| @@ -413,12 +413,12 class WeatherParamsPlot(Plot): | |||
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413 | 413 | factor = 1 |
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414 | 414 | if hasattr(dataOut, 'nFFTPoints'): |
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415 | 415 | factor = dataOut.normFactor |
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416 | ||
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416 | ||
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417 | 417 | mask = dataOut.data_snr<self.snr_threshold |
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418 | 418 | |
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419 | 419 | if 'pow' in self.attr_data[0].lower(): |
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420 | 420 | # data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
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421 | tmp = numpy.ma.masked_array(10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)), mask=mask) | |
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421 | tmp = numpy.ma.masked_array(10*numpy.log10(10.0*getattr(dataOut, self.attr_data[0])/(factor)), mask=mask) | |
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422 | 422 | else: |
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423 | 423 | tmp = numpy.ma.masked_array(getattr(dataOut, self.attr_data[0]), mask=mask) |
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424 | 424 | # tmp = getattr(dataOut, self.attr_data[0]) |
| @@ -446,10 +446,10 class WeatherParamsPlot(Plot): | |||
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446 | 446 | var = data['data'].flatten() |
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447 | 447 | r = numpy.tile(data['r'], data['data'].shape[0]).reshape(data['data'].shape)*1000 |
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448 | 448 | lla = georef.spherical_to_proj(r, data['azi'], data['ele'], (-75.295893, -12.040436, 3379.2147)) |
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449 |
meta['lat'] = lla[:,:,1].flatten()[var.mask==False] |
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449 | meta['lat'] = lla[:,:,1].flatten()[var.mask==False] | |
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450 | 450 | meta['lon'] = lla[:,:,0].flatten()[var.mask==False] |
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451 | 451 | data['var'] = numpy.array([var[var.mask==False]]) |
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452 | ||
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452 | ||
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453 | 453 | return data, meta |
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454 | 454 | |
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455 | 455 | def plot(self): |
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