I am using matplotlib to create 2d line-plots. For the purposes of publication, I would like to have those plots in black and white (not grayscale), and I am struggling to find a non-intrusive solution for that.
Gnuplot automatically alters dashing patterns for different lines, is something similar possible with matplotlib?
@alexzander If you want a black background for the axes, set 'axes. facecolor' to black.
MatPlotLib with Python The default color of a scatter point is blue. To get the default blue color of matplotlib scatter point, we can annotate them using annotate() method.
Below I provide functions to convert a colored line to a black line with unique style. My quick test showed that after 7 lines, the colors repeated. If this is not the case (and I made a mistake), then a minor adjustment is needed for the "constant" COLORMAP
in the provided routine.
Here's the routine and example:
import matplotlib.pyplot as plt import numpy as np def setAxLinesBW(ax): """ Take each Line2D in the axes, ax, and convert the line style to be suitable for black and white viewing. """ MARKERSIZE = 3 COLORMAP = { 'b': {'marker': None, 'dash': (None,None)}, 'g': {'marker': None, 'dash': [5,5]}, 'r': {'marker': None, 'dash': [5,3,1,3]}, 'c': {'marker': None, 'dash': [1,3]}, 'm': {'marker': None, 'dash': [5,2,5,2,5,10]}, 'y': {'marker': None, 'dash': [5,3,1,2,1,10]}, 'k': {'marker': 'o', 'dash': (None,None)} #[1,2,1,10]} } lines_to_adjust = ax.get_lines() try: lines_to_adjust += ax.get_legend().get_lines() except AttributeError: pass for line in lines_to_adjust: origColor = line.get_color() line.set_color('black') line.set_dashes(COLORMAP[origColor]['dash']) line.set_marker(COLORMAP[origColor]['marker']) line.set_markersize(MARKERSIZE) def setFigLinesBW(fig): """ Take each axes in the figure, and for each line in the axes, make the line viewable in black and white. """ for ax in fig.get_axes(): setAxLinesBW(ax) xval = np.arange(100)*.01 fig = plt.figure() ax = fig.add_subplot(211) ax.plot(xval,np.cos(2*np.pi*xval)) ax.plot(xval,np.cos(3*np.pi*xval)) ax.plot(xval,np.cos(4*np.pi*xval)) ax.plot(xval,np.cos(5*np.pi*xval)) ax.plot(xval,np.cos(6*np.pi*xval)) ax.plot(xval,np.cos(7*np.pi*xval)) ax.plot(xval,np.cos(8*np.pi*xval)) ax = fig.add_subplot(212) ax.plot(xval,np.cos(2*np.pi*xval)) ax.plot(xval,np.cos(3*np.pi*xval)) ax.plot(xval,np.cos(4*np.pi*xval)) ax.plot(xval,np.cos(5*np.pi*xval)) ax.plot(xval,np.cos(6*np.pi*xval)) ax.plot(xval,np.cos(7*np.pi*xval)) ax.plot(xval,np.cos(8*np.pi*xval)) fig.savefig("colorDemo.png") setFigLinesBW(fig) fig.savefig("bwDemo.png")
This provides the following two plots: First in color: Then in black and white:
You can adjust how each color is converted to a style. If you just want to only play with the dash style (-. vs. -- vs. whatever pattern you want), set the COLORMAP
corresponding 'marker' value to None
and adjusted the 'dash' pattern, or vice versa.
For example, the last color in the dictionary is 'k' (for black); originally I had only a dashed pattern [1,2,1,10]
, corresponding to one pixel shown, two not, one shown, 10 not, which is a dot-dot-space pattern. Then I commented that out, setting the dash to (None,None), a very formal way of saying solid line, and added the marker 'o', for circle.
I also set a 'constant' MARKERSIZE, which will set the size of each marker, because I found the default size to be a little large.
This obviously does not handle the case when your lines already have a dash or marker patter, but you can use these routines as a starting point to build a more sophisticated converter. For example if you original plot had a red solid line and a red dotted line, they both would turn into black dash-dot lines with these routines. Something to keep in mind when you use them.
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