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step_lib_plt.py
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step_lib_plt.py
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#! /usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import readfil
from matplotlib.colors import ListedColormap
from matplotlib import cm
import random
def plotwinx(axes, totalch, fn):
ax = axes.twinx()
ax.set_ylabel("Channel", color='w')
ax.set_ylim(totalch, 0)
ax.tick_params(colors='w')
ax.spines['right'].set_color('w')
ax.spines['left'].set_color('w')
ax.spines['top'].set_color('w')
ax.spines['bottom'].set_color('w')
ax.plot((fn.mean(axis=0)), np.arange(totalch-1, -0.1, -1), color='w', linewidth=1)
return ax
def plotdmraw(finn, dess, pltime, pldm, filname, avg, freqavg, med, rms, totalch, smap,
smpmax, header, totalsm, delay, maxbc, choff_low, choff_high, pdf,
plotpes, ispsrfits):
viewdw = smpmax//4*2
#### Read Para ####
if header['foff'] < 0:
ymax = header['fch1'] + header['foff']*choff_high*freqavg
ymin = header['fch1'] + header['foff']*header['nchans'] - header['foff']*choff_low*freqavg
else:
ymax = header['fch1'] + header['foff']*header['nchans'] - header['foff']*choff_high*freqavg
ymin = header['fch1'] + header['foff']*choff_low*freqavg
smpt = header['tsamp']*1e6
freqctr = (ymax+ymin)/2
timeoff = pltime*header['tsamp']*avg
# print(timeoff, pltime)
if ispsrfits :
telescope_id = header['telescope_id']
machine_id = header['machine_id']
else:
if header['telescope_id'] in [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 21, 64, 65]:
telescope_id = readfil.ids_to_telescope[header['telescope_id']]
else:
telescope_id = 'Unknow'
if header['machine_id'] in [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 20, 64, 65]:
machine_id = readfil.ids_to_machine[header['machine_id']]
else:
machine_id = 'Unknow'
#### Clac MaxSNR ####
# snr = (dess[:smpmax].copy().mean(axis=1)-med*maxbc)/(rms*np.sqrt(maxbc))
snr = (dess[:smpmax].copy().mean(axis=1)-med)/rms
maxsigma = np.max(snr)
sigma = snr[smpmax//2]
sampleoff = (np.argmax(snr) - smpmax//2)*smpt*1e-6*avg
# print(smpmax, np.argmax(snr))
#### SET DATA ####
fn = (dess[int(smpmax//2-viewdw): int(smpmax//2+viewdw)])[:, ::-1]
fn2 = (finn[int(smpmax//2-viewdw): int(smpmax//2+viewdw)])[:, ::-1]
fn = fn - fn.mean(axis = 0)
fn2 = fn2 - fn2.mean(axis = 0)
xlim = float(-smpmax//4*2)*smpt*1e-6*avg
xmax = float(+smpmax//4*2)*smpt*1e-6*avg
xstick = [xlim+(xmax-xlim)/4, xlim+(xmax-xlim)/2, xlim+(xmax-xlim)*3/4]
#### Plot ####
# print(fn.shape, viewdw, smpmax, int(smpmax//2-viewdw), int(smpmax//2+viewdw))
fig, axes = plt.subplots(3, 2, gridspec_kw={'height_ratios':[1,3,3], 'width_ratios':[10, 1]})
fig.set_facecolor('k')
fig.set_size_inches(15, 10)
plt.subplots_adjust(wspace= 0.01, hspace= 0.02, left=0.06, bottom=0.07, right=0.95, top=0.88)
#### Plot TEXT ####
fig.suptitle("STEP_SNAPSHOT Pulse: %s Offset: %8.4fs %s DM: %4.4f \
Average:%3d %sFreqAvg:%3d %sBOXCAR:%3d %sBeam: %3d/%3d\n\n\n\n\n"%(filname.ljust(25,' '),
timeoff, ' '.ljust(3,' '), pldm, avg, ' '.ljust(3,' '), freqavg, ' '.ljust(3,' '), maxbc,
' '.ljust(3,' '), header['ibeam'], header['nbeams']), color='1')
fig.text(0.12, 0.94, "Source: %s"%header['source_name'], color='1', size=12)
fig.text(0.12, 0.92, "Telscope: %s"%telescope_id, color='1', size=12)
fig.text(0.12, 0.90, "Instrument: %s"%machine_id, color='1', size=12)
fig.text(0.4, 0.94, "RA (J2000): %s"%str(header['src_raj']), color='1', size=12)
fig.text(0.4, 0.92, "DEC (J2000): %s"%str(header['src_dej']), color='1', size=12)
fig.text(0.4, 0.90, "MJD(bary): %s"%str(header['tstart']), color='1', size=12)
fig.text(0.65, 0.94, "N samples: %s"%str(totalsm), color='1', size=12)
fig.text(0.65, 0.92, "Sampling time: %s us"%str(smpt), color='1', size=12)
fig.text(0.65, 0.90, "Freq(ctr): %s MHz"%str(freqctr), color='1', size=12)
### SET STYLE ####
for yl in range(3):
axes[yl, 1].set_yticks([])
for xl in range(2):
if yl == 2 or xl != 1 :
axes[yl, xl].set_facecolor('k')
axes[yl, xl].tick_params(colors='w')
axes[yl, xl].spines['right'].set_color('w')
axes[yl, xl].spines['left'].set_color('w')
axes[yl, xl].spines['top'].set_color('w')
axes[yl, xl].spines['bottom'].set_color('w')
axes[0,1].set_facecolor('k')
axes[1,1].set_facecolor('k')
#### Plot Flux ####
axes[0,0].set_ylabel("Flux", color='w')
fig.text(0.875, 0.85, 'SNR: %4.3f'%sigma, color='1')
fig.text(0.875, 0.82, 'MAXSNR: %4.3f'%maxsigma, color='1')
fig.text(0.875, 0.79, 'OFFSET: %fs'%sampleoff, color='1')
axes[0,0].plot(np.arange(-viewdw, viewdw), (fn.mean(axis=1)), color='w', linewidth=1)
axes[0,0].set_xlim(-viewdw, viewdw)
axes[0,0].set_xticks([-viewdw/2, 0, viewdw/2])
#### Plot Result ####
re1 = axes[1,0].imshow(np.transpose(fn), aspect = 'auto', origin = 'lower',
extent = [-viewdw, viewdw, ymin, ymax],
cmap = 'plasma') # viridis, magma, Blues
axes[1,0].set_ylabel("Frequency (MHz)", color='w')
axes[1,0].tick_params(colors='w')
axes[1,0].set_xticks([-viewdw/2, 0, viewdw/2])
#### Plot Raw data ####
re2 = axes[2,0].imshow(np.transpose(fn2), aspect = 'auto', origin = 'lower',
extent = [xlim, xmax, ymin, ymax],
cmap = 'Blues') # viridis, magma, Blues
axes[2,0].set_ylabel("Frequency (MHz)", color='w')
axes[2,0].set_xlabel("Time (s)", color='w')
axes[2,0].tick_params(colors='w')
axes[2,0].set_xticks(xstick)
re1.set_clim(vmin=np.sort(fn).reshape(-1)[int(fn.size*(1-plotpes))], vmax= np.max(fn))
re2.set_clim(vmin=np.sort(fn2).reshape(-1)[int(fn2.size*(1-plotpes))], vmax= np.max(fn2))
#### Plot Raw Flux ####
plotwinx(axes[2,1], totalch, fn2)
axes[2,1].set_xlabel("Flux", color='w')
#### Plot colorbar ####
pst1 = fig.add_axes([0.875, 0.425, 0.012, 0.33])
pst1.set_facecolor('k')
cb1 = fig.colorbar(re1, cax=pst1)
cb1.ax.tick_params(colors='w')
pst2 = fig.add_axes([0.92, 0.425, 0.012, 0.33])
pst2.set_facecolor('k')
cb2 = fig.colorbar(re2, cax=pst2)
cb2.ax.tick_params(colors='w')
#### Save FIG File ####
pdf.savefig(facecolor='k')
plt.close()
def plotraw(fin1, fin2, smaples, filname, avg, freqavg, totalch, header, totalsm, choff_low,
choff_high, pdf, plotpes, ispsrfits, pldm, plbc, offset, winsize, maxsigma):
# cdict1 = {'red': ((0.0, 0.0, 0.0),
# (0.5, 0.0, 0.1),
# (1.0, 1.0, 1.0)),
# 'green': ((0.0, 0.0, 0.0),
# (1.0, 0.0, 0.0)),
# 'blue': ((0.0, 0.0, 1.0),
# (0.5, 0.1, 0.0),
# (1.0, 0.0, 0.0))}
# blue_red1 = LinearSegmentedColormap('BlueRed1', cdict1)
# inferno = cm.get_cmap('inferno', 256)
# newcolors = inferno(np.linspace(0, 1, 256))
# pink = np.array([0.993248, 0.906157, 0.143936, 1])
# newcolors[-50:, :] = pink
# newcmp = ListedColormap(newcolors)
## Resize data ##
plotrange = winsize #1024
if smaples > plotrange:
plotavg = smaples//plotrange
smaples = plotrange
fn = fin1[: plotavg*smaples, :].reshape(smaples, plotavg, -1).mean(axis=1)
fno2 = fin2[: plotavg*smaples, :].reshape(smaples, plotavg, -1).mean(axis=1)
else:
plotavg = 1
fn = fin1
fno2 = fin2
# fn = fn - fn.mean(axis = 0)
fn2 = fno2 - fno2.mean(axis = 0)
## Read Para ##
if header['foff'] < 0:
ymax = header['fch1']
ymin = header['fch1'] + header['foff']*header['nchans']
ymax2 = header['fch1'] + header['foff']*choff_high*freqavg
ymin2 = header['fch1'] + header['foff']*header['nchans'] - header['foff']*choff_low*freqavg
else:
ymax = header['fch1'] + header['foff']*header['nchans']
ymin = header['fch1']
ymax2 = header['fch1'] + header['foff']*header['nchans'] - header['foff']*choff_high*freqavg
ymin2 = header['fch1'] + header['foff']*choff_low*freqavg
smpt = header['tsamp']*1e6
freqctr = (ymax+ymin)/2
if ispsrfits:
telescope_id = header['telescope_id']
machine_id = header['machine_id']
else:
if header['telescope_id'] in [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 20, 21, 64, 65]:
telescope_id = readfil.ids_to_telescope[header['telescope_id']]
else:
telescope_id = 'Unknow'
if header['machine_id'] in [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 20, 64, 65]:
machine_id = readfil.ids_to_machine[header['machine_id']]
else:
machine_id = 'Unknow'
#### Plot ####
fig, axes = plt.subplots(3, 2, gridspec_kw={'height_ratios':[1,3,3], 'width_ratios':[10, 1]})
fig.set_facecolor('k')
fig.set_size_inches(15, 10)
plt.subplots_adjust(wspace= 0.01, hspace= 0.02, left=0.06, bottom=0.07, right=0.95, top=0.88)
## Plot TEXT ##
fig.suptitle("STEP_SNAPSHOT Subplot: %s %sDM: %4.4f \
Average:%3d %sPlotAvg:%3d %sFreqAvg:%3d %sBOXCAR:%3d %sBeam: %3d/%3d\n\n\n\n\n"%(filname.ljust(25,' '),
' '.ljust(5,' '), pldm, avg, ' '.ljust(3,' '), plotavg, ' '.ljust(3,' '), freqavg,
' '.ljust(3,' '), plbc, ' '.ljust(3,' '), header['ibeam'], header['nbeams']), color='1')
fig.text(0.15, 0.94, "Source: %s"%header['source_name'], color='1', size=12)
fig.text(0.15, 0.92, "Telscope: %s"%telescope_id, color='1', size=12)
fig.text(0.15, 0.90, "Instrument: %s"%machine_id, color='1', size=12)
fig.text(0.4, 0.94, "RA (J2000): %s"%str(header['src_raj']), color='1', size=12)
fig.text(0.4, 0.92, "DEC (J2000): %s"%str(header['src_dej']), color='1', size=12)
fig.text(0.4, 0.90, "MJD(bary): %s"%str(header['tstart']), color='1', size=12)
fig.text(0.65, 0.94, "N samples: %s"%str(totalsm), color='1', size=12)
fig.text(0.65, 0.92, "Sampling time: %s us"%str(smpt), color='1', size=12)
fig.text(0.65, 0.90, "Freq(ctr): %s MHz"%str(freqctr), color='1', size=12)
## SET STYLE ##
for yl in range(3):
axes[yl, 1].set_yticks([])
for xl in range(2):
if yl == 2 or xl != 1 :
axes[yl, xl].set_facecolor('k')
axes[yl, xl].tick_params(colors='w')
axes[yl, xl].spines['right'].set_color('w')
axes[yl, xl].spines['left'].set_color('w')
axes[yl, xl].spines['top'].set_color('w')
axes[yl, xl].spines['bottom'].set_color('w')
axes[0,1].set_facecolor('k')
axes[1,1].set_facecolor('k')
axes[1,1].tick_params(colors='w')
# axes[0,0].set_xticks(np.arange(100, 901, 100))
# axes[1,0].set_xticks(np.arange(100, 901, 100))
# axes[2,0].set_xticks(np.arange(0, 1001, 100)*plotavg*avg*smpt*1e-6)
# timetick = ['%.2f'%oi for oi in np.arange(0, 1001, 100)*plotavg*avg*smpt*1e-6 + offset]
axes[0,0].set_xticks(np.arange(plotrange/8, plotrange*7/8+1, plotrange/8))
axes[1,0].set_xticks(np.arange(plotrange/8, plotrange*7/8+1, plotrange/8))
axes[2,0].set_xticks(np.arange(0, plotrange+1, plotrange/8)*plotavg*avg*smpt*1e-6)
timetick = ['%.2f'%oi for oi in np.arange(0, plotrange+1, plotrange/8)*plotavg*avg*smpt*1e-6 + offset]
axes[2,0].set_xticklabels(timetick)
## Plot Top Flux ##
axes[0,0].plot(np.arange(0, smaples), (fn2.mean(axis=1)), color='w', linewidth=1)
axes[0,0].set_ylabel("Flux", color='w')
axes[0,0].set_xlim(0, smaples)
axes[0,0].yaxis.get_major_formatter().set_powerlimits((0,1))
fig.text(0.875, 0.86, 'MAX %4.3f'%(maxsigma), color='1')
## Plot Raw data ##
re1 = axes[2,0].imshow(np.transpose(fn), aspect = 'auto', origin = 'lower',
extent = [0, smaples*plotavg*avg*smpt*1e-6, ymin, ymax],
cmap = 'inferno', # viridis, magma, Blues
interpolation='nearest',
vmin=np.sort(fn).reshape(-1)[int(fn.size*(1-plotpes))], vmax= np.max(fn))
axes[2,0].set_ylabel("Frequency (MHz)", color='w')
axes[2,0].set_xlabel("Time (s)", color='w')
axes[2,0].tick_params(colors='w')
## Plot Dedispersion data ##
re2 = axes[1,0].imshow(np.transpose(fn2), aspect = 'auto', origin = 'lower',
extent = [0, smaples, ymin2, ymax2],
cmap = 'inferno', # viridis, magma, Blues, 'plasma'
interpolation='nearest',
vmin=np.sort(fn2).reshape(-1)[int(fn2.size*(1-plotpes))], vmax= np.max(fn2))
axes[1,0].set_ylabel("Frequency (MHz)", color='w')
axes[1,0].tick_params(colors='w')
## Plot Raw Flux ##
plotwinx(axes[2,1], totalch-choff_low-choff_high, fn)
axes[2,1].xaxis.get_major_formatter().set_powerlimits((0,1))
axes[2,1].set_xticks([0, np.max(fn.mean(axis=0))])
# axes[2,1].set_xlabel("Flux", color='w')
## Plot Dedispersion Flux ##
plotwinx(axes[1,1], totalch-choff_low-choff_high, fno2)
axes[1,1].set_xticks([0])
# axes[1,1].set_xlabel("Flux", color='w')
## Save FIG File ##
pdf.savefig(facecolor='k')
# plt.savefig('%s.%d.png'%(filname, header['ibeam']), facecolor='k')
plt.close()
def plotpng(fin1, fin2, smpmax, pngname):
viewdw = 336//2
fn1 = (fin1[int(smpmax//2-viewdw): int(smpmax//2+viewdw)])[:, ::-1]
fn2 = (fin2[int(smpmax//2-viewdw): int(smpmax//2+viewdw)])[:, ::-1]
fn1 = fn1 - fn1.mean(axis = 0)
fn2 = fn2 - fn2.mean(axis = 0)
fig = plt.figure(figsize=(16, 16), dpi=21,frameon=False)
ax = fig.add_axes([0, 0, 1, 1])
print(fn1.shape)
plt.imshow(np.transpose(fn1), aspect = 'auto', origin = 'lower',
cmap = plt.cm.Greys,
interpolation='nearest',) #bilinear
plt.savefig("FRB.%s.raw.png"%pngname)
exit()
plt.imshow(np.transpose(fn2), aspect = 'auto', origin = 'lower',
cmap = plt.cm.Greys,
interpolation='nearest',) #bilinear
plt.savefig("FRB.%s.des.png"%pngname)
plt.close()