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# Import C# CLR interface and system
import clr, sys

# Add C# Library Paths and add references via CLR module
sys.path.append('C:\\Program Files (x86)\\Accord.NET\\Framework\\Release\\net40')
sys.path.append('C:\\Program Files (x86)\\AForge.NET\\Framework\\Release')
clr.AddReference('System.Core')
clr.AddReference('AForge.Math')
clr.AddReference('Accord.Statistics')
clr.AddReference('System.Linq')

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"""
Initiating a 9000x9000 triangular matrix and applying XOR across all elements
"""

""" Using ufunc without at()  """
%%timeit
a = np.tri(9000,dtype=int)
a = np.bitwise_xor(a,1)
# 1 loops, best of 3: 373 ms per loop

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""" 
Test how to composite matrices with 'where' 
Test generator builds random incrementing matrices
The compositor takes output from this generator and performs the compositing.
Display an image map of the matrices
"""

import numpy as np
from matplotlib import pyplot as pl

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 def elim(row, minus_row, scale, n=3):
    m = np.eye(n)
    m[row, minus_row] = -scale
    return m

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def scramble2Decrypt(cipherText):
    halfLength = len(cipherText) // 2
    oddChars = cipherText[:halfLength]
    evenChars = cipherText[halfLength:]
    plainText = ""
    for i in range(halfLength):
        plainText = plainText + evenChars[i]
        plainText = plainText + oddChars[i]
    if len(oddChars) < len(evenChars):
        plainText = plainText + evenChars[-1]

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# Initialize two signals with arbitrary length
n, m = 5, 7
convolution_length = n+m-1

u = np.random.randint(0, 255, n)
v = np.random.randint(0, 255, m)


# Convolve the two signals
cv = sp.signal.convolve(u, v)

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import base64

# Create a string and encode to bytes
s  = 'Convert me to base64!'
sb = s.encode('utf-8')

# Take bytes and encode to base64 string
sb64 = base64.b64encode(sb).decode()
# Q29udmVydCBtZSB0byBiYXNlNjQh

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Project Name

A one or two line description.

Features

Enables you to do...

Project Contents

Setup

Requirements

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import numpy as np
A = np.eye(20)
A @ A               # `@` is the matrix multiplication operator

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Overfitting happens in education; it's called specialization.