Source code for simplestatistics.statistics.linear_regression_line

from .linear_regression import linear_regression

[docs]def linear_regression_line(mb): """ Given the output of ``linear_regression()`` function, or provided with a tuple of ``(m, b)``, where ``m`` is the slope and ``b`` is the intercept, ``inear_regression_line()`` returns a function that calculates y values based on given x values. Args: mb: A list or tuple of [m, b] or (m, b) where m is the slope and b is the y intercept. Returns: A function that accepts ints, floats, lists, or tuples of x values and returns y values. Examples: >>> linear_regression_line(linear_regression([0, 1], [0, 1]))(1) 1.0 >>> linear_regression_line(linear_regression([1,3,5,7,9], [10,11,12,13,14]))([1, 2, 3]) [10.0, 10.5, 11.0] >>> linear_regression_line([.5, 9.5])([1, 2, 3]) [10.0, 10.5, 11.0] >>> linear_regression_line(9.5) Traceback (most recent call last): ... TypeError: linear_regression_line() expects a list or tuple of (slope, intercept) or [slope, intercept] form. >>> linear_regression_line([2, 3, 4]) Traceback (most recent call last): ... ValueError: The list or tuple containing the slope and intercept needs to be of length = 2. """ if type(mb) not in [list, tuple]: raise TypeError('linear_regression_line() expects a list or tuple of (slope, intercept) or [slope, intercept] form.') if len(mb) != 2: raise ValueError('The list or tuple containing the slope and intercept needs to be of length = 2.') m = mb[0] b = mb[1] def line_function(x): # if int or float, return one value if type(x) in [int, float]: return((x * m) + b) # otherwise elif type(x) in [list, tuple]: y_values = [] for ii in x: y_values.append(((ii * m) + b)) return(y_values) return(line_function)