| Name | pyswi JSON |
| Version |
1.0
JSON |
| download |
| home_page | https://www.geo.tuwien.ac.at/ |
| Summary | Soil Water Index (SWI) computation |
| upload_time | 2023-01-13 16:31:11 |
| maintainer | |
| docs_url | None |
| author | TU Wien |
| requires_python | >=3.6 |
| license | mit |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
=====
pyswi
=====
Python package allowing computation of the Soil Water Index from surface soil moisture observations by means of exponential filter.
Description
===========
The package includes the following features:
* SWI time series calculation and error propagation from SSM time series
* a recursive approach to SWI and its noise with calculation routines in Cython
* an equivalent SWI calculation in Python with an exponential-filter-based
error propagation scheme
* Recursive SWI approach to calculate SWI for a single or a set of T-values in near-real time
* also *Weighted* calculation of the SWI, allowing for custom weight assignment to
individual observations
iterative_storage
=================
Storage of iteration data between processing runs.
Description
===========
In a process that works iteratively and needs to store some data
between processing runs, the classes in this package can be used to store
that data as netCDF files of any format. The main functionality of this package
is in the building of the storage filenames and in reading the correct iteration
data from the disk when the process is started again.
Installation
============
This package should be installable through pip:
.. code-block:: python
pip install pyswi
Note
====
This project has been set up using PyScaffold 3.2.3. For details and usage
information on PyScaffold see https://pyscaffold.org/.
Raw data
{
"_id": null,
"home_page": "https://www.geo.tuwien.ac.at/",
"name": "pyswi",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "",
"author": "TU Wien",
"author_email": "remote.sensing@geo.tuwien.ac.at",
"download_url": "https://files.pythonhosted.org/packages/c0/91/a1d1ded08165902e5d70f0f8ddc1c269c2dcbd6e7c7cac800cc7e72abbae/pyswi-1.0.tar.gz",
"platform": "any",
"description": "=====\npyswi\n=====\n\nPython package allowing computation of the Soil Water Index from surface soil moisture observations by means of exponential filter.\n\nDescription\n===========\n\nThe package includes the following features:\n\n* SWI time series calculation and error propagation from SSM time series\n * a recursive approach to SWI and its noise with calculation routines in Cython\n * an equivalent SWI calculation in Python with an exponential-filter-based\n error propagation scheme\n* Recursive SWI approach to calculate SWI for a single or a set of T-values in near-real time\n * also *Weighted* calculation of the SWI, allowing for custom weight assignment to\n individual observations\n\niterative_storage\n=================\n\nStorage of iteration data between processing runs.\n\nDescription\n===========\n\nIn a process that works iteratively and needs to store some data\nbetween processing runs, the classes in this package can be used to store\nthat data as netCDF files of any format. The main functionality of this package\nis in the building of the storage filenames and in reading the correct iteration\ndata from the disk when the process is started again.\n\n\nInstallation\n============\nThis package should be installable through pip:\n\n.. code-block:: python\n\n pip install pyswi\n\nNote\n====\n\nThis project has been set up using PyScaffold 3.2.3. For details and usage\ninformation on PyScaffold see https://pyscaffold.org/.\n",
"bugtrack_url": null,
"license": "mit",
"summary": "Soil Water Index (SWI) computation",
"version": "1.0",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "eaad48865d70bbe931d506a9287ffdacbaae4ea28e5602d5e4dc04ead86b20f5",
"md5": "f210a1ef3cf0ecaec8dda3fc632c3257",
"sha256": "64a7f8507701d57761ad759a321b6b10c5bd93fb8d7bd6c4d264b336b22eeab2"
},
"downloads": -1,
"filename": "pyswi-1.0-py2.py3-none-any.whl",
"has_sig": false,
"md5_digest": "f210a1ef3cf0ecaec8dda3fc632c3257",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": ">=3.6",
"size": 74592,
"upload_time": "2023-01-13T16:31:08",
"upload_time_iso_8601": "2023-01-13T16:31:08.817164Z",
"url": "https://files.pythonhosted.org/packages/ea/ad/48865d70bbe931d506a9287ffdacbaae4ea28e5602d5e4dc04ead86b20f5/pyswi-1.0-py2.py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "c091a1d1ded08165902e5d70f0f8ddc1c269c2dcbd6e7c7cac800cc7e72abbae",
"md5": "e1437b2f1611582d677b644c58fec41b",
"sha256": "2b83f7cdf081b92bdff2d019ea1d864fb102f515ae40959775ab67c2b04b0ecc"
},
"downloads": -1,
"filename": "pyswi-1.0.tar.gz",
"has_sig": false,
"md5_digest": "e1437b2f1611582d677b644c58fec41b",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 342643,
"upload_time": "2023-01-13T16:31:11",
"upload_time_iso_8601": "2023-01-13T16:31:11.219125Z",
"url": "https://files.pythonhosted.org/packages/c0/91/a1d1ded08165902e5d70f0f8ddc1c269c2dcbd6e7c7cac800cc7e72abbae/pyswi-1.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-13 16:31:11",
"github": false,
"gitlab": false,
"bitbucket": false,
"lcname": "pyswi"
}
