# -*- coding: utf-8 -*-
"""
Created on Wed Sep 28 11:01:16 2022
@author: chinn
"""
import numpy as np
from sklearn.linear_model import LinearRegression
from scipy import signal
import pywt
[docs]class snv():
def __init__(self):
pass
[docs] def fit(self, X):
self.mean = np.mean(X,axis=0)
self.std = np.std(X,axis=0)
return self
[docs]class cwt():
def __init__(self, wavelet = "morl", scale = 20):
"""
Parameters
----------
wavelet : string, optional
Wavelet object or name:
['cgau1'-'cgau8','cmor','fbsp',
'gaus1'-'gaus8','mexh','morl','shan'].
For details about this wavelet, refer to https://pywavelets.readthedocs.io/en/latest/ref/cwt.html
The default is "morl".
scale : array_like, optional
Wavelet scale to use. The default is 20.
Returns
-------
None.
"""
self.wavelet = wavelet
self.scale = scale
[docs] def getContinuousWavelet(self):
return pywt.wavelist(kind = 'continuous')
[docs] def getDiscreteWavelet(self):
return pywt.wavelist(kind = 'discrete')
[docs]class msc():
def __init__(self):
pass
[docs] def fit(self, X):
self.mean = np.mean(X,axis=0)
return self
[docs]class SG_filtering():
def __init__(self,window_length = 13, polyorder=2, **kwargs):
self.window_length = window_length
self.polyorder = polyorder
self.kwargs = kwargs
[docs]class centralization():
def __init__(self):
pass
[docs] def fit(self, X):
self.mean = np.mean(X,axis=0)
return self
# High level preprocessing function
[docs]class derivate():
def __init__(self,deriv = 1, window_length = 13, polyorder=2, **kwargs):
self.deriv = deriv
self.window_length = window_length
self.polyorder = polyorder
self.kwargs = kwargs
[docs]class smooth():
def __init__(self,window_length = 13, polyorder=2, **kwargs):
self.window_length = window_length
self.polyorder = polyorder
self.kwargs = kwargs