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(T)ool for (E)fficient co(MPU)tation of mode-coupling estimato(R) norm(A)lization

pytempura/tests/data/image.png

This package contains a python module to compute analytic normalization of quadratic estimators for lensing, cosmic birefringence, patchy tau and point sources, based on separable formula.

The code was verified in the following studies:

Installing

Make sure your pip tool is up-to-date. To install pytempura, run:

$ pip install pytempura --user

This will install a pre-compiled binary suitable for your system (only Linux and Mac OS X with Python>=3.10 are supported).

If you require more control over your installation, e.g. using Intel compilers, please see the section below on compiling from source.

Compiling from source (advanced / development workflow)

The easiest way to install from source is to use the pip tool, with the --no-binary flag. This will download the source distribution and compile it for you. Don’t forget to make sure you have CC and FC set if you have any problems.

For all other cases, below are general instructions.

First, download the source distribution or git clone this repository. You can work from master or checkout one of the released version tags (see the Releases section on Github). Then change into the cloned/source directory.

Once downloaded, you can install using pip install . inside the project directory. We use the meson build system, which should be understood by pip (it will build in an isolated environment).

We suggest you then test the installation by running the unit tests. You can do this by running pytest.

To run an editable install, you will need to do so in a way that does not have build isolation (as the backend build system, meson and ninja, actually perform micro-builds on usage in this case):

$ pip install --upgrade pip meson ninja meson-python cython numpy
$ pip install  --no-build-isolation --editable .

Examples

You can find example codes at “tests” directory.

Contact

Metadata

Release files for pytempura 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pytempura 0.2.0
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pytempura-0.2.0.tar.gz 19.5 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for pytempura 0.2.0
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pytempura-0.2.0-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details
pytempura-0.2.0-cp312-cp312-macosx_13_0_x86_64.whl CPython 3.12 CPython 3.12 macOS 13.0+ x86-64 Details
pytempura-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.17+ x86-64 Details
pytempura-0.2.0-cp311-cp311-macosx_14_0_arm64.whl CPython 3.11 CPython 3.11 macOS 14.0+ ARM64 Details
pytempura-0.2.0-cp311-cp311-macosx_13_0_x86_64.whl CPython 3.11 CPython 3.11 macOS 13.0+ x86-64 Details
pytempura-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.17+ x86-64 Details
pytempura-0.2.0-cp310-cp310-macosx_14_0_arm64.whl CPython 3.10 CPython 3.10 macOS 14.0+ ARM64 Details
pytempura-0.2.0-cp310-cp310-macosx_13_0_x86_64.whl CPython 3.10 CPython 3.10 macOS 13.0+ x86-64 Details

Total release size: 30.0 MB

Release files / pytempura-0.2.0.tar.gz

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