I'd like to hide the 3d grid background color and just display gridlines and axis labels, as it's currently the default gray color
like this (Not allowed to embed images since this is a new account). Thanks.
For your case, you can set the background color to black.
ax.set_facecolor("black")
https://matplotlib.org/3.5.0/gallery/color/color_demo.html#sphx-glr-gallery-color-color-demo-py
Related
How can I change the color of the plotting wedges to white?
and how i can make the plotting full of the screen in QT-designer?
My GUI //file:///C:/Users/Ghaliah%20Internet/Downloads/project1_sinewave.ui
When making a subplot we use facecolor argument to set the color of the background. For example
import matplotlib.pyplot as plt
fig, ax = plt.subplots(facecolor="black")
ax.set_facecolor("black")
This produces the following output:
Now the above output is a plain black color. What I want is to add an effect to this plain black color so that it will look like this:
If you observe closely there is a bit of white color scattered over the black colored background. How to produce this effect in matplotlib?
I believe that only solid colours can be set. You could create the desired effect in a different program and save it as an image. Then, set the background of the plot to that image as in this SO answer.
Whenever I plot this image I get issues with the whites turning yellow. I know it's due to the default color mapping viridis, which matplotlib uses. When I switch to cmap='gray', it ends up showing the right red color pane.
Can anyone explain why this is happening? What color map should be used generally for pictures like this? How is the picture able to show the right colors when I do the default imshow(img)? What changes when I isolate the a single color pane? And when isolating red green or blue color panes in images, what is the preferred cmap and why?
This is the output for the red color pane
The regular image plots correctly according to RGB color mode:
The logic is rather simple, possibly the following chart helps more than any explanation.
Is there an existing color map that can be easily applied to make a line plot visible on a grayscale medium (e.g. a paper printed in black and white) by modifying the way the line is drawn (e.g. black full line, black dashed line, gray full line, etc.)?
The gray color scale is a good start but it doesn't cut it: when I have more than 4 series on the same plot it's hard to distinguish once printed, and also it colors one series as white (making it invisible unless I change the background to something else).
You can vary the linestyles as shown here and use different markers as shown here.
Finally, I would suggest you look at cyclers to loop over different colors, linestyles and markers.
I would like to make the background of my imshow plots transparent. I know I can do this using the color to alpha option in GIMP. However, using GIMP in this case is not an option as I still need to perform actions after the background of imshow has been made transparent.
Is there a way to remove the background of imshow plots similar to GIMP's color to alpha in python without saving the figure first?