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Copy pathplot.py
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100 lines (84 loc) · 2.59 KB
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import matplotlib.pyplot as plt
def colorGenerator():
"Return cycling list of colors"
colors = [ 'red', 'green', 'blue', 'purple', 'orange', 'cyan']
index = 0
while True:
yield colors[ index ]
index = ( index + 1 ) % len( colors )
def markerGenerator():
"Return cycling list of colors"
markers = [ 'o', '^', 'v', '*', 'x', 'd']
index = 0
while True:
yield markers [ index ]
index = ( index + 1 ) % len(markers)
def convertToStep(x, y):
"""Convert to a "stepped" data format by duplicating all but the last elt."""
newx = []
newy = []
for i, d in enumerate(x):
newx.append(d)
newy.append(y[i])
if i != len(x) - 1:
newx.append(x[i + 1])
newy.append(y[i])
return newx, newy
def convertToStepUpCDF(x, y):
"""Convert to a "stepped" data format by duplicating all but the last elt.
Step goes up, rather than to the right.
"""
newx = []
newy = []
for i, d in enumerate(x):
newx.append(d)
newy.append(y[i])
if i != len(x) - 1:
newx.append(x[i])
newy.append(y[i + 1])
newx.append(newx[-1])
newy.append(1.0)
return newx, newy
def plotTimeSeries(data, title, xlabel, ylabel, step):
"""Plot a time series.
Input: data, a list of dicts.
Each inner-most dict includes the following fields:
x: array
y: array
label: string
step: if True, display data in stepped form.
"""
fig = plt.figure()
ax = plt.subplot(111)
cgen = colorGenerator()
colors = {}
fig.canvas.set_window_title( title )
for d in data:
x = d['x']
y = d['y']
if step:
x, y = convertToStep(x, y)
plt.plot( x, y, label=d['label'], color=cgen.next())
plt.xlabel( xlabel, fontsize=20 )
plt.ylabel( ylabel, fontsize=20 )
plt.grid( True )
for tick in ax.xaxis.get_major_ticks():
tick.label1.set_fontsize(18)
for tick in ax.yaxis.get_major_ticks():
tick.label1.set_fontsize(18)
return fig
def plotCDF(data, title, xlabel, ylabel, step):
data_mod = []
for index, line in enumerate(data):
vals = sorted(line['y'])
x = sorted(vals)
y = [(float(i) / len(x)) for i in range(len(x))]
x, y = convertToStepUpCDF(x, y)
entry = {}
entry['x'] = x
entry['y'] = y
entry['label'] = line['label']
data_mod.append(entry)
return plotTimeSeries(data_mod, title, xlabel, ylabel, step = False)
if __name__ == '__main__':
print convertToStep([1, 2, 3], [4, 5, 6])