Reverse colormap

reverse_cmap.py

from skimage import io as sio
import skimage
import numpy as np
import matplotlib.pyplot as plt

filename = 'Lennert jet.png'

img = skimage.img_as_float(sio.imread(filename))[:,:,:3]

jet = plt.cm.jet
jet._init()
lut = jet._lut[..., :3]

z = img - lut[:, None, None, :]
z *= z
d = z.sum(axis=-1)

out = d.argmin(axis=0)

"""
Create new image, keeping colors that aren't in the old colormap
"""

plt.imshow(d.min(axis=0))

new_cmap = plt.cm.get_cmap('bone')

out_img = img.copy()
#matches = d.min(axis=0) < 0.005

# Exclude white
matches = np.ones(img.shape[:2], dtype=bool)
matches[np.amin(img, axis=-1) > 0.7] = False
# Exclude black
matches[np.amax(img, axis=-1) < 0.4] = False
#imshow(matches)

out_img[matches] = new_cmap(out[matches])[:, :3]

plt.imsave(f'Reversed {filename}', out_img)


#f, (ax0, ax1, ax2) = plt.subplots(1, 3)
#ax0.imshow(img, cmap=plt.cm.gray)
#ax1.imshow(out, cmap=plt.cm.gray)
#ax2.imshow(out, cmap=plt.cm.jet)
#plt.show()

Nice script - where are you from? I have positions available in Chicago