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import os
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import datetime
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import numpy
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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.utils import log
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# libreria wradlib
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import wradlib as wrl
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EARTH_RADIUS = 6.3710e3
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def ll2xy(lat1, lon1, lat2, lon2):
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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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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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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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theta = -theta + numpy.pi/2
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return r*numpy.cos(theta), r*numpy.sin(theta)
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def km2deg(km):
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'''
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Convert distance in km to degrees
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'''
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return numpy.rad2deg(km/EARTH_RADIUS)
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class SpectralMomentsPlot(SpectraPlot):
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'''
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Plot for Spectral Moments
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'''
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CODE = 'spc_moments'
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# colormap = 'jet'
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# plot_type = 'pcolor'
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class DobleGaussianPlot(SpectraPlot):
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'''
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Plot for Double Gaussian Plot
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'''
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CODE = 'gaussian_fit'
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# colormap = 'jet'
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# plot_type = 'pcolor'
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class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
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'''
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Plot SpectraCut with Double Gaussian Fit
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'''
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CODE = 'cut_gaussian_fit'
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class SnrPlot(RTIPlot):
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'''
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Plot for SNR Data
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'''
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CODE = 'snr'
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colormap = 'jet'
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def update(self, dataOut):
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data = {
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'snr': 10*numpy.log10(dataOut.data_snr)
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}
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return data, {}
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class DopplerPlot(RTIPlot):
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'''
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Plot for DOPPLER Data (1st moment)
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'''
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CODE = 'dop'
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colormap = 'jet'
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def update(self, dataOut):
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data = {
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'dop': 10*numpy.log10(dataOut.data_dop)
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}
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return data, {}
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class PowerPlot(RTIPlot):
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'''
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Plot for Power Data (0 moment)
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'''
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CODE = 'pow'
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colormap = 'jet'
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def update(self, dataOut):
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data = {
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'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor)
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}
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return data, {}
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class SpectralWidthPlot(RTIPlot):
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'''
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Plot for Spectral Width Data (2nd moment)
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'''
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CODE = 'width'
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colormap = 'jet'
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def update(self, dataOut):
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data = {
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'width': dataOut.data_width
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}
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return data, {}
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class SkyMapPlot(Plot):
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'''
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Plot for meteors detection data
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'''
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CODE = 'param'
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def setup(self):
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self.ncols = 1
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self.nrows = 1
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self.width = 7.2
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self.height = 7.2
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self.nplots = 1
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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.polar = True
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self.ymin = -180
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self.ymax = 180
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self.colorbar = False
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def plot(self):
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arrayParameters = numpy.concatenate(self.data['param'])
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error = arrayParameters[:, -1]
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indValid = numpy.where(error == 0)[0]
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finalMeteor = arrayParameters[indValid, :]
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finalAzimuth = finalMeteor[:, 3]
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finalZenith = finalMeteor[:, 4]
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x = finalAzimuth * numpy.pi / 180
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y = finalZenith
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ax = self.axes[0]
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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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else:
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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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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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dt2,
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len(x))
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self.titles[0] = title
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class GenericRTIPlot(Plot):
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'''
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Plot for data_xxxx object
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'''
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CODE = 'param'
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colormap = 'viridis'
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plot_type = 'pcolorbuffer'
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def setup(self):
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self.xaxis = 'time'
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self.ncols = 1
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self.nrows = self.data.shape('param')[0]
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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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if not self.xlabel:
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self.xlabel = 'Time'
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self.ylabel = 'Range [km]'
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if not self.titles:
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self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
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def update(self, dataOut):
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data = {
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'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
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}
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meta = {}
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return data, meta
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def plot(self):
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# self.data.normalize_heights()
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self.x = self.data.times
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self.y = self.data.yrange
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self.z = self.data['param']
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self.z = 10*numpy.log10(self.z)
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self.z = numpy.ma.masked_invalid(self.z)
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if self.decimation is None:
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x, y, z = self.fill_gaps(self.x, self.y, self.z)
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else:
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x, y, z = self.fill_gaps(*self.decimate())
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for n, ax in enumerate(self.axes):
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self.zmax = self.zmax if self.zmax is not None else numpy.max(
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self.z[n])
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self.zmin = self.zmin if self.zmin is not None else numpy.min(
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self.z[n])
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if ax.firsttime:
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if self.zlimits is not None:
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self.zmin, self.zmax = self.zlimits[n]
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ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=self.cmaps[n]
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)
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else:
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if self.zlimits is not None:
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self.zmin, self.zmax = self.zlimits[n]
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ax.collections.remove(ax.collections[0])
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ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=self.cmaps[n]
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)
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class PolarMapPlot(Plot):
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'''
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Plot for weather radar
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'''
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CODE = 'param'
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colormap = 'seismic'
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def setup(self):
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self.ncols = 1
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self.nrows = 1
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self.width = 9
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self.height = 8
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self.mode = self.data.meta['mode']
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if self.channels is not None:
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self.nplots = len(self.channels)
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self.nrows = len(self.channels)
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else:
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self.nplots = self.data.shape(self.CODE)[0]
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self.nrows = self.nplots
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self.channels = list(range(self.nplots))
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if self.mode == 'E':
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self.xlabel = 'Longitude'
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self.ylabel = 'Latitude'
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else:
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self.xlabel = 'Range (km)'
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self.ylabel = 'Height (km)'
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self.bgcolor = 'white'
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self.cb_labels = self.data.meta['units']
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self.lat = self.data.meta['latitude']
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self.lon = self.data.meta['longitude']
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self.xmin, self.xmax = float(
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km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
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self.ymin, self.ymax = float(
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km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
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# self.polar = True
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def plot(self):
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for n, ax in enumerate(self.axes):
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data = self.data['param'][self.channels[n]]
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zeniths = numpy.linspace(
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0, self.data.meta['max_range'], data.shape[1])
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if self.mode == 'E':
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azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2
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r, theta = numpy.meshgrid(zeniths, azimuths)
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x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(
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theta)*numpy.cos(numpy.radians(self.data.meta['elevation']))
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x = km2deg(x) + self.lon
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y = km2deg(y) + self.lat
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else:
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azimuths = numpy.radians(self.data.yrange)
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r, theta = numpy.meshgrid(zeniths, azimuths)
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x, y = r*numpy.cos(theta), r*numpy.sin(theta)
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self.y = zeniths
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if ax.firsttime:
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if self.zlimits is not None:
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self.zmin, self.zmax = self.zlimits[n]
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ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
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x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=self.cmaps[n])
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else:
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if self.zlimits is not None:
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self.zmin, self.zmax = self.zlimits[n]
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ax.collections.remove(ax.collections[0])
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ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
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x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=self.cmaps[n])
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if self.mode == 'A':
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continue
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# plot district names
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f = open('/data/workspace/schain_scripts/distrito.csv')
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for line in f:
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label, lon, lat = [s.strip() for s in line.split(',') if s]
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lat = float(lat)
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lon = float(lon)
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# ax.plot(lon, lat, '.b', ms=2)
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ax.text(lon, lat, label.decode('utf8'), ha='center',
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va='bottom', size='8', color='black')
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# plot limites
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limites = []
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tmp = []
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for line in open('/data/workspace/schain_scripts/lima.csv'):
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if '#' in line:
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if tmp:
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limites.append(tmp)
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tmp = []
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continue
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values = line.strip().split(',')
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tmp.append((float(values[0]), float(values[1])))
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for points in limites:
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ax.add_patch(
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Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
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# plot Cuencas
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for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
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f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
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values = [line.strip().split(',') for line in f]
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points = [(float(s[0]), float(s[1])) for s in values]
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ax.add_patch(Polygon(points, ec='b', fc='none'))
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# plot grid
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for r in (15, 30, 45, 60):
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ax.add_artist(plt.Circle((self.lon, self.lat),
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km2deg(r), color='0.6', fill=False, lw=0.2))
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ax.text(
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self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180),
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self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180),
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'{}km'.format(r),
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ha='center', va='bottom', size='8', color='0.6', weight='heavy')
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if self.mode == 'E':
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title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
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label = 'E{:02d}'.format(int(self.data.meta['elevation']))
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else:
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title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
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label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
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self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
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self.titles = ['{} {}'.format(
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self.data.parameters[x], title) for x in self.channels]
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class WeatherPlot(Plot):
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CODE = 'weather'
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plot_name = 'weather'
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plot_type = 'ppistyle'
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buffering = False
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def setup(self):
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self.ncols = 1
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self.nrows = 1
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self.nplots= 1
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self.ylabel= 'Range [Km]'
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self.titles= ['Weather']
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self.colorbar=False
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self.width =8
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self.height =8
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self.ini =0
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self.len_azi =0
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self.buffer_ini = None
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self.buffer_azi = None
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self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
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self.flag =0
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self.indicador= 0
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def update(self, dataOut):
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data = {}
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meta = {}
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data['weather'] = 10*numpy.log10(dataOut.data_360[0]/(250.0))
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data['azi'] = dataOut.data_azi
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return data, meta
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def const_ploteo(self,data_weather,data_azi,step,res):
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if self.ini==0:
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#------- AZIMUTH
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n = (360/res)-len(data_azi)
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start = data_azi[-1] + res
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end = data_azi[0] - res
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if start>end:
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end = end + 360
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azi_vacia = numpy.linspace(start,end,int(n))
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azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia)
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data_azi = numpy.hstack((data_azi,azi_vacia))
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# RADAR
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val_mean = numpy.mean(data_weather[:,0])
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data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean
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data_weather = numpy.vstack((data_weather,data_weather_cmp))
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else:
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# azimuth
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flag=0
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start_azi = self.res_azi[0]
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start = data_azi[0]
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end = data_azi[-1]
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print("start",start)
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print("end",end)
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if start< start_azi:
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start = start +360
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if end <start_azi:
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end = end +360
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print("start",start)
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print("end",end)
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#### AQUI SERA LA MAGIA
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pos_ini = int((start-start_azi)/res)
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len_azi = len(data_azi)
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if (360-pos_ini)<len_azi:
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if pos_ini+1==360:
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pos_ini=0
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else:
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flag=1
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dif= 360-pos_ini
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comp= len_azi-dif
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|
|
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print(pos_ini)
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print(len_azi)
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print("shape",self.res_azi.shape)
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if flag==0:
|
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# AZIMUTH
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self.res_azi[pos_ini:pos_ini+len_azi] = data_azi
|
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|
# RADAR
|
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self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather
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else:
|
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|
# AZIMUTH
|
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self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif]
|
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|
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
|
|
|
|
|
|
def plot(self):
|
|
|
print("--------------------------------------",self.ini,"-----------------------------------")
|
|
|
#numpy.set_printoptions(suppress=True)
|
|
|
#print(self.data.times)
|
|
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1])
|
|
|
data = self.data[-1]
|
|
|
# ALTURA altura_tmp_h
|
|
|
altura_h = (data['weather'].shape[1])/10.0
|
|
|
stoprange = float(altura_h*1.5)#stoprange = float(33*1.5) por ahora 400
|
|
|
rangestep = float(0.15)
|
|
|
r = numpy.arange(0, stoprange, rangestep)
|
|
|
self.y = 2*r
|
|
|
# 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)
|
|
|
#print("step",step)
|
|
|
print("Time---->",self.data.times[-1],thisDatetime)
|
|
|
#print("alturas", len(self.y))
|
|
|
self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'],data_azi=data['azi'],step=step,res=res)
|
|
|
#numpy.set_printoptions(suppress=True)
|
|
|
#print("resultado",self.res_azi)
|
|
|
##########################################################
|
|
|
################# PLOTEO ###################
|
|
|
##########################################################
|
|
|
|
|
|
for i,ax in enumerate(self.axes):
|
|
|
if ax.firsttime:
|
|
|
plt.clf()
|
|
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=1, vmax=60)
|
|
|
else:
|
|
|
plt.clf()
|
|
|
cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=0, vmax=60)
|
|
|
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]')
|
|
|
plt.text(1.0, 1.05, 'azimuth '+str(thisDatetime)+"step"+str(self.ini), transform=caax.transAxes, va='bottom',ha='right')
|
|
|
|
|
|
self.ini= self.ini+1
|
|
|
|
