marcel/pylot
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[task] PDFStatistics object is now far more flexible

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This commit is contained in:
sebastianp 2016-08-09 10:07:27 +02:00
parent b72e16aaed
commit f4bdb38e16
1 changed files with 53 additions and 81 deletions
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134
pylot/core/pick/compare.py
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@ -345,13 +345,6 @@ class PDFstatistics(object):
''' '''
def __init__(self, directory): def __init__(self, directory):
self.directory = directory self.directory = directory
#self.arraylen = 0
# self.stations = {}
# self.p_std = {}
#self.s_std = {}
# self.theta0 = []
# self.theta1 = []
# self.theta2 = []
def readTheta(self, arname, dir, fnpattern): def readTheta(self, arname, dir, fnpattern):
@ -366,17 +359,11 @@ class PDFstatistics(object):
fid.close() fid.close()
def fromFileList(self):
self.makeFileList()
self.getData()
self.getStatistics()
def makeFileList(self, fn_pattern='*'): def makeFileList(self, fn_pattern='*'):
self.evtlist = glob.glob1((os.path.join(self.directory)), '*.xml') self.evtlist = glob.glob1((os.path.join(self.directory)), '*.xml')
def nextPDF(self):
def nextPDF(self):
for evt in self.evtlist: for evt in self.evtlist:
self.getPDFDict(self.directory, evt) self.getPDFDict(self.directory, evt)
for station, pdfs in self.pdfdict.pdf_data.items(): for station, pdfs in self.pdfdict.pdf_data.items():
@ -389,93 +376,75 @@ class PDFstatistics(object):
except KeyError: except KeyError:
yield np.nan yield np.nan
def getQD(self,value): def getQD(self,value):
pdfgen = self.nextPDF() pdfgen = self.nextPDF()
QDlist = [] QDlist = []
for pdf in pdfgen: for pdf in pdfgen:
if pdf == np.nan: try:
continue QD = pdf.quantile_distance(value)
QD = pdf.quantile_distance(value) QDlist.append(QD)
QDlist.append(QD) except AttributeError as e:
if e.message == "'float' object has no attribute 'quantile_distance'":
continue
return QDlist return QDlist
def getQDQ(self,value):
pdfgen = self.nextPDF()
QDQlist = []
for pdf in pdfgen:
try:
QDQ = pdf.qtile_dist_quot(value)
QDQlist.append(QDQ)
except AttributeError as e:
if e.message == "'float' object has no attribute 'quantile_distance'":
continue
return QDQlist
def getData(self):
for evt in self.evtlist: def getSTD(self):
print evt pdfgen = self.nextPDF()
self.stations[evt] = [] self.p_std = []
self.p_std[evt] = [] self.s_std = []
self.s_std[evt] = [] for pdf in pdfgen:
self.getPDFDict(self.directory, evt) try:
for station, pdfs in self.pdfdict.pdf_data.items(): self.p_std.append(pdf['P'].standard_deviation())
# print station, pdfs except KeyError:
try: pass
p_std = pdfs['P'].standard_deviation() try:
self.theta0.append(pdfs['P'].qtile_dist_quot(0.015)) self.s_std.append(pdf['S'].standard_deviation())
self.theta1.append(pdfs['P'].qtile_dist_quot(0.1)) except KeyError:
self.theta2.append(pdfs['P'].qtile_dist_quot(0.2)) pass
except KeyError:
p_std = np.nan
try:
s_std = pdfs['S'].standard_deviation()
self.theta0.append(pdfs['S'].qtile_dist_quot(0.015))
self.theta1.append(pdfs['S'].qtile_dist_quot(0.1))
self.theta2.append(pdfs['S'].qtile_dist_quot(0.2))
except KeyError:
s_std = np.nan
self.stations[evt].append(station)
self.p_std[evt].append(p_std)
self.s_std[evt].append(s_std)
self.arraylen += 1
self.makeArray() self.makeArray()
def makeArray(self): def makeArray(self):
index = 0 self.p_stdarray = np.array(self.p_std)
self.p_stdarray = np.zeros(self.arraylen) self.s_stdarray = np.array(self.s_std)
self.s_stdarray = np.zeros(self.arraylen)
for evt in self.p_std.keys():
for n in range(len(self.p_std[evt])):
self.p_stdarray[index] = self.p_std[evt][n]
self.s_stdarray[index] = self.s_std[evt][n]
index += 1
def histplot(self, num, label=None): def getBinList(self,l_boundary,u_boundary,nbins = 100):
binlist = [] binlist = []
if num == 0: for i in range(nbins):
bfactor = 0.001 binlist.append(l_boundary + i*(u_boundary-l_boundary)/nbins)
badd = 0 return binlist
elif num == 1:
bfactor = 0.003
badd = 0
else:
bfactor = 0.006
badd = 0.4
for i in range(100):
binlist.append(badd+bfactor*i)
import matplotlib.pyplot as plt
plt.hist(self.getTheta(num),bins = binlist)
def histplot(self, array, binlist, xlab = 'Values',
ylab = 'Frequency', title = None, label=None):
import matplotlib.pyplot as plt
plt.hist(array,bins = binlist)
plt.xlabel('Values') plt.xlabel('Values')
plt.ylabel('Frequency') plt.ylabel('Frequency')
title_str = 'Quantile distance quotient distribution' if title:
if label: title_str = 'Quantile distance quotient distribution'
title_str += ' (' + label + ')' if label:
plt.title(title_str) title_str += ' (' + label + ')'
plt.title(title_str)
plt.show() plt.show()
def getTheta(self,number):
if number == 0:
return self.theta0
elif number == 1:
return self.theta1
elif number == 2:
return self.theta2
def getPDFDict(self, month, evt): def getPDFDict(self, month, evt):
self.pdfdict = PDFDictionary.from_quakeml(os.path.join(self.directory,month,evt)) self.pdfdict = PDFDictionary.from_quakeml(os.path.join(self.directory,month,evt))
@ -499,8 +468,11 @@ def main():
root_dir ='/home/sebastianp/Codetesting/xmls/' root_dir ='/home/sebastianp/Codetesting/xmls/'
Insheim = PDFstatistics(root_dir) Insheim = PDFstatistics(root_dir)
Insheim.makeFileList() Insheim.makeFileList()
qdlist = Insheim.getQD(0.3) Insheim.getSTD()
Insheim.getStatistics()
qdlist = Insheim.getQDQ(0.3)
print qdlist print qdlist
if __name__ == "__main__": if __name__ == "__main__":
main() main()