Keeping track of scripts used to generate figures is difficult. Before realising that Jupyter Notebooks could solve most of my problems, I would have directories with dozens of scripts with filenames of varying levels of ambiguity. 371 more words
Tags » MatPlotLib
The introduction of sensor networks and the development of IoT devices and platforms makes essential the understanding and analysis of the collected data. We are developing a collection of Jupyter notebooks geared towards applied and computational… 16 more words
I prepared a solution to respond to the questions from KIVA. The project is described in the following link:
A clustering approach was used for 80 more words
plt.fill_between may be used to add shaded areas to charts. By using the alpha (transparency) argument shaded areas may overlap.
import matplotlib.pyplot as plt y1 = y1_max = y1_min = y2 = y2_max = y2_min = plt.plot(x, y1) plt.plot(x, y2, linestyle ='dashed') # alpha adjusts transparency, higher alpha --> darker grey # Or color could be set to, for example '0.2', but using transparency allows # overlapping shaded areas plt.fill_between(x, y1_min, y1_max, color = 'k', alpha = 0.1) plt.fill_between(x, y2_min, y2_max, color = 'k', alpha = 0.1) plt.show()