Skip to main content

Python Toolbox for the evaluation of soil moisture observations

Project description

https://github.com/TUW-GEO/pytesmo/workflows/tests/badge.svg https://coveralls.io/repos/TUW-GEO/pytesmo/badge.png?branch=master https://badge.fury.io/py/pytesmo.svg https://readthedocs.org/projects/pytesmo/badge/?version=latest

pytesmo, the Python Toolbox for the Evaluation of Soil Moisture Observations, is a package/python toolbox which aims it is to provide a library that can be used for the comparison and validation of geospatial time series datasets with a (initial) focus on soil moisture.

Documentation & Software Citation

https://zenodo.org/badge/DOI/10.5281/zenodo.596422.svg

To see the latest full documentation click on the docs badge at the top.

If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.

Please select your specific version at https://doi.org/10.5281/zenodo.596422 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.

You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning

Installation

This package should be installable through pip which downloads the package from the python package repository Pypi. However, pytesmo also needs some packages that depend on C or Fortran libraries (like netCDF4). They should be installed first with conda. See http://conda.pydata.org/docs/ on how to use it. We recommend using either Anaconda or Miniconda.

$ conda install -c conda-forge numpy scipy pandas netCDF4 cython pyresample pyresample

Afterwards pytesmo can be installed via pip.

$ pip install pytesmo

You can also install all needed (conda and pip) dependencies at once using the following commands after cloning this repository. This is recommended for developers of the package. Note that the git --recursive flag will clone test-data, which is needed by some tests.

$ git clone https://github.com/TUW-GEO/pytesmo.git --recursive
$ cd pytesmo
$ conda create -n pytesmo python=3.6 # or any supported python version
$ source activate pytesmo
$ conda env update -f environment.yml -n pytesmo
$ python setup.py develop

Supported Products

Soil moisture is observed using different methods and instruments, in this version several satellite datasets as well as in situ and reanalysis data are supported through independent and optional (reader) packages:

Contribute

We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.

Guidelines

If you want to contribute please follow these steps:

  • Fork the pytesmo repository to your account

  • Clone the repository, make sure you use git clone --recursive to also get the test data repository.

  • make a new feature branch from the pytesmo master branch

  • Add your feature

  • please include tests for your contributions in one of the test directories We use py.test so a simple function called test_my_feature is enough

  • submit a pull request to our master branch

Release Windows

In order to make a working release for windows the whl files for windows from appveyor CI have to be uploaded to PyPI. They can be found on the appveyor CI run for the created tag under the jobs/Artifacts tab. All the .whl files should be downloaded into a folder. They can then be added to the release on PyPI using e.g. twine upload pytesmo-0.7.1*whl

Note

This project has been set up using PyScaffold 3.2.3. For details and usage information on PyScaffold see https://pyscaffold.org/.

Project details


Download files

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

Source Distribution

pytesmo-0.10.1.tar.gz (1.4 MB view details)

Uploaded Source

Built Distributions

pytesmo-0.10.1-cp38-cp38-win_amd64.whl (160.8 kB view details)

Uploaded CPython 3.8 Windows x86-64

pytesmo-0.10.1-cp37-cp37m-win_amd64.whl (160.8 kB view details)

Uploaded CPython 3.7m Windows x86-64

pytesmo-0.10.1-cp36-cp36m-win_amd64.whl (160.7 kB view details)

Uploaded CPython 3.6m Windows x86-64

File details

Details for the file pytesmo-0.10.1.tar.gz.

File metadata

  • Download URL: pytesmo-0.10.1.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.10.0 pkginfo/1.6.1 requests/2.25.0 setuptools/41.6.0.post20191029 requests-toolbelt/0.8.0 tqdm/4.54.1 CPython/2.7.15

File hashes

Hashes for pytesmo-0.10.1.tar.gz
Algorithm Hash digest
SHA256 bcbb812aa042474fdb1937ede480acb985d99b0e32ea3f77445ad7365a90155d
MD5 78657204ab7f3c23404d5677766ec4ef
BLAKE2b-256 e3498e1e63197c2ddc466a31e2dcfb34c853f74821eb2c07cffa50550dc28d18

See more details on using hashes here.

File details

Details for the file pytesmo-0.10.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pytesmo-0.10.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 160.8 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.10.0 pkginfo/1.6.1 requests/2.25.0 setuptools/41.6.0.post20191029 requests-toolbelt/0.8.0 tqdm/4.54.1 CPython/2.7.15

File hashes

Hashes for pytesmo-0.10.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 1bb934c8b2b56a68d3314f09f9e7f411ba601f4002f16a45d14f64a25f7f5194
MD5 ba9b99d8fec629a773063a857d507407
BLAKE2b-256 8f3adc632276f9d1308b3566c085cfb86337fb551ddd1506425131e12cfb2a3c

See more details on using hashes here.

File details

Details for the file pytesmo-0.10.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: pytesmo-0.10.1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 160.8 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.10.0 pkginfo/1.6.1 requests/2.25.0 setuptools/41.6.0.post20191029 requests-toolbelt/0.8.0 tqdm/4.54.1 CPython/2.7.15

File hashes

Hashes for pytesmo-0.10.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 483a36f538381015f5a2fb7e6f9cbcc4e332e21120ae0eabba05686b9562777a
MD5 dd85e285d8354c4f7a687250179cedf7
BLAKE2b-256 6869aba54b8808d6ad5799b91f1a9e8ec0cafe67a0b0734d4544ef83b099c38d

See more details on using hashes here.

File details

Details for the file pytesmo-0.10.1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pytesmo-0.10.1-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 160.7 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.10.0 pkginfo/1.6.1 requests/2.25.0 setuptools/41.6.0.post20191029 requests-toolbelt/0.8.0 tqdm/4.54.1 CPython/2.7.15

File hashes

Hashes for pytesmo-0.10.1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 4ecea4213949b0c8ce35e6d3eecd252b38cb6e5b41c3d53e96069ec4140caa86
MD5 1c0884a3837d459d384855b2580defb0
BLAKE2b-256 ba2801cd82d502c33650ddfde6a01b25a8130e9fa96dc1b49300e3bdf9e3c4d9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page