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import os
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import os
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import datetime
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import datetime
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import numpy
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import numpy
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from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter
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from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter
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from schainpy.model.graphics.jroplot_base import Plot, plt
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from schainpy.model.graphics.jroplot_base import Plot, plt
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from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
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from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
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from schainpy.utils import log
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from schainpy.utils import log
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# libreria wradlib
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# libreria wradlib
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import wradlib as wrl
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import wradlib as wrl
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EARTH_RADIUS = 6.3710e3
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EARTH_RADIUS = 6.3710e3
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def ll2xy(lat1, lon1, lat2, lon2):
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def ll2xy(lat1, lon1, lat2, lon2):
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p = 0.017453292519943295
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p = 0.017453292519943295
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a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \
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a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \
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numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
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numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
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r = 12742 * numpy.arcsin(numpy.sqrt(a))
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r = 12742 * numpy.arcsin(numpy.sqrt(a))
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theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p)
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theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p)
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* numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p))
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* numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p))
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theta = -theta + numpy.pi/2
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theta = -theta + numpy.pi/2
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return r*numpy.cos(theta), r*numpy.sin(theta)
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return r*numpy.cos(theta), r*numpy.sin(theta)
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def km2deg(km):
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def km2deg(km):
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'''
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'''
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Convert distance in km to degrees
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Convert distance in km to degrees
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'''
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'''
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return numpy.rad2deg(km/EARTH_RADIUS)
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return numpy.rad2deg(km/EARTH_RADIUS)
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class SpectralMomentsPlot(SpectraPlot):
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class SpectralMomentsPlot(SpectraPlot):
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'''
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'''
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Plot for Spectral Moments
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Plot for Spectral Moments
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'''
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'''
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CODE = 'spc_moments'
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CODE = 'spc_moments'
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# colormap = 'jet'
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# colormap = 'jet'
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# plot_type = 'pcolor'
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# plot_type = 'pcolor'
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class DobleGaussianPlot(SpectraPlot):
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class DobleGaussianPlot(SpectraPlot):
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'''
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'''
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Plot for Double Gaussian Plot
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Plot for Double Gaussian Plot
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'''
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'''
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CODE = 'gaussian_fit'
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CODE = 'gaussian_fit'
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# colormap = 'jet'
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# colormap = 'jet'
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# plot_type = 'pcolor'
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# plot_type = 'pcolor'
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class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
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class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
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'''
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'''
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Plot SpectraCut with Double Gaussian Fit
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Plot SpectraCut with Double Gaussian Fit
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'''
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'''
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CODE = 'cut_gaussian_fit'
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CODE = 'cut_gaussian_fit'
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class SnrPlot(RTIPlot):
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class SnrPlot(RTIPlot):
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'''
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'''
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Plot for SNR Data
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Plot for SNR Data
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'''
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'''
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CODE = 'snr'
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CODE = 'snr'
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colormap = 'jet'
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colormap = 'jet'
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def update(self, dataOut):
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def update(self, dataOut):
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data = {
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data = {
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'snr': 10*numpy.log10(dataOut.data_snr)
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'snr': 10*numpy.log10(dataOut.data_snr)
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}
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}
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return data, {}
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return data, {}
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class DopplerPlot(RTIPlot):
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class DopplerPlot(RTIPlot):
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'''
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'''
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Plot for DOPPLER Data (1st moment)
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Plot for DOPPLER Data (1st moment)
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'''
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'''
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CODE = 'dop'
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CODE = 'dop'
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colormap = 'jet'
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colormap = 'jet'
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def update(self, dataOut):
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def update(self, dataOut):
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data = {
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data = {
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'dop': 10*numpy.log10(dataOut.data_dop)
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'dop': 10*numpy.log10(dataOut.data_dop)
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}
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}
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return data, {}
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return data, {}
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class PowerPlot(RTIPlot):
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class PowerPlot(RTIPlot):
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'''
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'''
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Plot for Power Data (0 moment)
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Plot for Power Data (0 moment)
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'''
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'''
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CODE = 'pow'
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CODE = 'pow'
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colormap = 'jet'
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colormap = 'jet'
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def update(self, dataOut):
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def update(self, dataOut):
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data = {
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data = {
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'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor)
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'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor)
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}
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}
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return data, {}
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return data, {}
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class SpectralWidthPlot(RTIPlot):
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class SpectralWidthPlot(RTIPlot):
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'''
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'''
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Plot for Spectral Width Data (2nd moment)
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Plot for Spectral Width Data (2nd moment)
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'''
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'''
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CODE = 'width'
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CODE = 'width'
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colormap = 'jet'
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colormap = 'jet'
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def update(self, dataOut):
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def update(self, dataOut):
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data = {
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data = {
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'width': dataOut.data_width
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'width': dataOut.data_width
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}
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}
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return data, {}
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return data, {}
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class SkyMapPlot(Plot):
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class SkyMapPlot(Plot):
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'''
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'''
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Plot for meteors detection data
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Plot for meteors detection data
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'''
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'''
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CODE = 'param'
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CODE = 'param'
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def setup(self):
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def setup(self):
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self.ncols = 1
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self.ncols = 1
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self.nrows = 1
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self.nrows = 1
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self.width = 7.2
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self.width = 7.2
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self.height = 7.2
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self.height = 7.2
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self.nplots = 1
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self.nplots = 1
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self.xlabel = 'Zonal Zenith Angle (deg)'
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self.xlabel = 'Zonal Zenith Angle (deg)'
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self.ylabel = 'Meridional Zenith Angle (deg)'
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self.ylabel = 'Meridional Zenith Angle (deg)'
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self.polar = True
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self.polar = True
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self.ymin = -180
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self.ymin = -180
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self.ymax = 180
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self.ymax = 180
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self.colorbar = False
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self.colorbar = False
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def plot(self):
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def plot(self):
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arrayParameters = numpy.concatenate(self.data['param'])
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arrayParameters = numpy.concatenate(self.data['param'])
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error = arrayParameters[:, -1]
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error = arrayParameters[:, -1]
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indValid = numpy.where(error == 0)[0]
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indValid = numpy.where(error == 0)[0]
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finalMeteor = arrayParameters[indValid, :]
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finalMeteor = arrayParameters[indValid, :]
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finalAzimuth = finalMeteor[:, 3]
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finalAzimuth = finalMeteor[:, 3]
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finalZenith = finalMeteor[:, 4]
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finalZenith = finalMeteor[:, 4]
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x = finalAzimuth * numpy.pi / 180
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x = finalAzimuth * numpy.pi / 180
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y = finalZenith
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y = finalZenith
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ax = self.axes[0]
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ax = self.axes[0]
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if ax.firsttime:
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if ax.firsttime:
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ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
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ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
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else:
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else:
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ax.plot.set_data(x, y)
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ax.plot.set_data(x, y)
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dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
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dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
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dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
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dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
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title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
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title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
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dt2,
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dt2,
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len(x))
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len(x))
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self.titles[0] = title
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self.titles[0] = title
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class GenericRTIPlot(Plot):
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class GenericRTIPlot(Plot):
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'''
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'''
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Plot for data_xxxx object
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Plot for data_xxxx object
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'''
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'''
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CODE = 'param'
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CODE = 'param'
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colormap = 'viridis'
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colormap = 'viridis'
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plot_type = 'pcolorbuffer'
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plot_type = 'pcolorbuffer'
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def setup(self):
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def setup(self):
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self.xaxis = 'time'
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self.xaxis = 'time'
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self.ncols = 1
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self.ncols = 1
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self.nrows = self.data.shape('param')[0]
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self.nrows = self.data.shape('param')[0]
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self.nplots = self.nrows
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self.nplots = self.nrows
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self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
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self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
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if not self.xlabel:
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if not self.xlabel:
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self.xlabel = 'Time'
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self.xlabel = 'Time'
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self.ylabel = 'Range [km]'
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self.ylabel = 'Range [km]'
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if not self.titles:
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188
|
if not self.titles:
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189
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self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
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189
|
self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
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190
|
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190
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|
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191
|
def update(self, dataOut):
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191
|
def update(self, dataOut):
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192
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192
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|
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193
|
data = {
|
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193
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data = {
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194
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'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
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194
|
'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
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195
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}
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195
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}
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196
|
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196
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197
|
meta = {}
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197
|
meta = {}
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198
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198
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199
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return data, meta
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199
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return data, meta
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200
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200
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201
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def plot(self):
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201
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def plot(self):
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202
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# self.data.normalize_heights()
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202
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# self.data.normalize_heights()
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203
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self.x = self.data.times
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203
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self.x = self.data.times
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204
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self.y = self.data.yrange
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204
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self.y = self.data.yrange
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205
|
self.z = self.data['param']
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205
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self.z = self.data['param']
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206
|
self.z = 10*numpy.log10(self.z)
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206
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self.z = 10*numpy.log10(self.z)
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207
|
self.z = numpy.ma.masked_invalid(self.z)
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207
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self.z = numpy.ma.masked_invalid(self.z)
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208
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208
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209
|
if self.decimation is None:
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209
|
if self.decimation is None:
|
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210
|
x, y, z = self.fill_gaps(self.x, self.y, self.z)
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210
|
x, y, z = self.fill_gaps(self.x, self.y, self.z)
|
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211
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else:
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211
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else:
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212
|
x, y, z = self.fill_gaps(*self.decimate())
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212
|
x, y, z = self.fill_gaps(*self.decimate())
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213
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213
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214
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for n, ax in enumerate(self.axes):
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214
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for n, ax in enumerate(self.axes):
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215
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215
|
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216
|
self.zmax = self.zmax if self.zmax is not None else numpy.max(
|
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216
|
self.zmax = self.zmax if self.zmax is not None else numpy.max(
|
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217
|
self.z[n])
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217
|
self.z[n])
|
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|
218
|
self.zmin = self.zmin if self.zmin is not None else numpy.min(
|
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218
|
self.zmin = self.zmin if self.zmin is not None else numpy.min(
|
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219
|
self.z[n])
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219
|
self.z[n])
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220
|
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220
|
|
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221
|
if ax.firsttime:
|
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221
|
if ax.firsttime:
|
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222
|
if self.zlimits is not None:
|
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222
|
if self.zlimits is not None:
|
|
|
223
|
self.zmin, self.zmax = self.zlimits[n]
|
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223
|
self.zmin, self.zmax = self.zlimits[n]
|
|
|
224
|
|
|
224
|
|
|
|
225
|
ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
|
|
225
|
ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
|
|
|
226
|
vmin=self.zmin,
|
|
226
|
vmin=self.zmin,
|
|
|
227
|
vmax=self.zmax,
|
|
227
|
vmax=self.zmax,
|
|
|
228
|
cmap=self.cmaps[n]
|
|
228
|
cmap=self.cmaps[n]
|
|
|
229
|
)
|
|
229
|
)
|
|
|
230
|
else:
|
|
230
|
else:
|
|
|
231
|
if self.zlimits is not None:
|
|
231
|
if self.zlimits is not None:
|
|
|
232
|
self.zmin, self.zmax = self.zlimits[n]
|
|
232
|
self.zmin, self.zmax = self.zlimits[n]
|
|
|
233
|
ax.collections.remove(ax.collections[0])
|
|
233
|
ax.collections.remove(ax.collections[0])
|
|
|
234
|
ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
|
|
234
|
ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
|
|
|
235
|
vmin=self.zmin,
|
|
235
|
vmin=self.zmin,
|
|
|
236
|
vmax=self.zmax,
|
|
236
|
vmax=self.zmax,
|
|
|
237
|
cmap=self.cmaps[n]
|
|
237
|
cmap=self.cmaps[n]
|
|
|
238
|
)
|
|
238
|
)
|
|
|
239
|
|
|
239
|
|
|
|
240
|
|
|
240
|
|
|
|
241
|
class PolarMapPlot(Plot):
|
|
241
|
class PolarMapPlot(Plot):
|
|
|
242
|
'''
|
|
242
|
'''
|
|
|
243
|
Plot for weather radar
|
|
243
|
Plot for weather radar
|
|
|
244
|
'''
|
|
244
|
'''
|
|
|
245
|
|
|
245
|
|
|
|
246
|
CODE = 'param'
|
|
246
|
CODE = 'param'
|
|
|
247
|
colormap = 'seismic'
|
|
247
|
colormap = 'seismic'
|
|
|
248
|
|
|
248
|
|
|
|
249
|
def setup(self):
|
|
249
|
def setup(self):
|
|
|
250
|
self.ncols = 1
|
|
250
|
self.ncols = 1
|
|
|
251
|
self.nrows = 1
|
|
251
|
self.nrows = 1
|
|
|
252
|
self.width = 9
|
|
252
|
self.width = 9
|
|
|
253
|
self.height = 8
|
|
253
|
self.height = 8
|
|
|
254
|
self.mode = self.data.meta['mode']
|
|
254
|
self.mode = self.data.meta['mode']
|
|
|
255
|
if self.channels is not None:
|
|
255
|
if self.channels is not None:
|
|
|
256
|
self.nplots = len(self.channels)
|
|
256
|
self.nplots = len(self.channels)
|
|
|
257
|
self.nrows = len(self.channels)
|
|
257
|
self.nrows = len(self.channels)
|
|
|
258
|
else:
|
|
258
|
else:
|
|
|
259
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
259
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
|
260
|
self.nrows = self.nplots
|
|
260
|
self.nrows = self.nplots
|
|
|
261
|
self.channels = list(range(self.nplots))
|
|
261
|
self.channels = list(range(self.nplots))
|
|
|
262
|
if self.mode == 'E':
|
|
262
|
if self.mode == 'E':
|
|
|
263
|
self.xlabel = 'Longitude'
|
|
263
|
self.xlabel = 'Longitude'
|
|
|
264
|
self.ylabel = 'Latitude'
|
|
264
|
self.ylabel = 'Latitude'
|
|
|
265
|
else:
|
|
265
|
else:
|
|
|
266
|
self.xlabel = 'Range (km)'
|
|
266
|
self.xlabel = 'Range (km)'
|
|
|
267
|
self.ylabel = 'Height (km)'
|
|
267
|
self.ylabel = 'Height (km)'
|
|
|
268
|
self.bgcolor = 'white'
|
|
268
|
self.bgcolor = 'white'
|
|
|
269
|
self.cb_labels = self.data.meta['units']
|
|
269
|
self.cb_labels = self.data.meta['units']
|
|
|
270
|
self.lat = self.data.meta['latitude']
|
|
270
|
self.lat = self.data.meta['latitude']
|
|
|
271
|
self.lon = self.data.meta['longitude']
|
|
271
|
self.lon = self.data.meta['longitude']
|
|
|
272
|
self.xmin, self.xmax = float(
|
|
272
|
self.xmin, self.xmax = float(
|
|
|
273
|
km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
|
|
273
|
km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
|
|
|
274
|
self.ymin, self.ymax = float(
|
|
274
|
self.ymin, self.ymax = float(
|
|
|
275
|
km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
|
|
275
|
km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
|
|
|
276
|
# self.polar = True
|
|
276
|
# self.polar = True
|
|
|
277
|
|
|
277
|
|
|
|
278
|
def plot(self):
|
|
278
|
def plot(self):
|
|
|
279
|
|
|
279
|
|
|
|
280
|
for n, ax in enumerate(self.axes):
|
|
280
|
for n, ax in enumerate(self.axes):
|
|
|
281
|
data = self.data['param'][self.channels[n]]
|
|
281
|
data = self.data['param'][self.channels[n]]
|
|
|
282
|
|
|
282
|
|
|
|
283
|
zeniths = numpy.linspace(
|
|
283
|
zeniths = numpy.linspace(
|
|
|
284
|
0, self.data.meta['max_range'], data.shape[1])
|
|
284
|
0, self.data.meta['max_range'], data.shape[1])
|
|
|
285
|
if self.mode == 'E':
|
|
285
|
if self.mode == 'E':
|
|
|
286
|
azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2
|
|
286
|
azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2
|
|
|
287
|
r, theta = numpy.meshgrid(zeniths, azimuths)
|
|
287
|
r, theta = numpy.meshgrid(zeniths, azimuths)
|
|
|
288
|
x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(
|
|
288
|
x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(
|
|
|
289
|
theta)*numpy.cos(numpy.radians(self.data.meta['elevation']))
|
|
289
|
theta)*numpy.cos(numpy.radians(self.data.meta['elevation']))
|
|
|
290
|
x = km2deg(x) + self.lon
|
|
290
|
x = km2deg(x) + self.lon
|
|
|
291
|
y = km2deg(y) + self.lat
|
|
291
|
y = km2deg(y) + self.lat
|
|
|
292
|
else:
|
|
292
|
else:
|
|
|
293
|
azimuths = numpy.radians(self.data.yrange)
|
|
293
|
azimuths = numpy.radians(self.data.yrange)
|
|
|
294
|
r, theta = numpy.meshgrid(zeniths, azimuths)
|
|
294
|
r, theta = numpy.meshgrid(zeniths, azimuths)
|
|
|
295
|
x, y = r*numpy.cos(theta), r*numpy.sin(theta)
|
|
295
|
x, y = r*numpy.cos(theta), r*numpy.sin(theta)
|
|
|
296
|
self.y = zeniths
|
|
296
|
self.y = zeniths
|
|
|
297
|
|
|
297
|
|
|
|
298
|
if ax.firsttime:
|
|
298
|
if ax.firsttime:
|
|
|
299
|
if self.zlimits is not None:
|
|
299
|
if self.zlimits is not None:
|
|
|
300
|
self.zmin, self.zmax = self.zlimits[n]
|
|
300
|
self.zmin, self.zmax = self.zlimits[n]
|
|
|
301
|
ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
301
|
ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
|
302
|
x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
302
|
x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
|
303
|
vmin=self.zmin,
|
|
303
|
vmin=self.zmin,
|
|
|
304
|
vmax=self.zmax,
|
|
304
|
vmax=self.zmax,
|
|
|
305
|
cmap=self.cmaps[n])
|
|
305
|
cmap=self.cmaps[n])
|
|
|
306
|
else:
|
|
306
|
else:
|
|
|
307
|
if self.zlimits is not None:
|
|
307
|
if self.zlimits is not None:
|
|
|
308
|
self.zmin, self.zmax = self.zlimits[n]
|
|
308
|
self.zmin, self.zmax = self.zlimits[n]
|
|
|
309
|
ax.collections.remove(ax.collections[0])
|
|
309
|
ax.collections.remove(ax.collections[0])
|
|
|
310
|
ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
310
|
ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
|
311
|
x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
311
|
x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
|
|
|
312
|
vmin=self.zmin,
|
|
312
|
vmin=self.zmin,
|
|
|
313
|
vmax=self.zmax,
|
|
313
|
vmax=self.zmax,
|
|
|
314
|
cmap=self.cmaps[n])
|
|
314
|
cmap=self.cmaps[n])
|
|
|
315
|
|
|
315
|
|
|
|
316
|
if self.mode == 'A':
|
|
316
|
if self.mode == 'A':
|
|
|
317
|
continue
|
|
317
|
continue
|
|
|
318
|
|
|
318
|
|
|
|
319
|
# plot district names
|
|
319
|
# plot district names
|
|
|
320
|
f = open('/data/workspace/schain_scripts/distrito.csv')
|
|
320
|
f = open('/data/workspace/schain_scripts/distrito.csv')
|
|
|
321
|
for line in f:
|
|
321
|
for line in f:
|
|
|
322
|
label, lon, lat = [s.strip() for s in line.split(',') if s]
|
|
322
|
label, lon, lat = [s.strip() for s in line.split(',') if s]
|
|
|
323
|
lat = float(lat)
|
|
323
|
lat = float(lat)
|
|
|
324
|
lon = float(lon)
|
|
324
|
lon = float(lon)
|
|
|
325
|
# ax.plot(lon, lat, '.b', ms=2)
|
|
325
|
# ax.plot(lon, lat, '.b', ms=2)
|
|
|
326
|
ax.text(lon, lat, label.decode('utf8'), ha='center',
|
|
326
|
ax.text(lon, lat, label.decode('utf8'), ha='center',
|
|
|
327
|
va='bottom', size='8', color='black')
|
|
327
|
va='bottom', size='8', color='black')
|
|
|
328
|
|
|
328
|
|
|
|
329
|
# plot limites
|
|
329
|
# plot limites
|
|
|
330
|
limites = []
|
|
330
|
limites = []
|
|
|
331
|
tmp = []
|
|
331
|
tmp = []
|
|
|
332
|
for line in open('/data/workspace/schain_scripts/lima.csv'):
|
|
332
|
for line in open('/data/workspace/schain_scripts/lima.csv'):
|
|
|
333
|
if '#' in line:
|
|
333
|
if '#' in line:
|
|
|
334
|
if tmp:
|
|
334
|
if tmp:
|
|
|
335
|
limites.append(tmp)
|
|
335
|
limites.append(tmp)
|
|
|
336
|
tmp = []
|
|
336
|
tmp = []
|
|
|
337
|
continue
|
|
337
|
continue
|
|
|
338
|
values = line.strip().split(',')
|
|
338
|
values = line.strip().split(',')
|
|
|
339
|
tmp.append((float(values[0]), float(values[1])))
|
|
339
|
tmp.append((float(values[0]), float(values[1])))
|
|
|
340
|
for points in limites:
|
|
340
|
for points in limites:
|
|
|
341
|
ax.add_patch(
|
|
341
|
ax.add_patch(
|
|
|
342
|
Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
|
|
342
|
Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
|
|
|
343
|
|
|
343
|
|
|
|
344
|
# plot Cuencas
|
|
344
|
# plot Cuencas
|
|
|
345
|
for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
|
|
345
|
for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
|
|
|
346
|
f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
|
|
346
|
f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
|
|
|
347
|
values = [line.strip().split(',') for line in f]
|
|
347
|
values = [line.strip().split(',') for line in f]
|
|
|
348
|
points = [(float(s[0]), float(s[1])) for s in values]
|
|
348
|
points = [(float(s[0]), float(s[1])) for s in values]
|
|
|
349
|
ax.add_patch(Polygon(points, ec='b', fc='none'))
|
|
349
|
ax.add_patch(Polygon(points, ec='b', fc='none'))
|
|
|
350
|
|
|
350
|
|
|
|
351
|
# plot grid
|
|
351
|
# plot grid
|
|
|
352
|
for r in (15, 30, 45, 60):
|
|
352
|
for r in (15, 30, 45, 60):
|
|
|
353
|
ax.add_artist(plt.Circle((self.lon, self.lat),
|
|
353
|
ax.add_artist(plt.Circle((self.lon, self.lat),
|
|
|
354
|
km2deg(r), color='0.6', fill=False, lw=0.2))
|
|
354
|
km2deg(r), color='0.6', fill=False, lw=0.2))
|
|
|
355
|
ax.text(
|
|
355
|
ax.text(
|
|
|
356
|
self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180),
|
|
356
|
self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180),
|
|
|
357
|
self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180),
|
|
357
|
self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180),
|
|
|
358
|
'{}km'.format(r),
|
|
358
|
'{}km'.format(r),
|
|
|
359
|
ha='center', va='bottom', size='8', color='0.6', weight='heavy')
|
|
359
|
ha='center', va='bottom', size='8', color='0.6', weight='heavy')
|
|
|
360
|
|
|
360
|
|
|
|
361
|
if self.mode == 'E':
|
|
361
|
if self.mode == 'E':
|
|
|
362
|
title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
|
|
362
|
title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
|
|
|
363
|
label = 'E{:02d}'.format(int(self.data.meta['elevation']))
|
|
363
|
label = 'E{:02d}'.format(int(self.data.meta['elevation']))
|
|
|
364
|
else:
|
|
364
|
else:
|
|
|
365
|
title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
|
|
365
|
title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
|
|
|
366
|
label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
|
|
366
|
label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
|
|
|
367
|
|
|
367
|
|
|
|
368
|
self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
|
|
368
|
self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
|
|
|
369
|
self.titles = ['{} {}'.format(
|
|
369
|
self.titles = ['{} {}'.format(
|
|
|
370
|
self.data.parameters[x], title) for x in self.channels]
|
|
370
|
self.data.parameters[x], title) for x in self.channels]
|
|
|
371
|
|
|
371
|
|
|
|
372
|
class WeatherPlot(Plot):
|
|
372
|
class WeatherPlot(Plot):
|
|
|
373
|
CODE = 'weather'
|
|
373
|
CODE = 'weather'
|
|
|
374
|
plot_name = 'weather'
|
|
374
|
plot_name = 'weather'
|
|
|
375
|
plot_type = 'ppistyle'
|
|
375
|
plot_type = 'ppistyle'
|
|
|
376
|
buffering = False
|
|
376
|
buffering = False
|
|
|
377
|
|
|
377
|
|
|
|
378
|
def setup(self):
|
|
378
|
def setup(self):
|
|
|
379
|
self.ncols = 1
|
|
379
|
self.ncols = 1
|
|
|
380
|
self.nrows = 1
|
|
380
|
self.nrows = 1
|
|
|
381
|
self.width =8
|
|
381
|
self.width =8
|
|
|
382
|
self.height =8
|
|
382
|
self.height =8
|
|
|
383
|
self.nplots= 1
|
|
383
|
self.nplots= 1
|
|
|
384
|
self.ylabel= 'Range [Km]'
|
|
384
|
self.ylabel= 'Range [Km]'
|
|
|
385
|
self.titles= ['Weather']
|
|
385
|
self.titles= ['Weather']
|
|
|
386
|
self.colorbar=False
|
|
386
|
self.colorbar=False
|
|
|
387
|
self.ini =0
|
|
387
|
self.ini =0
|
|
|
388
|
self.len_azi =0
|
|
388
|
self.len_azi =0
|
|
|
389
|
self.buffer_ini = None
|
|
389
|
self.buffer_ini = None
|
|
|
390
|
self.buffer_azi = None
|
|
390
|
self.buffer_azi = None
|
|
|
391
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
391
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
|
392
|
self.flag =0
|
|
392
|
self.flag =0
|
|
|
393
|
self.indicador= 0
|
|
393
|
self.indicador= 0
|
|
|
394
|
self.last_data_azi = None
|
|
394
|
self.last_data_azi = None
|
|
|
395
|
self.val_mean = None
|
|
395
|
self.val_mean = None
|
|
|
396
|
|
|
396
|
|
|
|
397
|
def update(self, dataOut):
|
|
397
|
def update(self, dataOut):
|
|
|
398
|
|
|
398
|
|
|
|
399
|
data = {}
|
|
399
|
data = {}
|
|
|
400
|
meta = {}
|
|
400
|
meta = {}
|
|
|
401
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
401
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
|
402
|
factor = 1
|
|
402
|
factor = 1
|
|
|
403
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
403
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
|
404
|
factor = dataOut.normFactor
|
|
404
|
factor = dataOut.normFactor
|
|
|
405
|
#print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape)
|
|
405
|
#print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape)
|
|
|
406
|
data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
406
|
data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
|
407
|
data['azi'] = dataOut.data_azi
|
|
407
|
data['azi'] = dataOut.data_azi
|
|
|
408
|
data['ele'] = dataOut.data_ele
|
|
408
|
data['ele'] = dataOut.data_ele
|
|
|
409
|
return data, meta
|
|
409
|
return data, meta
|
|
|
410
|
|
|
410
|
|
|
|
411
|
def get2List(self,angulos):
|
|
411
|
def get2List(self,angulos):
|
|
|
412
|
list1=[]
|
|
412
|
list1=[]
|
|
|
413
|
list2=[]
|
|
413
|
list2=[]
|
|
|
414
|
for i in reversed(range(len(angulos))):
|
|
414
|
for i in reversed(range(len(angulos))):
|
|
|
415
|
diff_ = angulos[i]-angulos[i-1]
|
|
415
|
diff_ = angulos[i]-angulos[i-1]
|
|
|
416
|
if diff_ >1.5:
|
|
416
|
if diff_ >1.5:
|
|
|
417
|
list1.append(i-1)
|
|
417
|
list1.append(i-1)
|
|
|
418
|
list2.append(diff_)
|
|
418
|
list2.append(diff_)
|
|
|
419
|
return list(reversed(list1)),list(reversed(list2))
|
|
419
|
return list(reversed(list1)),list(reversed(list2))
|
|
|
420
|
|
|
420
|
|
|
|
421
|
def fixData360(self,list_,ang_):
|
|
421
|
def fixData360(self,list_,ang_):
|
|
|
422
|
if list_[0]==-1:
|
|
422
|
if list_[0]==-1:
|
|
|
423
|
vec = numpy.where(ang_<ang_[0])
|
|
423
|
vec = numpy.where(ang_<ang_[0])
|
|
|
424
|
ang_[vec] = ang_[vec]+360
|
|
424
|
ang_[vec] = ang_[vec]+360
|
|
|
425
|
return ang_
|
|
425
|
return ang_
|
|
|
426
|
return ang_
|
|
426
|
return ang_
|
|
|
427
|
|
|
427
|
|
|
|
428
|
def fixData360HL(self,angulos):
|
|
428
|
def fixData360HL(self,angulos):
|
|
|
429
|
vec = numpy.where(angulos>=360)
|
|
429
|
vec = numpy.where(angulos>=360)
|
|
|
430
|
angulos[vec]=angulos[vec]-360
|
|
430
|
angulos[vec]=angulos[vec]-360
|
|
|
431
|
return angulos
|
|
431
|
return angulos
|
|
|
432
|
|
|
432
|
|
|
|
433
|
def search_pos(self,pos,list_):
|
|
433
|
def search_pos(self,pos,list_):
|
|
|
434
|
for i in range(len(list_)):
|
|
434
|
for i in range(len(list_)):
|
|
|
435
|
if pos == list_[i]:
|
|
435
|
if pos == list_[i]:
|
|
|
436
|
return True,i
|
|
436
|
return True,i
|
|
|
437
|
i=None
|
|
437
|
i=None
|
|
|
438
|
return False,i
|
|
438
|
return False,i
|
|
|
439
|
|
|
439
|
|
|
|
440
|
def fixDataComp(self,ang_,list1_,list2_):
|
|
440
|
def fixDataComp(self,ang_,list1_,list2_):
|
|
|
441
|
size = len(ang_)
|
|
441
|
size = len(ang_)
|
|
|
442
|
size2 = 0
|
|
442
|
size2 = 0
|
|
|
443
|
for i in range(len(list2_)):
|
|
443
|
for i in range(len(list2_)):
|
|
|
444
|
size2=size2+round(list2_[i])-1
|
|
444
|
size2=size2+round(list2_[i])-1
|
|
|
445
|
new_size= size+size2
|
|
445
|
new_size= size+size2
|
|
|
446
|
ang_new = numpy.zeros(new_size)
|
|
446
|
ang_new = numpy.zeros(new_size)
|
|
|
447
|
ang_new2 = numpy.zeros(new_size)
|
|
447
|
ang_new2 = numpy.zeros(new_size)
|
|
|
448
|
|
|
448
|
|
|
|
449
|
tmp = 0
|
|
449
|
tmp = 0
|
|
|
450
|
c = 0
|
|
450
|
c = 0
|
|
|
451
|
for i in range(len(ang_)):
|
|
451
|
for i in range(len(ang_)):
|
|
|
452
|
ang_new[tmp +c] = ang_[i]
|
|
452
|
ang_new[tmp +c] = ang_[i]
|
|
|
453
|
ang_new2[tmp+c] = ang_[i]
|
|
453
|
ang_new2[tmp+c] = ang_[i]
|
|
|
454
|
condition , value = self.search_pos(i,list1_)
|
|
454
|
condition , value = self.search_pos(i,list1_)
|
|
|
455
|
if condition:
|
|
455
|
if condition:
|
|
|
456
|
pos = tmp + c + 1
|
|
456
|
pos = tmp + c + 1
|
|
|
457
|
for k in range(round(list2_[value])-1):
|
|
457
|
for k in range(round(list2_[value])-1):
|
|
|
458
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
458
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
|
459
|
ang_new2[pos+k] = numpy.nan
|
|
459
|
ang_new2[pos+k] = numpy.nan
|
|
|
460
|
tmp = pos +k
|
|
460
|
tmp = pos +k
|
|
|
461
|
c = 0
|
|
461
|
c = 0
|
|
|
462
|
c=c+1
|
|
462
|
c=c+1
|
|
|
463
|
return ang_new,ang_new2
|
|
463
|
return ang_new,ang_new2
|
|
|
464
|
|
|
464
|
|
|
|
465
|
def globalCheckPED(self,angulos):
|
|
465
|
def globalCheckPED(self,angulos):
|
|
|
466
|
l1,l2 = self.get2List(angulos)
|
|
466
|
l1,l2 = self.get2List(angulos)
|
|
|
467
|
if len(l1)>0:
|
|
467
|
if len(l1)>0:
|
|
|
468
|
angulos2 = self.fixData360(list_=l1,ang_=angulos)
|
|
468
|
angulos2 = self.fixData360(list_=l1,ang_=angulos)
|
|
|
469
|
l1,l2 = self.get2List(angulos2)
|
|
469
|
l1,l2 = self.get2List(angulos2)
|
|
|
470
|
|
|
470
|
|
|
|
471
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2)
|
|
471
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2)
|
|
|
472
|
ang1_ = self.fixData360HL(ang1_)
|
|
472
|
ang1_ = self.fixData360HL(ang1_)
|
|
|
473
|
ang2_ = self.fixData360HL(ang2_)
|
|
473
|
ang2_ = self.fixData360HL(ang2_)
|
|
|
474
|
else:
|
|
474
|
else:
|
|
|
475
|
ang1_= angulos
|
|
475
|
ang1_= angulos
|
|
|
476
|
ang2_= angulos
|
|
476
|
ang2_= angulos
|
|
|
477
|
return ang1_,ang2_
|
|
477
|
return ang1_,ang2_
|
|
|
478
|
|
|
478
|
|
|
|
479
|
def analizeDATA(self,data_azi):
|
|
479
|
def analizeDATA(self,data_azi):
|
|
|
480
|
list1 = []
|
|
480
|
list1 = []
|
|
|
481
|
list2 = []
|
|
481
|
list2 = []
|
|
|
482
|
dat = data_azi
|
|
482
|
dat = data_azi
|
|
|
483
|
for i in reversed(range(1,len(dat))):
|
|
483
|
for i in reversed(range(1,len(dat))):
|
|
|
484
|
if dat[i]>dat[i-1]:
|
|
484
|
if dat[i]>dat[i-1]:
|
|
|
485
|
diff = int(dat[i])-int(dat[i-1])
|
|
485
|
diff = int(dat[i])-int(dat[i-1])
|
|
|
486
|
else:
|
|
486
|
else:
|
|
|
487
|
diff = 360+int(dat[i])-int(dat[i-1])
|
|
487
|
diff = 360+int(dat[i])-int(dat[i-1])
|
|
|
488
|
if diff > 1:
|
|
488
|
if diff > 1:
|
|
|
489
|
list1.append(i-1)
|
|
489
|
list1.append(i-1)
|
|
|
490
|
list2.append(diff-1)
|
|
490
|
list2.append(diff-1)
|
|
|
491
|
return list1,list2
|
|
491
|
return list1,list2
|
|
|
492
|
|
|
492
|
|
|
|
493
|
def fixDATANEW(self,data_azi,data_weather):
|
|
493
|
def fixDATANEW(self,data_azi,data_weather):
|
|
|
494
|
list1,list2 = self.analizeDATA(data_azi)
|
|
494
|
list1,list2 = self.analizeDATA(data_azi)
|
|
|
495
|
if len(list1)== 0:
|
|
495
|
if len(list1)== 0:
|
|
|
496
|
return data_azi,data_weather
|
|
496
|
return data_azi,data_weather
|
|
|
497
|
else:
|
|
497
|
else:
|
|
|
498
|
resize = 0
|
|
498
|
resize = 0
|
|
|
499
|
for i in range(len(list2)):
|
|
499
|
for i in range(len(list2)):
|
|
|
500
|
resize= resize + list2[i]
|
|
500
|
resize= resize + list2[i]
|
|
|
501
|
new_data_azi = numpy.resize(data_azi,resize)
|
|
501
|
new_data_azi = numpy.resize(data_azi,resize)
|
|
|
502
|
new_data_weather= numpy.resize(date_weather,resize)
|
|
502
|
new_data_weather= numpy.resize(date_weather,resize)
|
|
|
503
|
|
|
503
|
|
|
|
504
|
for i in range(len(list2)):
|
|
504
|
for i in range(len(list2)):
|
|
|
505
|
j=0
|
|
505
|
j=0
|
|
|
506
|
position=list1[i]+1
|
|
506
|
position=list1[i]+1
|
|
|
507
|
for j in range(list2[i]):
|
|
507
|
for j in range(list2[i]):
|
|
|
508
|
new_data_azi[position+j]=new_data_azi[position+j-1]+1
|
|
508
|
new_data_azi[position+j]=new_data_azi[position+j-1]+1
|
|
|
509
|
return new_data_azi
|
|
509
|
return new_data_azi
|
|
|
510
|
|
|
510
|
|
|
|
511
|
def fixDATA(self,data_azi):
|
|
511
|
def fixDATA(self,data_azi):
|
|
|
512
|
data=data_azi
|
|
512
|
data=data_azi
|
|
|
513
|
for i in range(len(data)):
|
|
513
|
for i in range(len(data)):
|
|
|
514
|
if numpy.isnan(data[i]):
|
|
514
|
if numpy.isnan(data[i]):
|
|
|
515
|
data[i]=data[i-1]+1
|
|
515
|
data[i]=data[i-1]+1
|
|
|
516
|
return data
|
|
516
|
return data
|
|
|
517
|
|
|
517
|
|
|
|
518
|
def replaceNAN(self,data_weather,data_azi,val):
|
|
518
|
def replaceNAN(self,data_weather,data_azi,val):
|
|
|
519
|
data= data_azi
|
|
519
|
data= data_azi
|
|
|
520
|
data_T= data_weather
|
|
520
|
data_T= data_weather
|
|
|
521
|
if data.shape[0]> data_T.shape[0]:
|
|
521
|
if data.shape[0]> data_T.shape[0]:
|
|
|
522
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
522
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
|
523
|
c = 0
|
|
523
|
c = 0
|
|
|
524
|
for i in range(len(data)):
|
|
524
|
for i in range(len(data)):
|
|
|
525
|
if numpy.isnan(data[i]):
|
|
525
|
if numpy.isnan(data[i]):
|
|
|
526
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
526
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
527
|
else:
|
|
527
|
else:
|
|
|
528
|
data_N[i,:]=data_T[c,:]
|
|
528
|
data_N[i,:]=data_T[c,:]
|
|
|
529
|
c=c+1
|
|
529
|
c=c+1
|
|
|
530
|
return data_N
|
|
530
|
return data_N
|
|
|
531
|
else:
|
|
531
|
else:
|
|
|
532
|
for i in range(len(data)):
|
|
532
|
for i in range(len(data)):
|
|
|
533
|
if numpy.isnan(data[i]):
|
|
533
|
if numpy.isnan(data[i]):
|
|
|
534
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
534
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
535
|
return data_T
|
|
535
|
return data_T
|
|
|
536
|
|
|
536
|
|
|
|
537
|
def const_ploteo(self,data_weather,data_azi,step,res):
|
|
537
|
def const_ploteo(self,data_weather,data_azi,step,res):
|
|
|
538
|
if self.ini==0:
|
|
538
|
if self.ini==0:
|
|
|
539
|
#-------
|
|
539
|
#-------
|
|
|
540
|
n = (360/res)-len(data_azi)
|
|
540
|
n = (360/res)-len(data_azi)
|
|
|
541
|
#--------------------- new -------------------------
|
|
541
|
#--------------------- new -------------------------
|
|
|
542
|
data_azi_new ,data_azi_old= self.globalCheckPED(data_azi)
|
|
542
|
data_azi_new ,data_azi_old= self.globalCheckPED(data_azi)
|
|
|
543
|
#------------------------
|
|
543
|
#------------------------
|
|
|
544
|
start = data_azi_new[-1] + res
|
|
544
|
start = data_azi_new[-1] + res
|
|
|
545
|
end = data_azi_new[0] - res
|
|
545
|
end = data_azi_new[0] - res
|
|
|
546
|
#------ new
|
|
546
|
#------ new
|
|
|
547
|
self.last_data_azi = end
|
|
547
|
self.last_data_azi = end
|
|
|
548
|
if start>end:
|
|
548
|
if start>end:
|
|
|
549
|
end = end + 360
|
|
549
|
end = end + 360
|
|
|
550
|
azi_vacia = numpy.linspace(start,end,int(n))
|
|
550
|
azi_vacia = numpy.linspace(start,end,int(n))
|
|
|
551
|
azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia)
|
|
551
|
azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia)
|
|
|
552
|
data_azi = numpy.hstack((data_azi_new,azi_vacia))
|
|
552
|
data_azi = numpy.hstack((data_azi_new,azi_vacia))
|
|
|
553
|
# RADAR
|
|
553
|
# RADAR
|
|
|
554
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
554
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
|
555
|
self.val_mean = val_mean
|
|
555
|
self.val_mean = val_mean
|
|
|
556
|
data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean
|
|
556
|
data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean
|
|
|
557
|
data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
|
|
557
|
data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
|
|
|
558
|
data_weather = numpy.vstack((data_weather,data_weather_cmp))
|
|
558
|
data_weather = numpy.vstack((data_weather,data_weather_cmp))
|
|
|
559
|
else:
|
|
559
|
else:
|
|
|
560
|
# azimuth
|
|
560
|
# azimuth
|
|
|
561
|
flag=0
|
|
561
|
flag=0
|
|
|
562
|
start_azi = self.res_azi[0]
|
|
562
|
start_azi = self.res_azi[0]
|
|
|
563
|
#-----------new------------
|
|
563
|
#-----------new------------
|
|
|
564
|
data_azi ,data_azi_old= self.globalCheckPED(data_azi)
|
|
564
|
data_azi ,data_azi_old= self.globalCheckPED(data_azi)
|
|
|
565
|
data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
|
|
565
|
data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
|
|
|
566
|
#--------------------------
|
|
566
|
#--------------------------
|
|
|
567
|
start = data_azi[0]
|
|
567
|
start = data_azi[0]
|
|
|
568
|
end = data_azi[-1]
|
|
568
|
end = data_azi[-1]
|
|
|
569
|
self.last_data_azi= end
|
|
569
|
self.last_data_azi= end
|
|
|
570
|
if start< start_azi:
|
|
570
|
if start< start_azi:
|
|
|
571
|
start = start +360
|
|
571
|
start = start +360
|
|
|
572
|
if end <start_azi:
|
|
572
|
if end <start_azi:
|
|
|
573
|
end = end +360
|
|
573
|
end = end +360
|
|
|
574
|
|
|
574
|
|
|
|
575
|
pos_ini = int((start-start_azi)/res)
|
|
575
|
pos_ini = int((start-start_azi)/res)
|
|
|
576
|
len_azi = len(data_azi)
|
|
576
|
len_azi = len(data_azi)
|
|
|
577
|
if (360-pos_ini)<len_azi:
|
|
577
|
if (360-pos_ini)<len_azi:
|
|
|
578
|
if pos_ini+1==360:
|
|
578
|
if pos_ini+1==360:
|
|
|
579
|
pos_ini=0
|
|
579
|
pos_ini=0
|
|
|
580
|
else:
|
|
580
|
else:
|
|
|
581
|
flag=1
|
|
581
|
flag=1
|
|
|
582
|
dif= 360-pos_ini
|
|
582
|
dif= 360-pos_ini
|
|
|
583
|
comp= len_azi-dif
|
|
583
|
comp= len_azi-dif
|
|
|
584
|
#-----------------
|
|
584
|
#-----------------
|
|
|
585
|
if flag==0:
|
|
585
|
if flag==0:
|
|
|
586
|
# AZIMUTH
|
|
586
|
# AZIMUTH
|
|
|
587
|
self.res_azi[pos_ini:pos_ini+len_azi] = data_azi
|
|
587
|
self.res_azi[pos_ini:pos_ini+len_azi] = data_azi
|
|
|
588
|
# RADAR
|
|
588
|
# RADAR
|
|
|
589
|
self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather
|
|
589
|
self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather
|
|
|
590
|
else:
|
|
590
|
else:
|
|
|
591
|
# AZIMUTH
|
|
591
|
# AZIMUTH
|
|
|
592
|
self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif]
|
|
592
|
self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif]
|
|
|
593
|
self.res_azi[0:comp] = data_azi[dif:]
|
|
593
|
self.res_azi[0:comp] = data_azi[dif:]
|
|
|
594
|
# RADAR
|
|
594
|
# RADAR
|
|
|
595
|
self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:]
|
|
595
|
self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:]
|
|
|
596
|
self.res_weather[0:comp,:] = data_weather[dif:,:]
|
|
596
|
self.res_weather[0:comp,:] = data_weather[dif:,:]
|
|
|
597
|
flag=0
|
|
597
|
flag=0
|
|
|
598
|
data_azi = self.res_azi
|
|
598
|
data_azi = self.res_azi
|
|
|
599
|
data_weather = self.res_weather
|
|
599
|
data_weather = self.res_weather
|
|
|
600
|
|
|
600
|
|
|
|
601
|
return data_weather,data_azi
|
|
601
|
return data_weather,data_azi
|
|
|
602
|
|
|
602
|
|
|
|
603
|
def plot(self):
|
|
603
|
def plot(self):
|
|
|
604
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
604
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
|
605
|
data = self.data[-1]
|
|
605
|
data = self.data[-1]
|
|
|
606
|
r = self.data.yrange
|
|
606
|
r = self.data.yrange
|
|
|
607
|
delta_height = r[1]-r[0]
|
|
607
|
delta_height = r[1]-r[0]
|
|
|
608
|
r_mask = numpy.where(r>=0)[0]
|
|
608
|
r_mask = numpy.where(r>=0)[0]
|
|
|
609
|
r = numpy.arange(len(r_mask))*delta_height
|
|
609
|
r = numpy.arange(len(r_mask))*delta_height
|
|
|
610
|
self.y = 2*r
|
|
610
|
self.y = 2*r
|
|
|
611
|
# RADAR
|
|
611
|
# RADAR
|
|
|
612
|
#data_weather = data['weather']
|
|
612
|
#data_weather = data['weather']
|
|
|
613
|
# PEDESTAL
|
|
613
|
# PEDESTAL
|
|
|
614
|
#data_azi = data['azi']
|
|
614
|
#data_azi = data['azi']
|
|
|
615
|
res = 1
|
|
615
|
res = 1
|
|
|
616
|
# STEP
|
|
616
|
# STEP
|
|
|
617
|
step = (360/(res*data['weather'].shape[0]))
|
|
617
|
step = (360/(res*data['weather'].shape[0]))
|
|
|
618
|
|
|
618
|
|
|
|
619
|
self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res)
|
|
619
|
self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res)
|
|
|
620
|
self.res_ele = numpy.mean(data['ele'])
|
|
620
|
self.res_ele = numpy.mean(data['ele'])
|
|
|
621
|
################# PLOTEO ###################
|
|
621
|
################# PLOTEO ###################
|
|
|
622
|
for i,ax in enumerate(self.axes):
|
|
622
|
for i,ax in enumerate(self.axes):
|
|
|
|
|
|
623
|
self.zmin = self.zmin if self.zmin else 20
|
|
|
|
|
|
624
|
self.zmax = self.zmax if self.zmax else 80
|
|
|
623
|
if ax.firsttime:
|
|
625
|
if ax.firsttime:
|
|
|
624
|
plt.clf()
|
|
626
|
plt.clf()
|
|
|
625
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=20, vmax=80)
|
|
627
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax)
|
|
|
626
|
else:
|
|
628
|
else:
|
|
|
627
|
plt.clf()
|
|
629
|
plt.clf()
|
|
|
628
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=20, vmax=80)
|
|
630
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax)
|
|
|
629
|
caax = cgax.parasites[0]
|
|
631
|
caax = cgax.parasites[0]
|
|
|
630
|
paax = cgax.parasites[1]
|
|
632
|
paax = cgax.parasites[1]
|
|
|
631
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
633
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
|
632
|
caax.set_xlabel('x_range [km]')
|
|
634
|
caax.set_xlabel('x_range [km]')
|
|
|
633
|
caax.set_ylabel('y_range [km]')
|
|
635
|
caax.set_ylabel('y_range [km]')
|
|
|
634
|
plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " Elev: "+str(round(self.res_ele,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
636
|
plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " EL: "+str(round(self.res_ele, 1)), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
635
|
|
|
637
|
|
|
|
636
|
self.ini= self.ini+1
|
|
638
|
self.ini= self.ini+1
|
|
|
637
|
|
|
639
|
|
|
|
638
|
|
|
640
|
|
|
|
639
|
class WeatherRHIPlot(Plot):
|
|
641
|
class WeatherRHIPlot(Plot):
|
|
|
640
|
CODE = 'weather'
|
|
642
|
CODE = 'weather'
|
|
|
641
|
plot_name = 'weather'
|
|
643
|
plot_name = 'weather'
|
|
|
642
|
plot_type = 'rhistyle'
|
|
644
|
plot_type = 'rhistyle'
|
|
|
643
|
buffering = False
|
|
645
|
buffering = False
|
|
|
644
|
data_ele_tmp = None
|
|
646
|
data_ele_tmp = None
|
|
|
645
|
|
|
647
|
|
|
|
646
|
def setup(self):
|
|
648
|
def setup(self):
|
|
|
647
|
print("********************")
|
|
649
|
print("********************")
|
|
|
648
|
print("********************")
|
|
650
|
print("********************")
|
|
|
649
|
print("********************")
|
|
651
|
print("********************")
|
|
|
650
|
print("SETUP WEATHER PLOT")
|
|
652
|
print("SETUP WEATHER PLOT")
|
|
|
651
|
self.ncols = 1
|
|
653
|
self.ncols = 1
|
|
|
652
|
self.nrows = 1
|
|
654
|
self.nrows = 1
|
|
|
653
|
self.nplots= 1
|
|
655
|
self.nplots= 1
|
|
|
654
|
self.ylabel= 'Range [Km]'
|
|
656
|
self.ylabel= 'Range [Km]'
|
|
|
655
|
self.titles= ['Weather']
|
|
657
|
self.titles= ['Weather']
|
|
|
656
|
if self.channels is not None:
|
|
658
|
if self.channels is not None:
|
|
|
657
|
self.nplots = len(self.channels)
|
|
659
|
self.nplots = len(self.channels)
|
|
|
658
|
self.nrows = len(self.channels)
|
|
660
|
self.nrows = len(self.channels)
|
|
|
659
|
else:
|
|
661
|
else:
|
|
|
660
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
662
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
|
661
|
self.nrows = self.nplots
|
|
663
|
self.nrows = self.nplots
|
|
|
662
|
self.channels = list(range(self.nplots))
|
|
664
|
self.channels = list(range(self.nplots))
|
|
|
663
|
print("channels",self.channels)
|
|
665
|
print("channels",self.channels)
|
|
|
664
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
666
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
|
665
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
667
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
|
666
|
print("self.titles",self.titles)
|
|
668
|
print("self.titles",self.titles)
|
|
|
667
|
self.colorbar=False
|
|
669
|
self.colorbar=False
|
|
|
668
|
self.width =8
|
|
670
|
self.width =12
|
|
|
669
|
self.height =8
|
|
671
|
self.height =8
|
|
|
670
|
self.ini =0
|
|
672
|
self.ini =0
|
|
|
671
|
self.len_azi =0
|
|
673
|
self.len_azi =0
|
|
|
672
|
self.buffer_ini = None
|
|
674
|
self.buffer_ini = None
|
|
|
673
|
self.buffer_ele = None
|
|
675
|
self.buffer_ele = None
|
|
|
674
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
676
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
|
675
|
self.flag =0
|
|
677
|
self.flag =0
|
|
|
676
|
self.indicador= 0
|
|
678
|
self.indicador= 0
|
|
|
677
|
self.last_data_ele = None
|
|
679
|
self.last_data_ele = None
|
|
|
678
|
self.val_mean = None
|
|
680
|
self.val_mean = None
|
|
|
679
|
|
|
681
|
|
|
|
680
|
def update(self, dataOut):
|
|
682
|
def update(self, dataOut):
|
|
|
681
|
|
|
683
|
|
|
|
682
|
data = {}
|
|
684
|
data = {}
|
|
|
683
|
meta = {}
|
|
685
|
meta = {}
|
|
|
684
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
686
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
|
685
|
factor = 1
|
|
687
|
factor = 1
|
|
|
686
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
688
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
|
687
|
factor = dataOut.normFactor
|
|
689
|
factor = dataOut.normFactor
|
|
|
688
|
print("dataOut",dataOut.data_360.shape)
|
|
690
|
print("dataOut",dataOut.data_360.shape)
|
|
|
689
|
#
|
|
691
|
#
|
|
|
690
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
692
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
|
691
|
#
|
|
693
|
#
|
|
|
692
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
694
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
|
693
|
data['azi'] = dataOut.data_azi
|
|
695
|
data['azi'] = dataOut.data_azi
|
|
|
694
|
data['ele'] = dataOut.data_ele
|
|
696
|
data['ele'] = dataOut.data_ele
|
|
|
695
|
#print("UPDATE")
|
|
697
|
#print("UPDATE")
|
|
|
696
|
#print("data[weather]",data['weather'].shape)
|
|
698
|
#print("data[weather]",data['weather'].shape)
|
|
|
697
|
#print("data[azi]",data['azi'])
|
|
699
|
#print("data[azi]",data['azi'])
|
|
|
698
|
return data, meta
|
|
700
|
return data, meta
|
|
|
699
|
|
|
701
|
|
|
|
700
|
def get2List(self,angulos):
|
|
702
|
def get2List(self,angulos):
|
|
|
701
|
list1=[]
|
|
703
|
list1=[]
|
|
|
702
|
list2=[]
|
|
704
|
list2=[]
|
|
|
703
|
for i in reversed(range(len(angulos))):
|
|
705
|
for i in reversed(range(len(angulos))):
|
|
|
704
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
706
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
|
705
|
diff_ = angulos[i]-angulos[i-1]
|
|
707
|
diff_ = angulos[i]-angulos[i-1]
|
|
|
706
|
if abs(diff_) >1.5:
|
|
708
|
if abs(diff_) >1.5:
|
|
|
707
|
list1.append(i-1)
|
|
709
|
list1.append(i-1)
|
|
|
708
|
list2.append(diff_)
|
|
710
|
list2.append(diff_)
|
|
|
709
|
return list(reversed(list1)),list(reversed(list2))
|
|
711
|
return list(reversed(list1)),list(reversed(list2))
|
|
|
710
|
|
|
712
|
|
|
|
711
|
def fixData90(self,list_,ang_):
|
|
713
|
def fixData90(self,list_,ang_):
|
|
|
712
|
if list_[0]==-1:
|
|
714
|
if list_[0]==-1:
|
|
|
713
|
vec = numpy.where(ang_<ang_[0])
|
|
715
|
vec = numpy.where(ang_<ang_[0])
|
|
|
714
|
ang_[vec] = ang_[vec]+90
|
|
716
|
ang_[vec] = ang_[vec]+90
|
|
|
715
|
return ang_
|
|
717
|
return ang_
|
|
|
716
|
return ang_
|
|
718
|
return ang_
|
|
|
717
|
|
|
719
|
|
|
|
718
|
def fixData90HL(self,angulos):
|
|
720
|
def fixData90HL(self,angulos):
|
|
|
719
|
vec = numpy.where(angulos>=90)
|
|
721
|
vec = numpy.where(angulos>=90)
|
|
|
720
|
angulos[vec]=angulos[vec]-90
|
|
722
|
angulos[vec]=angulos[vec]-90
|
|
|
721
|
return angulos
|
|
723
|
return angulos
|
|
|
722
|
|
|
724
|
|
|
|
723
|
|
|
725
|
|
|
|
724
|
def search_pos(self,pos,list_):
|
|
726
|
def search_pos(self,pos,list_):
|
|
|
725
|
for i in range(len(list_)):
|
|
727
|
for i in range(len(list_)):
|
|
|
726
|
if pos == list_[i]:
|
|
728
|
if pos == list_[i]:
|
|
|
727
|
return True,i
|
|
729
|
return True,i
|
|
|
728
|
i=None
|
|
730
|
i=None
|
|
|
729
|
return False,i
|
|
731
|
return False,i
|
|
|
730
|
|
|
732
|
|
|
|
731
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
733
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
|
732
|
size = len(ang_)
|
|
734
|
size = len(ang_)
|
|
|
733
|
size2 = 0
|
|
735
|
size2 = 0
|
|
|
734
|
for i in range(len(list2_)):
|
|
736
|
for i in range(len(list2_)):
|
|
|
735
|
size2=size2+round(abs(list2_[i]))-1
|
|
737
|
size2=size2+round(abs(list2_[i]))-1
|
|
|
736
|
new_size= size+size2
|
|
738
|
new_size= size+size2
|
|
|
737
|
ang_new = numpy.zeros(new_size)
|
|
739
|
ang_new = numpy.zeros(new_size)
|
|
|
738
|
ang_new2 = numpy.zeros(new_size)
|
|
740
|
ang_new2 = numpy.zeros(new_size)
|
|
|
739
|
|
|
741
|
|
|
|
740
|
tmp = 0
|
|
742
|
tmp = 0
|
|
|
741
|
c = 0
|
|
743
|
c = 0
|
|
|
742
|
for i in range(len(ang_)):
|
|
744
|
for i in range(len(ang_)):
|
|
|
743
|
ang_new[tmp +c] = ang_[i]
|
|
745
|
ang_new[tmp +c] = ang_[i]
|
|
|
744
|
ang_new2[tmp+c] = ang_[i]
|
|
746
|
ang_new2[tmp+c] = ang_[i]
|
|
|
745
|
condition , value = self.search_pos(i,list1_)
|
|
747
|
condition , value = self.search_pos(i,list1_)
|
|
|
746
|
if condition:
|
|
748
|
if condition:
|
|
|
747
|
pos = tmp + c + 1
|
|
749
|
pos = tmp + c + 1
|
|
|
748
|
for k in range(round(abs(list2_[value]))-1):
|
|
750
|
for k in range(round(abs(list2_[value]))-1):
|
|
|
749
|
if tipo_case==0 or tipo_case==3:#subida
|
|
751
|
if tipo_case==0 or tipo_case==3:#subida
|
|
|
750
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
752
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
|
751
|
ang_new2[pos+k] = numpy.nan
|
|
753
|
ang_new2[pos+k] = numpy.nan
|
|
|
752
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
754
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
|
753
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
755
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
|
754
|
ang_new2[pos+k] = numpy.nan
|
|
756
|
ang_new2[pos+k] = numpy.nan
|
|
|
755
|
|
|
757
|
|
|
|
756
|
tmp = pos +k
|
|
758
|
tmp = pos +k
|
|
|
757
|
c = 0
|
|
759
|
c = 0
|
|
|
758
|
c=c+1
|
|
760
|
c=c+1
|
|
|
759
|
return ang_new,ang_new2
|
|
761
|
return ang_new,ang_new2
|
|
|
760
|
|
|
762
|
|
|
|
761
|
def globalCheckPED(self,angulos,tipo_case):
|
|
763
|
def globalCheckPED(self,angulos,tipo_case):
|
|
|
762
|
l1,l2 = self.get2List(angulos)
|
|
764
|
l1,l2 = self.get2List(angulos)
|
|
|
763
|
##print("l1",l1)
|
|
765
|
##print("l1",l1)
|
|
|
764
|
##print("l2",l2)
|
|
766
|
##print("l2",l2)
|
|
|
765
|
if len(l1)>0:
|
|
767
|
if len(l1)>0:
|
|
|
766
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
768
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
|
767
|
#l1,l2 = self.get2List(angulos2)
|
|
769
|
#l1,l2 = self.get2List(angulos2)
|
|
|
768
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
770
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
|
769
|
#ang1_ = self.fixData90HL(ang1_)
|
|
771
|
#ang1_ = self.fixData90HL(ang1_)
|
|
|
770
|
#ang2_ = self.fixData90HL(ang2_)
|
|
772
|
#ang2_ = self.fixData90HL(ang2_)
|
|
|
771
|
else:
|
|
773
|
else:
|
|
|
772
|
ang1_= angulos
|
|
774
|
ang1_= angulos
|
|
|
773
|
ang2_= angulos
|
|
775
|
ang2_= angulos
|
|
|
774
|
return ang1_,ang2_
|
|
776
|
return ang1_,ang2_
|
|
|
775
|
|
|
777
|
|
|
|
776
|
|
|
778
|
|
|
|
777
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
779
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
|
778
|
data= data_ele
|
|
780
|
data= data_ele
|
|
|
779
|
data_T= data_weather
|
|
781
|
data_T= data_weather
|
|
|
780
|
if data.shape[0]> data_T.shape[0]:
|
|
782
|
if data.shape[0]> data_T.shape[0]:
|
|
|
781
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
783
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
|
782
|
c = 0
|
|
784
|
c = 0
|
|
|
783
|
for i in range(len(data)):
|
|
785
|
for i in range(len(data)):
|
|
|
784
|
if numpy.isnan(data[i]):
|
|
786
|
if numpy.isnan(data[i]):
|
|
|
785
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
787
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
786
|
else:
|
|
788
|
else:
|
|
|
787
|
data_N[i,:]=data_T[c,:]
|
|
789
|
data_N[i,:]=data_T[c,:]
|
|
|
788
|
c=c+1
|
|
790
|
c=c+1
|
|
|
789
|
return data_N
|
|
791
|
return data_N
|
|
|
790
|
else:
|
|
792
|
else:
|
|
|
791
|
for i in range(len(data)):
|
|
793
|
for i in range(len(data)):
|
|
|
792
|
if numpy.isnan(data[i]):
|
|
794
|
if numpy.isnan(data[i]):
|
|
|
793
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
795
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
794
|
return data_T
|
|
796
|
return data_T
|
|
|
795
|
|
|
797
|
|
|
|
796
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
798
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
|
797
|
start = data_ele[0]
|
|
799
|
start = data_ele[0]
|
|
|
798
|
end = data_ele[-1]
|
|
800
|
end = data_ele[-1]
|
|
|
799
|
number = (end-start)
|
|
801
|
number = (end-start)
|
|
|
800
|
len_ang=len(data_ele)
|
|
802
|
len_ang=len(data_ele)
|
|
|
801
|
print("start",start)
|
|
803
|
print("start",start)
|
|
|
802
|
print("end",end)
|
|
804
|
print("end",end)
|
|
|
803
|
print("number",number)
|
|
805
|
print("number",number)
|
|
|
804
|
|
|
806
|
|
|
|
805
|
print("len_ang",len_ang)
|
|
807
|
print("len_ang",len_ang)
|
|
|
806
|
|
|
808
|
|
|
|
807
|
#exit(1)
|
|
809
|
#exit(1)
|
|
|
808
|
|
|
810
|
|
|
|
809
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
811
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
|
810
|
return 0
|
|
812
|
return 0
|
|
|
811
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
813
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
812
|
# return 1
|
|
814
|
# return 1
|
|
|
813
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
815
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
814
|
return 1
|
|
816
|
return 1
|
|
|
815
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
817
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
|
816
|
return 2
|
|
818
|
return 2
|
|
|
817
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
819
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
|
818
|
return 3
|
|
820
|
return 3
|
|
|
819
|
|
|
821
|
|
|
|
820
|
|
|
822
|
|
|
|
821
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min):
|
|
823
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min):
|
|
|
822
|
ang_max= ang_max
|
|
824
|
ang_max= ang_max
|
|
|
823
|
ang_min= ang_min
|
|
825
|
ang_min= ang_min
|
|
|
824
|
data_weather=data_weather
|
|
826
|
data_weather=data_weather
|
|
|
825
|
val_ch=val_ch
|
|
827
|
val_ch=val_ch
|
|
|
826
|
##print("*********************DATA WEATHER**************************************")
|
|
828
|
##print("*********************DATA WEATHER**************************************")
|
|
|
827
|
##print(data_weather)
|
|
829
|
##print(data_weather)
|
|
|
828
|
if self.ini==0:
|
|
830
|
if self.ini==0:
|
|
|
829
|
'''
|
|
831
|
'''
|
|
|
830
|
print("**********************************************")
|
|
832
|
print("**********************************************")
|
|
|
831
|
print("**********************************************")
|
|
833
|
print("**********************************************")
|
|
|
832
|
print("***************ini**************")
|
|
834
|
print("***************ini**************")
|
|
|
833
|
print("**********************************************")
|
|
835
|
print("**********************************************")
|
|
|
834
|
print("**********************************************")
|
|
836
|
print("**********************************************")
|
|
|
835
|
'''
|
|
837
|
'''
|
|
|
836
|
#print("data_ele",data_ele)
|
|
838
|
#print("data_ele",data_ele)
|
|
|
837
|
#----------------------------------------------------------
|
|
839
|
#----------------------------------------------------------
|
|
|
838
|
tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
840
|
tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
|
839
|
print("check_case",tipo_case)
|
|
841
|
print("check_case",tipo_case)
|
|
|
840
|
#exit(1)
|
|
842
|
#exit(1)
|
|
|
841
|
#--------------------- new -------------------------
|
|
843
|
#--------------------- new -------------------------
|
|
|
842
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
844
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
|
843
|
|
|
845
|
|
|
|
844
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
846
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
845
|
start= ang_min
|
|
847
|
start= ang_min
|
|
|
846
|
end = ang_max
|
|
848
|
end = ang_max
|
|
|
847
|
n= (ang_max-ang_min)/res
|
|
849
|
n= (ang_max-ang_min)/res
|
|
|
848
|
#------ new
|
|
850
|
#------ new
|
|
|
849
|
self.start_data_ele = data_ele_new[0]
|
|
851
|
self.start_data_ele = data_ele_new[0]
|
|
|
850
|
self.end_data_ele = data_ele_new[-1]
|
|
852
|
self.end_data_ele = data_ele_new[-1]
|
|
|
851
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
853
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
|
852
|
n1= round(self.start_data_ele)- start
|
|
854
|
n1= round(self.start_data_ele)- start
|
|
|
853
|
n2= end - round(self.end_data_ele)
|
|
855
|
n2= end - round(self.end_data_ele)
|
|
|
854
|
print(self.start_data_ele)
|
|
856
|
print(self.start_data_ele)
|
|
|
855
|
print(self.end_data_ele)
|
|
857
|
print(self.end_data_ele)
|
|
|
856
|
if n1>0:
|
|
858
|
if n1>0:
|
|
|
857
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
859
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
858
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
860
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
859
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
861
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
860
|
print("ele1_nan",ele1_nan.shape)
|
|
862
|
print("ele1_nan",ele1_nan.shape)
|
|
|
861
|
print("data_ele_old",data_ele_old.shape)
|
|
863
|
print("data_ele_old",data_ele_old.shape)
|
|
|
862
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
864
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
863
|
if n2>0:
|
|
865
|
if n2>0:
|
|
|
864
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
866
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
865
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
867
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
866
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
868
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
867
|
print("ele2_nan",ele2_nan.shape)
|
|
869
|
print("ele2_nan",ele2_nan.shape)
|
|
|
868
|
print("data_ele_old",data_ele_old.shape)
|
|
870
|
print("data_ele_old",data_ele_old.shape)
|
|
|
869
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
871
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
870
|
|
|
872
|
|
|
|
871
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
873
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
|
872
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
874
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
|
873
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
875
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
874
|
data_weather = data_weather[::-1,:]# reversa
|
|
876
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
875
|
vec= numpy.where(data_ele_new<ang_max)
|
|
877
|
vec= numpy.where(data_ele_new<ang_max)
|
|
|
876
|
data_ele_new = data_ele_new[vec]
|
|
878
|
data_ele_new = data_ele_new[vec]
|
|
|
877
|
data_ele_old = data_ele_old[vec]
|
|
879
|
data_ele_old = data_ele_old[vec]
|
|
|
878
|
data_weather = data_weather[vec[0]]
|
|
880
|
data_weather = data_weather[vec[0]]
|
|
|
879
|
vec2= numpy.where(0<data_ele_new)
|
|
881
|
vec2= numpy.where(0<data_ele_new)
|
|
|
880
|
data_ele_new = data_ele_new[vec2]
|
|
882
|
data_ele_new = data_ele_new[vec2]
|
|
|
881
|
data_ele_old = data_ele_old[vec2]
|
|
883
|
data_ele_old = data_ele_old[vec2]
|
|
|
882
|
data_weather = data_weather[vec2[0]]
|
|
884
|
data_weather = data_weather[vec2[0]]
|
|
|
883
|
self.start_data_ele = data_ele_new[0]
|
|
885
|
self.start_data_ele = data_ele_new[0]
|
|
|
884
|
self.end_data_ele = data_ele_new[-1]
|
|
886
|
self.end_data_ele = data_ele_new[-1]
|
|
|
885
|
|
|
887
|
|
|
|
886
|
n1= round(self.start_data_ele)- start
|
|
888
|
n1= round(self.start_data_ele)- start
|
|
|
887
|
n2= end - round(self.end_data_ele)-1
|
|
889
|
n2= end - round(self.end_data_ele)-1
|
|
|
888
|
print(self.start_data_ele)
|
|
890
|
print(self.start_data_ele)
|
|
|
889
|
print(self.end_data_ele)
|
|
891
|
print(self.end_data_ele)
|
|
|
890
|
if n1>0:
|
|
892
|
if n1>0:
|
|
|
891
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
893
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
892
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
894
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
893
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
895
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
894
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
896
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
895
|
if n2>0:
|
|
897
|
if n2>0:
|
|
|
896
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
898
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
897
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
899
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
898
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
900
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
899
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
901
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
900
|
# RADAR
|
|
902
|
# RADAR
|
|
|
901
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
903
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
|
902
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
904
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
|
903
|
self.val_mean = val_mean
|
|
905
|
self.val_mean = val_mean
|
|
|
904
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
906
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
905
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
907
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
|
906
|
else:
|
|
908
|
else:
|
|
|
907
|
#print("**********************************************")
|
|
909
|
#print("**********************************************")
|
|
|
908
|
#print("****************VARIABLE**********************")
|
|
910
|
#print("****************VARIABLE**********************")
|
|
|
909
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
911
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
910
|
#---------------------------------------------------------------------
|
|
912
|
#---------------------------------------------------------------------
|
|
|
911
|
##print("INPUT data_ele",data_ele)
|
|
913
|
##print("INPUT data_ele",data_ele)
|
|
|
912
|
flag=0
|
|
914
|
flag=0
|
|
|
913
|
start_ele = self.res_ele[0]
|
|
915
|
start_ele = self.res_ele[0]
|
|
|
914
|
tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
916
|
tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
|
915
|
#print("TIPO DE DATA",tipo_case)
|
|
917
|
#print("TIPO DE DATA",tipo_case)
|
|
|
916
|
#-----------new------------
|
|
918
|
#-----------new------------
|
|
|
917
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
919
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
|
918
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
920
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
919
|
|
|
921
|
|
|
|
920
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
922
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
|
921
|
|
|
923
|
|
|
|
922
|
if tipo_case==0 : # SUBIDA
|
|
924
|
if tipo_case==0 : # SUBIDA
|
|
|
923
|
vec = numpy.where(data_ele<ang_max)
|
|
925
|
vec = numpy.where(data_ele<ang_max)
|
|
|
924
|
data_ele = data_ele[vec]
|
|
926
|
data_ele = data_ele[vec]
|
|
|
925
|
data_ele_old = data_ele_old[vec]
|
|
927
|
data_ele_old = data_ele_old[vec]
|
|
|
926
|
data_weather = data_weather[vec[0]]
|
|
928
|
data_weather = data_weather[vec[0]]
|
|
|
927
|
|
|
929
|
|
|
|
928
|
vec2 = numpy.where(0<data_ele)
|
|
930
|
vec2 = numpy.where(0<data_ele)
|
|
|
929
|
data_ele= data_ele[vec2]
|
|
931
|
data_ele= data_ele[vec2]
|
|
|
930
|
data_ele_old= data_ele_old[vec2]
|
|
932
|
data_ele_old= data_ele_old[vec2]
|
|
|
931
|
##print(data_ele_new)
|
|
933
|
##print(data_ele_new)
|
|
|
932
|
data_weather= data_weather[vec2[0]]
|
|
934
|
data_weather= data_weather[vec2[0]]
|
|
|
933
|
|
|
935
|
|
|
|
934
|
new_i_ele = int(round(data_ele[0]))
|
|
936
|
new_i_ele = int(round(data_ele[0]))
|
|
|
935
|
new_f_ele = int(round(data_ele[-1]))
|
|
937
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
936
|
#print(new_i_ele)
|
|
938
|
#print(new_i_ele)
|
|
|
937
|
#print(new_f_ele)
|
|
939
|
#print(new_f_ele)
|
|
|
938
|
#print(data_ele,len(data_ele))
|
|
940
|
#print(data_ele,len(data_ele))
|
|
|
939
|
#print(data_ele_old,len(data_ele_old))
|
|
941
|
#print(data_ele_old,len(data_ele_old))
|
|
|
940
|
if new_i_ele< 2:
|
|
942
|
if new_i_ele< 2:
|
|
|
941
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
943
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
942
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
944
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
943
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
945
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
|
944
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
946
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
|
945
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
947
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
|
946
|
data_ele = self.res_ele
|
|
948
|
data_ele = self.res_ele
|
|
|
947
|
data_weather = self.res_weather[val_ch]
|
|
949
|
data_weather = self.res_weather[val_ch]
|
|
|
948
|
|
|
950
|
|
|
|
949
|
elif tipo_case==1 : #BAJADA
|
|
951
|
elif tipo_case==1 : #BAJADA
|
|
|
950
|
data_ele = data_ele[::-1] # reversa
|
|
952
|
data_ele = data_ele[::-1] # reversa
|
|
|
951
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
953
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
952
|
data_weather = data_weather[::-1,:]# reversa
|
|
954
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
953
|
vec= numpy.where(data_ele<ang_max)
|
|
955
|
vec= numpy.where(data_ele<ang_max)
|
|
|
954
|
data_ele = data_ele[vec]
|
|
956
|
data_ele = data_ele[vec]
|
|
|
955
|
data_ele_old = data_ele_old[vec]
|
|
957
|
data_ele_old = data_ele_old[vec]
|
|
|
956
|
data_weather = data_weather[vec[0]]
|
|
958
|
data_weather = data_weather[vec[0]]
|
|
|
957
|
vec2= numpy.where(0<data_ele)
|
|
959
|
vec2= numpy.where(0<data_ele)
|
|
|
958
|
data_ele = data_ele[vec2]
|
|
960
|
data_ele = data_ele[vec2]
|
|
|
959
|
data_ele_old = data_ele_old[vec2]
|
|
961
|
data_ele_old = data_ele_old[vec2]
|
|
|
960
|
data_weather = data_weather[vec2[0]]
|
|
962
|
data_weather = data_weather[vec2[0]]
|
|
|
961
|
|
|
963
|
|
|
|
962
|
|
|
964
|
|
|
|
963
|
new_i_ele = int(round(data_ele[0]))
|
|
965
|
new_i_ele = int(round(data_ele[0]))
|
|
|
964
|
new_f_ele = int(round(data_ele[-1]))
|
|
966
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
965
|
#print(data_ele)
|
|
967
|
#print(data_ele)
|
|
|
966
|
#print(ang_max)
|
|
968
|
#print(ang_max)
|
|
|
967
|
#print(data_ele_old)
|
|
969
|
#print(data_ele_old)
|
|
|
968
|
if new_i_ele <= 1:
|
|
970
|
if new_i_ele <= 1:
|
|
|
969
|
new_i_ele = 1
|
|
971
|
new_i_ele = 1
|
|
|
970
|
if round(data_ele[-1])>=ang_max-1:
|
|
972
|
if round(data_ele[-1])>=ang_max-1:
|
|
|
971
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
973
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
972
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
974
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
973
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
975
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
|
974
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
976
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
|
975
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
977
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
|
976
|
data_ele = self.res_ele
|
|
978
|
data_ele = self.res_ele
|
|
|
977
|
data_weather = self.res_weather[val_ch]
|
|
979
|
data_weather = self.res_weather[val_ch]
|
|
|
978
|
|
|
980
|
|
|
|
979
|
elif tipo_case==2: #bajada
|
|
981
|
elif tipo_case==2: #bajada
|
|
|
980
|
vec = numpy.where(data_ele<ang_max)
|
|
982
|
vec = numpy.where(data_ele<ang_max)
|
|
|
981
|
data_ele = data_ele[vec]
|
|
983
|
data_ele = data_ele[vec]
|
|
|
982
|
data_weather= data_weather[vec[0]]
|
|
984
|
data_weather= data_weather[vec[0]]
|
|
|
983
|
|
|
985
|
|
|
|
984
|
len_vec = len(vec)
|
|
986
|
len_vec = len(vec)
|
|
|
985
|
data_ele_new = data_ele[::-1] # reversa
|
|
987
|
data_ele_new = data_ele[::-1] # reversa
|
|
|
986
|
data_weather = data_weather[::-1,:]
|
|
988
|
data_weather = data_weather[::-1,:]
|
|
|
987
|
new_i_ele = int(data_ele_new[0])
|
|
989
|
new_i_ele = int(data_ele_new[0])
|
|
|
988
|
new_f_ele = int(data_ele_new[-1])
|
|
990
|
new_f_ele = int(data_ele_new[-1])
|
|
|
989
|
|
|
991
|
|
|
|
990
|
n1= new_i_ele- ang_min
|
|
992
|
n1= new_i_ele- ang_min
|
|
|
991
|
n2= ang_max - new_f_ele-1
|
|
993
|
n2= ang_max - new_f_ele-1
|
|
|
992
|
if n1>0:
|
|
994
|
if n1>0:
|
|
|
993
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
995
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
994
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
996
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
995
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
997
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
996
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
998
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
997
|
if n2>0:
|
|
999
|
if n2>0:
|
|
|
998
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
1000
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
999
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1001
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1000
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1002
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1001
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1003
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1002
|
|
|
1004
|
|
|
|
1003
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
1005
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
1004
|
self.res_ele = data_ele
|
|
1006
|
self.res_ele = data_ele
|
|
|
1005
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1007
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1006
|
data_ele = self.res_ele
|
|
1008
|
data_ele = self.res_ele
|
|
|
1007
|
data_weather = self.res_weather[val_ch]
|
|
1009
|
data_weather = self.res_weather[val_ch]
|
|
|
1008
|
|
|
1010
|
|
|
|
1009
|
elif tipo_case==3:#subida
|
|
1011
|
elif tipo_case==3:#subida
|
|
|
1010
|
vec = numpy.where(0<data_ele)
|
|
1012
|
vec = numpy.where(0<data_ele)
|
|
|
1011
|
data_ele= data_ele[vec]
|
|
1013
|
data_ele= data_ele[vec]
|
|
|
1012
|
data_ele_new = data_ele
|
|
1014
|
data_ele_new = data_ele
|
|
|
1013
|
data_ele_old= data_ele_old[vec]
|
|
1015
|
data_ele_old= data_ele_old[vec]
|
|
|
1014
|
data_weather= data_weather[vec[0]]
|
|
1016
|
data_weather= data_weather[vec[0]]
|
|
|
1015
|
pos_ini = numpy.argmin(data_ele)
|
|
1017
|
pos_ini = numpy.argmin(data_ele)
|
|
|
1016
|
if pos_ini>0:
|
|
1018
|
if pos_ini>0:
|
|
|
1017
|
len_vec= len(data_ele)
|
|
1019
|
len_vec= len(data_ele)
|
|
|
1018
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
1020
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
|
1019
|
#print(vec3)
|
|
1021
|
#print(vec3)
|
|
|
1020
|
data_ele= data_ele[vec3]
|
|
1022
|
data_ele= data_ele[vec3]
|
|
|
1021
|
data_ele_new = data_ele
|
|
1023
|
data_ele_new = data_ele
|
|
|
1022
|
data_ele_old= data_ele_old[vec3]
|
|
1024
|
data_ele_old= data_ele_old[vec3]
|
|
|
1023
|
data_weather= data_weather[vec3]
|
|
1025
|
data_weather= data_weather[vec3]
|
|
|
1024
|
|
|
1026
|
|
|
|
1025
|
new_i_ele = int(data_ele_new[0])
|
|
1027
|
new_i_ele = int(data_ele_new[0])
|
|
|
1026
|
new_f_ele = int(data_ele_new[-1])
|
|
1028
|
new_f_ele = int(data_ele_new[-1])
|
|
|
1027
|
n1= new_i_ele- ang_min
|
|
1029
|
n1= new_i_ele- ang_min
|
|
|
1028
|
n2= ang_max - new_f_ele-1
|
|
1030
|
n2= ang_max - new_f_ele-1
|
|
|
1029
|
if n1>0:
|
|
1031
|
if n1>0:
|
|
|
1030
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
1032
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
1031
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1033
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1032
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1034
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1033
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
1035
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
1034
|
if n2>0:
|
|
1036
|
if n2>0:
|
|
|
1035
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
1037
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
1036
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1038
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1037
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1039
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1038
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1040
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1039
|
|
|
1041
|
|
|
|
1040
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
1042
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
1041
|
self.res_ele = data_ele
|
|
1043
|
self.res_ele = data_ele
|
|
|
1042
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1044
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1043
|
data_ele = self.res_ele
|
|
1045
|
data_ele = self.res_ele
|
|
|
1044
|
data_weather = self.res_weather[val_ch]
|
|
1046
|
data_weather = self.res_weather[val_ch]
|
|
|
1045
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
1047
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
|
1046
|
return data_weather,data_ele
|
|
1048
|
return data_weather,data_ele
|
|
|
1047
|
|
|
1049
|
|
|
|
1048
|
|
|
1050
|
|
|
|
1049
|
def plot(self):
|
|
1051
|
def plot(self):
|
|
|
1050
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
1052
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
|
1051
|
data = self.data[-1]
|
|
1053
|
data = self.data[-1]
|
|
|
1052
|
r = self.data.yrange
|
|
1054
|
r = self.data.yrange
|
|
|
1053
|
delta_height = r[1]-r[0]
|
|
1055
|
delta_height = r[1]-r[0]
|
|
|
1054
|
r_mask = numpy.where(r>=0)[0]
|
|
1056
|
r_mask = numpy.where(r>=0)[0]
|
|
|
1055
|
##print("delta_height",delta_height)
|
|
1057
|
##print("delta_height",delta_height)
|
|
|
1056
|
#print("r_mask",r_mask,len(r_mask))
|
|
1058
|
#print("r_mask",r_mask,len(r_mask))
|
|
|
1057
|
r = numpy.arange(len(r_mask))*delta_height
|
|
1059
|
r = numpy.arange(len(r_mask))*delta_height
|
|
|
1058
|
self.y = 2*r
|
|
1060
|
self.y = 2*r
|
|
|
1059
|
res = 1
|
|
1061
|
res = 1
|
|
|
1060
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
1062
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
|
1061
|
ang_max = self.ang_max
|
|
1063
|
ang_max = self.ang_max
|
|
|
1062
|
ang_min = self.ang_min
|
|
1064
|
ang_min = self.ang_min
|
|
|
1063
|
var_ang =ang_max - ang_min
|
|
1065
|
var_ang =ang_max - ang_min
|
|
|
1064
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
1066
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
|
1065
|
###print("step",step)
|
|
1067
|
###print("step",step)
|
|
|
1066
|
#--------------------------------------------------------
|
|
1068
|
#--------------------------------------------------------
|
|
|
1067
|
##print('weather',data['weather'].shape)
|
|
1069
|
##print('weather',data['weather'].shape)
|
|
|
1068
|
##print('ele',data['ele'].shape)
|
|
1070
|
##print('ele',data['ele'].shape)
|
|
|
1069
|
|
|
1071
|
|
|
|
1070
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
1072
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
1071
|
###self.res_azi = numpy.mean(data['azi'])
|
|
1073
|
###self.res_azi = numpy.mean(data['azi'])
|
|
|
1072
|
###print("self.res_ele",self.res_ele)
|
|
1074
|
###print("self.res_ele",self.res_ele)
|
|
|
1073
|
plt.clf()
|
|
1075
|
plt.clf()
|
|
|
1074
|
subplots = [121, 122]
|
|
1076
|
subplots = [121, 122]
|
|
|
|
|
|
1077
|
cg={'angular_spacing': 20.}
|
|
|
1075
|
if self.ini==0:
|
|
1078
|
if self.ini==0:
|
|
|
1076
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
1079
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
|
1077
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
1080
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
|
1078
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
1081
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
|
1079
|
|
|
1082
|
|
|
|
1080
|
for i,ax in enumerate(self.axes):
|
|
1083
|
for i,ax in enumerate(self.axes):
|
|
|
1081
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
1084
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
1082
|
self.res_azi = numpy.mean(data['azi'])
|
|
1085
|
self.res_azi = numpy.mean(data['azi'])
|
|
|
1083
|
if i==0:
|
|
1086
|
if i==0:
|
|
|
1084
|
print("*****************************************************************************to plot**************************",self.res_weather[i].shape)
|
|
1087
|
print("*****************************************************************************to plot**************************",self.res_weather[i].shape)
|
|
|
|
|
|
1088
|
self.zmin = self.zmin if self.zmin else 20
|
|
|
|
|
|
1089
|
self.zmax = self.zmax if self.zmax else 80
|
|
|
1085
|
if ax.firsttime:
|
|
1090
|
if ax.firsttime:
|
|
|
1086
|
#plt.clf()
|
|
1091
|
#plt.clf()
|
|
|
1087
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1092
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax)
|
|
|
1088
|
#fig=self.figures[0]
|
|
1093
|
#fig=self.figures[0]
|
|
|
1089
|
else:
|
|
1094
|
else:
|
|
|
1090
|
#plt.clf()
|
|
1095
|
#plt.clf()
|
|
|
1091
|
if i==0:
|
|
1096
|
if i==0:
|
|
|
1092
|
print(self.res_weather[i])
|
|
1097
|
print(self.res_weather[i])
|
|
|
1093
|
print(self.res_ele)
|
|
1098
|
print(self.res_ele)
|
|
|
1094
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1099
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax)
|
|
|
1095
|
caax = cgax.parasites[0]
|
|
1100
|
caax = cgax.parasites[0]
|
|
|
1096
|
paax = cgax.parasites[1]
|
|
1101
|
paax = cgax.parasites[1]
|
|
|
1097
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
1102
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
|
1098
|
caax.set_xlabel('x_range [km]')
|
|
1103
|
caax.set_xlabel('x_range [km]')
|
|
|
1099
|
caax.set_ylabel('y_range [km]')
|
|
1104
|
caax.set_ylabel('y_range [km]')
|
|
|
1100
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
1105
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
1101
|
print("***************************self.ini****************************",self.ini)
|
|
1106
|
print("***************************self.ini****************************",self.ini)
|
|
|
1102
|
self.ini= self.ini+1
|
|
1107
|
self.ini= self.ini+1
|
|
|
1103
|
|
|
1108
|
|
|
|
1104
|
class WeatherRHI_vRF2_Plot(Plot):
|
|
1109
|
class WeatherRHI_vRF2_Plot(Plot):
|
|
|
1105
|
CODE = 'weather'
|
|
1110
|
CODE = 'weather'
|
|
|
1106
|
plot_name = 'weather'
|
|
1111
|
plot_name = 'weather'
|
|
|
1107
|
plot_type = 'rhistyle'
|
|
1112
|
plot_type = 'rhistyle'
|
|
|
1108
|
buffering = False
|
|
1113
|
buffering = False
|
|
|
1109
|
data_ele_tmp = None
|
|
1114
|
data_ele_tmp = None
|
|
|
1110
|
|
|
1115
|
|
|
|
1111
|
def setup(self):
|
|
1116
|
def setup(self):
|
|
|
1112
|
print("********************")
|
|
1117
|
print("********************")
|
|
|
1113
|
print("********************")
|
|
1118
|
print("********************")
|
|
|
1114
|
print("********************")
|
|
1119
|
print("********************")
|
|
|
1115
|
print("SETUP WEATHER PLOT")
|
|
1120
|
print("SETUP WEATHER PLOT")
|
|
|
1116
|
self.ncols = 1
|
|
1121
|
self.ncols = 1
|
|
|
1117
|
self.nrows = 1
|
|
1122
|
self.nrows = 1
|
|
|
1118
|
self.nplots= 1
|
|
1123
|
self.nplots= 1
|
|
|
1119
|
self.ylabel= 'Range [Km]'
|
|
1124
|
self.ylabel= 'Range [Km]'
|
|
|
1120
|
self.titles= ['Weather']
|
|
1125
|
self.titles= ['Weather']
|
|
|
1121
|
if self.channels is not None:
|
|
1126
|
if self.channels is not None:
|
|
|
1122
|
self.nplots = len(self.channels)
|
|
1127
|
self.nplots = len(self.channels)
|
|
|
1123
|
self.nrows = len(self.channels)
|
|
1128
|
self.nrows = len(self.channels)
|
|
|
1124
|
else:
|
|
1129
|
else:
|
|
|
1125
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
1130
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
|
1126
|
self.nrows = self.nplots
|
|
1131
|
self.nrows = self.nplots
|
|
|
1127
|
self.channels = list(range(self.nplots))
|
|
1132
|
self.channels = list(range(self.nplots))
|
|
|
1128
|
print("channels",self.channels)
|
|
1133
|
print("channels",self.channels)
|
|
|
1129
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
1134
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
|
1130
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
1135
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
|
1131
|
print("self.titles",self.titles)
|
|
1136
|
print("self.titles",self.titles)
|
|
|
1132
|
self.colorbar=False
|
|
1137
|
self.colorbar=False
|
|
|
1133
|
self.width =8
|
|
1138
|
self.width =8
|
|
|
1134
|
self.height =8
|
|
1139
|
self.height =8
|
|
|
1135
|
self.ini =0
|
|
1140
|
self.ini =0
|
|
|
1136
|
self.len_azi =0
|
|
1141
|
self.len_azi =0
|
|
|
1137
|
self.buffer_ini = None
|
|
1142
|
self.buffer_ini = None
|
|
|
1138
|
self.buffer_ele = None
|
|
1143
|
self.buffer_ele = None
|
|
|
1139
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
1144
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
|
1140
|
self.flag =0
|
|
1145
|
self.flag =0
|
|
|
1141
|
self.indicador= 0
|
|
1146
|
self.indicador= 0
|
|
|
1142
|
self.last_data_ele = None
|
|
1147
|
self.last_data_ele = None
|
|
|
1143
|
self.val_mean = None
|
|
1148
|
self.val_mean = None
|
|
|
1144
|
|
|
1149
|
|
|
|
1145
|
def update(self, dataOut):
|
|
1150
|
def update(self, dataOut):
|
|
|
1146
|
|
|
1151
|
|
|
|
1147
|
data = {}
|
|
1152
|
data = {}
|
|
|
1148
|
meta = {}
|
|
1153
|
meta = {}
|
|
|
1149
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
1154
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
|
1150
|
factor = 1
|
|
1155
|
factor = 1
|
|
|
1151
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
1156
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
|
1152
|
factor = dataOut.normFactor
|
|
1157
|
factor = dataOut.normFactor
|
|
|
1153
|
print("dataOut",dataOut.data_360.shape)
|
|
1158
|
print("dataOut",dataOut.data_360.shape)
|
|
|
1154
|
#
|
|
1159
|
#
|
|
|
1155
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
1160
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
|
1156
|
#
|
|
1161
|
#
|
|
|
1157
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
1162
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
|
1158
|
data['azi'] = dataOut.data_azi
|
|
1163
|
data['azi'] = dataOut.data_azi
|
|
|
1159
|
data['ele'] = dataOut.data_ele
|
|
1164
|
data['ele'] = dataOut.data_ele
|
|
|
1160
|
data['case_flag'] = dataOut.case_flag
|
|
1165
|
data['case_flag'] = dataOut.case_flag
|
|
|
1161
|
#print("UPDATE")
|
|
1166
|
#print("UPDATE")
|
|
|
1162
|
#print("data[weather]",data['weather'].shape)
|
|
1167
|
#print("data[weather]",data['weather'].shape)
|
|
|
1163
|
#print("data[azi]",data['azi'])
|
|
1168
|
#print("data[azi]",data['azi'])
|
|
|
1164
|
return data, meta
|
|
1169
|
return data, meta
|
|
|
1165
|
|
|
1170
|
|
|
|
1166
|
def get2List(self,angulos):
|
|
1171
|
def get2List(self,angulos):
|
|
|
1167
|
list1=[]
|
|
1172
|
list1=[]
|
|
|
1168
|
list2=[]
|
|
1173
|
list2=[]
|
|
|
1169
|
for i in reversed(range(len(angulos))):
|
|
1174
|
for i in reversed(range(len(angulos))):
|
|
|
1170
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
1175
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
|
1171
|
diff_ = angulos[i]-angulos[i-1]
|
|
1176
|
diff_ = angulos[i]-angulos[i-1]
|
|
|
1172
|
if abs(diff_) >1.5:
|
|
1177
|
if abs(diff_) >1.5:
|
|
|
1173
|
list1.append(i-1)
|
|
1178
|
list1.append(i-1)
|
|
|
1174
|
list2.append(diff_)
|
|
1179
|
list2.append(diff_)
|
|
|
1175
|
return list(reversed(list1)),list(reversed(list2))
|
|
1180
|
return list(reversed(list1)),list(reversed(list2))
|
|
|
1176
|
|
|
1181
|
|
|
|
1177
|
def fixData90(self,list_,ang_):
|
|
1182
|
def fixData90(self,list_,ang_):
|
|
|
1178
|
if list_[0]==-1:
|
|
1183
|
if list_[0]==-1:
|
|
|
1179
|
vec = numpy.where(ang_<ang_[0])
|
|
1184
|
vec = numpy.where(ang_<ang_[0])
|
|
|
1180
|
ang_[vec] = ang_[vec]+90
|
|
1185
|
ang_[vec] = ang_[vec]+90
|
|
|
1181
|
return ang_
|
|
1186
|
return ang_
|
|
|
1182
|
return ang_
|
|
1187
|
return ang_
|
|
|
1183
|
|
|
1188
|
|
|
|
1184
|
def fixData90HL(self,angulos):
|
|
1189
|
def fixData90HL(self,angulos):
|
|
|
1185
|
vec = numpy.where(angulos>=90)
|
|
1190
|
vec = numpy.where(angulos>=90)
|
|
|
1186
|
angulos[vec]=angulos[vec]-90
|
|
1191
|
angulos[vec]=angulos[vec]-90
|
|
|
1187
|
return angulos
|
|
1192
|
return angulos
|
|
|
1188
|
|
|
1193
|
|
|
|
1189
|
|
|
1194
|
|
|
|
1190
|
def search_pos(self,pos,list_):
|
|
1195
|
def search_pos(self,pos,list_):
|
|
|
1191
|
for i in range(len(list_)):
|
|
1196
|
for i in range(len(list_)):
|
|
|
1192
|
if pos == list_[i]:
|
|
1197
|
if pos == list_[i]:
|
|
|
1193
|
return True,i
|
|
1198
|
return True,i
|
|
|
1194
|
i=None
|
|
1199
|
i=None
|
|
|
1195
|
return False,i
|
|
1200
|
return False,i
|
|
|
1196
|
|
|
1201
|
|
|
|
1197
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
1202
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
|
1198
|
size = len(ang_)
|
|
1203
|
size = len(ang_)
|
|
|
1199
|
size2 = 0
|
|
1204
|
size2 = 0
|
|
|
1200
|
for i in range(len(list2_)):
|
|
1205
|
for i in range(len(list2_)):
|
|
|
1201
|
size2=size2+round(abs(list2_[i]))-1
|
|
1206
|
size2=size2+round(abs(list2_[i]))-1
|
|
|
1202
|
new_size= size+size2
|
|
1207
|
new_size= size+size2
|
|
|
1203
|
ang_new = numpy.zeros(new_size)
|
|
1208
|
ang_new = numpy.zeros(new_size)
|
|
|
1204
|
ang_new2 = numpy.zeros(new_size)
|
|
1209
|
ang_new2 = numpy.zeros(new_size)
|
|
|
1205
|
|
|
1210
|
|
|
|
1206
|
tmp = 0
|
|
1211
|
tmp = 0
|
|
|
1207
|
c = 0
|
|
1212
|
c = 0
|
|
|
1208
|
for i in range(len(ang_)):
|
|
1213
|
for i in range(len(ang_)):
|
|
|
1209
|
ang_new[tmp +c] = ang_[i]
|
|
1214
|
ang_new[tmp +c] = ang_[i]
|
|
|
1210
|
ang_new2[tmp+c] = ang_[i]
|
|
1215
|
ang_new2[tmp+c] = ang_[i]
|
|
|
1211
|
condition , value = self.search_pos(i,list1_)
|
|
1216
|
condition , value = self.search_pos(i,list1_)
|
|
|
1212
|
if condition:
|
|
1217
|
if condition:
|
|
|
1213
|
pos = tmp + c + 1
|
|
1218
|
pos = tmp + c + 1
|
|
|
1214
|
for k in range(round(abs(list2_[value]))-1):
|
|
1219
|
for k in range(round(abs(list2_[value]))-1):
|
|
|
1215
|
if tipo_case==0 or tipo_case==3:#subida
|
|
1220
|
if tipo_case==0 or tipo_case==3:#subida
|
|
|
1216
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
1221
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
|
1217
|
ang_new2[pos+k] = numpy.nan
|
|
1222
|
ang_new2[pos+k] = numpy.nan
|
|
|
1218
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
1223
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
|
1219
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
1224
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
|
1220
|
ang_new2[pos+k] = numpy.nan
|
|
1225
|
ang_new2[pos+k] = numpy.nan
|
|
|
1221
|
|
|
1226
|
|
|
|
1222
|
tmp = pos +k
|
|
1227
|
tmp = pos +k
|
|
|
1223
|
c = 0
|
|
1228
|
c = 0
|
|
|
1224
|
c=c+1
|
|
1229
|
c=c+1
|
|
|
1225
|
return ang_new,ang_new2
|
|
1230
|
return ang_new,ang_new2
|
|
|
1226
|
|
|
1231
|
|
|
|
1227
|
def globalCheckPED(self,angulos,tipo_case):
|
|
1232
|
def globalCheckPED(self,angulos,tipo_case):
|
|
|
1228
|
l1,l2 = self.get2List(angulos)
|
|
1233
|
l1,l2 = self.get2List(angulos)
|
|
|
1229
|
##print("l1",l1)
|
|
1234
|
##print("l1",l1)
|
|
|
1230
|
##print("l2",l2)
|
|
1235
|
##print("l2",l2)
|
|
|
1231
|
if len(l1)>0:
|
|
1236
|
if len(l1)>0:
|
|
|
1232
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
1237
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
|
1233
|
#l1,l2 = self.get2List(angulos2)
|
|
1238
|
#l1,l2 = self.get2List(angulos2)
|
|
|
1234
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
1239
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
|
1235
|
#ang1_ = self.fixData90HL(ang1_)
|
|
1240
|
#ang1_ = self.fixData90HL(ang1_)
|
|
|
1236
|
#ang2_ = self.fixData90HL(ang2_)
|
|
1241
|
#ang2_ = self.fixData90HL(ang2_)
|
|
|
1237
|
else:
|
|
1242
|
else:
|
|
|
1238
|
ang1_= angulos
|
|
1243
|
ang1_= angulos
|
|
|
1239
|
ang2_= angulos
|
|
1244
|
ang2_= angulos
|
|
|
1240
|
return ang1_,ang2_
|
|
1245
|
return ang1_,ang2_
|
|
|
1241
|
|
|
1246
|
|
|
|
1242
|
|
|
1247
|
|
|
|
1243
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
1248
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
|
1244
|
data= data_ele
|
|
1249
|
data= data_ele
|
|
|
1245
|
data_T= data_weather
|
|
1250
|
data_T= data_weather
|
|
|
1246
|
if data.shape[0]> data_T.shape[0]:
|
|
1251
|
if data.shape[0]> data_T.shape[0]:
|
|
|
1247
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
1252
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
|
1248
|
c = 0
|
|
1253
|
c = 0
|
|
|
1249
|
for i in range(len(data)):
|
|
1254
|
for i in range(len(data)):
|
|
|
1250
|
if numpy.isnan(data[i]):
|
|
1255
|
if numpy.isnan(data[i]):
|
|
|
1251
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
1256
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
1252
|
else:
|
|
1257
|
else:
|
|
|
1253
|
data_N[i,:]=data_T[c,:]
|
|
1258
|
data_N[i,:]=data_T[c,:]
|
|
|
1254
|
c=c+1
|
|
1259
|
c=c+1
|
|
|
1255
|
return data_N
|
|
1260
|
return data_N
|
|
|
1256
|
else:
|
|
1261
|
else:
|
|
|
1257
|
for i in range(len(data)):
|
|
1262
|
for i in range(len(data)):
|
|
|
1258
|
if numpy.isnan(data[i]):
|
|
1263
|
if numpy.isnan(data[i]):
|
|
|
1259
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
1264
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
1260
|
return data_T
|
|
1265
|
return data_T
|
|
|
1261
|
|
|
1266
|
|
|
|
1262
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
1267
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
|
1263
|
start = data_ele[0]
|
|
1268
|
start = data_ele[0]
|
|
|
1264
|
end = data_ele[-1]
|
|
1269
|
end = data_ele[-1]
|
|
|
1265
|
number = (end-start)
|
|
1270
|
number = (end-start)
|
|
|
1266
|
len_ang=len(data_ele)
|
|
1271
|
len_ang=len(data_ele)
|
|
|
1267
|
print("start",start)
|
|
1272
|
print("start",start)
|
|
|
1268
|
print("end",end)
|
|
1273
|
print("end",end)
|
|
|
1269
|
print("number",number)
|
|
1274
|
print("number",number)
|
|
|
1270
|
|
|
1275
|
|
|
|
1271
|
print("len_ang",len_ang)
|
|
1276
|
print("len_ang",len_ang)
|
|
|
1272
|
|
|
1277
|
|
|
|
1273
|
#exit(1)
|
|
1278
|
#exit(1)
|
|
|
1274
|
|
|
1279
|
|
|
|
1275
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
1280
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
|
1276
|
return 0
|
|
1281
|
return 0
|
|
|
1277
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
1282
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
1278
|
# return 1
|
|
1283
|
# return 1
|
|
|
1279
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
1284
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
1280
|
return 1
|
|
1285
|
return 1
|
|
|
1281
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
1286
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
|
1282
|
return 2
|
|
1287
|
return 2
|
|
|
1283
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
1288
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
|
1284
|
return 3
|
|
1289
|
return 3
|
|
|
1285
|
|
|
1290
|
|
|
|
1286
|
|
|
1291
|
|
|
|
1287
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
1292
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
|
1288
|
ang_max= ang_max
|
|
1293
|
ang_max= ang_max
|
|
|
1289
|
ang_min= ang_min
|
|
1294
|
ang_min= ang_min
|
|
|
1290
|
data_weather=data_weather
|
|
1295
|
data_weather=data_weather
|
|
|
1291
|
val_ch=val_ch
|
|
1296
|
val_ch=val_ch
|
|
|
1292
|
##print("*********************DATA WEATHER**************************************")
|
|
1297
|
##print("*********************DATA WEATHER**************************************")
|
|
|
1293
|
##print(data_weather)
|
|
1298
|
##print(data_weather)
|
|
|
1294
|
if self.ini==0:
|
|
1299
|
if self.ini==0:
|
|
|
1295
|
'''
|
|
1300
|
'''
|
|
|
1296
|
print("**********************************************")
|
|
1301
|
print("**********************************************")
|
|
|
1297
|
print("**********************************************")
|
|
1302
|
print("**********************************************")
|
|
|
1298
|
print("***************ini**************")
|
|
1303
|
print("***************ini**************")
|
|
|
1299
|
print("**********************************************")
|
|
1304
|
print("**********************************************")
|
|
|
1300
|
print("**********************************************")
|
|
1305
|
print("**********************************************")
|
|
|
1301
|
'''
|
|
1306
|
'''
|
|
|
1302
|
#print("data_ele",data_ele)
|
|
1307
|
#print("data_ele",data_ele)
|
|
|
1303
|
#----------------------------------------------------------
|
|
1308
|
#----------------------------------------------------------
|
|
|
1304
|
tipo_case = case_flag[-1]
|
|
1309
|
tipo_case = case_flag[-1]
|
|
|
1305
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
1310
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
|
1306
|
print("check_case",tipo_case)
|
|
1311
|
print("check_case",tipo_case)
|
|
|
1307
|
#exit(1)
|
|
1312
|
#exit(1)
|
|
|
1308
|
#--------------------- new -------------------------
|
|
1313
|
#--------------------- new -------------------------
|
|
|
1309
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
1314
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
|
1310
|
|
|
1315
|
|
|
|
1311
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
1316
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
1312
|
start= ang_min
|
|
1317
|
start= ang_min
|
|
|
1313
|
end = ang_max
|
|
1318
|
end = ang_max
|
|
|
1314
|
n= (ang_max-ang_min)/res
|
|
1319
|
n= (ang_max-ang_min)/res
|
|
|
1315
|
#------ new
|
|
1320
|
#------ new
|
|
|
1316
|
self.start_data_ele = data_ele_new[0]
|
|
1321
|
self.start_data_ele = data_ele_new[0]
|
|
|
1317
|
self.end_data_ele = data_ele_new[-1]
|
|
1322
|
self.end_data_ele = data_ele_new[-1]
|
|
|
1318
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
1323
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
|
1319
|
n1= round(self.start_data_ele)- start
|
|
1324
|
n1= round(self.start_data_ele)- start
|
|
|
1320
|
n2= end - round(self.end_data_ele)
|
|
1325
|
n2= end - round(self.end_data_ele)
|
|
|
1321
|
print(self.start_data_ele)
|
|
1326
|
print(self.start_data_ele)
|
|
|
1322
|
print(self.end_data_ele)
|
|
1327
|
print(self.end_data_ele)
|
|
|
1323
|
if n1>0:
|
|
1328
|
if n1>0:
|
|
|
1324
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
1329
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
1325
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1330
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1326
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1331
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1327
|
print("ele1_nan",ele1_nan.shape)
|
|
1332
|
print("ele1_nan",ele1_nan.shape)
|
|
|
1328
|
print("data_ele_old",data_ele_old.shape)
|
|
1333
|
print("data_ele_old",data_ele_old.shape)
|
|
|
1329
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
1334
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
1330
|
if n2>0:
|
|
1335
|
if n2>0:
|
|
|
1331
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
1336
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
1332
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1337
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1333
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1338
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1334
|
print("ele2_nan",ele2_nan.shape)
|
|
1339
|
print("ele2_nan",ele2_nan.shape)
|
|
|
1335
|
print("data_ele_old",data_ele_old.shape)
|
|
1340
|
print("data_ele_old",data_ele_old.shape)
|
|
|
1336
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1341
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1337
|
|
|
1342
|
|
|
|
1338
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
1343
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
|
1339
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
1344
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
|
1340
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
1345
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
1341
|
data_weather = data_weather[::-1,:]# reversa
|
|
1346
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
1342
|
vec= numpy.where(data_ele_new<ang_max)
|
|
1347
|
vec= numpy.where(data_ele_new<ang_max)
|
|
|
1343
|
data_ele_new = data_ele_new[vec]
|
|
1348
|
data_ele_new = data_ele_new[vec]
|
|
|
1344
|
data_ele_old = data_ele_old[vec]
|
|
1349
|
data_ele_old = data_ele_old[vec]
|
|
|
1345
|
data_weather = data_weather[vec[0]]
|
|
1350
|
data_weather = data_weather[vec[0]]
|
|
|
1346
|
vec2= numpy.where(0<data_ele_new)
|
|
1351
|
vec2= numpy.where(0<data_ele_new)
|
|
|
1347
|
data_ele_new = data_ele_new[vec2]
|
|
1352
|
data_ele_new = data_ele_new[vec2]
|
|
|
1348
|
data_ele_old = data_ele_old[vec2]
|
|
1353
|
data_ele_old = data_ele_old[vec2]
|
|
|
1349
|
data_weather = data_weather[vec2[0]]
|
|
1354
|
data_weather = data_weather[vec2[0]]
|
|
|
1350
|
self.start_data_ele = data_ele_new[0]
|
|
1355
|
self.start_data_ele = data_ele_new[0]
|
|
|
1351
|
self.end_data_ele = data_ele_new[-1]
|
|
1356
|
self.end_data_ele = data_ele_new[-1]
|
|
|
1352
|
|
|
1357
|
|
|
|
1353
|
n1= round(self.start_data_ele)- start
|
|
1358
|
n1= round(self.start_data_ele)- start
|
|
|
1354
|
n2= end - round(self.end_data_ele)-1
|
|
1359
|
n2= end - round(self.end_data_ele)-1
|
|
|
1355
|
print(self.start_data_ele)
|
|
1360
|
print(self.start_data_ele)
|
|
|
1356
|
print(self.end_data_ele)
|
|
1361
|
print(self.end_data_ele)
|
|
|
1357
|
if n1>0:
|
|
1362
|
if n1>0:
|
|
|
1358
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
1363
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
1359
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1364
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1360
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1365
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1361
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
1366
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
1362
|
if n2>0:
|
|
1367
|
if n2>0:
|
|
|
1363
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
1368
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
1364
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1369
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1365
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1370
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1366
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1371
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1367
|
# RADAR
|
|
1372
|
# RADAR
|
|
|
1368
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
1373
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
|
1369
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
1374
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
|
1370
|
self.val_mean = val_mean
|
|
1375
|
self.val_mean = val_mean
|
|
|
1371
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1376
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1372
|
print("eleold",data_ele_old)
|
|
1377
|
print("eleold",data_ele_old)
|
|
|
1373
|
print(self.data_ele_tmp[val_ch])
|
|
1378
|
print(self.data_ele_tmp[val_ch])
|
|
|
1374
|
print(data_ele_old.shape[0])
|
|
1379
|
print(data_ele_old.shape[0])
|
|
|
1375
|
print(self.data_ele_tmp[val_ch].shape[0])
|
|
1380
|
print(self.data_ele_tmp[val_ch].shape[0])
|
|
|
1376
|
if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91):
|
|
1381
|
if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91):
|
|
|
1377
|
import sys
|
|
1382
|
import sys
|
|
|
1378
|
print("EXIT",self.ini)
|
|
1383
|
print("EXIT",self.ini)
|
|
|
1379
|
|
|
1384
|
|
|
|
1380
|
sys.exit(1)
|
|
1385
|
sys.exit(1)
|
|
|
1381
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
1386
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
|
1382
|
else:
|
|
1387
|
else:
|
|
|
1383
|
#print("**********************************************")
|
|
1388
|
#print("**********************************************")
|
|
|
1384
|
#print("****************VARIABLE**********************")
|
|
1389
|
#print("****************VARIABLE**********************")
|
|
|
1385
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
1390
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
1386
|
#---------------------------------------------------------------------
|
|
1391
|
#---------------------------------------------------------------------
|
|
|
1387
|
##print("INPUT data_ele",data_ele)
|
|
1392
|
##print("INPUT data_ele",data_ele)
|
|
|
1388
|
flag=0
|
|
1393
|
flag=0
|
|
|
1389
|
start_ele = self.res_ele[0]
|
|
1394
|
start_ele = self.res_ele[0]
|
|
|
1390
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
1395
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
|
1391
|
tipo_case = case_flag[-1]
|
|
1396
|
tipo_case = case_flag[-1]
|
|
|
1392
|
#print("TIPO DE DATA",tipo_case)
|
|
1397
|
#print("TIPO DE DATA",tipo_case)
|
|
|
1393
|
#-----------new------------
|
|
1398
|
#-----------new------------
|
|
|
1394
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
1399
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
|
1395
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1400
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1396
|
|
|
1401
|
|
|
|
1397
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
1402
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
|
1398
|
|
|
1403
|
|
|
|
1399
|
if tipo_case==0 : # SUBIDA
|
|
1404
|
if tipo_case==0 : # SUBIDA
|
|
|
1400
|
vec = numpy.where(data_ele<ang_max)
|
|
1405
|
vec = numpy.where(data_ele<ang_max)
|
|
|
1401
|
data_ele = data_ele[vec]
|
|
1406
|
data_ele = data_ele[vec]
|
|
|
1402
|
data_ele_old = data_ele_old[vec]
|
|
1407
|
data_ele_old = data_ele_old[vec]
|
|
|
1403
|
data_weather = data_weather[vec[0]]
|
|
1408
|
data_weather = data_weather[vec[0]]
|
|
|
1404
|
|
|
1409
|
|
|
|
1405
|
vec2 = numpy.where(0<data_ele)
|
|
1410
|
vec2 = numpy.where(0<data_ele)
|
|
|
1406
|
data_ele= data_ele[vec2]
|
|
1411
|
data_ele= data_ele[vec2]
|
|
|
1407
|
data_ele_old= data_ele_old[vec2]
|
|
1412
|
data_ele_old= data_ele_old[vec2]
|
|
|
1408
|
##print(data_ele_new)
|
|
1413
|
##print(data_ele_new)
|
|
|
1409
|
data_weather= data_weather[vec2[0]]
|
|
1414
|
data_weather= data_weather[vec2[0]]
|
|
|
1410
|
|
|
1415
|
|
|
|
1411
|
new_i_ele = int(round(data_ele[0]))
|
|
1416
|
new_i_ele = int(round(data_ele[0]))
|
|
|
1412
|
new_f_ele = int(round(data_ele[-1]))
|
|
1417
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
1413
|
#print(new_i_ele)
|
|
1418
|
#print(new_i_ele)
|
|
|
1414
|
#print(new_f_ele)
|
|
1419
|
#print(new_f_ele)
|
|
|
1415
|
#print(data_ele,len(data_ele))
|
|
1420
|
#print(data_ele,len(data_ele))
|
|
|
1416
|
#print(data_ele_old,len(data_ele_old))
|
|
1421
|
#print(data_ele_old,len(data_ele_old))
|
|
|
1417
|
if new_i_ele< 2:
|
|
1422
|
if new_i_ele< 2:
|
|
|
1418
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
1423
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
1419
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
1424
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
1420
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
1425
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
|
1421
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
1426
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
|
1422
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
1427
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
|
1423
|
data_ele = self.res_ele
|
|
1428
|
data_ele = self.res_ele
|
|
|
1424
|
data_weather = self.res_weather[val_ch]
|
|
1429
|
data_weather = self.res_weather[val_ch]
|
|
|
1425
|
|
|
1430
|
|
|
|
1426
|
elif tipo_case==1 : #BAJADA
|
|
1431
|
elif tipo_case==1 : #BAJADA
|
|
|
1427
|
data_ele = data_ele[::-1] # reversa
|
|
1432
|
data_ele = data_ele[::-1] # reversa
|
|
|
1428
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
1433
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
1429
|
data_weather = data_weather[::-1,:]# reversa
|
|
1434
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
1430
|
vec= numpy.where(data_ele<ang_max)
|
|
1435
|
vec= numpy.where(data_ele<ang_max)
|
|
|
1431
|
data_ele = data_ele[vec]
|
|
1436
|
data_ele = data_ele[vec]
|
|
|
1432
|
data_ele_old = data_ele_old[vec]
|
|
1437
|
data_ele_old = data_ele_old[vec]
|
|
|
1433
|
data_weather = data_weather[vec[0]]
|
|
1438
|
data_weather = data_weather[vec[0]]
|
|
|
1434
|
vec2= numpy.where(0<data_ele)
|
|
1439
|
vec2= numpy.where(0<data_ele)
|
|
|
1435
|
data_ele = data_ele[vec2]
|
|
1440
|
data_ele = data_ele[vec2]
|
|
|
1436
|
data_ele_old = data_ele_old[vec2]
|
|
1441
|
data_ele_old = data_ele_old[vec2]
|
|
|
1437
|
data_weather = data_weather[vec2[0]]
|
|
1442
|
data_weather = data_weather[vec2[0]]
|
|
|
1438
|
|
|
1443
|
|
|
|
1439
|
|
|
1444
|
|
|
|
1440
|
new_i_ele = int(round(data_ele[0]))
|
|
1445
|
new_i_ele = int(round(data_ele[0]))
|
|
|
1441
|
new_f_ele = int(round(data_ele[-1]))
|
|
1446
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
1442
|
#print(data_ele)
|
|
1447
|
#print(data_ele)
|
|
|
1443
|
#print(ang_max)
|
|
1448
|
#print(ang_max)
|
|
|
1444
|
#print(data_ele_old)
|
|
1449
|
#print(data_ele_old)
|
|
|
1445
|
if new_i_ele <= 1:
|
|
1450
|
if new_i_ele <= 1:
|
|
|
1446
|
new_i_ele = 1
|
|
1451
|
new_i_ele = 1
|
|
|
1447
|
if round(data_ele[-1])>=ang_max-1:
|
|
1452
|
if round(data_ele[-1])>=ang_max-1:
|
|
|
1448
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
1453
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
1449
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
1454
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
1450
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
1455
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
|
1451
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
1456
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
|
1452
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
1457
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
|
1453
|
data_ele = self.res_ele
|
|
1458
|
data_ele = self.res_ele
|
|
|
1454
|
data_weather = self.res_weather[val_ch]
|
|
1459
|
data_weather = self.res_weather[val_ch]
|
|
|
1455
|
|
|
1460
|
|
|
|
1456
|
elif tipo_case==2: #bajada
|
|
1461
|
elif tipo_case==2: #bajada
|
|
|
1457
|
vec = numpy.where(data_ele<ang_max)
|
|
1462
|
vec = numpy.where(data_ele<ang_max)
|
|
|
1458
|
data_ele = data_ele[vec]
|
|
1463
|
data_ele = data_ele[vec]
|
|
|
1459
|
data_weather= data_weather[vec[0]]
|
|
1464
|
data_weather= data_weather[vec[0]]
|
|
|
1460
|
|
|
1465
|
|
|
|
1461
|
len_vec = len(vec)
|
|
1466
|
len_vec = len(vec)
|
|
|
1462
|
data_ele_new = data_ele[::-1] # reversa
|
|
1467
|
data_ele_new = data_ele[::-1] # reversa
|
|
|
1463
|
data_weather = data_weather[::-1,:]
|
|
1468
|
data_weather = data_weather[::-1,:]
|
|
|
1464
|
new_i_ele = int(data_ele_new[0])
|
|
1469
|
new_i_ele = int(data_ele_new[0])
|
|
|
1465
|
new_f_ele = int(data_ele_new[-1])
|
|
1470
|
new_f_ele = int(data_ele_new[-1])
|
|
|
1466
|
|
|
1471
|
|
|
|
1467
|
n1= new_i_ele- ang_min
|
|
1472
|
n1= new_i_ele- ang_min
|
|
|
1468
|
n2= ang_max - new_f_ele-1
|
|
1473
|
n2= ang_max - new_f_ele-1
|
|
|
1469
|
if n1>0:
|
|
1474
|
if n1>0:
|
|
|
1470
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
1475
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
1471
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1476
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1472
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1477
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1473
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
1478
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
1474
|
if n2>0:
|
|
1479
|
if n2>0:
|
|
|
1475
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
1480
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
1476
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1481
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1477
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1482
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1478
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1483
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1479
|
|
|
1484
|
|
|
|
1480
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
1485
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
1481
|
self.res_ele = data_ele
|
|
1486
|
self.res_ele = data_ele
|
|
|
1482
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1487
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1483
|
data_ele = self.res_ele
|
|
1488
|
data_ele = self.res_ele
|
|
|
1484
|
data_weather = self.res_weather[val_ch]
|
|
1489
|
data_weather = self.res_weather[val_ch]
|
|
|
1485
|
|
|
1490
|
|
|
|
1486
|
elif tipo_case==3:#subida
|
|
1491
|
elif tipo_case==3:#subida
|
|
|
1487
|
vec = numpy.where(0<data_ele)
|
|
1492
|
vec = numpy.where(0<data_ele)
|
|
|
1488
|
data_ele= data_ele[vec]
|
|
1493
|
data_ele= data_ele[vec]
|
|
|
1489
|
data_ele_new = data_ele
|
|
1494
|
data_ele_new = data_ele
|
|
|
1490
|
data_ele_old= data_ele_old[vec]
|
|
1495
|
data_ele_old= data_ele_old[vec]
|
|
|
1491
|
data_weather= data_weather[vec[0]]
|
|
1496
|
data_weather= data_weather[vec[0]]
|
|
|
1492
|
pos_ini = numpy.argmin(data_ele)
|
|
1497
|
pos_ini = numpy.argmin(data_ele)
|
|
|
1493
|
if pos_ini>0:
|
|
1498
|
if pos_ini>0:
|
|
|
1494
|
len_vec= len(data_ele)
|
|
1499
|
len_vec= len(data_ele)
|
|
|
1495
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
1500
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
|
1496
|
#print(vec3)
|
|
1501
|
#print(vec3)
|
|
|
1497
|
data_ele= data_ele[vec3]
|
|
1502
|
data_ele= data_ele[vec3]
|
|
|
1498
|
data_ele_new = data_ele
|
|
1503
|
data_ele_new = data_ele
|
|
|
1499
|
data_ele_old= data_ele_old[vec3]
|
|
1504
|
data_ele_old= data_ele_old[vec3]
|
|
|
1500
|
data_weather= data_weather[vec3]
|
|
1505
|
data_weather= data_weather[vec3]
|
|
|
1501
|
|
|
1506
|
|
|
|
1502
|
new_i_ele = int(data_ele_new[0])
|
|
1507
|
new_i_ele = int(data_ele_new[0])
|
|
|
1503
|
new_f_ele = int(data_ele_new[-1])
|
|
1508
|
new_f_ele = int(data_ele_new[-1])
|
|
|
1504
|
n1= new_i_ele- ang_min
|
|
1509
|
n1= new_i_ele- ang_min
|
|
|
1505
|
n2= ang_max - new_f_ele-1
|
|
1510
|
n2= ang_max - new_f_ele-1
|
|
|
1506
|
if n1>0:
|
|
1511
|
if n1>0:
|
|
|
1507
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
1512
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
1508
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1513
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1509
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1514
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1510
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
1515
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
1511
|
if n2>0:
|
|
1516
|
if n2>0:
|
|
|
1512
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
1517
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
1513
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1518
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1514
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1519
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1515
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1520
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1516
|
|
|
1521
|
|
|
|
1517
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
1522
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
1518
|
self.res_ele = data_ele
|
|
1523
|
self.res_ele = data_ele
|
|
|
1519
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1524
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1520
|
data_ele = self.res_ele
|
|
1525
|
data_ele = self.res_ele
|
|
|
1521
|
data_weather = self.res_weather[val_ch]
|
|
1526
|
data_weather = self.res_weather[val_ch]
|
|
|
1522
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
1527
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
|
1523
|
return data_weather,data_ele
|
|
1528
|
return data_weather,data_ele
|
|
|
1524
|
|
|
1529
|
|
|
|
1525
|
|
|
1530
|
|
|
|
1526
|
def plot(self):
|
|
1531
|
def plot(self):
|
|
|
1527
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
1532
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
|
1528
|
data = self.data[-1]
|
|
1533
|
data = self.data[-1]
|
|
|
1529
|
r = self.data.yrange
|
|
1534
|
r = self.data.yrange
|
|
|
1530
|
delta_height = r[1]-r[0]
|
|
1535
|
delta_height = r[1]-r[0]
|
|
|
1531
|
r_mask = numpy.where(r>=0)[0]
|
|
1536
|
r_mask = numpy.where(r>=0)[0]
|
|
|
1532
|
##print("delta_height",delta_height)
|
|
1537
|
##print("delta_height",delta_height)
|
|
|
1533
|
#print("r_mask",r_mask,len(r_mask))
|
|
1538
|
#print("r_mask",r_mask,len(r_mask))
|
|
|
1534
|
r = numpy.arange(len(r_mask))*delta_height
|
|
1539
|
r = numpy.arange(len(r_mask))*delta_height
|
|
|
1535
|
self.y = 2*r
|
|
1540
|
self.y = 2*r
|
|
|
1536
|
res = 1
|
|
1541
|
res = 1
|
|
|
1537
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
1542
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
|
1538
|
ang_max = self.ang_max
|
|
1543
|
ang_max = self.ang_max
|
|
|
1539
|
ang_min = self.ang_min
|
|
1544
|
ang_min = self.ang_min
|
|
|
1540
|
var_ang =ang_max - ang_min
|
|
1545
|
var_ang =ang_max - ang_min
|
|
|
1541
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
1546
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
|
1542
|
###print("step",step)
|
|
1547
|
###print("step",step)
|
|
|
1543
|
#--------------------------------------------------------
|
|
1548
|
#--------------------------------------------------------
|
|
|
1544
|
##print('weather',data['weather'].shape)
|
|
1549
|
##print('weather',data['weather'].shape)
|
|
|
1545
|
##print('ele',data['ele'].shape)
|
|
1550
|
##print('ele',data['ele'].shape)
|
|
|
1546
|
|
|
1551
|
|
|
|
1547
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
1552
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
1548
|
###self.res_azi = numpy.mean(data['azi'])
|
|
1553
|
###self.res_azi = numpy.mean(data['azi'])
|
|
|
1549
|
###print("self.res_ele",self.res_ele)
|
|
1554
|
###print("self.res_ele",self.res_ele)
|
|
|
1550
|
plt.clf()
|
|
1555
|
plt.clf()
|
|
|
1551
|
subplots = [121, 122]
|
|
1556
|
subplots = [121, 122]
|
|
|
1552
|
try:
|
|
1557
|
try:
|
|
|
1553
|
if self.data[-2]['ele'].max()<data['ele'].max():
|
|
1558
|
if self.data[-2]['ele'].max()<data['ele'].max():
|
|
|
1554
|
self.ini=0
|
|
1559
|
self.ini=0
|
|
|
1555
|
except:
|
|
1560
|
except:
|
|
|
1556
|
pass
|
|
1561
|
pass
|
|
|
1557
|
if self.ini==0:
|
|
1562
|
if self.ini==0:
|
|
|
1558
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
1563
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
|
1559
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
1564
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
|
1560
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
1565
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
|
1561
|
|
|
1566
|
|
|
|
1562
|
for i,ax in enumerate(self.axes):
|
|
1567
|
for i,ax in enumerate(self.axes):
|
|
|
1563
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag'])
|
|
1568
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag'])
|
|
|
1564
|
self.res_azi = numpy.mean(data['azi'])
|
|
1569
|
self.res_azi = numpy.mean(data['azi'])
|
|
|
1565
|
|
|
1570
|
|
|
|
1566
|
if ax.firsttime:
|
|
1571
|
if ax.firsttime:
|
|
|
1567
|
#plt.clf()
|
|
1572
|
#plt.clf()
|
|
|
1568
|
print("Frist Plot")
|
|
1573
|
print("Frist Plot")
|
|
|
1569
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1574
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
1570
|
#fig=self.figures[0]
|
|
1575
|
#fig=self.figures[0]
|
|
|
1571
|
else:
|
|
1576
|
else:
|
|
|
1572
|
#plt.clf()
|
|
1577
|
#plt.clf()
|
|
|
1573
|
print("ELSE PLOT")
|
|
1578
|
print("ELSE PLOT")
|
|
|
1574
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1579
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
1575
|
caax = cgax.parasites[0]
|
|
1580
|
caax = cgax.parasites[0]
|
|
|
1576
|
paax = cgax.parasites[1]
|
|
1581
|
paax = cgax.parasites[1]
|
|
|
1577
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
1582
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
|
1578
|
caax.set_xlabel('x_range [km]')
|
|
1583
|
caax.set_xlabel('x_range [km]')
|
|
|
1579
|
caax.set_ylabel('y_range [km]')
|
|
1584
|
caax.set_ylabel('y_range [km]')
|
|
|
1580
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
1585
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
1581
|
print("***************************self.ini****************************",self.ini)
|
|
1586
|
print("***************************self.ini****************************",self.ini)
|
|
|
1582
|
self.ini= self.ini+1
|
|
1587
|
self.ini= self.ini+1
|
|
|
1583
|
|
|
1588
|
|
|
|
1584
|
class WeatherRHI_vRF_Plot(Plot):
|
|
1589
|
class WeatherRHI_vRF_Plot(Plot):
|
|
|
1585
|
CODE = 'weather'
|
|
1590
|
CODE = 'weather'
|
|
|
1586
|
plot_name = 'weather'
|
|
1591
|
plot_name = 'weather'
|
|
|
1587
|
plot_type = 'rhistyle'
|
|
1592
|
plot_type = 'rhistyle'
|
|
|
1588
|
buffering = False
|
|
1593
|
buffering = False
|
|
|
1589
|
data_ele_tmp = None
|
|
1594
|
data_ele_tmp = None
|
|
|
1590
|
|
|
1595
|
|
|
|
1591
|
def setup(self):
|
|
1596
|
def setup(self):
|
|
|
1592
|
print("********************")
|
|
1597
|
print("********************")
|
|
|
1593
|
print("********************")
|
|
1598
|
print("********************")
|
|
|
1594
|
print("********************")
|
|
1599
|
print("********************")
|
|
|
1595
|
print("SETUP WEATHER PLOT")
|
|
1600
|
print("SETUP WEATHER PLOT")
|
|
|
1596
|
self.ncols = 1
|
|
1601
|
self.ncols = 1
|
|
|
1597
|
self.nrows = 1
|
|
1602
|
self.nrows = 1
|
|
|
1598
|
self.nplots= 1
|
|
1603
|
self.nplots= 1
|
|
|
1599
|
self.ylabel= 'Range [Km]'
|
|
1604
|
self.ylabel= 'Range [Km]'
|
|
|
1600
|
self.titles= ['Weather']
|
|
1605
|
self.titles= ['Weather']
|
|
|
1601
|
if self.channels is not None:
|
|
1606
|
if self.channels is not None:
|
|
|
1602
|
self.nplots = len(self.channels)
|
|
1607
|
self.nplots = len(self.channels)
|
|
|
1603
|
self.nrows = len(self.channels)
|
|
1608
|
self.nrows = len(self.channels)
|
|
|
1604
|
else:
|
|
1609
|
else:
|
|
|
1605
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
1610
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
|
1606
|
self.nrows = self.nplots
|
|
1611
|
self.nrows = self.nplots
|
|
|
1607
|
self.channels = list(range(self.nplots))
|
|
1612
|
self.channels = list(range(self.nplots))
|
|
|
1608
|
print("channels",self.channels)
|
|
1613
|
print("channels",self.channels)
|
|
|
1609
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
1614
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
|
1610
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
1615
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
|
1611
|
print("self.titles",self.titles)
|
|
1616
|
print("self.titles",self.titles)
|
|
|
1612
|
self.colorbar=False
|
|
1617
|
self.colorbar=False
|
|
|
1613
|
self.width =8
|
|
1618
|
self.width =8
|
|
|
1614
|
self.height =8
|
|
1619
|
self.height =8
|
|
|
1615
|
self.ini =0
|
|
1620
|
self.ini =0
|
|
|
1616
|
self.len_azi =0
|
|
1621
|
self.len_azi =0
|
|
|
1617
|
self.buffer_ini = None
|
|
1622
|
self.buffer_ini = None
|
|
|
1618
|
self.buffer_ele = None
|
|
1623
|
self.buffer_ele = None
|
|
|
1619
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
1624
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
|
1620
|
self.flag =0
|
|
1625
|
self.flag =0
|
|
|
1621
|
self.indicador= 0
|
|
1626
|
self.indicador= 0
|
|
|
1622
|
self.last_data_ele = None
|
|
1627
|
self.last_data_ele = None
|
|
|
1623
|
self.val_mean = None
|
|
1628
|
self.val_mean = None
|
|
|
1624
|
|
|
1629
|
|
|
|
1625
|
def update(self, dataOut):
|
|
1630
|
def update(self, dataOut):
|
|
|
1626
|
|
|
1631
|
|
|
|
1627
|
data = {}
|
|
1632
|
data = {}
|
|
|
1628
|
meta = {}
|
|
1633
|
meta = {}
|
|
|
1629
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
1634
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
|
1630
|
factor = 1
|
|
1635
|
factor = 1
|
|
|
1631
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
1636
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
|
1632
|
factor = dataOut.normFactor
|
|
1637
|
factor = dataOut.normFactor
|
|
|
1633
|
print("dataOut",dataOut.data_360.shape)
|
|
1638
|
print("dataOut",dataOut.data_360.shape)
|
|
|
1634
|
#
|
|
1639
|
#
|
|
|
1635
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
1640
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
|
1636
|
#
|
|
1641
|
#
|
|
|
1637
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
1642
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
|
1638
|
data['azi'] = dataOut.data_azi
|
|
1643
|
data['azi'] = dataOut.data_azi
|
|
|
1639
|
data['ele'] = dataOut.data_ele
|
|
1644
|
data['ele'] = dataOut.data_ele
|
|
|
1640
|
data['case_flag'] = dataOut.case_flag
|
|
1645
|
data['case_flag'] = dataOut.case_flag
|
|
|
1641
|
#print("UPDATE")
|
|
1646
|
#print("UPDATE")
|
|
|
1642
|
#print("data[weather]",data['weather'].shape)
|
|
1647
|
#print("data[weather]",data['weather'].shape)
|
|
|
1643
|
#print("data[azi]",data['azi'])
|
|
1648
|
#print("data[azi]",data['azi'])
|
|
|
1644
|
return data, meta
|
|
1649
|
return data, meta
|
|
|
1645
|
|
|
1650
|
|
|
|
1646
|
def get2List(self,angulos):
|
|
1651
|
def get2List(self,angulos):
|
|
|
1647
|
list1=[]
|
|
1652
|
list1=[]
|
|
|
1648
|
list2=[]
|
|
1653
|
list2=[]
|
|
|
1649
|
#print(angulos)
|
|
1654
|
#print(angulos)
|
|
|
1650
|
#exit(1)
|
|
1655
|
#exit(1)
|
|
|
1651
|
for i in reversed(range(len(angulos))):
|
|
1656
|
for i in reversed(range(len(angulos))):
|
|
|
1652
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
1657
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
|
1653
|
diff_ = angulos[i]-angulos[i-1]
|
|
1658
|
diff_ = angulos[i]-angulos[i-1]
|
|
|
1654
|
if abs(diff_) >1.5:
|
|
1659
|
if abs(diff_) >1.5:
|
|
|
1655
|
list1.append(i-1)
|
|
1660
|
list1.append(i-1)
|
|
|
1656
|
list2.append(diff_)
|
|
1661
|
list2.append(diff_)
|
|
|
1657
|
return list(reversed(list1)),list(reversed(list2))
|
|
1662
|
return list(reversed(list1)),list(reversed(list2))
|
|
|
1658
|
|
|
1663
|
|
|
|
1659
|
def fixData90(self,list_,ang_):
|
|
1664
|
def fixData90(self,list_,ang_):
|
|
|
1660
|
if list_[0]==-1:
|
|
1665
|
if list_[0]==-1:
|
|
|
1661
|
vec = numpy.where(ang_<ang_[0])
|
|
1666
|
vec = numpy.where(ang_<ang_[0])
|
|
|
1662
|
ang_[vec] = ang_[vec]+90
|
|
1667
|
ang_[vec] = ang_[vec]+90
|
|
|
1663
|
return ang_
|
|
1668
|
return ang_
|
|
|
1664
|
return ang_
|
|
1669
|
return ang_
|
|
|
1665
|
|
|
1670
|
|
|
|
1666
|
def fixData90HL(self,angulos):
|
|
1671
|
def fixData90HL(self,angulos):
|
|
|
1667
|
vec = numpy.where(angulos>=90)
|
|
1672
|
vec = numpy.where(angulos>=90)
|
|
|
1668
|
angulos[vec]=angulos[vec]-90
|
|
1673
|
angulos[vec]=angulos[vec]-90
|
|
|
1669
|
return angulos
|
|
1674
|
return angulos
|
|
|
1670
|
|
|
1675
|
|
|
|
1671
|
|
|
1676
|
|
|
|
1672
|
def search_pos(self,pos,list_):
|
|
1677
|
def search_pos(self,pos,list_):
|
|
|
1673
|
for i in range(len(list_)):
|
|
1678
|
for i in range(len(list_)):
|
|
|
1674
|
if pos == list_[i]:
|
|
1679
|
if pos == list_[i]:
|
|
|
1675
|
return True,i
|
|
1680
|
return True,i
|
|
|
1676
|
i=None
|
|
1681
|
i=None
|
|
|
1677
|
return False,i
|
|
1682
|
return False,i
|
|
|
1678
|
|
|
1683
|
|
|
|
1679
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
1684
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
|
1680
|
size = len(ang_)
|
|
1685
|
size = len(ang_)
|
|
|
1681
|
size2 = 0
|
|
1686
|
size2 = 0
|
|
|
1682
|
for i in range(len(list2_)):
|
|
1687
|
for i in range(len(list2_)):
|
|
|
1683
|
size2=size2+round(abs(list2_[i]))-1
|
|
1688
|
size2=size2+round(abs(list2_[i]))-1
|
|
|
1684
|
new_size= size+size2
|
|
1689
|
new_size= size+size2
|
|
|
1685
|
ang_new = numpy.zeros(new_size)
|
|
1690
|
ang_new = numpy.zeros(new_size)
|
|
|
1686
|
ang_new2 = numpy.zeros(new_size)
|
|
1691
|
ang_new2 = numpy.zeros(new_size)
|
|
|
1687
|
|
|
1692
|
|
|
|
1688
|
tmp = 0
|
|
1693
|
tmp = 0
|
|
|
1689
|
c = 0
|
|
1694
|
c = 0
|
|
|
1690
|
for i in range(len(ang_)):
|
|
1695
|
for i in range(len(ang_)):
|
|
|
1691
|
ang_new[tmp +c] = ang_[i]
|
|
1696
|
ang_new[tmp +c] = ang_[i]
|
|
|
1692
|
ang_new2[tmp+c] = ang_[i]
|
|
1697
|
ang_new2[tmp+c] = ang_[i]
|
|
|
1693
|
condition , value = self.search_pos(i,list1_)
|
|
1698
|
condition , value = self.search_pos(i,list1_)
|
|
|
1694
|
if condition:
|
|
1699
|
if condition:
|
|
|
1695
|
pos = tmp + c + 1
|
|
1700
|
pos = tmp + c + 1
|
|
|
1696
|
for k in range(round(abs(list2_[value]))-1):
|
|
1701
|
for k in range(round(abs(list2_[value]))-1):
|
|
|
1697
|
if tipo_case==0 or tipo_case==3:#subida
|
|
1702
|
if tipo_case==0 or tipo_case==3:#subida
|
|
|
1698
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
1703
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
|
1699
|
ang_new2[pos+k] = numpy.nan
|
|
1704
|
ang_new2[pos+k] = numpy.nan
|
|
|
1700
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
1705
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
|
1701
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
1706
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
|
1702
|
ang_new2[pos+k] = numpy.nan
|
|
1707
|
ang_new2[pos+k] = numpy.nan
|
|
|
1703
|
|
|
1708
|
|
|
|
1704
|
tmp = pos +k
|
|
1709
|
tmp = pos +k
|
|
|
1705
|
c = 0
|
|
1710
|
c = 0
|
|
|
1706
|
c=c+1
|
|
1711
|
c=c+1
|
|
|
1707
|
return ang_new,ang_new2
|
|
1712
|
return ang_new,ang_new2
|
|
|
1708
|
|
|
1713
|
|
|
|
1709
|
def globalCheckPED(self,angulos,tipo_case):
|
|
1714
|
def globalCheckPED(self,angulos,tipo_case):
|
|
|
1710
|
l1,l2 = self.get2List(angulos)
|
|
1715
|
l1,l2 = self.get2List(angulos)
|
|
|
1711
|
print("l1",l1)
|
|
1716
|
print("l1",l1)
|
|
|
1712
|
print("l2",l2)
|
|
1717
|
print("l2",l2)
|
|
|
1713
|
if len(l1)>0:
|
|
1718
|
if len(l1)>0:
|
|
|
1714
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
1719
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
|
1715
|
#l1,l2 = self.get2List(angulos2)
|
|
1720
|
#l1,l2 = self.get2List(angulos2)
|
|
|
1716
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
1721
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
|
1717
|
#ang1_ = self.fixData90HL(ang1_)
|
|
1722
|
#ang1_ = self.fixData90HL(ang1_)
|
|
|
1718
|
#ang2_ = self.fixData90HL(ang2_)
|
|
1723
|
#ang2_ = self.fixData90HL(ang2_)
|
|
|
1719
|
else:
|
|
1724
|
else:
|
|
|
1720
|
ang1_= angulos
|
|
1725
|
ang1_= angulos
|
|
|
1721
|
ang2_= angulos
|
|
1726
|
ang2_= angulos
|
|
|
1722
|
return ang1_,ang2_
|
|
1727
|
return ang1_,ang2_
|
|
|
1723
|
|
|
1728
|
|
|
|
1724
|
|
|
1729
|
|
|
|
1725
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
1730
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
|
1726
|
data= data_ele
|
|
1731
|
data= data_ele
|
|
|
1727
|
data_T= data_weather
|
|
1732
|
data_T= data_weather
|
|
|
1728
|
#print(data.shape[0])
|
|
1733
|
#print(data.shape[0])
|
|
|
1729
|
#print(data_T.shape[0])
|
|
1734
|
#print(data_T.shape[0])
|
|
|
1730
|
#exit(1)
|
|
1735
|
#exit(1)
|
|
|
1731
|
if data.shape[0]> data_T.shape[0]:
|
|
1736
|
if data.shape[0]> data_T.shape[0]:
|
|
|
1732
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
1737
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
|
1733
|
c = 0
|
|
1738
|
c = 0
|
|
|
1734
|
for i in range(len(data)):
|
|
1739
|
for i in range(len(data)):
|
|
|
1735
|
if numpy.isnan(data[i]):
|
|
1740
|
if numpy.isnan(data[i]):
|
|
|
1736
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
1741
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
1737
|
else:
|
|
1742
|
else:
|
|
|
1738
|
data_N[i,:]=data_T[c,:]
|
|
1743
|
data_N[i,:]=data_T[c,:]
|
|
|
1739
|
c=c+1
|
|
1744
|
c=c+1
|
|
|
1740
|
return data_N
|
|
1745
|
return data_N
|
|
|
1741
|
else:
|
|
1746
|
else:
|
|
|
1742
|
for i in range(len(data)):
|
|
1747
|
for i in range(len(data)):
|
|
|
1743
|
if numpy.isnan(data[i]):
|
|
1748
|
if numpy.isnan(data[i]):
|
|
|
1744
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
1749
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
1745
|
return data_T
|
|
1750
|
return data_T
|
|
|
1746
|
|
|
1751
|
|
|
|
1747
|
|
|
1752
|
|
|
|
1748
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
1753
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
|
1749
|
ang_max= ang_max
|
|
1754
|
ang_max= ang_max
|
|
|
1750
|
ang_min= ang_min
|
|
1755
|
ang_min= ang_min
|
|
|
1751
|
data_weather=data_weather
|
|
1756
|
data_weather=data_weather
|
|
|
1752
|
val_ch=val_ch
|
|
1757
|
val_ch=val_ch
|
|
|
1753
|
##print("*********************DATA WEATHER**************************************")
|
|
1758
|
##print("*********************DATA WEATHER**************************************")
|
|
|
1754
|
##print(data_weather)
|
|
1759
|
##print(data_weather)
|
|
|
1755
|
|
|
1760
|
|
|
|
1756
|
'''
|
|
1761
|
'''
|
|
|
1757
|
print("**********************************************")
|
|
1762
|
print("**********************************************")
|
|
|
1758
|
print("**********************************************")
|
|
1763
|
print("**********************************************")
|
|
|
1759
|
print("***************ini**************")
|
|
1764
|
print("***************ini**************")
|
|
|
1760
|
print("**********************************************")
|
|
1765
|
print("**********************************************")
|
|
|
1761
|
print("**********************************************")
|
|
1766
|
print("**********************************************")
|
|
|
1762
|
'''
|
|
1767
|
'''
|
|
|
1763
|
#print("data_ele",data_ele)
|
|
1768
|
#print("data_ele",data_ele)
|
|
|
1764
|
#----------------------------------------------------------
|
|
1769
|
#----------------------------------------------------------
|
|
|
1765
|
|
|
1770
|
|
|
|
1766
|
#exit(1)
|
|
1771
|
#exit(1)
|
|
|
1767
|
tipo_case = case_flag[-1]
|
|
1772
|
tipo_case = case_flag[-1]
|
|
|
1768
|
print("tipo_case",tipo_case)
|
|
1773
|
print("tipo_case",tipo_case)
|
|
|
1769
|
#--------------------- new -------------------------
|
|
1774
|
#--------------------- new -------------------------
|
|
|
1770
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
1775
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
|
1771
|
|
|
1776
|
|
|
|
1772
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
1777
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
1773
|
|
|
1778
|
|
|
|
1774
|
vec = numpy.where(data_ele<ang_max)
|
|
1779
|
vec = numpy.where(data_ele<ang_max)
|
|
|
1775
|
data_ele = data_ele[vec]
|
|
1780
|
data_ele = data_ele[vec]
|
|
|
1776
|
data_weather= data_weather[vec[0]]
|
|
1781
|
data_weather= data_weather[vec[0]]
|
|
|
1777
|
|
|
1782
|
|
|
|
1778
|
len_vec = len(vec)
|
|
1783
|
len_vec = len(vec)
|
|
|
1779
|
data_ele_new = data_ele[::-1] # reversa
|
|
1784
|
data_ele_new = data_ele[::-1] # reversa
|
|
|
1780
|
data_weather = data_weather[::-1,:]
|
|
1785
|
data_weather = data_weather[::-1,:]
|
|
|
1781
|
new_i_ele = int(data_ele_new[0])
|
|
1786
|
new_i_ele = int(data_ele_new[0])
|
|
|
1782
|
new_f_ele = int(data_ele_new[-1])
|
|
1787
|
new_f_ele = int(data_ele_new[-1])
|
|
|
1783
|
|
|
1788
|
|
|
|
1784
|
n1= new_i_ele- ang_min
|
|
1789
|
n1= new_i_ele- ang_min
|
|
|
1785
|
n2= ang_max - new_f_ele-1
|
|
1790
|
n2= ang_max - new_f_ele-1
|
|
|
1786
|
if n1>0:
|
|
1791
|
if n1>0:
|
|
|
1787
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
1792
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
1788
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
1793
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
1789
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
1794
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
1790
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
1795
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
1791
|
if n2>0:
|
|
1796
|
if n2>0:
|
|
|
1792
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
1797
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
1793
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
1798
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
1794
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
1799
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
1795
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
1800
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
1796
|
|
|
1801
|
|
|
|
1797
|
|
|
1802
|
|
|
|
1798
|
print("ele shape",data_ele.shape)
|
|
1803
|
print("ele shape",data_ele.shape)
|
|
|
1799
|
print(data_ele)
|
|
1804
|
print(data_ele)
|
|
|
1800
|
|
|
1805
|
|
|
|
1801
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
1806
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
|
1802
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
1807
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
|
1803
|
self.val_mean = val_mean
|
|
1808
|
self.val_mean = val_mean
|
|
|
1804
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
1809
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
1805
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
1810
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
|
1806
|
|
|
1811
|
|
|
|
1807
|
|
|
1812
|
|
|
|
1808
|
print("data_weather shape",data_weather.shape)
|
|
1813
|
print("data_weather shape",data_weather.shape)
|
|
|
1809
|
print(data_weather)
|
|
1814
|
print(data_weather)
|
|
|
1810
|
#exit(1)
|
|
1815
|
#exit(1)
|
|
|
1811
|
return data_weather,data_ele
|
|
1816
|
return data_weather,data_ele
|
|
|
1812
|
|
|
1817
|
|
|
|
1813
|
|
|
1818
|
|
|
|
1814
|
def plot(self):
|
|
1819
|
def plot(self):
|
|
|
1815
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
1820
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
|
1816
|
data = self.data[-1]
|
|
1821
|
data = self.data[-1]
|
|
|
1817
|
r = self.data.yrange
|
|
1822
|
r = self.data.yrange
|
|
|
1818
|
delta_height = r[1]-r[0]
|
|
1823
|
delta_height = r[1]-r[0]
|
|
|
1819
|
r_mask = numpy.where(r>=0)[0]
|
|
1824
|
r_mask = numpy.where(r>=0)[0]
|
|
|
1820
|
##print("delta_height",delta_height)
|
|
1825
|
##print("delta_height",delta_height)
|
|
|
1821
|
#print("r_mask",r_mask,len(r_mask))
|
|
1826
|
#print("r_mask",r_mask,len(r_mask))
|
|
|
1822
|
r = numpy.arange(len(r_mask))*delta_height
|
|
1827
|
r = numpy.arange(len(r_mask))*delta_height
|
|
|
1823
|
self.y = 2*r
|
|
1828
|
self.y = 2*r
|
|
|
1824
|
res = 1
|
|
1829
|
res = 1
|
|
|
1825
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
1830
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
|
1826
|
ang_max = self.ang_max
|
|
1831
|
ang_max = self.ang_max
|
|
|
1827
|
ang_min = self.ang_min
|
|
1832
|
ang_min = self.ang_min
|
|
|
1828
|
var_ang =ang_max - ang_min
|
|
1833
|
var_ang =ang_max - ang_min
|
|
|
1829
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
1834
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
|
1830
|
###print("step",step)
|
|
1835
|
###print("step",step)
|
|
|
1831
|
#--------------------------------------------------------
|
|
1836
|
#--------------------------------------------------------
|
|
|
1832
|
##print('weather',data['weather'].shape)
|
|
1837
|
##print('weather',data['weather'].shape)
|
|
|
1833
|
##print('ele',data['ele'].shape)
|
|
1838
|
##print('ele',data['ele'].shape)
|
|
|
1834
|
|
|
1839
|
|
|
|
1835
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
1840
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
1836
|
###self.res_azi = numpy.mean(data['azi'])
|
|
1841
|
###self.res_azi = numpy.mean(data['azi'])
|
|
|
1837
|
###print("self.res_ele",self.res_ele)
|
|
1842
|
###print("self.res_ele",self.res_ele)
|
|
|
1838
|
plt.clf()
|
|
1843
|
plt.clf()
|
|
|
1839
|
subplots = [121, 122]
|
|
1844
|
subplots = [121, 122]
|
|
|
1840
|
if self.ini==0:
|
|
1845
|
if self.ini==0:
|
|
|
1841
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
1846
|
self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
|
|
|
1842
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
1847
|
self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
|
1843
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
1848
|
print("SHAPE",self.data_ele_tmp.shape)
|
|
|
1844
|
|
|
1849
|
|
|
|
1845
|
for i,ax in enumerate(self.axes):
|
|
1850
|
for i,ax in enumerate(self.axes):
|
|
|
1846
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag'])
|
|
1851
|
self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag'])
|
|
|
1847
|
self.res_azi = numpy.mean(data['azi'])
|
|
1852
|
self.res_azi = numpy.mean(data['azi'])
|
|
|
1848
|
|
|
1853
|
|
|
|
1849
|
print(self.res_ele)
|
|
1854
|
print(self.res_ele)
|
|
|
1850
|
#exit(1)
|
|
1855
|
#exit(1)
|
|
|
1851
|
if ax.firsttime:
|
|
1856
|
if ax.firsttime:
|
|
|
1852
|
#plt.clf()
|
|
1857
|
#plt.clf()
|
|
|
1853
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1858
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
1854
|
#fig=self.figures[0]
|
|
1859
|
#fig=self.figures[0]
|
|
|
1855
|
else:
|
|
1860
|
else:
|
|
|
1856
|
|
|
1861
|
|
|
|
1857
|
#plt.clf()
|
|
1862
|
#plt.clf()
|
|
|
1858
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
1863
|
cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
1859
|
caax = cgax.parasites[0]
|
|
1864
|
caax = cgax.parasites[0]
|
|
|
1860
|
paax = cgax.parasites[1]
|
|
1865
|
paax = cgax.parasites[1]
|
|
|
1861
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
1866
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
|
1862
|
caax.set_xlabel('x_range [km]')
|
|
1867
|
caax.set_xlabel('x_range [km]')
|
|
|
1863
|
caax.set_ylabel('y_range [km]')
|
|
1868
|
caax.set_ylabel('y_range [km]')
|
|
|
1864
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
1869
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
1865
|
print("***************************self.ini****************************",self.ini)
|
|
1870
|
print("***************************self.ini****************************",self.ini)
|
|
|
1866
|
self.ini= self.ini+1
|
|
1871
|
self.ini= self.ini+1
|
|
|
1867
|
|
|
1872
|
|
|
|
1868
|
class WeatherRHI_vRF3_Plot(Plot):
|
|
1873
|
class WeatherRHI_vRF3_Plot(Plot):
|
|
|
1869
|
CODE = 'weather'
|
|
1874
|
CODE = 'weather'
|
|
|
1870
|
plot_name = 'weather'
|
|
1875
|
plot_name = 'weather'
|
|
|
1871
|
plot_type = 'rhistyle'
|
|
1876
|
plot_type = 'rhistyle'
|
|
|
1872
|
buffering = False
|
|
1877
|
buffering = False
|
|
|
1873
|
data_ele_tmp = None
|
|
1878
|
data_ele_tmp = None
|
|
|
1874
|
|
|
1879
|
|
|
|
1875
|
def setup(self):
|
|
1880
|
def setup(self):
|
|
|
1876
|
print("********************")
|
|
1881
|
print("********************")
|
|
|
1877
|
print("********************")
|
|
1882
|
print("********************")
|
|
|
1878
|
print("********************")
|
|
1883
|
print("********************")
|
|
|
1879
|
print("SETUP WEATHER PLOT")
|
|
1884
|
print("SETUP WEATHER PLOT")
|
|
|
1880
|
self.ncols = 1
|
|
1885
|
self.ncols = 1
|
|
|
1881
|
self.nrows = 1
|
|
1886
|
self.nrows = 1
|
|
|
1882
|
self.nplots= 1
|
|
1887
|
self.nplots= 1
|
|
|
1883
|
self.ylabel= 'Range [Km]'
|
|
1888
|
self.ylabel= 'Range [Km]'
|
|
|
1884
|
self.titles= ['Weather']
|
|
1889
|
self.titles= ['Weather']
|
|
|
1885
|
if self.channels is not None:
|
|
1890
|
if self.channels is not None:
|
|
|
1886
|
self.nplots = len(self.channels)
|
|
1891
|
self.nplots = len(self.channels)
|
|
|
1887
|
self.nrows = len(self.channels)
|
|
1892
|
self.nrows = len(self.channels)
|
|
|
1888
|
else:
|
|
1893
|
else:
|
|
|
1889
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
1894
|
self.nplots = self.data.shape(self.CODE)[0]
|
|
|
1890
|
self.nrows = self.nplots
|
|
1895
|
self.nrows = self.nplots
|
|
|
1891
|
self.channels = list(range(self.nplots))
|
|
1896
|
self.channels = list(range(self.nplots))
|
|
|
1892
|
print("channels",self.channels)
|
|
1897
|
print("channels",self.channels)
|
|
|
1893
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
1898
|
print("que saldra", self.data.shape(self.CODE)[0])
|
|
|
1894
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
1899
|
self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
|
|
|
1895
|
print("self.titles",self.titles)
|
|
1900
|
print("self.titles",self.titles)
|
|
|
1896
|
self.colorbar=False
|
|
1901
|
self.colorbar=False
|
|
|
1897
|
self.width =8
|
|
1902
|
self.width =8
|
|
|
1898
|
self.height =8
|
|
1903
|
self.height =8
|
|
|
1899
|
self.ini =0
|
|
1904
|
self.ini =0
|
|
|
1900
|
self.len_azi =0
|
|
1905
|
self.len_azi =0
|
|
|
1901
|
self.buffer_ini = None
|
|
1906
|
self.buffer_ini = None
|
|
|
1902
|
self.buffer_ele = None
|
|
1907
|
self.buffer_ele = None
|
|
|
1903
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
1908
|
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
|
|
|
1904
|
self.flag =0
|
|
1909
|
self.flag =0
|
|
|
1905
|
self.indicador= 0
|
|
1910
|
self.indicador= 0
|
|
|
1906
|
self.last_data_ele = None
|
|
1911
|
self.last_data_ele = None
|
|
|
1907
|
self.val_mean = None
|
|
1912
|
self.val_mean = None
|
|
|
1908
|
|
|
1913
|
|
|
|
1909
|
def update(self, dataOut):
|
|
1914
|
def update(self, dataOut):
|
|
|
1910
|
|
|
1915
|
|
|
|
1911
|
data = {}
|
|
1916
|
data = {}
|
|
|
1912
|
meta = {}
|
|
1917
|
meta = {}
|
|
|
1913
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
1918
|
if hasattr(dataOut, 'dataPP_POWER'):
|
|
|
1914
|
factor = 1
|
|
1919
|
factor = 1
|
|
|
1915
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
1920
|
if hasattr(dataOut, 'nFFTPoints'):
|
|
|
1916
|
factor = dataOut.normFactor
|
|
1921
|
factor = dataOut.normFactor
|
|
|
1917
|
print("dataOut",dataOut.data_360.shape)
|
|
1922
|
print("dataOut",dataOut.data_360.shape)
|
|
|
1918
|
#
|
|
1923
|
#
|
|
|
1919
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
1924
|
data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
|
|
|
1920
|
#
|
|
1925
|
#
|
|
|
1921
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
1926
|
#data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
|
|
|
1922
|
data['azi'] = dataOut.data_azi
|
|
1927
|
data['azi'] = dataOut.data_azi
|
|
|
1923
|
data['ele'] = dataOut.data_ele
|
|
1928
|
data['ele'] = dataOut.data_ele
|
|
|
1924
|
#data['case_flag'] = dataOut.case_flag
|
|
1929
|
#data['case_flag'] = dataOut.case_flag
|
|
|
1925
|
#print("UPDATE")
|
|
1930
|
#print("UPDATE")
|
|
|
1926
|
#print("data[weather]",data['weather'].shape)
|
|
1931
|
#print("data[weather]",data['weather'].shape)
|
|
|
1927
|
#print("data[azi]",data['azi'])
|
|
1932
|
#print("data[azi]",data['azi'])
|
|
|
1928
|
return data, meta
|
|
1933
|
return data, meta
|
|
|
1929
|
|
|
1934
|
|
|
|
1930
|
def get2List(self,angulos):
|
|
1935
|
def get2List(self,angulos):
|
|
|
1931
|
list1=[]
|
|
1936
|
list1=[]
|
|
|
1932
|
list2=[]
|
|
1937
|
list2=[]
|
|
|
1933
|
for i in reversed(range(len(angulos))):
|
|
1938
|
for i in reversed(range(len(angulos))):
|
|
|
1934
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
1939
|
if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
|
|
|
1935
|
diff_ = angulos[i]-angulos[i-1]
|
|
1940
|
diff_ = angulos[i]-angulos[i-1]
|
|
|
1936
|
if abs(diff_) >1.5:
|
|
1941
|
if abs(diff_) >1.5:
|
|
|
1937
|
list1.append(i-1)
|
|
1942
|
list1.append(i-1)
|
|
|
1938
|
list2.append(diff_)
|
|
1943
|
list2.append(diff_)
|
|
|
1939
|
return list(reversed(list1)),list(reversed(list2))
|
|
1944
|
return list(reversed(list1)),list(reversed(list2))
|
|
|
1940
|
|
|
1945
|
|
|
|
1941
|
def fixData90(self,list_,ang_):
|
|
1946
|
def fixData90(self,list_,ang_):
|
|
|
1942
|
if list_[0]==-1:
|
|
1947
|
if list_[0]==-1:
|
|
|
1943
|
vec = numpy.where(ang_<ang_[0])
|
|
1948
|
vec = numpy.where(ang_<ang_[0])
|
|
|
1944
|
ang_[vec] = ang_[vec]+90
|
|
1949
|
ang_[vec] = ang_[vec]+90
|
|
|
1945
|
return ang_
|
|
1950
|
return ang_
|
|
|
1946
|
return ang_
|
|
1951
|
return ang_
|
|
|
1947
|
|
|
1952
|
|
|
|
1948
|
def fixData90HL(self,angulos):
|
|
1953
|
def fixData90HL(self,angulos):
|
|
|
1949
|
vec = numpy.where(angulos>=90)
|
|
1954
|
vec = numpy.where(angulos>=90)
|
|
|
1950
|
angulos[vec]=angulos[vec]-90
|
|
1955
|
angulos[vec]=angulos[vec]-90
|
|
|
1951
|
return angulos
|
|
1956
|
return angulos
|
|
|
1952
|
|
|
1957
|
|
|
|
1953
|
|
|
1958
|
|
|
|
1954
|
def search_pos(self,pos,list_):
|
|
1959
|
def search_pos(self,pos,list_):
|
|
|
1955
|
for i in range(len(list_)):
|
|
1960
|
for i in range(len(list_)):
|
|
|
1956
|
if pos == list_[i]:
|
|
1961
|
if pos == list_[i]:
|
|
|
1957
|
return True,i
|
|
1962
|
return True,i
|
|
|
1958
|
i=None
|
|
1963
|
i=None
|
|
|
1959
|
return False,i
|
|
1964
|
return False,i
|
|
|
1960
|
|
|
1965
|
|
|
|
1961
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
1966
|
def fixDataComp(self,ang_,list1_,list2_,tipo_case):
|
|
|
1962
|
size = len(ang_)
|
|
1967
|
size = len(ang_)
|
|
|
1963
|
size2 = 0
|
|
1968
|
size2 = 0
|
|
|
1964
|
for i in range(len(list2_)):
|
|
1969
|
for i in range(len(list2_)):
|
|
|
1965
|
size2=size2+round(abs(list2_[i]))-1
|
|
1970
|
size2=size2+round(abs(list2_[i]))-1
|
|
|
1966
|
new_size= size+size2
|
|
1971
|
new_size= size+size2
|
|
|
1967
|
ang_new = numpy.zeros(new_size)
|
|
1972
|
ang_new = numpy.zeros(new_size)
|
|
|
1968
|
ang_new2 = numpy.zeros(new_size)
|
|
1973
|
ang_new2 = numpy.zeros(new_size)
|
|
|
1969
|
|
|
1974
|
|
|
|
1970
|
tmp = 0
|
|
1975
|
tmp = 0
|
|
|
1971
|
c = 0
|
|
1976
|
c = 0
|
|
|
1972
|
for i in range(len(ang_)):
|
|
1977
|
for i in range(len(ang_)):
|
|
|
1973
|
ang_new[tmp +c] = ang_[i]
|
|
1978
|
ang_new[tmp +c] = ang_[i]
|
|
|
1974
|
ang_new2[tmp+c] = ang_[i]
|
|
1979
|
ang_new2[tmp+c] = ang_[i]
|
|
|
1975
|
condition , value = self.search_pos(i,list1_)
|
|
1980
|
condition , value = self.search_pos(i,list1_)
|
|
|
1976
|
if condition:
|
|
1981
|
if condition:
|
|
|
1977
|
pos = tmp + c + 1
|
|
1982
|
pos = tmp + c + 1
|
|
|
1978
|
for k in range(round(abs(list2_[value]))-1):
|
|
1983
|
for k in range(round(abs(list2_[value]))-1):
|
|
|
1979
|
if tipo_case==0 or tipo_case==3:#subida
|
|
1984
|
if tipo_case==0 or tipo_case==3:#subida
|
|
|
1980
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
1985
|
ang_new[pos+k] = ang_new[pos+k-1]+1
|
|
|
1981
|
ang_new2[pos+k] = numpy.nan
|
|
1986
|
ang_new2[pos+k] = numpy.nan
|
|
|
1982
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
1987
|
elif tipo_case==1 or tipo_case==2:#bajada
|
|
|
1983
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
1988
|
ang_new[pos+k] = ang_new[pos+k-1]-1
|
|
|
1984
|
ang_new2[pos+k] = numpy.nan
|
|
1989
|
ang_new2[pos+k] = numpy.nan
|
|
|
1985
|
|
|
1990
|
|
|
|
1986
|
tmp = pos +k
|
|
1991
|
tmp = pos +k
|
|
|
1987
|
c = 0
|
|
1992
|
c = 0
|
|
|
1988
|
c=c+1
|
|
1993
|
c=c+1
|
|
|
1989
|
return ang_new,ang_new2
|
|
1994
|
return ang_new,ang_new2
|
|
|
1990
|
|
|
1995
|
|
|
|
1991
|
def globalCheckPED(self,angulos,tipo_case):
|
|
1996
|
def globalCheckPED(self,angulos,tipo_case):
|
|
|
1992
|
l1,l2 = self.get2List(angulos)
|
|
1997
|
l1,l2 = self.get2List(angulos)
|
|
|
1993
|
##print("l1",l1)
|
|
1998
|
##print("l1",l1)
|
|
|
1994
|
##print("l2",l2)
|
|
1999
|
##print("l2",l2)
|
|
|
1995
|
if len(l1)>0:
|
|
2000
|
if len(l1)>0:
|
|
|
1996
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
2001
|
#angulos2 = self.fixData90(list_=l1,ang_=angulos)
|
|
|
1997
|
#l1,l2 = self.get2List(angulos2)
|
|
2002
|
#l1,l2 = self.get2List(angulos2)
|
|
|
1998
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
2003
|
ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
|
|
|
1999
|
#ang1_ = self.fixData90HL(ang1_)
|
|
2004
|
#ang1_ = self.fixData90HL(ang1_)
|
|
|
2000
|
#ang2_ = self.fixData90HL(ang2_)
|
|
2005
|
#ang2_ = self.fixData90HL(ang2_)
|
|
|
2001
|
else:
|
|
2006
|
else:
|
|
|
2002
|
ang1_= angulos
|
|
2007
|
ang1_= angulos
|
|
|
2003
|
ang2_= angulos
|
|
2008
|
ang2_= angulos
|
|
|
2004
|
return ang1_,ang2_
|
|
2009
|
return ang1_,ang2_
|
|
|
2005
|
|
|
2010
|
|
|
|
2006
|
|
|
2011
|
|
|
|
2007
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
2012
|
def replaceNAN(self,data_weather,data_ele,val):
|
|
|
2008
|
data= data_ele
|
|
2013
|
data= data_ele
|
|
|
2009
|
data_T= data_weather
|
|
2014
|
data_T= data_weather
|
|
|
2010
|
|
|
2015
|
|
|
|
2011
|
if data.shape[0]> data_T.shape[0]:
|
|
2016
|
if data.shape[0]> data_T.shape[0]:
|
|
|
2012
|
print("IF")
|
|
2017
|
print("IF")
|
|
|
2013
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
2018
|
data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
|
|
|
2014
|
c = 0
|
|
2019
|
c = 0
|
|
|
2015
|
for i in range(len(data)):
|
|
2020
|
for i in range(len(data)):
|
|
|
2016
|
if numpy.isnan(data[i]):
|
|
2021
|
if numpy.isnan(data[i]):
|
|
|
2017
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
2022
|
data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
2018
|
else:
|
|
2023
|
else:
|
|
|
2019
|
data_N[i,:]=data_T[c,:]
|
|
2024
|
data_N[i,:]=data_T[c,:]
|
|
|
2020
|
c=c+1
|
|
2025
|
c=c+1
|
|
|
2021
|
return data_N
|
|
2026
|
return data_N
|
|
|
2022
|
else:
|
|
2027
|
else:
|
|
|
2023
|
print("else")
|
|
2028
|
print("else")
|
|
|
2024
|
for i in range(len(data)):
|
|
2029
|
for i in range(len(data)):
|
|
|
2025
|
if numpy.isnan(data[i]):
|
|
2030
|
if numpy.isnan(data[i]):
|
|
|
2026
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
2031
|
data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
|
|
|
2027
|
return data_T
|
|
2032
|
return data_T
|
|
|
2028
|
|
|
2033
|
|
|
|
2029
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
2034
|
def check_case(self,data_ele,ang_max,ang_min):
|
|
|
2030
|
start = data_ele[0]
|
|
2035
|
start = data_ele[0]
|
|
|
2031
|
end = data_ele[-1]
|
|
2036
|
end = data_ele[-1]
|
|
|
2032
|
number = (end-start)
|
|
2037
|
number = (end-start)
|
|
|
2033
|
len_ang=len(data_ele)
|
|
2038
|
len_ang=len(data_ele)
|
|
|
2034
|
print("start",start)
|
|
2039
|
print("start",start)
|
|
|
2035
|
print("end",end)
|
|
2040
|
print("end",end)
|
|
|
2036
|
print("number",number)
|
|
2041
|
print("number",number)
|
|
|
2037
|
|
|
2042
|
|
|
|
2038
|
print("len_ang",len_ang)
|
|
2043
|
print("len_ang",len_ang)
|
|
|
2039
|
|
|
2044
|
|
|
|
2040
|
#exit(1)
|
|
2045
|
#exit(1)
|
|
|
2041
|
|
|
2046
|
|
|
|
2042
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
2047
|
if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
|
|
|
2043
|
return 0
|
|
2048
|
return 0
|
|
|
2044
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
2049
|
#elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
2045
|
# return 1
|
|
2050
|
# return 1
|
|
|
2046
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
2051
|
elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
|
|
|
2047
|
return 1
|
|
2052
|
return 1
|
|
|
2048
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
2053
|
elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
|
|
|
2049
|
return 2
|
|
2054
|
return 2
|
|
|
2050
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
2055
|
elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
|
|
|
2051
|
return 3
|
|
2056
|
return 3
|
|
|
2052
|
|
|
2057
|
|
|
|
2053
|
|
|
2058
|
|
|
|
2054
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
2059
|
def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
|
|
|
2055
|
ang_max= ang_max
|
|
2060
|
ang_max= ang_max
|
|
|
2056
|
ang_min= ang_min
|
|
2061
|
ang_min= ang_min
|
|
|
2057
|
data_weather=data_weather
|
|
2062
|
data_weather=data_weather
|
|
|
2058
|
val_ch=val_ch
|
|
2063
|
val_ch=val_ch
|
|
|
2059
|
##print("*********************DATA WEATHER**************************************")
|
|
2064
|
##print("*********************DATA WEATHER**************************************")
|
|
|
2060
|
##print(data_weather)
|
|
2065
|
##print(data_weather)
|
|
|
2061
|
if self.ini==0:
|
|
2066
|
if self.ini==0:
|
|
|
2062
|
|
|
2067
|
|
|
|
2063
|
#--------------------- new -------------------------
|
|
2068
|
#--------------------- new -------------------------
|
|
|
2064
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
2069
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
|
|
|
2065
|
|
|
2070
|
|
|
|
2066
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
2071
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
2067
|
start= ang_min
|
|
2072
|
start= ang_min
|
|
|
2068
|
end = ang_max
|
|
2073
|
end = ang_max
|
|
|
2069
|
n= (ang_max-ang_min)/res
|
|
2074
|
n= (ang_max-ang_min)/res
|
|
|
2070
|
#------ new
|
|
2075
|
#------ new
|
|
|
2071
|
self.start_data_ele = data_ele_new[0]
|
|
2076
|
self.start_data_ele = data_ele_new[0]
|
|
|
2072
|
self.end_data_ele = data_ele_new[-1]
|
|
2077
|
self.end_data_ele = data_ele_new[-1]
|
|
|
2073
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
2078
|
if tipo_case==0 or tipo_case==3: # SUBIDA
|
|
|
2074
|
n1= round(self.start_data_ele)- start
|
|
2079
|
n1= round(self.start_data_ele)- start
|
|
|
2075
|
n2= end - round(self.end_data_ele)
|
|
2080
|
n2= end - round(self.end_data_ele)
|
|
|
2076
|
print(self.start_data_ele)
|
|
2081
|
print(self.start_data_ele)
|
|
|
2077
|
print(self.end_data_ele)
|
|
2082
|
print(self.end_data_ele)
|
|
|
2078
|
if n1>0:
|
|
2083
|
if n1>0:
|
|
|
2079
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
2084
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
2080
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
2085
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
2081
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
2086
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
2082
|
print("ele1_nan",ele1_nan.shape)
|
|
2087
|
print("ele1_nan",ele1_nan.shape)
|
|
|
2083
|
print("data_ele_old",data_ele_old.shape)
|
|
2088
|
print("data_ele_old",data_ele_old.shape)
|
|
|
2084
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
2089
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
2085
|
if n2>0:
|
|
2090
|
if n2>0:
|
|
|
2086
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
2091
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
2087
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
2092
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
2088
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
2093
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
2089
|
print("ele2_nan",ele2_nan.shape)
|
|
2094
|
print("ele2_nan",ele2_nan.shape)
|
|
|
2090
|
print("data_ele_old",data_ele_old.shape)
|
|
2095
|
print("data_ele_old",data_ele_old.shape)
|
|
|
2091
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
2096
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
2092
|
|
|
2097
|
|
|
|
2093
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
2098
|
if tipo_case==1 or tipo_case==2: # BAJADA
|
|
|
2094
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
2099
|
data_ele_new = data_ele_new[::-1] # reversa
|
|
|
2095
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
2100
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
2096
|
data_weather = data_weather[::-1,:]# reversa
|
|
2101
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
2097
|
vec= numpy.where(data_ele_new<ang_max)
|
|
2102
|
vec= numpy.where(data_ele_new<ang_max)
|
|
|
2098
|
data_ele_new = data_ele_new[vec]
|
|
2103
|
data_ele_new = data_ele_new[vec]
|
|
|
2099
|
data_ele_old = data_ele_old[vec]
|
|
2104
|
data_ele_old = data_ele_old[vec]
|
|
|
2100
|
data_weather = data_weather[vec[0]]
|
|
2105
|
data_weather = data_weather[vec[0]]
|
|
|
2101
|
vec2= numpy.where(0<data_ele_new)
|
|
2106
|
vec2= numpy.where(0<data_ele_new)
|
|
|
2102
|
data_ele_new = data_ele_new[vec2]
|
|
2107
|
data_ele_new = data_ele_new[vec2]
|
|
|
2103
|
data_ele_old = data_ele_old[vec2]
|
|
2108
|
data_ele_old = data_ele_old[vec2]
|
|
|
2104
|
data_weather = data_weather[vec2[0]]
|
|
2109
|
data_weather = data_weather[vec2[0]]
|
|
|
2105
|
self.start_data_ele = data_ele_new[0]
|
|
2110
|
self.start_data_ele = data_ele_new[0]
|
|
|
2106
|
self.end_data_ele = data_ele_new[-1]
|
|
2111
|
self.end_data_ele = data_ele_new[-1]
|
|
|
2107
|
|
|
2112
|
|
|
|
2108
|
n1= round(self.start_data_ele)- start
|
|
2113
|
n1= round(self.start_data_ele)- start
|
|
|
2109
|
n2= end - round(self.end_data_ele)-1
|
|
2114
|
n2= end - round(self.end_data_ele)-1
|
|
|
2110
|
print(self.start_data_ele)
|
|
2115
|
print(self.start_data_ele)
|
|
|
2111
|
print(self.end_data_ele)
|
|
2116
|
print(self.end_data_ele)
|
|
|
2112
|
if n1>0:
|
|
2117
|
if n1>0:
|
|
|
2113
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
2118
|
ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
|
|
|
2114
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
2119
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
2115
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
2120
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
2116
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
2121
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
|
|
|
2117
|
if n2>0:
|
|
2122
|
if n2>0:
|
|
|
2118
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
2123
|
ele2= numpy.linspace(self.end_data_ele+1,end,n2)
|
|
|
2119
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
2124
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
2120
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
2125
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
2121
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
2126
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
2122
|
# RADAR
|
|
2127
|
# RADAR
|
|
|
2123
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
2128
|
# NOTA data_ele y data_weather es la variable que retorna
|
|
|
2124
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
2129
|
val_mean = numpy.mean(data_weather[:,-1])
|
|
|
2125
|
self.val_mean = val_mean
|
|
2130
|
self.val_mean = val_mean
|
|
|
2126
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
2131
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
2127
|
print("eleold",data_ele_old)
|
|
2132
|
print("eleold",data_ele_old)
|
|
|
2128
|
print(self.data_ele_tmp[val_ch])
|
|
2133
|
print(self.data_ele_tmp[val_ch])
|
|
|
2129
|
print(data_ele_old.shape[0])
|
|
2134
|
print(data_ele_old.shape[0])
|
|
|
2130
|
print(self.data_ele_tmp[val_ch].shape[0])
|
|
2135
|
print(self.data_ele_tmp[val_ch].shape[0])
|
|
|
2131
|
if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91):
|
|
2136
|
if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91):
|
|
|
2132
|
import sys
|
|
2137
|
import sys
|
|
|
2133
|
print("EXIT",self.ini)
|
|
2138
|
print("EXIT",self.ini)
|
|
|
2134
|
|
|
2139
|
|
|
|
2135
|
sys.exit(1)
|
|
2140
|
sys.exit(1)
|
|
|
2136
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
2141
|
self.data_ele_tmp[val_ch]= data_ele_old
|
|
|
2137
|
else:
|
|
2142
|
else:
|
|
|
2138
|
#print("**********************************************")
|
|
2143
|
#print("**********************************************")
|
|
|
2139
|
#print("****************VARIABLE**********************")
|
|
2144
|
#print("****************VARIABLE**********************")
|
|
|
2140
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
2145
|
#-------------------------CAMBIOS RHI---------------------------------
|
|
|
2141
|
#---------------------------------------------------------------------
|
|
2146
|
#---------------------------------------------------------------------
|
|
|
2142
|
##print("INPUT data_ele",data_ele)
|
|
2147
|
##print("INPUT data_ele",data_ele)
|
|
|
2143
|
flag=0
|
|
2148
|
flag=0
|
|
|
2144
|
start_ele = self.res_ele[0]
|
|
2149
|
start_ele = self.res_ele[0]
|
|
|
2145
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
2150
|
#tipo_case = self.check_case(data_ele,ang_max,ang_min)
|
|
|
2146
|
tipo_case = case_flag[-1]
|
|
2151
|
tipo_case = case_flag[-1]
|
|
|
2147
|
#print("TIPO DE DATA",tipo_case)
|
|
2152
|
#print("TIPO DE DATA",tipo_case)
|
|
|
2148
|
#-----------new------------
|
|
2153
|
#-----------new------------
|
|
|
2149
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
2154
|
data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
|
|
|
2150
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
2155
|
data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
2151
|
|
|
2156
|
|
|
|
2152
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
2157
|
#-------------------------------NEW RHI ITERATIVO-------------------------
|
|
|
2153
|
|
|
2158
|
|
|
|
2154
|
if tipo_case==0 : # SUBIDA
|
|
2159
|
if tipo_case==0 : # SUBIDA
|
|
|
2155
|
vec = numpy.where(data_ele<ang_max)
|
|
2160
|
vec = numpy.where(data_ele<ang_max)
|
|
|
2156
|
data_ele = data_ele[vec]
|
|
2161
|
data_ele = data_ele[vec]
|
|
|
2157
|
data_ele_old = data_ele_old[vec]
|
|
2162
|
data_ele_old = data_ele_old[vec]
|
|
|
2158
|
data_weather = data_weather[vec[0]]
|
|
2163
|
data_weather = data_weather[vec[0]]
|
|
|
2159
|
|
|
2164
|
|
|
|
2160
|
vec2 = numpy.where(0<data_ele)
|
|
2165
|
vec2 = numpy.where(0<data_ele)
|
|
|
2161
|
data_ele= data_ele[vec2]
|
|
2166
|
data_ele= data_ele[vec2]
|
|
|
2162
|
data_ele_old= data_ele_old[vec2]
|
|
2167
|
data_ele_old= data_ele_old[vec2]
|
|
|
2163
|
##print(data_ele_new)
|
|
2168
|
##print(data_ele_new)
|
|
|
2164
|
data_weather= data_weather[vec2[0]]
|
|
2169
|
data_weather= data_weather[vec2[0]]
|
|
|
2165
|
|
|
2170
|
|
|
|
2166
|
new_i_ele = int(round(data_ele[0]))
|
|
2171
|
new_i_ele = int(round(data_ele[0]))
|
|
|
2167
|
new_f_ele = int(round(data_ele[-1]))
|
|
2172
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
2168
|
#print(new_i_ele)
|
|
2173
|
#print(new_i_ele)
|
|
|
2169
|
#print(new_f_ele)
|
|
2174
|
#print(new_f_ele)
|
|
|
2170
|
#print(data_ele,len(data_ele))
|
|
2175
|
#print(data_ele,len(data_ele))
|
|
|
2171
|
#print(data_ele_old,len(data_ele_old))
|
|
2176
|
#print(data_ele_old,len(data_ele_old))
|
|
|
2172
|
if new_i_ele< 2:
|
|
2177
|
if new_i_ele< 2:
|
|
|
2173
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
2178
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
2174
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
2179
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
2175
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
2180
|
self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
|
|
|
2176
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
2181
|
self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
|
|
|
2177
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
2182
|
self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
|
|
|
2178
|
data_ele = self.res_ele
|
|
2183
|
data_ele = self.res_ele
|
|
|
2179
|
data_weather = self.res_weather[val_ch]
|
|
2184
|
data_weather = self.res_weather[val_ch]
|
|
|
2180
|
|
|
2185
|
|
|
|
2181
|
elif tipo_case==1 : #BAJADA
|
|
2186
|
elif tipo_case==1 : #BAJADA
|
|
|
2182
|
data_ele = data_ele[::-1] # reversa
|
|
2187
|
data_ele = data_ele[::-1] # reversa
|
|
|
2183
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
2188
|
data_ele_old = data_ele_old[::-1]# reversa
|
|
|
2184
|
data_weather = data_weather[::-1,:]# reversa
|
|
2189
|
data_weather = data_weather[::-1,:]# reversa
|
|
|
2185
|
vec= numpy.where(data_ele<ang_max)
|
|
2190
|
vec= numpy.where(data_ele<ang_max)
|
|
|
2186
|
data_ele = data_ele[vec]
|
|
2191
|
data_ele = data_ele[vec]
|
|
|
2187
|
data_ele_old = data_ele_old[vec]
|
|
2192
|
data_ele_old = data_ele_old[vec]
|
|
|
2188
|
data_weather = data_weather[vec[0]]
|
|
2193
|
data_weather = data_weather[vec[0]]
|
|
|
2189
|
vec2= numpy.where(0<data_ele)
|
|
2194
|
vec2= numpy.where(0<data_ele)
|
|
|
2190
|
data_ele = data_ele[vec2]
|
|
2195
|
data_ele = data_ele[vec2]
|
|
|
2191
|
data_ele_old = data_ele_old[vec2]
|
|
2196
|
data_ele_old = data_ele_old[vec2]
|
|
|
2192
|
data_weather = data_weather[vec2[0]]
|
|
2197
|
data_weather = data_weather[vec2[0]]
|
|
|
2193
|
|
|
2198
|
|
|
|
2194
|
|
|
2199
|
|
|
|
2195
|
new_i_ele = int(round(data_ele[0]))
|
|
2200
|
new_i_ele = int(round(data_ele[0]))
|
|
|
2196
|
new_f_ele = int(round(data_ele[-1]))
|
|
2201
|
new_f_ele = int(round(data_ele[-1]))
|
|
|
2197
|
#print(data_ele)
|
|
2202
|
#print(data_ele)
|
|
|
2198
|
#print(ang_max)
|
|
2203
|
#print(ang_max)
|
|
|
2199
|
#print(data_ele_old)
|
|
2204
|
#print(data_ele_old)
|
|
|
2200
|
if new_i_ele <= 1:
|
|
2205
|
if new_i_ele <= 1:
|
|
|
2201
|
new_i_ele = 1
|
|
2206
|
new_i_ele = 1
|
|
|
2202
|
if round(data_ele[-1])>=ang_max-1:
|
|
2207
|
if round(data_ele[-1])>=ang_max-1:
|
|
|
2203
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
2208
|
self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
|
|
|
2204
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
2209
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
|
|
|
2205
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
2210
|
self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
|
|
|
2206
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
2211
|
self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
|
|
|
2207
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
2212
|
self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
|
|
|
2208
|
data_ele = self.res_ele
|
|
2213
|
data_ele = self.res_ele
|
|
|
2209
|
data_weather = self.res_weather[val_ch]
|
|
2214
|
data_weather = self.res_weather[val_ch]
|
|
|
2210
|
|
|
2215
|
|
|
|
2211
|
elif tipo_case==2: #bajada
|
|
2216
|
elif tipo_case==2: #bajada
|
|
|
2212
|
vec = numpy.where(data_ele<ang_max)
|
|
2217
|
vec = numpy.where(data_ele<ang_max)
|
|
|
2213
|
data_ele = data_ele[vec]
|
|
2218
|
data_ele = data_ele[vec]
|
|
|
2214
|
data_weather= data_weather[vec[0]]
|
|
2219
|
data_weather= data_weather[vec[0]]
|
|
|
2215
|
|
|
2220
|
|
|
|
2216
|
len_vec = len(vec)
|
|
2221
|
len_vec = len(vec)
|
|
|
2217
|
data_ele_new = data_ele[::-1] # reversa
|
|
2222
|
data_ele_new = data_ele[::-1] # reversa
|
|
|
2218
|
data_weather = data_weather[::-1,:]
|
|
2223
|
data_weather = data_weather[::-1,:]
|
|
|
2219
|
new_i_ele = int(data_ele_new[0])
|
|
2224
|
new_i_ele = int(data_ele_new[0])
|
|
|
2220
|
new_f_ele = int(data_ele_new[-1])
|
|
2225
|
new_f_ele = int(data_ele_new[-1])
|
|
|
2221
|
|
|
2226
|
|
|
|
2222
|
n1= new_i_ele- ang_min
|
|
2227
|
n1= new_i_ele- ang_min
|
|
|
2223
|
n2= ang_max - new_f_ele-1
|
|
2228
|
n2= ang_max - new_f_ele-1
|
|
|
2224
|
if n1>0:
|
|
2229
|
if n1>0:
|
|
|
2225
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
2230
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
2226
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
2231
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
2227
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
2232
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
2228
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
2233
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
2229
|
if n2>0:
|
|
2234
|
if n2>0:
|
|
|
2230
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
2235
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
2231
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
2236
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
2232
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
2237
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
2233
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
2238
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
2234
|
|
|
2239
|
|
|
|
2235
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
2240
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
2236
|
self.res_ele = data_ele
|
|
2241
|
self.res_ele = data_ele
|
|
|
2237
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
2242
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
2238
|
data_ele = self.res_ele
|
|
2243
|
data_ele = self.res_ele
|
|
|
2239
|
data_weather = self.res_weather[val_ch]
|
|
2244
|
data_weather = self.res_weather[val_ch]
|
|
|
2240
|
|
|
2245
|
|
|
|
2241
|
elif tipo_case==3:#subida
|
|
2246
|
elif tipo_case==3:#subida
|
|
|
2242
|
vec = numpy.where(0<data_ele)
|
|
2247
|
vec = numpy.where(0<data_ele)
|
|
|
2243
|
data_ele= data_ele[vec]
|
|
2248
|
data_ele= data_ele[vec]
|
|
|
2244
|
data_ele_new = data_ele
|
|
2249
|
data_ele_new = data_ele
|
|
|
2245
|
data_ele_old= data_ele_old[vec]
|
|
2250
|
data_ele_old= data_ele_old[vec]
|
|
|
2246
|
data_weather= data_weather[vec[0]]
|
|
2251
|
data_weather= data_weather[vec[0]]
|
|
|
2247
|
pos_ini = numpy.argmin(data_ele)
|
|
2252
|
pos_ini = numpy.argmin(data_ele)
|
|
|
2248
|
if pos_ini>0:
|
|
2253
|
if pos_ini>0:
|
|
|
2249
|
len_vec= len(data_ele)
|
|
2254
|
len_vec= len(data_ele)
|
|
|
2250
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
2255
|
vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
|
|
|
2251
|
#print(vec3)
|
|
2256
|
#print(vec3)
|
|
|
2252
|
data_ele= data_ele[vec3]
|
|
2257
|
data_ele= data_ele[vec3]
|
|
|
2253
|
data_ele_new = data_ele
|
|
2258
|
data_ele_new = data_ele
|
|
|
2254
|
data_ele_old= data_ele_old[vec3]
|
|
2259
|
data_ele_old= data_ele_old[vec3]
|
|
|
2255
|
data_weather= data_weather[vec3]
|
|
2260
|
data_weather= data_weather[vec3]
|
|
|
2256
|
|
|
2261
|
|
|
|
2257
|
new_i_ele = int(data_ele_new[0])
|
|
2262
|
new_i_ele = int(data_ele_new[0])
|
|
|
2258
|
new_f_ele = int(data_ele_new[-1])
|
|
2263
|
new_f_ele = int(data_ele_new[-1])
|
|
|
2259
|
n1= new_i_ele- ang_min
|
|
2264
|
n1= new_i_ele- ang_min
|
|
|
2260
|
n2= ang_max - new_f_ele-1
|
|
2265
|
n2= ang_max - new_f_ele-1
|
|
|
2261
|
if n1>0:
|
|
2266
|
if n1>0:
|
|
|
2262
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
2267
|
ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
|
|
|
2263
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
2268
|
ele1_nan= numpy.ones(n1)*numpy.nan
|
|
|
2264
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
2269
|
data_ele = numpy.hstack((ele1,data_ele_new))
|
|
|
2265
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
2270
|
data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
|
|
|
2266
|
if n2>0:
|
|
2271
|
if n2>0:
|
|
|
2267
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
2272
|
ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
|
|
|
2268
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
2273
|
ele2_nan= numpy.ones(n2)*numpy.nan
|
|
|
2269
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
2274
|
data_ele = numpy.hstack((data_ele,ele2))
|
|
|
2270
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
2275
|
data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
|
|
|
2271
|
|
|
2276
|
|
|
|
2272
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
2277
|
self.data_ele_tmp[val_ch] = data_ele_old
|
|
|
2273
|
self.res_ele = data_ele
|
|
2278
|
self.res_ele = data_ele
|
|
|
2274
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
2279
|
self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
|
|
|
2275
|
data_ele = self.res_ele
|
|
2280
|
data_ele = self.res_ele
|
|
|
2276
|
data_weather = self.res_weather[val_ch]
|
|
2281
|
data_weather = self.res_weather[val_ch]
|
|
|
2277
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
2282
|
#print("self.data_ele_tmp",self.data_ele_tmp)
|
|
|
2278
|
return data_weather,data_ele
|
|
2283
|
return data_weather,data_ele
|
|
|
2279
|
|
|
2284
|
|
|
|
2280
|
def const_ploteo_vRF(self,val_ch,data_weather,data_ele,res,ang_max,ang_min):
|
|
2285
|
def const_ploteo_vRF(self,val_ch,data_weather,data_ele,res,ang_max,ang_min):
|
|
|
2281
|
|
|
2286
|
|
|
|
2282
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,1)
|
|
2287
|
data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,1)
|
|
|
2283
|
|
|
2288
|
|
|
|
2284
|
data_ele = data_ele_old.copy()
|
|
2289
|
data_ele = data_ele_old.copy()
|
|
|
2285
|
|
|
2290
|
|
|
|
2286
|
diff_1 = ang_max - data_ele[0]
|
|
2291
|
diff_1 = ang_max - data_ele[0]
|
|
|
2287
|
angles_1_nan = numpy.linspace(ang_max,data_ele[0]+1,int(diff_1)-1)#*numpy.nan
|
|
2292
|
angles_1_nan = numpy.linspace(ang_max,data_ele[0]+1,int(diff_1)-1)#*numpy.nan
|
|
|
2288
|
|
|
2293
|
|
|
|
2289
|
diff_2 = data_ele[-1]-ang_min
|
|
2294
|
diff_2 = data_ele[-1]-ang_min
|
|
|
2290
|
angles_2_nan = numpy.linspace(data_ele[-1]-1,ang_min,int(diff_2)-1)#*numpy.nan
|
|
2295
|
angles_2_nan = numpy.linspace(data_ele[-1]-1,ang_min,int(diff_2)-1)#*numpy.nan
|
|
|
2291
|
|
|
2296
|
|
|
|
2292
|
angles_filled = numpy.concatenate((angles_1_nan,data_ele,angles_2_nan))
|
|
2297
|
angles_filled = numpy.concatenate((angles_1_nan,data_ele,angles_2_nan))
|
|
|
2293
|
|
|
2298
|
|
|
|
2294
|
print(angles_filled)
|
|
2299
|
print(angles_filled)
|
|
|
2295
|
|
|
2300
|
|
|
|
2296
|
data_1_nan = numpy.ones([angles_1_nan.shape[0],len(self.r_mask)])*numpy.nan
|
|
2301
|
data_1_nan = numpy.ones([angles_1_nan.shape[0],len(self.r_mask)])*numpy.nan
|
|
|
2297
|
data_2_nan = numpy.ones([angles_2_nan.shape[0],len(self.r_mask)])*numpy.nan
|
|
2302
|
data_2_nan = numpy.ones([angles_2_nan.shape[0],len(self.r_mask)])*numpy.nan
|
|
|
2298
|
|
|
2303
|
|
|
|
2299
|
data_filled = numpy.concatenate((data_1_nan,data_weather,data_2_nan),axis=0)
|
|
2304
|
data_filled = numpy.concatenate((data_1_nan,data_weather,data_2_nan),axis=0)
|
|
|
2300
|
#val_mean = numpy.mean(data_weather[:,-1])
|
|
2305
|
#val_mean = numpy.mean(data_weather[:,-1])
|
|
|
2301
|
#self.val_mean = val_mean
|
|
2306
|
#self.val_mean = val_mean
|
|
|
2302
|
print(data_filled)
|
|
2307
|
print(data_filled)
|
|
|
2303
|
data_filled = self.replaceNAN(data_weather=data_filled,data_ele=angles_filled,val=numpy.nan)
|
|
2308
|
data_filled = self.replaceNAN(data_weather=data_filled,data_ele=angles_filled,val=numpy.nan)
|
|
|
2304
|
|
|
2309
|
|
|
|
2305
|
print(data_filled)
|
|
2310
|
print(data_filled)
|
|
|
2306
|
print(data_filled.shape)
|
|
2311
|
print(data_filled.shape)
|
|
|
2307
|
print(angles_filled.shape)
|
|
2312
|
print(angles_filled.shape)
|
|
|
2308
|
|
|
2313
|
|
|
|
2309
|
return data_filled,angles_filled
|
|
2314
|
return data_filled,angles_filled
|
|
|
2310
|
|
|
2315
|
|
|
|
2311
|
def plot(self):
|
|
2316
|
def plot(self):
|
|
|
2312
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
2317
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
|
|
|
2313
|
data = self.data[-1]
|
|
2318
|
data = self.data[-1]
|
|
|
2314
|
r = self.data.yrange
|
|
2319
|
r = self.data.yrange
|
|
|
2315
|
delta_height = r[1]-r[0]
|
|
2320
|
delta_height = r[1]-r[0]
|
|
|
2316
|
r_mask = numpy.where(r>=0)[0]
|
|
2321
|
r_mask = numpy.where(r>=0)[0]
|
|
|
2317
|
self.r_mask =r_mask
|
|
2322
|
self.r_mask =r_mask
|
|
|
2318
|
##print("delta_height",delta_height)
|
|
2323
|
##print("delta_height",delta_height)
|
|
|
2319
|
#print("r_mask",r_mask,len(r_mask))
|
|
2324
|
#print("r_mask",r_mask,len(r_mask))
|
|
|
2320
|
r = numpy.arange(len(r_mask))*delta_height
|
|
2325
|
r = numpy.arange(len(r_mask))*delta_height
|
|
|
2321
|
self.y = 2*r
|
|
2326
|
self.y = 2*r
|
|
|
2322
|
res = 1
|
|
2327
|
res = 1
|
|
|
2323
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
2328
|
###print("data['weather'].shape[0]",data['weather'].shape[0])
|
|
|
2324
|
ang_max = self.ang_max
|
|
2329
|
ang_max = self.ang_max
|
|
|
2325
|
ang_min = self.ang_min
|
|
2330
|
ang_min = self.ang_min
|
|
|
2326
|
var_ang =ang_max - ang_min
|
|
2331
|
var_ang =ang_max - ang_min
|
|
|
2327
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
2332
|
step = (int(var_ang)/(res*data['weather'].shape[0]))
|
|
|
2328
|
###print("step",step)
|
|
2333
|
###print("step",step)
|
|
|
2329
|
#--------------------------------------------------------
|
|
2334
|
#--------------------------------------------------------
|
|
|
2330
|
##print('weather',data['weather'].shape)
|
|
2335
|
##print('weather',data['weather'].shape)
|
|
|
2331
|
##print('ele',data['ele'].shape)
|
|
2336
|
##print('ele',data['ele'].shape)
|
|
|
2332
|
|
|
2337
|
|
|
|
2333
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
2338
|
###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
2334
|
###self.res_azi = numpy.mean(data['azi'])
|
|
2339
|
###self.res_azi = numpy.mean(data['azi'])
|
|
|
2335
|
###print("self.res_ele",self.res_ele)
|
|
2340
|
###print("self.res_ele",self.res_ele)
|
|
|
2336
|
|
|
2341
|
|
|
|
2337
|
plt.clf()
|
|
2342
|
plt.clf()
|
|
|
2338
|
subplots = [121, 122]
|
|
2343
|
subplots = [121, 122]
|
|
|
2339
|
#if self.ini==0:
|
|
2344
|
#if self.ini==0:
|
|
|
2340
|
#self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
2345
|
#self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
|
|
|
2341
|
#print("SHAPE",self.data_ele_tmp.shape)
|
|
2346
|
#print("SHAPE",self.data_ele_tmp.shape)
|
|
|
2342
|
|
|
2347
|
|
|
|
2343
|
for i,ax in enumerate(self.axes):
|
|
2348
|
for i,ax in enumerate(self.axes):
|
|
|
2344
|
res_weather, self.res_ele = self.const_ploteo_vRF(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],res=res,ang_max=ang_max,ang_min=ang_min)
|
|
2349
|
res_weather, self.res_ele = self.const_ploteo_vRF(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],res=res,ang_max=ang_max,ang_min=ang_min)
|
|
|
2345
|
self.res_azi = numpy.mean(data['azi'])
|
|
2350
|
self.res_azi = numpy.mean(data['azi'])
|
|
|
2346
|
|
|
2351
|
|
|
|
2347
|
if ax.firsttime:
|
|
2352
|
if ax.firsttime:
|
|
|
2348
|
#plt.clf()
|
|
2353
|
#plt.clf()
|
|
|
2349
|
print("Frist Plot")
|
|
2354
|
print("Frist Plot")
|
|
|
2350
|
print(data['weather'][i][:,r_mask].shape)
|
|
2355
|
print(data['weather'][i][:,r_mask].shape)
|
|
|
2351
|
print(data['ele'].shape)
|
|
2356
|
print(data['ele'].shape)
|
|
|
2352
|
cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
2357
|
cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
2353
|
#cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
2358
|
#cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
2354
|
gh = cgax.get_grid_helper()
|
|
2359
|
gh = cgax.get_grid_helper()
|
|
|
2355
|
locs = numpy.linspace(ang_min,ang_max,var_ang+1)
|
|
2360
|
locs = numpy.linspace(ang_min,ang_max,var_ang+1)
|
|
|
2356
|
gh.grid_finder.grid_locator1 = FixedLocator(locs)
|
|
2361
|
gh.grid_finder.grid_locator1 = FixedLocator(locs)
|
|
|
2357
|
gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs]))
|
|
2362
|
gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs]))
|
|
|
2358
|
|
|
2363
|
|
|
|
2359
|
|
|
2364
|
|
|
|
2360
|
#fig=self.figures[0]
|
|
2365
|
#fig=self.figures[0]
|
|
|
2361
|
else:
|
|
2366
|
else:
|
|
|
2362
|
#plt.clf()
|
|
2367
|
#plt.clf()
|
|
|
2363
|
print("ELSE PLOT")
|
|
2368
|
print("ELSE PLOT")
|
|
|
2364
|
cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
2369
|
cgax, pm = wrl.vis.plot_rhi(res_weather,r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
2365
|
#cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
2370
|
#cgax, pm = wrl.vis.plot_rhi(data['weather'][i][:,r_mask],r=r,th=data['ele'],ax=subplots[i], proj='cg',vmin=20, vmax=80)
|
|
|
2366
|
gh = cgax.get_grid_helper()
|
|
2371
|
gh = cgax.get_grid_helper()
|
|
|
2367
|
locs = numpy.linspace(ang_min,ang_max,var_ang+1)
|
|
2372
|
locs = numpy.linspace(ang_min,ang_max,var_ang+1)
|
|
|
2368
|
gh.grid_finder.grid_locator1 = FixedLocator(locs)
|
|
2373
|
gh.grid_finder.grid_locator1 = FixedLocator(locs)
|
|
|
2369
|
gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs]))
|
|
2374
|
gh.grid_finder.tick_formatter1 = DictFormatter(dict([(i, r"${0:.0f}^\circ$".format(i)) for i in locs]))
|
|
|
2370
|
|
|
2375
|
|
|
|
2371
|
caax = cgax.parasites[0]
|
|
2376
|
caax = cgax.parasites[0]
|
|
|
2372
|
paax = cgax.parasites[1]
|
|
2377
|
paax = cgax.parasites[1]
|
|
|
2373
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
2378
|
cbar = plt.gcf().colorbar(pm, pad=0.075)
|
|
|
2374
|
caax.set_xlabel('x_range [km]')
|
|
2379
|
caax.set_xlabel('x_range [km]')
|
|
|
2375
|
caax.set_ylabel('y_range [km]')
|
|
2380
|
caax.set_ylabel('y_range [km]')
|
|
|
2376
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
2381
|
plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
2377
|
print("***************************self.ini****************************",self.ini)
|
|
2382
|
print("***************************self.ini****************************",self.ini)
|
|
|
2378
|
self.ini= self.ini+1
|
|
2383
|
self.ini= self.ini+1
|
