Time Ordered Astrophysics Scalable Tools

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Development Status
- 5 - Production/Stable
Environment
- Console
Intended Audience
- Science/Research
License
- OSI Approved :: BSD License
Operating System
- POSIX
Programming Language
Topic
- Scientific/Engineering :: Astronomy

Project description

Time Ordered Astrophysics Scalable Tools

Build Status

Description

TOAST is a software framework for simulating and processing timestream data collected by telescopes. Telescopes which collect data as timestreams rather than images give us a unique set of analysis challenges. Detector data usually contains noise which is correlated in time as well as sources of correlated signal from the instrument and the environment. Large pieces of data must often be analyzed simultaneously to extract an estimate of the sky signal.

Documentation

See the full documentation here:

https://toast-cmb.readthedocs.io/en/toast3/

Project details

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Development Status
- 5 - Production/Stable
Environment
- Console
Intended Audience
- Science/Research
License
- OSI Approved :: BSD License
Operating System
- POSIX
Programming Language
Topic
- Scientific/Engineering :: Astronomy

Release history Release notifications | RSS feed

3.0.0a23 pre-release

Mar 21, 2024

3.0.0a21 pre-release

Jan 30, 2024

3.0.0a20 pre-release

Oct 11, 2023

3.0.0a19 pre-release

Aug 17, 2023

3.0.0a18 pre-release

Jul 27, 2023

3.0.0a17 pre-release yanked

Jul 27, 2023

Reason this release was yanked:

Sporadic wheel build failure, not all wheels deployed.

3.0.0a16 pre-release

Jul 5, 2023

3.0.0a15 pre-release

Mar 13, 2023

3.0.0a14 pre-release

Feb 18, 2023

3.0.0a13 pre-release

Feb 1, 2023

3.0.0a12 pre-release

Jan 24, 2023

3.0.0a9 pre-release

Oct 27, 2022

3.0.0a8 pre-release

Oct 24, 2022

3.0.0a6 pre-release

Oct 23, 2022

3.0.0a5 pre-release

Oct 21, 2022

3.0.0a4 pre-release

Sep 25, 2022

3.0.0a3 pre-release

Jul 10, 2022

This version

3.0.0a2 pre-release

May 6, 2022

3.0.0a1 pre-release yanked

May 5, 2022

Reason this release was yanked:

Deprecated

2.3.14

Oct 10, 2021

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

toast-3.0.0a2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.5 MB view hashes)

Uploaded May 6, 2022 CPython 3.10 manylinux: glibc 2.17+ x86-64

toast-3.0.0a2-cp310-cp310-macosx_10_9_x86_64.whl (5.6 MB view hashes)

Uploaded May 6, 2022 CPython 3.10 macOS 10.9+ x86-64

toast-3.0.0a2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.5 MB view hashes)

Uploaded May 6, 2022 CPython 3.9 manylinux: glibc 2.17+ x86-64

toast-3.0.0a2-cp39-cp39-macosx_10_9_x86_64.whl (5.6 MB view hashes)

Uploaded May 6, 2022 CPython 3.9 macOS 10.9+ x86-64

toast-3.0.0a2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.5 MB view hashes)

Uploaded May 6, 2022 CPython 3.8 manylinux: glibc 2.17+ x86-64

toast-3.0.0a2-cp38-cp38-macosx_10_9_x86_64.whl (5.6 MB view hashes)

Uploaded May 6, 2022 CPython 3.8 macOS 10.9+ x86-64

toast-3.0.0a2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.5 MB view hashes)

Uploaded May 6, 2022 CPython 3.7m manylinux: glibc 2.17+ x86-64

toast-3.0.0a2-cp37-cp37m-macosx_10_9_x86_64.whl (5.5 MB view hashes)

Uploaded May 6, 2022 CPython 3.7m macOS 10.9+ x86-64

Hashes for toast-3.0.0a2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for toast-3.0.0a2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`df19fa14009d6cb53b18cf656be39c83f457111e80474ef1189f860baeb90257`
MD5	`9611783b7c961d92b08bc3b6c3a9afac`
BLAKE2b-256	`b493bfd4f53e034f69793b1c0b1f8a45eb22d330200aaaa9232d4fbdf94df499`

Hashes for toast-3.0.0a2-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for toast-3.0.0a2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`f31bfb90179a16bc11e83eac3982edd69d6b8c083ea78ca9a459567098019c5e`
MD5	`34e6968076521d4fd964c1ff6e9aa537`
BLAKE2b-256	`e1c75cba6cc344a8af9c5b54cb2b2ec08d5afc66bd1686285178ed0684f62551`

Hashes for toast-3.0.0a2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for toast-3.0.0a2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`a29f1d40a8906711d703b74f46b74caae6dbcd31f86a93a3bda9ad888c9f53c1`
MD5	`bfc2f31d2ee698b787bf579becb3ef4d`
BLAKE2b-256	`3563f1498909505df730cc2f487adb6d55adf8a532368109f53c284ef5a99f8f`

Hashes for toast-3.0.0a2-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for toast-3.0.0a2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`1099601518c2482dc200bd6be367aae744dc63faa2968f44b03d49d5dc4b5585`
MD5	`a955243a8d290d2808cf73dde366e405`
BLAKE2b-256	`e33e75b98af961ccc0dfcc4585bee43deb3ffa4eae90ec4ddc011980bb3f77e5`

Hashes for toast-3.0.0a2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for toast-3.0.0a2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`afbe50506f4b23cd66a82b6751afc10821f16919b3169602f66ba4edc0ca73b1`
MD5	`7792058227c8901e05fa9ec8c328d565`
BLAKE2b-256	`f96d0642041b3a7785b1607667c4979c33cc99701774235dabee5ae77bf354e6`

Hashes for toast-3.0.0a2-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for toast-3.0.0a2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`5726caa02f1e67ebc64b9a0fcc39ac3e8f97c042be4a8c3d040d6d502320854a`
MD5	`aa626f23efe7a7f4559000ce6404563c`
BLAKE2b-256	`e5c82ace8150e803579fa3415e0d983d7fd2d4d7a60e7228cde3ef21f447dd2f`

Hashes for toast-3.0.0a2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for toast-3.0.0a2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`8a89578b4d067ad0e1ab81c981dcb8ae73a555c014fed7afd653d04999029e0b`
MD5	`609ca142f2964e88fcf096f8c91b89c9`
BLAKE2b-256	`8bfb41c27710af6c992586be36b3c8fbd7477b1dbdfc9ee58a612ab96c7681f3`

Hashes for toast-3.0.0a2-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for toast-3.0.0a2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`dab98d4ee368cfb549b439b0c4bc87140acfb322f3460308e6fb3a1d35b709bc`
MD5	`2b741096e67fe23597f4328ce04e8c80`
BLAKE2b-256	`5d5c20e8dba75e3de10f78498b6594ce4b59ea08af06262a62ac25c42617811f`