schain Commit - r1733:67f6900b4a62 · Jicamarca Repository

fix faraday plots

rflores -

r1733:67f6900b4a62

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r1733:67f6900b4a62

schainpy/model/graphics/jroplot_spectra.py +1 -1

             # Copyright (c) 2012-2021 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """Classes to plot Spectra data
             """
             import os
             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt, log
             from matplotlib import __version__ as plt_version
             if plt_version >='3.3.4':
                 EXTRA_POINTS = 0
             else:
                 EXTRA_POINTS = 1
             class SpectraPlot(Plot):
                 '''
                 Plot for Spectra data
                 '''
                 CODE = 'spc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 buffering = False
                 def setup(self):
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.height = 2.6 * self.nrows
                     self.cb_label = 'dB'
                     if self.showprofile:
                         self.width = 4 * self.ncols
                     else:
                         self.width = 3.5 * self.ncols
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     self.ylabel = 'Range [km]'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = 10 * numpy.log10(dataOut.data_spc / dataOut.normFactor)
                     data['spc'] = spc
                     data['rti'] = dataOut.getPower()
                     if hasattr(dataOut, 'LagPlot'): #Double Pulse
                         max_hei_id = dataOut.nHeights - 2*dataOut.LagPlot
                         data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=53,ymax_index=max_hei_id)/dataOut.normFactor)
                         data['noise'][0] = 10*numpy.log10(dataOut.getNoise(ymin_index=53)[0]/dataOut.normFactor)
                     else:
                         data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor)
                     extrapoints = spc.shape[1] % dataOut.nFFTPoints
                     extrapoints=1
                     meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS))
                     if self.CODE == 'spc_moments':
                         data['moments'] = dataOut.moments
                     if self.CODE == 'gaussian_fit':
                         data['gaussfit'] = dataOut.DGauFitParams
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'):
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     self.y = y
                     data = self.data[-1]
                     z = data['spc']
                     for n, ax in enumerate(self.axes):
                         noise = data['noise'][n]
                         if self.CODE == 'spc_moments':
                             mean = data['moments'][n, 1]
                         if self.CODE == 'gaussian_fit':
                             gau0 = data['gaussfit'][n][2,:,0]
                             gau1 = data['gaussfit'][n][2,:,1]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else numpy.nanmin(x)#-self.xmax
                             #self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                             #self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plt_profile = self.pf_axes[n].plot(
                                     data['rti'][n], y)[0]
                                 ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
                                                                     color="k", linestyle="dashed", lw=1)[0]
                             if self.CODE == 'spc_moments':
                                 ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0]
                             if self.CODE == 'gaussian_fit':
                                 ax.plt_gau0 = ax.plot(gau0, y, color='r', lw=1)[0]
                                 ax.plt_gau1 = ax.plot(gau1, y, color='y', lw=1)[0]
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt.set_array(z[n].T.ravel())
                             if self.showprofile:
                                 ax.plt_profile.set_data(data['rti'][n], y)
                                 ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
                             if self.CODE == 'spc_moments':
                                 ax.plt_mean.set_data(mean, y)
                             if self.CODE == 'gaussian_fit':
                                 ax.plt_gau0.set_data(gau0, y)
                                 ax.plt_gau1.set_data(gau1, y)
                         self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
             class SpectraObliquePlot(Plot):
                 '''
                 Plot for Spectra data
                 Written by R. Flores
                 '''
                 CODE = 'spc_oblique'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 def setup(self):
                     self.xaxis = "oblique"
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.height = 2.6 * self.nrows
                     self.cb_label = 'dB'
                     if self.showprofile:
                         self.width = 4 * self.ncols
                     else:
                         self.width = 3.5 * self.ncols
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     self.ylabel = 'Range [km]'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor)
                     data['spc'] = spc
                     data['rti'] = dataOut.getPower()
                     data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
                     meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS))
                     data['shift1'] = dataOut.Dop_EEJ_T1[0]
                     data['shift2'] = dataOut.Dop_EEJ_T2[0]
                     data['max_val_2'] = dataOut.Oblique_params[0,-1,:]
                     data['shift1_error'] = dataOut.Err_Dop_EEJ_T1[0]
                     data['shift2_error'] = dataOut.Err_Dop_EEJ_T2[0]
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     self.y = y
                     data = self.data[-1]
                     z = data['spc']
                     for n, ax in enumerate(self.axes):
                         noise = self.data['noise'][n][-1]
                         shift1 = data['shift1']
                         shift2 = data['shift2']
                         max_val_2 = data['max_val_2']
                         err1 = data['shift1_error']
                         err2 = data['shift2_error']
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plt_profile = self.pf_axes[n].plot(
                                     self.data['rti'][n][-1], y)[0]
                                 ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
                                                                     color="k", linestyle="dashed", lw=1)[0]
                             self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                             self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                             self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                         else:
                             self.ploterr1.remove()
                             self.ploterr2.remove()
                             self.ploterr3.remove()
                             ax.plt.set_array(z[n].T.ravel())
                             if self.showprofile:
                                 ax.plt_profile.set_data(self.data['rti'][n][-1], y)
                                 ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
                             self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                             self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                             self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2)
                         self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
             class CrossSpectraPlot(Plot):
                 CODE = 'cspc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 def setup(self):
                     self.ncols = 4
                     self.nplots = len(self.data.pairs) * 2
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.width = 3.1 * self.ncols
                     self.height = 5 * self.nrows
                     self.ylabel = 'Range [km]'
                     self.showprofile = False
                     self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = dataOut.data_spc
                     cspc = dataOut.data_cspc
                     extrapoints = spc.shape[1] % dataOut.nFFTPoints
                     meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS))
                     meta['pairs'] = dataOut.pairsList
                     tmp = []
                     for n, pair in enumerate(meta['pairs']):
                         out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
                         coh = numpy.abs(out)
                         phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
                         tmp.append(coh)
                         tmp.append(phase)
                     data['cspc'] = numpy.array(tmp)
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     self.y = y
                     data = self.data[-1]
                     cspc = data['cspc']
                     for n in range(len(self.data.pairs)):
                         pair = self.data.pairs[n]
                         coh = cspc[n * 2]
                         phase = cspc[n * 2 + 1]
                         ax = self.axes[2 * n]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, coh.T,
                                                    vmin=0,
                                                    vmax=1,
                                                    cmap=plt.get_cmap(self.colormap_coh)
                                                    )
                         else:
                             ax.plt.set_array(coh.T.ravel())
                         self.titles.append(
                             'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
                         ax = self.axes[2 * n + 1]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, phase.T,
                                                    vmin=-180,
                                                    vmax=180,
                                                    cmap=plt.get_cmap(self.colormap_phase)
                                                    )
                         else:
                             ax.plt.set_array(phase.T.ravel())
                         self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
             class CrossSpectra4Plot(Plot):
                 CODE = 'cspc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 def setup(self):
                     self.ncols = 4
                     self.nrows = len(self.data.pairs)
                     self.nplots = self.nrows * 4
                     self.width = 3.1 * self.ncols
                     self.height = 5 * self.nrows
                     self.ylabel = 'Range [km]'
                     self.showprofile = False
                     self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.heights
                     self.y = y
                     nspc = self.data['spc']
                     #print(numpy.shape(self.data['spc']))
                     spc = self.data['cspc'][0]
                     #print(numpy.shape(nspc))
                     #exit()
                     #nspc[1,:,:] = numpy.flip(nspc[1,:,:],axis=0)
                     #print(numpy.shape(spc))
                     #exit()
                     cspc = self.data['cspc'][1]
                     #xflip=numpy.flip(x)
                     #print(numpy.shape(cspc))
                     #exit()
                     for n in range(self.nrows):
                         noise = self.data['noise'][:,-1]
                         pair = self.data.pairs[n]
                         #print(pair)
                         #exit()
                         ax = self.axes[4 * n]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(nspc)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(nspc)
                             ax.plt = ax.pcolormesh(x , y , nspc[pair[0]].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             #print(numpy.shape(nspc[pair[0]].T))
                             #exit()
                             ax.plt.set_array(nspc[pair[0]].T.ravel())
                         self.titles.append('CH {}: {:3.2f}dB'.format(pair[0], noise[pair[0]]))
                         ax = self.axes[4 * n + 1]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x , y, numpy.flip(nspc[pair[1]],axis=0).T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             ax.plt.set_array(numpy.flip(nspc[pair[1]],axis=0).T.ravel())
                         self.titles.append('CH {}: {:3.2f}dB'.format(pair[1], noise[pair[1]]))
                         out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
                         coh = numpy.abs(out)
                         phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
                         ax = self.axes[4 * n + 2]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, numpy.flip(coh,axis=0).T,
                                                    vmin=0,
                                                    vmax=1,
                                                    cmap=plt.get_cmap(self.colormap_coh)
                                                    )
                         else:
                             ax.plt.set_array(numpy.flip(coh,axis=0).T.ravel())
                         self.titles.append(
                             'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
                         ax = self.axes[4 * n + 3]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, numpy.flip(phase,axis=0).T,
                                                    vmin=-180,
                                                    vmax=180,
                                                    cmap=plt.get_cmap(self.colormap_phase)
                                                    )
                         else:
                             ax.plt.set_array(numpy.flip(phase,axis=0).T.ravel())
                         self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
             class CrossSpectra2Plot(Plot):
                 CODE = 'cspc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 def setup(self):
                     self.ncols = 1
                     self.nrows = len(self.data.pairs)
                     self.nplots = self.nrows * 1
                     self.width = 3.1 * self.ncols
                     self.height = 5 * self.nrows
                     self.ylabel = 'Range [km]'
                     self.showprofile = False
                     self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.heights
                     self.y = y
                     #nspc = self.data['spc']
                     #print(numpy.shape(self.data['spc']))
                     #spc = self.data['cspc'][0]
                     #print(numpy.shape(spc))
                     #exit()
                     cspc = self.data['cspc'][1]
                     #print(numpy.shape(cspc))
                     #exit()
                     for n in range(self.nrows):
                         noise = self.data['noise'][:,-1]
                         pair = self.data.pairs[n]
                         #print(pair)            #exit()
                         out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
                         #print(out[:,53])
                         #exit()
                         cross = numpy.abs(out)
                         z = cross/self.data.nFactor
                         #print("here")
                         #print(dataOut.data_spc[0,0,0])
                         #exit()
                         cross = 10*numpy.log10(z)
                         #print(numpy.shape(cross))
                         #print(cross[0,:])
                         #print(self.data.nFactor)
                         #exit()
                         #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
                         ax = self.axes[1 * n]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
                             ax.plt = ax.pcolormesh(x, y, cross.T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             ax.plt.set_array(cross.T.ravel())
                         self.titles.append(
                             'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1]))
             class CrossSpectra3Plot(Plot):
                 CODE = 'cspc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 def setup(self):
                     self.ncols = 3
                     self.nrows = len(self.data.pairs)
                     self.nplots = self.nrows * 3
                     self.width = 3.1 * self.ncols
                     self.height = 5 * self.nrows
                     self.ylabel = 'Range [km]'
                     self.showprofile = False
                     self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.heights
                     self.y = y
                     #nspc = self.data['spc']
                     #print(numpy.shape(self.data['spc']))
                     #spc = self.data['cspc'][0]
                     #print(numpy.shape(spc))
                     #exit()
                     cspc = self.data['cspc'][1]
                     #print(numpy.shape(cspc))
                     #exit()
                     for n in range(self.nrows):
                         noise = self.data['noise'][:,-1]
                         pair = self.data.pairs[n]
                         #print(pair)            #exit()
                         out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
                         #print(out[:,53])
                         #exit()
                         cross = numpy.abs(out)
                         z = cross/self.data.nFactor
                         cross = 10*numpy.log10(z)
                         out_r= out.real/self.data.nFactor
                         #out_r = 10*numpy.log10(out_r)
                         out_i= out.imag/self.data.nFactor
                         #out_i = 10*numpy.log10(out_i)
                         #print(numpy.shape(cross))
                         #print(cross[0,:])
                         #print(self.data.nFactor)
                         #exit()
                         #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
                         ax = self.axes[3 * n]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
                             ax.plt = ax.pcolormesh(x, y, cross.T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             ax.plt.set_array(cross.T.ravel())
                         self.titles.append(
                             'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1]))
                         ax = self.axes[3 * n + 1]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
                             ax.plt = ax.pcolormesh(x, y, out_r.T,
                                                    vmin=-1.e6,
                                                    vmax=0,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             ax.plt.set_array(out_r.T.ravel())
                         self.titles.append(
                             'Cross Spectra Real Ch{} * Ch{}'.format(pair[0], pair[1]))
                         ax = self.axes[3 * n + 2]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
                             ax.plt = ax.pcolormesh(x, y, out_i.T,
                                                    vmin=-1.e6,
                                                    vmax=1.e6,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
                             ax.plt.set_array(out_i.T.ravel())
                         self.titles.append(
                             'Cross Spectra Imag Ch{} * Ch{}'.format(pair[0], pair[1]))
             class RTIPlot(Plot):
                 '''
                 Plot for RTI data
                 '''
                 CODE = 'rti'
                 colormap = 'jet'
                 plot_type = 'pcolorbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = len(self.data.channels)
                     self.nplots = len(self.data.channels)
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time'
                     self.cb_label = 'dB'
                     self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95})
                     self.titles = ['{} Channel {}'.format(
                         self.CODE.upper(), x) for x in range(self.nrows)]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['rti'] = dataOut.getPower()
                     data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor)
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.y = self.data.yrange
                     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.zmin = self.zmin if self.zmin else numpy.min(self.z)
                         self.zmax = self.zmax if self.zmax else numpy.max(self.z)
                         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,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plot_profile = self.pf_axes[n].plot(
                                     self.data['rti'][n][-1], self.y)[0]
                                 ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y,
                                                                      color="k", linestyle="dashed", lw=1)[0]
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plot_profile.set_data(self.data['rti'][n][-1], self.y)
                                 ax.plot_noise.set_data(numpy.repeat(
                                     self.data['noise'][n][-1], len(self.y)), self.y)
             class SpectrogramPlot(Plot):
                 '''
                 Plot for Spectrogram data
                 '''
                 CODE = 'Spectrogram_Profile'
                 colormap = 'binary'
                 plot_type = 'pcolorbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = len(self.data.channels)
                     self.nplots = len(self.data.channels)
                     self.xlabel = 'Time'
                     #self.cb_label = 'dB'
                     self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95})
                     self.titles = []
                     #self.titles = ['{} Channel {} \n H = {} km ({} - {})'.format(
                         #self.CODE.upper(), x, self.data.heightList[self.data.hei], self.data.heightList[self.data.hei],self.data.heightList[self.data.hei]+(self.data.DH*self.data.nProfiles)) for x in range(self.nrows)]
                     self.titles = ['{} Channel {}'.format(
                         self.CODE.upper(), x) for x in range(self.nrows)]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     maxHei = 1620#+12000
                     maxHei = 1180
                     indb = numpy.where(dataOut.heightList <= maxHei)
                     hei = indb[0][-1]
                     #print(dataOut.heightList)
                     factor = dataOut.nIncohInt
                     z = dataOut.data_spc[:,:,hei] / factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     #buffer = 10 * numpy.log10(z)
                     meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS))
                     #self.hei = hei
                     #self.heightList = dataOut.heightList
                     #self.DH = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step
                     #self.nProfiles = dataOut.nProfiles
                     data['Spectrogram_Profile'] = 10 * numpy.log10(z)
                     data['hei'] = hei
                     data['DH'] = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step
                     data['nProfiles'] = dataOut.nProfiles
                     #meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS]
                     '''
                     import matplotlib.pyplot as plt
                     plt.plot(10 * numpy.log10(z[0,:]))
                     plt.show()
                     from time import sleep
                     sleep(10)
                     '''
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.z = self.data[self.CODE]
                     self.y = self.data.xrange[0]
                     hei = self.data['hei'][-1]
                     DH = self.data['DH'][-1]
                     nProfiles = self.data['nProfiles'][-1]
                     self.ylabel = "Frequency (kHz)"
                     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.zmin = self.zmin if self.zmin else numpy.min(self.z)
                         self.zmax = self.zmax if self.zmax else numpy.max(self.z)
                         data = self.data[-1]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                         else:
-                            ax.collections.remove(ax.collections[0])
+                            ax.plt.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                     #self.titles.append('Spectrogram')
                     #self.titles.append('{} Channel {} \n H = {} km ({} - {})'.format(
                         #self.CODE.upper(), x, y[hei], y[hei],y[hei]+(DH*nProfiles)))
             class CoherencePlot(RTIPlot):
                 '''
                 Plot for Coherence data
                 '''
                 CODE = 'coh'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = len(self.data.pairs)
                     self.nplots = len(self.data.pairs)
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time'
                     self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1, 'right':0.95})
                     if self.CODE == 'coh':
                         self.cb_label = ''
                         self.titles = [
                             'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
                     else:
                         self.cb_label = 'Degrees'
                         self.titles = [
                             'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['coh'] = dataOut.getCoherence()
                     meta['pairs'] = dataOut.pairsList
                     return data, meta
             class PhasePlot(CoherencePlot):
                 '''
                 Plot for Phase map data
                 '''
                 CODE = 'phase'
                 colormap = 'seismic'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['phase'] = dataOut.getCoherence(phase=True)
                     meta['pairs'] = dataOut.pairsList
                     return data, meta
             class NoisePlot(Plot):
                 '''
                 Plot for noise
                 '''
                 CODE = 'noise'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Intensity [dB]'
                     self.xlabel = 'Time'
                     self.titles = ['Noise']
                     self.colorbar = False
                     self.plots_adjust.update({'right': 0.85 })
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor).reshape(dataOut.nChannels, 1)
                     meta['yrange'] = numpy.array([])
                     return data, meta
                 def plot(self):
                     x = self.data.times
                     xmin = self.data.min_time
                     xmax = xmin + self.xrange * 60 * 60
                     Y = self.data['noise']
                     if self.axes[0].firsttime:
                         self.ymin = numpy.nanmin(Y) - 5
                         self.ymax = numpy.nanmax(Y) + 5
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
                         plt.legend(bbox_to_anchor=(1.18, 1.0))
                     else:
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].lines[ch].set_data(x, y)
                     self.ymin = numpy.nanmin(Y) - 5
                     self.ymax = numpy.nanmax(Y) + 10
             class PowerProfilePlot(Plot):
                 CODE = 'pow_profile'
                 plot_type = 'scatter'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.height = 4
                     self.width = 3
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Intensity [dB]'
                     self.titles = ['Power Profile']
                     self.colorbar = False
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data[self.CODE] = dataOut.getPower()
                     return data, meta
                 def plot(self):
                     y = self.data.yrange
                     self.y = y
                     x = self.data[-1][self.CODE]
                     if self.xmin is None: self.xmin = numpy.nanmin(x) * 0.9
                     if self.xmax is None: self.xmax = numpy.nanmax(x) * 1.1
                     if self.axes[0].firsttime:
                         for ch in self.data.channels:
                             self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch))
                         plt.legend()
                     else:
                         for ch in self.data.channels:
                             self.axes[0].lines[ch].set_data(x[ch], y)
             class SpectraCutPlot(Plot):
                 CODE = 'spc_cut'
                 plot_type = 'scatter'
                 buffering = False
                 def setup(self):
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.width = 3.4 * self.ncols + 1.5
                     self.height = 3 * self.nrows
                     self.ylabel = 'Power [dB]'
                     self.colorbar = False
                     self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.75, 'bottom':0.08})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = 10 * numpy.log10(dataOut.data_pre[0] / dataOut.normFactor)
                     data['spc'] = spc
                     meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS))
                     if self.CODE == 'cut_gaussian_fit':
                         data['gauss_fit0'] = 10 * numpy.log10(dataOut.GaussFit0 / dataOut.normFactor)
                         data['gauss_fit1'] = 10 * numpy.log10(dataOut.GaussFit1 / dataOut.normFactor)
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0][1:]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2][:-1]
                         self.xlabel = "Velocity (m/s)"
                     if self.CODE == 'cut_gaussian_fit':
                         x = self.data.xrange[2][:-1]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     data = self.data[-1]
                     z = data['spc']
                     if self.height_index:
                         index = numpy.array(self.height_index)
                     else:
                         index = numpy.arange(0, len(y), int((len(y)) / 9))
                     for n, ax in enumerate(self.axes):
                         if self.CODE == 'cut_gaussian_fit':
                             gau0 = data['gauss_fit0']
                             gau1 = data['gauss_fit1']
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.ymin = self.ymin if self.ymin else numpy.nanmin(z[:,:,index])
                             self.ymax = self.ymax if self.ymax else numpy.nanmax(z[:,:,index])
                             ax.plt = ax.plot(x, z[n, :, index].T, lw=0.25)
                             if self.CODE == 'cut_gaussian_fit':
                                 ax.plt_gau0 = ax.plot(x, gau0[n, :, index].T, lw=1, linestyle='-.')
                                 for i, line in enumerate(ax.plt_gau0):
                                     line.set_color(ax.plt[i].get_color())
                                 ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--')
                                 for i, line in enumerate(ax.plt_gau1):
                                     line.set_color(ax.plt[i].get_color())
                             labels = ['Range = {:2.1f}km'.format(y[i]) for i in index]
                             self.figures[0].legend(ax.plt, labels, loc='center right')
                         else:
                             for i, line in enumerate(ax.plt):
                                 line.set_data(x, z[n, :, index[i]].T)
                             for i, line in enumerate(ax.plt_gau0):
                                 line.set_data(x, gau0[n, :, index[i]].T)
                                 line.set_color(ax.plt[i].get_color())
                             for i, line in enumerate(ax.plt_gau1):
                                 line.set_data(x, gau1[n, :, index[i]].T)
                                 line.set_color(ax.plt[i].get_color())
                         self.titles.append('CH {}'.format(n))
             class BeaconPhase(Plot):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'beacon_phase'
                 def __init__(self):
                     Plot.__init__(self)
                     self.timerange = 24 * 60 * 60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 800
                     self.HEIGHT = 400
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = BEACON_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.filename_phase = None
                     self.figfile = None
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 7
                     colspan = 6
                     self.__nsubplots = 2
                     self.createFigure(id=id,
                                       wintitle=wintitle,
                                       widthplot=self.WIDTH + self.WIDTHPROF,
                                       heightplot=self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     self.addAxes(nrow, ncol * ncolspan, 0, 0, colspan, 1)
                 def save_phase(self, filename_phase):
                     f = open(filename_phase, 'w+')
                     f.write('\n\n')
                     f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n')
                     f.write('DD MM YYYY  HH MM SS   pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n')
                     f.close()
                 def save_data(self, filename_phase, data, data_datetime):
                     f = open(filename_phase, 'a')
                     timetuple_data = data_datetime.timetuple()
                     day = str(timetuple_data.tm_mday)
                     month = str(timetuple_data.tm_mon)
                     year = str(timetuple_data.tm_year)
                     hour = str(timetuple_data.tm_hour)
                     minute = str(timetuple_data.tm_min)
                     second = str(timetuple_data.tm_sec)
                     f.write(day + ' ' + month + ' ' + year + '  ' + hour + ' ' + minute + ' ' + second + '   ' + str(data[0]) + '   ' + str(data[1]) + '   ' + str(data[2]) + '   ' + str(data[3]) + '\n')
                     f.close()
                 def plot(self):
                     log.warning('TODO: Not yet implemented...')
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None,
                         timerange=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if dataOut.flagNoData:
                         return dataOut
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList[:10]
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" % (pair))
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if pairsIndexList == []:
                         return
              #         if len(pairsIndexList) > 4:
              #             pairsIndexList = pairsIndexList[0:4]
                     hmin_index = None
                     hmax_index = None
                     if hmin != None and hmax != None:
                         indexes = numpy.arange(dataOut.nHeights)
                         hmin_list = indexes[dataOut.heightList >= hmin]
                         hmax_list = indexes[dataOut.heightList <= hmax]
                         if hmin_list.any():
                             hmin_index = hmin_list[0]
                         if hmax_list.any():
                             hmax_index = hmax_list[-1] + 1
                     x = dataOut.getTimeRange()
                     thisDatetime = dataOut.datatime
                     title = wintitle + " Signal Phase"  # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase (degrees)"
                     update_figfile = False
                     nplots = len(pairsIndexList)
                     # phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = numpy.zeros(len(pairsIndexList))
                     for i in range(nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0)
                         powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0)
                         powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0)
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
                         phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real) * 180 / numpy.pi
                         if dataOut.beacon_heiIndexList:
                             phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList])
                         else:
                             phase_beacon[i] = numpy.average(phase)
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = 0
                         if ymax == None: ymax = 360
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         self.figfile = figfile
                         self.xdata = numpy.array([])
                         self.ydata = numpy.array([])
                         update_figfile = True
                         # open file beacon phase
                         path = '%s%03d' % (self.PREFIX, self.id)
                         beacon_file = os.path.join(path, '%s.txt' % self.name)
                         self.filename_phase = os.path.join(figpath, beacon_file)
                         # self.save_phase(self.filename_phase)
                     # store data beacon phase
                     # self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Plot %s" % (thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["Pair (%d,%d)" % (pair[0], pair[1]) for pair in dataOut.pairsList]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata) == 0:
                         self.ydata = phase_beacon.reshape(-1, 1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1, 1)))
                     axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
                                 XAxisAsTime=True, grid='both'
                                 )
                     self.draw()
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     return dataOut

schainpy/model/graphics/jroplot_voltage_lags.py +6 -6

             import os
             import time
             import math
             import datetime
             import numpy
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator  #YONG
             from .jroplot_spectra import RTIPlot, NoisePlot
             from schainpy.utils import log
             from .plotting_codes import *
             from schainpy.model.graphics.jroplot_base import Plot, plt
             import matplotlib.pyplot as plt
             import matplotlib.colors as colors
             from matplotlib.ticker import MultipleLocator, LogLocator, NullFormatter
             class RTIDPPlot(RTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''Plot for RTI Double Pulse Experiment Using Cross Products Analysis
                 '''
                 CODE = 'RTIDP'
                 colormap = 'jro'
                 plot_name = 'RTI'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 3
                     self.nplots = self.nrows
                     #self.height=10
                     if self.showSNR:
                         self.nrows += 1
                         self.nplots += 1
                     self.ylabel = 'Height [km]'
                     self.xlabel = 'Time (LT)'
                     self.cb_label = 'Intensity (dB)'
                     self.titles = ['{} Channel {}'.format(
                         self.plot_name.upper(), '0x1'),'{} Channel {}'.format(
                             self.plot_name.upper(), '0'),'{} Channel {}'.format(
                                 self.plot_name.upper(), '1')]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data[self.CODE] = dataOut.data_for_RTI_DP
                     data['NRANGE'] = dataOut.NDP
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.y = self.data.yrange[0: self.data['NRANGE']]
                     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[1][0,12:40])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[1][0,12:40])
                         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.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
             class RTILPPlot(RTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for RTI Long Pulse Using Cross Products Analysis
                 '''
                 CODE = 'RTILP'
                 colormap = 'jro'
                 plot_name = 'RTI LP'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 2
                     self.nplots = self.nrows
                     if self.showSNR:
                         self.nrows += 1
                         self.nplots += 1
                     self.ylabel = 'Height [km]'
                     self.xlabel = 'Time (LT)'
                     self.cb_label = 'Intensity (dB)'
                     self.titles = ['{} Channel {}'.format(
                         self.plot_name.upper(), '0'),'{} Channel {}'.format(
                             self.plot_name.upper(), '1'),'{} Channel {}'.format(
                                 self.plot_name.upper(), '2'),'{} Channel {}'.format(
                                     self.plot_name.upper(), '3')]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['rti'] = dataOut.data_for_RTI_LP
                     data['NRANGE'] = dataOut.NRANGE
                     return data, meta
                 def plot(self):
                     NRANGE = self.data['NRANGE'][-1]
                     self.x = self.data.times
                     self.y = self.data.yrange[0:NRANGE]
                     self.z = self.data['rti']
                     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[1][0,12:40])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[1][0,12:40])
                         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]
                                                    )
                             #plt.tight_layout()
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
-                            ax.collections.remove(ax.collections[0])
+                            ax.plt.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
                             #plt.tight_layout()
             class DenRTIPlot(RTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    RTI Plot for Electron Densities
                 '''
                 CODE = 'denrti'
                 colormap = 'jet'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = self.data.shape(self.CODE)[0]
                     self.nplots = self.nrows
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time (LT)'
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     if self.CODE == 'denrti':
                         self.cb_label = r'$\mathrm{N_e}$ Electron Density ($\mathrm{1/cm^3}$)'
                     self.titles = ['Electron Density RTI']
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['denrti'] = dataOut.DensityFinal*1.e-6 #To Plot in cm^-3
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.y = self.data.yrange
                     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]
                             if numpy.log10(self.zmin)<0:
                                 self.zmin=1
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n],
                                                    norm=colors.LogNorm()
                                                    )
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
-                            ax.collections.remove(ax.collections[0])
+                            ax.plt.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n],
                                                    norm=colors.LogNorm()
                                                    )
             class ETempRTIPlot(RTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for Electron Temperature
                 '''
                 CODE = 'ETemp'
                 colormap = 'jet'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = self.data.shape(self.CODE)[0]
                     self.nplots = self.nrows
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time (LT)'
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     if self.CODE == 'ETemp':
                         self.cb_label = 'Electron Temperature (K)'
                         self.titles = ['Electron Temperature RTI']
                     if self.CODE == 'ITemp':
                         self.cb_label = 'Ion Temperature (K)'
                         self.titles = ['Ion Temperature RTI']
                     if self.CODE == 'HeFracLP':
                         self.cb_label ='He+ Fraction'
                         self.titles = ['He+ Fraction RTI']
                         self.zmax=0.16
                     if self.CODE == 'HFracLP':
                         self.cb_label ='H+ Fraction'
                         self.titles = ['H+ Fraction RTI']
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['ETemp'] = dataOut.ElecTempFinal
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.y = self.data.yrange
                     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]
                                                    )
                             #plt.tight_layout()
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
-                            ax.collections.remove(ax.collections[0])
+                            ax.plt.remove()
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
             class ITempRTIPlot(ETempRTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for Ion Temperature
                 '''
                 CODE = 'ITemp'
                 colormap = 'jet'
                 plot_name = 'Ion Temperature'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['ITemp'] = dataOut.IonTempFinal
                     return data, meta
             class HFracRTIPlot(ETempRTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for H+ LP
                 '''
                 CODE = 'HFracLP'
                 colormap = 'jet'
                 plot_name = 'H+ Frac'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['HFracLP'] = dataOut.PhyFinal
                     return data, meta
             class HeFracRTIPlot(ETempRTIPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for He+ LP
                 '''
                 CODE = 'HeFracLP'
                 colormap = 'jet'
                 plot_name = 'He+ Frac'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['HeFracLP'] = dataOut.PheFinal
                     return data, meta
             class TempsDPPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for Electron - Ion Temperatures
                 '''
                 CODE = 'tempsDP'
                 #plot_name = 'Temperatures'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Temperature (K)'
                     self.titles = ['Electron/Ion Temperatures']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['Te'] = dataOut.te2
                     data['Ti'] = dataOut.ti2
                     data['Te_error'] = dataOut.ete2
                     data['Ti_error'] = dataOut.eti2
                     meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS]
                     return data, meta
                 def plot(self):
                     y = self.data.yrange
                     self.xmin = -100
                     self.xmax = 5000
                     ax = self.axes[0]
                     data = self.data[-1]
                     Te = data['Te']
                     Ti = data['Ti']
                     errTe = data['Te_error']
                     errTi = data['Ti_error']
                     if ax.firsttime:
                         ax.errorbar(Te, y, xerr=errTe, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(Ti, y, fmt='k^', xerr=errTi,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         self.ystep_given = 50
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
                     else:
                         self.clear_figures()
                         ax.errorbar(Te, y, xerr=errTe, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(Ti, y, fmt='k^', xerr=errTi,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
             class TempsHPPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for Temperatures Hybrid Experiment
                 '''
                 CODE = 'temps_LP'
                 #plot_name = 'Temperatures'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Temperature (K)'
                     self.titles = ['Electron/Ion Temperatures']
                     self.width = 3.5
                     self.height = 6.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['Te'] = numpy.concatenate((dataOut.te2[:dataOut.cut],dataOut.te[dataOut.cut:]))
                     data['Ti'] = numpy.concatenate((dataOut.ti2[:dataOut.cut],dataOut.ti[dataOut.cut:]))
                     data['Te_error'] = numpy.concatenate((dataOut.ete2[:dataOut.cut],dataOut.ete[dataOut.cut:]))
                     data['Ti_error'] = numpy.concatenate((dataOut.eti2[:dataOut.cut],dataOut.eti[dataOut.cut:]))
                     meta['yrange'] = dataOut.heightList[0:dataOut.NACF]
                     return data, meta
                 def plot(self):
                     self.y = self.data.yrange
                     self.xmin = -100
                     self.xmax = 4500
                     ax = self.axes[0]
                     data = self.data[-1]
                     Te = data['Te']
                     Ti = data['Ti']
                     errTe = data['Te_error']
                     errTi = data['Ti_error']
                     if ax.firsttime:
                         ax.errorbar(Te, self.y, xerr=errTe, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(Ti, self.y, fmt='k^', xerr=errTi,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         self.ystep_given = 200
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
                     else:
                         self.clear_figures()
                         ax.errorbar(Te, self.y, xerr=errTe, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(Ti, self.y, fmt='k^', xerr=errTi,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
             class FracsHPPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for Composition LP
                 '''
                 CODE = 'fracs_LP'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Frac'
                     self.titles = ['Composition']
                     self.width = 3.5
                     self.height = 6.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     #aux_nan=numpy.zeros(dataOut.cut,'float32')
                     #aux_nan[:]=numpy.nan
                     #data['ph'] = numpy.concatenate((aux_nan,dataOut.ph[dataOut.cut:]))
                     #data['eph'] = numpy.concatenate((aux_nan,dataOut.eph[dataOut.cut:]))
                     data['ph'] = dataOut.ph[dataOut.cut:]
                     data['eph'] = dataOut.eph[dataOut.cut:]
                     data['phe'] = dataOut.phe[dataOut.cut:]
                     data['ephe'] = dataOut.ephe[dataOut.cut:]
                     data['cut'] = dataOut.cut
                     meta['yrange'] = dataOut.heightList[0:dataOut.NACF]
                     return data, meta
                 def plot(self):
                     data = self.data[-1]
                     ph = data['ph']
                     eph = data['eph']
                     phe = data['phe']
                     ephe = data['ephe']
                     cut = data['cut']
                     self.y = self.data.yrange
                     self.xmin = 0
                     self.xmax = 1
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.errorbar(ph, self.y[cut:], xerr=eph, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='H+')
                         ax.errorbar(phe, self.y[cut:], fmt='k^', xerr=ephe,elinewidth=1.0,color='b',linewidth=2.0, label='He+')
                         plt.legend(loc='lower right')
                         self.xstep_given = 0.2
                         self.ystep_given = 200
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
                     else:
                         self.clear_figures()
                         ax.errorbar(ph, self.y[cut:], xerr=eph, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='H+')
                         ax.errorbar(phe, self.y[cut:], fmt='k^', xerr=ephe,elinewidth=1.0,color='b',linewidth=2.0, label='He+')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
             class EDensityPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for electron density
                 '''
                 CODE = 'den'
                 #plot_name = 'Electron Density'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = r'$\mathrm{N_e}$ Electron Density ($\mathrm{1/cm^3}$)'
                     self.titles = ['Electron Density']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['den_power'] = dataOut.ph2[:dataOut.NSHTS]
                     data['den_Faraday'] = dataOut.dphi[:dataOut.NSHTS]
                     data['den_error'] = dataOut.sdp2[:dataOut.NSHTS]
                     #data['err_Faraday'] = dataOut.sdn1[:dataOut.NSHTS]
                     #print(numpy.shape(data['den_power']))
                     #print(numpy.shape(data['den_Faraday']))
                     #print(numpy.shape(data['den_error']))
                     data['NSHTS'] = dataOut.NSHTS
                     meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS]
                     return data, meta
                 def plot(self):
                     y = self.data.yrange
                     #self.xmin = 1e3
                     #self.xmax = 1e7
                     ax = self.axes[0]
                     data = self.data[-1]
                     DenPow = data['den_power']
                     DenFar = data['den_Faraday']
                     errDenPow = data['den_error']
                     #errFaraday = data['err_Faraday']
                     NSHTS = data['NSHTS']
                     if self.CODE == 'denLP':
                         DenPowLP = data['den_LP']
                         errDenPowLP = data['den_LP_error']
                         cut = data['cut']
                     if ax.firsttime:
                         self.autoxticks=False
                         #ax.errorbar(DenFar, y[:NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         ax.errorbar(DenFar, y[:NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday',markersize=2,linestyle='-')
                         #ax.errorbar(DenPow, y[:NSHTS], fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                         ax.errorbar(DenPow, y[:NSHTS], fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power',markersize=2,linestyle='-')
                         if self.CODE=='denLP':
                             ax.errorbar(DenPowLP[cut:], y[cut:], xerr=errDenPowLP[cut:], fmt='r^-',elinewidth=1.0,color='r',linewidth=1.0, label='LP Profile',markersize=2)
                         plt.legend(loc='upper left',fontsize=8.5)
                         #plt.legend(loc='lower left',fontsize=8.5)
                         ax.set_xscale("log", nonposx='clip')
                         grid_y_ticks=numpy.arange(numpy.nanmin(y),numpy.nanmax(y),50)
                         self.ystep_given=100
                         if self.CODE=='denLP':
                             self.ystep_given=200
                         ax.set_yticks(grid_y_ticks,minor=True)
                         locmaj = LogLocator(base=10,numticks=12)
                         ax.xaxis.set_major_locator(locmaj)
                         locmin = LogLocator(base=10.0,subs=(0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9),numticks=12)
                         ax.xaxis.set_minor_locator(locmin)
                         ax.xaxis.set_minor_formatter(NullFormatter())
                         ax.grid(which='minor')
                     else:
                         dataBefore = self.data[-2]
                         DenPowBefore = dataBefore['den_power']
                         self.clear_figures()
                         #ax.errorbar(DenFar, y[:NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         ax.errorbar(DenFar, y[:NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday',markersize=2,linestyle='-')
                         #ax.errorbar(DenPow, y[:NSHTS], fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                         ax.errorbar(DenPow, y[:NSHTS], fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power',markersize=2,linestyle='-')
                         ax.errorbar(DenPowBefore, y[:NSHTS], elinewidth=1.0,color='r',linewidth=0.5,linestyle="dashed")
                         if self.CODE=='denLP':
                             ax.errorbar(DenPowLP[cut:], y[cut:], fmt='r^-', xerr=errDenPowLP[cut:],elinewidth=1.0,color='r',linewidth=1.0, label='LP Profile',markersize=2)
                         ax.set_xscale("log", nonposx='clip')
                         grid_y_ticks=numpy.arange(numpy.nanmin(y),numpy.nanmax(y),50)
                         ax.set_yticks(grid_y_ticks,minor=True)
                         locmaj = LogLocator(base=10,numticks=12)
                         ax.xaxis.set_major_locator(locmaj)
                         locmin = LogLocator(base=10.0,subs=(0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9),numticks=12)
                         ax.xaxis.set_minor_locator(locmin)
                         ax.xaxis.set_minor_formatter(NullFormatter())
                         ax.grid(which='minor')
                         plt.legend(loc='upper left',fontsize=8.5)
                         #plt.legend(loc='lower left',fontsize=8.5)
             class RelativeDenPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for electron density
                 '''
                 CODE = 'den'
                 #plot_name = 'Electron Density'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = r'$\mathrm{N_e}$ Relative Electron Density ($\mathrm{1/cm^3}$)'
                     self.titles = ['Electron Density']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['den_power'] = dataOut.ph2
                     data['den_error'] = dataOut.sdp2
                     meta['yrange'] = dataOut.heightList
                     return data, meta
                 def plot(self):
                     y = self.data.yrange
                     ax = self.axes[0]
                     data = self.data[-1]
                     DenPow = data['den_power']
                     errDenPow = data['den_error']
                     if ax.firsttime:
                         self.autoxticks=False
                         ax.errorbar(DenPow, y, fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power',markersize=2,linestyle='-')
                         plt.legend(loc='upper left',fontsize=8.5)
                         #plt.legend(loc='lower left',fontsize=8.5)
                         ax.set_xscale("log", nonposx='clip')
                         grid_y_ticks=numpy.arange(numpy.nanmin(y),numpy.nanmax(y),50)
                         self.ystep_given=100
                         ax.set_yticks(grid_y_ticks,minor=True)
                         locmaj = LogLocator(base=10,numticks=12)
                         ax.xaxis.set_major_locator(locmaj)
                         locmin = LogLocator(base=10.0,subs=(0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9),numticks=12)
                         ax.xaxis.set_minor_locator(locmin)
                         ax.xaxis.set_minor_formatter(NullFormatter())
                         ax.grid(which='minor')
                     else:
                         dataBefore = self.data[-2]
                         DenPowBefore = dataBefore['den_power']
                         self.clear_figures()
                         ax.errorbar(DenPow, y, fmt='k^-', xerr=errDenPow,elinewidth=1.0,color='b',linewidth=1.0, label='Power',markersize=2,linestyle='-')
                         ax.errorbar(DenPowBefore, y, elinewidth=1.0,color='r',linewidth=0.5,linestyle="dashed")
                         ax.set_xscale("log", nonposx='clip')
                         grid_y_ticks=numpy.arange(numpy.nanmin(y),numpy.nanmax(y),50)
                         ax.set_yticks(grid_y_ticks,minor=True)
                         locmaj = LogLocator(base=10,numticks=12)
                         ax.xaxis.set_major_locator(locmaj)
                         locmin = LogLocator(base=10.0,subs=(0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9),numticks=12)
                         ax.xaxis.set_minor_locator(locmin)
                         ax.xaxis.set_minor_formatter(NullFormatter())
                         ax.grid(which='minor')
                         plt.legend(loc='upper left',fontsize=8.5)
                         #plt.legend(loc='lower left',fontsize=8.5)
             class FaradayAnglePlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for electron density
                 '''
                 CODE = 'angle'
                 plot_name = 'Faraday Angle'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Faraday Angle (º)'
                     self.titles = ['Electron Density']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['angle'] = numpy.degrees(dataOut.phi)
                     #'''
                     #print(dataOut.phi_uwrp)
                     #print(data['angle'])
                     #exit(1)
                     #'''
                     data['dphi'] = dataOut.dphi_uc*10
                     #print(dataOut.dphi)
                     #data['NSHTS'] = dataOut.NSHTS
                     #meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS]
                     return data, meta
                 def plot(self):
                     data = self.data[-1]
                     self.x = data[self.CODE]
                     dphi = data['dphi']
                     self.y = self.data.yrange
                     self.xmin = -360#-180
                     self.xmax = 360#180
                     ax = self.axes[0]
                     if ax.firsttime:
                         self.autoxticks=False
                         #if self.CODE=='den':
                         ax.plot(self.x, self.y,marker='o',color='g',linewidth=1.0,markersize=2)
                         ax.plot(dphi, self.y,marker='o',color='blue',linewidth=1.0,markersize=2)
                         grid_y_ticks=numpy.arange(numpy.nanmin(self.y),numpy.nanmax(self.y),50)
                         self.ystep_given=100
                         if self.CODE=='denLP':
                             self.ystep_given=200
                         ax.set_yticks(grid_y_ticks,minor=True)
                         ax.grid(which='minor')
                         #plt.tight_layout()
                     else:
                         self.clear_figures()
                         #if self.CODE=='den':
                         #print(numpy.shape(self.x))
                         ax.plot(self.x, self.y, marker='o',color='g',linewidth=1.0, markersize=2)
                         ax.plot(dphi, self.y,marker='o',color='blue',linewidth=1.0,markersize=2)
                         grid_y_ticks=numpy.arange(numpy.nanmin(self.y),numpy.nanmax(self.y),50)
                         ax.set_yticks(grid_y_ticks,minor=True)
                         ax.grid(which='minor')
             class EDensityHPPlot(EDensityPlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                    Plot for Electron Density Hybrid Experiment
                 '''
                 CODE = 'denLP'
                 plot_name = 'Electron Density'
                 plot_type = 'scatterbuffer'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['den_power'] = dataOut.ph2[:dataOut.NSHTS]
                     data['den_Faraday']=dataOut.dphi[:dataOut.NSHTS]
                     data['den_error']=dataOut.sdp2[:dataOut.NSHTS]
                     data['den_LP']=dataOut.ne[:dataOut.NACF]
                     data['den_LP_error']=dataOut.ene[:dataOut.NACF]*dataOut.ne[:dataOut.NACF]*0.434
                     #self.ene=10**dataOut.ene[:dataOut.NACF]
                     data['NSHTS']=dataOut.NSHTS
                     data['cut']=dataOut.cut
                     return data, meta
             class ACFsPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for ACFs Double Pulse Experiment
                 '''
                 CODE = 'acfs'
                 #plot_name = 'ACF'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Lag (ms)'
                     self.titles = ['ACFs']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['ACFs'] = dataOut.acfs_to_plot
                     data['ACFs_error'] = dataOut.acfs_error_to_plot
                     data['lags'] = dataOut.lags_to_plot
                     data['Lag_contaminated_1'] = dataOut.x_igcej_to_plot
                     data['Lag_contaminated_2'] = dataOut.x_ibad_to_plot
                     data['Height_contaminated_1'] = dataOut.y_igcej_to_plot
                     data['Height_contaminated_2'] = dataOut.y_ibad_to_plot
                     meta['yrange'] = numpy.array([])
                     #meta['NSHTS'] = dataOut.NSHTS
                     #meta['DPL'] = dataOut.DPL
                     data['NSHTS'] = dataOut.NSHTS #This is metadata
                     data['DPL'] = dataOut.DPL #This is metadata
                     return data, meta
                 def plot(self):
                     data = self.data[-1]
                     #NSHTS = self.meta['NSHTS']
                     #DPL = self.meta['DPL']
                     NSHTS = data['NSHTS'] #This is metadata
                     DPL = data['DPL'] #This is metadata
                     lags = data['lags']
                     ACFs = data['ACFs']
                     errACFs = data['ACFs_error']
                     BadLag1 = data['Lag_contaminated_1']
                     BadLag2 = data['Lag_contaminated_2']
                     BadHei1 = data['Height_contaminated_1']
                     BadHei2 = data['Height_contaminated_2']
                     self.xmin = 0.0
                     self.xmax = 2.0
                     self.y = ACFs
                     ax = self.axes[0]
                     if ax.firsttime:
                         for i in range(NSHTS):
                             x_aux = numpy.isfinite(lags[i,:])
                             y_aux = numpy.isfinite(ACFs[i,:])
                             yerr_aux = numpy.isfinite(errACFs[i,:])
                             x_igcej_aux = numpy.isfinite(BadLag1[i,:])
                             y_igcej_aux = numpy.isfinite(BadHei1[i,:])
                             x_ibad_aux = numpy.isfinite(BadLag2[i,:])
                             y_ibad_aux = numpy.isfinite(BadHei2[i,:])
                             if lags[i,:][~numpy.isnan(lags[i,:])].shape[0]>2:
                                 ax.errorbar(lags[i,x_aux], ACFs[i,y_aux], yerr=errACFs[i,x_aux],color='b',marker='o',linewidth=1.0,markersize=2)
                             ax.plot(BadLag1[i,x_igcej_aux],BadHei1[i,y_igcej_aux],'x',color='red',markersize=2)
                             ax.plot(BadLag2[i,x_ibad_aux],BadHei2[i,y_ibad_aux],'X',color='red',markersize=2)
                         self.xstep_given = (self.xmax-self.xmin)/(DPL-1)
                         self.ystep_given = 50
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
                     else:
                         self.clear_figures()
                         for i in range(NSHTS):
                             x_aux = numpy.isfinite(lags[i,:])
                             y_aux = numpy.isfinite(ACFs[i,:])
                             yerr_aux = numpy.isfinite(errACFs[i,:])
                             x_igcej_aux = numpy.isfinite(BadLag1[i,:])
                             y_igcej_aux = numpy.isfinite(BadHei1[i,:])
                             x_ibad_aux = numpy.isfinite(BadLag2[i,:])
                             y_ibad_aux = numpy.isfinite(BadHei2[i,:])
                             if lags[i,:][~numpy.isnan(lags[i,:])].shape[0]>2:
                                 ax.errorbar(lags[i,x_aux], ACFs[i,y_aux], yerr=errACFs[i,x_aux],linewidth=1.0,markersize=2,color='b',marker='o')
                             ax.plot(BadLag1[i,x_igcej_aux],BadHei1[i,y_igcej_aux],'x',color='red',markersize=2)
                             ax.plot(BadLag2[i,x_ibad_aux],BadHei2[i,y_ibad_aux],'X',color='red',markersize=2)
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
             class ACFsLPPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for ACFs Double Pulse Experiment
                 '''
                 CODE = 'acfs_LP'
                 #plot_name = 'ACF'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Lag (ms)'
                     self.titles = ['ACFs']
                     self.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     aux=numpy.zeros((dataOut.NACF,dataOut.IBITS),'float32')
                     errors=numpy.zeros((dataOut.NACF,dataOut.IBITS),'float32')
                     lags_LP_to_plot=numpy.zeros((dataOut.NACF,dataOut.IBITS),'float32')
                     for i in range(dataOut.NACF):
                         for j in range(dataOut.IBITS):
                             if numpy.abs(dataOut.errors[j,i]/dataOut.output_LP_integrated.real[0,i,0])<1.0:
                                 aux[i,j]=dataOut.output_LP_integrated.real[j,i,0]/dataOut.output_LP_integrated.real[0,i,0]
                                 aux[i,j]=max(min(aux[i,j],1.0),-1.0)*dataOut.DH+dataOut.heightList[i]
                                 lags_LP_to_plot[i,j]=dataOut.lags_LP[j]
                                 errors[i,j]=dataOut.errors[j,i]/dataOut.output_LP_integrated.real[0,i,0]*dataOut.DH
                             else:
                                 aux[i,j]=numpy.nan
                                 lags_LP_to_plot[i,j]=numpy.nan
                                 errors[i,j]=numpy.nan
                     data['ACFs'] = aux
                     data['ACFs_error'] = errors
                     data['lags'] = lags_LP_to_plot
                     meta['yrange'] = numpy.array([])
                     #meta['NACF'] = dataOut.NACF
                     #meta['NLAG'] = dataOut.NLAG
                     data['NACF'] = dataOut.NACF #This is metadata
                     data['NLAG'] = dataOut.NLAG #This is metadata
                     return data, meta
                 def plot(self):
                     data = self.data[-1]
                     #NACF = self.meta['NACF']
                     #NLAG = self.meta['NLAG']
                     NACF = data['NACF'] #This is metadata
                     NLAG = data['NLAG'] #This is metadata
                     lags = data['lags']
                     ACFs = data['ACFs']
                     errACFs = data['ACFs_error']
                     self.xmin = 0.0
                     self.xmax = 1.5
                     self.y = ACFs
                     ax = self.axes[0]
                     if ax.firsttime:
                         for i in range(NACF):
                             x_aux = numpy.isfinite(lags[i,:])
                             y_aux = numpy.isfinite(ACFs[i,:])
                             yerr_aux = numpy.isfinite(errACFs[i,:])
                             if lags[i,:][~numpy.isnan(lags[i,:])].shape[0]>2:
                                 ax.errorbar(lags[i,x_aux], ACFs[i,y_aux], yerr=errACFs[i,x_aux],color='b',linewidth=1.0,markersize=2,ecolor='r')
                         #self.xstep_given = (self.xmax-self.xmin)/(self.data.NLAG-1)
                         self.xstep_given=0.3
                         self.ystep_given = 200
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         ax.grid(which='minor')
                     else:
                         self.clear_figures()
                         for i in range(NACF):
                             x_aux = numpy.isfinite(lags[i,:])
                             y_aux = numpy.isfinite(ACFs[i,:])
                             yerr_aux = numpy.isfinite(errACFs[i,:])
                             if lags[i,:][~numpy.isnan(lags[i,:])].shape[0]>2:
                                 ax.errorbar(lags[i,x_aux], ACFs[i,y_aux], yerr=errACFs[i,x_aux],color='b',linewidth=1.0,markersize=2,ecolor='r')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
             class CrossProductsPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for cross products
                 '''
                 CODE = 'crossprod'
                 plot_name = 'Cross Products'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 3
                     self.nrows = 1
                     self.nplots = 3
                     self.ylabel = 'Range [km]'
                     self.width = 3.5*self.nplots
                     self.height = 5.5
                     self.colorbar = False
                     self.titles = []
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['crossprod'] = dataOut.crossprods
                     data['NDP'] = dataOut.NDP
                     return data, meta
                 def plot(self):
                     self.x = self.data['crossprod'][:,-1,:,:,:,:]
                     self.y = self.data.heights[0:self.data['NDP']]
                     for n, ax in enumerate(self.axes):
                         self.xmin=numpy.min(numpy.concatenate((self.x[n][0,20:30,0,0],self.x[n][1,20:30,0,0],self.x[n][2,20:30,0,0],self.x[n][3,20:30,0,0])))
                         self.xmax=numpy.max(numpy.concatenate((self.x[n][0,20:30,0,0],self.x[n][1,20:30,0,0],self.x[n][2,20:30,0,0],self.x[n][3,20:30,0,0])))
                         if ax.firsttime:
                             self.autoxticks=False
                             if n==0:
                                 label1='kax'
                                 label2='kay'
                                 label3='kbx'
                                 label4='kby'
                                 self.xlimits=[(self.xmin,self.xmax)]
                             elif n==1:
                                 label1='kax2'
                                 label2='kay2'
                                 label3='kbx2'
                                 label4='kby2'
                                 self.xlimits.append((self.xmin,self.xmax))
                             elif n==2:
                                 label1='kaxay'
                                 label2='kbxby'
                                 label3='kaxbx'
                                 label4='kaxby'
                                 self.xlimits.append((self.xmin,self.xmax))
                             ax.plotline1 = ax.plot(self.x[n][0,:,0,0], self.y, color='r',linewidth=2.0, label=label1)
                             ax.plotline2 = ax.plot(self.x[n][1,:,0,0], self.y, color='k',linewidth=2.0, label=label2)
                             ax.plotline3 = ax.plot(self.x[n][2,:,0,0], self.y, color='b',linewidth=2.0, label=label3)
                             ax.plotline4 = ax.plot(self.x[n][3,:,0,0], self.y, color='m',linewidth=2.0, label=label4)
                             ax.legend(loc='upper right')
                             ax.set_xlim(self.xmin, self.xmax)
                             self.titles.append('{}'.format(self.plot_name.upper()))
                         else:
                             if n==0:
                                 self.xlimits=[(self.xmin,self.xmax)]
                             else:
                                 self.xlimits.append((self.xmin,self.xmax))
                             ax.set_xlim(self.xmin, self.xmax)
                             ax.plotline1[0].set_data(self.x[n][0,:,0,0],self.y)
                             ax.plotline2[0].set_data(self.x[n][1,:,0,0],self.y)
                             ax.plotline3[0].set_data(self.x[n][2,:,0,0],self.y)
                             ax.plotline4[0].set_data(self.x[n][3,:,0,0],self.y)
                             self.titles.append('{}'.format(self.plot_name.upper()))
             class CrossProductsLPPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for cross products LP
                 '''
                 CODE = 'crossprodslp'
                 plot_name = 'Cross Products LP'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 2
                     self.nrows = 1
                     self.nplots = 2
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'dB'
                     self.width = 3.5*self.nplots
                     self.height = 5.5
                     self.colorbar = False
                     self.titles = []
                     self.plots_adjust.update({'wspace': .8 ,'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['crossprodslp'] = 10*numpy.log10(numpy.abs(dataOut.output_LP))
                     data['NRANGE'] = dataOut.NRANGE #This is metadata
                     data['NLAG'] = dataOut.NLAG #This is metadata
                     return data, meta
                 def plot(self):
                     NRANGE = self.data['NRANGE'][-1]
                     NLAG = self.data['NLAG'][-1]
                     x = self.data[self.CODE][:,-1,:,:]
                     self.y = self.data.yrange[0:NRANGE]
                     label_array=numpy.array(['lag '+ str(x) for x in range(NLAG)])
                     color_array=['r','k','g','b','c','m','y','orange','steelblue','purple','peru','darksalmon','grey','limegreen','olive','midnightblue']
                     for n, ax in enumerate(self.axes):
                         self.xmin=28#30
                         self.xmax=70#70
                         #self.xmin=numpy.min(numpy.concatenate((self.x[0,:,n],self.x[1,:,n])))
                         #self.xmax=numpy.max(numpy.concatenate((self.x[0,:,n],self.x[1,:,n])))
                         if ax.firsttime:
                             self.autoxticks=False
                             if n == 0:
                                 self.plotline_array=numpy.zeros((2,NLAG),dtype=object)
                             for i in range(NLAG):
                                 self.plotline_array[n,i], = ax.plot(x[i,:,n], self.y, color=color_array[i],linewidth=1.0, label=label_array[i])
                             ax.legend(loc='upper right')
                             ax.set_xlim(self.xmin, self.xmax)
                             if n==0:
                                 self.titles.append('{} CH0'.format(self.plot_name.upper()))
                             if n==1:
                                 self.titles.append('{} CH1'.format(self.plot_name.upper()))
                         else:
                             for i in range(NLAG):
                                 self.plotline_array[n,i].set_data(x[i,:,n],self.y)
                             if n==0:
                                 self.titles.append('{} CH0'.format(self.plot_name.upper()))
                             if n==1:
                                 self.titles.append('{} CH1'.format(self.plot_name.upper()))
             class NoiseDPPlot(NoisePlot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for noise Double Pulse
                 '''
                 CODE = 'noise'
                 #plot_name = 'Noise'
                 #plot_type = 'scatterbuffer'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['noise'] = 10*numpy.log10(dataOut.noise_final)
                     return data, meta
             class XmitWaveformPlot(Plot):
                 '''
                 Written by R. Flores
                 '''
                 '''
                 Plot for xmit waveform
                 '''
                 CODE = 'xmit'
                 plot_name = 'Xmit Waveform'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = ''
                     self.xlabel = 'Number of Lag'
                     self.width = 5.5
                     self.height = 3.5
                     self.colorbar = False
                     self.plots_adjust.update({'right': 0.85 })
                     self.titles = [self.plot_name]
                     #self.plots_adjust.update({'left': 0.17, 'right': 0.88, 'bottom': 0.1})
                     #if not self.titles:
                         #self.titles = self.data.parameters \
                             #if self.data.parameters else ['{}'.format(self.plot_name.upper())]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     y_1=numpy.arctan2(dataOut.output_LP[:,0,2].imag,dataOut.output_LP[:,0,2].real)* 180 / (numpy.pi*10)
                     y_2=numpy.abs(dataOut.output_LP[:,0,2])
                     norm=numpy.max(y_2)
                     norm=max(norm,0.1)
                     y_2=y_2/norm
                     meta['yrange'] = numpy.array([])
                     data['xmit'] = numpy.vstack((y_1,y_2))
                     data['NLAG'] = dataOut.NLAG
                     return data, meta
                 def plot(self):
                     data = self.data[-1]
                     NLAG = data['NLAG']
                     x = numpy.arange(0,NLAG,1,'float32')
                     y = data['xmit']
                     self.xmin = 0
                     self.xmax = NLAG-1
                     self.ymin = -1.0
                     self.ymax = 1.0
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.plotline0=ax.plot(x,y[0,:],color='blue')
                         ax.plotline1=ax.plot(x,y[1,:],color='red')
                         secax=ax.secondary_xaxis(location=0.5)
                         secax.xaxis.tick_bottom()
                         secax.tick_params( labelleft=False, labeltop=False,
                                   labelright=False, labelbottom=False)
                         self.xstep_given = 3
                         self.ystep_given = .25
                         secax.set_xticks(numpy.linspace(self.xmin, self.xmax, 6)) #only works on matplotlib.version>3.2
                     else:
                         ax.plotline0[0].set_data(x,y[0,:])
                         ax.plotline1[0].set_data(x,y[1,:])

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