fix(types): removing implicit generics. <!-- Thank you for contributing to Pyodide! All improvements are welcome,
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### Description

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# setup: import numpy as np ; N = 500000 ; X, Y = np.random.rand(N), np.random.rand(N)
# run: lstsqr(X, Y)
# from:
# http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day10_fortran_lstsqr.ipynb

# pythran export lstsqr(float[], float[])
import numpy as np


def lstsqr(x, y):
    """Computes the least-squares solution to a linear matrix equation."""
    x_avg = np.average(x)
    y_avg = np.average(y)
    dx = x - x_avg
    var_x = np.sum(dx**2)
    cov_xy = np.sum(dx * (y - y_avg))
    slope = cov_xy / var_x
    y_interc = y_avg - slope * x_avg
    return (slope, y_interc)

# setup: import numpy as np ; N = 500000 ; X, Y = np.random.rand(N), np.random.rand(N)
# run: lstsqr(X, Y)
# from:
# http://nbviewer.ipython.org/github/rasbt/One-Python-benchmark-per-day/blob/master/ipython_nbs/day10_fortran_lstsqr.ipynb

# pythran export lstsqr(float[], float[])
import numpy as np


def lstsqr(x, y):
    """Computes the least-squares solution to a linear matrix equation."""
    x_avg = np.average(x)
    y_avg = np.average(y)
    dx = x - x_avg
    var_x = np.sum(dx**2)
    cov_xy = np.sum(dx * (y - y_avg))
    slope = cov_xy / var_x
    y_interc = y_avg - slope * x_avg
    return (slope, y_interc)
