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00.py
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00.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Oct 11 17:38:15 2019
@author: mifiamigahna
"""
import numpy
import matplotlib.pyplot as pyplot
amount = 1000
middle = [0.5, 0.5]
distances = []
sample = numpy.random.rand(amount, 2)
j = 0
for i in sample:
distances.append(numpy.sqrt(numpy.square(sample[j][0] - 0.5) + numpy.square(sample[j][1] - 0.5)))
j += 1
histData = numpy.histogram(distances)
j = 0
histogramX = []
for i in histData[0]:
histogramX.append((histData[1][j] + histData[1][j + 1]) / 2)
j += 1
pyplot.subplot(131)
pyplot.plot(histogramX, histData[0])
normal = numpy.random.randn(amount)
histDataN = numpy.histogram(normal)
j = 0
histogramNX = []
for i in histDataN[0]:
histogramNX.append((histDataN[1][j] + histDataN[1][j + 1]) / 2)
j += 1
pyplot.subplot(132)
pyplot.plot(histogramNX, histDataN[0])
distances.sort()
normal.sort()
accuracy = 25
j = 1
ascend = []
for i in range(accuracy - 1):
ascend.append(j / accuracy)
j += 1
sampleQ = numpy.quantile(distances, ascend)
normalQ = numpy.quantile(normal, ascend)
pyplot.subplot(133)
pyplot.scatter(normalQ, sampleQ)
pyplot.plot([normalQ[0], normalQ[-1]], [sampleQ[0], sampleQ[-1]])