The library with a most popular tools for Digital Signal Analysis (DSA). 

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dsatools

The library with a most popular tools for Digital Signal Analysis (DSA)

mvRonkin

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Bidirectional unicode control characters

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Bin script confusion

This Chrome extension includes content scripts that execute JavaScript on specified websites.

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Chrome: Content Script

This Chrome extension requests host permissions to access specific websites or domains.

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Chrome: Host Permission

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Chrome: Permission

This Chrome extension requests wildcard host permissions that grant broad access to websites.

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Chrome: Wildcard Host Permission

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Chronological version anomaly

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Compromised SSH key

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Copyleft License

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Title

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High CVE

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Deprecated

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Native code

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High entropy strings

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Unicode homoglyphs

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HTTP dependency

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Install scripts

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Invalid manifest file

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Invisible chars

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License change

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Long strings

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Major refactor

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Manifest confusion

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Medium CVE

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Low CVE

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Minified code

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Mixed license

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Modified license exception

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What is a modified license?

Modified license

What is network access?

Network access

A new npm collaborator published a version of the package for the first time. New collaborators are usually benign additions to a project, but do indicate a change to the security surface area of a package.

		Metadata-Version: 1.1
		Name: dsatools
		Version: 0.1.77
		Version: 0.1.78
		Summary: The library with a most popular tools for Digital Signal Analysis (DSA)
		@@ -5,0 +5,0 @@ Home-page: https://github.com/MVRonkin/dsatools

		@@ -19,3 +19,3 @@
		from ._hht import hht
		from ._smoothing import moving_average, movav
		from ._instant_parameters import instant_parameters
		#from ._smoothing import moving_average, movav

		@@ -0,1 +1,2 @@
		'''
		import numpy as np
		@@ -10,3 +11,3 @@
		def moving_average(vector,av_cof, mode='postw'):
		'''

		Simple Moving Average or Weighted Moving Average
		@@ -36,3 +37,3 @@
		* smoothed array: 1d ndarray.
		'''

		av_cof = np.asarray(av_cof,dtype=int)
		@@ -50,3 +51,3 @@
		def movav(vector,window_size,straight = True):
		'''

		Alternative Moving Average Implementation.
		@@ -66,3 +67,3 @@
		smoothed vector: 1d ndarray.
		'''

		vector = np.asarray(vector)
		@@ -69,0 +70,0 @@ N = vector.shape[0]

		@@ -38,3 +38,3 @@ from ._awgn import (awgn,

		from ._smooth import movingaverage, movav
		from ._smooth import moving_average, movav
		from ..operators import *

		import numpy as np
		from .. import operators

		__all__=['movingaverage','movav']
		__all__=['moving_average','movav']

		#------------------------------------------
		def movingaverage(vector,av_cof, mode='same'):
		def moving_average(vector,av_cof, mode='same'):
		'''
		@@ -9,0 +9,0 @@ Simple Moving Average or Weighted Moving Average

dsatools - pypi Package Compare versions

Worsened metrics

		@@ -10,3 +10,3 @@
		packages=find_packages(),
		version="0.1.77",
		version="0.1.78",
		description=""" The library with a most popular tools for Digital Signal Analysis (DSA) """,
		@@ -13,0 +13,0 @@ long_description=readme,