I am trying to extract discrete colors from a matplotlib colormap by manipulating this example. However, I cannot find the N
discrete colors that are extracted from the colormap.
In the code below I've used cmap._segmentdata
, but I've found that it is the definition of the entire colormap. Given a colormap and an integer N
, how do I extract N
discrete colors from the colormap and export them in hex-format?
from pylab import *
delta = 0.01
x = arange(-3.0, 3.0, delta)
y = arange(-3.0, 3.0, delta)
X,Y = meshgrid(x, y)
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = Z2 - Z1 # difference of Gaussians
cmap = cm.get_cmap('seismic', 5) # PiYG
cmap_colors = cmap._segmentdata
def print_hex(r,b,g):
if not(0 <= r <= 255 or 0 <= b <= 255 or 0 <= g <= 255):
raise ValueError('rgb not in range(256)')
print '#%02x%02x%02x' % (r, b, g)
for i in range(len(cmap_colors['blue'])):
r = int(cmap_colors['red'][i][2]*255)
b = int(cmap_colors['blue'][i][2]*255)
g = int(cmap_colors['green'][i][2]*255)
print_hex(r, g, b)
im = imshow(Z, cmap=cmap, interpolation='bilinear',
vmax=abs(Z).max(), vmin=-abs(Z).max())
axis('off')
colorbar()
show()
You can get a tuple of rgba values for the segment with index i
by calling cmap(i)
. There is also already a function that turns rgb values into hex. As Joe Kington wrote in the comments, you can use matplotlib.colors.rgb2hex
. Therefore, a possible solution would be:
from pylab import *
cmap = cm.get_cmap('seismic', 5) # PiYG
for i in range(cmap.N):
rgba = cmap(i)
# rgb2hex accepts rgb or rgba
print(matplotlib.colors.rgb2hex(rgba))
The output is:
#00004c
#0000ff
#ffffff
#ff0000
#7f0000