Fixing more code climate issues

gwastro · Jul 11, 2023 · cd679b2 · cd679b2
1 parent 4aeb1b4
commit cd679b2
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Showing 2 changed files with 19 additions and 11 deletions.
diff --git a/pycbc/psd/__init__.py b/pycbc/psd/__init__.py
@@ -318,26 +318,26 @@ def insert_psd_option_group_multi_ifo(parser):
                              "mean, median or median-mean.")
     psd_options.add_argument("--psd-segment-length", type=float, nargs="+",
                              action=MultiDetOptionAction, metavar='IFO:LENGTH',
-                             help="(Required for --psd-estimation) The segment "
-                             "length for PSD estimation (s)")
+                             help="(Required for --psd-estimation) The "
+                             "segment length for PSD estimation (s)")
     psd_options.add_argument("--psd-segment-stride", type=float, nargs="+",
                              action=MultiDetOptionAction, metavar='IFO:STRIDE',
-                             help="(Required for --psd-estimation) The separation"
-                             " between consecutive segments (s)")
+                             help="(Required for --psd-estimation) The "
+                             "separation between consecutive segments (s)")
     psd_options.add_argument("--psd-num-segments", type=int, nargs="+",
                              default=None,
                              action=MultiDetOptionAction, metavar='IFO:NUM',
-                             help="(Optional, used only with --psd-estimation). "
-                             "If given PSDs will be estimated using only "
+                             help="(Optional, used only with --psd-estimation)"
+                             " If given PSDs will be estimated using only "
                              "this number of segments. If more data is "
                              "given than needed to make this number of "
                              "segments than excess data will not be used in "
                              "the PSD estimate. If not enough data is given "
                              "the code will fail.")
     psd_options.add_argument("--psd-inverse-length", type=float, nargs="+",
                              action=MultiDetOptionAction, metavar='IFO:LENGTH',
-                             help="(Optional) The maximum length of the impulse"
-                             " response of the overwhitening filter (s)")
+                             help="(Optional) The maximum length of the "
+                             "impulse response of the overwhitening filter(s)")
     psd_options.add_argument("--invpsd-trunc-method", default=None,
                              choices=["hann"],
                              help="(Optional) What truncation method to use "

diff --git a/pycbc/psd/read.py b/pycbc/psd/read.py
@@ -23,7 +23,7 @@
 import scipy.interpolate
 
 from ligo import segments
-from pycbc.types import FrequencySeries, load_frequencyseries, zeros, float32
+from pycbc.types import FrequencySeries, load_frequencyseries, zeros
 import pycbc.psd
 
 
@@ -52,7 +52,8 @@ def from_numpy_arrays(freq_data, noise_data, length, delta_f, low_freq_cutoff):
     # Only include points above the low frequency cutoff
     if freq_data[0] > low_freq_cutoff:
         raise ValueError('Lowest frequency in input data '
-                         ' is higher than requested low-frequency cutoff ' + str(low_freq_cutoff))
+                         ' is higher than requested low-frequency cutoff '
+                         + str(low_freq_cutoff))
 
     kmin = int(low_freq_cutoff / delta_f)
     flow = kmin * delta_f
@@ -194,8 +195,13 @@ def from_xml(filename, length, delta_f, low_freq_cutoff, ifo_string=None,
                              low_freq_cutoff)
 
 
-class PrecomputedTimeVaryingPSD(object):
+class PrecomputedTimeVaryingPSD:
+    '''Class to read merge psd like files and to attach
+    appropriate PSD to the data segment
+    '''
+
     def __init__(self, file_name, length=None, delta_f=None, f_low=None):
+
         with h5py.File(file_name, 'r') as f:
             self.file_name = file_name
             detector = tuple(f.keys())[0]
@@ -244,6 +250,8 @@ def assosiate_psd_to_inspiral_segment(self, inp_seg, delta_f=None):
         return best_psd
 
     def get_psd(self, index, delta_f=None):
+        '''fetch psd based on index corresponding to times.
+        '''
         group = self.detector + '/psds/' + str(index)
         psd = load_frequencyseries(self.file_name, group=group)
         if delta_f is not None and psd.delta_f != delta_f: