CODEWITHSUNDEEP
pythonmatplotlibcolormap
durbachit
durbachit

Reputation: 4896

How can I normalize colormap in matplotlib scatter plot?

The matplotlib documentation explain in detail how to normalize colormaps for a pcolormesh, but how can I correctly do it for a scatter plot?

normalize = mcolors.Normalize(vmin=-1, vmax=1)
plt.scatter(x,y,z,cmap=colormap(normalize),marker='*',s=5)

doesn't work (TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe')

it's just that the z data are not exactly from -1 to 1, I am plotting multiple datasets that have the limits around +/- 0.93 - 98, but I want the colours to be centered at zero and go from -1 to 1 so that I have the same reference for all the various datasets.

Oh, and when I don't attempt to normalize, I get TypeError: scatter() got multiple values for keyword argument 's'. Clearly I don't know how to use colormap in scatter plots.

Upvotes: 10

Views: 34781

Answers (2)

aerijman
aerijman

Reputation: 2782

# define the range of values in the data (100 is arbitrary)
my_range = np.linspace(-1,1,100)

# cmap is a function. It returns (rgba) colors base on a range 0-1. Therefore, 
# transform your values to 0-1 to use them as input for cmap() 
cmap = cm.get_cmap('viridis', 100)
my_transformed_range = (my_range - np.min(my_range)) / (np.max(my_range) - np.min(my_range))

# colors should be supplied as a single color or a list (here using the cmap fx)
plt.scatter(my_range, np.ones(100), color=[cmap(i) for i in my_transformed_range])

Upvotes: 0

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339550

The syntax you're using is completely different to the one in the linked documentation. There is essentially no difference between normalizing a scatter or a pcolor(mesh) or just any other scalar mappable object.

It's always 

colormap = plt.cm.bwr #or any other colormap
normalize = matplotlib.colors.Normalize(vmin=-1, vmax=1)
plt.scatter(x, y, c=z, s=5, cmap=colormap, norm=normalize, marker='*')

Upvotes: 28

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