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https://github.com/moble/spinsfast
Fast and exact spin-s spherical-harmonic transforms
https://github.com/moble/spinsfast
Last synced: 2 months ago
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Fast and exact spin-s spherical-harmonic transforms
- Host: GitHub
- URL: https://github.com/moble/spinsfast
- Owner: moble
- License: gpl-3.0
- Created: 2015-02-05T06:01:09.000Z (almost 10 years ago)
- Default Branch: main
- Last Pushed: 2024-09-03T22:47:32.000Z (4 months ago)
- Last Synced: 2024-10-15T01:25:23.979Z (3 months ago)
- Language: Jupyter Notebook
- Size: 1.62 MB
- Stars: 6
- Watchers: 5
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README
- License: COPYING
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README
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[](https://pypi.org/project/spinsfast/)
[](https://anaconda.org/conda-forge/spinsfast)
[](https://github.com/moble/spinsfast/blob/main/LICENSE)
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# spinsfast
Fast and exact spin-s spherical-harmonic transforms
This code is a modified version of the code hosted
[here](http://astrophysics.physics.fsu.edu/~huffenbe/research/spinsfast/index.html)
by Huffenberger, based on work by [Huffenberger and
Wandelt](http://stacks.iop.org/0067-0049/189/255).
My (@moble's) modifications mostly deal with the user interface:
* add `multi_map2salm` and `multi_salm2map` for running many similar transformations efficiently;
* create python wrappers for the `map2salm` and `salm2map` functions to deal with any (reasonable)
type or shape of input data, including multi-dimensional;
* add python 3.x compatibility to `python/spinsfast_module.c`;
* fix segfaults due to use of `free` instead of `fftw_free` when `fftw_malloc` was used;
* make it easier to install as a python module by trying to detect paths to
FFTW;
* fix numerous massive memory leaks in python extension module;
* include an ipython/jupyter notebook in the `example` directory;
* add integration with [pip](https://pypi.python.org/pypi/pip)
and [pypi](https://pypi.python.org/pypi/spinsfast), for easy installation
([see below](#installation));
* add integration with [conda](https://conda.io/docs/)
and [anaconda.org](https://anaconda.org/moble/spinsfast), for easiest installation
([see below](#installation)).
# License
The original work is licensed under GPL, so that's what I have to
license this under as well. (I usually go for the more liberal MIT
license, but GPL is fine.) See the `LICENSE` file in this directory
for more details.
I based my work on Huffenberger and Wandelt's "Revision 104, 13 Apr
2012", which is current as of this writing (August 2015). Whenever I
notice updates on their end, I will gladly update this code, so feel
free to open an [issue](https://github.com/moble/spinsfast/issues) to
notify me. To see more specifically what I've added, look through the
[commits](https://github.com/moble/spinsfast/commits/master); my
contributions are just everything since the initial commit.
# Example Usage
A convenient ipython/jupyter notebook is found in the `example`
directory, and can also be [viewed directly
online](http://nbviewer.ipython.org/github/moble/spinsfast/blob/master/example/spinsfast.ipynb).
It shows some example python code that can be used to run this module,
and explains some of the conventions established by the `spinsfast`
authors.
In the interests of a very short, explicit example, here is one using
random `(ell,m)` modes:
```python
from numpy.random import normal, seed
import spinsfast
# Some boilerplate for setting things up:
s = 1 # spin weight of the field
lmax = 8 # maximum ell value used
Ntheta = 2*lmax+1 # Minimum value for accuracy
Nphi = 2*lmax+1 # Minimum value for accuracy
Nlm = spinsfast.N_lm(lmax); # Total number of complex components of the mode decomposition
# `alm` will hold the mode components as discussed in `example/spinsfast.ipynb`
# Here we just fill it with some random numbers to test it
seed(3124432) # Seed the random-number generator, for reproducibility
alm = normal(size=(Nlm,)) + 1j*normal(size=(Nlm,))
# This is the key line, where spinsfast converts from (ell,m) modes to values in physical space
f = spinsfast.salm2map(alm,s,lmax,Ntheta,Nphi)
# We can also convert in the opposite direction like this:
alm2 = spinsfast.map2salm(f,s,lmax)
```
# Installation
## Anaconda
Though manual installation is possible, the best way by far to satisfy
these dependencies is to use the
[`anaconda`](http://continuum.io/downloads) distribution. This
distribution can co-exist with your system python with no trouble --
you simply add the path to anaconda before your system executables.
It installs into your home directory, so it doesn't require root
access. It can be uninstalled easily, since it exists entirely inside
its own directory. And updates are trivial.
Once `anaconda` is installed, this package may be installed with the
command
```bash
conda install --channel conda-forge spinsfast
```
Note this may also install `numpy` and `fftw` automatically.
## Pip
While generally less robust, this package is also available via `pip`:
```bash
python -m pip install spinsfast
```
Unfortunately, maintaining binary distributions on pip is very
complicated, so `pip` may try to compile the source code for you, in
which case you will need to have FFTW and a compiler installed. But
`pip` has no good way of handling these dependencies. See below for
environment variables you may need to set to get compilation working
properly.
It may be helpful to install `pyfftw` first. Or, on MacOS, you may
have better luck installing FFTW via homebrew and adding flags like
`CFLAGS=" -L/opt/homebrew/lib " python -m pip install spinsfast`.
## Manual installation
Manual installation of this package is slightly more delicate. The
[FFTW package](http://www.fftw.org/) must be installed first. This is
usually very simple. But the resulting header and library must be
found by the compilation step for this package. You can first simply
try to run
```bash
python -m pip install .
```
from the top directory of the `spinsfast` code. This attempts to find
the `fftw` header or library for you, using some common defaults
checked by code in `setup.py`.
If this doesn't work, you can read the error message, but the most
likely problem is that the compiler cannot find the `fftw` header, or
the linker cannot find the `fftw` library. To solve these problems,
you will need to run something more like this:
```bash
export LIBRARY_PATH=/path/to/fftw/lib
export C_INCLUDE_PATH=/path/to/fftw/include
python -m pip install .
```
Alternatively, you could try to alter `setup.py` to point to the right
paths.
# Original installation instructions
Though these are not necessary for installing the python module, the
following are the instructions in the original source code for
building the C code.
Get the latest version at:
http://www.physics.miami.edu/~huffenbe/research/spinsfast/
## Compilation instructions
1. Edit the file (or make a new file) called build/config.mk so that
the proper locations for header and library files are included.
2. Set the environment variable "build" so that it points to that
file. I.e., in bash, say
export build=build/config.mk
3. Build the library and example codes with
make
## (Optional) Checking the compilation
Run the example code following the instructions at
http://www.physics.miami.edu/~huffenbe/research/spinsfast/