Source code for padasip.preprocess.standardize_back
"""
.. versionadded:: 0.1
This function transforms series to the original score according to
equation:
:math:`\\textbf{x} = \\textbf{x}_s \cdot b + a`
where :math:`\\textbf{x}` is time series to de-standardize,
:math:`a` is offset to add and :math:`b` desired scaling factor.
.. contents::
:local:
:depth: 1
See also: :ref:`preprocess-standardize`
Usage Explanation
********************
As simple as
.. code-block:: python
x = pa.standardize(xs, offset=a, scale=b)
Code Explanation
*****************
"""
from __future__ import division
import numpy as np
[docs]def standardize_back(xs, offset, scale):
"""
This is function for de-standarization of input series.
**Args:**
* `xs` : standardized input (1 dimensional array)
* `offset` : offset to add (float).
* `scale` : scale (float).
**Returns:**
* `x` : original (destandardised) series
"""
try:
offset = float(offset)
except:
raise ValueError('The argument offset is not None or float.')
try:
scale = float(scale)
except:
raise ValueError('The argument scale is not None or float.')
try:
xs = np.array(xs, dtype="float64")
except:
raise ValueError('The argument xs is not numpy array or similar.')
return xs*scale + offset