[refs #195] implementation of histogram plots
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@ -130,6 +130,46 @@ class Comparison(object):
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plt.show()
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def get_expectation_array(self, phase):
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pdf_dict = self.comparison
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exp_array = list()
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for station, phases in pdf_dict.items():
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exp_array.append(phases[phase].expectation())
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return exp_array
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def get_std_array(self, phase):
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pdf_dict = self.comparison
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std_array = list()
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for station, phases in pdf_dict.items():
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std_array.append(phases[phase].standard_deviation())
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return std_array
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def hist_expectation(self, phases='all', bins=50, normed=False):
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phases.strip()
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if phases.find('all') == 0:
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phases = 'ps'
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phases = phases.upper()
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nsp = len(phases)
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fig, axarray = plt.subplots(1, nsp, sharey=True)
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for n, phase in enumerate(phases):
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ax = axarray[0, n]
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data = self.get_expectation_array(phase)
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xlims = [np.floor(min(data)), np.ceil(max(data))]
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ax.hist(data, xlims=xlims, bins=bins, normed=normed)
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title_str = 'phase: {0}, samples: {1}'.format(phase, len(data))
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ax.title(title_str)
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ax.xlabel('expectation [s]')
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if n is 0:
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ax.ylabel('abundance [-]')
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plt.setp([a.get_yticklabels() for a in axarray[0, 1:]], visible=False)
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plt.show()
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def hist_standard_deviation(self):
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pass
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def hist(self, type='std'):
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pass
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class PDFDictionary(object):
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"""
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