m-thesis-introduction/simulations/lib/sampling/sampling.py

"""
Sampling related stuff

Such as a Sampler and Digitizer
"""

import numpy as np

def quantise(signal, resolution, bias=0):
    """
    Quantise the signal with resolution

    Parameters
    ##########
    signal - arraylike
        The signal to be quantised
    resolution - float
        Resolution for quantising the signal
    bias - optional,float
        Optional bias applied before quantising
    """

    return np.round(signal / resolution - bias) * resolution

def resample(signal, signal_fs, sample_frequency = 1):
    """
    Resample signal (sampled at signal_fs) to sample_frequency

    Parameters
    ##########
    signal - arraylike
        The signal to be resampled
    signal_fs - float
        Sampling frequency of signal
    sample_frequency - float
        Wanted sampling frequency for the resampled signal
    """

    scale = sample_frequency / signal_fs

    return _resample(signal, scale)

def _resample(signal, scale):
    """
    Quick resampling algorithm

    From: https://github.com/nwhitehead/swmixer/blob/master/swmixer.py
    """
    n = round( len(signal) * scale )

    return np.interp(
        np.linspace(0, 1, n, endpoint=False), # where to interpret
        np.linspace(0, 1, len(signal), endpoint=False), # known positions
        signal, # known data points
    )