add basic frame reading function

tupak/utils.py

@@ -4,6 +4,8 @@ import os
 import numpy as np
 from math import fmod
 from gwpy.timeseries import TimeSeries
+from gwpy.signal import filter_design
+from scipy import signal
 import argparse
 
 # Constants
@@ -514,6 +516,110 @@ def get_open_strain_data(
     return strain
 
 
+def read_frame_file(file_name, t1, t2, channel=None, **kwargs):
+    """ A function which accesses the open strain data
+
+    This uses `gwpy` to download the open data and then saves a cached copy for
+    later use
+
+    Parameters
+    ----------
+    file_name: str
+        The name of the frame to read
+    t1, t2: float
+        The GPS time of the start and end of the data
+    channel: str
+        The name of the channel being searched for, some standard channel names are attempted
+        if channel is not specified or if specified channel is not found.
+    **kwargs:
+        Passed to `gwpy.timeseries.TimeSeries.fetch_open_data`
+
+    Returns
+    -----------
+    strain: gwpy.timeseries.TimeSeries
+
+    """
+    loaded = False
+    if channel is not None:
+        try:
+            strain = TimeSeries.read(source=file_name, channel=channel, start=t1, end=t2, **kwargs)
+            loaded = True
+            logging.info('Successfully loaded {}.'.format(channel))
+        except RuntimeError:
+            logging.warning('Channel {} not found. Trying preset channel names'.format(channel))
+    for channel in ['GDS-CALIB_STRAIN', 'DCS-CALIB_STRAIN_C01', 'DCS-CALIB_STRAIN_C02']:
+        if loaded:
+            continue
+        try:
+            strain = TimeSeries.read(source=file_name, channel=channel, start=t1, end=t2, **kwargs)
+            loaded = True
+            logging.info('Successfully loaded {}.'.format(channel))
+        except RuntimeError:
+            None
+
+    if loaded:
+        return strain
+    else:
+        logging.warning('No data loaded.')
+        return None
+
+
+def process_strain_data(
+        strain, alpha=0.25, filter_freq=1024, **kwargs):
+    """
+    Helper function to obtain an Interferometer instance with appropriate
+    PSD and data, given an center_time.
+
+    Parameters
+    ----------
+    name: str
+        Detector name, e.g., 'H1'.
+    center_time: float
+        GPS time of the center_time about which to perform the analysis.
+        Note: the analysis data is from `center_time-T/2` to `center_time+T/2`.
+    T: float
+        The total time (in seconds) to analyse. Defaults to 4s.
+    alpha: float
+        The tukey window shape parameter passed to `scipy.signal.tukey`.
+    psd_offset, psd_duration: float
+        The power spectral density (psd) is estimated using data from
+        `center_time+psd_offset` to `center_time+psd_offset + psd_duration`.
+    outdir: str
+        Directory where the psd files are saved
+    plot: bool
+        If true, create an ASD + strain plot
+    filter_freq: float
+        Low pass filter frequency
+    **kwargs:
+        All keyword arguments are passed to
+        `gwpy.timeseries.TimeSeries.fetch_open_data()`.
+
+    Returns
+    -------
+    interferometer: `tupak.detector.Interferometer`
+        An Interferometer instance with a PSD and frequency-domain strain data.
+
+    """
+
+    sampling_frequency = int(strain.sample_rate.value)
+
+    # Low pass filter
+    bp = filter_design.lowpass(filter_freq, strain.sample_rate)
+    strain = strain.filter(bp, filtfilt=True)
+    strain = strain.crop(*strain.span.contract(1))
+
+    time_series = strain.times.value
+    time_duration = time_series[-1] - time_series[0]
+
+    # Apply Tukey window
+    N = len(time_series)
+    strain = strain * signal.windows.tukey(N, alpha=alpha)
+
+    frequency_domain_strain = nfft(strain.value, sampling_frequency)[0]
+
+    return frequency_domain_strain
+
+
 def set_up_command_line_arguments():
     parser = argparse.ArgumentParser(
         description="Command line interface for tupak scripts")