if t != tprev:
# New time
l += 1
tprev = t
if l == 600:
break
if len(data.nonzero()[0]) == nf:
out[ibl[i,j],:,l,k] = data[data.nonzero()]
return out, freq
import copy
import spectrogram_fit as sp
from util import Time
trange = Time(['2015-06-21 01:26:00','2015-06-21 01:46:00'])
s = sp.Spectrogram(trange)
s.fidx = [0,213]
tsys, std = s.get_median_data()
out,fghz = readXdata('/data1/IDB/IDB20150621012612')
out2,f = readXdata('/data1/IDB/IDB20150621013612')
out = concatenate((out,out2),2)
pcal = angle(out[:,:,550,:])
acal = abs(out[:,:,550,:])
calout = copy.copy(out)
# Calibrate for time 550, just before the peak of the flare.
for i in range(1200):
calout[:,:,i,:] = calout[:,:,i,:]*(cos(pcal)-1j*sin(pcal))/acal
# Normalize to the total power spectrum at the same time, with reference
# to the shortest baseline (preserves the relative amplitudes on various
def show_selfcalibrated(index, trange, plot='multipanel', antennas=0):
#for index, choose a time when the flare starting, with a large slope.
#the options for plot are 'multipanel' , 'saturation' , and 'uncalibrated'
#antennas controls which pair the saturation plot shows.
data = get_trange_files(trange)
IDBdata, uvw, freq, times = get_X_data(data)
s = sp.Spectrogram(trange)
s.fidx = [0, IDBdata.shape[2]]
tsys, std = s.get_median_data()
pcal = np.angle(IDBdata[:, :, :, index])
acal = abs(IDBdata[:, :, :, index])
calout = copy.copy(IDBdata)
# Calibrate for time 'index', just before the initial peak of the flare.
for i in range(IDBdata.shape[3]):
calout[:, :, :,
i] = calout[:, :, :,
i] * (np.cos(pcal) - 1j * np.sin(pcal)) / acal
# Normalize to the total power spectrum at the same time, with reference
# to the shortest baseline (preserves the relative amplitudes on various
# baselines and polarizations.
norm = abs(calout[:, :, :, index])
for i in range(12):
for j in range(2):
norm[i, j, :] = tsys[:, index] * abs(calout[i, j, :, index]) / abs(
calout[0, 0, :, index])
for i in range(IDBdata.shape[3]):
calout[:, :, :, i] = calout[:, :, :, i] * norm
if plot == 'multipanel':
# Multi-panel Plot
f, ax = plt.subplots(4, 5)
sbl = ['1-2', '1-3', '1-4', '2-3', '2-4', '3-4', '5-7', '5-8', '7-8']
for i, ibl in enumerate([0, 1, 2, 3, 4, 5, 7, 8, 11]):
if (i > 4):
ax[2, i % 5].imshow(abs(calout[ibl, 0, 50:, :]))
ax[2, i % 5].text(100, 10, sbl[i] + ' Amp', color='white')
ax[3, i % 5].imshow(np.angle(calout[ibl, 0, 50:, :]))
ax[3, i % 5].text(100, 10, sbl[i] + ' Phase')
else:
ax[0, i % 5].imshow(abs(calout[ibl, 0, 50:, :]))
ax[0, i % 5].text(100, 10, sbl[i] + ' Amp', color='white')
ax[1, i % 5].imshow(np.angle(calout[ibl, 0, 50:, :]))
ax[1, i % 5].text(100, 10, sbl[i] + ' Phase')
ax[2, 4].imshow(tsys[50:, :])
ax[2, 4].text(100, 10, 'Total Power', color='white')
plt.subplots_adjust(left=0.02,
bottom=0.03,
right=0.99,
top=0.97,
wspace=0.20,
hspace=0.20)
else:
if plot == 'saturation':
# Saturation Plot
ants_ = 'Ants ' + str(antennas + 1) + '-' + str(antennas + 2)
plt.figure()
plt.plot(tsys[IDBdata.shape[2] - 110, :],
abs(calout[antennas, 0, IDBdata.shape[2] - 110, :]),
'.',
label=str(freq[IDBdata.shape[2] - 110])[:5] + ' GHz')
plt.plot(tsys[IDBdata.shape[2] - 60, :],
abs(calout[antennas, 0, IDBdata.shape[2] - 60, :]),
'.',
label=str(freq[IDBdata.shape[2] - 60])[:5] + ' GHz')
plt.plot(tsys[IDBdata.shape[2] - 10, :],
abs(calout[antennas, 0, IDBdata.shape[2] - 10, :]),
'.',
label=str(freq[IDBdata.shape[2] - 10])[:5] + ' GHz')
plt.xlabel('Total Power [sfu]')
plt.ylabel('Correlated Power (' + ants_ + ') [sfu]')
plt.legend(loc='lower right')
else:
if plot == 'uncalibrated':
#"uncalibrated"
f, ax = plt.subplots(4, 5)
sbl = [
'1-2', '1-3', '1-4', '2-3', '2-4', '3-4', '5-7', '5-8',
'7-8'
]
for i, ibl in enumerate([0, 1, 2, 3, 4, 5, 7, 8, 11]):
if (i > 4):
ax[2, i % 5].imshow(abs(IDBdata[ibl, 0, 50:, :]))
ax[2, i % 5].text(100,
10,
sbl[i] + ' Amp',
color='white')
ax[3, i % 5].imshow(np.angle(IDBdata[ibl, 0, 50:, :]))
ax[3, i % 5].text(100, 10, sbl[i] + ' Phase')
else:
ax[0, i % 5].imshow(abs(IDBdata[ibl, 0, 50:, :]))
ax[0, i % 5].text(100,
10,
sbl[i] + ' Amp',
color='white')
ax[1, i % 5].imshow(np.angle(IDBdata[ibl, 0, 50:, :]))
ax[1, i % 5].text(100, 10, sbl[i] + ' Phase')
ax[2, 4].imshow(tsys[50:, :])
ax[2, 4].text(100, 10, 'Total Power', color='white')
plt.subplots_adjust(left=0.02,
bottom=0.03,
right=0.99,
top=0.97,
wspace=0.20,
hspace=0.20)
else:
print 'please choose valid plot type'