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51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
#
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# Copyright (c) 2023 Maxim Slipenko, Euegene Lazurenko.
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#
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# This file is part of Statapp
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# (see https://github.com/shizand/statapp).
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.#
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import numpy as np
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import pandas as pd
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DIRECT_LINK = 0
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INDIRECT_LINK = 1
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def generate_x_values(mean, std, typeConnection, y):
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yMean = np.mean(y)
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values = []
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for cur_y in y:
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raz = np.abs(mean - np.random.normal(mean, std))
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if typeConnection == INDIRECT_LINK:
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raz *= -1
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if cur_y > yMean:
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x = mean + raz
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elif cur_y < yMean:
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x = mean - raz
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else:
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x = mean
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values.append(x)
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return np.array(values)
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def variance_analysis(data):
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return np.array([
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[np.mean(col), np.std(col), np.min(col), np.max(col)] for col in data.T
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])
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def correlation_analysis(data):
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return pd.DataFrame(data).corr().to_numpy()
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