"""
simple_linear.py             2.1, 2018-10-10

Copyright (c) 2018, Nicholas Bennett (nick@nickbenn.com).
All rights reserved. Usage is subject to license terms as stated in license.txt.

Usage: from simple_linear import SimpleLinear
       model = SimpleLinear(data_file, delimiter, skip)
       model.regress()

When regress() is called, regression properties are assigned values from linear
least squares computations, using SciPy.

"""

from scipy.stats import linregress


__author__="Nicholas Bennett"
__date__ ="$Oct 10, 2018$"


class SimpleLinear(object):
    """The SimpleLinear class implements a simple linear regression model,
    including computation of slope, intercept, and coefficient of
    determination."""

    def __init__(self, x, y):
        """Creates a new SimpleLinear, taking data from observations."""
        self._n = len(x)
        self._x = tuple(x)
        self._y = tuple(y)
        self._intercept = 0
        self._slope = 0
        self._r2 = -1

    def regress(self):
        """Perform least squares regression on data."""
        self._slope, self._intercept, r, p, std_err = linregress(self._x, self._y)
        self._r2 = r * r
        fitted = [self._intercept + self._slope * x for x in self._x]

    @property
    def n(self):
        """Number of data points."""
        return self._n

    @property
    def x(self):
        """List of x values."""
        return self._x

    @property
    def y(self):
        """List of actual y values."""
        return self._y

    @property
    def intercept(self):
        """Intercept of regression equation."""
        return self._intercept

    @property
    def slope(self):
        """Slope of regression equation."""
        return self._slope

    @property
    def r2(self):
        """Coefficient of determination."""
        return self._r2