Marianne Lemoine / ctools

Commit 081224fa2b3ed360cb63532bcbc1b0f6964aa636

Authored by knodlseder
1 parent e2e4bf73

show log histogram

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Showing 1 changed file with 6 additions and 6 deletions
examples/show_ts_distribution.py
  View file @081224f
@@ -99,7 +99,7 @@ if __name__ == '__main__': @@ -99,7 +99,7 @@ if __name__ == '__main__':
99 nbins = 30 99 nbins = 30
100 100
101 # Set lin/log 101 # Set lin/log
102 - log = False 102 + log = True
103 103
104 # Read values from CSV file 104 # Read values from CSV file
105 values = read_ts(filename) 105 values = read_ts(filename)
@@ -116,7 +116,7 @@ if __name__ == '__main__': @@ -116,7 +116,7 @@ if __name__ == '__main__':
116 116
117 # Create histogram 117 # Create histogram
118 n, bins, patches = plt.hist(values, nbins, range=[min_value, max_value], \ 118 n, bins, patches = plt.hist(values, nbins, range=[min_value, max_value], \
119 - align='mid', normed=True, facecolor='green', \ 119 + align='mid', facecolor='green', \
120 log=log) 120 log=log)
121 121
122 # Create expected distribution (onyl for positive TS). We compute the 122 # Create expected distribution (onyl for positive TS). We compute the
@@ -125,11 +125,11 @@ if __name__ == '__main__': @@ -125,11 +125,11 @@ if __name__ == '__main__':
125 x = [] 125 x = []
126 y_full = [] 126 y_full = []
127 y_half = [] 127 y_half = []
128 - norm = 1.0/(math.sqrt(2.0)*math.sqrt(math.pi))  
129 width = bins[1]-bins[0] 128 width = bins[1]-bins[0]
  129 + norm = len(values)/(math.sqrt(2.0)*math.sqrt(math.pi))*width
130 x.append(0.0) 130 x.append(0.0)
131 - y_full.append(1.0/width)  
132 - y_half.append(0.5/width) 131 + y_full.append(len(values))
  132 + y_half.append(0.5*len(values))
133 for bin in bins: 133 for bin in bins:
134 ts = bin + 0.5*width 134 ts = bin + 0.5*width
135 if ts > 0: 135 if ts > 0:
@@ -146,7 +146,7 @@ if __name__ == '__main__': @@ -146,7 +146,7 @@ if __name__ == '__main__':
146 146
147 # Set plot 147 # Set plot
148 plt.xlabel('TS') 148 plt.xlabel('TS')
149 - plt.ylabel('Arbitrary units') 149 + plt.ylabel('Number of trials')
150 plt.title('TS distribution') 150 plt.title('TS distribution')
151 plt.grid(True) 151 plt.grid(True)
152 152