colorstamps
Python package for 2D colormaps. Most included colormaps are based on the 'CAM02-LCD' colorspace as defined in the package colorspacious (https://pypi.org/project/colorspacious/)
Documentation is hosted at https://colorstamps.readthedocs.io/en/latest/ but a summary follows below:
Installation: pip install colorstamps
Example:
import matplotlib.pyplot as plt
import colorstamps
img = colorstamps.helpers.get_random_data() # numpy array of shape (100,200,2) with 2d data to plot
rgb, stamp = colorstamps.apply_stamp(img[:,:,0], img[:,:,1], 'peak',
vmin_0 = -1.2, vmax_0 = 1.2,
vmin_1 = -1, vmax_1 = 1,
)
fig, axes = plt.subplots(1,2,figsize=(10,3), dpi = 100)
axes[0].imshow(rgb)
# show colormap as overlay
overlaid_ax = stamp.overlay_ax(axes[0], lower_left_corner = [0.7,0.85], width = 0.2)
overlaid_ax.set_ylabel(r'$\phi$')
overlaid_ax.set_xlabel(r'$\omega$')
# also show colormap as in separate ax to illustrate functionality
stamp.show_in_ax(axes[1])
axes[1].set_ylabel(r'$\phi$')
axes[1].set_xlabel(r'$\omega$')
Examples of included colormaps are shown below:
Customization
All the colormaps are called by colorstamps.stamps.get_cmap() and the following keyword can be used with either colorstamps.apply_stamp() or colorstamps.stamps.get_cmap() to customize the colormaps:
l: int, the size of the colormap will be (l,l), defaults to 256 if None
rot: float, rotation of the colormap (where applicable)
J: array-like of length 2 (float,float), determins min and max luminocity where applicable
sat: float, maximum saturation where applicable
limit_sat: string, 'individual' or 'shared'. How saturation is limited for relevant colormaps when colors outside sRGB are required
'individual': each combination J, hue in the colormap has an individual limit to saturation
'shared': for each J, all hues share a limit, the maximum where all hues can be represented
a: range along a-axis, array-like [min,max]
Used to move the center of the colormap where applicable.
Defaults to (-1,1) which is then multiplied internally with sat
b: range along b-axis, see a.
Additionally, for radial colormaps the name may have a postfix separated by a space, i.e. 'cone tr'
the postfix must be some combination of (t,b) and/or (l,r) which defines the quadrant/side of the colormap to include
t-> top, b-> bottom, r-> right, l-> left, and 'tr'-> top right, etc.
Evaluation of colormaps
The package also includes a method for evaluating colormaps, by evaluating the distribution of lighness, hue, saturation, and how it can be percieved by those with partial colorblindness
stamp = colorstamps.Stamp('hsv')
fig, ax = stamp.eval()
stamp = colorstamps.Stamp('peak')
fig, ax = stamp.eval()
The package also supports different methods for clipping data to the colormap, using the 'clip' keyword in colorstamps.apply_stamp()
Additional colormaps
Additional colormaps available by converting 1d colormaps in matplotlib to 2d colormaps by varying the lightness along the y-axis:
User-provided colormaps
Custom colormaps may be integrated by providing a numpy array of shape (l,l,3) detailing a 2d colormap instead of a name when calling colorstamps.apply_stamp()
my_cmap = np.zeros((256,256,3))
my_cmap[:,:,0] = np.linspace(0,1,256)[:,np.newaxis]
my_cmap[:,:,2] = np.linspace(0,1,256)[np.newaxis,:]
my_cmap[:,:,1] = 0.5*(my_cmap[:,:,0]+my_cmap[:,:,2])
img = colorstamps.helpers.get_random_data() # numpy array of shape (100,200,2) with 2d data to plot
fig, ax = plt.subplots(1,1,figsize=(5,3), dpi = 100)
rgb, stamp = colorstamps.apply_stamp(img[:,:,0], img[:,:,1], my_cmap)
ax.imshow(rgb)
overlaid_ax = stamp.overlay_ax(ax, lower_left_corner = [0.66,0.85], width = 0.2)
overlaid_ax.set_ylabel(r'$\phi$')
overlaid_ax.set_xlabel(r'$\omega$')
support
Any contributions that would provide additional colormaps for are welcome, as are contributions to increase the functionality.
