mirror of https://github.com/pyodide/pyodide.git
20 lines
635 B
Python
20 lines
635 B
Python
# setup: import numpy as np ; N = 500000 ; X, Y = np.random.rand(N), np.random.rand(N) # noqa
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# run: lstsqr(X, Y)
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# from:
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# http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day10_fortran_lstsqr.ipynb
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# pythran export lstsqr(float[], float[])
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import numpy as np
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def lstsqr(x, y):
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""" Computes the least-squares solution to a linear matrix equation. """
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x_avg = np.average(x)
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y_avg = np.average(y)
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dx = x - x_avg
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var_x = np.sum(dx ** 2)
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cov_xy = np.sum(dx * (y - y_avg))
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slope = cov_xy / var_x
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y_interc = y_avg - slope * x_avg
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return (slope, y_interc)
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