python做频率统计图 完整版

1
2from matplotlib import pyplot as plt
3
4import pandas as pd
5
6def linearCongruentialMethod(Xo, m, a, c, randomNums, U):
7
8    randomNums[0] = Xo
9
10    U[0] = randomNums[0] / m
11
12    for i in range(1, 10000):
13
14        # Follow the linear congruential method
15
16        randomNums[i] = ((randomNums[i - 1] * a) + c) % m
17
18        U[i] = randomNums[i] / m
19
20print("a = 1597, b = 0, m = 244944")
21
22a = 1597
23
24c = 0
25
26m = 244944
27
28i = 0.01
29
30for i in range(1, 6):
31
32    X0 = i * 0.01
33
34    print("\n X0 = ", X0, "\n")
35
36    noOfRandomNums = 10005
37
38    randomNums = [0] * (noOfRandomNums)
39
40    U = [0] * (noOfRandomNums)
41
42    linearCongruentialMethod(X0, m, a, c, randomNums, U)
43
44    intervals = 20
45
46    freq = [0] * (intervals)
47
48    for j in U:
49
50        x = 1
51
52        x = j * 100 / 5
53
54        freq[int(x)] = freq[int(x)] + 1
55
56    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)',
57
58                             '[0.30,0.35)', '[0.35,0.40)', '[0.40,0.45)', '[0.45,0.50)', '[0.50,0.55)', '[0.55,0.60)',
59
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)',
61
62                             '[0.90,0.95)', '[0.95,1.00)'],
63
64              'Freuency': freq}
65
66    df = pd.DataFrame(mydata)
67
68    print(df)
69
70    data = {'1': freq[0], '2': freq[1], '3': freq[2], '4': freq[3], '5': freq[4], '6': freq[5], '7': freq[6],
71
72            '8': freq[7], '9': freq[8], '10': freq[9], '11': freq[10], '12': freq[11], '13': freq[12], '14': freq[13],
73
74            '15': freq[14], '16': freq[15], '17': freq[16], '18': freq[17], '19': freq[18], '20': freq[19], }
75
76    interval = list(data.keys())
77
78    frequency = list(data.values())
79
80    fig = plt.figure(figsize=(10, 5))
81
82    plt.bar(interval, frequency, color='maroon', width=0.4)
83
84    plt.show()
85
86print("\na = 51749, b = 0, m = 244944")
87
88a = 51749
89
90c = 0
91
92m = 244944
93
94i = 0.01
95
96for i in range(1, 6):
97
98    X0 = i * 0.01
99
100    print("\n X0 = ", X0, "\n")
101
102    noOfRandomNums = 10005
103
104    randomNums = [0] * (noOfRandomNums)
105
106    U = [0] * (noOfRandomNums)
107
108    linearCongruentialMethod(X0, m, a, c, randomNums, U)
109
110    intervals = 20
111
112    freq = [0] * (intervals)
113
114    for j in U:
115
116        x = 1
117
118        x = j * 100 / 5
119
120        freq[int(x)] = freq[int(x)] + 1
121
122    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)',
123
124                             '[0.30,0.35)', '[0.35,0.40)', '[0.40,0.45)', '[0.45,0.50)', '[0.50,0.55)', '[0.55,0.60)',
125
126                             '[0.60,0.65)', '[0.65,0.70)', '[0.70,0.75)', '[0.75,0.80)', '[0.80,0.85)', '[0.85,0.90)',
127
128                             '[0.90,0.95)', '[0.95,1.00)'],
129
130              'Freuency': freq}
131
132    df = pd.DataFrame(mydata)
133
134    print(df)
135
136    data = {'1': freq[0], '2': freq[1], '3': freq[2], '4': freq[3], '5': freq[4], '6': freq[5], '7': freq[6],
137
138            '8': freq[7], '9': freq[8], '10': freq[9], '11': freq[10], '12': freq[11], '13': freq[12], '14': freq[13],
139
140            '15': freq[14], '16': freq[15], '17': freq[16], '18': freq[17], '19': freq[18], '20': freq[19], }
141
142    interval = list(data.keys())
143
144    frequency = list(data.values())
145
146    fig = plt.figure(figsize=(10, 5))
147
148    plt.bar(interval, frequency, color='blue', width=0.4)
149
150    plt.show()

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