# Input Matrix Construction¶

New in version 0.1.

This function creates input matrix from historical values.

## Minimal Working Example¶

An example how to create input matrix from historical values

>>> import numpy as np
>>> a = np.arange(1, 7, 1)
>>> a
array([1, 2, 3, 4, 5, 6])
>>> pa.input_from_history(a,3)
array([[1, 2, 3],
[2, 3, 4],
[3, 4, 5],
[4, 5, 6]])


## Code Explanation¶

padasip.preprocess.input_from_history.input_from_history(a, n, bias=False)[source]

This is function for creation of input matrix.

Args:

• a : series (1 dimensional array)
• n : size of input matrix row (int). It means how many samples of previous history you want to use as the filter input. It also represents the filter length.

Kwargs:

• bias : decides if the bias is used (Boolean). If True, array of all ones is appended as a last column to matrix x. So matrix x has n+1 columns.

Returns:

• x : input matrix (2 dimensional array) constructed from an array a. The length of x is calculated as length of a - n + 1. If the bias is used, then the amount of columns is n if not then amount of columns is n+1).