def assign_defaults(self):
self.assign_constants()
self.AVOID_HANGUP = False # this is to avoid the hangup of communication with QubicStudio. See acquisition.py
self.logfile = None
self.NPIXELS = NPIXELS
self.assign_obsdate()
#self.assign_datadir() # already called from assign_obsdate() above
self.endobs = None
self.NPIXELS_requested = False # this is a hack to help with the hangup problem
self.NPIXELS_sampled = None
self.detector_name = 'undefined'
self.FLL_state = None
self.FLL_P = None
self.FLL_I = None
self.FLL_D = None
self.Rfeedback = 10e3 # 10kOhm, this is selectable between 10kOhm and 100kOhm (also called "relay" resistance)
self.asic = None
self.assign_integration_time()
self.adu = None
self.vbias = None
self.timeline_vbias = None
self.cycle_vbias = True
self.nbiascycles = None
self.bias_frequency = None
self.bias_period = None
self.max_permitted_bias = 3.0
self.max_bias = None
self.min_bias = None
self.max_bias_position = None
self.bias_factor = 1.0
self.bias_mode = None
self.pausetime = 0.3
self.observer = 'APC LaboMM'
self.nsamples = None
self.chunk_size = None
self.rawmask = None
self.timeline_conversion = None
self.tdata = None
self.pix_grid = assign_pix_grid()
self.filtersummary = []
for idx in range(self.NPIXELS):
self.filtersummary.append(None)
self.assign_lookup_table()
self.temperature = None
self.oxford_assign_temperature_labels()
self.oxford_assign_heater_ranges()
self.calsource_LF = None
self.calsource_HF = None
self.modulator = None
self.datafiletype = None
self.dataset_name = None
self.hornswitch_files = None
self.hk = {}
self.assign_fitsblurbs()
return
from pysimulators import FitsArray
import matplotlib.mlab as mlab
import sys
import scipy.signal as scsig
import scipy.stats
from scipy.ndimage.filters import correlate1d, gaussian_filter1d
import glob
from astropy.io import fits
from qubic.utils import progress_bar
from qubicpack import qubicpack as qp
from qubicpack.pix2tes import assign_pix_grid, assign_pix2tes, tes2pix, pix2tes, TES2PIX
pix_grid = assign_pix_grid()
TES2PIX = assign_pix2tes()
def printnow(truc):
print(truc)
sys.stdout.flush()
def isfloat(s):
try:
a = float(s)
return True
except ValueError:
pass
return False
def plot_fp(args):
'''
plot curves and background colour on the QUBIC focal plane
the argument is a dictionary with the curves and options
valid keywords (n is the ASIC number):
'ASIC<n>' : the array of NPIXELS curves
'ASIC<n> x-axis' : x-axis (use this to plot bias curves)
'ASIC<n> bg' : the value to determine the background colour
'ASIC<n> good' : an array of bool for each TES (good or not)
'obsdate' : observation date (datetime object)
'title' : plot title
'subtitle' : plot subtitle
'lutmin' : min value for colour look up table
'lutmax' : max value for colour look up table
'pngname' : name of file for saving the plot
'nolabels' : if true, do not plot TES labels in each box
'quadrant' : quadrant in which to plot the quarter focal plane (default=3)
'''
# initialize stuff
pix_grid = assign_pix_grid()
nrows = pix_grid.shape[0]
ncols = pix_grid.shape[1]
if 'figsize' in args.keys():
figsize = args['figsize']
else:
figwidth = plt.rcParams['figure.figsize'][0]
figsize = (figwidth, figwidth)
fontsize = figsize[0]
ttlfontsize = figsize[0] * 1.2
quadrant = 3
if 'quadrant' in args.keys():
quadrant = args['quadrant']
obsdate = None
if 'obsdate' in args.keys():
obsdate = args['obsdate']
tes_grid = assign_tes_grid()
if 'pngname' in args.keys():
pngname = args['pngname']
elif obsdate:
pngname = 'QUBIC_focal_plane_%s.png' % obsdate.strftime(
'%Y%m%dT%H%M%S')
else:
pngname = 'QUBIC_focal_plane.png'
if 'title' in args.keys():
ttl = args['title']
else:
ttl = 'QUBIC TES array'
subttl = None
if 'subtitle' in args.keys():
subttl = args['subtitle']
lutmin = 0.0
if 'lutmin' in args.keys():
lutmin = args['lutmin']
lutmax = 10.0
if 'lutmax' in args.keys():
lutmax = args['lutmax']
face_colours = {}
face_colours['ASIC0'] = 'black'
face_colours['ASIC1'] = 'white'
face_colours['ASIC2'] = 'white'
curve_colours = {}
curve_colours['ASIC0'] = 'black'
curve_colours['ASIC1'] = 'black'
curve_colours['ASIC2'] = 'blue'
label_boxprops = dict(boxstyle='round, pad=0.1',
facecolor='white',
alpha=1.0)
label_colours = {}
label_colours['ASIC0'] = 'black'
label_colours['ASIC1'] = 'black'
label_colours['ASIC2'] = 'blue'
if 'nolabels' in args.keys() and args['nolabels']:
print_labels = False
else:
print_labels = True
plt.ion()
fig, ax = plt.subplots(nrows, ncols, figsize=figsize)
fig.text(0.5, 0.985, ttl, ha='center', fontsize=ttlfontsize)
figure_window_title(fig, ttl)
fig.suptitle(subttl, fontsize=ttlfontsize)
for j in range(nrows):
for i in range(ncols):
if quadrant == 1:
row = j
col = i
elif quadrant == 2:
row = i
col = j
elif quadrant == 3:
row = 16 - j
col = 16 - i
else:
row = 16 - i
col = 16 - j
ax[row, col].get_xaxis().set_visible(False)
ax[row, col].get_yaxis().set_visible(False)
# the pixel identity associated with its physical location in the array
TES = tes_grid[j, i].TES
TES_str = '%03i' % TES
asic = tes_grid[j, i].ASIC
asic_str = '%i' % asic
TES_idx = TES - 1
pix_label = TES_str
asic_key = 'ASIC%s' % asic_str
asicbg_key = '%s bg' % asic_key
asicgood_key = '%s good' % asic_key
xaxis_key = '%s x-axis' % asic_key
face_colour = face_colours[asic_key]
label_colour = label_colours[asic_key]
curve_colour = curve_colours[asic_key]
text_x = 0.5
text_y = 0.9
labelfontsize = ttlfontsize
if asic_key in args.keys() and args[asic_key] is not None:
if xaxis_key in args.keys() and args[xaxis_key] is not None:
curve_x = args[xaxis_key][TES_idx]
else:
curve_x = range(args[asic_key].shape[1])
curve = args[asic_key][TES_idx]
text_x = 0.5
text_y = 0.9
labelfontsize = 0.8 * fontsize
if asicgood_key in args.keys(
) and not args[asicgood_key][TES_idx]:
face_colour = 'black'
label_colour = 'white'
curve_colour = 'white'
elif asicbg_key in args.keys():
if args[asicbg_key][TES_idx] is None:
face_colour = 'white'
else:
face_colour = mylut(args[asicbg_key][TES_idx], lutmin,
lutmax)
ax[row, col].plot(curve_x, curve, color=curve_colour)
#print('(%i,%i) : facecolour=%s, labelcolour=%s' % (row,col,face_colour,label_colour))
ax[row, col].set_facecolor(face_colour)
label_boxprops['facecolor'] = face_colour
if print_labels:
ax[row, col].text(text_x,
text_y,
pix_label,
va='top',
ha='center',
color=label_colour,
fontsize=labelfontsize,
bbox=label_boxprops,
transform=ax[row, col].transAxes)
plt.savefig(pngname, format='png', dpi=100, bbox_inches='tight')
plt.show()
return