关于python:python做频率统计图-完整版

from matplotlib import pyplot as plt

import pandas as pd

def linearCongruentialMethod(Xo, m, a, c, randomNums, U):

randomNums[0] = Xo

U[0] = randomNums[0] / m

for i in range(1, 10000):

    # Follow the linear congruential method

    randomNums[i] = ((randomNums[i - 1] * a) + c) % m

    U[i] = randomNums[i] / m

print(“a = 1597, b = 0, m = 244944”)

a = 1597

c = 0

m = 244944

i = 0.01

for i in range(1, 6):

X0 = i * 0.01

print("\n X0 =", X0, "\n")

noOfRandomNums = 10005

randomNums = [0] * (noOfRandomNums)

U = [0] * (noOfRandomNums)

linearCongruentialMethod(X0, m, a, c, randomNums, U)

intervals = 20

freq = [0] * (intervals)

for j in U:

    x = 1

    x = j * 100 / 5

    freq[int(x)] = freq[int(x)] + 1

mydata = {'Interval': ['[0.00,0.05)', '[0.05,0.10)', '[0.10,0.15)', '[0.15,0.20)', '[0.20,0.25)', '[0.25,0.30)',

                         '[0.30,0.35)', '[0.35,0.40)', '[0.40,0.45)', '[0.45,0.50)', '[0.50,0.55)', '[0.55,0.60)',

                         '[0.60,0.65)', '[0.65,0.70)', '[0.70,0.75)', '[0.75,0.80)', '[0.80,0.85)', '[0.85,0.90)',

                         '[0.90,0.95)', '[0.95,1.00)'],

          'Freuency': freq}

df = pd.DataFrame(mydata)

print(df)

data = {'1': freq[0], '2': freq[1], '3': freq[2], '4': freq[3], '5': freq[4], '6': freq[5], '7': freq[6],

        '8': freq[7], '9': freq[8], '10': freq[9], '11': freq[10], '12': freq[11], '13': freq[12], '14': freq[13],

        '15': freq[14], '16': freq[15], '17': freq[16], '18': freq[17], '19': freq[18], '20': freq[19], }

interval = list(data.keys())

frequency = list(data.values())

fig = plt.figure(figsize=(10, 5))

plt.bar(interval, frequency, color='maroon', width=0.4)

plt.show()

print(“\na = 51749, b = 0, m = 244944”)

a = 51749

c = 0

m = 244944

i = 0.01

for i in range(1, 6):

X0 = i * 0.01

print("\n X0 =", X0, "\n")

noOfRandomNums = 10005

randomNums = [0] * (noOfRandomNums)

U = [0] * (noOfRandomNums)

linearCongruentialMethod(X0, m, a, c, randomNums, U)

intervals = 20

freq = [0] * (intervals)

for j in U:

    x = 1

    x = j * 100 / 5

    freq[int(x)] = freq[int(x)] + 1

mydata = {'Interval': ['[0.00,0.05)', '[0.05,0.10)', '[0.10,0.15)', '[0.15,0.20)', '[0.20,0.25)', '[0.25,0.30)',

                         '[0.30,0.35)', '[0.35,0.40)', '[0.40,0.45)', '[0.45,0.50)', '[0.50,0.55)', '[0.55,0.60)',

                         '[0.60,0.65)', '[0.65,0.70)', '[0.70,0.75)', '[0.75,0.80)', '[0.80,0.85)', '[0.85,0.90)',

                         '[0.90,0.95)', '[0.95,1.00)'],

          'Freuency': freq}

df = pd.DataFrame(mydata)

print(df)

data = {'1': freq[0], '2': freq[1], '3': freq[2], '4': freq[3], '5': freq[4], '6': freq[5], '7': freq[6],

        '8': freq[7], '9': freq[8], '10': freq[9], '11': freq[10], '12': freq[11], '13': freq[12], '14': freq[13],

        '15': freq[14], '16': freq[15], '17': freq[16], '18': freq[17], '19': freq[18], '20': freq[19], }

interval = list(data.keys())

frequency = list(data.values())

fig = plt.figure(figsize=(10, 5))

plt.bar(interval, frequency, color='blue', width=0.4)

plt.show()

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