26 lines
798 B
Python
26 lines
798 B
Python
#!/usr/bin/env python
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# From https://www.geeksforgeeks.org/python/how-to-plot-a-normal-distribution-with-matplotlib-in-python/
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import numpy as np
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import matplotlib.pyplot as plt
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from scipy.stats import norm
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data = np.array([1, 1.1, 0.9, 1, 1, 0.9, 0.9])
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lowerbound = 0.9
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upperbound = 1.0
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mean = data.mean()
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stddev = data.std()
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x = np.linspace(mean-3*stddev, mean+3*stddev, 1000)
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y = norm.pdf(x, mean, stddev)
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plt.plot(x, y, 'b-', label='Normal Distribution')
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coloredregion = (x >= lowerbound) & ( x <= upperbound ) #select x values
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plt.vlines([lowerbound, upperbound], 0, plt.ylim()[1])#ylim returns [bot, top]
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plt.fill_between(x, 0, y, where=coloredregion, color="grey", alpha=0.5, label="Design Range")
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plt.xlabel('X')
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plt.ylabel('Probability Density')
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plt.legend()
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plt.grid(True)
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plt.show()
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