Indexing

Like NumPy, Aesara distinguishes between basic and advanced indexing. Aesara fully supports basic indexing (see NumPy’s indexing) and integer advanced indexing.

Index-assignment is not supported. If you want to do something like a[5] = b or a[5]+=b, see aesara.tensor.subtensor.set_subtensor() and aesara.tensor.subtensor.inc_subtensor() below.

Generating index tensors

where	if cond then ift else iff Generalizes a scalar Op to tensors.
ogrid	Create a dense n-dimensional 'meshgrid' with equally spaced points.
ravel_multi_index(multi_index, dims[, mode, ...])	Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.
unravel_index(indices, dims[, order])	Converts a flat index or array of flat indices into a tuple of coordinate arrays.
tril_indices_from(a[, k])	Return the indices for the lower-triangle of arr.
tril_indices(n[, k, m])	Return the indices for the lower-triangle of an (n, m) array.
triu_indices(n[, k, m])	Return the indices for the upper-triangle of an (n, m) array.
triu_indices_from(a[, k])	Return the indices for the upper-triangle of arr.

Indexing-like operations

take(a, indices[, axis, mode])	Take elements from an array along an axis.
take_along_axis(arr, indices[, axis])	Take values from the input array by matching 1d index and data slices.
choose(a, choices[, mode])	Construct an array from an index array and a set of arrays to choose from.
compress(condition, x[, axis])	Return selected slices of an array along given axis.
diag(v[, k])	A helper function for two ops: ExtractDiag and AllocDiag.
diagonal(a[, offset, axis1, axis2])	A helper function for ExtractDiag.

Inserting data into tensors

set_subtensor(x, y[, inplace, ...])	Return x with the given subtensor overwritten by y.
inc_subtensor(x, y[, inplace, ...])	Update the value of an indexed array by a given amount.