Flash calculations with guesses powered by K-D trees
Project description
README
Routines for making use of superancillary equations and K-D trees to make iterative calculations with thermodynamic models much faster and much more reliable.
Much more information in the docs.
Docs
Build of docs follow the instructions in the doc folder
Run tests
mkdir bld
cd bld
cmake .. -DTEQPFLSH_TESTS=ON -DCMAKE_BUILD_TYPE=Release
cmake --build . --config Release
All tests should pass on all platforms
Development information
How to do incremental rebuilds with nanobind
See https://nanobind.readthedocs.io/en/latest/packaging.html#step-5-incremental-rebuilds ::
pip install nanobind scikit-build-core[pyproject]
pip install --no-build-isolation -ve .
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file teqpflsh-0.0.3.tar.gz.
File metadata
- Download URL: teqpflsh-0.0.3.tar.gz
- Upload date:
- Size: 50.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6c6468dfd9a1dbb1af1481c1325643afcf34765d832226e59993fa050a0e2e44
|
|
| MD5 |
726575102bb03f92bfc7b8c8b743b255
|
|
| BLAKE2b-256 |
bfbdf5ea3d428d91949c370f36eaa603a66521011c8a07336323d3da46b8006e
|
File details
Details for the file teqpflsh-0.0.3-cp313-cp313-win_amd64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp313-cp313-win_amd64.whl
- Upload date:
- Size: 4.7 MB
- Tags: CPython 3.13, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
75074ca3b17ce606e52bea6adf8b64239d6a5120cb04700edaf004baec059b0c
|
|
| MD5 |
f10ca885c68231a5698bc867b58a0de6
|
|
| BLAKE2b-256 |
5373e331bc920e24b340ce5faa9c537bac9aaf2dfcc56337d7f52b063f1d40a6
|
File details
Details for the file teqpflsh-0.0.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
- Upload date:
- Size: 5.3 MB
- Tags: CPython 3.13, manylinux: glibc 2.17+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f04344c8946f13e7d36ce927cf98980ee4cd93eba8c16f442bfcf678b1f1e452
|
|
| MD5 |
e56708f5974ed3d56a7575d6b38de093
|
|
| BLAKE2b-256 |
b8f4d64c007a83e5b7bea26ed611551f8324c31237da87b305b1c5e7fa83b248
|
File details
Details for the file teqpflsh-0.0.3-cp313-cp313-macosx_11_0_x86_64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp313-cp313-macosx_11_0_x86_64.whl
- Upload date:
- Size: 4.9 MB
- Tags: CPython 3.13, macOS 11.0+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d79585ab5279d1bcdc4dcd85518732acf2c7d9939db310ac3cd7e4406a097dcb
|
|
| MD5 |
1c38e63a92bd792a3d33366c5e6b9509
|
|
| BLAKE2b-256 |
f60265b658f5b4baeabb993594c89095108cbb6ac50f67e2a7d7b54f2a89c85f
|
File details
Details for the file teqpflsh-0.0.3-cp313-cp313-macosx_11_0_arm64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp313-cp313-macosx_11_0_arm64.whl
- Upload date:
- Size: 4.2 MB
- Tags: CPython 3.13, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
85a58c3b9a7174ac751e171d1f144354ee418949fcc255bba322d1491e2aeafd
|
|
| MD5 |
31ac68a68ebc7880bf0a809014ca14f7
|
|
| BLAKE2b-256 |
6b6c638c26ecc756b735e6d2a9e6deb5e13bb38b021fe5da5024e6bd7013bc6e
|
File details
Details for the file teqpflsh-0.0.3-cp312-cp312-win_amd64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp312-cp312-win_amd64.whl
- Upload date:
- Size: 4.7 MB
- Tags: CPython 3.12, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a59d71b4f7cd0a6f68eb5b013eda76b8114cf60ad177ff0876ccc4635746c245
|
|
| MD5 |
4d08bce53d5c4586f07e23658daf219f
|
|
| BLAKE2b-256 |
953a5cd33102429dff5b950582ab7b8880171e6165f5fddea3d23c8b0e679b59
|
File details
Details for the file teqpflsh-0.0.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
- Upload date:
- Size: 5.3 MB
- Tags: CPython 3.12, manylinux: glibc 2.17+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4ddc99d17664797a54f29c52429f631619d33527239328647952552991405f9a
|
|
| MD5 |
41b00e6958dc6c4a54cc9b13b499d5b6
|
|
| BLAKE2b-256 |
5b86590f68322a6d5808776cdfaeb28d51e390ff3da4ccd75998984a0f1e652e
|
File details
Details for the file teqpflsh-0.0.3-cp312-cp312-macosx_11_0_x86_64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp312-cp312-macosx_11_0_x86_64.whl
- Upload date:
- Size: 5.0 MB
- Tags: CPython 3.12, macOS 11.0+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0a6dbbd48ed17bd60edb1457f116376feaefaf8fb8471ac0e6f4baee36a97569
|
|
| MD5 |
afc272d453381c0f42fa12071b618046
|
|
| BLAKE2b-256 |
f8108bc025ea8653e8d46e6ed0126852a0901def92add883101ecb30006572d1
|
File details
Details for the file teqpflsh-0.0.3-cp312-cp312-macosx_11_0_arm64.whl.
File metadata
- Download URL: teqpflsh-0.0.3-cp312-cp312-macosx_11_0_arm64.whl
- Upload date:
- Size: 4.3 MB
- Tags: CPython 3.12, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b31685daa0281176872cb0e09b0502d5a3f7accde53ae8b92b322e0c8287df9b
|
|
| MD5 |
e595f3b0edb266b3973a38cffd817276
|
|
| BLAKE2b-256 |
dae1db783d5b391f1e16ac770ffc3e5a4c79485d8d50f09bf28546b2cc87ba7b
|
