marcel/pylot
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[edit] implemented a plotting method for pdf dictionaries

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This commit is contained in:
Sebastian Wehling-Benatelli 2016-05-11 06:01:26 +02:00
parent c7d7acd7e3
commit 63ac0107d0
1 changed files with 67 additions and 3 deletions
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70
pylot/core/pick/compare.py
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@ -86,8 +86,8 @@ class Comparison(object):
"""
compare_pdfs = dict()
pdf_a = self.get(self.names[0]).pdf_data(type)
pdf_b = self.get(self.names[1]).pdf_data(type)
pdf_a = self.get(self.names[0]).generate_pdf_data(type)
pdf_b = self.get(self.names[1]).generate_pdf_data(type)
for station, phases in pdf_a.items():
if station in pdf_b.keys():
@ -206,6 +206,7 @@ class PDFDictionary(object):
def __init__(self, data):
self._pickdata = data
self._pdfdata = self.generate_pdf_data()
def __nonzero__(self):
if len(self.pick_data) < 1:
@ -213,6 +214,14 @@ class PDFDictionary(object):
else:
return True
@property
def pdf_data(self):
return self._pdfdata
@pdf_data.setter
def pdf_data(self, data):
self._pdfdata = data
@property
def pick_data(self):
return self._pickdata
@ -221,6 +230,14 @@ class PDFDictionary(object):
def pick_data(self, data):
self._pickdata = data
@property
def stations(self):
return self.pick_data.keys()
@property
def nstations(self):
return len(self.stations)
@classmethod
def from_quakeml(self, fn):
cat = read_events(fn)
@ -229,7 +246,7 @@ class PDFDictionary(object):
'time is not implemented yet! Sorry!')
return PDFDictionary(picksdict_from_picks(cat[0]))
def pdf_data(self, type='exp'):
def generate_pdf_data(self, type='exp'):
"""
Returns probabiliy density function dictionary containing the
representation of the actual pick_data.
@ -251,3 +268,50 @@ class PDFDictionary(object):
return pdf_picks
def plot(self, stations=None):
assert stations is not None or not isinstance(stations, list), \
'parameter stations should be a list not {0}'.format(type(stations))
if not stations:
nstations = self.nstations
stations = self.stations
else:
nstations = len(stations)
istations = range(nstations)
fig, axarr = plt.subplots(nstations, 2, sharex='col', sharey='row')
for n in istations:
station = stations[n]
pdfs = self.pdf_data[station]
for l, phase in enumerate(pdfs.keys()):
hide_labels = True
try:
axarr[n, l].plot(pdfs[phase].axis, pdfs[phase].data)
if n is 0:
axarr[n, l].set_title(phase)
if l is 0:
axann = axarr[n, l].annotate(station, xy=(.05, .5),
xycoords='axes fraction')
bbox_props = dict(boxstyle='round', facecolor='lightgrey',
alpha=.7)
axann.set_bbox(bbox_props)
if n == int(np.median(istations)) and l is 0:
label = 'probability density (qualitative)'
axarr[n, l].set_ylabel(label)
except IndexError as e:
print('trying aligned plotting\n{0}'.format(e))
hide_labels = False
axarr[l].plot(pdfs[phase].axis, pdfs[phase].data)
axarr[l].set_title(phase)
if l is 0:
axann = axarr[l].annotate(station, xy=(.05, .5),
xycoords='axes fraction')
bbox_props = dict(boxstyle='round', facecolor='lightgrey',
alpha=.7)
axann.set_bbox(bbox_props)
if hide_labels:
plt.setp([a.get_xticklabels() for a in axarr[0, :]], visible=False)
plt.setp([a.get_yticklabels() for a in axarr[:, 1]], visible=False)
plt.setp([a.get_yticklabels() for a in axarr[:, 0]], visible=False)
plt.show()