mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-12-23 03:43:32 +01:00
55 lines
1.3 KiB
Python
55 lines
1.3 KiB
Python
"""
|
|
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
|
|
)
|