jroplot_spectra.py
1206 lines
| 40.6 KiB
| text/x-python
|
PythonLexer
sebastianVP
|
r1745 | # MASTER | |
Danny Scipión
|
r1358 | # Copyright (c) 2012-2021 Jicamarca Radio Observatory | |
| r1343 | # All rights reserved. | ||
| # | |||
| # Distributed under the terms of the BSD 3-clause license. | |||
| """Classes to plot Spectra data | |||
Miguel Valdez
|
r568 | ||
| r1343 | """ | ||
Juan C. Espinoza
|
r1285 | ||
Daniel Valdez
|
r487 | import os | |
| import numpy | |||
| r1343 | from schainpy.model.graphics.jroplot_base import Plot, plt, log | ||
José Chávez
|
r953 | ||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | class SpectraPlot(Plot): | |
| ''' | |||
| Plot for Spectra data | |||
| ''' | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | CODE = 'spc' | |
| colormap = 'jet' | |||
| plot_type = 'pcolor' | |||
| r1343 | buffering = False | ||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | def setup(self): | |
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | 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) | |||
| r1334 | self.height = 2.6 * self.nrows | ||
|
Juan C. Espinoza
|
r1285 | self.cb_label = 'dB' | |
| if self.showprofile: | |||
| self.width = 4 * self.ncols | |||
|
Daniel Valdez
|
r487 | else: | |
|
Juan C. Espinoza
|
r1285 | self.width = 3.5 * self.ncols | |
|
Alexander Valdez
|
r1696 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) | |
|
Juan C. Espinoza
|
r1285 | self.ylabel = 'Range [km]' | |
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
| spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |||
| data['spc'] = spc | |||
| data['rti'] = dataOut.getPower() | |||
|
sebastianVP
|
r1745 | if hasattr(dataOut, 'LagPlot'): #Double Pulse | |
| max_hei_id = dataOut.nHeights - 2*dataOut.LagPlot | |||
| data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=53,ymax_index=max_hei_id)/dataOut.normFactor) | |||
| data['noise'][0] = 10*numpy.log10(dataOut.getNoise(ymin_index=53)[0]/dataOut.normFactor) | |||
| else: | |||
| data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |||
| r1343 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | ||
|
Alexander Valdez
|
r1696 | ||
| r1343 | if self.CODE == 'spc_moments': | ||
| data['moments'] = dataOut.moments | |||
|
Danny Scipión
|
r1358 | if self.CODE == 'gaussian_fit': | |
| data['gaussfit'] = dataOut.DGauFitParams | |||
|
Alexander Valdez
|
r1696 | return data, meta | |
|
Juan C. Espinoza
|
r1285 | def plot(self): | |
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | 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)" | |||
ebocanegra
|
r965 | else: | |
|
Juan C. Espinoza
|
r1285 | x = self.data.xrange[2] | |
| self.xlabel = "Velocity (m/s)" | |||
|
Danny Scipión
|
r1358 | if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'): | |
|
Juan C. Espinoza
|
r1285 | x = self.data.xrange[2] | |
| self.xlabel = "Velocity (m/s)" | |||
| self.titles = [] | |||
| r1343 | y = self.data.yrange | ||
|
Juan C. Espinoza
|
r1285 | self.y = y | |
| r1343 | |||
| data = self.data[-1] | |||
| z = data['spc'] | |||
|
Juan C. Espinoza
|
r1285 | ||
|
sebastianVP
|
r1745 | self.CODE2 = 'spc_oblique' | |
|
Juan C. Espinoza
|
r1285 | for n, ax in enumerate(self.axes): | |
| r1343 | noise = data['noise'][n] | ||
|
Juan C. Espinoza
|
r1285 | if self.CODE == 'spc_moments': | |
|
Danny Scipión
|
r1358 | mean = data['moments'][n, 1] | |
|
Alexander Valdez
|
r1696 | if self.CODE == 'gaussian_fit': | |
|
Danny Scipión
|
r1358 | gau0 = data['gaussfit'][n][2,:,0] | |
| gau1 = data['gaussfit'][n][2,:,1] | |||
|
Juan C. Espinoza
|
r1285 | if ax.firsttime: | |
| self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |||
|
sebastianVP
|
r1745 | self.xmin = self.xmin if self.xmin else numpy.nanmin(x)#-self.xmax | |
| #self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |||
| #self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |||
| if self.zlimits is not None: | |||
| self.zmin, self.zmax = self.zlimits[n] | |||
| # CORREGIR CON matplotlib==3.3.4 | |||
|
Juan C. Espinoza
|
r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |
| vmin=self.zmin, | |||
| vmax=self.zmax, | |||
|
sebastianVP
|
r1745 | cmap=plt.get_cmap(self.colormap), | |
|
Juan C. Espinoza
|
r1285 | ) | |
| if self.showprofile: | |||
| ax.plt_profile = self.pf_axes[n].plot( | |||
| r1343 | data['rti'][n], y)[0] | ||
|
Juan C. Espinoza
|
r1285 | 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': | |||
|
Danny Scipión
|
r1358 | 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] | |||
|
Juan C. Espinoza
|
r1285 | else: | |
|
sebastianVP
|
r1745 | if self.zlimits is not None: | |
| self.zmin, self.zmax = self.zlimits[n] | |||
|
Juan C. Espinoza
|
r1285 | ax.plt.set_array(z[n].T.ravel()) | |
| if self.showprofile: | |||
| r1343 | ax.plt_profile.set_data(data['rti'][n], y) | ||
|
Juan C. Espinoza
|
r1285 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | |
| if self.CODE == 'spc_moments': | |||
| ax.plt_mean.set_data(mean, y) | |||
|
Danny Scipión
|
r1358 | if self.CODE == 'gaussian_fit': | |
| ax.plt_gau0.set_data(gau0, y) | |||
| ax.plt_gau1.set_data(gau1, y) | |||
|
Juan C. Espinoza
|
r1285 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | |
|
Alexander Valdez
|
r1696 | class SpectraObliquePlot(Plot): | |
| ''' | |||
| Plot for Spectra data | |||
| ''' | |||
| 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.Dop_EEJ_T1[0] | |||
| data['shift2'] = dataOut.Dop_EEJ_T2[0] | |||
| data['max_val_2'] = dataOut.Oblique_params[0,-1,:] | |||
| data['shift1_error'] = dataOut.Err_Dop_EEJ_T1[0] | |||
| data['shift2_error'] = dataOut.Err_Dop_EEJ_T2[0] | |||
| return data, meta | |||
| def plot(self): | |||
| if self.xaxis == "frequency": | |||
| x = self.data.xrange[0] | |||
| self.xlabel = "Frequency (kHz)" | |||
| elif self.xaxis == "time": | |||
| x = self.data.xrange[1] | |||
| self.xlabel = "Time (ms)" | |||
| else: | |||
| x = self.data.xrange[2] | |||
| self.xlabel = "Velocity (m/s)" | |||
| self.titles = [] | |||
| y = self.data.yrange | |||
| self.y = y | |||
| data = self.data[-1] | |||
| z = data['spc'] | |||
| for n, ax in enumerate(self.axes): | |||
| noise = self.data['noise'][n][-1] | |||
| shift1 = data['shift1'] | |||
| shift2 = data['shift2'] | |||
| max_val_2 = data['max_val_2'] | |||
| err1 = data['shift1_error'] | |||
| err2 = data['shift2_error'] | |||
| if ax.firsttime: | |||
| self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |||
| self.xmin = self.xmin if self.xmin else -self.xmax | |||
| self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |||
| self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | |||
| ax.plt = ax.pcolormesh(x, y, z[n].T, | |||
| vmin=self.zmin, | |||
| vmax=self.zmax, | |||
| cmap=plt.get_cmap(self.colormap) | |||
| ) | |||
| if self.showprofile: | |||
| ax.plt_profile = self.pf_axes[n].plot( | |||
| self.data['rti'][n][-1], y)[0] | |||
| ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y, | |||
| color="k", linestyle="dashed", lw=1)[0] | |||
| self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| else: | |||
| self.ploterr1.remove() | |||
| self.ploterr2.remove() | |||
| self.ploterr3.remove() | |||
| ax.plt.set_array(z[n].T.ravel()) | |||
| if self.showprofile: | |||
| ax.plt_profile.set_data(self.data['rti'][n][-1], y) | |||
| ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | |||
| self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=2.2, marker='o', linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| self.ploterr3 = ax.errorbar(max_val_2, y, xerr=0, fmt='g^',elinewidth=2.2,marker='o',linestyle='None',markersize=2.5,capsize=0.3,markeredgewidth=0.2) | |||
| self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | |||
|
Juan C. Espinoza
|
r1285 | ||
| 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 | |||
| r1343 | self.nplots = len(self.data.pairs) * 2 | ||
| self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) | |||
| r1334 | self.width = 3.1 * self.ncols | ||
|
Alexander Valdez
|
r1696 | self.height = 5 * self.nrows | |
|
Juan C. Espinoza
|
r1285 | self.ylabel = 'Range [km]' | |
| self.showprofile = False | |||
| r1334 | self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08}) | ||
|
Juan C. Espinoza
|
r1285 | ||
| r1343 | 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) | |||
|
Alexander Valdez
|
r1696 | return data, meta | |
|
Juan C. Espinoza
|
r1285 | 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)" | |||
|
Miguel Valdez
|
r777 | else: | |
|
Juan C. Espinoza
|
r1285 | x = self.data.xrange[2] | |
| self.xlabel = "Velocity (m/s)" | |||
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | self.titles = [] | |
| r1343 | y = self.data.yrange | ||
|
Juan C. Espinoza
|
r1285 | self.y = y | |
| r1343 | data = self.data[-1] | ||
| cspc = data['cspc'] | |||
|
Juan C. Espinoza
|
r1285 | ||
| r1343 | 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] | |||
|
Juan C. Espinoza
|
r1285 | 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])) | |||
|
Alexander Valdez
|
r1696 | ||
| r1343 | ax = self.axes[2 * n + 1] | ||
|
Juan C. Espinoza
|
r1285 | if ax.firsttime: | |
| ax.plt = ax.pcolormesh(x, y, phase.T, | |||
| vmin=-180, | |||
| vmax=180, | |||
|
Alexander Valdez
|
r1696 | cmap=plt.get_cmap(self.colormap_phase) | |
|
Juan C. Espinoza
|
r1285 | ) | |
| else: | |||
| ax.plt.set_array(phase.T.ravel()) | |||
| self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) | |||
|
Alexander Valdez
|
r1696 | 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'] | |||
| spc = self.data['cspc'][0] | |||
| cspc = self.data['cspc'][1] | |||
| for n in range(self.nrows): | |||
| noise = self.data['noise'][:,-1] | |||
| pair = self.data.pairs[n] | |||
| 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: | |||
| 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 | |||
| cspc = self.data['cspc'][1] | |||
| for n in range(self.nrows): | |||
| noise = self.data['noise'][:,-1] | |||
| pair = self.data.pairs[n] | |||
| out = cspc[n] | |||
| cross = numpy.abs(out) | |||
| z = cross/self.data.nFactor | |||
| cross = 10*numpy.log10(z) | |||
| 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 | |||
| cspc = self.data['cspc'][1] | |||
| for n in range(self.nrows): | |||
| noise = self.data['noise'][:,-1] | |||
| pair = self.data.pairs[n] | |||
| out = cspc[n] | |||
| cross = numpy.abs(out) | |||
| z = cross/self.data.nFactor | |||
| cross = 10*numpy.log10(z) | |||
| out_r= out.real/self.data.nFactor | |||
| out_i= out.imag/self.data.nFactor | |||
| 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])) | |||
|
Juan C. Espinoza
|
r1285 | 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' | |||
|
Alexander Valdez
|
r1696 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95}) | |
|
Juan C. Espinoza
|
r1285 | self.titles = ['{} Channel {}'.format( | |
| self.CODE.upper(), x) for x in range(self.nrows)] | |||
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
| data['rti'] = dataOut.getPower() | |||
| data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |||
| return data, meta | |||
|
Juan C. Espinoza
|
r1285 | def plot(self): | |
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | self.x = self.data.times | |
| r1343 | self.y = self.data.yrange | ||
|
Juan C. Espinoza
|
r1285 | 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) | |||
|
ebocanegra
|
r965 | else: | |
|
Juan C. Espinoza
|
r1285 | x, y, z = self.fill_gaps(*self.decimate()) | |
| for n, ax in enumerate(self.axes): | |||
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |
| self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |||
| r1343 | data = self.data[-1] | ||
|
Juan C. Espinoza
|
r1285 | 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( | |||
| r1343 | data['rti'][n], self.y)[0] | ||
| ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y, | |||
|
Juan C. Espinoza
|
r1285 | 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: | |||
| r1343 | ax.plot_profile.set_data(data['rti'][n], self.y) | ||
|
Juan C. Espinoza
|
r1285 | ax.plot_noise.set_data(numpy.repeat( | |
| r1343 | data['noise'][n], len(self.y)), self.y) | ||
|
Juan C. Espinoza
|
r1285 | ||
|
Alexander Valdez
|
r1696 | class SpectrogramPlot(Plot): | |
| ''' | |||
| Plot for Spectrogram data | |||
| ''' | |||
| CODE = 'Spectrogram_Profile' | |||
| colormap = 'binary' | |||
| plot_type = 'pcolorbuffer' | |||
| def setup(self): | |||
| self.xaxis = 'time' | |||
| self.ncols = 1 | |||
| self.nrows = len(self.data.channels) | |||
| self.nplots = len(self.data.channels) | |||
| self.xlabel = 'Time' | |||
| self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95}) | |||
| self.titles = [] | |||
| self.titles = ['{} Channel {}'.format( | |||
| self.CODE.upper(), x) for x in range(self.nrows)] | |||
| def update(self, dataOut): | |||
| data = {} | |||
| meta = {} | |||
| maxHei = 1620#+12000 | |||
| indb = numpy.where(dataOut.heightList <= maxHei) | |||
| hei = indb[0][-1] | |||
| factor = dataOut.nIncohInt | |||
| z = dataOut.data_spc[:,:,hei] / factor | |||
| z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |||
| meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |||
| data['Spectrogram_Profile'] = 10 * numpy.log10(z) | |||
| data['hei'] = hei | |||
| data['DH'] = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step | |||
| data['nProfiles'] = dataOut.nProfiles | |||
| return data, meta | |||
| def plot(self): | |||
| self.x = self.data.times | |||
| self.z = self.data[self.CODE] | |||
| self.y = self.data.xrange[0] | |||
| hei = self.data['hei'][-1] | |||
| DH = self.data['DH'][-1] | |||
| nProfiles = self.data['nProfiles'][-1] | |||
| self.ylabel = "Frequency (kHz)" | |||
| self.z = numpy.ma.masked_invalid(self.z) | |||
| if self.decimation is None: | |||
| x, y, z = self.fill_gaps(self.x, self.y, self.z) | |||
| else: | |||
| x, y, z = self.fill_gaps(*self.decimate()) | |||
| for n, ax in enumerate(self.axes): | |||
| self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |||
| self.zmax = self.zmax if self.zmax else numpy.max(self.z) | |||
| data = self.data[-1] | |||
| if ax.firsttime: | |||
| ax.plt = ax.pcolormesh(x, y, z[n].T, | |||
| vmin=self.zmin, | |||
| vmax=self.zmax, | |||
| cmap=plt.get_cmap(self.colormap) | |||
| ) | |||
| else: | |||
| ax.collections.remove(ax.collections[0]) | |||
| ax.plt = ax.pcolormesh(x, y, z[n].T, | |||
| vmin=self.zmin, | |||
| vmax=self.zmax, | |||
| cmap=plt.get_cmap(self.colormap) | |||
| ) | |||
|
Juan C. Espinoza
|
r1285 | ||
| 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] | |||
|
Miguel Valdez
|
r825 | else: | |
|
Juan C. Espinoza
|
r1285 | self.cb_label = 'Degrees' | |
| self.titles = [ | |||
| 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | |||
|
Juan C. Valdez
|
r858 | ||
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
| data['coh'] = dataOut.getCoherence() | |||
| meta['pairs'] = dataOut.pairsList | |||
| return data, meta | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | class PhasePlot(CoherencePlot): | |
| ''' | |||
| Plot for Phase map data | |||
| ''' | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | CODE = 'phase' | |
| colormap = 'seismic' | |||
|
Juan C. Valdez
|
r858 | ||
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
| data['phase'] = dataOut.getCoherence(phase=True) | |||
| meta['pairs'] = dataOut.pairsList | |||
| return data, meta | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | class NoisePlot(Plot): | |
| ''' | |||
|
Alexander Valdez
|
r1696 | Plot for noise | |
|
Juan C. Espinoza
|
r1285 | ''' | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | CODE = 'noise' | |
| plot_type = 'scatterbuffer' | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | def setup(self): | |
| self.xaxis = 'time' | |||
| self.ncols = 1 | |||
| self.nrows = 1 | |||
| self.nplots = 1 | |||
| self.ylabel = 'Intensity [dB]' | |||
|
Juan C. Espinoza
|
r1308 | self.xlabel = 'Time' | |
|
Juan C. Espinoza
|
r1285 | self.titles = ['Noise'] | |
| self.colorbar = False | |||
| r1343 | 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 | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | def plot(self): | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | x = self.data.times | |
| xmin = self.data.min_time | |||
| xmax = xmin + self.xrange * 60 * 60 | |||
| r1343 | Y = self.data['noise'] | ||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | if self.axes[0].firsttime: | |
| r1343 | self.ymin = numpy.nanmin(Y) - 5 | ||
| self.ymax = numpy.nanmax(Y) + 5 | |||
|
Juan C. Espinoza
|
r1285 | for ch in self.data.channels: | |
| y = Y[ch] | |||
| self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch)) | |||
| r1343 | plt.legend(bbox_to_anchor=(1.18, 1.0)) | ||
Julio Valdez
|
r832 | else: | |
|
Juan C. Espinoza
|
r1285 | for ch in self.data.channels: | |
| y = Y[ch] | |||
| self.axes[0].lines[ch].set_data(x, y) | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | class PowerProfilePlot(Plot): | |
|
Juan C. Valdez
|
r858 | ||
| r1343 | CODE = 'pow_profile' | ||
|
Juan C. Espinoza
|
r1285 | plot_type = 'scatter' | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | def setup(self): | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | 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 | |||
|
Juan C. Valdez
|
r858 | ||
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
| data[self.CODE] = dataOut.getPower() | |||
| return data, meta | |||
|
Juan C. Espinoza
|
r1285 | def plot(self): | |
|
Juan C. Valdez
|
r858 | ||
| r1343 | y = self.data.yrange | ||
|
Juan C. Espinoza
|
r1285 | self.y = y | |
|
Juan C. Valdez
|
r858 | ||
| r1343 | x = self.data[-1][self.CODE] | ||
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 | |
| if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 | |||
|
Alexander Valdez
|
r1696 | ||
|
Juan C. Espinoza
|
r1285 | 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() | |||
|
Miguel Valdez
|
r777 | else: | |
|
Juan C. Espinoza
|
r1285 | 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}) | |||
| r1343 | def update(self, dataOut): | ||
| data = {} | |||
| meta = {} | |||
|
Alexander Valdez
|
r1696 | try: | |
| spc = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor) | |||
| except: | |||
| spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |||
| r1343 | data['spc'] = spc | ||
| meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |||
|
Danny Scipión
|
r1358 | 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) | |||
| r1343 | return data, meta | ||
|
Juan C. Espinoza
|
r1285 | 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)" | |||
|
Daniel Valdez
|
r487 | else: | |
|
Danny Scipión
|
r1358 | x = self.data.xrange[2][:-1] | |
| self.xlabel = "Velocity (m/s)" | |||
|
Alexander Valdez
|
r1696 | ||
|
Danny Scipión
|
r1358 | if self.CODE == 'cut_gaussian_fit': | |
| x = self.data.xrange[2][:-1] | |||
|
Juan C. Espinoza
|
r1285 | self.xlabel = "Velocity (m/s)" | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | self.titles = [] | |
|
Juan C. Valdez
|
r858 | ||
| r1343 | y = self.data.yrange | ||
|
Danny Scipión
|
r1358 | data = self.data[-1] | |
| z = data['spc'] | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | if self.height_index: | |
| index = numpy.array(self.height_index) | |||
|
Daniel Valdez
|
r487 | else: | |
|
Juan C. Espinoza
|
r1285 | index = numpy.arange(0, len(y), int((len(y))/9)) | |
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1285 | for n, ax in enumerate(self.axes): | |
|
Alexander Valdez
|
r1696 | if self.CODE == 'cut_gaussian_fit': | |
|
Danny Scipión
|
r1358 | gau0 = data['gauss_fit0'] | |
| gau1 = data['gauss_fit1'] | |||
|
Juan C. Espinoza
|
r1285 | if ax.firsttime: | |
| self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | |||
| self.xmin = self.xmin if self.xmin else -self.xmax | |||
|
Alexander Valdez
|
r1696 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z[:,:,index]) | |
| self.ymax = self.ymax if self.ymax else numpy.nanmax(z[:,:,index]) | |||
|
Danny Scipión
|
r1358 | 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): | |||
|
Alexander Valdez
|
r1696 | line.set_color(ax.plt[i].get_color()) | |
|
Danny Scipión
|
r1358 | ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--') | |
| for i, line in enumerate(ax.plt_gau1): | |||
|
Alexander Valdez
|
r1696 | line.set_color(ax.plt[i].get_color()) | |
|
Juan C. Espinoza
|
r1285 | 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): | |||
|
Danny Scipión
|
r1358 | 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()) | |||
|
Juan C. Espinoza
|
r1285 | self.titles.append('CH {}'.format(n)) | |
|
Juan C. Valdez
|
r858 | ||
George Yong
|
r1171 | ||
|
Juan C. Espinoza
|
r1285 | class BeaconPhase(Plot): | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | __isConfig = None | |
| __nsubplots = None | |||
| PREFIX = 'beacon_phase' | |||
|
Juan C. Valdez
|
r858 | ||
|
George Yong
|
r1179 | def __init__(self): | |
|
Juan C. Espinoza
|
r1285 | Plot.__init__(self) | |
|
Daniel Valdez
|
r494 | self.timerange = 24*60*60 | |
|
Miguel Valdez
|
r760 | self.isConfig = False | |
|
Daniel Valdez
|
r494 | self.__nsubplots = 1 | |
| self.counter_imagwr = 0 | |||
|
Miguel Valdez
|
r760 | self.WIDTH = 800 | |
| self.HEIGHT = 400 | |||
|
Daniel Valdez
|
r494 | self.WIDTHPROF = 120 | |
| self.HEIGHTPROF = 0 | |||
| self.xdata = None | |||
| self.ydata = None | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r573 | self.PLOT_CODE = BEACON_CODE | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.FTP_WEI = None | |
| self.EXP_CODE = None | |||
| self.SUB_EXP_CODE = None | |||
| self.PLOT_POS = None | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.filename_phase = None | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.figfile = None | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r568 | self.xmin = None | |
| self.xmax = None | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | def getSubplots(self): | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | ncol = 1 | |
| nrow = 1 | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | return nrow, ncol | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.__showprofile = showprofile | |
| self.nplots = nplots | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | ncolspan = 7 | |
| colspan = 6 | |||
| self.__nsubplots = 2 | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.createFigure(id = id, | |
| wintitle = wintitle, | |||
| widthplot = self.WIDTH+self.WIDTHPROF, | |||
| heightplot = self.HEIGHT+self.HEIGHTPROF, | |||
| show=show) | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | nrow, ncol = self.getSubplots() | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| def save_phase(self, filename_phase): | |||
|
Juan C. Valdez
|
r858 | f = open(filename_phase,'w+') | |
|
Daniel Valdez
|
r494 | f.write('\n\n') | |
| f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | |||
|
Juan C. Valdez
|
r858 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | |
|
Daniel Valdez
|
r494 | 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() | |||
|
Juan C. Espinoza
|
r1285 | def plot(self): | |
| log.warning('TODO: Not yet implemented...') | |||
|
Daniel Valdez
|
r494 | ||
| def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |||
|
Miguel Valdez
|
r760 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | |
|
Daniel Valdez
|
r494 | timerange=None, | |
|
Miguel Valdez
|
r568 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
|
Daniel Valdez
|
r494 | server=None, folder=None, username=None, password=None, | |
| ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |||
|
Juan C. Valdez
|
r858 | ||
|
Alexander Valdez
|
r1696 | if dataOut.flagNoData: | |
|
George Yong
|
r1171 | return dataOut | |
|
Miguel Valdez
|
r760 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| return | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | if pairsList == None: | |
|
Miguel Valdez
|
r760 | pairsIndexList = dataOut.pairsIndexList[:10] | |
|
Daniel Valdez
|
r494 | else: | |
| pairsIndexList = [] | |||
| for pair in pairsList: | |||
| if pair not in dataOut.pairsList: | |||
|
George Yong
|
r1167 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) | |
|
Daniel Valdez
|
r494 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | if pairsIndexList == []: | |
| return | |||
|
Juan C. Valdez
|
r858 | ||
|
Juan C. Espinoza
|
r1207 | # if len(pairsIndexList) > 4: | |
| # pairsIndexList = pairsIndexList[0:4] | |||
|
Miguel Valdez
|
r760 | ||
| hmin_index = None | |||
| hmax_index = None | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if hmin != None and hmax != None: | |
| indexes = numpy.arange(dataOut.nHeights) | |||
| hmin_list = indexes[dataOut.heightList >= hmin] | |||
| hmax_list = indexes[dataOut.heightList <= hmax] | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if hmin_list.any(): | |
| hmin_index = hmin_list[0] | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if hmax_list.any(): | |
| hmax_index = hmax_list[-1]+1 | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | x = dataOut.getTimeRange() | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | thisDatetime = dataOut.datatime | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
|
Daniel Valdez
|
r494 | xlabel = "Local Time" | |
|
Miguel Valdez
|
r760 | ylabel = "Phase (degrees)" | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | update_figfile = False | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | nplots = len(pairsIndexList) | |
| phase_beacon = numpy.zeros(len(pairsIndexList)) | |||
| for i in range(nplots): | |||
| pair = dataOut.pairsList[pairsIndexList[i]] | |||
|
Miguel Valdez
|
r760 | 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) | |||
|
Daniel Valdez
|
r494 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if dataOut.beacon_heiIndexList: | |
| phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | |||
| else: | |||
| phase_beacon[i] = numpy.average(phase) | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if not self.isConfig: | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | nplots = len(pairsIndexList) | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.setup(id=id, | |
| nplots=nplots, | |||
| wintitle=wintitle, | |||
| showprofile=showprofile, | |||
| show=show) | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r568 | if timerange != None: | |
| self.timerange = timerange | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r568 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if ymin == None: ymin = 0 | |
| if ymax == None: ymax = 360 | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.FTP_WEI = ftp_wei | |
| self.EXP_CODE = exp_code | |||
| self.SUB_EXP_CODE = sub_exp_code | |||
| self.PLOT_POS = plot_pos | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
|
Miguel Valdez
|
r760 | self.isConfig = True | |
|
Daniel Valdez
|
r494 | self.figfile = figfile | |
| self.xdata = numpy.array([]) | |||
| self.ydata = numpy.array([]) | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | update_figfile = True | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | #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) | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.setWinTitle(title) | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | axes = self.axesList[0] | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | if len(self.ydata)==0: | |
| self.ydata = phase_beacon.reshape(-1,1) | |||
| else: | |||
| self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
|
Miguel Valdez
|
r568 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
|
Daniel Valdez
|
r494 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| XAxisAsTime=True, grid='both' | |||
| ) | |||
|
Juan C. Valdez
|
r858 | ||
|
Daniel Valdez
|
r494 | self.draw() | |
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r760 | if dataOut.ltctime >= self.xmax: | |
|
Daniel Valdez
|
r494 | self.counter_imagwr = wr_period | |
|
Miguel Valdez
|
r760 | self.isConfig = False | |
| update_figfile = True | |||
|
Juan C. Valdez
|
r858 | ||
|
Miguel Valdez
|
r573 | self.save(figpath=figpath, | |
| figfile=figfile, | |||
| save=save, | |||
| ftp=ftp, | |||
| wr_period=wr_period, | |||
| thisDatetime=thisDatetime, | |||
|
George Yong
|
r1171 | update_figfile=update_figfile) | |
|
George Yong
|
r1179 | return dataOut |
