scatseisnet.operation#

Miscellaneous operations for scatseisnet.

This module contains miscellaneous operations for scatseisnet, such as segmentation and pooling.

Terms of use
Copyright (C) 2021 Léonard Seydoux.

This program is free software: you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation, either version 3 of the License, or (at your
option) any later version.

This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
General Public License for more details.

You should have received a copy of the GNU General Public License along
with this program.  If not, see <https://www.gnu.org/licenses/>.

Functions#

segment(→ Generator[numpy.ndarray, None, None])

Segment array into overlapping windows.

segmentize(→ numpy.ndarray)

Segment array into overlapping windows.

pool(→ numpy.ndarray)

Pooling operation performed on the last axis.

Module Contents#

scatseisnet.operation.segment(x: numpy.ndarray, window_size: int, stride: int | None = None) → Generator[numpy.ndarray, None, None][source]#

Segment array into overlapping windows.

Parameters:

  • x (numpy.ndarray) – Array to segment.

  • window_size (int) – Sliding window size in numpy of points

  • stride (int, optional) – Sliding window stride in numpy of points. If None, stride is equal to window_size.

Yields:

The elements of the segmented array.

scatseisnet.operation.segmentize(x: numpy.ndarray, window_size: int, stride: int | None = None) → numpy.ndarray[source]#

Segment array into overlapping windows.

Parameters:

  • x (numpy.ndarray) – Array to segment.

  • window_size (int) – Sliding window size in numpy of points

  • stride (int, optional) – Sliding window stride in numpy of points. If None, stride is equal to window_size.

Return type:

The segmented array with shape (n_windows, n_channels, n_times).

scatseisnet.operation.pool(x: numpy.ndarray, reduce_type: Callable | None = None) → numpy.ndarray[source]#

Pooling operation performed on the last axis.

Parameters:

  • x (numpy.ndarray) – The input data to pool.

  • reduce_type (callable, optional) – The reducing operation (e.g. numpy.mean()). If None, no operation is performed.

Returns:

pooled – The data pooled with same shape of input data minus last dimension.

Return type:

numpy.ndarray