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Merge EW-Drifts
Merge EW-Drifts
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optimun_offset.py
117 lines | 3.2 KiB | text/x-python | PythonLexer
/ schainpy / scripts / optimun_offset.py
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Juan C. Espinoza
Add optimun offset to scripts
 r990 import h5py
import numpy
import matplotlib.pyplot as plt
import glob
import os
#---------------------- Functions ---------------------
def findFiles(path):
dirList = []
fileList = []
for thisPath in os.listdir(path):
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 r1396 dirList.append(os.path.join(path, thisPath))
Juan C. Espinoza
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 r990 dirList.sort()
for thisDirectory in dirList:
files = glob.glob1(thisDirectory, "*.hdf5")
files.sort()
for thisFile in files:
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 r1396 fileList.append(os.path.join(thisDirectory, thisFile))
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 r990
return fileList
def readFiles(fileList):
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 r1396 meteors_array = numpy.zeros((1, 4))
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 r990
for thisFile in fileList:
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 r1396 # Leer
f1 = h5py.File(thisFile, 'r')
Juan C. Espinoza
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 r990 grp1 = f1['Data']
grp2 = grp1['data_output']
meteors1 = grp2['table0'][:]
jespinoza
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 r1396 meteors_array = numpy.vstack((meteors_array, meteors1))
# cerrar
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 r990 f1.close()
meteors_array = numpy.delete(meteors_array, 0, axis=0)
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 r1396 meteors_list = [meteors_array[:, 0], meteors_array[:, 1], meteors_array[:, 2], meteors_array[:, 3]]
Juan C. Espinoza
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 r990 return meteors_list
def estimateMean(offset_list):
mean_off = []
axisY_off = []
axisX_off = []
for thisOffset in offset_list:
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 r1396 mean_aux = numpy.mean(thisOffset, axis=0)
Juan C. Espinoza
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 r990 mean_off.append(mean_aux)
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 r1396 axisX_off.append(numpy.array([0, numpy.size(thisOffset)]))
axisY_off.append(numpy.array([mean_aux, mean_aux]))
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 r990
return mean_off, axisY_off, axisX_off
def plotPhases(offset0, axisY0, axisX0, title):
f, axarr = plt.subplots(4, sharey=True)
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 r1396 color = ['b', 'g', 'r', 'c']
Juan C. Espinoza
Add optimun offset to scripts
 r990 # plt.grid()
for i in range(len(offset0)):
thisMeteor = offset0[i]
thisY = axisY0[i]
thisX = axisX0[i]
thisColor = color[i]
opt = thisColor + 'o'
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 r1396 axarr[i].plot(thisMeteor, opt)
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 r990 axarr[i].plot(thisX, thisY, thisColor)
axarr[i].set_ylabel('Offset ' + str(i))
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 r1396 plt.ylim((-180, 180))
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 r990 axarr[0].set_title(title + ' Offsets')
axarr[3].set_xlabel('Number of estimations')
return
def filterOffsets(offsets0, stdvLimit):
offsets1 = []
for thisOffset in offsets0:
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 r1396 pstd = numpy.std(thisOffset) * stdvLimit
Juan C. Espinoza
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 r990 pmean = numpy.mean(thisOffset)
outlier1 = thisOffset > pmean - pstd
outlier2 = thisOffset < pmean + pstd
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 r1396 not_outlier = numpy.logical_and(outlier1, outlier2)
Juan C. Espinoza
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 r990 thisOffset1 = thisOffset[not_outlier]
offsets1.append(thisOffset1)
return offsets1
#---------------------- Setup ---------------------------
José Chávez
merge from master
 r1014 <<<<<<< HEAD
José Chávez
scripts?
 r993 path = '/home/nanosat/Pictures/JASMET30_mp/201608/phase'
jespinoza
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 r1396 == == == =
Juan C. Espinoza
Update setup and README
 r1000 path = '/home/jespinoza/Pictures/JASMET30/201608/phase'
José Chávez
merge from master
 r1014 >>>>>>> master
Juan C. Espinoza
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 r990 stdvLimit = 0.5
#---------------------- Script ---------------------------
fileList = findFiles(path)
offsets0 = readFiles(fileList)
mean0, axisY0, axisX0 = estimateMean(offsets0)
plotPhases(offsets0, axisY0, axisX0, 'Original')
offsets1 = filterOffsets(offsets0, stdvLimit)
mean1, axisY1, axisX1 = estimateMean(offsets1)
plotPhases(offsets1, axisY1, axisX1, 'Filtered')
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 r1396 print "Original Offsets: %.2f, %.2f, %.2f, %.2f" % (mean0[0], mean0[1], mean0[2], mean0[3])
print "Filtered Offsets: %.2f, %.2f, %.2f, %.2f" % (mean1[0], mean1[1], mean1[2], mean1[3])
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 r990
plt.show()