def create_plot(testpath, always_make=False):
filename = testpath / THUMBNAIL_FILE_NAME
if (not always_make) and filename.exists():
log.debug(
'File "%s" already exist for test "%s", so no need to re-create it',
THUMBNAIL_FILE_NAME,
str(testpath),
)
return filename
try:
a = qubicfp()
a.read_qubicstudio_dataset(str(testpath))
a.quicklook(xwin=False, filename=filename)
except:
log.error('Unable to create plot for test "%s"', str(testpath))
# Do not bother complaining too much, just keep things going
return None
try:
# Optimize the size of the PNG file
temp_name = next(tempfile._get_candidate_names())
full_temp_name = str(default_tmp_dir / temp_name)
subprocess.run(
["pngquant", "-f", "--output", full_temp_name, "32", filename])
subprocess.run(["optipng", full_temp_name])
subprocess.run(["mv", "-f", full_temp_name, filename])
log.debug('Plot for test in "%s" has been compressed successfully',
str(testpath))
except CalledProcessError:
log.warn('Unable to compress "%s", leaving it uncompressed', filename)
pass # Ignore the error, we'll live with an uncompressed plot!
return filename
def get_data(dirs, nf, asic, tes=28, doplot=True):
asic = str(asic)
thedir = dirs[nf]
# Qubicpack object
a = qubicfp()
a.verbosity = 0
a.read_qubicstudio_dataset(thedir)
data = a.azel_etc(TES=None)
# Signal for one TES
t0 = data['t_data ' + asic][0]
t_data = data['t_data ' + asic] - t0
data = data['data ' + asic]
if doplot:
fig, axs = plt.subplots(1, 2, figsize=(15, 3))
plt.subplots_adjust(wspace=0.5)
axs[0].plot(t_data, data[tes - 1, :])
axs[0].set_title(thedir[-5:])
axs[1].plot(t_data, data[tes - 1, :])
axs[1].set_title(thedir[-5:])
axs[1].set_xlim(0, 40)
return thedir, t_data, data
# import necessary stuff
import os,sys
jupyter=False
if sys.argv[0].find('ipykernel')>=0:jupyter=True
# make plots within the notebook if using jupyter notebook
if jupyter:
%matplotlib notebook
import matplotlib.pyplot as plt
from qubicpack.qubicfp import qubicfp
from qubicpack.temperature_analysis import *
# create the qubicpack focal plane object and read the data
d0=qubicfp()
if jupyter: d0.figsize=9,5
# the first data file contains measurements at high temperature
# these are used to correct the Normal Resistance
d0.read_qubicstudio_dataset(dataset_dir)
# The data contains multiple timelines at different temperatures
# you can print out a summary table
print_datlist(d0)
# first of all, have a look at all timelines for all the TES
d0.plot_timeline_focalplane()
# now look at one in particular.
ASIC = 1
TES = 85
#!/usr/bin/env python3
'''
$Id: quicklook.py<scripts>
$auth: Steve Torchinsky <*****@*****.**>
$created: Mon 23 Dec 2019 08:59:23 CET
$license: GPLv3 or later, see https://www.gnu.org/licenses/gpl-3.0.txt
This is free software: you are free to change and
redistribute it. There is NO WARRANTY, to the extent
permitted by law.
find the latest data and make a quicklook plot
'''
from glob import glob
from qubicpack.qubicfp import qubicfp
qubicfp.verbosity = 1
datadir = '/qs2'
datasets = glob('%s/20??-??-??/*' % datadir)
datasets.sort()
latest_dset = datasets[-1]
a = qubicfp()
a.read_qubicstudio_dataset(latest_dset)
a.quicklook()
prmpt = 'Press return to exit. '
ans = input(prmpt)