Skip to content

Commit

Permalink
Merge pull request #3282 from ericpre/remove_beta_lazy
Browse files Browse the repository at this point in the history
Remove beta warning lazy signal
  • Loading branch information
ericpre committed Dec 19, 2023
2 parents ecaccf0 + e848200 commit 02e7e6a
Show file tree
Hide file tree
Showing 2 changed files with 12 additions and 10 deletions.
21 changes: 11 additions & 10 deletions doc/user_guide/big_data.rst
Expand Up @@ -3,16 +3,6 @@
Working with big data
*********************

.. warning:: All the features described in this chapter are in beta state.

Although most of them work as described, their operation may not always
be optimal, well-documented and/or consistent with their in-memory counterparts.

Therefore, although efforts will be taken to minimise major disruptions,
the syntax and features described here may change in patch and minor
HyperSpy releases. If you experience issues with HyperSpy's lazy features
please report them to the developers.

.. versionadded:: 1.2

HyperSpy makes it possible to analyse data larger than the available memory by
Expand Down Expand Up @@ -141,6 +131,11 @@ operations are only performed lazily, use the
Machine learning
----------------

.. warning:: The machine learning features are in beta state.

Although most of them work as described, their operation may not always
be optimal, well-documented and/or consistent with their in-memory counterparts.

:ref:`mva.decomposition` algorithms for machine learning often perform
large matrix manipulations, requiring significantly more memory than the data size.
To perform decomposition operation lazily, HyperSpy provides access to several "online"
Expand Down Expand Up @@ -542,6 +537,12 @@ Dask has two schedulers available for single machines.
Distributed Scheduler
^^^^^^^^^^^^^^^^^^^^^
.. warning:: Distributed computing is not supported for all file formats.
Distributed computing is limited to a few file formats, see the list of
:external+rsciio:ref:`supported file format <supported-formats>` in
RosettaSciIO documentation.
The recommended way to use dask is with the distributed scheduler. This allows you to scale your computations
to a cluster of machines. The distributed scheduler can be used on a single machine as well. ``dask-distributed``
also gives you access to the dask dashboard which allows you to monitor your computations.
Expand Down
1 change: 1 addition & 0 deletions upcoming_changes/3282.doc.rst
@@ -0,0 +1 @@
Update warning of "beta" state in big data section to be more specific.

0 comments on commit 02e7e6a

Please sign in to comment.