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Sphinx/github docs tweaks to fix broken links #1286

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8 changes: 4 additions & 4 deletions docs/source/CaImAn_Tips.rst
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
CaImAn Tips
===========
General Tips
============

Motion Correction tips
----------------------
Expand Down Expand Up @@ -33,7 +33,7 @@ Motion Correction tips
of chunks (``params.motion.splits_els`` and ``params.motion.split_rig``)
with the length of your recording (e.g. ``int((number of total frames)/200)``).

CaImAn Online Processing tips
Caiman Online Processing tips
-----------------------------

- Important parameters for online processing are the CNN threshold
Expand Down Expand Up @@ -71,7 +71,7 @@ CaImAn Online Processing tips
- When using the CNN for screening candidate components, the usage of a
GPU can lead to significant computational gains.

CaImAn Batch processing tips
Caiman Batch processing tips
----------------------------

- In order to optimize memory consumption and parallelize computing, it
Expand Down
11 changes: 5 additions & 6 deletions docs/source/CaImAn_features_and_references.rst
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@@ -1,7 +1,7 @@
Features
--------
Caiman Features
---------------

CaImAn includes a variety of scalable methods for the analysis of
Caiman includes a variety of scalable methods for the analysis of
calcium (and voltage) imaging data:

|
Expand Down Expand Up @@ -44,7 +44,7 @@ calcium (and voltage) imaging data:

- Uses a Mask R-CNN to identify neurons in the FOV
- Extracts spiking activity using adaptive template matching.
- Fully integrated with CaImAn, inherits all its capabilities.
- Fully integrated with Caiman, inherits all its capabilities.
|
- **Behavioral Analysis** [Behavior]_

Expand All @@ -59,8 +59,7 @@ calcium (and voltage) imaging data:

- Noise parameters estimation under the Poisson-Gaussian noise model
- Fast algorithm that scales to large datasets
- A basic demo can be found at
``CaImAn/demos/notebooks/demo_VST.ipynb``
- A basic demo can be found in the default demos as demo_VST.ipynb



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8 changes: 4 additions & 4 deletions docs/source/GUI.rst
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@@ -1,14 +1,14 @@
Graphical interfaces
====================

The CaImAn GUI
---------------
The Caiman GUI
--------------

.. image:: ../img/GUI_img.png
:width: 600px
:align: center

CaImAn comes with an experimental visual interface. To see an example on
Caiman comes with an experimental visual interface. To see an example on
how use it, first load and run either \* demo_OnACID_mesoscope.py \*
demo_caiman_basic.py \* demo_pipeline.py

Expand Down Expand Up @@ -37,7 +37,7 @@ More features will be added in the future.
External interfaces
-------------------

A couple of very nice visualization tools that directly call CaImAn have been developed recently
A couple of very nice visualization tools that directly call Caiman have been developed recently
by external researchers. For more information please check the following projects:

- `mesmerize-core <https://github.com/nel-lab/mesmerize-core>`_ - also simplifies grid search for parameter tuning
Expand Down
35 changes: 16 additions & 19 deletions docs/source/Getting_Started.rst
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@@ -1,16 +1,15 @@
Getting Started with CaImAn
Getting Started
===========================

Demos
-----

- Notebooks: The notebooks provide a simple and friendly way to get
into CaImAn and understand its main characteristics. They are located
in the ``demos/notebooks``. To launch one of the jupyter notebooks:
into Caiman and understand its main characteristics. They are located
in the ``demos/notebooks``. To launch one of the jupyter notebooks, activate your conda caiman environment, enter the caiman_data directory, and then:

.. code:: bash

source activate CaImAn
jupyter notebook --NotebookApp.iopub_data_rate_limit=1.0e10

and select the notebook from within Jupyter’s browser. The argument
Expand All @@ -21,9 +20,6 @@ Demos
trying demo_pipeline.py first as it contains most of the tasks
required by calcium imaging. For behavior use demo_behavior.py

- If you want to directly launch the python files, your python console
still must be in the CaImAn directory.

Basic Structure
---------------

Expand All @@ -36,13 +32,13 @@ the following objects:
easily and is passed into all the algorithms.
- ``MotionCorrect``: An object for motion correction which can be used
for both rigid and piece-wise rigid motion correction.
- ``cnmf``: An object for running the CaImAn batch algorithm either in
- ``cnmf``: An object for running the Caiman batch algorithm either in
patches or not, suitable for both two-photon (CNMF) and one-photon
(CNMF-E) data.
- ``online_cnmf``: An object for running the CaImAn online (OnACID)
- ``online_cnmf``: An object for running the Caiman online (OnACID)
algorithm on two-photon data with or without motion correction.
- ``estimates``: A single object that stores the results of the
algorithms (CaImAn batch, CaImAn online) in a unified way that also
algorithms (batch, online) in a unified way that also
contains plotting methods.

To see examples of how these methods are used, please consult the demos.
Expand All @@ -51,7 +47,7 @@ To see examples of how these methods are used, please consult the demos.
Parameters
-----------

CaImAn gives you access to a lot of parameters and lets you adapt the analysis to your data. Parameters are stored in
Caiman gives you access to a lot of parameters and lets you adapt the analysis to your data. Parameters are stored in
the ``params`` object in a set of dictionaries, sorted by the part of the analysis they are used in:

- ``data``: General params describing the dataset like dimensions, decay time, filename and framerate
Expand Down Expand Up @@ -123,7 +119,7 @@ As mentioned above, the results of the analysis are stored within the
Result variables for 2p batch analysis
--------------------------------------

The results of CaImAn are saved in an ``estimates`` object. This is
The results of Caiman are saved in an ``estimates`` object. This is
stored inside the cnmf object, i.e. it can be accessed using
``cnmf.estimates``. The variables of interest are:

Expand Down Expand Up @@ -305,19 +301,20 @@ The cluster is set up with Caiman's ``setup_cluster()`` function, which takes in
n_processes=None,
ignore_preexisting=False)

The ``backend`` parameter determines the type of cluster used. The default value, ``'multiprocessing'``, uses the
multiprocessing package, but ``ipyparallel`` is also available. More information on these choices can be
found `here <https://github.com/flatironinstitute/CaImAn/blob/master/docs/CLUSTER.md>`_. You can set the number of
processes (cpu cores) to use with the ``n_processes`` parameter: the default value ``None`` will lead to the function
selecting one *less* than the total number of logical cores available.
The **backend** parameter determines the type of cluster used. The default value, **'multiprocessing'**, uses the
multiprocessing package, but **ipyparallel** is also available. You can set the number of
processes (cpu cores) to use with the **n_processes** parameter: the default value **None** will lead to the function
selecting one *less* than the total number of logical cores available.

More information on these choices can be found :doc:`in the cluster doc <cluster>`.

The parameter ``ignore_preexisting``, which defaults to ``False``, is a failsafe used to avoid overwhelming your resources.
If you try to start another cluster when Caiman already has one running, you will get an error. However, sometimes
on more powerful machines you may want to spin up multiple Caiman environments. In that case,
set ``ignore_preexisting`` to ``True``.

The output variable ``cluster`` is the multicore processing object that will be used in subsequent processing steps. It will
be passed as a parameter in subsequent stages and is the fulcrum for parallelization. The
be passed as a parameter in subsequent stages and sets policy for parallelization. The
other output that can be useful to check is ``n_processes``, as it will tell you how many CPU cores you have set up
in your cluster.

Expand Down Expand Up @@ -347,4 +344,4 @@ will be read/written by column or by row, respectively. This is important becaus
faster on C-order arrays vs F-order arrays. For motion correction, which needs to access contiguous sequences of
frames (often in the middle of the movie), it is much more efficient to read and write in F order. On the other
hand, when it comes to CNMF, you need to access individual pixels across the entire movie, so Caiman saves the
motion-corrected movie in C-order before running CNMF.
motion-corrected movie in C-order before running CNMF.
2 changes: 1 addition & 1 deletion docs/source/Handling_Movies.rst
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Expand Up @@ -2,7 +2,7 @@ Handling movies
================

This page gives a basic intro on the movie object for loading, manipulating,
displaying and saving movies within CaImAn.
displaying and saving movies.

Loading movies
--------------
Expand Down
23 changes: 12 additions & 11 deletions docs/source/Installation.rst
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@@ -1,7 +1,7 @@
Installation and Updating
=========================

This page will give more detailed setup instructions for Caiman than the `main readme <../../README.md>`_.
This page will give more detailed setup instructions for Caiman than the main readme in the source tree.
This is the place you should visit first if you run into problems and need to troubleshoot. It includes
info on initial setup, as well as updating with new releases. There is a Table of Contents on the
left-hand side of this page, so if you need help with a particular task, that should help you get oriented.
Expand Down Expand Up @@ -36,7 +36,7 @@ and make contributions to Caiman.

Section 1A. Install with conda
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
These are basically the Quickstart instructions on the `main readme page <../../README.md>`_, so if you follow those, you
These are basically the Quickstart instructions on the main readme page at the repo: <https://github.com/flatironinstitute/CaImAn>, so if you follow those, you
should be good to go.

.. raw:: html
Expand Down Expand Up @@ -72,8 +72,7 @@ Section 1B. Development-mode install
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Dev mode install allows you to modify the source files of Caiman and makes it easier
to contribute to the project, fix bugs etc. The general motivation for setting up
an editable development environment is described in more detail in our `contributors page <../../CONTRIBUTING.md>`_.
to contribute to the project, fix bugs etc.

If you install in dev mode you will likely need to set some environment variables manually (it is
done automatically when you do the conda install): this is discussed in Section 4C.
Expand Down Expand Up @@ -107,7 +106,7 @@ At the conda prompt:

.. code:: bash

git clone https://github.com/your-username/CaImAn
git clone git@github.com:flatironinstitute/CaImAn.git
cd CaImAn
mamba env create -f environment.yml -n caiman
conda activate caiman
Expand Down Expand Up @@ -140,7 +139,7 @@ Dev Mode Install on MacOS and Linux

.. code:: bash

git clone https://github.com/your-username/CaImAn
git clone git@github.com:flatironinstitute/CaImAn.git
cd CaImAn/
mamba env create -f environment.yml -n caiman
source activate caiman
Expand Down Expand Up @@ -235,7 +234,7 @@ below to update the code. However, if the environment file has changed
since your last update this may lead to you not the latest version. None of this applies
to the conda-forge route (for which instructions are given above).

From the conda environment you used to install CaImAn:
From the conda environment you used to install Caiman:

1. ``pip uninstall caiman``

Expand All @@ -257,7 +256,7 @@ From the conda environment you used to install CaImAn:
variables have changed.

- The same applies if you want to modify some internal function of
CaImAn. If you used the ``pip install -e .`` option then you can
Caiman. If you used the ``pip install -e .`` option then you can
directly modify it (that's why it's the editable developer mode). If you
used the ``pip install .`` option then you will need to
``pip uninstall caiman`` followed by ``pip install .`` for your
Expand All @@ -278,7 +277,7 @@ Section 3C: Upgrade the demos with caimanmanager
<summary>Upgrade the demos</summary>

When you upgrade Caiman, sometimes the underlying APIs change. When this happens and it impacts a demo (or otherwise
requires changes to files in ``caiman_data``), we update the demo and data. This means that upgrading CaImAn works
requires changes to files in ``caiman_data``), we update the demo and data. This means that upgrading Caiman works
best if you also replace the ``caiman_data`` directory with a new version.

To check if the demos or datafiles have changed since your last install, you can run ``caimanmanager check``. If they have not,
Expand Down Expand Up @@ -372,6 +371,8 @@ following the instructions

Section 4D: Other topics
~~~~~~~~~~~~~~~~~~~~~~~~~
See also:

* :doc:`Our clustering doc <cluster>`
* :doc:`Caiman and GPUs <readme-gpu>`

- `Running Caiman on a cluster <./CLUSTER.md>`_
- `Setting up Caiman to use your GPUs <./README-GPU.md>`_
60 changes: 0 additions & 60 deletions docs/source/On_file_types_and_sizes.rst

This file was deleted.

6 changes: 3 additions & 3 deletions docs/source/Overview.rst
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@@ -1,13 +1,13 @@
Overview
=========
========

.. image:: ../LOGOS/Caiman_logo_FI.png
:width: 300px
:align: right

CaImAn is a Python toolbox for large scale **Ca**\ lcium **Im**\ aging data **An**\ alysis and behavioral analysis.
Caiman is a Python toolbox for large scale **Ca**\ lcium **Im**\ aging data **An**\ alysis and behavioral analysis.

CaImAn implements a set of essential methods required in the analysis pipeline of large scale calcium imaging data. Fast and scalable algorithms are implemented for motion correction, source extraction, spike deconvolution, and component registration across multiple days. It is suitable for both two-photon and one-photon fluorescence microscopy data, and can be run in both batch and online modes. CaImAn also contains some routines for the analysis of behavior from video cameras. A list of features as well as relevant references can be found `here
Caiman implements a set of essential methods required in the analysis pipeline of large scale calcium imaging data. Fast and scalable algorithms are implemented for motion correction, source extraction, spike deconvolution, and component registration across multiple days. It is suitable for both two-photon and one-photon fluorescence microscopy data, and can be run in both batch and online modes. It also contains some routines for the analysis of behavior from video cameras. A list of features as well as relevant references can be found `here
<CaImAn_features_and_references.html>`_.

Companion paper
Expand Down
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