matplotlib cmap number of colors

Getting individual colors from a color map in matplotlib

stackoverflow.com › questions › 25408393 › getting-individual-colors-from-a-color-map-in-matplotlib

You can do this with the code below, and the code in your question was actually very close to what you needed, all you have to do is call the cmap object you have.

import matplotlib

cmap = matplotlib.cm.get_cmap('Spectral')

rgba = cmap(0.5)
print(rgba) # (0.99807766255210428, 0.99923106502084169, 0.74602077638401709, 1.0)

For values outside of the range [0.0, 1.0] it will return the under and over colour (respectively). This, by default, is the minimum and maximum colour within the range (so 0.0 and 1.0). This default can be changed with cmap.set_under() and cmap.set_over().

For "special" numbers such as np.nan and np.inf the default is to use the 0.0 value, this can be changed using cmap.set_bad() similarly to under and over as above.

Finally it may be necessary for you to normalize your data such that it conforms to the range [0.0, 1.0]. This can be done using matplotlib.colors.Normalize simply as shown in the small example below where the arguments vmin and vmax describe what numbers should be mapped to 0.0 and 1.0 respectively.

import matplotlib

norm = matplotlib.colors.Normalize(vmin=10.0, vmax=20.0)

print(norm(15.0)) # 0.5

A logarithmic normaliser (matplotlib.colors.LogNorm) is also available for data ranges with a large range of values.

(Thanks to both Joe Kington and tcaswell for suggestions on how to improve the answer.)

Answer from Ffisegydd on Stack Overflow

Matplotlib

matplotlib.org › stable › users › explain › colors › colormaps.html

Choosing Colormaps in Matplotlib — Matplotlib 3.11.2 documentation

First, we'll show the range of each colormap. Note that some seem to change more "quickly" than others. cmaps = {} gradient = np.linspace(0, 1, 256) gradient = np.vstack((gradient, gradient)) def plot_color_gradients(category, cmap_list): # Create figure and adjust figure height to number of colormaps nrows = len(cmap_list) figh = 0.35 + 0.15 + (nrows + (nrows - 1) * 0.1) * 0.22 fig, axs = plt.subplots(nrows=nrows + 1, figsize=(6.4, figh)) fig.subplots_adjust(top=1 - 0.35 / figh, bottom=0.15 / figh, left=0.2, right=0.99) axs[0].set_title(f'{category} colormaps', fontsize=14) for ax, name in zip(axs, cmap_list): ax.imshow(gradient, aspect='auto', cmap=mpl.colormaps[name]) ax.text(-0.01, 0.5, name, va='center', ha='right', fontsize=10, transform=ax.transAxes) # Turn off *all* ticks & spines, not just the ones with colormaps.

Stack Overflow

stackoverflow.com › questions › 25408393 › getting-individual-colors-from-a-color-map-in-matplotlib

python - Getting individual colors from a color map in matplotlib - Stack Overflow

Top answer

1 of 9

415

You can do this with the code below, and the code in your question was actually very close to what you needed, all you have to do is call the cmap object you have.

import matplotlib

cmap = matplotlib.cm.get_cmap('Spectral')

rgba = cmap(0.5)
print(rgba) # (0.99807766255210428, 0.99923106502084169, 0.74602077638401709, 1.0)

For values outside of the range [0.0, 1.0] it will return the under and over colour (respectively). This, by default, is the minimum and maximum colour within the range (so 0.0 and 1.0). This default can be changed with cmap.set_under() and cmap.set_over().

For "special" numbers such as np.nan and np.inf the default is to use the 0.0 value, this can be changed using cmap.set_bad() similarly to under and over as above.

Finally it may be necessary for you to normalize your data such that it conforms to the range [0.0, 1.0]. This can be done using matplotlib.colors.Normalize simply as shown in the small example below where the arguments vmin and vmax describe what numbers should be mapped to 0.0 and 1.0 respectively.

import matplotlib

norm = matplotlib.colors.Normalize(vmin=10.0, vmax=20.0)

print(norm(15.0)) # 0.5

A logarithmic normaliser (matplotlib.colors.LogNorm) is also available for data ranges with a large range of values.

(Thanks to both Joe Kington and tcaswell for suggestions on how to improve the answer.)

2 of 9

24

In order to get rgba integer value instead of float value, we can do

rgba = cmap(0.5,bytes=True)

So to simplify the code based on answer from Ffisegydd, the code would be like this:

#import colormap
from matplotlib import cm

#normalize item number values to colormap
norm = matplotlib.colors.Normalize(vmin=0, vmax=1000)

#colormap possible values = viridis, jet, spectral
rgba_color = cm.jet(norm(400),bytes=True) 

#400 is one of value between 0 and 1000

numpy - Generating user-defined colormap in Python matplotlib

python - Matplotlib colormap range

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This way of using the API certainly looks much cleaner. 2019-12-11T05:50:44.713Z+00:00 ... Save this answer. ... Show activity on this post. ... Copyimport matplotlib.cm as cm import matplotlib as matplotlib def color_map_color(value, cmap_name='Wistia', vmin=0, vmax=1): # norm = ... More on stackoverflow.com

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Colormaps explained courtesy of matplotlib. You spend a lot of time on your simulations, make sure you spend a little bit of time selecting the correct colormap for your figures.

Id actually suggest this video: https://youtu.be/xAoljeRJ3lU More than that website. Since this gives a better explanation of which colormap to use More on reddit.com

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