Merge pull request #239 from raphaelquast/dev

merge for v8.2

Author: raphaelquast

.github/workflows/testMaps.yml

@@ -33,8 +33,14 @@ jobs:
       - name: Test Maps
         shell: bash -l {0}
         run: |
-          pip install -e .[all]
+          pip install -e .[test]
           python -m pytest -v --cov=eomaps --cov-report=xml
+      - name: Upload Image Comparison Artefacts
+        if: ${{ failure() }}
+        uses: actions/upload-artifact@v4
+        with:
+          name: code-coverage-report
+          path: img_comparison_results
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:

docs/api_data_visualization.rst

@@ -619,6 +619,7 @@ Shade Raster
     :nosignatures:
 
     Maps.set_shape.shade_raster
+    Maps.set_shade_dpi
 
 .. list-table::
    :header-rows: 1
@@ -640,6 +641,7 @@ Shade Raster
                              agg_hook=None,        # datashader aggregation hook callback
                              )
 
+
 .. _shp_shade_points:
 
 Shade Points
@@ -649,6 +651,7 @@ Shade Points
     :nosignatures:
 
     Maps.set_shape.shade_raster
+    Maps.set_shade_dpi
 
 .. list-table::
    :header-rows: 1

docs/contribute.rst

@@ -99,26 +99,40 @@ The `environment.yml` file already contains the packages required to run the tes
 
 - `pytest <https://docs.pytest.org>`__ to run the tests
 - `pytest-cov <https://github.com/pytest-dev/pytest-cov>`__ and `coveralls <https://github.com/TheKevJames/coveralls-python>`__ to track lines covered by the tests
-
+- `pytest-mpl <https://pytest-mpl.readthedocs.io/en/stable/>`__ to perform image comparisons
 
 To run the primary test suite and generate coverage report, navigate to the parent `eomaps` directory and run:
 
 .. code-block:: console
 
-    python -m pytest -v --cov eomaps
+    python -m pytest -v --cov eomaps --mpl
+
+Some of the tests compare exported images with a set of baseline-images to ensure stable image exports and to catch
+potential issues that are not detected by the code based tests.
+
+If changes require an update of the baseline images, you have to invoke
+`pytest-mpl <https://pytest-mpl.readthedocs.io/en/stable/>`__ with the `mpl-generate-path` option:
+
+.. code-block:: console
+
+    python -m pytest -v --cov eomaps --mpl --mpl-generate-path=tests/baseline
+
+This will update all images in the `tests/baseline` folder.
 
 .. note::
 
     During the tests, a lot of figures will be created and destroyed!
 
+    Before updating new baseline images, make sure to manually check that they look exactly as expected!
+
 
 .. tip::
 
    You can run only a subset of the tests by using the ``-k`` flag! (This will select only tests whose names contain the provided keyword)
 
    .. code-block:: console
 
-      python -m pytest -k <KEYWORD>
+      python -m pytest -k <QUERY KEYWORD>
 
    (see `pytest command-line-flags <https://docs.pytest.org/en/7.3.x/reference/reference.html#command-line-flags>`_ for more details)
 
@@ -129,7 +143,7 @@ To run the primary test suite and generate coverage report, navigate to the pare
 
     .. code-block:: console
 
-        python -m pytest -n <NUMCORE> --cov eomaps
+        python -m pytest -n <NUMBER OF CORES>
 
 Style Checking
 ~~~~~~~~~~~~~~

docs/examples/example_multiple_maps.py

@@ -14,8 +14,8 @@
 
 # initialize a grid of Maps objects
 m = Maps(ax=131, crs=4326, figsize=(11, 5))
-m2 = Maps(f=m.f, ax=132, crs=Maps.CRS.Stereographic())
-m3 = Maps(f=m.f, ax=133, crs=3035)
+m2 = m.new_map(ax=132, crs=Maps.CRS.Stereographic())
+m3 = m.new_map(ax=133, crs=3035)
 
 # --------- set specs for the first map
 m.text(0.5, 1.1, "epsg=4326", transform=m.ax.transAxes)

docs/examples/example_scalebars.py

@@ -1,5 +1,4 @@
 # EOmaps example: Adding scalebars - what about distances?
-
 from eomaps import Maps
 
 m = Maps(figsize=(9, 5))
@@ -14,7 +13,9 @@
     n=10,
     scale_props=dict(width=5, colors=("k", ".25", ".5", ".75", ".95")),
     patch_props=dict(offsets=(1, 1.4, 1, 1), fc=(0.7, 0.8, 0.3, 1)),
-    label_props=dict(offset=0.5, scale=1.4, every=5, weight="bold", family="Calibri"),
+    label_props=dict(
+        offset=0.5, scale=1.4, every=5, weight="bold"  # , family="Calibri"
+    ),
 )
 
 s3 = m.add_scalebar(
@@ -25,7 +26,7 @@
     scale_props=dict(width=3, colors=(*["w", "darkred"] * 2, *["w"] * 5, "darkred")),
     patch_props=dict(fc=(0.25, 0.25, 0.25, 0.8), ec="k", lw=0.5, offsets=(1, 1, 1, 2)),
     label_props=dict(
-        every=(1, 4, 10), color="w", rotation=45, weight="bold", family="Impact"
+        every=(1, 4, 10), color="w", rotation=45, weight="bold"  # , family="Impact"
     ),
     line_props=dict(color="w"),
 )

environment.yml

@@ -36,6 +36,7 @@ dependencies:
   - coveralls
   - pytest
   - pytest-cov
+  - pytest-mpl
   # --------------for testing the docs
   # (e.g. parsing .rst code-blocks and Jupyter Notebooks)
   - docutils

eomaps/_blit_manager.py

@@ -268,7 +268,9 @@ def _get_renderer(self):
 
     def _get_all_map_axes(self):
         maxes = {
-            m.ax for m in (self._m.parent, *self._m.parent._children) if m._new_axis_map
+            m.ax
+            for m in (self._m.parent, *self._m.parent._children)
+            if getattr(m, "_new_axis_map", False)
         }
         return maxes
 
@@ -331,9 +333,9 @@ def _do_on_layer_change(self, layer, new=False):
                 try:
                     f = self._on_layer_change[False].pop(0)
                     f(layer=layer)
-                except Exception:
+                except Exception as ex:
                     _log.error(
-                        "EOmaps: Issue while executing a layer-change action",
+                        f"EOmaps: Issue during layer-change action: {ex}",
                         exc_info=_log.getEffectiveLevel() <= logging.DEBUG,
                     )
 
@@ -352,9 +354,9 @@ def _do_on_layer_change(self, layer, new=False):
                     try:
                         f = single_shot_funcs.pop(0)
                         f(layer=l)
-                    except Exception:
+                    except Exception as ex:
                         _log.error(
-                            "EOmaps: Issue while executing a layer-change action",
+                            f"EOmaps: Issue during layer-change action: {ex}",
                             exc_info=_log.getEffectiveLevel() <= logging.DEBUG,
                         )
 
@@ -430,7 +432,7 @@ def bg_layer(self, val):
         for m in [self._m.parent, *self._m.parent._children]:
             layer_visible = self._layer_is_subset(val, m.layer)
 
-            for cb in m._colorbars:
+            for cb in getattr(m, "_colorbars", []):
                 cb._hide_singular_axes()
 
                 if layer_visible:
@@ -727,8 +729,9 @@ def _do_fetch_bg(self, layer, bbox=None):
 
         # update axes spines and patches since they are used to clip artists!
         for ax in self._get_all_map_axes():
-            ax.spines["geo"]._adjust_location()
-            ax.patch._adjust_location()
+            if "geo" in ax.spines:
+                ax.spines["geo"]._adjust_location()
+                ax.patch._adjust_location()
 
         # use contextmanagers to make sure the background patches are not stored
         # in the buffer regions!
@@ -978,8 +981,11 @@ def add_bg_artist(self, art, layer=None, draw=True):
             and not layer.startswith("__inset_")
         ):
             layer = "__inset_" + str(layer)
+
         if layer in self._bg_artists and art in self._bg_artists[layer]:
-            _log.info(f"EOmaps: Background-artist '{art}' already added")
+            _log.info(
+                f"EOmaps: Background-artist '{art}' already added on layer '{layer}'"
+            )
             return
 
         art.set_animated(True)

eomaps/_data_manager.py

@@ -724,6 +724,153 @@ def _get_current_datasize(self):
         else:
             return 99
 
+    def _sel_c_transp(self, c):
+        return self._select_vals(
+            c.T if self._z_transposed else c,
+            qs=self._last_qs,
+            slices=self._last_slices,
+        )
+
+    def _handle_explicit_colors(self, color):
+        if isinstance(color, (int, float, str, np.number)):
+            # if a scalar is provided, broadcast it
+            pass
+        elif isinstance(color, (list, tuple)) and len(color) in [3, 4]:
+            if all(map(lambda i: isinstance(i, (int, float, np.number)), color)):
+                # check if a tuple of numbers is provided, and if so broadcast
+                # it as a rgb or rgba tuple
+                pass
+            elif all(map(lambda i: isinstance(i, (list, np.ndarray)), color)):
+                # check if a tuple of lists or arrays is provided, and if so,
+                # broadcast them as RGB arrays
+                color = self._sel_c_transp(
+                    np.rec.fromarrays(np.broadcast_arrays(*color))
+                )
+        elif isinstance(color, np.ndarray) and (color.shape[-1] in [3, 4]):
+            color = self._sel_c_transp(np.rec.fromarrays(color.T))
+        elif isinstance(color, np.ndarray) and (color.shape[-1] in [3, 4]):
+            color = self._sel_c_transp(np.rec.fromarrays(color.T))
+        else:
+            # still use np.asanyarray in here in case lists are provided
+            color = self._sel_c_transp(np.asanyarray(color).reshape(self.m._zshape))
+
+        return color
+
+    @staticmethod
+    def _convert_1d_to_2d(data, x, y, fill_value=np.nan):
+        """A function to convert 1D vectors + data into 2D."""
+
+        if _log.getEffectiveLevel() <= logging.DEBUG:
+            _log.debug(
+                "EOmaps: Required conversion of 1D arrays to 2D for 'raster'"
+                "shape might be slow and consume a lot of memory!"
+            )
+
+        x, y, data = map(np.asanyarray, (x, y, data))
+        assert (
+            x.size == y.size == data.size
+        ), "EOmaps: You cannot use 1D arrays with different sizes for x, y and data"
+
+        x_vals, x_idx = np.unique(x, return_inverse=True)
+        y_vals, y_idx = np.unique(y, return_inverse=True)
+        # Get output array shape
+        m, n = (x_vals.size, y_vals.size)
+
+        # Get linear indices to be used as IDs with bincount
+        lidx = np.ravel_multi_index(np.vstack((x_idx, y_idx)), (m, n))
+        idx2d = np.unravel_index(lidx, (m, n))
+
+        # Distribute data to 2D
+
+        if not np.issubdtype(data.dtype, np.integer):
+            # Integer-dtypes do not support None!
+            data2d = np.full((m, n), fill_value=fill_value, dtype=data.dtype)
+            data2d[idx2d] = data
+
+        else:
+            # use smallest possible value as fill-value
+            fill_value = np.iinfo(data.dtype).min
+            data2d = np.full((m, n), fill_value=fill_value, dtype=data.dtype)
+            data2d[idx2d] = data
+
+            mask2d = np.full((m, n), fill_value=True, dtype=bool)
+            mask2d[idx2d] = False
+
+            data2d = np.ma.masked_array(data2d, mask2d)
+
+        # Distribute coordinates to 2D
+        x_vals, y_vals = np.meshgrid(x_vals, y_vals, indexing="ij")
+
+        return data2d, x_vals, y_vals
+
+    def _get_coll(self, props, **kwargs):
+        # handle selection of explicitly provided facecolors
+        # (e.g. for rgb composites)
+
+        # allow only one of the synonyms "color", "fc" and "facecolor"
+        if (
+            np.count_nonzero(
+                [kwargs.get(i, None) is not None for i in ["color", "fc", "facecolor"]]
+            )
+            > 1
+        ):
+            raise TypeError(
+                "EOmaps: only one of 'color', 'facecolor' or 'fc' " "can be specified!"
+            )
+
+        explicit_fc = False
+        for key in ("color", "facecolor", "fc"):
+            if kwargs.get(key, None) is not None:
+                explicit_fc = True
+                kwargs[key] = self._handle_explicit_colors(kwargs[key])
+
+        # don't pass the array if explicit facecolors are set
+        if explicit_fc and self.m.shape.name not in ["contour"]:
+            args = dict(array=None, cmap=None, norm=None, **kwargs)
+        else:
+            args = dict(
+                array=props["z_data"],
+                cmap=getattr(self.m, "_cbcmap", "Reds"),
+                norm=getattr(self.m, "_norm", None),
+                **kwargs,
+            )
+
+        if (
+            self.m.shape.name in ["contour"]
+            and len(self.m._xshape) == 2
+            and len(self.m._yshape) == 2
+        ):
+            # if 2D data is provided for a contour plot, keep the data 2d!
+            coll = self.m.shape.get_coll(props["xorig"], props["yorig"], "in", **args)
+        elif self.m.shape.name in ["raster"]:
+            # if input-data is 1D, try to convert data to 2D (required for raster)
+            # TODO make an explicit data-conversion function for 2D-only shapes
+            if len(self.m._xshape) == 2 and len(self.m._yshape) == 2:
+                coll = self.m.shape.get_coll(
+                    props["xorig"], props["yorig"], "in", **args
+                )
+            else:
+                data2d, x2d, y2d = self._convert_1d_to_2d(
+                    data=props["z_data"].ravel(),
+                    x=props["x0"].ravel(),
+                    y=props["y0"].ravel(),
+                )
+
+                if args["array"] is not None:
+                    args["array"] = data2d
+
+                coll = self.m.shape.get_coll(x2d, y2d, "out", **args)
+
+        else:
+            # convert to 1D for further processing
+            if args["array"] is not None:
+                args["array"] = args["array"].ravel()
+
+            coll = self.m.shape.get_coll(
+                props["x0"].ravel(), props["y0"].ravel(), "out", **args
+            )
+        return coll
+
     def on_fetch_bg(self, layer=None, bbox=None, check_redraw=True):
         # TODO support providing a bbox as extent?
         if layer is None:
@@ -757,7 +904,7 @@ def on_fetch_bg(self, layer=None, bbox=None, check_redraw=True):
             # remove previous collection from the map
             self._remove_existing_coll()
             # draw the new collection
-            coll = self.m._get_coll(props, **self.m._coll_kwargs)
+            coll = self._get_coll(props, **self.m._coll_kwargs)
             coll.set_clim(self.m._vmin, self.m._vmax)
 
             coll.set_label("Dataset " f"({self.m.shape.name}  |  {self.z_data.shape})")