mpltex is a python package for creating publication-quality plots using matplotlib.
The internal matplotlib color cycle is replaced by Tableau classic 10 color scheme which looks less saturated and more pleasing to eyes. Other available color schemes for multi-line plots are ColorBrewer Set 1 and Tableau classic 20. For more information on these color schemes, see documentation of palettable.
mpltex also provide a way to generate highly configurable line styles with colors, line types, and line markers. Hollow markers are supported.
$ pip install mpltex
Examples and sample plots can be found here.
To use mpltex, just add one of mpltex decorators before your plot functions.
import mpltex @mpltex.acs_decorator def your_plot(): # plot images by matplotlib ... # Save the image. Give a file name without extension. # You can also save figure outside your_plot if you like. fig.save_fig('/path/to/save/fig/figname') # Then use your_plot in a normal way. your_plot()
And it will create a plot ready for publishing in journals published by American Chemical Society (ACS).
- mpltex.acs_decorator: output EPS images for publishing in ACS (American Chemical Society).
- mpltex.aps_decorator: output EPS images for publishing in APS (American Physical Society).
- mpltex.rsc_decorator: output EPS images for publishing in RSC (Royal Society of Chemistry).
- mpltex.presentation_decorator: output PDF images for presentation slides (Keynote).
- mpltex.web_decorator: output PNG images for web pages.
mpltex also provides several helper functions to facilitate production of specific type of images. Following codes will produce a set of line arts with cycled line styles with the help of mpltex.linestyle_generator function. Note that since version 0.5, linestyles is a shorthand for linestyle_generator.
import matplotlib.pyplot as plt import mpltex @mpltex.acs_decorator def your_plot(): # ... # generate data x and y fig, ax = plt.subplots(111) # The default line style is iterating over # color, line, and marker with hollow types. linestyles = mpltex.linestyles() # equivalently # linestyles = mpltex.linestyles() for i in range(number_of_lines): ax.plot(x[i], y[i], label=str(i), **linestyles.next()) ax.locator_params(nbins=5) # limit the number of major ticks ax.legend(loc='best') # show legend in a best location fig.tight_layout(pad=0.1) # make layout as tight as possible fig.savefig('/path/to/save/fig/figname')
Fork the project at github.com and file a pull request.