@@ -0,0 +1,1953 @@
+#!/usr/bin/env python%0A# a bar plot with errorbars%0Aimport numpy as np%0Aimport matplotlib.pyplot as plt%0A%0A# extract column of the dataset%0Adata = np.genfromtxt('../data/sens_scores_difftable.csv',delimiter=',',dtype=None)%0Astar_category = data%5B0,1:6%5D%0Adiffmeans     = data%5B1,1:6%5D%0Adiffstd       = data%5B2,1:6%5D%0A%0A# or type in the data%0AN = 5%0Adiffmeans = (8.2784, 15.6807, 0.9163, -40.3757, -18.6863)%0Adiffstd =   (10.5863, 10.0328, 9.9718, 35.6703, 28.8641)%0A%0Aind = np.arange(5)  # the x locations for the groups%0Awidth = 0.35       # the width of the bars%0A%0Afig = plt.figure()%0Aax = fig.add_subplot(111)%0Ap1 = ax.bar(ind, diffmeans, width, color='r', yerr=diffstd)%0A%0A# add some%0Aax.set_xlabel('Star Classification Method')%0Aax.set_ylabel('Difference in Mean GHI Scores Compared to the Default')%0Aax.set_title('Difference in Mean GHI Scores between 5 classification methods and the Default')%0Aax.set_xticks(ind+width)%0Aax.set_xticklabels( ('Geo', 'Geo-up', 'Geo-down', 'Infra-auto', 'Infra-selective') )%0A%0Aplt.show()%0A-------------------------%0A#!/usr/bin/env python%0A# a bar plot with errorbars%0Aimport numpy as np%0Aimport matplotlib.pyplot as plt%0A%0A# extract column of the dataset%0Adiffdata = np.genfromtxt('../data/sens_scores_difftable.csv',delimiter=',',dtype=None)%0A%0A# plot data%0Adef plot_bar_with_error(results):%0A    fig = plt.figure()%0A    ax = fig.add_subplot(111)%0A    # extract each column into a variable%0A    diffmeans = results%5B1,1:6%5D%0A    diffstd = results%5B2,1:6%5D%0A    ind = np.arange(5)%0A    width = 0.35%0A    p1 = ax.bar(ind, diffmeans, width, color='r', yerr=diffstd)%0A    plt.xlabel('Star Classification Method')%0A    plt.legend( (p1%5B0%5D, p1%5B1%5D, p1%5B2%5D, p1%5B3%5D, p1%5B4%5D), label)%0A    plt.xticks(ind+width/2., ('Default','GEO','GEO-Up','GEO-Down','INFRA-Auto','INFRA-Selective') )%0A%0Aplot_bar_with_error(diffdata)%0Aplt.ylabel('Difference in Mean GHI Scores Compared to the Default')%0Aplt.title('Difference in Mean GHI Scores between 5 Classification Methods and the Default')%0A%0Aplt.show()%0A

Create bar charts with error bars for foj sensitivity scores.