scripts? Thanks for you help!
I have tried using plotly and matplotlib, however these do not give the desired heatmap (it is all one colour).

Scatter 3D for Large Data-Set in Plotly

I have a 3D scatter which wanna plot using Plotly in python. The problem is size of the dataframe is too large and I want to use webgl to plot the graph. As I know plotly has go.Scatter3d function to plot scatters. Also, there is a go.Scattergl to plot large datasets. However, U can't find something like go.Scatter3Dgl. What should I do?
I believe 3D scatter plots use webgl by default. If you inspect a scatter_3d you'll find that it is in a class="gl-container". Likewise a regular Scatter is in a class="main-svg and a Scattergl is in a class="gl-container".
From plotly:
Note: It is important to note that any figures containing WebGL traces
(i.e. of type scattergl, heatmapgl, contourgl, scatter3d, surface,
mesh3d, scatterpolargl, cone, streamtube, splom, or parcoords) that
are exported in a vector format will include encapsulated rasters,
instead of vectors, for some parts of the image.

How to place country boarders as background for a plot with matplotlib?

I have some data made of coordinates and the count of each coordinate which I plot in a heatmap like this:
pyplot.subplot(211)
pyplot.scatter(longitudes, latitudes, c=counts)
pyplot.colorbar()
which is inspired by this great answer here in SO.
If you look closely you can see, that the dots shape the worldmap somehow. To underline this effect I'd like to put the real country boarders (simply drawn would be enough) as background to my plot. Is this possible with matplotlib? Maybe there is some (hidden) builtin in matplotlib?
You can likely achieve this if you have some image of the world map that you want as a background. You can read this into a numpy array and plot the image. Then you should be able to add your scatter plot overtop of the image. This matplotlib cookbook example shows how to insert images and such. There is also the matplotlib image tutorial that may be of use.
I've not used it, but you may also be interested in the basemap toolkit for matplotlib. In particular, the section on drawing a map background mentions specifically a drawcountries() method.

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