def detect_change(pipeline, name):
# Get the data from the frames
data = pipeparts.mklalcachesrc(pipeline,
location=options.frame_cache,
cache_dsc_regex=options.ifo)
data = pipeparts.mkframecppchanneldemux(pipeline,
data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(
map("%s:%s".__mod__,
ifo_channel_list)))
streams = []
for chan in channel_list:
stream = calibration_parts.hook_up(pipeline, data, chan, options.ifo,
64.0)
streams.append(stream)
summed_streams = calibration_parts.mkadder(pipeline, streams)
if options.statevector_channel is not None:
state_vector = calibration_parts.hook_up(pipeline, data,
options.statevector_channel,
options.ifo, 64.0)
state_vector = pipeparts.mkgeneric(pipeline,
state_vector,
"lal_logicalundersample",
required_on=1)
summed_streams = calibration_parts.mkgate(pipeline,
summed_streams,
state_vector,
threshold=1.0)
summed_streams = pipeparts.mkgeneric(
pipeline,
summed_streams,
"lal_detectchange",
average_samples=int(options.average_time * options.sample_rate),
detection_threshold=options.detection_threshold,
filename=options.filename)
pipeparts.mkfakesink(pipeline, summed_streams)
#
# done
#
return pipeline
def frame_manipulator(pipeline, name):
#
# This pipeline reads the channels needed for calibration from the raw frames
# and writes them to smaller frames for faster access.
#
head_dict = {}
# Get the data from the raw frames and pick out the channels we want
src = pipeparts.mklalcachesrc(pipeline,
location=frame_cache,
cache_dsc_regex=ifo)
src = pipeparts.mkprogressreport(pipeline, src, "start")
demux = pipeparts.mkframecppchanneldemux(pipeline,
src,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(
map("%s:%s".__mod__,
ifo_channel_list)))
# Make a muxer to collect the channels we need
channelmux_input_dict = {}
for key, chan in zip(channel_list, channel_list):
head_dict[key] = calibration_parts.hook_up(pipeline, demux, chan, ifo,
1.0)
head_dict[key] = pipeparts.mkprogressreport(pipeline, head_dict[key],
"before muxer %s" % key)
channelmux_input_dict["%s:%s" %
(ifo, chan)] = calibration_parts.mkqueue(
pipeline, head_dict[key])
if output_path == 'txt':
for chan in channel_list:
pipeparts.mknxydumpsink(
pipeline, channelmux_input_dict["%s:%s" % (ifo, chan)],
"%s-%s.txt" % (ifo, chan))
else:
mux = pipeparts.mkframecppchannelmux(pipeline,
channelmux_input_dict,
frame_duration=frame_length,
frames_per_file=frames_per_file,
compression_scheme=6,
compression_level=3)
mux = pipeparts.mkprogressreport(pipeline, mux, "end")
pipeparts.mkframecppfilesink(pipeline,
mux,
frame_type=frame_type,
path=output_path,
instrument=ifo)
#
# done
#
return pipeline
def compute_RMS_timeseries(pipeline, name):
# Get the data from the frames
for i in range(len(channel_list)):
data = pipeparts.mklalcachesrc(pipeline, location = frame_cache_list[i], cache_dsc_regex = ifo)
data = pipeparts.mkframecppchanneldemux(pipeline, data, do_file_checksum = False, skip_bad_files = True, channel_list = list(map("%s:%s".__mod__, channel_list)))
data = calibration_parts.hook_up(pipeline, data, channel_list[i][1], ifo, 1.0)
data = calibration_parts.caps_and_progress(pipeline, data, "audio/x-raw,format=F64LE", labels[i])
RMS = calibration_parts.compute_rms(pipeline, data, rates[i], average_time, filter_length = 10.0, f_min = fmin, f_max = fmax, rate_out = 1)
pipeparts.mknxydumpsink(pipeline, RMS, "%s_RMS_%s_%d-%d.txt" % (ifo, labels[i].replace(' ', '_'), gps_start_time, data_duration))
#
# done
#
return pipeline
def pcal2darm(pipeline, name):
# Get pcal from the raw frames
raw_data = pipeparts.mklalcachesrc(pipeline,
location=options.raw_frame_cache,
cache_dsc_regex=ifo)
raw_data = pipeparts.mkframecppchanneldemux(
pipeline,
raw_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
pcal = calibration_parts.hook_up(pipeline, raw_data,
options.pcal_channel_name, ifo, 1.0)
pcal = calibration_parts.caps_and_progress(
pipeline, pcal,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
"pcal")
pcal = pipeparts.mktee(pipeline, pcal)
# Demodulate the pcal channel at the lines of interest
for i in range(0, len(frequencies)):
demodulated_pcal = calibration_parts.demodulate(
pipeline,
pcal,
frequencies[i],
True,
rate_out,
filter_time,
0.5,
prefactor_real=pcal_corrections[2 * i],
prefactor_imag=pcal_corrections[2 * i + 1])
demodulated_pcal_list.append(
pipeparts.mktee(pipeline, demodulated_pcal))
# Check if we are taking pcal-to-darm ratios for CALCS data
for channel, label in zip(calcs_channels, labels[0:len(calcs_channels)]):
calcs_deltal = calibration_parts.hook_up(pipeline, raw_data, channel,
ifo, 1.0)
calcs_deltal = calibration_parts.caps_and_progress(
pipeline, calcs_deltal,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
calcs_deltal = pipeparts.mktee(pipeline, calcs_deltal)
for i in range(0, len(frequencies)):
# Demodulate DELTAL_EXTERNAL at each line
demodulated_calcs_deltal = calibration_parts.demodulate(
pipeline, calcs_deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Take ratio \DeltaL(f) / pcal(f)
deltaL_over_pcal = calibration_parts.complex_division(
pipeline, demodulated_calcs_deltaL, demodulated_pcal_list[i])
# Take a running average
deltaL_over_pcal = pipeparts.mkgeneric(
pipeline,
deltaL_over_pcal,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out * average_time))
# Write to file
pipeparts.mknxydumpsink(
pipeline, deltaL_over_pcal,
"%s_%s_over_%s_at_line%d.txt" % (ifo, label.replace(
' ', '_'), options.pcal_channel_name, i + 1))
# Check if we are taking pcal-to-darm ratios for gstlal calibrated data
if options.gstlal_channel_list is not None:
cache_num = 0
for cache, channel, label in zip(
gstlal_frame_cache_list, gstlal_channels,
labels[len(calcs_channels):len(calcs_channels) +
len(gstlal_channels)]):
# Get gstlal channels from the gstlal frames
hoft_data = pipeparts.mklalcachesrc(pipeline,
location=cache,
cache_dsc_regex=ifo)
hoft_data = pipeparts.mkframecppchanneldemux(
pipeline,
hoft_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
hoft = calibration_parts.hook_up(pipeline,
hoft_data,
channel,
ifo,
1.0,
element_name_suffix="_%d" %
cache_num)
cache_num = cache_num + 1
hoft = calibration_parts.caps_and_progress(
pipeline, hoft,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
deltal = pipeparts.mkaudioamplify(pipeline, hoft, arm_length)
deltal = pipeparts.mktee(pipeline, deltal)
for i in range(0, len(frequencies)):
# Demodulate \DeltaL at each line
demodulated_deltal = calibration_parts.demodulate(
pipeline, deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Take ratio \DeltaL(f) / pcal(f)
deltaL_over_pcal = calibration_parts.complex_division(
pipeline, demodulated_deltal, demodulated_pcal_list[i])
# Take a running average
deltaL_over_pcal = pipeparts.mkgeneric(
pipeline,
deltaL_over_pcal,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out * average_time))
# Find the magnitude
deltaL_over_pcal = pipeparts.mktee(pipeline, deltaL_over_pcal)
magnitude = pipeparts.mkgeneric(pipeline, deltaL_over_pcal,
"cabs")
# Find the phase
phase = pipeparts.mkgeneric(pipeline, deltaL_over_pcal, "carg")
phase = pipeparts.mkaudioamplify(pipeline, phase,
180.0 / numpy.pi)
# Interleave
magnitude_and_phase = calibration_parts.mkinterleave(
pipeline, [magnitude, phase])
# Write to file
pipeparts.mknxydumpsink(
pipeline, magnitude_and_phase,
"%s_%s_over_%s_at_%0.1fHz_%d.txt" %
(ifo, label.replace(' ', '_'), options.pcal_channel_name,
frequencies[i], options.gps_start_time))
# Check of we are reading in kappa channels
if options.kappa_channel_list is not None:
# Get gstlal channels from the gstlal frames
kappa_data = pipeparts.mklalcachesrc(
pipeline,
location=gstlal_frame_cache_list[0],
cache_dsc_regex=ifo)
kappa_data = pipeparts.mkframecppchanneldemux(
pipeline,
kappa_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
for i in range(len(kappa_channels) // 2):
kappa_real = calibration_parts.hook_up(
pipeline,
kappa_data,
kappa_channels[2 * i],
ifo,
1.0,
element_name_suffix="_%d" % (2 * i))
kappa_imag = calibration_parts.hook_up(
pipeline,
kappa_data,
kappa_channels[2 * i + 1],
ifo,
1.0,
element_name_suffix="_%d" % (2 * i + 1))
kappa_real = calibration_parts.caps_and_progress(
pipeline, kappa_real,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
kappa_channels[2 * i])
kappa_imag = calibration_parts.caps_and_progress(
pipeline, kappa_imag,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
kappa_channels[2 * i + 1])
kappa = calibration_parts.merge_into_complex(
pipeline, kappa_real, kappa_imag)
phase_angle = pipeparts.mkgeneric(pipeline, kappa, "carg")
actuation_stage = 'UNKNOWN'
act_freq = 17.0 # A guess...
if 'TST' in kappa_channels[2 * i]:
actuation_stage = 'T'
act_freq = float(filters["ktst_esd_line_freq"])
elif 'PUM' in kappa_channels[2 * i]:
actuation_stage = 'P'
act_freq = float(filters["pum_act_line_freq"])
elif 'UIM' in kappa_channels[2 * i]:
actuation_stage = 'U'
act_freq = float(filters["uim_act_line_freq"])
elif 'PU' in kappa_channels[2 * i]:
actuation_stage = 'PU'
act_freq = float(filters["ka_esd_line_freq"])
actuation_stages.append(actuation_stage)
tau = pipeparts.mkaudioamplify(
pipeline, phase_angle,
1000000.0 / 2.0 / numpy.pi / act_freq)
pipeparts.mknxydumpsink(
pipeline, tau, "%s_%s_%d.txt" %
(ifo, actuation_stage, options.gps_start_time))
#
# done
#
return pipeline
def plot_transfer_function(pipeline, name):
# Get the data from the denominator frames
denominator = pipeparts.mklalcachesrc(
pipeline,
location=options.denominator_frame_cache,
cache_dsc_regex=ifo)
denominator = pipeparts.mkframecppchanneldemux(
pipeline,
denominator,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
denominator = calibration_parts.hook_up(pipeline, denominator,
options.denominator_channel_name,
ifo, 1.0)
denominator = calibration_parts.caps_and_progress(
pipeline, denominator, "audio/x-raw,format=F64LE", "denominator")
denominator = calibration_parts.mkresample(pipeline, denominator, 5, False,
int(sample_rate))
if denominator_correction is not None:
if numpy.size(filters[denominator_correction]) == 1:
denominator = pipeparts.mkaudioamplify(
pipeline, denominator, float(filters[denominator_correction]))
denominator = pipeparts.mktee(pipeline, denominator)
# Get the data from the numerator frames
for i in range(0, len(labels)):
numerator = pipeparts.mklalcachesrc(
pipeline,
location=numerator_frame_cache_list[i],
cache_dsc_regex=ifo)
numerator = pipeparts.mkframecppchanneldemux(
pipeline,
numerator,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
numerator = calibration_parts.hook_up(pipeline,
numerator,
numerator_channel_list[i],
ifo,
1.0,
element_name_suffix="%d" % i)
numerator = calibration_parts.caps_and_progress(
pipeline, numerator, "audio/x-raw,format=F64LE", labels[i])
numerator = calibration_parts.mkresample(pipeline, numerator, 5, False,
int(sample_rate))
if numerator_correction is not None:
if numerator_correction[i] is not None:
if numpy.size(filters[numerator_correction[i]] == 1):
numerator = pipeparts.mkaudioamplify(
pipeline, numerator,
float(filters[numerator_correction[i]]))
# Interleave the channels to make one stream
channels = calibration_parts.mkinterleave(pipeline,
[numerator, denominator])
# Send the data to lal_transferfunction to compute and write transfer functions
pipeparts.mkgeneric(pipeline,
channels,
"lal_transferfunction",
fft_length=fft_length,
fft_overlap=fft_overlap,
num_ffts=num_ffts,
fir_length=td_tf_length,
use_median=True if options.use_median else False,
update_samples=1e15,
filename='%s_%s_over_%s_%d-%d.txt' %
(ifo, labels[i].replace(' ', '_').replace(
'/', 'over'), options.denominator_channel_name,
options.gps_start_time, data_duration))
#
# done
#
return pipeline
def gstlal_compute_kappas_without_D(pipeline, name):
# The first line makes the element lal_cachesrc, which reads in raw data using the cache file
source = pipeparts.mklalcachesrc(pipeline,
location=frame_cache,
cache_dsc_regex=ifo)
# Next, the demuxer splits it into separate channels
demux = pipeparts.mkframecppchanneldemux(pipeline,
source,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(
map("%s:%s".__mod__,
channel_list)))
# Next, we use a function from calibration_parts.py that hooks up to the demuxer
# and does a few sanity checks on the data. This uses multiple elements.
darm_err = calibration_parts.hook_up(pipeline, demux,
"CAL-DARM_ERR_DBL_DQ", ifo, 1.0)
# Another calibration_parts function to set the "caps", which are stream parameters
# that tell gstreamer the data type, sample rate, etc. A progress report will produce
# output to the screen so that you can see it is running.
darm_err = calibration_parts.caps_and_progress(
pipeline, darm_err,
"audio/x-raw, format=F64LE, rate=%d, channels=1, channel-mask=(bitmask)0x0",
"darm_err")
# You will need to use the error signal in more than one place (you'll have to
# demodulate it at all five frequencies), so we need a tee here.
darm_err = pipeparts.mktee(pipeline, darm_err)
# Finally, an interesting operation - now you need to demodulate the error signal.
# You will have to do this to every input signal. darm_err is currently a time series,
# but you want to know its amplitude and phase at a single frequency. To do this, we
# Demodulate it at the specified frequency
darm_err_at_f1 = calibration_parts.demodulate(pipeline, darm_err, f1, True,
16, 20, 0)
# You'll also need this in multiple places, so here's a tee
darm_err_at_f1 = pipeparts.mktee(pipeline, darm_err_at_f1)
# This writes the data to a file, currently called "darm_err_at_f1.txt." Eventually,
# you will want to write the TDCFs to a file.
pipeparts.mknxydumpsink(pipeline, darm_err_at_f1, "darm_err_at_f1.txt")
# To move forward, you can remove the nxydumpsink above and use darm_err_at_f1 for
# your calculations. You will also need to demodulate the Pcal channel at f1. And
# you will have to do several more demodulations (10 total I think, since each of
# the five lines is present in darm_err and in one injection channel). Then, you
# will need to do additions, multiplications, divisions, powers, etc. I would
# suggest looking in gstlal_compute_strain (the calibration pipeline) and
# calibration_parts.py for examples of how to do these. calibration_parts has lots
# of functions that should be helpful.
#
# done
#
return pipeline
def demod_ratio(pipeline, name):
# Get denominator data from the raw frames
denominator_data = pipeparts.mklalcachesrc(
pipeline,
location=options.denominator_frame_cache,
cache_dsc_regex=ifo)
denominator_data = pipeparts.mkframecppchanneldemux(
pipeline,
denominator_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
denominator = calibration_parts.hook_up(pipeline, denominator_data,
options.denominator_channel_name,
ifo, 1.0)
denominator = calibration_parts.caps_and_progress(
pipeline, denominator,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
"denominator")
denominator = pipeparts.mktee(pipeline, denominator)
# Get numerator data from the raw frames
if not options.denominator_frame_cache == options.numerator_frame_cache:
numerator_data = pipeparts.mklalcachesrc(
pipeline,
location=options.numerator_frame_cache,
cache_dsc_regex=ifo)
numerator_data = pipeparts.mkframecppchanneldemux(
pipeline,
numerator_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
numerator = calibration_parts.hook_up(pipeline, numerator_data,
options.numerator_channel_name,
ifo, 1.0)
else:
numerator = calibration_parts.hook_up(pipeline, denominator_data,
options.numerator_channel_name,
ifo, 1.0)
numerator = calibration_parts.caps_and_progress(
pipeline, numerator,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
"numerator")
numerator = pipeparts.mktee(pipeline, numerator)
# Demodulate numerator and denominator at each frequency, take ratios, and write to file
for i in range(0, len(frequencies)):
# Demodulate
demodulated_denominator = calibration_parts.demodulate(
pipeline, denominator, frequencies[i], True, rate_out, filter_time,
0.5)
demodulated_numerator = calibration_parts.demodulate(
pipeline, numerator, frequencies[i], True, rate_out, filter_time,
0.5)
demodulated_numerator = pipeparts.mktee(pipeline,
demodulated_numerator)
demodulated_denominator = pipeparts.mktee(pipeline,
demodulated_denominator)
# Take ratio
ratio = calibration_parts.complex_division(pipeline,
demodulated_numerator,
demodulated_denominator)
# Average
ratio = pipeparts.mkgeneric(pipeline,
ratio,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out *
average_time),
filter_latency=1.0)
# Find magnitude and phase
ratio = pipeparts.mktee(pipeline, ratio)
magnitude = pipeparts.mkgeneric(pipeline, ratio, "cabs")
phase = pipeparts.mkgeneric(pipeline, ratio, "carg")
phase = pipeparts.mkaudioamplify(pipeline, phase, 180.0 / numpy.pi)
# Interleave
magnitude_and_phase = calibration_parts.mkinterleave(
pipeline, [magnitude, phase])
# Write to file
pipeparts.mknxydumpsink(
pipeline, magnitude_and_phase, "%s_%s_over_%s_%0.1fHz.txt" %
(ifo, options.numerator_channel_name,
options.denominator_channel_name, frequencies[i]))
#
# done
#
return pipeline
def pcal2darm(pipeline, name):
# Get pcal from the raw frames
raw_data = pipeparts.mklalcachesrc(pipeline,
location=options.raw_frame_cache,
cache_dsc_regex=ifo)
raw_data = pipeparts.mkframecppchanneldemux(
pipeline,
raw_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
pcal = calibration_parts.hook_up(pipeline, raw_data,
options.pcal_channel_name, ifo, 1.0)
pcal = calibration_parts.caps_and_progress(
pipeline, pcal,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
"pcal")
pcal = pipeparts.mktee(pipeline, pcal)
# Demodulate the pcal channel at the lines of interest
for i in range(0, len(frequencies)):
demodulated_pcal = calibration_parts.demodulate(
pipeline,
pcal,
frequencies[i],
True,
rate_out,
filter_time,
0.5,
prefactor_real=pcal_corrections[2 * i],
prefactor_imag=pcal_corrections[2 * i + 1])
demodulated_pcal_list.append(
pipeparts.mktee(pipeline, demodulated_pcal))
# Check if we are taking pcal-to-darm ratios for CALCS data
for channel, label in zip(calcs_channels, labels[0:len(calcs_channels)]):
calcs_deltal = calibration_parts.hook_up(pipeline, raw_data, channel,
ifo, 1.0)
calcs_deltal = calibration_parts.caps_and_progress(
pipeline, calcs_deltal,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
calcs_deltal = pipeparts.mktee(pipeline, calcs_deltal)
for i in range(0, len(frequencies)):
# Demodulate DELTAL_EXTERNAL at each line
demodulated_calcs_deltal = calibration_parts.demodulate(
pipeline, calcs_deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Take ratio \DeltaL(f) / pcal(f)
deltaL_over_pcal = calibration_parts.complex_division(
pipeline, demodulated_calcs_deltaL, demodulated_pcal_list[i])
# Take a running average
deltaL_over_pcal = pipeparts.mkgeneric(
pipeline,
deltaL_over_pcal,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out * average_time))
# Write to file
pipeparts.mknxydumpsink(
pipeline, deltaL_over_pcal,
"%s_%s_over_%s_at_line%d.txt" % (ifo, label.replace(
' ', '_'), options.pcal_channel_name, i + 1))
# Check if we are taking pcal-to-darm ratios for gstlal calibrated data
if options.gstlal_channel_list is not None:
cache_num = 0
for cache, channel, label in zip(
gstlal_frame_cache_list, gstlal_channels,
labels[len(calcs_channels):len(channel_list)]):
# Get gstlal channels from the gstlal frames
hoft_data = pipeparts.mklalcachesrc(pipeline,
location=cache,
cache_dsc_regex=ifo)
hoft_data = pipeparts.mkframecppchanneldemux(
pipeline,
hoft_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(
map("%s:%s".__mod__, channel_list + DQ_channels)))
hoft = calibration_parts.hook_up(pipeline,
hoft_data,
channel,
ifo,
1.0,
element_name_suffix="_%d" %
cache_num)
hoft = calibration_parts.caps_and_progress(
pipeline, hoft,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
deltal = pipeparts.mkaudioamplify(pipeline, hoft, arm_length)
deltal = pipeparts.mktee(pipeline, deltal)
# Get a DQ channel
DQ_channel = "%sCALIB_STATE_VECTOR%s" % (chan_prefixes[cache_num],
chan_suffixes[cache_num])
DQ = calibration_parts.hook_up(pipeline,
hoft_data,
DQ_channel,
ifo,
1.0,
element_name_suffix="_%d" %
cache_num)
DQ = calibration_parts.caps_and_progress(
pipeline, DQ,
"audio/x-raw,format=U32LE,channels=1,channel-mask=(bitmask)0x0",
"DQ_%s" % label)
DQ = pipeparts.mkgeneric(pipeline,
DQ,
"lal_logicalundersample",
required_on=1,
status_out=1)
DQ = pipeparts.mkcapsfilter(
pipeline, DQ,
"audio/x-raw,format=U32LE,rate=%d,channels=1,channel-mask=(bitmask)0x0"
% rate_out)
DQ = pipeparts.mkgeneric(
pipeline,
DQ,
"lal_drop",
drop_samples=int((7.0 + 0.5 * filter_time) * rate_out + 0.5))
DQ = pipeparts.mktee(pipeline, DQ)
for i in range(0, len(frequencies)):
# Demodulate \DeltaL at each line
demodulated_deltal = calibration_parts.demodulate(
pipeline, deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Take ratio \DeltaL(f) / pcal(f)
deltaL_over_pcal = calibration_parts.complex_division(
pipeline, demodulated_deltal, demodulated_pcal_list[i])
# Take a running average
deltaL_over_pcal = pipeparts.mkgeneric(
pipeline,
deltaL_over_pcal,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out * average_time))
# Find the magnitude
deltaL_over_pcal = pipeparts.mktee(pipeline, deltaL_over_pcal)
magnitude = pipeparts.mkgeneric(pipeline, deltaL_over_pcal,
"cabs")
# Find the phase
phase = pipeparts.mkgeneric(pipeline, deltaL_over_pcal, "carg")
phase = pipeparts.mkaudioamplify(pipeline, phase,
180.0 / numpy.pi)
# Interleave
magnitude_and_phase = calibration_parts.mkinterleave(
pipeline, [magnitude, phase])
# Gate with DQ channel
magnitude_and_phase = calibration_parts.mkgate(
pipeline, magnitude_and_phase, DQ, 1)
magnitude_and_phase = pipeparts.mkprogressreport(
pipeline,
magnitude_and_phase,
name="progress_sink_%s_%d" % (label, i))
# Write to file
pipeparts.mknxydumpsink(
pipeline, magnitude_and_phase,
"%s_%s_over_%s_at_%0.1fHz_%d.txt" %
(ifo, label.replace(' ', '_'), options.pcal_channel_name,
frequencies[i], options.gps_start_time))
cache_num = cache_num + 1
#
# done
#
return pipeline
def act2darm(pipeline, name):
# Get actuation injection channels from the raw frames
act_inj_channels = []
raw_data = pipeparts.mklalcachesrc(pipeline,
location=options.raw_frame_cache,
cache_dsc_regex=ifo)
raw_data = pipeparts.mkframecppchanneldemux(
pipeline,
raw_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(map("%s:%s".__mod__, channel_list)))
for i in range(len(act_channels)):
act_inj_channels.append(
calibration_parts.hook_up(pipeline, raw_data, act_channels[i], ifo,
1.0))
act_inj_channels[i] = calibration_parts.caps_and_progress(
pipeline, act_inj_channels[i],
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
"act_inj_%d" % i)
act_inj_channels[i] = pipeparts.mktee(pipeline, act_inj_channels[i])
# Demodulate the actuation injection channels at the lines of interest
for i in range(0, len(frequencies)):
demodulated_act = calibration_parts.demodulate(
pipeline,
act_inj_channels[i],
frequencies[i],
True,
rate_out,
filter_time,
0.5,
prefactor_real=act_corrections[2 * i],
prefactor_imag=act_corrections[2 * i + 1])
demodulated_act_list.append(pipeparts.mktee(pipeline, demodulated_act))
# Check if we are taking act-to-darm ratios for CALCS data
for channel, label in zip(calcs_channels, labels[0:len(calcs_channels)]):
calcs_deltal = calibration_parts.hook_up(pipeline, raw_data, channel,
ifo, 1.0)
calcs_deltal = calibration_parts.caps_and_progress(
pipeline, calcs_deltal,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
calcs_deltal = pipeparts.mktee(pipeline, calcs_deltal)
for i in range(0, len(frequencies)):
# Demodulate DELTAL_EXTERNAL at each line
demodulated_calcs_deltal = calibration_parts.demodulate(
pipeline, calcs_deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Take ratio \DeltaL(f) / act_injection(f)
deltaL_over_act = calibration_parts.complex_division(
pipeline, demodulated_calcs_deltaL, demodulated_act_list[i])
# Take a running average
deltaL_over_act = pipeparts.mkgeneric(pipeline,
deltaL_over_act,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(
rate_out * average_time))
# Write to file
pipeparts.mknxydumpsink(
pipeline, deltaL_over_act, "%s_%s_over_%s_at_line%d.txt" %
(ifo, label.replace(' ', '_'), act_channels[i], i + 1))
# Check if we are taking act-to-darm ratios for gstlal calibrated data
if options.gstlal_channel_list is not None:
cache_num = 0
for cache, channel, label in zip(
gstlal_frame_cache_list, gstlal_channels,
labels[len(calcs_channels):len(channel_list)]):
# Get gstlal channels from the gstlal frames
hoft_data = pipeparts.mklalcachesrc(pipeline,
location=cache,
cache_dsc_regex=ifo)
hoft_data = pipeparts.mkframecppchanneldemux(
pipeline,
hoft_data,
do_file_checksum=False,
skip_bad_files=True,
channel_list=list(
map("%s:%s".__mod__, channel_list +
TDCF_channels[cache_num] + DQ_channels)))
hoft = calibration_parts.hook_up(pipeline,
hoft_data,
channel,
ifo,
1.0,
element_name_suffix="_%d" %
cache_num)
hoft = calibration_parts.caps_and_progress(
pipeline, hoft,
"audio/x-raw,format=F64LE,channels=1,channel-mask=(bitmask)0x0",
label)
deltal = pipeparts.mkaudioamplify(pipeline, hoft, arm_length)
deltal = pipeparts.mktee(pipeline, deltal)
# Get a DQ channel
DQ_channel = "%sCALIB_STATE_VECTOR%s" % (chan_prefixes[cache_num],
chan_suffixes[cache_num])
DQ = calibration_parts.hook_up(pipeline,
hoft_data,
DQ_channel,
ifo,
1.0,
element_name_suffix="_%d" %
cache_num)
DQ = calibration_parts.caps_and_progress(
pipeline, DQ,
"audio/x-raw,format=U32LE,channels=1,channel-mask=(bitmask)0x0",
"DQ_%s" % label)
DQ = pipeparts.mkgeneric(pipeline,
DQ,
"lal_logicalundersample",
required_on=1,
status_out=1)
DQ = pipeparts.mkcapsfilter(
pipeline, DQ,
"audio/x-raw,format=U32LE,rate=%d,channels=1,channel-mask=(bitmask)0x0"
% rate_out)
DQ = pipeparts.mktee(pipeline, DQ)
for i in range(0, len(frequencies)):
# Demodulate \DeltaL at each line
demodulated_deltal = calibration_parts.demodulate(
pipeline, deltal, frequencies[i], True, rate_out,
filter_time, 0.5)
# Divide by a TDCF if needed
if ('tst' in act_line_names[i] or 'esd' in act_line_names[i]
) and (apply_complex_kappatst[cache_num]
or apply_kappatst[cache_num]):
# Get KAPPA_TST
TDCF_real = "%sCALIB_KAPPA_TST_REAL%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_imag = "%sCALIB_KAPPA_TST_IMAGINARY%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_real = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_real,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF_imag = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_imag,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF = calibration_parts.merge_into_complex(
pipeline, TDCF_real, TDCF_imag)
TDCF = calibration_parts.caps_and_progress(
pipeline, TDCF,
"audio/x-raw,format=Z128LE,channels=1,channel-mask=(bitmask)0x0",
'KAPPA_TST_%s' % label)
TDCF = calibration_parts.mkresample(
pipeline, TDCF, 3, False, rate_out)
if not apply_complex_kappatst[cache_num]:
# Only divide by the magnitude
TDCF = pipeparts.mkgeneric(pipeline, TDCF, "cabs")
TDCF = pipeparts.mktogglecomplex(
pipeline,
pipeparts.mkmatrixmixer(pipeline,
TDCF,
matrix=[[1.0, 0.0]]))
demodulated_deltal = calibration_parts.complex_division(
pipeline, demodulated_deltal, TDCF)
elif 'pum' in act_line_names[i] and (
apply_complex_kappapum[cache_num]
or apply_kappapum[cache_num]):
# Get KAPPA_PUM
TDCF_real = "%sCALIB_KAPPA_PUM_REAL%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_imag = "%sCALIB_KAPPA_PUM_IMAGINARY%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_real = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_real,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF_imag = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_imag,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF = calibration_parts.merge_into_complex(
pipeline, TDCF_real, TDCF_imag)
TDCF = calibration_parts.caps_and_progress(
pipeline, TDCF,
"audio/x-raw,format=Z128LE,channels=1,channel-mask=(bitmask)0x0",
'KAPPA_PUM_%s' % label)
TDCF = calibration_parts.mkresample(
pipeline, TDCF, 3, False, rate_out)
if not apply_complex_kappapum[cache_num]:
# Only divide by the magnitude
TDCF = pipeparts.mkgeneric(pipeline, TDCF, "cabs")
TDCF = pipeparts.mktogglecomplex(
pipeline,
pipeparts.mkmatrixmixer(pipeline,
TDCF,
matrix=[[1.0, 0.0]]))
demodulated_deltal = calibration_parts.complex_division(
pipeline, demodulated_deltal, TDCF)
elif 'uim' in act_line_names[i] and (
apply_complex_kappauim[cache_num]
or apply_kappauim[cache_num]):
# Get KAPPA_UIM
TDCF_real = "%sCALIB_KAPPA_UIM_REAL%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_imag = "%sCALIB_KAPPA_UIM_IMAGINARY%s" % (
chan_prefixes[cache_num], chan_suffixes[cache_num])
TDCF_real = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_real,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF_imag = calibration_parts.hook_up(
pipeline,
hoft_data,
TDCF_imag,
ifo,
1.0,
element_name_suffix="_%d" % cache_num)
TDCF = calibration_parts.merge_into_complex(
pipeline, TDCF_real, TDCF_imag)
TDCF = calibration_parts.caps_and_progress(
pipeline, TDCF,
"audio/x-raw,format=Z128LE,channels=1,channel-mask=(bitmask)0x0",
'KAPPA_UIM_%s' % label)
TDCF = calibration_parts.mkresample(
pipeline, TDCF, 3, False, rate_out)
if not apply_complex_kappauim[cache_num]:
# Only divide by the magnitude
TDCF = pipeparts.mkgeneric(pipeline, TDCF, "cabs")
TDCF = pipeparts.mktogglecomplex(
pipeline,
pipeparts.mkmatrixmixer(pipeline,
TDCF,
matrix=[[1.0, 0.0]]))
demodulated_deltal = calibration_parts.complex_division(
pipeline, demodulated_deltal, TDCF)
# Take ratio \DeltaL(f) / act_injection(f)
deltaL_over_act = calibration_parts.complex_division(
pipeline, demodulated_deltal, demodulated_act_list[i])
# Take a running average
deltaL_over_act = pipeparts.mkgeneric(
pipeline,
deltaL_over_act,
"lal_smoothkappas",
array_size=1,
avg_array_size=int(rate_out * average_time))
# Find the magnitude
deltaL_over_act = pipeparts.mktee(pipeline, deltaL_over_act)
magnitude = pipeparts.mkgeneric(pipeline, deltaL_over_act,
"cabs")
# Find the phase
phase = pipeparts.mkgeneric(pipeline, deltaL_over_act, "carg")
phase = pipeparts.mkaudioamplify(pipeline, phase,
180.0 / numpy.pi)
# Interleave
magnitude_and_phase = calibration_parts.mkinterleave(
pipeline, [magnitude, phase])
# Gate with DQ channel
magnitude_and_phase = calibration_parts.mkgate(
pipeline, magnitude_and_phase, DQ, 1)
magnitude_and_phase = pipeparts.mkprogressreport(
pipeline,
magnitude_and_phase,
name="progress_sink_%s_%d" % (label, i))
# Write to file
pipeparts.mknxydumpsink(
pipeline, magnitude_and_phase,
"%s_%s_over_%s_at_%0.1fHz_%d.txt" %
(ifo, label.replace(' ', '_'), act_channels[i],
frequencies[i], options.gps_start_time))
cache_num = cache_num + 1
#
# done
#
return pipeline