Merge remote-tracking branch 'ribasim-python/main' into merge

.github/workflows/docs.yml

@@ -16,7 +16,7 @@ jobs:
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - uses: julia-actions/setup-julia@v1
         with:
           version: ${{ matrix.version }}
@@ -37,9 +37,8 @@ jobs:
       # setup Python / Jupyter
       - uses: actions/setup-python@v4
         with:
-          python-version: '3.x'
-      # avoid jupyter-client 8: https://github.com/quarto-dev/quarto-cli/issues/4122
-      - run: pip install jupyter jupyter-client==7.4.9
+          python-version: '3.11'
+      - run: pip install jupyter
 
       - name: Install IJulia
         run: julia -e 'using Pkg; Pkg.add("IJulia")'

.gitignore

@@ -23,3 +23,142 @@ compile/create_binaries/libribasim/
 JuliaSysimage.dll
 LocalPreferences.toml
 .ipynb_checkpoints
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Generated docs
+/docs
+
+# VS Code settings
+*.vscode
+
+# Example models
+/examples/basic
+/examples/basic-transient

README.rst

@@ -0,0 +1,11 @@
+ribasim-python
+==============
+
+A Python package for working with `Ribasim.jl <https://github.com/Deltares/Ribasim.jl>`_.
+
+
+Documentation
+-------------
+
+API documentation can be found `here <https://deltares.github.io/ribasim-python/ribasim.html>`_.
+See also the examples directory.

environment.yml

@@ -0,0 +1,18 @@
+name: ribasim
+
+channels:
+  - conda-forge
+
+dependencies:
+  - python >= 3.9
+  - matplotlib
+  - pandas
+  - geopandas
+  - pandera
+  - pyarrow
+  - pydantic
+  - pyogrio
+  - shapely >=2.0
+  - tomli
+  - tomli-w
+  - xarray

examples/basic-transient.py

@@ -0,0 +1,78 @@
+# %%
+import os
+
+os.environ["USE_PYGEOS"] = "0"
+
+import numpy as np
+import pandas as pd
+import xarray as xr
+
+import ribasim
+
+# %%
+
+model = ribasim.Model.from_toml("basic/basic.toml")
+
+# %%
+
+time = pd.date_range(model.starttime, model.endtime)
+day_of_year = time.day_of_year.values
+seconds_per_day = 24 * 60 * 60
+evaporation = (
+    (-1.0 * np.cos(day_of_year / 365.0 * 2 * np.pi) + 1.0) * 0.0025 / seconds_per_day
+)
+rng = np.random.default_rng()
+precipitation = (
+    rng.lognormal(mean=-1.0, sigma=1.7, size=time.size) * 0.001 / seconds_per_day
+)
+
+# %%
+# We'll use xarray to easily broadcast the values.
+
+timeseries = (
+    pd.DataFrame(
+        data={
+            "node_id": 1,
+            "time": time,
+            "drainage": 0.0,
+            "potential_evaporation": evaporation,
+            "infiltration": 0.0,
+            "precipitation": precipitation,
+            "urban_runoff": 0.0,
+        }
+    )
+    .set_index("time")
+    .to_xarray()
+)
+
+basin_ids = model.basin.static["node_id"].unique()
+basin_nodes = xr.DataArray(
+    np.ones(len(basin_ids)), coords={"node_id": basin_ids}, dims=["node_id"]
+)
+forcing = (timeseries * basin_nodes).to_dataframe().reset_index()
+
+# %%
+
+state = pd.DataFrame(
+    data={
+        "node_id": basin_ids,
+        "storage": 1000.0,
+        "concentration": 0.0,
+    }
+)
+
+# %%
+
+model.basin.forcing = forcing
+model.basin.state = state
+
+# %%
+
+model.write("basic-transient")
+# %%
+# After running the model, read back the input:
+
+df = pd.read_feather(r"c:\src\ribasim.jl\examples\basic-transient\basin.arrow")
+output = df.set_index(["time", "node_id"]).to_xarray()
+output["level"].plot(hue="node_id")
+# %%