PCSE

A framework developed for implementing crop simulation models developed in Wageningen.
https://github.com/ajwdewit/pcse

Last synced: about 21 hours ago
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Repository for the Python Crop Simulation Environment

• Host: GitHub
• URL: https://github.com/ajwdewit/pcse
• Owner: ajwdewit
• License: other
• Created: 2013-09-16T19:29:23.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2024-04-11T13:51:23.000Z (about 1 month ago)
• Last Synced: 2024-04-14T03:00:25.479Z (28 days ago)
• Language: Python
• Size: 96.4 MB
• Stars: 175
• Watchers: 28
• Forks: 120
• Open Issues: 1
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

README

        
Python Crop Simulation Environment - PCSE

=========================================

PCSE is a framework developed for implementing crop simulation models developed in

Wageningen. Many of the Wageningen crop simulation models were originally developed

in FORTRAN77 or using the FORTRAN Simulation Translator (`FST`_). Although this

approach has yielded high quality models with high numerical performance, the

inherent limitations of models written in FORTRAN is also becoming increasingly evident:

* The structure of the models is often rather monolithic and the different parts are

  very tightly coupled. Replacing parts of the model with another simulation approach

  is not easy.

* The models rely on file-based I/O which is difficult to change. For example,

  interfacing with databases is complicated in FORTRAN.

* In general, with low-level languages like FORTRAN, simple things already take many

  lines of code and mistakes are easily made, particularly by agronomists and crop

  scientist that have limited experience in developing or adapting software.

To overcome many of the limitations above, the Python Crop Simulation Environment

(PCSE) was developed which provides an environment for developing simulation models

as well as a number of implementations of crop simulation models. PCSE is written

in pure python code which makes it more flexible, easier to modify and extensible

allowing easy interfacing with databases, graphical user interfaces, visualization

tools and numerical/statistical packages. PCSE has several interesting features:

* Implementation in pure python with dependencies only on popular packages available from

  the Python Package Index (PyPI) (`SQLAlchemy`, `PyYAML`, `pandas`, `Openpyxl`, `xlrd`,

  `requests` and `numpy`)

* Modular design allowing you to add or change components relatively quickly with

  a simple but powerful approach to communicate variables between modules.

* Similar to `FST`_, it enforces good model design by explicitly separating parameters,

  rate variables and state variables. Moreover PCSE takes care of the module

  initialization, calculation of rates of changes, updating of state variables

  and actions needed to finalize the simulation.

* Input/Output is completely separated from the simulation model itself. Therefore

  PCSE models can easily read from and write to text files, databases and scientific

  formats such as HDF or NetCDF.

* Tools are available for reading parameter and weather files from existing models to

  have as much backward compatibility as possible.

* An `AgroManager` module which allows to define the agromanagement actions that

  happen on a farmers field. Such actions can be specified as events based on

  time or model state.

* Built-in testing of program modules ensuring integrity of the system.

To contribute to PCSE, you can fork your own copy at https://github.com/ajwdewit/pcse

Full documentation is available on http://pcse.readthedocs.io

Testing PCSE

------------

The PCSE package has some built-in tests that can used to test if any PCSE installation is

producing the correct outputs::

    >>> pcse.test()

    runTest (pcse.tests.test_abioticdamage.Test_FROSTOL) ... ok

    runTest (pcse.tests.test_partitioning.Test_DVS_Partitioning) ... ok

    runTest (pcse.tests.test_evapotranspiration.Test_PotentialEvapotranspiration) ... ok

    runTest (pcse.tests.test_wofost.TestWaterlimitedWinterWheat) ... ok

    ...

    runTest (pcse.tests.test_wofost.TestWaterlimitedGrainMaize) ... ok

    runTest (pcse.tests.test_wofost.TestPotentialPotato) ... ok

    runTest (pcse.tests.test_wofost80.TestWOFOST80_Potential_WinterWheat) ... ok

    runTest (pcse.tests.test_wofost80.TestWOFOST80_WaterLimited_WinterWheat) ... ok

    ----------------------------------------------------------------------

    Ran 32 tests in 39.809s

    OK

If the model output matches the expected output the test will report 'OK',

otherwise an error will be produced with a detailed traceback on where the

problem occurred. Note that the results may deviate from the output above

when tests were added or removed.

On top of the built-in tests, a larger suite of tests is available in the

git repository of PCSE. The latter also includes tests of the LINGRA model

which are not included in the internal tests. The tests can be execute through

the `tests` package::

    (py3_pcse) $ python -m tests

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_potentialproduction_wofost72_01.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_potentialproduction_wofost72_11.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_potentialproduction_wofost72_21.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_potentialproduction_wofost72_31.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_potentialproduction_wofost72_41.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_waterlimitedproduction_wofost72_01.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_waterlimitedproduction_wofost72_11.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_waterlimitedproduction_wofost72_21.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_waterlimitedproduction_wofost72_31.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_waterlimitedproduction_wofost72_41.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Belgium-Michamps-1986_PP.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Netherlands-Zegveld-1986_PP.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Belgium-Michamps-1986_WLP.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Netherlands-Zegveld-1986_WLP.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Belgium-Michamps-1986_NWLP.yaml) ... ok

    runTest (tests.run_tests./home/wit015/Sources/python/pcse/tests/test_data/test_LINGRA_Netherlands-Zegveld-1986_NWLP.yaml) ... ok

    ----------------------------------------------------------------------

    Ran 16 tests in 101.956s

    OK

By default this runs a limited selection of tests. The full test suite can be run with::

    (py3_pcse) $ python -m tests --full

But this will take at least 30 minutes to complete.

Comparing PCSE models against experiments

-----------------------------------------

Starting with PCSE 5.5, there is an additional folder `exp` inside the repository which contains experimental

data which can be used to compare the results from a PCSE model against. Experiments are collected in an

'experimental collection' which contains references to experiments that belong together. For example, all

experiments for potato for a given variety. Currently, the available experiments are limited to grassland for the

LINGRA model and consist of two collections. One for grassland under irrigated conditions and one for rain-fed

conditions. Tt is expected that more experimental data will be collected and stored here in order to have a

reference set to compare model results.

Running the experiments is similar to running the unit tests::

    (py3_pcse) $ python -m exp

    Writing expriment results to: /tmp/exp_results

    Processing collection for Rye grass: Potential

      - Processing experiment: LINGRA_FAO/LINGRA_FAO_experiment_000_UK2_1982.yaml

      - Processing experiment: LINGRA_FAO/LINGRA_FAO_experiment_004_SW1_1983.yaml

      - Processing experiment: LINGRA_FAO/LINGRA_FAO_experiment_006_SW1_1984.yaml

    ...

This will generate figures of simulated vs observed data in order to assess how the model

performs against experimental data. In the future, this will be extended to include a

report with error values.

.. _FST: http://models.pps.wur.nl/sites/models.pps.wur.nl/files/FST%203.pdf
      

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Owner metadata

• Name: Allard de Wit
• Login: ajwdewit
• Email:
• Kind: user
• Description:
• Website:
• Location: Wageningen, The Netherlands
• Twitter:
• Company: Wageningen Environmental Research, Wageningen-UR
• Icon url: https://avatars.githubusercontent.com/u/5472566?u=93f05d77dc1ff825ccaa72e8d595ffbaf2a47c17&v=4
• Repositories: 21
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• Profile URL: https://github.com/ajwdewit

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Name	Email	Commits
Allard de Wit	a****t@x****l	287
hoek008	s****k@w****l	38
unknown	w****5@D****l	10
Ivan Orzan	i****n@g****m	10
Zacharias Steinmetz	s****z@p****e	7
ajwdewit	w****5@L****l	6
Marek Petrik	m****k@p****s	6
fanquake	f****e@g****m	3
Wit	w****5@D****l	2
Julien Malard	j****d@m****a	2
solid	1****3@q****m	2
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• Total packages: 1
• Total downloads:
  • pypi: 503 last-month
• Total dependent packages: 1
• Total dependent repositories: 10
• Total versions: 20
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Dependencies

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