Python-only healpy

Stripped down hacked version of healpy with only map-loading and plotting capabilities.

Install the package with:

    pip install .

Test that it can visualize a map:

    python test_healpyvis.py

Check it creates map.png file.

Building PyHealpy with JupyterLite's Pyodide

by @VeerioSDSC

Steps include building the wheel to serve, setting up JupyterLite, and commands for the Lite cells.

Building the PyHealpy Wheel to Serve

First need to set up the pyodide compiler with the following

pip install pyodide-build
git clone https://github.com/emscripten-core/emsdk.git
cd emsdk
PYODIDE_EMSCRIPTEN_VERSION=$(pyodide config get emscripten_version)
./emsdk install ${PYODIDE_EMSCRIPTEN_VERSION}
./emsdk activate ${PYODIDE_EMSCRIPTEN_VERSION}
source emsdk_env.sh
cd ..

Then building the wheel:

git clone https://github.com/healpy/pyhealpy.git
cd pyhealpy
pyodide build

It builds the wheel in a dist folder

Serving the wheel locally:

python3 -m http.server --directory dist

Using it with JupyterLite

If one just wants to use another environment they can use the demo one found here: https://jupyterlite.github.io/demo/lab/index.html

If one wants to deploy Lite with GitHub Pages:

Template to use: https://github.com/jupyterlite/demo Since the initial commit will fail, go to settings→actions→general and allow read/write perms for workflows, and go to settings→pages and make sure GitHub Actions is selected as the source for Deployment. Make a commmit and then it will deploy.

If one wants to deploy Lite locally:

python -m pip install jupyterlite-core
jupyter lite init
python3 -m pip install jupyterlite-pyodide-kernel
cd _output
jupyter lite build
jupyter lite serve

Commands to Run in JupyterLite - web address for installation is based on where the wheel is served.

If locally, you might face CORS Issue.

Commands for the cells:

import micropip
await micropip.install ("http://localhost:8000/healpy-0.1.dev1885+g71d9336-py3-none-any.whl") 
await micropip.install("matplotlib")
import healpy

Then it can be tested with the contents of file from above:

import healpy as hp
import matplotlib.pyplot as plt

m = hp.read_map(
    "wmap_band_iqumap_r9_7yr_W_v4_udgraded32_masked_smoothed10deg_fortran.fits"
);
#link will change based on where file is 

hp.projview(m, coord=["G"], projection_type="mollweide");

plt.savefig("map.png")