Source code for toto.filters.moving_average

""" Run a moving average

    Parameters
    ~~~~~~~~~~
    input_array : Panda Obj
        The Panda dataframe.
    N-Points filter : int,
        Number of point to use.
    mode : {'valid', 'same'}, optional
        'same':
          Mode 'same' returns output of length ``max(M, N)``.  Boundary
          effects are still visible.
        'valid':
          Mode 'valid' returns output of length
          ``max(M, N) - min(M, N) + 1``.  The convolution product is only given
          for points where the signals overlap completely.  Values outside
          the signal boundary have no effect.

    Note
    ~~~~

    see <https://numpy.org/doc/stable/reference/generated/numpy.convolve.html>_

"""
import numpy as np


def moving_average(input_array,args={'N-Points filter':int(),\
                                    'Mode':{"valid": False, "same":True}}):


    N=args['N-Points filter']
    #mode=[key for key in args['Mode'] if args['Mode'][key]][0]
    mode=args['Mode']

    if mode=='valid':
        y=input_array.to_numpy(copy=True)
        y_padded = np.pad(y, (N//2, N-1-N//2), mode='edge')
        input_array.values[:] = np.convolve(y_padded, np.ones((N,))/N, mode='valid') 
    else:
        input_array.values[:]=np.convolve(input_array.to_numpy(copy=True), np.ones((N,))/N, mode=mode)
    
    return input_array