Module wavelet.compression.compressor
Simple Compression method to zeroed the data that is below certain level
Expand source code
""" Simple Compression method to zeroed the data that is below certain level """
import numpy as np
class Compressor:
"""
The input magnitude, defines how to threshold the data. The range below the magnitude
is made zero, which is then counted to determine the compression rate for the data and the
algorithm
Attributes
----------
__magnitude: float
magnitude to compare the data with
__threshold: float
threshold to compare the data with
__substitute: float
value to change with
"""
def __init__(self):
self.__magnitude = 0.
self.__threshold = 1.
self.__substitute = 0.
def compress(self, data, magnitude):
"""
Compress the data using the magnitude, make the elements zero which are lower the value
Parameters
----------
data: array_like
input signal
magnitude: float
min magnitude to threshold
Returns
-------
array_like
thresholded values
"""
self.__magnitude = magnitude
con = np.less(data, (self.__magnitude * self.__threshold))
return np.where(con, self.__substitute, data)
def calculateCompressionRate(self, data):
"""
Calculates the compression rate that is just the number of zeros
in the signal
Parameters
----------
data: array_like
input signal from the final step
Returns
-------
float
percentage value of the compression rate
"""
data = np.asanyarray(data).flatten()
noOfZeros = np.count_nonzero(data == 0)
if noOfZeros == 0:
return noOfZeros
return (noOfZeros / len(data)) * 100
def getMagnitude(self):
"""
Returns the magnitude calculated
Returns
-------
float
magnitude calculated
"""
return self.__magnitude
def getThreshold(self):
"""
Returns the threshold
Returns
-------
float
default is 1
"""
return self.__thresholdClasses
class Compressor-
The input magnitude, defines how to threshold the data. The range below the magnitude is made zero, which is then counted to determine the compression rate for the data and the algorithm
Attributes
__magnitude:float- magnitude to compare the data with
__threshold:float- threshold to compare the data with
__substitute:float- value to change with
Expand source code
class Compressor: """ The input magnitude, defines how to threshold the data. The range below the magnitude is made zero, which is then counted to determine the compression rate for the data and the algorithm Attributes ---------- __magnitude: float magnitude to compare the data with __threshold: float threshold to compare the data with __substitute: float value to change with """ def __init__(self): self.__magnitude = 0. self.__threshold = 1. self.__substitute = 0. def compress(self, data, magnitude): """ Compress the data using the magnitude, make the elements zero which are lower the value Parameters ---------- data: array_like input signal magnitude: float min magnitude to threshold Returns ------- array_like thresholded values """ self.__magnitude = magnitude con = np.less(data, (self.__magnitude * self.__threshold)) return np.where(con, self.__substitute, data) def calculateCompressionRate(self, data): """ Calculates the compression rate that is just the number of zeros in the signal Parameters ---------- data: array_like input signal from the final step Returns ------- float percentage value of the compression rate """ data = np.asanyarray(data).flatten() noOfZeros = np.count_nonzero(data == 0) if noOfZeros == 0: return noOfZeros return (noOfZeros / len(data)) * 100 def getMagnitude(self): """ Returns the magnitude calculated Returns ------- float magnitude calculated """ return self.__magnitude def getThreshold(self): """ Returns the threshold Returns ------- float default is 1 """ return self.__thresholdMethods
def calculateCompressionRate(self, data)-
Calculates the compression rate that is just the number of zeros in the signal
Parameters
data:array_like- input signal from the final step
Returns
float- percentage value of the compression rate
Expand source code
def calculateCompressionRate(self, data): """ Calculates the compression rate that is just the number of zeros in the signal Parameters ---------- data: array_like input signal from the final step Returns ------- float percentage value of the compression rate """ data = np.asanyarray(data).flatten() noOfZeros = np.count_nonzero(data == 0) if noOfZeros == 0: return noOfZeros return (noOfZeros / len(data)) * 100 def compress(self, data, magnitude)-
Compress the data using the magnitude, make the elements zero which are lower the value Parameters
data:array_like- input signal
magnitude:float- min magnitude to threshold
Returns
array_like- thresholded values
Expand source code
def compress(self, data, magnitude): """ Compress the data using the magnitude, make the elements zero which are lower the value Parameters ---------- data: array_like input signal magnitude: float min magnitude to threshold Returns ------- array_like thresholded values """ self.__magnitude = magnitude con = np.less(data, (self.__magnitude * self.__threshold)) return np.where(con, self.__substitute, data) def getMagnitude(self)-
Returns the magnitude calculated
Returns
float- magnitude calculated
Expand source code
def getMagnitude(self): """ Returns the magnitude calculated Returns ------- float magnitude calculated """ return self.__magnitude def getThreshold(self)-
Returns the threshold
Returns
float- default is 1
Expand source code
def getThreshold(self): """ Returns the threshold Returns ------- float default is 1 """ return self.__threshold