Skip to main content
  • Home
  • Development
  • Documentation
  • Donate
  • Operational login
  • Browse the archive

swh logo
SoftwareHeritage
Software
Heritage
Archive
Features
  • Search

  • Downloads

  • Save code now

  • Add forge now

  • Help

Revision e54a8ffb2a30952542234280d443c6dd6e2649d5 authored by TUNA Caglayan on 26 April 2021, 13:54:29 UTC, committed by TUNA Caglayan on 12 May 2021, 12:26:22 UTC
decimal and tensor to vec
1 parent 5412537
  • Files
  • Changes
  • 1633999
  • /
  • examples
  • /
  • plot_tensor.py
Raw File Download
Permalinks

To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.

  • revision
  • directory
  • content
revision badge
swh:1:rev:e54a8ffb2a30952542234280d443c6dd6e2649d5
directory badge Iframe embedding
swh:1:dir:861931d15798d78a4b1354cb873598a68ff024f8
content badge Iframe embedding
swh:1:cnt:e808fb42b5f7eda8fc3bb0484a12dea59dbc94dd
Citations

This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
Select below a type of object currently browsed in order to generate citations for them.

  • revision
  • directory
  • content
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
plot_tensor.py
# -*- coding: utf-8 -*-
"""
Basic tensor operations
=======================

Example on how to use :mod:`tensorly` to perform basic tensor operations.

"""
import numpy as np
import tensorly as tl
from tensorly.testing import assert_array_equal

###########################################################################
# A tensor is simply a numpy array
tensor = tl.tensor(np.arange(24).reshape((3, 4, 2)))
print('* original tensor:\n{}'.format(tensor))

###########################################################################
# Unfolding a tensor is easy
for mode in range(tensor.ndim):
    print('* mode-{} unfolding:\n{}'.format(mode, tl.unfold(tensor, mode)))

###########################################################################
# Re-folding the tensor is as easy:
for mode in range(tensor.ndim):
    unfolding = tl.unfold(tensor, mode)
    folded = tl.fold(unfolding, mode, tensor.shape)
    assert_array_equal(folded, tensor)
The diff you're trying to view is too large. Only the first 1000 changed files have been loaded.
Showing with 0 additions and 0 deletions (0 / 0 diffs computed)
swh spinner

Computing file changes ...

Software Heritage — Copyright (C) 2015–2025, The Software Heritage developers. License: GNU AGPLv3+.
The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Contact— JavaScript license information— Web API

back to top