jroplot_parameters.py
605 lines
| 20.1 KiB
| text/x-python
|
PythonLexer
Julio Valdez
|
r502 | import os | ||
| import datetime | ||||
| import numpy | ||||
ebocanegra
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r1001 | |||
Juan C. Espinoza
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r1285 | from schainpy.model.graphics.jroplot_base import Plot, plt | ||
Danny Scipión
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r1358 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot | ||
|
Juan C. Espinoza
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r1285 | from schainpy.utils import log | ||
| r1367 | # libreria wradlib | |||
| import wradlib as wrl | ||||
|
ebocanegra
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r1001 | |||
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Juan C. Espinoza
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r1285 | EARTH_RADIUS = 6.3710e3 | ||
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ebocanegra
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r1001 | |||
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Juan C. Espinoza
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r1285 | def ll2xy(lat1, lon1, lat2, lon2): | ||
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ebocanegra
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r1001 | |||
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Juan C. Espinoza
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r1285 | p = 0.017453292519943295 | ||
| a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ | ||||
| numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 | ||||
| r = 12742 * numpy.arcsin(numpy.sqrt(a)) | ||||
| theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) | ||||
| * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) | ||||
| theta = -theta + numpy.pi/2 | ||||
| return r*numpy.cos(theta), r*numpy.sin(theta) | ||||
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | def km2deg(km): | ||
| ''' | ||||
| Convert distance in km to degrees | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | return numpy.rad2deg(km/EARTH_RADIUS) | ||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | class SpectralMomentsPlot(SpectraPlot): | ||
| ''' | ||||
| Plot for Spectral Moments | ||||
| ''' | ||||
| CODE = 'spc_moments' | ||||
|
Danny Scipión
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r1358 | # colormap = 'jet' | ||
| # plot_type = 'pcolor' | ||||
| class DobleGaussianPlot(SpectraPlot): | ||||
| ''' | ||||
| Plot for Double Gaussian Plot | ||||
| ''' | ||||
| CODE = 'gaussian_fit' | ||||
| # colormap = 'jet' | ||||
| # plot_type = 'pcolor' | ||||
|
José Chávez
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r897 | |||
|
Danny Scipión
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r1358 | class DoubleGaussianSpectraCutPlot(SpectraCutPlot): | ||
| ''' | ||||
| Plot SpectraCut with Double Gaussian Fit | ||||
| ''' | ||||
| CODE = 'cut_gaussian_fit' | ||||
|
José Chávez
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r897 | |||
|
Juan C. Espinoza
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r1285 | class SnrPlot(RTIPlot): | ||
| ''' | ||||
| Plot for SNR Data | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | CODE = 'snr' | ||
| colormap = 'jet' | ||||
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José Chávez
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r897 | |||
| r1343 | def update(self, dataOut): | |||
| data = { | ||||
| r1367 | 'snr': 10*numpy.log10(dataOut.data_snr) | |||
| r1343 | } | |||
| return data, {} | ||||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | class DopplerPlot(RTIPlot): | ||
| ''' | ||||
| Plot for DOPPLER Data (1st moment) | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | CODE = 'dop' | ||
| colormap = 'jet' | ||||
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José Chávez
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r897 | |||
| r1343 | def update(self, dataOut): | |||
| data = { | ||||
| r1367 | 'dop': 10*numpy.log10(dataOut.data_dop) | |||
| r1343 | } | |||
| return data, {} | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | class PowerPlot(RTIPlot): | ||
| ''' | ||||
| Plot for Power Data (0 moment) | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | CODE = 'pow' | ||
| colormap = 'jet' | ||||
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José Chávez
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r897 | |||
| r1343 | def update(self, dataOut): | |||
| data = { | ||||
| r1367 | 'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor) | |||
| r1343 | } | |||
| return data, {} | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | class SpectralWidthPlot(RTIPlot): | ||
| ''' | ||||
| Plot for Spectral Width Data (2nd moment) | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | CODE = 'width' | ||
| colormap = 'jet' | ||||
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José Chávez
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r897 | |||
| r1343 | def update(self, dataOut): | |||
| data = { | ||||
| 'width': dataOut.data_width | ||||
| } | ||||
| return data, {} | ||||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | class SkyMapPlot(Plot): | ||
| ''' | ||||
| Plot for meteors detection data | ||||
| ''' | ||||
|
José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | CODE = 'param' | ||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | def setup(self): | ||
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Julio Valdez
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r502 | |||
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Juan C. Espinoza
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r1285 | self.ncols = 1 | ||
| self.nrows = 1 | ||||
| self.width = 7.2 | ||||
| self.height = 7.2 | ||||
| self.nplots = 1 | ||||
| self.xlabel = 'Zonal Zenith Angle (deg)' | ||||
| self.ylabel = 'Meridional Zenith Angle (deg)' | ||||
| self.polar = True | ||||
| self.ymin = -180 | ||||
| self.ymax = 180 | ||||
| self.colorbar = False | ||||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | def plot(self): | ||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | arrayParameters = numpy.concatenate(self.data['param']) | ||
| error = arrayParameters[:, -1] | ||||
| indValid = numpy.where(error == 0)[0] | ||||
| finalMeteor = arrayParameters[indValid, :] | ||||
| finalAzimuth = finalMeteor[:, 3] | ||||
| finalZenith = finalMeteor[:, 4] | ||||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | x = finalAzimuth * numpy.pi / 180 | ||
| y = finalZenith | ||||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | ax = self.axes[0] | ||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | if ax.firsttime: | ||
| ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] | ||||
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Julio Valdez
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r832 | else: | ||
|
Juan C. Espinoza
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r1285 | ax.plot.set_data(x, y) | ||
| dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S') | ||||
| dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S') | ||||
| title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, | ||||
| dt2, | ||||
| len(x)) | ||||
| self.titles[0] = title | ||||
| r1343 | class GenericRTIPlot(Plot): | |||
|
Juan C. Espinoza
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r1285 | ''' | ||
| r1343 | Plot for data_xxxx object | |||
|
Juan C. Espinoza
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r1285 | ''' | ||
| CODE = 'param' | ||||
| r1343 | colormap = 'viridis' | |||
| plot_type = 'pcolorbuffer' | ||||
|
Juan C. Espinoza
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r1285 | |||
| def setup(self): | ||||
| self.xaxis = 'time' | ||||
| self.ncols = 1 | ||||
| r1359 | self.nrows = self.data.shape('param')[0] | |||
|
Juan C. Espinoza
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r1285 | self.nplots = self.nrows | ||
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Juan C. Espinoza
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r1322 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) | ||
| r1367 | ||||
|
Juan C. Espinoza
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r1322 | if not self.xlabel: | ||
| self.xlabel = 'Time' | ||||
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Juan C. Espinoza
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r1285 | |||
|
Danny Scipión
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r1358 | self.ylabel = 'Range [km]' | ||
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Juan C. Espinoza
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r1285 | if not self.titles: | ||
| r1360 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] | |||
|
Juan C. Espinoza
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r1285 | |||
| r1343 | def update(self, dataOut): | |||
| data = { | ||||
| r1359 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) | |||
| r1343 | } | |||
| meta = {} | ||||
| return data, meta | ||||
| r1367 | ||||
|
Juan C. Espinoza
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r1285 | def plot(self): | ||
| r1343 | # self.data.normalize_heights() | |||
|
Juan C. Espinoza
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r1285 | self.x = self.data.times | ||
| r1343 | self.y = self.data.yrange | |||
| r1359 | self.z = self.data['param'] | |||
david c
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r1378 | self.z = 10*numpy.log10(self.z) | ||
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Juan C. Espinoza
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r1285 | self.z = numpy.ma.masked_invalid(self.z) | ||
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José Chávez
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r897 | |||
|
Juan C. Espinoza
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r1285 | if self.decimation is None: | ||
| x, y, z = self.fill_gaps(self.x, self.y, self.z) | ||||
|
Julio Valdez
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r511 | else: | ||
|
Juan C. Espinoza
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r1285 | x, y, z = self.fill_gaps(*self.decimate()) | ||
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José Chávez
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r897 | |||
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Juan C. Espinoza
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r1285 | for n, ax in enumerate(self.axes): | ||
Miguel Valdez
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r588 | |||
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Juan C. Espinoza
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r1285 | self.zmax = self.zmax if self.zmax is not None else numpy.max( | ||
| self.z[n]) | ||||
| self.zmin = self.zmin if self.zmin is not None else numpy.min( | ||||
| self.z[n]) | ||||
|
José Chávez
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r897 | |||
|
Juan C. Espinoza
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r1285 | if ax.firsttime: | ||
| if self.zlimits is not None: | ||||
| self.zmin, self.zmax = self.zlimits[n] | ||||
|
José Chávez
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r897 | |||
|
Juan C. Espinoza
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r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], | ||
| vmin=self.zmin, | ||||
| vmax=self.zmax, | ||||
| cmap=self.cmaps[n] | ||||
| ) | ||||
| else: | ||||
| if self.zlimits is not None: | ||||
| self.zmin, self.zmax = self.zlimits[n] | ||||
| ax.collections.remove(ax.collections[0]) | ||||
| ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], | ||||
| vmin=self.zmin, | ||||
| vmax=self.zmax, | ||||
| cmap=self.cmaps[n] | ||||
| ) | ||||
| class PolarMapPlot(Plot): | ||||
| ''' | ||||
| Plot for weather radar | ||||
| ''' | ||||
| CODE = 'param' | ||||
| colormap = 'seismic' | ||||
| def setup(self): | ||||
| self.ncols = 1 | ||||
| self.nrows = 1 | ||||
| self.width = 9 | ||||
| self.height = 8 | ||||
| self.mode = self.data.meta['mode'] | ||||
| if self.channels is not None: | ||||
| self.nplots = len(self.channels) | ||||
| self.nrows = len(self.channels) | ||||
| r1065 | else: | |||
|
Juan C. Espinoza
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r1285 | self.nplots = self.data.shape(self.CODE)[0] | ||
| self.nrows = self.nplots | ||||
| self.channels = list(range(self.nplots)) | ||||
| if self.mode == 'E': | ||||
| self.xlabel = 'Longitude' | ||||
| self.ylabel = 'Latitude' | ||||
| else: | ||||
| self.xlabel = 'Range (km)' | ||||
| self.ylabel = 'Height (km)' | ||||
| self.bgcolor = 'white' | ||||
| self.cb_labels = self.data.meta['units'] | ||||
| self.lat = self.data.meta['latitude'] | ||||
| self.lon = self.data.meta['longitude'] | ||||
| self.xmin, self.xmax = float( | ||||
| km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) | ||||
| self.ymin, self.ymax = float( | ||||
| km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) | ||||
| # self.polar = True | ||||
| def plot(self): | ||||
| for n, ax in enumerate(self.axes): | ||||
| data = self.data['param'][self.channels[n]] | ||||
| zeniths = numpy.linspace( | ||||
| 0, self.data.meta['max_range'], data.shape[1]) | ||||
| if self.mode == 'E': | ||||
| r1343 | azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2 | |||
|
Juan C. Espinoza
|
r1285 | r, theta = numpy.meshgrid(zeniths, azimuths) | ||
| x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin( | ||||
| theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) | ||||
| x = km2deg(x) + self.lon | ||||
| y = km2deg(y) + self.lat | ||||
| r1065 | else: | |||
| r1343 | azimuths = numpy.radians(self.data.yrange) | |||
|
Juan C. Espinoza
|
r1285 | r, theta = numpy.meshgrid(zeniths, azimuths) | ||
| x, y = r*numpy.cos(theta), r*numpy.sin(theta) | ||||
| self.y = zeniths | ||||
| if ax.firsttime: | ||||
| if self.zlimits is not None: | ||||
| self.zmin, self.zmax = self.zlimits[n] | ||||
| ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), | ||||
| x, y, numpy.ma.array(data, mask=numpy.isnan(data)), | ||||
| vmin=self.zmin, | ||||
| vmax=self.zmax, | ||||
| cmap=self.cmaps[n]) | ||||
|
Julio Valdez
|
r513 | else: | ||
|
Juan C. Espinoza
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r1285 | if self.zlimits is not None: | ||
| self.zmin, self.zmax = self.zlimits[n] | ||||
| ax.collections.remove(ax.collections[0]) | ||||
| ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), | ||||
| x, y, numpy.ma.array(data, mask=numpy.isnan(data)), | ||||
| vmin=self.zmin, | ||||
| vmax=self.zmax, | ||||
| cmap=self.cmaps[n]) | ||||
| if self.mode == 'A': | ||||
| continue | ||||
| # plot district names | ||||
| f = open('/data/workspace/schain_scripts/distrito.csv') | ||||
| for line in f: | ||||
| label, lon, lat = [s.strip() for s in line.split(',') if s] | ||||
| lat = float(lat) | ||||
| lon = float(lon) | ||||
| # ax.plot(lon, lat, '.b', ms=2) | ||||
| ax.text(lon, lat, label.decode('utf8'), ha='center', | ||||
| va='bottom', size='8', color='black') | ||||
| # plot limites | ||||
| limites = [] | ||||
| tmp = [] | ||||
| for line in open('/data/workspace/schain_scripts/lima.csv'): | ||||
| if '#' in line: | ||||
| if tmp: | ||||
| limites.append(tmp) | ||||
| tmp = [] | ||||
| continue | ||||
| values = line.strip().split(',') | ||||
| tmp.append((float(values[0]), float(values[1]))) | ||||
| for points in limites: | ||||
| ax.add_patch( | ||||
| Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) | ||||
| # plot Cuencas | ||||
| for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): | ||||
| f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) | ||||
| values = [line.strip().split(',') for line in f] | ||||
| points = [(float(s[0]), float(s[1])) for s in values] | ||||
| ax.add_patch(Polygon(points, ec='b', fc='none')) | ||||
| # plot grid | ||||
| for r in (15, 30, 45, 60): | ||||
| ax.add_artist(plt.Circle((self.lon, self.lat), | ||||
| km2deg(r), color='0.6', fill=False, lw=0.2)) | ||||
| ax.text( | ||||
| self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), | ||||
| self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), | ||||
| '{}km'.format(r), | ||||
| ha='center', va='bottom', size='8', color='0.6', weight='heavy') | ||||
| if self.mode == 'E': | ||||
| title = 'El={}$^\circ$'.format(self.data.meta['elevation']) | ||||
| label = 'E{:02d}'.format(int(self.data.meta['elevation'])) | ||||
|
Julio Valdez
|
r608 | else: | ||
|
Juan C. Espinoza
|
r1285 | title = 'Az={}$^\circ$'.format(self.data.meta['azimuth']) | ||
| label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) | ||||
|
José Chávez
|
r897 | |||
|
Juan C. Espinoza
|
r1285 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] | ||
| self.titles = ['{} {}'.format( | ||||
| self.data.parameters[x], title) for x in self.channels] | ||||
|
José Chávez
|
r897 | |||
| r1367 | class WeatherPlot(Plot): | |||
| CODE = 'weather' | ||||
| plot_name = 'weather' | ||||
| plot_type = 'ppistyle' | ||||
| buffering = False | ||||
| def setup(self): | ||||
| self.ncols = 1 | ||||
| self.nrows = 1 | ||||
| self.nplots= 1 | ||||
| self.ylabel= 'Range [Km]' | ||||
| self.titles= ['Weather'] | ||||
| self.colorbar=False | ||||
| self.width =8 | ||||
| self.height =8 | ||||
| self.ini =0 | ||||
| self.len_azi =0 | ||||
| self.buffer_ini = None | ||||
| self.buffer_azi = None | ||||
| self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) | ||||
| self.flag =0 | ||||
| self.indicador= 0 | ||||
avaldezp
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r1405 | self.last_data_azi = None | ||
| self.val_mean = None | ||||
| r1367 | ||||
| def update(self, dataOut): | ||||
| data = {} | ||||
| meta = {} | ||||
| r1394 | if hasattr(dataOut, 'dataPP_POWER'): | |||
| factor = 1 | ||||
| if hasattr(dataOut, 'nFFTPoints'): | ||||
| factor = dataOut.normFactor | ||||
| r1395 | ####print("factor",factor) | |||
|
avaldezp
|
r1405 | data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) | ||
| ####print("weather",data['weather']) | ||||
| r1367 | data['azi'] = dataOut.data_azi | |||
| return data, meta | ||||
|
avaldezp
|
r1405 | def analizeDATA(self,data_azi): | ||
| list1 = [] | ||||
| list2 = [] | ||||
| dat = data_azi | ||||
| for i in reversed(range(1,len(dat))): | ||||
| if dat[i]>dat[i-1]: | ||||
| diff = int(dat[i])-int(dat[i-1]) | ||||
| else: | ||||
| diff = 360+int(dat[i])-int(dat[i-1]) | ||||
| if diff > 1: | ||||
| list1.append(i-1) | ||||
| list2.append(diff-1) | ||||
| return list1,list2 | ||||
| def fixDATANEW(self,data_azi,data_weather): | ||||
| list1,list2 = self.analizeDATA(data_azi) | ||||
| if len(list1)== 0: | ||||
| return data_azi,data_weather | ||||
| else: | ||||
| resize = 0 | ||||
| for i in range(len(list2)): | ||||
| resize= resize + list2[i] | ||||
| new_data_azi = numpy.resize(data_azi,resize) | ||||
| new_data_weather= numpy.resize(date_weather,resize) | ||||
| for i in range(len(list2)): | ||||
| j=0 | ||||
| position=list1[i]+1 | ||||
| for j in range(list2[i]): | ||||
| new_data_azi[position+j]=new_data_azi[position+j-1]+1 | ||||
| return new_data_azi | ||||
| def fixDATA(self,data_azi): | ||||
| data=data_azi | ||||
| for i in range(len(data)): | ||||
| if numpy.isnan(data[i]): | ||||
| data[i]=data[i-1]+1 | ||||
| return data | ||||
| def replaceNAN(self,data_weather,data_azi,val): | ||||
| print("----------------activeNEWFUNCTION") | ||||
| data= data_azi | ||||
| data_T= data_weather | ||||
| print("data_azi",data_azi) | ||||
| print("VAL:",val) | ||||
| print("SHAPE",data_T.shape) | ||||
| for i in range(len(data)): | ||||
| if numpy.isnan(data[i]): | ||||
| print("NAN") | ||||
| data_T[i,:]=numpy.ones(data_T.shape[1])*val | ||||
| #data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan | ||||
| return data_T | ||||
| r1384 | def const_ploteo(self,data_weather,data_azi,step,res): | |||
| if self.ini==0: | ||||
| #------- AZIMUTH | ||||
| n = (360/res)-len(data_azi) | ||||
|
avaldezp
|
r1405 | ##### new | ||
| data_azi_old = data_azi | ||||
| data_azi_new = self.fixDATA(data_azi) | ||||
| #ata_azi_new = self.fixDATANEW(data_azi) | ||||
| start = data_azi_new[-1] + res | ||||
| end = data_azi_new[0] - res | ||||
| ##### new | ||||
| self.last_data_azi = end | ||||
| r1384 | if start>end: | |||
| end = end + 360 | ||||
| azi_vacia = numpy.linspace(start,end,int(n)) | ||||
| azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia) | ||||
|
avaldezp
|
r1405 | data_azi = numpy.hstack((data_azi_new,azi_vacia)) | ||
| r1384 | # RADAR | |||
|
avaldezp
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r1405 | val_mean = numpy.mean(data_weather[:,-1]) | ||
| self.val_mean = val_mean | ||||
| r1384 | data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean | |||
|
avaldezp
|
r1405 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) | ||
| r1384 | data_weather = numpy.vstack((data_weather,data_weather_cmp)) | |||
| else: | ||||
| # azimuth | ||||
| flag=0 | ||||
| start_azi = self.res_azi[0] | ||||
|
avaldezp
|
r1405 | #### new | ||
| data_azi_old = data_azi | ||||
| ### weather ### | ||||
| data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) | ||||
| if numpy.isnan(data_azi[0]): | ||||
| data_azi[0]=self.last_data_azi+1 | ||||
| data_azi = self.fixDATA(data_azi) | ||||
| #### | ||||
| r1384 | start = data_azi[0] | |||
| end = data_azi[-1] | ||||
|
avaldezp
|
r1405 | self.last_data_azi= end | ||
| ####print("start",start) | ||||
| ####print("end",end) | ||||
| r1384 | if start< start_azi: | |||
| start = start +360 | ||||
| if end <start_azi: | ||||
| end = end +360 | ||||
|
avaldezp
|
r1405 | ####print("start",start) | ||
| ####print("end",end) | ||||
| r1384 | #### AQUI SERA LA MAGIA | |||
| pos_ini = int((start-start_azi)/res) | ||||
| len_azi = len(data_azi) | ||||
| if (360-pos_ini)<len_azi: | ||||
| if pos_ini+1==360: | ||||
| pos_ini=0 | ||||
| else: | ||||
| flag=1 | ||||
| dif= 360-pos_ini | ||||
| comp= len_azi-dif | ||||
|
avaldezp
|
r1405 | #----------------- | ||
| ####print(pos_ini) | ||||
| ####print(len_azi) | ||||
| ####print("shape",self.res_azi.shape) | ||||
| r1384 | if flag==0: | |||
| # AZIMUTH | ||||
| self.res_azi[pos_ini:pos_ini+len_azi] = data_azi | ||||
| # RADAR | ||||
| self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather | ||||
| else: | ||||
| # AZIMUTH | ||||
| self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif] | ||||
| self.res_azi[0:comp] = data_azi[dif:] | ||||
| # RADAR | ||||
| self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:] | ||||
| self.res_weather[0:comp,:] = data_weather[dif:,:] | ||||
| flag=0 | ||||
| data_azi = self.res_azi | ||||
| data_weather = self.res_weather | ||||
| return data_weather,data_azi | ||||
| r1367 | def plot(self): | |||
|
avaldezp
|
r1405 | #print("--------------------------------------",self.ini,"-----------------------------------") | ||
| r1384 | #numpy.set_printoptions(suppress=True) | |||
|
avaldezp
|
r1405 | ####print("times: ",self.data.times) | ||
| thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') | ||||
| #print("times: ",thisDatetime) | ||||
| r1384 | data = self.data[-1] | |||
|
avaldezp
|
r1405 | ####ALTURA altura_tmp_h | ||
| ###print("Y RANGES",self.data.yrange,len(self.data.yrange)) | ||||
| ###altura_h = (data['weather'].shape[1])/10.0 | ||||
| ###stoprange = float(altura_h*0.3)#stoprange = float(33*1.5) por ahora 400 | ||||
| ###rangestep = float(0.03) | ||||
| ###r = numpy.arange(0, stoprange, rangestep) | ||||
| ###print("r",r,len(r)) | ||||
| #-----------------------------update---------------------- | ||||
| r= self.data.yrange | ||||
| delta_height = r[1]-r[0] | ||||
| #print("1",r) | ||||
| r_mask= numpy.where(r>=0)[0] | ||||
| r = numpy.arange(len(r_mask))*delta_height | ||||
| #print("2",r) | ||||
| r1367 | self.y = 2*r | |||
|
avaldezp
|
r1405 | ######self.y = self.data.yrange | ||
| r1384 | # RADAR | |||
| #data_weather = data['weather'] | ||||
| # PEDESTAL | ||||
| #data_azi = data['azi'] | ||||
| res = 1 | ||||
| # STEP | ||||
| step = (360/(res*data['weather'].shape[0])) | ||||
| #print("shape wr_data", wr_data.shape) | ||||
| #print("shape wr_azi",wr_azi.shape) | ||||
|
david c
|
r1378 | #print("step",step) | ||
|
avaldezp
|
r1405 | ####print("Time---->",self.data.times[-1],thisDatetime) | ||
| #print("alturas", len(self.y))numpy.where(r>=0) | ||||
| self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res) | ||||
| r1384 | #numpy.set_printoptions(suppress=True) | |||
| #print("resultado",self.res_azi) | ||||
|
avaldezp
|
r1405 | ###########################/DATA_RM/10_tmp/ch0############################### | ||
| r1384 | ################# PLOTEO ################### | |||
| ########################################################## | ||||
| r1367 | ||||
| for i,ax in enumerate(self.axes): | ||||
| if ax.firsttime: | ||||
| plt.clf() | ||||
|
avaldezp
|
r1405 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=8, vmax=35) | ||
| r1367 | else: | |||
| plt.clf() | ||||
|
avaldezp
|
r1405 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=8, vmax=35) | ||
| r1367 | caax = cgax.parasites[0] | |||
| paax = cgax.parasites[1] | ||||
| cbar = plt.gcf().colorbar(pm, pad=0.075) | ||||
| caax.set_xlabel('x_range [km]') | ||||
| caax.set_ylabel('y_range [km]') | ||||
|
avaldezp
|
r1405 | plt.text(1.0, 1.05, 'azimuth '+str(thisDatetime)+" step "+str(self.ini), transform=caax.transAxes, va='bottom',ha='right') | ||
| r1384 | ||||
| self.ini= self.ini+1 | ||||
