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'''
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New Plots Operations
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@author: juan.espinoza@jro.igp.gob.pe
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'''
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import time
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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.utils import log
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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 SpectraPlot(Plot):
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'''
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Plot for Spectra data
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'''
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CODE = 'spc'
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colormap = 'jro'
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plot_name = 'Spectra'
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plot_type = 'pcolor'
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def setup(self):
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self.nplots = len(self.data.channels)
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self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
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self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
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self.width = 3.4 * self.ncols
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self.height = 3 * self.nrows
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self.cb_label = 'dB'
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if self.showprofile:
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self.width += 0.8 * self.ncols
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self.ylabel = 'Range [km]'
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def plot(self):
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if self.xaxis == "frequency":
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x = self.data.xrange[0]
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self.xlabel = "Frequency (kHz)"
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elif self.xaxis == "time":
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x = self.data.xrange[1]
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self.xlabel = "Time (ms)"
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else:
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x = self.data.xrange[2]
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self.xlabel = "Velocity (m/s)"
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if self.CODE == 'spc_moments':
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x = self.data.xrange[2]
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self.xlabel = "Velocity (m/s)"
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self.titles = []
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y = self.data.heights
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self.y = y
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z = self.data['spc']
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for n, ax in enumerate(self.axes):
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noise = self.data['noise'][n][-1]
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if self.CODE == 'spc_moments':
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mean = self.data['moments'][n, :, 1, :][-1]
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if ax.firsttime:
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self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
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self.xmin = self.xmin if self.xmin else -self.xmax
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self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
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self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
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ax.plt = ax.pcolormesh(x, y, z[n].T,
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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if self.showprofile:
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ax.plt_profile = self.pf_axes[n].plot(
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self.data['rti'][n][-1], y)[0]
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ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
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color="k", linestyle="dashed", lw=1)[0]
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if self.CODE == 'spc_moments':
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ax.plt_mean = ax.plot(mean, y, color='k')[0]
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else:
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ax.plt.set_array(z[n].T.ravel())
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if self.showprofile:
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ax.plt_profile.set_data(self.data['rti'][n][-1], y)
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ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
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if self.CODE == 'spc_moments':
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ax.plt_mean.set_data(mean, y)
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self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
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class CrossSpectraPlot(Plot):
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CODE = 'cspc'
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colormap = 'jet'
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plot_name = 'CrossSpectra'
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plot_type = 'pcolor'
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zmin_coh = None
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zmax_coh = None
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zmin_phase = None
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zmax_phase = None
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def setup(self):
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self.ncols = 4
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self.nrows = len(self.data.pairs)
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self.nplots = self.nrows * 4
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self.width = 3.4 * self.ncols
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self.height = 3 * self.nrows
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self.ylabel = 'Range [km]'
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self.showprofile = False
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def plot(self):
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if self.xaxis == "frequency":
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x = self.data.xrange[0]
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self.xlabel = "Frequency (kHz)"
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elif self.xaxis == "time":
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x = self.data.xrange[1]
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self.xlabel = "Time (ms)"
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else:
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x = self.data.xrange[2]
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self.xlabel = "Velocity (m/s)"
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self.titles = []
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y = self.data.heights
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self.y = y
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spc = self.data['spc']
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cspc = self.data['cspc']
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for n in range(self.nrows):
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noise = self.data['noise'][n][-1]
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pair = self.data.pairs[n]
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ax = self.axes[4 * n]
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spc0 = 10.*numpy.log10(spc[pair[0]]/self.data.factor)
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if ax.firsttime:
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self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
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self.xmin = self.xmin if self.xmin else -self.xmax
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self.zmin = self.zmin if self.zmin else numpy.nanmin(spc)
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self.zmax = self.zmax if self.zmax else numpy.nanmax(spc)
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ax.plt = ax.pcolormesh(x , y , spc0.T,
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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else:
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ax.plt.set_array(spc0.T.ravel())
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self.titles.append('CH {}: {:3.2f}dB'.format(pair[0], noise))
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ax = self.axes[4 * n + 1]
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spc1 = 10.*numpy.log10(spc[pair[1]]/self.data.factor)
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if ax.firsttime:
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ax.plt = ax.pcolormesh(x , y, spc1.T,
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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else:
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ax.plt.set_array(spc1.T.ravel())
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self.titles.append('CH {}: {:3.2f}dB'.format(pair[1], noise))
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out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
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coh = numpy.abs(out)
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phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
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ax = self.axes[4 * n + 2]
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if ax.firsttime:
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ax.plt = ax.pcolormesh(x, y, coh.T,
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vmin=0,
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vmax=1,
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cmap=plt.get_cmap(self.colormap_coh)
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)
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else:
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ax.plt.set_array(coh.T.ravel())
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self.titles.append(
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'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
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ax = self.axes[4 * n + 3]
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if ax.firsttime:
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ax.plt = ax.pcolormesh(x, y, phase.T,
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vmin=-180,
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vmax=180,
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cmap=plt.get_cmap(self.colormap_phase)
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)
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else:
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ax.plt.set_array(phase.T.ravel())
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self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
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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 = 'jro'
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plot_name = 'SpectralMoments'
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plot_type = 'pcolor'
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class RTIPlot(Plot):
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'''
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Plot for RTI data
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'''
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CODE = 'rti'
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colormap = 'jro'
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plot_name = 'RTI'
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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 = len(self.data.channels)
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self.nplots = len(self.data.channels)
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self.ylabel = 'Range [km]'
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self.cb_label = 'dB'
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self.titles = ['{} Channel {}'.format(
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self.CODE.upper(), x) for x in range(self.nrows)]
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def plot(self):
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self.x = self.data.times
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self.y = self.data.heights
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self.z = self.data[self.CODE]
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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.zmin = self.zmin if self.zmin else numpy.min(self.z)
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self.zmax = self.zmax if self.zmax else numpy.max(self.z)
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if ax.firsttime:
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ax.plt = ax.pcolormesh(x, y, z[n].T,
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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if self.showprofile:
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ax.plot_profile = self.pf_axes[n].plot(
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self.data['rti'][n][-1], self.y)[0]
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ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y,
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color="k", linestyle="dashed", lw=1)[0]
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else:
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ax.collections.remove(ax.collections[0])
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ax.plt = ax.pcolormesh(x, y, z[n].T,
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vmin=self.zmin,
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vmax=self.zmax,
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cmap=plt.get_cmap(self.colormap)
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)
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if self.showprofile:
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ax.plot_profile.set_data(self.data['rti'][n][-1], self.y)
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ax.plot_noise.set_data(numpy.repeat(
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self.data['noise'][n][-1], len(self.y)), self.y)
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class CoherencePlot(RTIPlot):
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'''
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Plot for Coherence data
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'''
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CODE = 'coh'
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plot_name = 'Coherence'
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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 = len(self.data.pairs)
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self.nplots = len(self.data.pairs)
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self.ylabel = 'Range [km]'
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if self.CODE == 'coh':
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self.cb_label = ''
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self.titles = [
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'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
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else:
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self.cb_label = 'Degrees'
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self.titles = [
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'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
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class PhasePlot(CoherencePlot):
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'''
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Plot for Phase map data
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'''
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CODE = 'phase'
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colormap = 'seismic'
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plot_name = 'Phase'
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class NoisePlot(Plot):
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'''
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Plot for noise
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'''
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CODE = 'noise'
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plot_name = 'Noise'
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plot_type = 'scatterbuffer'
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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 = 1
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self.nplots = 1
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self.ylabel = 'Intensity [dB]'
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self.titles = ['Noise']
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self.colorbar = False
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def plot(self):
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x = self.data.times
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xmin = self.data.min_time
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xmax = xmin + self.xrange * 60 * 60
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Y = self.data[self.CODE]
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if self.axes[0].firsttime:
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for ch in self.data.channels:
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y = Y[ch]
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self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
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plt.legend()
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else:
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for ch in self.data.channels:
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y = Y[ch]
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self.axes[0].lines[ch].set_data(x, y)
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self.ymin = numpy.nanmin(Y) - 5
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self.ymax = numpy.nanmax(Y) + 5
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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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plot_name = 'SNR'
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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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plot_name = 'DopplerShift'
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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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plot_name = 'TotalPower'
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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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plot_name = 'SpectralWidth'
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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 ParametersPlot(RTIPlot):
|
|
|
'''
|
|
|
Plot for data_param object
|
|
|
'''
|
|
|
|
|
|
CODE = 'param'
|
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|
colormap = 'seismic'
|
|
|
plot_name = 'Parameters'
|
|
|
|
|
|
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(self.CODE)[0]
|
|
|
self.nplots = self.nrows
|
|
|
if self.showSNR:
|
|
|
self.nrows += 1
|
|
|
self.nplots += 1
|
|
|
|
|
|
self.ylabel = 'Height [km]'
|
|
|
if not self.titles:
|
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|
self.titles = self.data.parameters \
|
|
|
if self.data.parameters else ['Param {}'.format(x) for x in range(self.nrows)]
|
|
|
if self.showSNR:
|
|
|
self.titles.append('SNR')
|
|
|
|
|
|
def plot(self):
|
|
|
self.data.normalize_heights()
|
|
|
self.x = self.data.times
|
|
|
self.y = self.data.heights
|
|
|
if self.showSNR:
|
|
|
self.z = numpy.concatenate(
|
|
|
(self.data[self.CODE], self.data['snr'])
|
|
|
)
|
|
|
else:
|
|
|
self.z = self.data[self.CODE]
|
|
|
|
|
|
self.z = numpy.ma.masked_invalid(self.z)
|
|
|
|
|
|
if self.decimation is None:
|
|
|
x, y, z = self.fill_gaps(self.x, self.y, self.z)
|
|
|
else:
|
|
|
x, y, z = self.fill_gaps(*self.decimate())
|
|
|
|
|
|
for n, ax in enumerate(self.axes):
|
|
|
|
|
|
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])
|
|
|
|
|
|
if ax.firsttime:
|
|
|
if self.zlimits is not None:
|
|
|
self.zmin, self.zmax = self.zlimits[n]
|
|
|
|
|
|
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 OutputPlot(ParametersPlot):
|
|
|
'''
|
|
|
Plot data_output object
|
|
|
'''
|
|
|
|
|
|
CODE = 'output'
|
|
|
colormap = 'seismic'
|
|
|
plot_name = 'Output'
|
|
|
|
|
|
|
|
|
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)
|
|
|
else:
|
|
|
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':
|
|
|
azimuths = -numpy.radians(self.data.heights)+numpy.pi/2
|
|
|
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
|
|
|
else:
|
|
|
azimuths = numpy.radians(self.data.heights)
|
|
|
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])
|
|
|
else:
|
|
|
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']))
|
|
|
else:
|
|
|
title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
|
|
|
label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
|
|
|
|
|
|
self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
|
|
|
self.titles = ['{} {}'.format(
|
|
|
self.data.parameters[x], title) for x in self.channels]
|
|
|
|
|
|
|
|
|
class ScopePlot(Plot):
|
|
|
|
|
|
'''
|
|
|
Plot for Scope
|
|
|
'''
|
|
|
|
|
|
CODE = 'scope'
|
|
|
plot_name = 'Scope'
|
|
|
plot_type = 'scatter'
|
|
|
|
|
|
def setup(self):
|
|
|
|
|
|
self.xaxis = 'Range (Km)'
|
|
|
self.ncols = 1
|
|
|
self.nrows = 1
|
|
|
self.nplots = 1
|
|
|
self.ylabel = 'Intensity [dB]'
|
|
|
self.titles = ['Scope']
|
|
|
self.colorbar = False
|
|
|
colspan = 3
|
|
|
rowspan = 1
|
|
|
|
|
|
def plot_iq(self, x, y, channelIndexList, thisDatetime, wintitle):
|
|
|
|
|
|
yreal = y[channelIndexList,:].real
|
|
|
yimag = y[channelIndexList,:].imag
|
|
|
title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y"))
|
|
|
self.xlabel = "Range (Km)"
|
|
|
self.ylabel = "Intensity - IQ"
|
|
|
|
|
|
self.y = yreal
|
|
|
self.x = x
|
|
|
self.xmin = min(x)
|
|
|
self.xmax = max(x)
|
|
|
|
|
|
|
|
|
self.titles[0] = title
|
|
|
|
|
|
for i,ax in enumerate(self.axes):
|
|
|
title = "Channel %d" %(i)
|
|
|
if ax.firsttime:
|
|
|
ax.plt_r = ax.plot(x, yreal[i,:], color='b')[0]
|
|
|
ax.plt_i = ax.plot(x, yimag[i,:], color='r')[0]
|
|
|
else:
|
|
|
#pass
|
|
|
ax.plt_r.set_data(x, yreal[i,:])
|
|
|
ax.plt_i.set_data(x, yimag[i,:])
|
|
|
|
|
|
def plot_power(self, x, y, channelIndexList, thisDatetime, wintitle):
|
|
|
y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:])
|
|
|
yreal = y.real
|
|
|
self.y = yreal
|
|
|
title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y"))
|
|
|
self.xlabel = "Range (Km)"
|
|
|
self.ylabel = "Intensity"
|
|
|
self.xmin = min(x)
|
|
|
self.xmax = max(x)
|
|
|
|
|
|
|
|
|
self.titles[0] = title
|
|
|
|
|
|
for i,ax in enumerate(self.axes):
|
|
|
title = "Channel %d" %(i)
|
|
|
|
|
|
ychannel = yreal[i,:]
|
|
|
|
|
|
if ax.firsttime:
|
|
|
ax.plt_r = ax.plot(x, ychannel)[0]
|
|
|
else:
|
|
|
#pass
|
|
|
ax.plt_r.set_data(x, ychannel)
|
|
|
|
|
|
|
|
|
def plot(self):
|
|
|
|
|
|
if self.channels:
|
|
|
channels = self.channels
|
|
|
else:
|
|
|
channels = self.data.channels
|
|
|
|
|
|
|
|
|
|
|
|
thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1])
|
|
|
|
|
|
scope = self.data['scope']
|
|
|
|
|
|
|
|
|
if self.data.flagDataAsBlock:
|
|
|
|
|
|
for i in range(self.data.nProfiles):
|
|
|
|
|
|
wintitle1 = " [Profile = %d] " %i
|
|
|
|
|
|
if self.type == "power":
|
|
|
self.plot_power(self.data.heights,
|
|
|
scope[:,i,:],
|
|
|
channels,
|
|
|
thisDatetime,
|
|
|
wintitle1
|
|
|
)
|
|
|
|
|
|
if self.type == "iq":
|
|
|
self.plot_iq(self.data.heights,
|
|
|
scope[:,i,:],
|
|
|
channels,
|
|
|
thisDatetime,
|
|
|
wintitle1
|
|
|
)
|
|
|
else:
|
|
|
wintitle = " [Profile = %d] " %self.data.profileIndex
|
|
|
|
|
|
if self.type == "power":
|
|
|
self.plot_power(self.data.heights,
|
|
|
scope,
|
|
|
channels,
|
|
|
thisDatetime,
|
|
|
wintitle
|
|
|
)
|
|
|
|
|
|
if self.type == "iq":
|
|
|
self.plot_iq(self.data.heights,
|
|
|
scope,
|
|
|
channels,
|
|
|
thisDatetime,
|
|
|
wintitle
|
|
|
)
|
|
|
|
