schain Commit - r1509:3817490cb0ad · Jicamarca Repository

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factor = 1

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factor = 1

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if hasattr(dataOut, 'nFFTPoints'):

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if hasattr(dataOut, 'nFFTPoints'):

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factor = dataOut.normFactor

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factor = dataOut.normFactor

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mask = dataOut.data_snr<self.snr_threshold

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mask = dataOut.data_snr<self.snr_threshold

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if 'pow' in self.attr_data[0].lower():

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if 'pow' in self.attr_data[0].lower():

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# data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor))

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# data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor))

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tmp = numpy.ma.masked_array(10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)), mask=mask)

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tmp = numpy.ma.masked_array(10*numpy.log10(10.0*getattr(dataOut, self.attr_data[0])/(factor)), mask=mask)

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else:

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else:

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tmp = numpy.ma.masked_array(getattr(dataOut, self.attr_data[0]), mask=mask)

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tmp = numpy.ma.masked_array(getattr(dataOut, self.attr_data[0]), mask=mask)

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# tmp = getattr(dataOut, self.attr_data[0])

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# tmp = getattr(dataOut, self.attr_data[0])

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var = data['data'].flatten()

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var = data['data'].flatten()

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r = numpy.tile(data['r'], data['data'].shape[0]).reshape(data['data'].shape)*1000

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r = numpy.tile(data['r'], data['data'].shape[0]).reshape(data['data'].shape)*1000

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lla = georef.spherical_to_proj(r, data['azi'], data['ele'], (-75.295893, -12.040436, 3379.2147))

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lla = georef.spherical_to_proj(r, data['azi'], data['ele'], (-75.295893, -12.040436, 3379.2147))

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meta['lat'] = lla[:,:,1].flatten()[var.mask==False]

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meta['lat'] = lla[:,:,1].flatten()[var.mask==False]

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meta['lon'] = lla[:,:,0].flatten()[var.mask==False]

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meta['lon'] = lla[:,:,0].flatten()[var.mask==False]

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data['var'] = numpy.array([var[var.mask==False]])

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data['var'] = numpy.array([var[var.mask==False]])

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return data, meta

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return data, meta

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def plot(self):

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def plot(self):

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                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     mask = dataOut.data_snr<self.snr_threshold
                     if 'pow' in self.attr_data[0].lower():
                         # data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor))
-                        tmp = numpy.ma.masked_array(10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)), mask=mask)
+                        tmp = numpy.ma.masked_array(10*numpy.log10(10.0*getattr(dataOut, self.attr_data[0])/(factor)), mask=mask)
                     else:
                         tmp = numpy.ma.masked_array(getattr(dataOut, self.attr_data[0]), mask=mask)
                         # tmp = getattr(dataOut, self.attr_data[0])
                     var = data['data'].flatten()
                     r = numpy.tile(data['r'], data['data'].shape[0]).reshape(data['data'].shape)*1000
                     lla = georef.spherical_to_proj(r, data['azi'], data['ele'], (-75.295893, -12.040436, 3379.2147))
                     meta['lat'] = lla[:,:,1].flatten()[var.mask==False]
                     meta['lon'] = lla[:,:,0].flatten()[var.mask==False]
                     data['var'] = numpy.array([var[var.mask==False]])
                     return data, meta
                 def plot(self):