pulse2percept.utils.array

is_strictly_increasing, sample, unique, radial_mask

Functions

is_strictly_increasing(arr[, tol])
radial_mask(shape[, mask, sd])
sample(sequence[, k])	Randomly selects k elements from a sequence
unique(a[, tol, return_index])	Find the unique elements of a sorted 1D array

pulse2percept.utils.array.sample(sequence, k=1)

Randomly selects k elements from a sequence

New in version 0.8.

Parameters:

• sequence (list, tuple, np.ndarray) – A sequence like a list, a tuple, an array, etc.
• k (int or float, optional) – If an integer, the number of elements to pick If a float between 0 and 1, the fraction of elements to pick

Returns:

sample (list) – List of randomly chosen elements from the sequence

pulse2percept.utils.array.unique(a, tol=1e-06, return_index=False)

Find the unique elements of a sorted 1D array

Special case of numpy.unique (array is flat, sortened) with a tolerance level tol.

New in version 0.7.

Parameters:

• a (array_like) – Input array: must be sorted, and will be flattened if it is not already 1-D.
• tol (float, optional) – If the difference between two elements in the array is smaller than tol, the two elements are considered equal.
• return_index (bool, optional) – If True, also return the indices of a that result in the unique array.

Returns:

• unique (ndarray) – The sorted unique values
• unique_indices (ndarray, optional) – The indices of the first occurrences of the unique values in the original array. Only provided if return_index is True.