SALib.plotting.morris module#

Created on 29 Jun 2015

@author: @willu47

This module provides the basic infrastructure for plotting charts for the Method of Morris results

The procedures should build upon and return an axes instance:

import matplotlib.pyplot as plt
Si = morris.analyze(problem, param_values, Y, conf_level=0.95,
                    print_to_console=False, num_levels=10)

# set plot style etc.
fig, ax = plt.subplots(1)
p = SALib.plotting.morris.horizontal_bar_plot(ax, Si, {'marker':'x'})
p.show()
SALib.plotting.morris.covariance_plot(ax, Si, opts=None, unit='')[source]#

Plots mu* against sigma or the 95% confidence interval

SALib.plotting.morris.horizontal_bar_plot(ax, Si, opts=None, sortby='mu_star', unit='')[source]#

Updates a matplotlib axes instance with a horizontal bar plot of mu_star, with error bars representing mu_star_conf.

SALib.plotting.morris.sample_histograms(fig, input_sample, problem, opts=None)[source]#

Plots a set of subplots of histograms of the input sample