72 lines
1.6 KiB
Python
72 lines
1.6 KiB
Python
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"""
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Komputerowa analiza danych
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Zadanie 2
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Michał Leśniak 195642
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"""
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from statistics import mean
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def var(lst):
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x_mean = mean(lst)
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return sum((x-x_mean)**2 for x in lst)/len(lst)
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def cov(lst_x, lst_y):
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assert len(lst_x) == len(lst_y)
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x_mean = mean(lst_x)
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y_mean = mean(lst_y)
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return sum((lst_x[i]-x_mean)*(lst_y[i]-y_mean) for i in range(len(lst_x)))/len(lst_x)
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def load_data(*args):
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ret = ()
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for arg in args:
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with open(arg, 'r') as f:
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lines = f.read().splitlines()
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lst = []
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for line in lines:
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lst.append(tuple([float(x.strip()) for x in line.split(',')]))
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ret += lst,
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return ret
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def model1(data):
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lst_x = [x for x, _ in data]
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lst_y = [y for _, y in data]
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a = cov(lst_x, lst_y)/var(lst_x)
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print(f'f(X) = {a} * X')
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def model2(data):
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lst_x = [x for x, _ in data]
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lst_y = [y for _, y in data]
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a = cov(lst_x, lst_y)/var(lst_x)
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b = mean(lst_y) - a*mean(lst_x)
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print(f'f(X) = {a} * X + {b}')
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def main():
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data1, data2, data3, data4 = load_data(
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'data1.csv', 'data2.csv', 'data3.csv', 'data4.csv')
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print(var([x for x, _ in data1]))
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print(cov([x for x, _ in data1], [y for _, y in data1]))
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# print(data2)
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# print(data3)
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# print(data4)
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model1(data1)
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model1(data2)
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model2(data1)
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model2(data2)
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x_mean = mean([x for x, _ in data1])
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y_mean = mean([y for _, y in data1])
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xy = sum([x*y for x, y in data1])
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x_2 = sum([x**2 for x, _ in data1])
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print(sum([2*x-2*x*y for x,y in data1])/len(data1))
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print(xy/x_2)
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if __name__ == '__main__':
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main()
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