Pre-release clean-up

.github/workflows/ci-tests.yaml

@@ -16,7 +16,7 @@ jobs:
       max-parallel: 1
       matrix:
         os: [ubuntu-latest]
-        python-version: ['3.13']
+        python-version: ['3.12', '3.13', '3.14']
     name: pytest (Python ${{ matrix.python-version }}) (OS ${{ matrix.os }})
 
     # Configure tests
@@ -33,5 +33,4 @@ jobs:
     - name: Test with pytest
       run: |
         # not run benchmark test
-        pytest 
         pytest -vv -m "not benchmark"

.github/workflows/publish-pypi.yaml

@@ -11,10 +11,10 @@ jobs:
     environment: pypi-publish
     steps:
     - uses: actions/checkout@main
-    - name: Set up Python 3.10
+    - name: Set up Python 3.13
       uses: actions/setup-python@v3
       with:
-        python-version: "3.10"
+        python-version: "3.13"
 
     - name: Install pypa/build
       run: >-

.github/workflows/publish-test-pypi.yaml

@@ -13,10 +13,10 @@ jobs:
     environment: pypi-publish
     steps:
     - uses: actions/checkout@main
-    - name: Set up Python 3.10
+    - name: Set up Python 3.13
       uses: actions/setup-python@v3
       with:
-        python-version: "3.10"
+        python-version: "3.13"
 
     - name: Install pypa/build
       run: >-

.pre-commit-config.yaml

@@ -1,13 +1,14 @@
 exclude: 'docs|node_modules|migrations|.git|.tox'
 default_stages: [pre-commit]
-fail_fast: true
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
   rev: v6.0.0
   hooks:
     - id: trailing-whitespace
       files: (^|/)a/.+\.(py|html|sh|css|js)$
+    - id: end-of-file-fixer
+      files: (^|/)a/.+\.(py|html|sh|css|js)$
     - id: check-added-large-files
       args: ["--maxkb=2000"]
 

CHANGELOG.md

@@ -1,8 +1,15 @@
 Changelog
 =========
 
-v0.0.3.dev
+v0.1.0
 ------------------------------------------------------------
+- Reduce computational load of disaggretation by re-organising code and allowing parallelisation with dask [#18](https://github.com/modelblocks-org/gregor/pull/18).
+- Add a more computationally expensive performance test, which disaggregates rooftop PV capacities in Europe, to be run locally [#18](https://github.com/modelblocks-org/gregor/pull/18).
+- Add CI testing [#19](https://github.com/modelblocks-org/gregor/pull/19).
+- Add more unit tests [#17](https://github.com/modelblocks-org/gregor/pull/17).
+- Fix failing aggregation when polygon index is unnamed [#14](https://github.com/modelblocks-org/gregor/pull/14).
+- Move to the [modelblocks-org](https://github.com/modelblocks-org).
+
 
 v0.0.2 (2024-11-21)
 ------------------------------------------------------------

CITATION.cff

@@ -9,7 +9,7 @@ authors:
 title: "Gregor"
 type: software
 license: MIT
-version: 0.0.3.dev
+version: 0.1.0
 doi:
 date-released: 
-url: "https://github.com/jnnr/gregor"
+url: "https://github.com/modelblocks-org/gregor"

README.md

@@ -2,7 +2,7 @@
 
 Gregor is a tool that makes your life easier when aggregating and dis-aggregating spatial data. It has been developed in the context of preparing data for energy system modeling, but can be applied in any situation involving spatial data.
 
-<img src="https://raw.githubusercontent.com/jnnr/gregor/refs/heads/main/docs/img/polygons-to-raster-and-back.png" width=850>
+<img src="https://raw.githubusercontent.com/modelblocks-org/gregor/refs/heads/main/docs/img/polygons-to-raster-and-back.png" width=850>
 
 ## Installation
 
@@ -20,4 +20,4 @@ Please have a look at the examples presented in the [documentation](https://greg
 
 ## Development
 
-If you encounter a bug, consider opening an issue on [GitHub](https://github.com/jnnr/gregor/issues).
+If you encounter a bug, consider opening an issue on [GitHub](https://github.com/modelblocks-org/gregor/issues).

docs/api.md

@@ -5,7 +5,3 @@
 ::: gregor.disaggregate
     options:
         show_source: false
-
-::: gregor.raster
-    options:
-        show_source: false

docs/examples/disaggregate-to-point.py

@@ -58,7 +58,7 @@
 plt.show()
 
 # %% [markdown]
-# Now, we disaggregate the demand data using the population data as a proxy. The result is a raster dataset with the resolution of the proxy.
+# Now, we disaggregate the demand data using the population data as a proxy. The result is a raster with the resolution of the proxy.
 
 # %%
 demand_point = gregor.disaggregate.disaggregate_polygon_to_point(demand_geo, "FC_OTH_HH_E", cities, "pop_max")

docs/examples/disaggregate-to-raster.py

@@ -64,7 +64,7 @@
 plt.show()
 
 # %% [markdown]
-# Now, we disaggregate the demand data using the population data as a proxy. The result is a raster dataset with the resolution of the proxy.
+# Now, we disaggregate the demand data using the population data as a proxy. The result is a raster with the resolution of the proxy.
 
 # %%
 demand_raster = gregor.disaggregate.disaggregate_polygon_to_raster(demand_geo, column="FC_OTH_HH_E", proxy=population)

pyproject.toml

@@ -5,16 +5,15 @@ authors = [
 ]
 description = "A library for spatial aggregation and disaggregation"
 readme = "README.md"
-version = "0.0.3.dev"
+version = "0.1.0"
 dynamic = ["dependencies", "optional-dependencies"]
 
 # complete classifier list:
 # http://pypi.org/classifiers/
 classifiers = [
-  'Programming Language :: Python :: 3.8',
-  'Programming Language :: Python :: 3.9',
-  'Programming Language :: Python :: 3.10',
-  'Programming Language :: Python :: 3.11',
+  'Programming Language :: Python :: 3.12',
+  'Programming Language :: Python :: 3.13',
+  'Programming Language :: Python :: 3.14',
 ]
 
 keywords = [
@@ -24,9 +23,9 @@ keywords = [
 requires-python = ">=3.8, <4"
 
 [project.urls]
-changelog = "https://github.com/jnnr/gregor/blob/main/CHANGELOG.md"
+changelog = "https://github.com/modelblocks-org/gregor/blob/main/CHANGELOG.md"
 homepage = "https://gregor.readthedocs.io/en/latest/"
-repository = "https://github.com/jnnr/gregor.git"
+repository = "https://github.com/modelblocks-org/gregor.git"
 
 [build-system]
 build-backend = "setuptools.build_meta"

src/gregor/disaggregate.py

@@ -1,3 +1,6 @@
+import logging
+import warnings
+
 import dask.array as da
 import geopandas as gpd
 import numpy as np
@@ -8,6 +11,9 @@
 from gregor.aggregate import aggregate_raster_to_polygon
 
 
+logger = logging.getLogger(__name__)
+
+
 def disaggregate_polygon_to_raster(
     data: gpd.GeoDataFrame,
     column: str,
@@ -38,8 +44,10 @@ def disaggregate_polygon_to_raster(
         _proxy = proxy
     elif isinstance(proxy, xr.Dataset):
         if len(proxy.data_vars) == 1:
-            raise DeprecationWarning(
-                "Passing DataSet is deprecated and will be disallowed in the future. Use DataArray instead."
+            warnings.warn(
+                "Passing DataSet is deprecated and will be disallowed in the future. Use DataArray instead.",
+                DeprecationWarning,
+                stacklevel=2,
             )
             var_name = next(iter(proxy.data_vars))
             _proxy = proxy[var_name]
@@ -62,7 +70,7 @@ def disaggregate_polygon_to_raster(
 
     # make sure that crs of data and proxy match
     if _proxy.rio.crs != _data.crs:
-        print(
+        logger.info(
             f"CRS of `data` ({_data.crs}) does not match CRS of `proxy` ({_proxy.rio.crs}). Reprojecting CRS of `data` to match `proxy`'s CRS."
         )
         _data = _data.to_crs(_proxy.rio.crs)
@@ -86,7 +94,10 @@ def disaggregate_polygon_to_raster(
     id_nodata = len(value_lookup) - 1  # index of nodata in value_lookup
     belongs_to = get_belongs_to_matrix(_proxy, _data.geometry, nodata=id_nodata)
     if is_chunked_dask_array:
-        belongs_to = belongs_to.chunk(_proxy.chunks)
+        chunks = {
+            dim: chunk_size for dim, chunk_size in zip(_proxy.dims, _proxy.chunks)
+        }
+        belongs_to = belongs_to.chunk(chunks)
     belongs_to = belongs_to.data.astype("int32")
 
     if is_chunked_dask_array:
@@ -111,7 +122,7 @@ def lookup_func(blk):
     )
 
     if to_data_crs and _proxy.rio.crs != data.crs:
-        print(f"Reprojecting results to `data`'s CRS {data.crs}.")
+        logger.info(f"Reprojecting results to `data`'s CRS {data.crs}.")
         raster = raster.rio.reproject(data.crs)
 
     return raster
@@ -151,44 +162,6 @@ def get_belongs_to_matrix(
     return xr.DataArray(arr, coords=raster.coords, dims=raster.dims)
 
 
-def get_uniform_proxy(
-    polygons: gpd.GeoSeries, raster_resolution: tuple[int, int]
-) -> xr.Dataset:
-    r"""
-    Get a uniform proxy which sums to one for each region.
-
-    Parameters
-    ----------
-    polygons : gpd.GeoSeries
-        Polygons to compute the proxy for.
-    raster_resolution : tuple[int, int]
-        Resolution of the desired raster proxy.
-
-    Returns
-    -------
-    xr.Dataset
-        Uniform proxy which sums to 1 in each region.
-    """
-    # get spatial extent of spatial_units
-    x_min, y_min, x_max, y_max = polygons.total_bounds
-
-    # define coords
-    x_coords = np.linspace(x_min, x_max, raster_resolution[0])
-    y_coords = np.linspace(y_min, y_max, raster_resolution[1])
-
-    # create raster Dataset
-    uniform_proxy = xr.Dataset(
-        data_vars={}, coords={"x": ("x", x_coords), "y": ("y", y_coords)}
-    )
-
-    # TODO Set transform and crs
-    # uniform_proxy = uniform_proxy.rio.set_spatial_dims('x', 'y')
-    # uniform_proxy = uniform_proxy.rio.write_transform()
-    uniform_proxy = uniform_proxy.rio.set_crs(polygons.crs)
-
-    return uniform_proxy
-
-
 def disaggregate_polygon_to_point(
     data: gpd.GeoDataFrame,
     column: str,
@@ -217,7 +190,7 @@ def disaggregate_polygon_to_point(
 
     # compare crs. If not the same, project data to proxy's crs
     if not proxy.crs == _data.crs:
-        print(
+        logger.info(
             f"CRS of `proxy` ({proxy.crs}) does not match CRS of `data` ({_data.crs}). Reprojecting CRS of `data` to `proxy`'s CRS."
         )
         _data = _data.to_crs(proxy.crs)
@@ -255,7 +228,7 @@ def disaggregate_polygon_to_point(
     points = points[["geometry", "disaggregated"]]
 
     if to_data_crs:
-        print(f"Reprojecting results to `data`'s CRS {_data.crs}.")
+        logger.info(f"Reprojecting results to `data`'s CRS {_data.crs}.")
         points = points.to_crs(_data.crs)
 
     return points