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Commit a73b555c authored by John Douglas Veitch's avatar John Douglas Veitch
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Revert "Reformat strain_data.py to satisfy pre-commit" 

This reverts commit bc15e3b0.
parent bc15e3b0
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1 merge request!1233Print fewer info statements when setting strain data
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bilby/gw/detector/strain_data.py
+ 165
− 273
View file @ a73b555c
......@@ -7,24 +7,17 @@ from .. import utils as gwutils
class InterferometerStrainData(object):
"""Strain data for an interferometer"""
duration = PropertyAccessor("_times_and_frequencies", "duration")
sampling_frequency = PropertyAccessor(
"_times_and_frequencies", "sampling_frequency"
)
start_time = PropertyAccessor("_times_and_frequencies", "start_time")
frequency_array = PropertyAccessor("_times_and_frequencies", "frequency_array")
time_array = PropertyAccessor("_times_and_frequencies", "time_array")
def __init__(
self,
minimum_frequency=0,
maximum_frequency=np.inf,
roll_off=0.2,
notch_list=None,
):
"""Initiate an InterferometerStrainData object
""" Strain data for an interferometer """
duration = PropertyAccessor('_times_and_frequencies', 'duration')
sampling_frequency = PropertyAccessor('_times_and_frequencies', 'sampling_frequency')
start_time = PropertyAccessor('_times_and_frequencies', 'start_time')
frequency_array = PropertyAccessor('_times_and_frequencies', 'frequency_array')
time_array = PropertyAccessor('_times_and_frequencies', 'time_array')
def __init__(self, minimum_frequency=0, maximum_frequency=np.inf,
roll_off=0.2, notch_list=None):
""" Initiate an InterferometerStrainData object
The initialised object contains no data, this should be added using one
of the `set_from..` methods.
......@@ -58,26 +51,22 @@ class InterferometerStrainData(object):
self._channel = None
def __eq__(self, other):
if (
self.minimum_frequency == other.minimum_frequency
and self.maximum_frequency == other.maximum_frequency
and self.roll_off == other.roll_off
and self.window_factor == other.window_factor
and self.sampling_frequency == other.sampling_frequency
and self.duration == other.duration
and self.start_time == other.start_time
and np.array_equal(self.time_array, other.time_array)
and np.array_equal(self.frequency_array, other.frequency_array)
and np.array_equal(
self.frequency_domain_strain, other.frequency_domain_strain
)
and np.array_equal(self.time_domain_strain, other.time_domain_strain)
):
if self.minimum_frequency == other.minimum_frequency \
and self.maximum_frequency == other.maximum_frequency \
and self.roll_off == other.roll_off \
and self.window_factor == other.window_factor \
and self.sampling_frequency == other.sampling_frequency \
and self.duration == other.duration \
and self.start_time == other.start_time \
and np.array_equal(self.time_array, other.time_array) \
and np.array_equal(self.frequency_array, other.frequency_array) \
and np.array_equal(self.frequency_domain_strain, other.frequency_domain_strain) \
and np.array_equal(self.time_domain_strain, other.time_domain_strain):
return True
return False
def time_within_data(self, time):
"""Check if time is within the data span
""" Check if time is within the data span
Parameters
==========
......@@ -110,10 +99,10 @@ class InterferometerStrainData(object):
@property
def maximum_frequency(self):
"""Force the maximum frequency be less than the Nyquist frequency"""
""" Force the maximum frequency be less than the Nyquist frequency """
if self.sampling_frequency is not None:
if 2 * self._maximum_frequency > self.sampling_frequency:
self._maximum_frequency = self.sampling_frequency / 2.0
self._maximum_frequency = self.sampling_frequency / 2.
return self._maximum_frequency
@maximum_frequency.setter
......@@ -127,7 +116,7 @@ class InterferometerStrainData(object):
@notch_list.setter
def notch_list(self, notch_list):
"""Set the notch_list
""" Set the notch_list
Parameters
==========
......@@ -148,7 +137,7 @@ class InterferometerStrainData(object):
@property
def frequency_mask(self):
"""Masking array for limiting the frequency band.
""" Masking array for limiting the frequency band.
Returns
=======
......@@ -157,9 +146,8 @@ class InterferometerStrainData(object):
"""
if not self._frequency_mask_updated:
frequency_array = self._times_and_frequencies.frequency_array
mask = (frequency_array >= self.minimum_frequency) & (
frequency_array <= self.maximum_frequency
)
mask = ((frequency_array >= self.minimum_frequency) &
(frequency_array <= self.maximum_frequency))
for notch in self.notch_list:
mask[notch.get_idxs(frequency_array)] = False
self._frequency_mask = mask
......@@ -196,24 +184,22 @@ class InterferometerStrainData(object):
Window function over time array
"""
from scipy.signal.windows import tukey
if roll_off is not None:
self.roll_off = roll_off
elif alpha is not None:
self.roll_off = alpha * self.duration / 2
window = tukey(len(self._time_domain_strain), alpha=self.alpha)
self.window_factor = np.mean(window**2)
self.window_factor = np.mean(window ** 2)
return window
@property
def time_domain_strain(self):
"""The time domain strain, in units of strain"""
""" The time domain strain, in units of strain """
if self._time_domain_strain is not None:
return self._time_domain_strain
elif self._frequency_domain_strain is not None:
self._time_domain_strain = utils.infft(
self.frequency_domain_strain, self.sampling_frequency
)
self.frequency_domain_strain, self.sampling_frequency)
return self._time_domain_strain
else:
......@@ -221,7 +207,7 @@ class InterferometerStrainData(object):
@property
def frequency_domain_strain(self):
"""Returns the frequency domain strain
""" Returns the frequency domain strain
This is the frequency domain strain normalised to units of
strain / Hz, obtained by a one-sided Fourier transform of the
......@@ -230,19 +216,14 @@ class InterferometerStrainData(object):
if self._frequency_domain_strain is not None:
return self._frequency_domain_strain * self.frequency_mask
elif self._time_domain_strain is not None:
logger.debug(
"Generating frequency domain strain from given time " "domain strain."
)
logger.debug(
"Applying a tukey window with alpha={}, roll off={}".format(
self.alpha, self.roll_off
)
)
logger.debug("Generating frequency domain strain from given time "
"domain strain.")
logger.debug("Applying a tukey window with alpha={}, roll off={}".format(
self.alpha, self.roll_off))
# self.low_pass_filter()
window = self.time_domain_window()
self._frequency_domain_strain, self.frequency_array = utils.nfft(
self._time_domain_strain * window, self.sampling_frequency
)
self._time_domain_strain * window, self.sampling_frequency)
return self._frequency_domain_strain * self.frequency_mask
else:
raise ValueError("frequency domain strain data not yet set")
......@@ -250,9 +231,7 @@ class InterferometerStrainData(object):
@frequency_domain_strain.setter
def frequency_domain_strain(self, frequency_domain_strain):
if not len(self.frequency_array) == len(frequency_domain_strain):
raise ValueError(
"The frequency_array and the set strain have different lengths"
)
raise ValueError("The frequency_array and the set strain have different lengths")
self._frequency_domain_strain = frequency_domain_strain
self._time_domain_strain = None
......@@ -266,10 +245,8 @@ class InterferometerStrainData(object):
raise ModuleNotFoundError("Cannot output strain data as gwpy TimeSeries")
return TimeSeries(
self.time_domain_strain,
sample_rate=self.sampling_frequency,
t0=self.start_time,
channel=self.channel,
self.time_domain_strain, sample_rate=self.sampling_frequency,
t0=self.start_time, channel=self.channel
)
def to_pycbc_timeseries(self):
......@@ -284,9 +261,8 @@ class InterferometerStrainData(object):
raise ModuleNotFoundError("Cannot output strain data as PyCBC TimeSeries")
return TimeSeries(
self.time_domain_strain,
delta_t=(1.0 / self.sampling_frequency),
epoch=LIGOTimeGPS(self.start_time),
self.time_domain_strain, delta_t=(1. / self.sampling_frequency),
epoch=LIGOTimeGPS(self.start_time)
)
def to_lal_timeseries(self):
......@@ -299,12 +275,8 @@ class InterferometerStrainData(object):
raise ModuleNotFoundError("Cannot output strain data as PyCBC TimeSeries")
lal_data = CreateREAL8TimeSeries(
"",
LIGOTimeGPS(self.start_time),
0,
1 / self.sampling_frequency,
SecondUnit,
len(self.time_domain_strain),
"", LIGOTimeGPS(self.start_time), 0, 1 / self.sampling_frequency,
SecondUnit, len(self.time_domain_strain)
)
lal_data.data.data[:] = self.time_domain_strain
......@@ -317,15 +289,13 @@ class InterferometerStrainData(object):
try:
from gwpy.frequencyseries import FrequencySeries
except ModuleNotFoundError:
raise ModuleNotFoundError(
"Cannot output strain data as gwpy FrequencySeries"
)
raise ModuleNotFoundError("Cannot output strain data as gwpy FrequencySeries")
return FrequencySeries(
self.frequency_domain_strain,
frequencies=self.frequency_array,
epoch=self.start_time,
channel=self.channel,
channel=self.channel
)
def to_pycbc_frequencyseries(self):
......@@ -342,7 +312,7 @@ class InterferometerStrainData(object):
return FrequencySeries(
self.frequency_domain_strain,
delta_f=1 / self.duration,
epoch=LIGOTimeGPS(self.start_time),
epoch=LIGOTimeGPS(self.start_time)
)
def to_lal_frequencyseries(self):
......@@ -360,49 +330,39 @@ class InterferometerStrainData(object):
self.frequency_array[0],
1 / self.duration,
SecondUnit,
len(self.frequency_domain_strain),
len(self.frequency_domain_strain)
)
lal_data.data.data[:] = self.frequency_domain_strain
return lal_data
def low_pass_filter(self, filter_freq=None):
"""Low pass filter the data"""
""" Low pass filter the data """
from gwpy.signal.filter_design import lowpass
from gwpy.timeseries import TimeSeries
if filter_freq is None:
logger.debug("Setting low pass filter_freq using given maximum frequency")
logger.debug(
"Setting low pass filter_freq using given maximum frequency")
filter_freq = self.maximum_frequency
if 2 * filter_freq >= self.sampling_frequency:
logger.info(
"Low pass filter frequency of {}Hz requested, this is equal"
" or greater than the Nyquist frequency so no filter applied".format(
filter_freq
)
)
" or greater than the Nyquist frequency so no filter applied"
.format(filter_freq))
return
logger.debug(
"Applying low pass filter with filter frequency {}".format(filter_freq)
)
logger.debug("Applying low pass filter with filter frequency {}".format(filter_freq))
bp = lowpass(filter_freq, self.sampling_frequency)
strain = TimeSeries(
self.time_domain_strain, sample_rate=self.sampling_frequency
)
strain = TimeSeries(self.time_domain_strain, sample_rate=self.sampling_frequency)
strain = strain.filter(bp, filtfilt=True)
self._time_domain_strain = strain.value
def create_power_spectral_density(
self,
fft_length,
overlap=0,
name="unknown",
outdir=None,
analysis_segment_start_time=None,
):
"""Use the time domain strain to generate a power spectral density
self, fft_length, overlap=0, name='unknown', outdir=None,
analysis_segment_start_time=None):
""" Use the time domain strain to generate a power spectral density
This create a Tukey-windowed power spectral density and writes it to a
PSD file.
......@@ -435,16 +395,13 @@ class InterferometerStrainData(object):
if analysis_segment_start_time is not None:
analysis_segment_end_time = analysis_segment_start_time + fft_length
inside = (
analysis_segment_start_time
> self.time_array[0] + analysis_segment_end_time
< self.time_array[-1]
)
inside = (analysis_segment_start_time > self.time_array[0] +
analysis_segment_end_time < self.time_array[-1])
if inside:
logger.info("Removing analysis segment data from the PSD data")
idxs = (self.time_array < analysis_segment_start_time) + (
self.time_array > analysis_segment_end_time
)
idxs = (
(self.time_array < analysis_segment_start_time) +
(self.time_array > analysis_segment_end_time))
data = data[idxs]
# WARNING this line can cause issues if the data is non-contiguous
......@@ -452,87 +409,63 @@ class InterferometerStrainData(object):
psd_alpha = 2 * self.roll_off / fft_length
logger.info(
"Tukey window PSD data with alpha={}, roll off={}".format(
psd_alpha, self.roll_off
)
)
psd_alpha, self.roll_off))
psd = strain.psd(
fftlength=fft_length, overlap=overlap, window=("tukey", psd_alpha)
)
fftlength=fft_length, overlap=overlap, window=('tukey', psd_alpha))
if outdir:
psd_file = "{}/{}_PSD_{}_{}.txt".format(
outdir, name, self.start_time, self.duration
)
with open("{}".format(psd_file), "w+") as opened_file:
psd_file = '{}/{}_PSD_{}_{}.txt'.format(outdir, name, self.start_time, self.duration)
with open('{}'.format(psd_file), 'w+') as opened_file:
for f, p in zip(psd.frequencies.value, psd.value):
opened_file.write("{} {}\n".format(f, p))
opened_file.write('{} {}\n'.format(f, p))
return psd.frequencies.value, psd.value
def _infer_time_domain_dependence(
self, start_time, sampling_frequency, duration, time_array
):
"""Helper function to figure out if the time_array, or
sampling_frequency and duration where given
"""
self._infer_dependence(
domain="time",
array=time_array,
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
self, start_time, sampling_frequency, duration, time_array):
""" Helper function to figure out if the time_array, or
sampling_frequency and duration where given
"""
self._infer_dependence(domain='time', array=time_array, duration=duration,
sampling_frequency=sampling_frequency, start_time=start_time)
def _infer_frequency_domain_dependence(
self, start_time, sampling_frequency, duration, frequency_array
):
"""Helper function to figure out if the frequency_array, or
sampling_frequency and duration where given
"""
self._infer_dependence(
domain="frequency",
array=frequency_array,
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
self, start_time, sampling_frequency, duration, frequency_array):
""" Helper function to figure out if the frequency_array, or
sampling_frequency and duration where given
"""
def _infer_dependence(
self, domain, array, duration, sampling_frequency, start_time
):
self._infer_dependence(domain='frequency', array=frequency_array,
duration=duration, sampling_frequency=sampling_frequency, start_time=start_time)
def _infer_dependence(self, domain, array, duration, sampling_frequency, start_time):
if (sampling_frequency is not None) and (duration is not None):
if array is not None:
raise ValueError(
"You have given the sampling_frequency, duration, and " "an array"
)
"You have given the sampling_frequency, duration, and "
"an array")
pass
elif array is not None:
if domain == "time":
if domain == 'time':
self.time_array = array
elif domain == "frequency":
elif domain == 'frequency':
self.frequency_array = array
self.start_time = start_time
return
elif sampling_frequency is None or duration is None:
raise ValueError("You must provide both sampling_frequency and duration")
raise ValueError(
"You must provide both sampling_frequency and duration")
else:
raise ValueError("Insufficient information given to set arrays")
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
raise ValueError(
"Insufficient information given to set arrays")
self._times_and_frequencies = CoupledTimeAndFrequencySeries(duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time)
def set_from_time_domain_strain(
self,
time_domain_strain,
sampling_frequency=None,
duration=None,
start_time=0,
time_array=None,
):
"""Set the strain data from a time domain strain array
self, time_domain_strain, sampling_frequency=None, duration=None,
start_time=0, time_array=None):
""" Set the strain data from a time domain strain array
This sets the time_domain_strain attribute, the frequency_domain_strain
is automatically calculated after a low-pass filter and Tukey window
......@@ -553,14 +486,12 @@ class InterferometerStrainData(object):
given.
"""
self._infer_time_domain_dependence(
start_time=start_time,
sampling_frequency=sampling_frequency,
duration=duration,
time_array=time_array,
)
self._infer_time_domain_dependence(start_time=start_time,
sampling_frequency=sampling_frequency,
duration=duration,
time_array=time_array)
logger.debug("Setting data using provided time_domain_strain")
logger.debug('Setting data using provided time_domain_strain')
if np.shape(time_domain_strain) == np.shape(self.time_array):
self._time_domain_strain = time_domain_strain
self._frequency_domain_strain = None
......@@ -568,7 +499,7 @@ class InterferometerStrainData(object):
raise ValueError("Data times do not match time array")
def set_from_gwpy_timeseries(self, time_series):
"""Set the strain data from a gwpy TimeSeries
""" Set the strain data from a gwpy TimeSeries
This sets the time_domain_strain attribute, the frequency_domain_strain
is automatically calculated after a low-pass filter and Tukey window
......@@ -581,15 +512,13 @@ class InterferometerStrainData(object):
"""
from gwpy.timeseries import TimeSeries
logger.debug("Setting data using provided gwpy TimeSeries object")
logger.debug('Setting data using provided gwpy TimeSeries object')
if not isinstance(time_series, TimeSeries):
raise ValueError("Input time_series is not a gwpy TimeSeries")
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=time_series.duration.value,
sampling_frequency=time_series.sample_rate.value,
start_time=time_series.epoch.value,
)
self._times_and_frequencies = \
CoupledTimeAndFrequencySeries(duration=time_series.duration.value,
sampling_frequency=time_series.sample_rate.value,
start_time=time_series.epoch.value)
self._time_domain_strain = time_series.value
self._frequency_domain_strain = None
self._channel = time_series.channel
......@@ -599,9 +528,9 @@ class InterferometerStrainData(object):
return self._channel
def set_from_open_data(
self, name, start_time, duration=4, outdir="outdir", cache=True, **kwargs
):
"""Set the strain data from open LOSC data
self, name, start_time, duration=4, outdir='outdir', cache=True,
**kwargs):
""" Set the strain data from open LOSC data
This sets the time_domain_strain attribute, the frequency_domain_strain
is automatically calculated after a low-pass filter and Tukey window
......@@ -626,18 +555,13 @@ class InterferometerStrainData(object):
"""
timeseries = gwutils.get_open_strain_data(
name,
start_time,
start_time + duration,
outdir=outdir,
cache=cache,
**kwargs
)
name, start_time, start_time + duration, outdir=outdir, cache=cache,
**kwargs)
self.set_from_gwpy_timeseries(timeseries)
def set_from_csv(self, filename):
"""Set the strain data from a csv file
""" Set the strain data from a csv file
Parameters
==========
......@@ -646,19 +570,13 @@ class InterferometerStrainData(object):
"""
from gwpy.timeseries import TimeSeries
timeseries = TimeSeries.read(filename, format="csv")
timeseries = TimeSeries.read(filename, format='csv')
self.set_from_gwpy_timeseries(timeseries)
def set_from_frequency_domain_strain(
self,
frequency_domain_strain,
sampling_frequency=None,
duration=None,
start_time=0,
frequency_array=None,
):
"""Set the `frequency_domain_strain` from a numpy array
self, frequency_domain_strain, sampling_frequency=None,
duration=None, start_time=0, frequency_array=None):
""" Set the `frequency_domain_strain` from a numpy array
Parameters
==========
......@@ -676,14 +594,12 @@ class InterferometerStrainData(object):
"""
self._infer_frequency_domain_dependence(
start_time=start_time,
sampling_frequency=sampling_frequency,
duration=duration,
frequency_array=frequency_array,
)
self._infer_frequency_domain_dependence(start_time=start_time,
sampling_frequency=sampling_frequency,
duration=duration,
frequency_array=frequency_array)
logger.debug("Setting data using provided frequency_domain_strain")
logger.debug('Setting data using provided frequency_domain_strain')
if np.shape(frequency_domain_strain) == np.shape(self.frequency_array):
self._frequency_domain_strain = frequency_domain_strain
self.window_factor = 1
......@@ -691,9 +607,9 @@ class InterferometerStrainData(object):
raise ValueError("Data frequencies do not match frequency_array")
def set_from_power_spectral_density(
self, power_spectral_density, sampling_frequency, duration, start_time=0
):
"""Set the `frequency_domain_strain` by generating a noise realisation
self, power_spectral_density, sampling_frequency, duration,
start_time=0):
""" Set the `frequency_domain_strain` by generating a noise realisation
Parameters
==========
......@@ -708,20 +624,15 @@ class InterferometerStrainData(object):
"""
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
self._times_and_frequencies = CoupledTimeAndFrequencySeries(duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time)
logger.debug(
"Setting data using noise realization from provided" "power_spectal_density"
)
(
frequency_domain_strain,
frequency_array,
) = power_spectral_density.get_noise_realisation(
self.sampling_frequency, self.duration
)
'Setting data using noise realization from provided'
'power_spectal_density')
frequency_domain_strain, frequency_array = \
power_spectral_density.get_noise_realisation(
self.sampling_frequency, self.duration)
if np.array_equal(frequency_array, self.frequency_array):
self._frequency_domain_strain = frequency_domain_strain
......@@ -729,7 +640,7 @@ class InterferometerStrainData(object):
raise ValueError("Data frequencies do not match frequency_array")
def set_from_zero_noise(self, sampling_frequency, duration, start_time=0):
"""Set the `frequency_domain_strain` to zero noise
""" Set the `frequency_domain_strain` to zero noise
Parameters
==========
......@@ -742,26 +653,17 @@ class InterferometerStrainData(object):
"""
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
logger.debug("Setting zero noise data")
self._frequency_domain_strain = np.zeros_like(
self.frequency_array, dtype=complex
)
self._times_and_frequencies = CoupledTimeAndFrequencySeries(duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time)
logger.debug('Setting zero noise data')
self._frequency_domain_strain = np.zeros_like(self.frequency_array,
dtype=complex)
def set_from_frame_file(
self,
frame_file,
sampling_frequency,
duration,
start_time=0,
channel=None,
buffer_time=1,
):
"""Set the `frequency_domain_strain` from a frame fiile
self, frame_file, sampling_frequency, duration, start_time=0,
channel=None, buffer_time=1):
""" Set the `frequency_domain_strain` from a frame fiile
Parameters
==========
......@@ -782,25 +684,19 @@ class InterferometerStrainData(object):
"""
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
duration=duration, sampling_frequency=sampling_frequency,
start_time=start_time)
logger.info("Reading data from frame file {}".format(frame_file))
logger.info('Reading data from frame file {}'.format(frame_file))
strain = gwutils.read_frame_file(
frame_file,
start_time=start_time,
end_time=start_time + duration,
buffer_time=buffer_time,
channel=channel,
resample=sampling_frequency,
)
frame_file, start_time=start_time, end_time=start_time + duration,
buffer_time=buffer_time, channel=channel,
resample=sampling_frequency)
self.set_from_gwpy_timeseries(strain)
def set_from_channel_name(self, channel, duration, start_time, sampling_frequency):
"""Set the `frequency_domain_strain` by fetching from given channel
""" Set the `frequency_domain_strain` by fetching from given channel
using gwpy.TimesSeries.get(), which dynamically accesses either frames
on disk, or a remote NDS2 server to find and return data. This function
also verifies that the specified channel is given in the correct format.
......@@ -818,18 +714,15 @@ class InterferometerStrainData(object):
"""
from gwpy.timeseries import TimeSeries
channel_comp = channel.split(":")
channel_comp = channel.split(':')
if len(channel_comp) != 2:
raise IndexError("Channel name must have format `IFO:Channel`")
raise IndexError('Channel name must have format `IFO:Channel`')
self._times_and_frequencies = CoupledTimeAndFrequencySeries(
duration=duration,
sampling_frequency=sampling_frequency,
start_time=start_time,
)
duration=duration, sampling_frequency=sampling_frequency,
start_time=start_time)
logger.info("Fetching data using channel {}".format(channel))
logger.info('Fetching data using channel {}'.format(channel))
strain = TimeSeries.get(channel, start_time, start_time + duration)
strain = strain.resample(sampling_frequency)
......@@ -838,7 +731,7 @@ class InterferometerStrainData(object):
class Notch(object):
def __init__(self, minimum_frequency, maximum_frequency):
"""A notch object storing the maximum and minimum frequency of the notch
""" A notch object storing the maximum and minimum frequency of the notch
Parameters
==========
......@@ -851,13 +744,12 @@ class Notch(object):
self.minimum_frequency = minimum_frequency
self.maximum_frequency = maximum_frequency
else:
msg = "Your notch minimum_frequency {} and maximum_frequency {} are invalid".format(
minimum_frequency, maximum_frequency
)
msg = ("Your notch minimum_frequency {} and maximum_frequency {} are invalid"
.format(minimum_frequency, maximum_frequency))
raise ValueError(msg)
def get_idxs(self, frequency_array):
"""Get a boolean mask for the frequencies in frequency_array in the notch
""" Get a boolean mask for the frequencies in frequency_array in the notch
Parameters
==========
......@@ -870,12 +762,12 @@ class Notch(object):
An array of booleans which are True for frequencies in the notch
"""
lower = frequency_array > self.minimum_frequency
upper = frequency_array < self.maximum_frequency
lower = (frequency_array > self.minimum_frequency)
upper = (frequency_array < self.maximum_frequency)
return lower & upper
def check_frequency(self, freq):
"""Check if freq is inside the notch
""" Check if freq is inside the notch
Parameters
==========
......@@ -896,7 +788,7 @@ class Notch(object):
class NotchList(list):
def __init__(self, notch_list):
"""A list of notches
""" A list of notches
Parameters
==========
......@@ -919,7 +811,7 @@ class NotchList(list):
raise ValueError(msg)
def check_frequency(self, freq):
"""Check if freq is inside the notch list
""" Check if freq is inside the notch list
Parameters
==========
......
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