semvec/pypi-packages huggingface dataset:
symlens 0.3.3
Symbolic Mode Coupling
License: BSD license
Keywords: symlens

.. sectnum::

=======
symlens
=======

.. image:: https://img.shields.io/pypi/v/symlens.svg
        :target: https://pypi.python.org/pypi/symlens

.. image:: https://img.shields.io/travis/simonsobs/symlens.svg
        :target: https://travis-ci.org/simonsobs/symlens

.. image:: https://readthedocs.org/projects/symlens/badge/?version=latest
        :target: https://symlens.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status




This library allows one to build and evaluate arbitrary separable mode-coupling
estimators. In practice, its main purpose is to provide a flat-sky lensing estimator
code. More generally, one can build estimators and noise functions for
convergence, magnification, shear, mixed estimators (for gradient cleaning),
split-based lensing, birefringence, patchy tau, etc. and cross-covariances
between these.

Instead of having to calculate by hand the separable forms of the above, one
simply provides the mode-coupling and filter expressions, and a ``sympy``-based
(Mathematica-like) backend factorizes these expressions into FFT-only form
(i.e., no explicit convolutions are required).

Curved sky support does not exist. Adding it is possibly non-trivial, but
thoughts and ideas (and PRs!) are highly appreciated. Still, this package can
serve as the backend for quick exploration of various kinds of estimators.

* Free software: BSD license
* Documentation: https://symlens.readthedocs.io.

Dependencies
============

* Python>=3.6
* pixell_
* numpy, sympy

Installing
==========

To install, run:

.. code-block:: console
		
   $ python setup.py install --user

Usage
=====

See the Usage_ guide and the API Reference_.

An important thing to remember is that by default, the code
expects "physical" normalization of FFTs in pixell (not the
default normalization in pixell), i.e. you
should be passing in Fourier maps that come from something like

.. code-block:: python
		
   kmap = enmap.fft(imap,normalize='phys')

or

.. code-block:: python
		
   kmaps = enmap.map2harm(imaps,normalize='phys')



Contributing
------------

If you have write access to this repository, please:

1. create a new branch
2. push your changes to that branch
3. merge or rebase to get in sync with master
4. submit a pull request on github

If you do not have write access, create a fork of this repository and proceed as described above. 

.. _pixell: https://github.com/simonsobs/pixell/
.. _Usage: https://symlens.readthedocs.io/en/latest/usage.html
.. _Reference: https://symlens.readthedocs.io/en/latest/reference.html


=======
History
=======

.. sectnum:: :start: 4

0.1.0 (2019-03-06)
==================


* First release on PyPI.

0.3.3 (2020-07-25)
==================

* Better treatment of FFT factors
* Lots of new features including bias hardening and isotropic RDN0