numpy_function#

clipped_cumsum(a: ndarray, xmin=-inf, xmax=inf)[source]#

Compute a cumulative sum along the first axis with clipping.

This function computes the cumulative sum of a along the first axis (rows). After adding each row, intermediate cumulative values are clipped to the interval [xmin, xmax]. The clipping is applied elementwise across columns for 2-D input. The function preserves the input shape:

  • If a is 1-D, it is treated as a single column and the result is a

1-D array of the same shape. - If a is 2-D (shape (n_steps, n_series)), the cumulative sum is computed independently for each column and the result has the same shape as a.

Parameters:

  • a (np.ndarray) – Input array. Expected shape is (n_steps,) or (n_steps, n_series). The cumulative sum is performed along axis 0.

  • xmin (float, optional) – Minimum allowed cumulative value (inclusive). Defaults to -inf.

  • xmax (float, optional) – Maximum allowed cumulative value (inclusive). Defaults to +inf.

Returns:

Array of the same shape as a containing the clipped cumulative sums.

Return type:

np.ndarray

Notes

  • The function uses an internal accumulator initialized to zeros with

length equal to the number of columns (1 for 1-D input). - Clipping is applied elementwise after each accumulation step using np.minimum and np.maximum so values stay within [xmin, xmax].

Examples

>>> import numpy as np
>>> a = np.array([1, 2, -1, 5])
>>> clipped_cumsum(a, xmin=0, xmax=5)
array([1, 3, 2, 5])

>>> b = np.array([[1, 0], [2, 3], [4, -2]])
>>> clipped_cumsum(b, xmin=-1, xmax=4)
array([[ 1,  0],
       [ 3,  3],
       [ 4,  1]])
error_within_boundaries(x: array, low: array, high: array) → array[source]#

Calculate the error of values within specified boundaries.

Parameters:

  • x (np.array) – The array of values.

  • low (np.array) – The lower boundary array.

  • high (np.array) – The upper boundary array.

Returns:

The array of errors.

Return type:

np.array

relative_error_within_boundaries(x: array, low: array, high: array) → array[source]#

Calculate the relative error of values within specified boundaries.

Parameters:

  • x (np.array) – The array of values.

  • low (np.array) – The lower boundary array.

  • high (np.array) – The upper boundary array.

Returns:

The array of relative errors.

Return type:

np.array