schain Commit - r1381:3afd912ddcce · Jicamarca Repository

First faraday ops review #TODO: fix plots

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schainpy/model/graphics/jroplot_spectra.py +31 -56

             # 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
             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()
                     data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     if self.CODE == 'spc_moments':
                         data['moments'] = dataOut.moments
-                        # data['spc'] = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor)
                     if self.CODE == 'gaussian_fit':
-                        # data['moments'] = dataOut.moments
                         data['gaussfit'] = dataOut.DGauFitParams
-                        # data['spc'] = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor)
                     return data, meta
                 def plot(self):
-                    #print(self.xaxis)
-                    #exit(1)
                     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']
                     self.CODE2 = 'spc_oblique'
                     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':
-                            # mean = data['moments'][n, 1]
                             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 -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
-                            #print(numpy.shape(x))
                             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:
                             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
                 '''
-                CODE = 'spc'
+                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(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
+                    data['shift1'] = dataOut.Oblique_params[0][1]
+                    data['shift2'] = dataOut.Oblique_params[0][4]
+                    data['shift1_error'] = dataOut.Oblique_param_errors[0][1]
+                    data['shift2_error'] = dataOut.Oblique_param_errors[0][4]
+                    return data, meta
                 def plot(self):
-                    #print(self.xaxis)
-                    #exit(1)
                     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':
-                        x = self.data.xrange[2]
-                        self.xlabel = "Velocity (m/s)"
                     self.titles = []
-                    #self.xlabel = "Velocidad (m/s)"
-                    #self.ylabel = 'Rango (km)'
-                    y = self.data.heights
+                    y = self.data.yrange
                     self.y = y
                     z = self.data['spc']
-                    self.CODE2 = 'spc_oblique'
                     for n, ax in enumerate(self.axes):
                         noise = self.data['noise'][n][-1]
-                        if self.CODE == 'spc_moments':
+                        shift1 = self.data['shift1']
-                            mean = self.data['moments'][n, :, 1, :][-1]
+                        shift2 = self.data['shift2']
-                        if self.CODE2 == 'spc_oblique':
+                        err1 = self.data['shift1_error']
-                            shift1 = self.data.shift1
+                        err2 = self.data['shift2_error']
-                            shift2 = self.data.shift2
                         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)
-                            #print(numpy.shape(x))
                             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]
-                            if self.CODE == 'spc_moments':
-                                ax.plt_mean = ax.plot(mean, y, color='k')[0]
+                            self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=0.2, marker='x', linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
+                            self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
-                            if self.CODE2 == 'spc_oblique':
-                                #ax.plt_shift1 = ax.plot(shift1, y, color='k', marker='x', linestyle='None', markersize=0.5)[0]
-                                #ax.plt_shift2 = ax.plot(shift2, y, color='m', marker='x', linestyle='None', markersize=0.5)[0]
-                                self.ploterr1 = ax.errorbar(shift1, y, xerr=self.data.shift1_error,fmt='k^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
-                                self.ploterr2 = ax.errorbar(shift2, y, xerr=self.data.shift2_error,fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
                         else:
                             self.ploterr1.remove()
                             self.ploterr2.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)
-                            if self.CODE == 'spc_moments':
+                                self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
-                                ax.plt_mean.set_data(mean, y)
+                                self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
-                            if self.CODE2 == 'spc_oblique':
-                                #ax.plt_shift1.set_data(shift1, y)
-                                #ax.plt_shift2.set_data(shift2, y)
-                                #ax.clf()
-                                self.ploterr1 = ax.errorbar(shift1, y, xerr=self.data.shift1_error,fmt='k^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
-                                self.ploterr2 = ax.errorbar(shift2, y, xerr=self.data.shift2_error,fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
                         self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
-                        #self.titles.append('{}'.format('Velocidad Doppler'))
             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
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     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:
                             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:
                             ax.collections.remove(ax.collections[0])
                             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'
                 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)
-                    #print(self.dataOut.heightList)
-                    #self.ylabel = 'Range [km]'
                     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 = ['{} 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)]
                 def plot(self):
                     self.x = self.data.times
-                    #self.y = self.data.heights
                     self.z = self.data[self.CODE]
                     self.y = self.data.xrange[0]
-                    #import time
-                    #print(time.ctime(self.x))
-                    '''
-                    print(numpy.shape(self.x))
-                    print(numpy.shape(self.y))
-                    print(numpy.shape(self.z))
-                    '''
                     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)
                                                    )
                             if self.showprofile:
                                 ax.plot_profile = self.pf_axes[n].plot(
                                     data['rti'][n], self.y)[0]
                                 ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y,
                                                                      color="k", linestyle="dashed", lw=1)[0]
                         else:
                             ax.collections.remove(ax.collections[0])
                             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(data['rti'][n], self.y)
                                 ax.plot_noise.set_data(numpy.repeat(
                                     data['noise'][n], len(self.y)), self.y)
             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(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     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)
                             self.ymax = self.ymax if self.ymax else numpy.nanmax(z)
                             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 +22 -52

             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
-            import time
-            import math
             from matplotlib.ticker import MultipleLocator
             class RTIDPPlot(RTIPlot):
-                '''
+                '''Plot for RTI Double Pulse Experiment
-                   Plot for RTI Double Pulse Experiment
                 '''
                 CODE = 'RTIDP'
                 colormap = 'jro'
                 plot_name = 'RTI'
-                #cb_label = 'Ne Electron Density (1/cm3)'
                 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.cb_label = cb_label
                     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):
-                def plot(self):
+                    data = {}
+                    meta = {}
-                    self.data.normalize_heights()
+                    data[self.CODE] = dataOut.data_for_RTI_DP
-                    self.x = self.data.times
+                    data['NRANGE'] = dataOut.NDP
-                    self.y = self.data.heights[0:self.data.NDP]
-                    if self.showSNR:
+                    return data, meta
-                        self.z = numpy.concatenate(
-                            (self.data[self.CODE], self.data['snr'])
-                    else:
-                        self.z = self.data[self.CODE]
+                def plot(self):
-                        #print(numpy.max(self.z[0,0:]))
+                    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]
                                                    )
-                            #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 = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
-                            #plt.tight_layout()
             class RTILPPlot(RTIPlot):
                 '''
                    Plot for RTI Long Pulse
                 '''
                 CODE = 'RTILP'
                 colormap = 'jro'
                 plot_name = 'RTI LP'
-                #cb_label = 'Ne Electron Density (1/cm3)'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 4
                     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.cb_label = cb_label
                     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 plot(self):
                     self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.heights[0:self.data.NRANGE]
                     if self.showSNR:
                         self.z = numpy.concatenate(
                             (self.data[self.CODE], self.data['snr'])
                         )
                     else:
                         self.z = self.data[self.CODE]
                         #print(numpy.max(self.z[0,0:]))
                     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 = 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):
                 '''
                    Plot for Den
                 '''
                 CODE = 'denrti'
                 colormap = 'jro'
                 plot_name = 'Electron Density'
                 #cb_label = 'Ne Electron Density (1/cm3)'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = self.data.shape(self.CODE)[0]
                     self.nplots = self.nrows
                     if self.showSNR:
                         self.nrows += 1
                         self.nplots += 1
                     self.ylabel = 'Height [km]'
                     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' or self.CODE=='denrtiLP':
                         self.cb_label = r'$\mathrm{N_e}$ Electron Density ($\mathrm{1/cm^3}$)'
                     #self.cb_label = cb_label
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.plot_name)]
                         if self.showSNR:
                             self.titles.append('SNR')
                 def plot(self):
                     self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.heights
                     if self.showSNR:
                         self.z = numpy.concatenate(
                             (self.data[self.CODE], self.data['snr'])
                         )
                     else:
                         self.z = self.data[self.CODE]
                     self.z = numpy.ma.masked_invalid(self.z)
                     if self.decimation is None:
                         x, y, z = self.fill_gaps(self.x, self.y, self.z)
                     else:
                         x, y, z = self.fill_gaps(*self.decimate())
                     for n, ax in enumerate(self.axes):
                         self.zmax = self.zmax if self.zmax is not None else numpy.max(
                             self.z[n])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[n])
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             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()
                                                    )
                             #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 = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n],
                                                    norm=colors.LogNorm()
                                                    )
                             #plt.tight_layout()
             class DenRTILPPlot(DenRTIPlot):
                 '''
                    Plot for Electron Temperature
                 '''
                 CODE = 'denrtiLP'
                 colormap = 'jro'
                 plot_name = 'Electron Density'
             class ETempRTIPlot(RTIPlot):
                 '''
                    Plot for Electron Temperature
                 '''
                 CODE = 'ETemp'
                 colormap = 'jet'
                 plot_name = 'Electron Temperature'
                 #cb_label = 'Ne Electron Density (1/cm3)'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = self.data.shape(self.CODE)[0]
                     self.nplots = self.nrows
                     if self.showSNR:
                         self.nrows += 1
                         self.nplots += 1
                     self.ylabel = 'Height [km]'
                     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' or self.CODE == 'ETempLP':
                         self.cb_label = 'Electron Temperature (K)'
                     if self.CODE == 'ITemp' or self.CODE == 'ITempLP':
                         self.cb_label = 'Ion Temperature (K)'
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.plot_name)]
                         if self.showSNR:
                             self.titles.append('SNR')
                 def plot(self):
                     self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.heights
                     if self.showSNR:
                         self.z = numpy.concatenate(
                             (self.data[self.CODE], self.data['snr'])
                         )
                     else:
                         self.z = self.data[self.CODE]
                     self.z = numpy.ma.masked_invalid(self.z)
                     if self.decimation is None:
                         x, y, z = self.fill_gaps(self.x, self.y, self.z)
                     else:
                         x, y, z = self.fill_gaps(*self.decimate())
                     for n, ax in enumerate(self.axes):
                         self.zmax = self.zmax if self.zmax is not None else numpy.max(
                             self.z[n])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[n])
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
                             #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 = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
                             #plt.tight_layout()
             class ITempRTIPlot(ETempRTIPlot):
                 '''
                    Plot for Ion Temperature
                 '''
                 CODE = 'ITemp'
                 colormap = 'jet'
                 plot_name = 'Ion Temperature'
             class ElectronTempLPPlot(ETempRTIPlot):
                 '''
                    Plot for Electron Temperature LP
                 '''
                 CODE = 'ETempLP'
                 colormap = 'jet'
                 plot_name = 'Electron Temperature'
             class IonTempLPPlot(ETempRTIPlot):
                 '''
                    Plot for Ion Temperature LP
                 '''
                 CODE = 'ITempLP'
                 colormap = 'jet'
                 plot_name = 'Ion Temperature'
             class HFracRTIPlot(ETempRTIPlot):
                 '''
                    Plot for H+ LP
                 '''
                 CODE = 'HFracLP'
                 colormap = 'jet'
                 plot_name = 'H+ Frac'
             class HeFracRTIPlot(ETempRTIPlot):
                 '''
                    Plot for He+ LP
                 '''
                 CODE = 'HeFracLP'
                 colormap = 'jet'
                 plot_name = 'He+ Frac'
             class TempsDPPlot(Plot):
                 '''
                 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.width = 3.5
                     self.height = 5.5
                     self.colorbar = False
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data['tempsDP'][:,-1]
                     self.y = self.data.heights[0:self.data.NSHTS]
                     self.xmin = -100
                     self.xmax = 5000
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.errorbar(self.x, self.y, xerr=self.data.ete2, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(self.data.ti2, self.y, fmt='k^', xerr=self.data.eti2,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')
                         #plt.tight_layout()
                     else:
                         self.clear_figures()
                         ax.errorbar(self.x, self.y, xerr=self.data.ete2, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(self.data.ti2, self.y, fmt='k^', xerr=self.data.eti2,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         #plt.tight_layout()
             class TempsHPPlot(Plot):
                 '''
                 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.width = 3.5
                     self.height = 6.5
                     self.colorbar = False
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data['temps_LP'][:,-1]
                     self.y = self.data.heights[0:self.data.NACF]
                     self.xmin = -100
                     self.xmax = 4500
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.errorbar(self.x, self.y, xerr=self.data.ete, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(self.data.ti, self.y, fmt='k^', xerr=self.data.eti,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')
                         #plt.tight_layout()
                     else:
                         self.clear_figures()
                         ax.errorbar(self.x, self.y, xerr=self.data.ete, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='Te')
                         ax.errorbar(self.data.ti, self.y, fmt='k^', xerr=self.data.eti,elinewidth=1.0,color='b',linewidth=2.0, label='Ti')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         #plt.tight_layout()
             class FracsHPPlot(Plot):
                 '''
                 Plot for Composition LP
                 '''
                 CODE = 'fracs_LP'
                 plot_name = 'Composition'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Frac'
                     self.width = 3.5
                     self.height = 6.5
                     self.colorbar = False
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data['fracs_LP'][:,-1]
                     self.y = self.data.heights[0:self.data.NACF]
                     self.xmin = 0
                     self.xmax = 1
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.errorbar(self.x, self.y[self.data.cut:], xerr=self.data.eph, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='H+')
                         ax.errorbar(self.data.phe, self.y[self.data.cut:], fmt='k^', xerr=self.data.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')
                         #plt.tight_layout()
                     else:
                         self.clear_figures()
                         ax.errorbar(self.x, self.y[self.data.cut:], xerr=self.data.eph, fmt='r^',elinewidth=1.0,color='b',linewidth=2.0, label='H+')
                         ax.errorbar(self.data.phe, self.y[self.data.cut:], fmt='k^', xerr=self.data.ephe,elinewidth=1.0,color='b',linewidth=2.0, label='He+')
                         plt.legend(loc='lower right')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
                         #plt.tight_layout()
             class EDensityPlot(Plot):
                 '''
                 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.width = 4
                     self.height = 6.5
                     self.colorbar = False
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data[self.CODE]
                     self.y = self.data.heights
                     self.xmin = 1000
                     self.xmax = 10000000
                     ax = self.axes[0]
                     if ax.firsttime:
                         self.autoxticks=False
                         #if self.CODE=='den':
                         ax.errorbar(self.data.dphi, self.y[:self.data.NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         #ax.errorbar(self.data.dphi, self.y[:self.data.NSHTS], xerr=self.data.sdn1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         ax.errorbar(self.x[:,-1], self.y[:self.data.NSHTS], fmt='k^-', xerr=self.data.sdp2,elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                         #else:
                             #ax.errorbar(self.data.dphi[:self.data.cut], self.y[:self.data.cut], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                             #ax.errorbar(self.x[:self.data.cut,-1], self.y[:self.data.cut], fmt='k^-', xerr=self.data.sdp2[:self.data.cut],elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                         if self.CODE=='denLP':
                             ax.errorbar(self.data.ne[self.data.cut:], self.y[self.data.cut:], xerr=self.data.ene[self.data.cut:], fmt='r^-',elinewidth=1.0,color='r',linewidth=1.0, label='LP Profile',markersize=2)
                         plt.legend(loc='upper right')
                         ax.set_xscale("log", nonposx='clip')
                         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':
                         ax.errorbar(self.data.dphi, self.y[:self.data.NSHTS], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         #ax.errorbar(self.data.dphi, self.y[:self.data.NSHTS], xerr=self.data.sdn1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                         ax.errorbar(self.x[:,-1], self.y[:self.data.NSHTS], fmt='k^-', xerr=self.data.sdp2,elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                         ax.errorbar(self.x[:,-2], self.y[:self.data.NSHTS], elinewidth=1.0,color='r',linewidth=0.5,linestyle="dashed")
                         #else:
                             #ax.errorbar(self.data.dphi[:self.data.cut], self.y[:self.data.cut], xerr=1, fmt='h-',elinewidth=1.0,color='g',linewidth=1.0, label='Faraday Profile',markersize=2)
                             #ax.errorbar(self.x[:self.data.cut,-1], self.y[:self.data.cut], fmt='k^-', xerr=self.data.sdp2[:self.data.cut],elinewidth=1.0,color='b',linewidth=1.0, label='Power Profile',markersize=2)
                             #ax.errorbar(self.x[:self.data.cut,-2], self.y[:self.data.cut], elinewidth=1.0,color='r',linewidth=0.5,linestyle="dashed")
                         if self.CODE=='denLP':
                             ax.errorbar(self.data.ne[self.data.cut:], self.y[self.data.cut:], fmt='r^-', xerr=self.data.ene[self.data.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(self.y),numpy.nanmax(self.y),50)
                         ax.set_yticks(grid_y_ticks,minor=True)
                         ax.grid(which='minor')
                         plt.legend(loc='upper right')
                         #plt.tight_layout()
             class FaradayAnglePlot(Plot):
                 '''
                 Plot for electron density
                 '''
                 CODE = 'FaradayAngle'
                 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.width = 4
                     self.height = 6.5
                     self.colorbar = False
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data[self.CODE]
                     self.y = self.data.heights
                     self.xmin = -180
                     self.xmax = 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)
                         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[:,-1], self.y, marker='o',color='g',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):
                 '''
                    Plot for Electron Density Hybrid Experiment
                 '''
                 CODE = 'denLP'
                 plot_name = 'Electron Density'
                 plot_type = 'scatterbuffer'
             class ACFsPlot(Plot):
                 '''
                 Plot for ACFs Double Pulse Experiment
                 '''
                 CODE = 'acfs'
                 plot_name = 'ACF'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     #self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'lags (ms)'
                     self.width = 3.5
                     self.height = 6
                     self.colorbar = False
                     self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data.lags_to_plot
                     self.y = self.data['acfs'][:,-1]
                     self.xmin = 0.0
                     self.xmax = 2.0
                     ax = self.axes[0]
                     if ax.firsttime:
                         for i in range(self.data.NSHTS):
                             x_aux = numpy.isfinite(self.x[i,:])
                             y_aux = numpy.isfinite(self.y[i,:])
                             yerr_aux = numpy.isfinite(self.data.acfs_error_to_plot[i,:])
                             x_igcej_aux = numpy.isfinite(self.data.x_igcej_to_plot[i,:])
                             y_igcej_aux = numpy.isfinite(self.data.y_igcej_to_plot[i,:])
                             x_ibad_aux = numpy.isfinite(self.data.x_ibad_to_plot[i,:])
                             y_ibad_aux = numpy.isfinite(self.data.y_ibad_to_plot[i,:])
                             if self.x[i,:][~numpy.isnan(self.x[i,:])].shape[0]>2:
                                 ax.errorbar(self.x[i,x_aux], self.y[i,y_aux], yerr=self.data.acfs_error_to_plot[i,x_aux],color='b',marker='o',linewidth=1.0,markersize=2)
                             ax.plot(self.data.x_igcej_to_plot[i,x_igcej_aux],self.data.y_igcej_to_plot[i,y_igcej_aux],'x',color='red',markersize=2)
                             ax.plot(self.data.x_ibad_to_plot[i,x_ibad_aux],self.data.y_ibad_to_plot[i,y_ibad_aux],'X',color='red',markersize=2)
                         self.xstep_given = (self.xmax-self.xmin)/(self.data.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(self.data.NSHTS):
                             x_aux = numpy.isfinite(self.x[i,:])
                             y_aux = numpy.isfinite(self.y[i,:])
                             yerr_aux = numpy.isfinite(self.data.acfs_error_to_plot[i,:])
                             x_igcej_aux = numpy.isfinite(self.data.x_igcej_to_plot[i,:])
                             y_igcej_aux = numpy.isfinite(self.data.y_igcej_to_plot[i,:])
                             x_ibad_aux = numpy.isfinite(self.data.x_ibad_to_plot[i,:])
                             y_ibad_aux = numpy.isfinite(self.data.y_ibad_to_plot[i,:])
                             if self.x[i,:][~numpy.isnan(self.x[i,:])].shape[0]>2:
                                 ax.errorbar(self.x[i,x_aux], self.y[i,y_aux], yerr=self.data.acfs_error_to_plot[i,x_aux],linewidth=1.0,markersize=2,color='b',marker='o')
                             ax.plot(self.data.x_igcej_to_plot[i,x_igcej_aux],self.data.y_igcej_to_plot[i,y_igcej_aux],'x',color='red',markersize=2)
                             ax.plot(self.data.x_ibad_to_plot[i,x_ibad_aux],self.data.y_ibad_to_plot[i,y_ibad_aux],'X',color='red',markersize=2)
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
             class ACFsLPPlot(Plot):
                 '''
                 Plot for ACFs Double Pulse Experiment
                 '''
                 CODE = 'acfs_LP'
                 plot_name = 'ACF'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     #self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'lags (ms)'
                     self.width = 3.5
                     self.height = 7
                     self.colorbar = False
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.CODE.upper())]
                 def plot(self):
                     self.x = self.data.lags_LP_to_plot
                     self.y = self.data['acfs_LP'][:,-1]
                     self.xmin = 0.0
                     self.xmax = 1.5
                     ax = self.axes[0]
                     if ax.firsttime:
                         for i in range(self.data.NACF):
                             x_aux = numpy.isfinite(self.x[i,:])
                             y_aux = numpy.isfinite(self.y[i,:])
                             yerr_aux = numpy.isfinite(self.data.errors[i,:])
                             if self.x[i,:][~numpy.isnan(self.x[i,:])].shape[0]>2:
                                 ax.errorbar(self.x[i,x_aux], self.y[i,y_aux], yerr=self.data.errors[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(self.data.NACF):
                             x_aux = numpy.isfinite(self.x[i,:])
                             y_aux = numpy.isfinite(self.y[i,:])
                             yerr_aux = numpy.isfinite(self.data.errors[i,:])
                             if self.x[i,:][~numpy.isnan(self.x[i,:])].shape[0]>2:
                                 ax.errorbar(self.x[i,x_aux], self.y[i,y_aux], yerr=self.data.errors[i,x_aux],color='b',linewidth=1.0,markersize=2,ecolor='r')
                         ax.yaxis.set_minor_locator(MultipleLocator(15))
             class CrossProductsPlot(Plot):
                 '''
                 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 plot(self):
+                def update(self, dataOut):
-                    self.x = self.data['crossprod'][:,-1,:,:,:,:]
+                    data = {}
+                    meta = {}
+                    data['crossprod'] = dataOut.crossprods
+                    data['NDP'] = dataOut.NDP
-                    self.y = self.data.heights[0:self.data.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()))
-                            #plt.tight_layout()
                         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()))
-                            #plt.tight_layout()
             class CrossProductsLPPlot(Plot):
                 '''
                 Plot for cross products LP
                 '''
                 CODE = 'crossprodlp'
                 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.plotline_array=numpy.zeros((2,self.data.NLAG),dtype=object)
                 def plot(self):
                     self.x = self.data[self.CODE][:,-1,:,:]
                     self.y = self.data.heights[0:self.data.NRANGE]
                     label_array=numpy.array(['lag '+ str(x) for x in range(self.data.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=30
                         self.xmax=70
                         #print(self.x[0,12:15,n])
                         #input()
                         #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])))
                         #print("before",self.plotline_array)
                         if ax.firsttime:
                             self.autoxticks=False
                             for i in range(self.data.NLAG):
                                 #print(i)
                                 #print(numpy.shape(self.x))
                                 self.plotline_array[n,i], = ax.plot(self.x[i,:,n], self.y, color=color_array[i],linewidth=1.0, label=label_array[i])
                             #ax.plotline1 = ax.plot(self.x[0,:,n], self.y, color='r',linewidth=2.0, label=label_array[0])
                             #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)
                             #print(self.plotline_array)
                             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()))
                             #plt.tight_layout()
                         else:
                             #print(self.plotline_array)
                             for i in range(self.data.NLAG):
                                 self.plotline_array[n,i].set_data(self.x[i,:,n],self.y)
                             #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)
                             if n==0:
                                 self.titles.append('{} CH0'.format(self.plot_name.upper()))
                             if n==1:
                                 self.titles.append('{} CH1'.format(self.plot_name.upper()))
                             #plt.tight_layout()
             class NoiseDPPlot(NoisePlot):
                 '''
                 Plot for noise Double Pulse
                 '''
                 CODE = 'noisedp'
                 plot_name = 'Noise'
                 plot_type = 'scatterbuffer'
             class XmitWaveformPlot(Plot):
                 '''
                 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
                     if not self.titles:
                         self.titles = self.data.parameters \
                             if self.data.parameters else ['{}'.format(self.plot_name.upper())]
                 def plot(self):
                     self.x = numpy.arange(0,self.data.NLAG,1,'float32')
                     self.y = self.data['xmit'][:,-1,:]
                     self.xmin = 0
                     self.xmax = self.data.NLAG-1
                     self.ymin = -1.0
                     self.ymax = 1.0
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.plotline0=ax.plot(self.x,self.y[0,:],color='blue')
                         ax.plotline1=ax.plot(self.x,self.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(self.x,self.y[0,:])
                         ax.plotline1[0].set_data(self.x,self.y[1,:])

schainpy/model/proc/__init__.py +1 -1

             '''
             $Author: murco $
             $Id: Processor.py 1 2012-11-12 18:56:07Z murco $
             '''
             from .jroproc_voltage import *
             from .jroproc_spectra import *
             from .jroproc_heispectra import *
             from .jroproc_amisr import *
             from .jroproc_correlation import *
             from .jroproc_parameters import *
             from .jroproc_spectra_lags import *
             from .jroproc_spectra_acf import *
             from .bltrproc_parameters import *
             from .pxproc_parameters import *
             ###########DP###########
             from .jroproc_voltage_lags import *
             ###########DP###########
-            from .jroproc_spectra_lags_faraday import *
+            # from .jroproc_spectra_lags_faraday import *

schainpy/model/proc/jroproc_voltage.py 0 0

	1	NO CONTENT: modified file			NO CONTENT: modified file
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