jroplot_spectra.py
1351 lines
| 45.8 KiB
| text/x-python
|
PythonLexer
|
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 | ||||
|
r568 | |||
r1343 | """ | |||
|
r1285 | |||
|
r487 | import os | ||
import numpy | ||||
r1561 | #import collections.abc | |||
|
r487 | |||
r1343 | from schainpy.model.graphics.jroplot_base import Plot, plt, log | |||
|
r953 | |||
|
r1285 | class SpectraPlot(Plot): | ||
''' | ||||
Plot for Spectra data | ||||
''' | ||||
|
r858 | |||
|
r1285 | CODE = 'spc' | ||
colormap = 'jet' | ||||
plot_type = 'pcolor' | ||||
r1343 | buffering = False | |||
|
r858 | |||
|
r1285 | def setup(self): | ||
r1377 | ||||
|
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 | |||
|
r1285 | self.cb_label = 'dB' | ||
if self.showprofile: | ||||
self.width = 4 * self.ncols | ||||
|
r487 | else: | ||
|
r1285 | self.width = 3.5 * self.ncols | ||
r1377 | self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18}) | |||
|
r1285 | self.ylabel = 'Range [km]' | ||
r1343 | def update(self, dataOut): | |||
data = {} | ||||
meta = {} | ||||
r1549 | ||||
r1343 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) | |||
r1600 | #print("dataOut.normFactor: ", dataOut.normFactor) | |||
#print("spc: ", dataOut.data_spc[0,0,0]) | ||||
#spc = 10*numpy.log10(dataOut.data_spc) | ||||
r1549 | #print("Spc: ",spc[0]) | |||
#exit(1) | ||||
r1343 | data['spc'] = spc | |||
data['rti'] = dataOut.getPower() | ||||
r1549 | #print(data['rti'][0]) | |||
#exit(1) | ||||
r1542 | #print("NormFactor: ",dataOut.normFactor) | |||
r1504 | #data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |||
if hasattr(dataOut, 'LagPlot'): #Double Pulse | ||||
max_hei_id = dataOut.nHeights - 2*dataOut.LagPlot | ||||
#data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=46,ymax_index=max_hei_id)/dataOut.normFactor) | ||||
#data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=40,ymax_index=max_hei_id)/dataOut.normFactor) | ||||
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) | ||||
#data['noise'][1] = 22.035507 | ||||
else: | ||||
data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | ||||
#data['noise'] = 10*numpy.log10(dataOut.getNoise(ymin_index=26,ymax_index=44)/dataOut.normFactor) | ||||
r1786 | extrapoints = spc.shape[1] % dataOut.nFFTPoints | |||
r1787 | meta['xrange'] = (dataOut.getFreqRange(extrapoints)/1000., dataOut.getAcfRange(extrapoints), dataOut.getVelRange(extrapoints)) | |||
r1389 | ||||
r1343 | if self.CODE == 'spc_moments': | |||
data['moments'] = dataOut.moments | ||||
|
r1358 | if self.CODE == 'gaussian_fit': | ||
data['gaussfit'] = dataOut.DGauFitParams | ||||
r1389 | return data, meta | |||
|
r1285 | def plot(self): | ||
r1377 | ||||
|
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)" | ||||
|
r965 | else: | ||
|
r1285 | x = self.data.xrange[2] | ||
self.xlabel = "Velocity (m/s)" | ||||
|
r1358 | if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'): | ||
|
r1285 | x = self.data.xrange[2] | ||
self.xlabel = "Velocity (m/s)" | ||||
self.titles = [] | ||||
r1343 | y = self.data.yrange | |||
|
r1285 | self.y = y | ||
r1343 | ||||
data = self.data[-1] | ||||
z = data['spc'] | ||||
|
r1285 | |||
r1377 | self.CODE2 = 'spc_oblique' | |||
|
r1285 | for n, ax in enumerate(self.axes): | ||
r1343 | noise = data['noise'][n] | |||
|
r1285 | if self.CODE == 'spc_moments': | ||
|
r1358 | mean = data['moments'][n, 1] | ||
r1389 | if self.CODE == 'gaussian_fit': | |||
|
r1358 | gau0 = data['gaussfit'][n][2,:,0] | ||
gau1 = data['gaussfit'][n][2,:,1] | ||||
|
r1285 | if ax.firsttime: | ||
self.xmax = self.xmax if self.xmax else numpy.nanmax(x) | ||||
r1504 | self.xmin = self.xmin if self.xmin else numpy.nanmin(x)#-self.xmax | |||
r1550 | #self.zmin = self.zmin if self.zmin else numpy.nanmin(z) | |||
#self.zmax = self.zmax if self.zmax else numpy.nanmax(z) | ||||
r1551 | if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | ||||
r1542 | ||||
|
r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T, | ||
r1551 | vmin=self.zmin, | |||
vmax=self.zmax, | ||||
r1542 | cmap=plt.get_cmap(self.colormap), | |||
|
r1285 | ) | ||
if self.showprofile: | ||||
ax.plt_profile = self.pf_axes[n].plot( | ||||
r1343 | data['rti'][n], y)[0] | |||
|
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': | ||||
|
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] | ||||
|
r1285 | else: | ||
r1551 | if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | ||||
|
r1285 | ax.plt.set_array(z[n].T.ravel()) | ||
if self.showprofile: | ||||
r1343 | ax.plt_profile.set_data(data['rti'][n], y) | |||
|
r1285 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) | ||
if self.CODE == 'spc_moments': | ||||
ax.plt_mean.set_data(mean, y) | ||||
|
r1358 | if self.CODE == 'gaussian_fit': | ||
ax.plt_gau0.set_data(gau0, y) | ||||
ax.plt_gau1.set_data(gau1, y) | ||||
|
r1285 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | ||
r1377 | class SpectraObliquePlot(Plot): | |||
''' | ||||
Plot for Spectra data | ||||
''' | ||||
r1381 | CODE = 'spc_oblique' | |||
r1377 | 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]' | ||||
r1381 | def update(self, dataOut): | |||
r1389 | ||||
r1381 | data = {} | |||
meta = {} | ||||
r1567 | ||||
r1381 | 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)) | ||||
r1549 | ''' | |||
data['shift1'] = dataOut.Oblique_params[0,-2,:] | ||||
data['shift2'] = dataOut.Oblique_params[0,-1,:] | ||||
data['shift1_error'] = dataOut.Oblique_param_errors[0,-2,:] | ||||
data['shift2_error'] = dataOut.Oblique_param_errors[0,-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,:] | ||||
''' | ||||
data['shift1'] = dataOut.Dop_EEJ_T1[0] | ||||
data['shift2'] = dataOut.Dop_EEJ_T2[0] | ||||
r1561 | data['max_val_2'] = dataOut.Oblique_params[0,-1,:] | |||
r1549 | data['shift1_error'] = dataOut.Err_Dop_EEJ_T1[0] | |||
data['shift2_error'] = dataOut.Err_Dop_EEJ_T2[0] | ||||
r1389 | ||||
return data, meta | ||||
r1381 | ||||
r1377 | 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 = [] | ||||
r1381 | y = self.data.yrange | |||
r1377 | self.y = y | |||
r1549 | ||||
data = self.data[-1] | ||||
z = data['spc'] | ||||
r1377 | ||||
for n, ax in enumerate(self.axes): | ||||
noise = self.data['noise'][n][-1] | ||||
r1549 | shift1 = data['shift1'] | |||
#print(shift1) | ||||
shift2 = data['shift2'] | ||||
r1561 | max_val_2 = data['max_val_2'] | |||
r1549 | err1 = data['shift1_error'] | |||
err2 = data['shift2_error'] | ||||
r1377 | if ax.firsttime: | |||
r1549 | ||||
r1377 | 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] | ||||
r1389 | ||||
r1549 | 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) | ||||
r1561 | 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) | |||
r1549 | #print("plotter1: ", self.ploterr1,shift1) | |||
r1377 | else: | |||
r1549 | #print("else plotter1: ", self.ploterr1,shift1) | |||
r1377 | self.ploterr1.remove() | |||
self.ploterr2.remove() | ||||
r1561 | self.ploterr3.remove() | |||
r1377 | 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) | ||||
r1549 | 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) | ||||
r1561 | 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) | |||
r1377 | ||||
self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | ||||
r1381 | ||||
|
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 | |||
r1377 | self.height = 5 * self.nrows | |||
|
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}) | |||
|
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) | ||||
r1389 | return data, meta | |||
|
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)" | ||||
|
r777 | else: | ||
|
r1285 | x = self.data.xrange[2] | ||
self.xlabel = "Velocity (m/s)" | ||||
r1377 | ||||
|
r1285 | self.titles = [] | ||
r1343 | y = self.data.yrange | |||
|
r1285 | self.y = y | ||
r1343 | data = self.data[-1] | |||
cspc = data['cspc'] | ||||
|
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] | ||||
|
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])) | ||||
r1389 | ||||
r1343 | ax = self.axes[2 * n + 1] | |||
|
r1285 | if ax.firsttime: | ||
ax.plt = ax.pcolormesh(x, y, phase.T, | ||||
vmin=-180, | ||||
vmax=180, | ||||
r1377 | cmap=plt.get_cmap(self.colormap_phase) | |||
|
r1285 | ) | ||
else: | ||||
ax.plt.set_array(phase.T.ravel()) | ||||
self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1])) | ||||
r1377 | 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])) | ||||
|
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' | ||||
r1377 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95}) | |||
|
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() | ||||
r1549 | #print(numpy.shape(data['rti'])) | |||
r1504 | ||||
r1343 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) | |||
return data, meta | ||||
|
r1285 | def plot(self): | ||
r1504 | ||||
|
r1285 | self.x = self.data.times | ||
r1343 | self.y = self.data.yrange | |||
|
r1285 | self.z = self.data[self.CODE] | ||
r1600 | #print("Inside RTI: ", self.z) | |||
r1377 | 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()) | ||||
r1600 | #print("self.z: ", self.z) | |||
#exit(1) | ||||
r1551 | ''' | |||
r1550 | if not isinstance(self.zmin, collections.abc.Sequence): | |||
if not self.zmin: | ||||
self.zmin = [numpy.min(self.z)]*len(self.axes) | ||||
else: | ||||
self.zmin = [self.zmin]*len(self.axes) | ||||
if not isinstance(self.zmax, collections.abc.Sequence): | ||||
if not self.zmax: | ||||
self.zmax = [numpy.max(self.z)]*len(self.axes) | ||||
else: | ||||
self.zmax = [self.zmax]*len(self.axes) | ||||
r1551 | ''' | |||
r1377 | for n, ax in enumerate(self.axes): | |||
r1550 | ||||
r1551 | self.zmin = self.zmin if self.zmin else numpy.min(self.z) | |||
self.zmax = self.zmax if self.zmax else numpy.max(self.z) | ||||
r1549 | ||||
r1377 | if ax.firsttime: | |||
r1551 | if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | ||||
r1377 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |||
r1551 | vmin=self.zmin, | |||
vmax=self.zmax, | ||||
r1377 | 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: | ||||
r1551 | if self.zlimits is not None: | |||
self.zmin, self.zmax = self.zlimits[n] | ||||
r1737 | ax.plt.remove() | |||
r1377 | ax.plt = ax.pcolormesh(x, y, z[n].T, | |||
r1551 | vmin=self.zmin, | |||
vmax=self.zmax, | ||||
r1377 | 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 | ||||
''' | ||||
r1504 | CODE = 'Spectrogram_Profile' | |||
r1377 | 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' | ||||
r1504 | #self.cb_label = 'dB' | |||
r1377 | self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95}) | |||
r1504 | self.titles = [] | |||
#self.titles = ['{} Channel {} \n H = {} km ({} - {})'.format( | ||||
#self.CODE.upper(), x, self.data.heightList[self.data.hei], self.data.heightList[self.data.hei],self.data.heightList[self.data.hei]+(self.data.DH*self.data.nProfiles)) for x in range(self.nrows)] | ||||
self.titles = ['{} Channel {}'.format( | ||||
self.CODE.upper(), x) for x in range(self.nrows)] | ||||
r1377 | ||||
r1389 | def update(self, dataOut): | |||
data = {} | ||||
meta = {} | ||||
r1504 | maxHei = 1620#+12000 | |||
r1727 | maxHei = 1180 | |||
r1757 | maxHei = 500 | |||
r1389 | indb = numpy.where(dataOut.heightList <= maxHei) | |||
hei = indb[0][-1] | ||||
r1504 | #print(dataOut.heightList) | |||
r1389 | ||||
factor = dataOut.nIncohInt | ||||
z = dataOut.data_spc[:,:,hei] / factor | ||||
z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | ||||
#buffer = 10 * numpy.log10(z) | ||||
r1504 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) | |||
r1389 | ||||
r1504 | #self.hei = hei | |||
#self.heightList = dataOut.heightList | ||||
#self.DH = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step | ||||
#self.nProfiles = dataOut.nProfiles | ||||
r1389 | ||||
r1504 | data['Spectrogram_Profile'] = 10 * numpy.log10(z) | |||
r1389 | ||||
r1504 | data['hei'] = hei | |||
data['DH'] = (dataOut.heightList[1] - dataOut.heightList[0])/dataOut.step | ||||
data['nProfiles'] = dataOut.nProfiles | ||||
#meta['yrange'] = dataOut.heightList[0:dataOut.NSHTS] | ||||
''' | ||||
import matplotlib.pyplot as plt | ||||
plt.plot(10 * numpy.log10(z[0,:])) | ||||
plt.show() | ||||
from time import sleep | ||||
sleep(10) | ||||
''' | ||||
r1389 | return data, meta | |||
r1377 | def plot(self): | |||
r1381 | ||||
r1377 | self.x = self.data.times | |||
self.z = self.data[self.CODE] | ||||
self.y = self.data.xrange[0] | ||||
r1389 | ||||
r1504 | hei = self.data['hei'][-1] | |||
DH = self.data['DH'][-1] | ||||
nProfiles = self.data['nProfiles'][-1] | ||||
r1377 | self.ylabel = "Frequency (kHz)" | |||
|
r1285 | 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) | ||||
|
r965 | else: | ||
|
r1285 | 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) | ||||
r1343 | data = self.data[-1] | |||
|
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) | ||||
) | ||||
else: | ||||
r1737 | ax.plt.remove() | |||
|
r1285 | ax.plt = ax.pcolormesh(x, y, z[n].T, | ||
vmin=self.zmin, | ||||
vmax=self.zmax, | ||||
cmap=plt.get_cmap(self.colormap) | ||||
) | ||||
r1504 | ||||
#self.titles.append('Spectrogram') | ||||
#self.titles.append('{} Channel {} \n H = {} km ({} - {})'.format( | ||||
#self.CODE.upper(), x, y[hei], y[hei],y[hei]+(DH*nProfiles))) | ||||
|
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] | ||||
|
r825 | else: | ||
|
r1285 | self.cb_label = 'Degrees' | ||
self.titles = [ | ||||
'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs] | ||||
|
r858 | |||
r1343 | def update(self, dataOut): | |||
data = {} | ||||
meta = {} | ||||
data['coh'] = dataOut.getCoherence() | ||||
meta['pairs'] = dataOut.pairsList | ||||
return data, meta | ||||
|
r858 | |||
|
r1285 | class PhasePlot(CoherencePlot): | ||
''' | ||||
Plot for Phase map data | ||||
''' | ||||
|
r858 | |||
|
r1285 | CODE = 'phase' | ||
colormap = 'seismic' | ||||
|
r858 | |||
r1343 | def update(self, dataOut): | |||
data = {} | ||||
meta = {} | ||||
data['phase'] = dataOut.getCoherence(phase=True) | ||||
meta['pairs'] = dataOut.pairsList | ||||
return data, meta | ||||
|
r858 | |||
|
r1285 | class NoisePlot(Plot): | ||
''' | ||||
r1377 | Plot for noise | |||
|
r1285 | ''' | ||
|
r858 | |||
|
r1285 | CODE = 'noise' | ||
plot_type = 'scatterbuffer' | ||||
|
r858 | |||
|
r1285 | def setup(self): | ||
self.xaxis = 'time' | ||||
self.ncols = 1 | ||||
self.nrows = 1 | ||||
self.nplots = 1 | ||||
self.ylabel = 'Intensity [dB]' | ||||
|
r1308 | self.xlabel = 'Time' | ||
|
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 | ||||
|
r858 | |||
|
r1285 | def plot(self): | ||
|
r858 | |||
|
r1285 | x = self.data.times | ||
xmin = self.data.min_time | ||||
xmax = xmin + self.xrange * 60 * 60 | ||||
r1343 | Y = self.data['noise'] | |||
|
r858 | |||
|
r1285 | if self.axes[0].firsttime: | ||
r1343 | self.ymin = numpy.nanmin(Y) - 5 | |||
self.ymax = numpy.nanmax(Y) + 5 | ||||
|
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)) | |||
|
r832 | else: | ||
|
r1285 | for ch in self.data.channels: | ||
y = Y[ch] | ||||
self.axes[0].lines[ch].set_data(x, y) | ||||
|
r858 | |||
|
r1285 | self.ymin = numpy.nanmin(Y) - 5 | ||
r1377 | self.ymax = numpy.nanmax(Y) + 10 | |||
|
r487 | |||
|
r858 | |||
|
r1285 | class PowerProfilePlot(Plot): | ||
|
r858 | |||
r1343 | CODE = 'pow_profile' | |||
|
r1285 | plot_type = 'scatter' | ||
|
r858 | |||
|
r1285 | def setup(self): | ||
|
r858 | |||
|
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 | ||||
|
r858 | |||
r1343 | def update(self, dataOut): | |||
data = {} | ||||
meta = {} | ||||
data[self.CODE] = dataOut.getPower() | ||||
return data, meta | ||||
|
r1285 | def plot(self): | ||
|
r858 | |||
r1343 | y = self.data.yrange | |||
|
r1285 | self.y = y | ||
|
r858 | |||
r1343 | x = self.data[-1][self.CODE] | |||
r1389 | ||||
|
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 | ||||
r1377 | ||||
|
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() | ||||
|
r777 | else: | ||
|
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 = {} | ||||
r1504 | 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)) | ||||
|
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 | |||
|
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)" | ||||
|
r487 | else: | ||
|
r1358 | x = self.data.xrange[2][:-1] | ||
self.xlabel = "Velocity (m/s)" | ||||
r1389 | ||||
|
r1358 | if self.CODE == 'cut_gaussian_fit': | ||
x = self.data.xrange[2][:-1] | ||||
|
r1285 | self.xlabel = "Velocity (m/s)" | ||
|
r858 | |||
|
r1285 | self.titles = [] | ||
|
r858 | |||
r1343 | y = self.data.yrange | |||
|
r1358 | data = self.data[-1] | ||
z = data['spc'] | ||||
|
r858 | |||
|
r1285 | if self.height_index: | ||
index = numpy.array(self.height_index) | ||||
|
r487 | else: | ||
|
r1285 | index = numpy.arange(0, len(y), int((len(y))/9)) | ||
|
r858 | |||
|
r1285 | for n, ax in enumerate(self.axes): | ||
r1389 | if self.CODE == 'cut_gaussian_fit': | |||
|
r1358 | gau0 = data['gauss_fit0'] | ||
gau1 = data['gauss_fit1'] | ||||
|
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 | ||||
r1504 | self.ymin = self.ymin if self.ymin else numpy.nanmin(z[:,:,index]) | |||
self.ymax = self.ymax if self.ymax else numpy.nanmax(z[:,:,index]) | ||||
#print(self.ymax) | ||||
#print(z[n, :, index]) | ||||
|
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): | ||||
r1389 | line.set_color(ax.plt[i].get_color()) | |||
|
r1358 | ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--') | ||
for i, line in enumerate(ax.plt_gau1): | ||||
r1389 | line.set_color(ax.plt[i].get_color()) | |||
|
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): | ||||
|
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()) | ||||
|
r1285 | self.titles.append('CH {}'.format(n)) | ||
|
r858 | |||
|
r1171 | |||
|
r1285 | class BeaconPhase(Plot): | ||
|
r858 | |||
|
r494 | __isConfig = None | ||
__nsubplots = None | ||||
PREFIX = 'beacon_phase' | ||||
|
r858 | |||
|
r1179 | def __init__(self): | ||
|
r1285 | Plot.__init__(self) | ||
|
r494 | self.timerange = 24*60*60 | ||
|
r760 | self.isConfig = False | ||
|
r494 | self.__nsubplots = 1 | ||
self.counter_imagwr = 0 | ||||
|
r760 | self.WIDTH = 800 | ||
self.HEIGHT = 400 | ||||
|
r494 | self.WIDTHPROF = 120 | ||
self.HEIGHTPROF = 0 | ||||
self.xdata = None | ||||
self.ydata = None | ||||
|
r858 | |||
|
r573 | self.PLOT_CODE = BEACON_CODE | ||
|
r858 | |||
|
r494 | self.FTP_WEI = None | ||
self.EXP_CODE = None | ||||
self.SUB_EXP_CODE = None | ||||
self.PLOT_POS = None | ||||
|
r858 | |||
|
r494 | self.filename_phase = None | ||
|
r858 | |||
|
r494 | self.figfile = None | ||
|
r858 | |||
|
r568 | self.xmin = None | ||
self.xmax = None | ||||
|
r858 | |||
|
r494 | def getSubplots(self): | ||
|
r858 | |||
|
r494 | ncol = 1 | ||
nrow = 1 | ||||
|
r858 | |||
|
r494 | return nrow, ncol | ||
|
r858 | |||
|
r494 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | ||
|
r858 | |||
|
r494 | self.__showprofile = showprofile | ||
self.nplots = nplots | ||||
|
r858 | |||
|
r494 | ncolspan = 7 | ||
colspan = 6 | ||||
self.__nsubplots = 2 | ||||
|
r858 | |||
|
r494 | self.createFigure(id = id, | ||
wintitle = wintitle, | ||||
widthplot = self.WIDTH+self.WIDTHPROF, | ||||
heightplot = self.HEIGHT+self.HEIGHTPROF, | ||||
show=show) | ||||
|
r858 | |||
|
r494 | nrow, ncol = self.getSubplots() | ||
|
r858 | |||
|
r494 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | ||
def save_phase(self, filename_phase): | ||||
|
r858 | f = open(filename_phase,'w+') | ||
|
r494 | f.write('\n\n') | ||
f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | ||||
|
r858 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | ||
|
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() | ||||
|
r1285 | def plot(self): | ||
log.warning('TODO: Not yet implemented...') | ||||
|
r494 | |||
def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | ||||
|
r760 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | ||
|
r494 | timerange=None, | ||
|
r568 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | ||
|
r494 | server=None, folder=None, username=None, password=None, | ||
ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | ||||
|
r858 | |||
r1377 | if dataOut.flagNoData: | |||
|
r1171 | return dataOut | ||
|
r760 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | ||
return | ||||
|
r858 | |||
|
r494 | if pairsList == None: | ||
|
r760 | pairsIndexList = dataOut.pairsIndexList[:10] | ||
|
r494 | else: | ||
pairsIndexList = [] | ||||
for pair in pairsList: | ||||
if pair not in dataOut.pairsList: | ||||
|
r1167 | raise ValueError("Pair %s is not in dataOut.pairsList" %(pair)) | ||
|
r494 | pairsIndexList.append(dataOut.pairsList.index(pair)) | ||
|
r858 | |||
|
r494 | if pairsIndexList == []: | ||
return | ||||
|
r858 | |||
|
r1207 | # if len(pairsIndexList) > 4: | ||
# pairsIndexList = pairsIndexList[0:4] | ||||
|
r760 | |||
hmin_index = None | ||||
hmax_index = None | ||||
|
r858 | |||
|
r760 | if hmin != None and hmax != None: | ||
indexes = numpy.arange(dataOut.nHeights) | ||||
hmin_list = indexes[dataOut.heightList >= hmin] | ||||
hmax_list = indexes[dataOut.heightList <= hmax] | ||||
|
r858 | |||
|
r760 | if hmin_list.any(): | ||
hmin_index = hmin_list[0] | ||||
|
r858 | |||
|
r760 | if hmax_list.any(): | ||
hmax_index = hmax_list[-1]+1 | ||||
|
r858 | |||
|
r494 | x = dataOut.getTimeRange() | ||
|
r858 | |||
|
r760 | thisDatetime = dataOut.datatime | ||
|
r858 | |||
|
r760 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | ||
|
r494 | xlabel = "Local Time" | ||
|
r760 | ylabel = "Phase (degrees)" | ||
|
r858 | |||
|
r760 | update_figfile = False | ||
|
r858 | |||
|
r494 | 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]] | ||||
|
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) | ||||
|
r494 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | ||
phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | ||||
|
r858 | |||
|
r760 | if dataOut.beacon_heiIndexList: | ||
phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | ||||
else: | ||||
phase_beacon[i] = numpy.average(phase) | ||||
|
r858 | |||
|
r760 | if not self.isConfig: | ||
|
r858 | |||
|
r494 | nplots = len(pairsIndexList) | ||
|
r858 | |||
|
r494 | self.setup(id=id, | ||
nplots=nplots, | ||||
wintitle=wintitle, | ||||
showprofile=showprofile, | ||||
show=show) | ||||
|
r858 | |||
|
r568 | if timerange != None: | ||
self.timerange = timerange | ||||
|
r858 | |||
|
r568 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | ||
|
r858 | |||
|
r760 | if ymin == None: ymin = 0 | ||
if ymax == None: ymax = 360 | ||||
|
r858 | |||
|
r494 | self.FTP_WEI = ftp_wei | ||
self.EXP_CODE = exp_code | ||||
self.SUB_EXP_CODE = sub_exp_code | ||||
self.PLOT_POS = plot_pos | ||||
|
r858 | |||
|
r494 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | ||
|
r760 | self.isConfig = True | ||
|
r494 | self.figfile = figfile | ||
self.xdata = numpy.array([]) | ||||
self.ydata = numpy.array([]) | ||||
|
r858 | |||
|
r760 | update_figfile = True | ||
|
r858 | |||
|
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) | ||||
#self.save_phase(self.filename_phase) | ||||
|
r858 | |||
|
r494 | #store data beacon phase | ||
#self.save_data(self.filename_phase, phase_beacon, thisDatetime) | ||||
|
r858 | |||
|
r494 | self.setWinTitle(title) | ||
|
r858 | |||
|
r760 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | ||
|
r858 | |||
|
r760 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | ||
|
r858 | |||
|
r494 | axes = self.axesList[0] | ||
|
r858 | |||
|
r494 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | ||
|
r858 | |||
|
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))) | ||||
|
r858 | |||
|
r494 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | ||
|
r568 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | ||
|
r494 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | ||
XAxisAsTime=True, grid='both' | ||||
) | ||||
|
r858 | |||
|
r494 | self.draw() | ||
|
r858 | |||
|
r760 | if dataOut.ltctime >= self.xmax: | ||
|
r494 | self.counter_imagwr = wr_period | ||
|
r760 | self.isConfig = False | ||
update_figfile = True | ||||
|
r858 | |||
|
r573 | self.save(figpath=figpath, | ||
figfile=figfile, | ||||
save=save, | ||||
ftp=ftp, | ||||
wr_period=wr_period, | ||||
thisDatetime=thisDatetime, | ||||
|
r1171 | update_figfile=update_figfile) | ||
r1377 | return dataOut | |||