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https://github.com/simonsobs/psplay

Interactive power spectrum code
https://github.com/simonsobs/psplay

cmb jupyterlab-extension leaflet

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Interactive power spectrum code

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.. raw:: html

A tool to visualize and play with CMB maps. ``psplay`` is a ``jupyter`` extension to allow
interactive visualization of CMB maps through `Leaflet `_ library. ``psplay`` also
provides a set of tools based on `pspy `_ to compute and to show
CMB power spectra. You can have a better idea of what ``psplay`` can do by watching this short
`video `_.

All the specific javascript library developed for ``psplay`` is done by `Sigurd Naess
`_. The build process and javascript architecture is highly inspired by
`ipyleaflet `_ project.

.. image:: https://img.shields.io/pypi/v/psplay.svg?style=flat
:target: https://pypi.python.org/pypi/psplay/
.. image:: https://img.shields.io/npm/v/jupyter-leaflet-car
:target: https://www.npmjs.com/package/jupyter-leaflet-car
.. image:: https://img.shields.io/github/actions/workflow/status/simonsobs/psplay/main.yml
:target: https://github.com/simonsobs/psplay/actions

Examples
--------

* `From simulated CAR map to psplay `_
* `From HEALPIX map file to psplay `_

Installation
------------

To install, you will need to have or to install ``numpy``. Then, run

.. code:: shell

$ pip install psplay [--user]

``psplay`` runs within a Jupyter notebook and we recommend to use JupyterLab to fully enjoy ``psplay``

To enable the extension within Jupyter, you will need to install several JupyterLab extensions
especially the Python ``plotly`` `library `_ and the Jupyter `widgets
`_. You will also need `nodejs library
`_ and its package manager ``npm``. For JupyterLab > 2.0.0, you can do

.. code:: shell

$ jupyter labextension install plotlywidget jupyterlab-plotly
$ jupyter labextension install @jupyter-widgets/jupyterlab-manager @jupyter-widgets/jupyterlab-sidecar

Finally, you need to install the `jupyter-leaflet-car `_ extension

.. code:: shell

$ jupyter labextension install jupyter-leaflet jupyter-leaflet-car

Using ``docker``
----------------

Given the number of requirements, you can use a ``docker`` image already made with the needed
libraries and everything compiled and installed. You should first install `docker
`_ for your operating system.

Then, you can run the ``simonsobs/psplay`` image by doing

..
$ docker run --rm -p 8888:8888 ghcr.io/simonsobs/psplay:master

.. code:: shell

$ docker run --rm -p 8888:8888 simonsobs/psplay:latest

After pulling the ``docker`` image, a JupyterLab instance should start. If your web browser does not
automatically load the web page, you can copy-paste the JupyterLab URL.

You can bind a local directory to make it available within the ``docker`` container with the ``-v``
flag (see https://docs.docker.com/storage/bind-mounts for more details).

..
Using at ``NERSC``
------------------

On NERSC machines, you can install ``psplay`` within a ``conda`` environment but you can also use a
common installation for Simons Observatory people (*i.e.* people belonging to ``sobs`` group)
without need to redo the long installation process.

First you need to log to ``cori.nersc.gov`` machines by enabling port forward to your local machine

.. code:: shell

$ ssh -L 8888:localhost:8888 [email protected]

Everything passing *via* port 8888 in ``NERSC`` will be forwarded to your local machine and you will
be able to grab the JupyterLab instance within your local web browser.

Given a successful connection, you must load the latest ``python`` module

.. code:: shell

$ module load python

and then you can load the ``conda`` environment with the whole software suite for ``psplay``

.. code:: shell

$ source activate /global/cscratch1/sd/xgarrido/psplay/env

Finally, you can copy the ``/global/cscratch1/sd/xgarrido/psplay/examples/minimal`` directory to
your home or scratch directory. For example purpose, this directory holds simulation files already
converted into ``Leaflet`` tiles. Then, fire a JupyterLab instance by typing

.. code:: shell

$ cd /your/owned/directory
$ cp -r /global/cscratch1/sd/xgarrido/psplay/examples/minimal .
$ jupyter lab --port 8888 --no-browser minimal_working_example.ipynb

Copy-paste the URL into your local browser and run the Jupyter notebook.

If port 8888 is already in use, JupyterLab will try another one and then breaks the port forward. In
this case you should restart the ssh session with another port.

Installation from sources
-------------------------

For a development installation (requires `npm `_)

.. code:: shell

$ git clone https://github.com/xgarrido/psplay.git
$ cd psplay
$ pip install -e .

If you are using the classic Jupyter Notebook you need to install the nbextension:

.. code:: shell

$ jupyter nbextension install --py --symlink --sys-prefix psplay
$ jupyter nbextension enable --py --sys-prefix psplay

If you are using JupyterLab, you need to install the labextension:

.. code:: shell

$ jupyter labextension install @jupyter-widgets/jupyterlab-manager js

Note for developers:

- the ``-e`` pip option allows one to modify the Python code in-place. Restart the kernel in order
to see the changes.
- the ``--symlink`` argument on Linux or OS X allows one to modify the JavaScript code
in-place. This feature is not available with Windows.

For automatically building the JavaScript code every time there is a change, run the following
command from the ``psplay/js/`` directory:

.. code:: shell

$ npm run watch

If you are on JupyterLab you also need to run the following in a separate terminal:

.. code:: shell

$ jupyter lab --watch

Every time a JavaScript build has terminated you need to refresh the Notebook page in order to load
the JavaScript code again.

Authors
-------

* Xavier Garrido
* Thibaut Louis
* Sigurd Naess

The code is part of `PSpipe `_ the Simons Observatory power spectrum pipeline.