Simplify affine matrix calculation for datashader

.github/workflows/test.yaml

@@ -59,7 +59,7 @@ jobs:
           pytest -v --cov --color=yes --cov-report=xml
       - name: Archive figures generated during testing
         if: always()
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: visual_test_results_${{ matrix.os }}-python${{ matrix.python }}
           path: /home/runner/work/spatialdata-plot/spatialdata-plot/tests/figures/*

.pre-commit-config.yaml

@@ -12,8 +12,8 @@ repos:
     rev: 24.10.0
     hooks:
       - id: black
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v4.0.0-alpha.8
+  - repo: https://github.com/rbubley/mirrors-prettier
+    rev: v3.5.0
     hooks:
       - id: prettier
   - repo: https://github.com/asottile/blacken-docs

src/spatialdata_plot/pl/render.py

@@ -19,7 +19,7 @@
 from scanpy._settings import settings as sc_settings
 from spatialdata import get_extent, get_values, join_spatialelement_table
 from spatialdata.models import PointsModel, ShapesModel, get_table_keys
-from spatialdata.transformations import get_transformation, set_transformation
+from spatialdata.transformations import set_transformation
 from spatialdata.transformations.transformations import Identity
 from xarray import DataTree
 
@@ -43,7 +43,6 @@
     _get_colors_for_categorical_obs,
     _get_extent_and_range_for_datashader_canvas,
     _get_linear_colormap,
-    _get_transformation_matrix_for_datashader,
     _is_coercable_to_float,
     _map_color_seg,
     _maybe_set_colors,
@@ -184,10 +183,9 @@ def _render_shapes(
             sdata_filt.shapes[element].loc[is_point, "geometry"] = _geometry[is_point].buffer(scale.to_numpy())
 
         # apply transformations to the individual points
-        element_trans = get_transformation(sdata_filt.shapes[element])
-        tm = _get_transformation_matrix_for_datashader(element_trans)
+        tm = trans.get_matrix()
         transformed_element = sdata_filt.shapes[element].transform(
-            lambda x: (np.hstack([x, np.ones((x.shape[0], 1))]) @ tm)[:, :2]
+            lambda x: (np.hstack([x, np.ones((x.shape[0], 1))]) @ tm.T)[:, :2]
         )
         transformed_element = ShapesModel.parse(
             gpd.GeoDataFrame(data=sdata_filt.shapes[element].drop("geometry", axis=1), geometry=transformed_element)

src/spatialdata_plot/pl/utils.py

@@ -19,7 +19,6 @@
 import matplotlib.transforms as mtransforms
 import numpy as np
 import numpy.ma as ma
-import numpy.typing as npt
 import pandas as pd
 import shapely
 import spatialdata as sd
@@ -59,11 +58,8 @@
 from spatialdata._core.query.relational_query import _locate_value
 from spatialdata._types import ArrayLike
 from spatialdata.models import Image2DModel, Labels2DModel, SpatialElement
-
-# from spatialdata.transformations.transformations import Scale
-from spatialdata.transformations import Affine, Identity, MapAxis, Scale, Translation
-from spatialdata.transformations import Sequence as SDSequence
 from spatialdata.transformations.operations import get_transformation
+from spatialdata.transformations.transformations import Scale
 from xarray import DataArray, DataTree
 
 from spatialdata_plot._logging import logger
@@ -2235,34 +2231,3 @@ def _prepare_transformation(
     trans_data = trans + ax.transData if ax is not None else None
 
     return trans, trans_data
-
-
-def _get_datashader_trans_matrix_of_single_element(
-    trans: Identity | Scale | Affine | MapAxis | Translation,
-) -> npt.NDArray[Any]:
-    flip_matrix = np.array([[1, 0, 0], [0, -1, 0], [0, 0, 1]])
-    tm: npt.NDArray[Any] = trans.to_affine_matrix(("x", "y"), ("x", "y"))
-
-    if isinstance(trans, Identity):
-        return np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
-    if isinstance(trans, (Scale | Affine)):
-        # idea: "flip the y-axis", apply transformation, flip back
-        flip_and_transform: npt.NDArray[Any] = flip_matrix @ tm @ flip_matrix
-        return flip_and_transform
-    if isinstance(trans, MapAxis):
-        # no flipping needed
-        return tm
-    # for a Translation, we need the transposed transformation matrix
-    return tm.T
-
-
-def _get_transformation_matrix_for_datashader(
-    trans: Scale | Identity | Affine | MapAxis | Translation | SDSequence,
-) -> npt.NDArray[Any]:
-    """Get the affine matrix needed to transform shapes for rendering with datashader."""
-    if isinstance(trans, SDSequence):
-        tm = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
-        for x in trans.transformations:
-            tm = tm @ _get_datashader_trans_matrix_of_single_element(x)
-        return tm
-    return _get_datashader_trans_matrix_of_single_element(trans)