def line_separation_test_01(pipeline, name, line_sep=0.5):
#
# This test measures and plots the amount of contamination a calibration line adds to the result of demodulating at a nearby frequency as a function of frequency separation.
#
rate = 1000 # Hz
buffer_length = 1.0 # seconds
test_duration = 10.0 # seconds
#
# build pipeline
#
noise = test_common.test_src(pipeline,
rate=16384,
test_duration=1000,
wave=5,
src_suffix='0')
noise = pipeparts.mkaudioamplify(pipeline, noise, 2.5)
noise = pipeparts.mktee(pipeline, noise)
signal = test_common.test_src(pipeline,
rate=16384,
test_duration=1000,
wave=0,
freq=16.3 + line_sep,
src_suffix='1')
noisy_signal = calibration_parts.mkadder(
pipeline, calibration_parts.list_srcs(pipeline, signal, noise))
demod_noise = calibration_parts.demodulate(pipeline, noise, 16.3, True, 16,
20, 0)
demod_noise = pipeparts.mkgeneric(pipeline, demod_noise, "cabs")
rms_noise = calibration_parts.compute_rms(pipeline,
demod_noise,
16,
900,
filter_latency=0,
rate_out=1)
pipeparts.mknxydumpsink(pipeline, rms_noise, "rms_noise.txt")
demod_signal = calibration_parts.demodulate(pipeline, noisy_signal, 16.3,
True, 16, 20, 0)
demod_signal = pipeparts.mkgeneric(pipeline, demod_signal, "cabs")
rms_signal = calibration_parts.compute_rms(pipeline,
demod_signal,
16,
900,
filter_latency=0,
rate_out=1)
pipeparts.mknxydumpsink(pipeline, rms_signal, "rms_signal.txt")
#
# done
#
return pipeline
def fill_silence_test_01(pipeline, name, line_sep=0.5):
#
# This test is intended to help get rid of error messages associated with adding two streams that have different start times
#
rate = 16 # Hz
buffer_length = 1.0 # seconds
test_duration = 300.0 # seconds
filter_latency = 1.0
#
# build pipeline
#
head = test_common.test_src(pipeline,
rate=rate,
test_duration=test_duration,
wave=5)
head = pipeparts.mktee(pipeline, head)
smooth = calibration_parts.mkcomplexfirbank(
pipeline,
head,
latency=int((rate * 40 - 1) * filter_latency + 0.5),
fir_matrix=[numpy.ones(rate * 40)],
time_domain=True)
smooth = calibration_parts.mkcomplexfirbank(pipeline,
smooth,
latency=23,
fir_matrix=[numpy.ones(45)],
time_domain=True)
#smooth = pipeparts.mkgeneric(pipeline, head, "lal_smoothkappas", array_size = rate * 128, avg_array_size = rate * 10, filter_latency = 1)
#smooth = pipeparts.mkgeneric(pipeline, smooth, "splitcounter", name = "smooth")
#head = pipeparts.mkgeneric(pipeline, head, "splitcounter", name = "unsmooth")
#channelmux_input_dict = {}
#channelmux_input_dict["unsmooth"] = calibration_parts.mkqueue(pipeline, head)
#channelmux_input_dict["smooth"] = calibration_parts.mkqueue(pipeline, smooth)
#mux = pipeparts.mkframecppchannelmux(pipeline, channelmux_input_dict, frame_duration = 64, frames_per_file = 1, compression_scheme = 6, compression_level = 3)
head = calibration_parts.mkadder(
pipeline, calibration_parts.list_srcs(pipeline, head, smooth))
#mux = pipeparts.mkgeneric(pipeline, mux, "splitcounter", name = "sum")
#head = calibration_parts.mkgate(pipeline, smooth, head, 0)
pipeparts.mknxydumpsink(pipeline, head, "%s_out.txt" % name)
#pipeparts.mkframecppfilesink(pipeline, mux, frame_type = "H1DCS", instrument = "H1")
#
# done
#
return pipeline
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 lal_multiple_srcs(pipeline, name):
#
# This test uses multiple source elements
#
rate = 1000 # Hz
buffer_length = 1.0 # seconds
test_duration = 10.0 # seconds
#
# build pipeline
#
src1 = test_common.test_src(pipeline,
buffer_length=buffer_length,
rate=rate,
test_duration=test_duration,
width=32,
verbose=False)
capsfilter1 = pipeparts.mkcapsfilter(
pipeline, src1, "audio/x-raw, format=F32LE, rate=%d" % int(rate))
src2 = test_common.test_src(pipeline,
buffer_length=buffer_length,
rate=rate,
test_duration=test_duration,
width=32,
verbose=False)
capsfilter2 = pipeparts.mkcapsfilter(
pipeline, src2, "audio/x-raw, format=F32LE, rate=%d" % int(rate))
combined = calibration_parts.mkadder(
pipeline,
calibration_parts.list_srcs(pipeline, capsfilter1, capsfilter2))
pipeparts.mknxydumpsink(pipeline, pipeparts.mkqueue(pipeline, combined),
"multiple_srcs_out.dump")
#
# done
#
return pipeline
def lal_transferfunction_01(pipeline, name):
#
# This test adds various noise into a stream and uses lal_transferfunction to remove it
#
rate = 16384 # Hz
buffer_length = 1.0 # seconds
test_duration = 3000.0 # seconds
width = 64 # bits
#
# build pipeline
#
hoft = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
volume=0.001,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
hoft = pipeparts.mktee(pipeline, hoft)
common_noise = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
freq=512,
volume=1,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
common_noise = pipeparts.mktee(pipeline, common_noise)
noise1 = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
freq=512,
volume=1,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
noise1 = calibration_parts.mkadder(
pipeline, calibration_parts.list_srcs(pipeline, common_noise, noise1))
noise1 = pipeparts.mktee(pipeline, noise1)
noise1_for_cleaning = pipeparts.mkgeneric(pipeline, noise1, "identity")
hoft_noise1 = pipeparts.mkshift(pipeline, noise1, shift=00000000)
hoft_noise1 = pipeparts.mkaudioamplify(pipeline, hoft_noise1, 2)
hoft_noise1 = pipeparts.mktee(pipeline, hoft_noise1)
noise2 = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
freq=1024,
volume=1,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
noise2 = calibration_parts.mkadder(
pipeline, calibration_parts.list_srcs(pipeline, common_noise, noise2))
noise2 = pipeparts.mktee(pipeline, noise2)
noise2_for_cleaning = pipeparts.mkgeneric(pipeline, noise2, "identity")
hoft_noise2 = pipeparts.mkshift(pipeline, noise2, shift=00000)
hoft_noise2 = pipeparts.mkaudioamplify(pipeline, hoft_noise2, 3)
hoft_noise2 = pipeparts.mktee(pipeline, hoft_noise2)
noisy_hoft = calibration_parts.mkadder(
pipeline,
calibration_parts.list_srcs(pipeline, hoft, hoft_noise1, hoft_noise2))
noisy_hoft = pipeparts.mktee(pipeline, noisy_hoft)
clean_hoft = calibration_parts.clean_data(
pipeline,
calibration_parts.list_srcs(pipeline, noisy_hoft, noise1_for_cleaning,
noise2_for_cleaning), rate / 4, rate / 8,
16384, test_duration * rate)
clean_hoft = pipeparts.mktee(pipeline, clean_hoft)
# hoft_inv = pipeparts.mkpow(pipeline, hoft, exponent = -1.0)
# clean_hoft_over_hoft = calibration_parts.mkmultiplier(pipeline, calibration_parts.list_srcs(pipeline, hoft_inv, clean_hoft))
# pipeparts.mknxydumpsink(pipeline, clean_hoft_over_hoft, "%s_clean_hoft_over_hoft.txt" % name)
pipeparts.mknxydumpsink(pipeline, hoft, "%s_hoft.txt" % name)
pipeparts.mknxydumpsink(pipeline, hoft_noise1, "%s_hoft_noise1.txt" % name)
pipeparts.mknxydumpsink(pipeline, hoft_noise2, "%s_hoft_noise2.txt" % name)
pipeparts.mknxydumpsink(pipeline, noisy_hoft, "%s_noisy_hoft.txt" % name)
pipeparts.mknxydumpsink(pipeline, clean_hoft, "%s_clean_hoft.txt" % name)
#
# done
#
return pipeline
def lal_transferfunction_03(pipeline, name):
#
# This test produces three-channel data to be read into lal_transferfunction
#
rate = 16384 # Hz
buffer_length = 1.0 # seconds
test_duration = 50.0 # seconds
width = 64 # bits
freq = 512 # Hz
num_witnesses = 2
witness_factor = 0.5 # Ratio of amplitudes of witness / signal
#
# build pipeline
#
hoft = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
volume=1,
freq=freq,
channels=1,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
hoft = pipeparts.mktee(pipeline, hoft)
noise = []
for i in range(0, num_witnesses):
difference = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
volume=0.001,
channels=1,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
noisy_hoft = calibration_parts.mkadder(
pipeline,
calibration_parts.list_srcs(
pipeline,
pipeparts.mkaudioamplify(pipeline, hoft, witness_factor),
difference))
noisy_hoft = pipeparts.mkprogressreport(pipeline, noisy_hoft,
"noisy_hoft_%d" % i)
noise.append(noisy_hoft)
clean_data = calibration_parts.clean_data(pipeline,
hoft,
rate,
noise,
rate,
2 * rate,
rate,
10,
rate * 1000,
rate,
4,
filename="tfs.txt")
pipeparts.mknxydumpsink(pipeline, hoft, "%s_hoft.txt" % name)
pipeparts.mknxydumpsink(pipeline, clean_data, "%s_out.txt" % name)
return pipeline
def lal_transferfunction_02(pipeline, name):
#
# This test produces three-channel data to be read into lal_transferfunction
#
rate = 16384 # Hz
buffer_length = 1.0 # seconds
test_duration = 500.0 # seconds
width = 64 # bits
channels = 1
freq = 512 # Hz
#
# build pipeline
#
hoft = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
volume=1,
freq=freq,
channels=channels,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
hoft = pipeparts.mktee(pipeline, hoft)
noise = test_common.test_src(pipeline,
buffer_length=buffer_length,
wave=5,
volume=1,
freq=freq,
channels=channels,
rate=rate,
test_duration=test_duration,
width=width,
verbose=False)
noise = pipeparts.mktee(pipeline, noise)
witness1 = calibration_parts.mkadder(
pipeline,
calibration_parts.list_srcs(
pipeline, calibration_parts.highpass(pipeline,
hoft,
rate,
fcut=400),
calibration_parts.lowpass(pipeline, noise, rate, fcut=400)))
witness2 = calibration_parts.mkadder(
pipeline,
calibration_parts.list_srcs(
pipeline, calibration_parts.lowpass(pipeline, hoft, rate,
fcut=600),
calibration_parts.highpass(pipeline, noise, rate, fcut=600)))
hoft = calibration_parts.highpass(pipeline, hoft, rate)
clean_data = calibration_parts.clean_data(
pipeline,
hoft,
rate,
calibration_parts.list_srcs(pipeline, witness1, witness2),
rate,
4 * rate,
2 * rate,
128,
rate * test_duration,
int(0.5 * rate),
10.0,
filename="highpass_lowpass_tfs.txt")
pipeparts.mknxydumpsink(pipeline, clean_data, "%s_out.txt" % name)
return pipeline