import sys
import numpy as np
from blimpy import Waterfall
[docs]def max_freq(waterfall):
"""
Returns central frequency of the highest-frequency bin in a .fil file.
Parameters
----------
waterfall : str or Waterfall
Name of filterbank file or Waterfall object
Returns
-------
fmax : float
Maximum frequency in data
"""
if isinstance(waterfall, str):
waterfall = Waterfall(waterfall, load_data=False)
elif not isinstance(waterfall, Waterfall):
sys.exit('Invalid fil file!')
return waterfall.container.f_stop
[docs]def min_freq(waterfall):
"""
Returns central frequency of the lowest-frequency bin in a .fil file.
Parameters
----------
waterfall : str or Waterfall
Name of filterbank file or Waterfall object
Returns
-------
fmin : float
Minimum frequency in data
"""
if isinstance(waterfall, str):
waterfall = Waterfall(waterfall, load_data=False)
elif not isinstance(waterfall, Waterfall):
sys.exit('Invalid data file!')
return waterfall.container.f_start
[docs]def get_data(waterfall, use_db=False):
"""
Gets time-frequency data from filterbank file as a 2d NumPy array.
Note: when multiple Stokes parameters are supported, this will have to
be expanded.
Parameters
----------
waterfall : str or Waterfall
Name of filterbank file or Waterfall object
Returns
-------
data : ndarray
Time-frequency data
"""
if isinstance(waterfall, str):
waterfall = Waterfall(waterfall)
elif not isinstance(waterfall, Waterfall):
sys.exit('Invalid data file!')
if use_db:
return 10 * np.log10(waterfall.data[:, 0, :])
return waterfall.data[:, 0, :]
[docs]def get_fs(waterfall):
"""
Gets frequency values from filterbank file.
Parameters
----------
waterfall : str or Waterfall
Name of filterbank file or Waterfall object
Returns
-------
fs : ndarray
Frequency values
"""
if isinstance(waterfall, str):
waterfall = Waterfall(waterfall, load_data=False)
elif not isinstance(waterfall, Waterfall):
sys.exit('Invalid data file!')
fch1 = waterfall.header[b'fch1']
df = waterfall.header[b'foff']
fchans = waterfall.header[b'nchans']
return np.arange(fch1, fch1 + fchans * df, df)
[docs]def get_ts(waterfall):
"""
Gets time values from filterbank file.
Parameters
----------
waterfall : str or Waterfall
Name of filterbank file or Waterfall object
Returns
-------
ts : ndarray
Time values
"""
if isinstance(waterfall, str):
waterfall = Waterfall(waterfall, load_data=False)
elif not isinstance(waterfall, Waterfall):
sys.exit('Invalid data file!')
tsamp = waterfall.header[b'tsamp']
tchans = waterfall.container.selection_shape[0]
return np.arange(0, tchans * tsamp, tsamp)