use image comparison in tests

.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/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"),
 )

pyproject.toml

@@ -76,6 +76,12 @@ gui = [
     "qtpy"
     ]
 
+test = [
+    "eomaps[io, classify, wms, shade, gui, test]",
+    "pytest",
+    "pytest-mpl"
+]
+
 [project.scripts]
 eomaps = "eomaps.scripts.open:cli"
 
@@ -84,6 +90,9 @@ Documentation = "https://eomaps.readthedocs.io/"
 Repository = "https://github.com/raphaelquast/eomaps"
 
 [tool.pytest.ini_options]
+mpl-use-full-test-name = "True"
+mpl-default-style = "default"
+mpl-results-path = "img_comparison_results"
 filterwarnings = [
     "ignore:Downloading*",
     "ignore:Passing a SingleBlockManager to Series is deprecated *:DeprecationWarning",

tests/_testdata/testfile.csv

@@ -2,3 +2,6 @@ a,x,y,data
 0,1,2,1
 1,3,5,3
 2,4,6,5
+10,23,45,67
+4, -17, -67, 20
+16, 15, 16, 78

tests/test_examples.py

@@ -2,12 +2,18 @@
 from pathlib import Path
 import matplotlib.pyplot as plt
 import unittest
+import pytest
+import numpy as np
 
 
 def gen_test(name, code):
+    @pytest.mark.mpl_image_compare()
     def test(*args, **kwargs):
         try:
+            np.random.seed(0)  # make tests descriptive
             exec(code)
+
+            return locals()["m"]
         except Exception as ex:
             raise AssertionError(f"Example '{name}' failed.") from ex
         finally:

tests/test_from_file.py

@@ -1,72 +1,60 @@
-import matplotlib as mpl
-
-mpl.rcParams["toolbar"] = "None"
-
-import unittest
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-
+import pytest
 from eomaps import Maps
 from pathlib import Path
 
-
-class TestFromFile(unittest.TestCase):
-    def setUp(self):
-        self.csvpath = Path(__file__).parent / "_testdata" / "testfile.csv"
-        self.tiffpath = Path(__file__).parent / "_testdata" / "testfile.tif"
-        self.netcdfpath = Path(__file__).parent / "_testdata" / "testfile.nc"
-        pass
-
-    def test_CSV(self):
-        data = Maps.read_file.CSV(
-            self.csvpath, x="x", y="y", parameter="data", crs=4326
-        )
-        m = Maps.from_file.CSV(
-            self.csvpath, x="x", y="y", parameter="data", data_crs=4326
-        )
-
-        m2 = m.new_layer_from_file.CSV(
-            self.csvpath,
-            x="x",
-            y="y",
-            parameter="data",
-            data_crs=4326,
-            layer="second",
-            cmap="cividis",
-            extent=(-20, 20, -56, 78),
-        )
-        m.show_layer(m2.layer)
-
-        plt.close("all")
-
-    def test_GeoTIFF(self):
-        data = Maps.read_file.GeoTIFF(self.tiffpath)
-        m = Maps.from_file.GeoTIFF(self.tiffpath)
-
-        m2 = m.new_layer_from_file.GeoTIFF(
-            self.tiffpath,
-            layer="second",
-            cmap="cividis",
-            shape="shade_points",
-            extent=(7, 9, 41, 42),
-        )
-        m.show_layer(m2.layer)
-        plt.close("all")
-
-    def test_NetCDF(self):
-        data = Maps.read_file.NetCDF(self.netcdfpath, data_crs=4326)
-        m = Maps.from_file.NetCDF(
-            self.netcdfpath, data_crs=4326, shape="voronoi_diagram"
-        )
-
-        m2 = m.new_layer_from_file.NetCDF(
-            self.netcdfpath,
-            layer="second",
-            cmap="cividis",
-            shape="shade_raster",
-            data_crs=4326,
-            extent=((7, 9, 41, 42), 4326),
-        )
-        m.show_layer(m2.layer)
-        plt.close("all")
+paths = {
+    "CSV": Path(__file__).parent / "_testdata" / "testfile.csv",
+    "GeoTIFF": Path(__file__).parent / "_testdata" / "testfile.tif",
+    "NetCDF": Path(__file__).parent / "_testdata" / "testfile.nc",
+}
+
+read_args = {
+    "CSV": dict(x="x", y="y", parameter="data", crs=4326),
+    "NetCDF": dict(data_crs=4326),
+}
+
+plot_args = {
+    "CSV": dict(x="x", y="y", parameter="data", data_crs=4326),
+    "NetCDF": dict(data_crs=4326),
+}
+
+style_args = {
+    "CSV": dict(cmap="cividis", shape="ellipses"),
+    "GeoTIFF": dict(shape="raster", extent=(7, 9, 41, 42)),
+    "NetCDF": dict(shape="voronoi_diagram"),
+}
+
+
+@pytest.mark.parametrize("method", ["CSV", "GeoTIFF", "NetCDF"])
+def test_read_file(method):
+    _ = getattr(Maps.read_file, method)(paths[method], **read_args.get(method, {}))
+
+
+@pytest.mark.parametrize("method", ["CSV", "GeoTIFF", "NetCDF"])
+@pytest.mark.mpl_image_compare()
+def test_from_file(method):
+    m = getattr(Maps.from_file, method)(
+        paths[method], **plot_args.get(method, {}), **style_args.get(method, {})
+    )
+    m.add_feature.preset.coastline()
+    m.add_gridlines(lw=2, auto_n=5)
+    return m
+
+
+@pytest.mark.parametrize("method", ["CSV", "GeoTIFF", "NetCDF"])
+@pytest.mark.mpl_image_compare()
+def test_new_layer_from_file(method):
+
+    m = Maps(Maps.CRS.Mollweide(), layer="all")
+    m.add_feature.preset.coastline()
+    m.add_gridlines(lw=2, auto_n=5)
+
+    m2 = getattr(m.new_layer_from_file, method)(
+        paths[method],
+        **plot_args.get(method, {}),
+        **style_args.get(method, {}),
+        layer="second",
+    )
+    m.show_layer(m2.layer)
+
+    return m

tests/test_plot_shapes.py

@@ -41,12 +41,13 @@ def close_all():
 
 @pytest.mark.usefixtures("close_all")
 @pytest.mark.parametrize("data", testdata, ids=ids)
+@pytest.mark.mpl_image_compare()
 def test_hexbin(data):
     m = Maps(ax=221, figsize=(10, 6))
     m.set_data(**data)
     m.set_shape.hexbin(size=(10, 5))
     m.plot_map()
-    m.add_colorbar()
+    cb = m.add_colorbar()
 
     m2 = m.new_map(ax=222, inherit_data=True)
     m2.set_shape.hexbin(size=20, aggregator="median")
@@ -64,9 +65,12 @@ def test_hexbin(data):
     m4.plot_map(cmap="RdYlBu")
     m4.add_colorbar()
 
+    return m
+
 
 @pytest.mark.usefixtures("close_all")
 @pytest.mark.parametrize("data", testdata, ids=ids)
+@pytest.mark.mpl_image_compare()
 def test_contour(data):
     m = Maps(ax=221, figsize=(10, 6))
     m.subplots_adjust(left=0.01, right=0.99)
@@ -89,8 +93,8 @@ def test_contour(data):
     )
 
     m3 = m.new_map(ax=224, inherit_data=True)
-    m3.set_shape.ellipses()
-    m3.plot_map(alpha=0.25)
+    m3.set_shape.voronoi_diagram()
+    m3.plot_map(alpha=0.25, lw=0.25, ec="k")
     cb3 = m3.add_colorbar()
 
     m3_1 = m3.new_layer("contours", inherit_data=True)
@@ -125,30 +129,41 @@ def test_contour(data):
 
     m.show_layer("base", "contours")
 
+    return m
+
 
 @pytest.mark.usefixtures("close_all")
 @pytest.mark.parametrize("data", testdata, ids=ids)
+@pytest.mark.mpl_image_compare()
 def test_shade_points(data):
     m = Maps(ax=221, figsize=(10, 6))
+
     m.set_data(**data)
     m.set_shape.shade_points(aggregator="mean")
+    m.set_shade_dpi(100)
     m.plot_map()
     m.add_colorbar()
 
     m2 = m.new_map(ax=222, inherit_data=True)
-    m.set_shape.shade_points(aggregator="max")
+    m2.set_shape.shade_points(aggregator="max")
+    m2.set_shade_dpi(30)
     m2.plot_map(cmap="RdYlBu")
     m2.add_colorbar()
-    m2.set_shade_dpi(10)
 
     m3 = m.new_map(ax=223, inherit_data=True)
-    m.set_shape.shade_points(aggregator="max")
+    m3.set_shape.shade_points(aggregator="max")
+    m3.set_shade_dpi(20)
     m3.plot_map(cmap="RdYlBu")
     m3.add_colorbar()
-    m3.set_shade_dpi(50)
 
     m4 = m.new_map(ax=224, inherit_data=True)
-    m.set_shape.shade_points(aggregator="max")
+    m4.set_shape.shade_points(aggregator="max")
+    m4.set_shade_dpi(10)
     m4.set_classify.EqualInterval(k=5)
     m4.plot_map(cmap="RdYlBu")
     m4.add_colorbar()
+
+    for mi in [m, m2, m3, m4]:
+        mi.add_title(f"shade dpi = {mi._shade_dpi}")
+
+    return m