Use matplotlib default colourmap

continuous-integration/requirements-3.12.txt

@@ -184,7 +184,7 @@ pytest==9.0.1
     #   pytest-mpl
 pytest-cov==7.0.0
     # via emsarray (pyproject.toml)
-pytest-mpl==0.17.0
+pytest-mpl==0.18.0
     # via emsarray (pyproject.toml)
 python-dateutil==2.9.0.post0
     # via

continuous-integration/requirements-3.13.txt

@@ -184,7 +184,7 @@ pytest==9.0.1
     #   pytest-mpl
 pytest-cov==7.0.0
     # via emsarray (pyproject.toml)
-pytest-mpl==0.17.0
+pytest-mpl==0.18.0
     # via emsarray (pyproject.toml)
 python-dateutil==2.9.0.post0
     # via

continuous-integration/requirements-3.14.txt

@@ -184,7 +184,7 @@ pytest==9.0.1
     #   pytest-mpl
 pytest-cov==7.0.0
     # via emsarray (pyproject.toml)
-pytest-mpl==0.17.0
+pytest-mpl==0.18.0
     # via emsarray (pyproject.toml)
 python-dateutil==2.9.0.post0
     # via

docs/examples/kgari-transect.py

@@ -4,7 +4,7 @@
 import emsarray
 from emsarray import plot, transect
 
-dataset_url = 'https://thredds.nci.org.au/thredds/dodsC/fx3/model_data/gbr4_bgc_GBR4_H2p0_B2p0_Chyd_Dcrt.ncml'
+dataset_url = 'https://thredds.nci.org.au/thredds/dodsC/fx3/gbr4_H4p0_ABARRAr2_OBRAN2020_FG2Gv3_Dhnd/gbr4_simple_2022-10-31.nc'
 dataset = emsarray.open_dataset(dataset_url).isel(time=-1)
 dataset = dataset.ems.select_variables(['botz', 'temp'])
 
@@ -34,7 +34,9 @@
     dataset, line, dataset['temp'],
     figsize=(7.9, 3),
     bathymetry=dataset['botz'],
-    landmarks=landmarks)
+    landmarks=landmarks,
+    title="Temperature",
+    cmap='Oranges_r')
 figure.savefig('kgari-transect.png')
 
 # Plot the path of the transect
@@ -43,14 +45,15 @@
 axes.set_aspect(aspect='equal', adjustable='datalim')
 axes.set_title('Transect path')
 axes.add_collection(dataset.ems.make_poly_collection(
-    dataset['botz'], cmap='Blues_r', edgecolor='face',
+    dataset['botz'], cmap='Blues', clim=(0, 2000), edgecolor='face',
     linewidth=0.5, zorder=0))
+axes = figure.axes[0]
+axes.set_extent(plot.bounds_to_extent(line.envelope.buffer(0.2).bounds))
+axes.plot(*line.coords.xy, zorder=2, c='orange', linewidth=4)
+
 plot.add_coast(axes, zorder=1)
 plot.add_gridlines(axes)
 plot.add_landmarks(axes, landmarks)
-axes = figure.axes[0]
-axes.set_extent(plot.bounds_to_extent(line.envelope.buffer(0.2).bounds))
-axes.plot(*line.coords.xy, zorder=2)
 figure.savefig('kgari-path.png')
 
 pyplot.show(block=True)

docs/releases/development.rst

@@ -24,3 +24,7 @@ Next release (in development)
   which is a backwards incompatible change
   but is difficult to add meaningful backwards compatible support
   (:issue:`109`, :pr:`204`)
+* Use default matplotlib colour map when plotting instead of "jet".
+  In practice this will usually be "viridis"
+  unless the user has changed their local defaults
+  (:pr:`206`).

pyproject.toml

@@ -89,12 +89,6 @@ where = ["src"]
 mypkg = ["py.typed"]
 
 [tool.pytest.ini_options]
-addopts = [
-	# TODO Work around till the mpl-baseline-path ini option is included in the
-	# next pytest-mpl release.
-	"--mpl-baseline-path", "tests/baseline_images",
-]
-
 testpaths = ["tests"]
 filterwarnings = [
 	"error",
@@ -106,9 +100,8 @@ markers = [
 ]
 
 mpl-use-full-test-name = true
-# TODO This option will be included in the next version of pytest-mpl.
-# Till then, it is added using addopts above
-# mpl-baseline-path = "tests/baseline_images"
+mpl-baseline-path = "tests/baseline_images"
+mpl-default-style = "default"
 
 [tool.mypy]
 python_version = "3.12"

src/emsarray/plot.py

@@ -130,7 +130,7 @@ def add_landmarks(
         # Plot the temperature
         temperature = dataset.ems.make_poly_collection(
             dataset['temp'].isel(time=0, k=-1),
-            cmap='jet', edgecolor='face', zorder=0)
+            cmap='viridis', edgecolor='face', zorder=0)
         axes.add_collection(temperature)
         figure.colorbar(temperature, label='°C')
 
@@ -321,7 +321,7 @@ def plot_on_figure(
     if scalar is not None:
         # Plot a scalar variable on the polygons using a colour map
         collection = convention.make_poly_collection(
-            scalar, cmap='jet', edgecolor='face')
+            scalar, edgecolor='face')
         axes.add_collection(collection)
         units = scalar.attrs.get('units')
         figure.colorbar(collection, ax=axes, location='right', label=units)
@@ -437,7 +437,7 @@ def animate_on_figure(
         # Plot a scalar variable on the polygons using a colour map
         scalar_values = convention.ravel(scalar).values[:, convention.mask]
         collection = convention.make_poly_collection(
-            cmap='jet', edgecolor='face',
+            edgecolor='face',
             clim=(numpy.nanmin(scalar_values), numpy.nanmax(scalar_values)))
         axes.add_collection(collection)
         collection.set_animated(True)

src/emsarray/transect.py

@@ -8,7 +8,7 @@
 import shapely
 import xarray
 from cartopy import crs
-from matplotlib import animation, colormaps, pyplot
+from matplotlib import animation, pyplot
 from matplotlib.artist import Artist
 from matplotlib.axes import Axes
 from matplotlib.collections import PolyCollection
@@ -558,7 +558,7 @@ def plot_on_figure(
         trim_nans: bool = True,
         clamp_to_surface: bool = True,
         bathymetry: xarray.DataArray | None = None,
-        cmap: str | Colormap = 'jet',
+        cmap: str | Colormap | None = None,
         clim: tuple[float, float] | None = None,
         ocean_floor_colour: str = 'black',
         landmarks: list[Landmark] | None = None,
@@ -620,7 +620,7 @@ def animate_on_figure(
         trim_nans: bool = True,
         clamp_to_surface: bool = True,
         bathymetry: xarray.DataArray | None = None,
-        cmap: str | Colormap = 'jet',
+        cmap: str | Colormap | None = None,
         clim: tuple[float, float] | None = None,
         ocean_floor_colour: str = 'black',
         landmarks: list[Landmark] | None = None,
@@ -717,7 +717,7 @@ def _plot_on_figure(
         trim_nans: bool = True,
         clamp_to_surface: bool = True,
         bathymetry: xarray.DataArray | None = None,
-        cmap: str | Colormap = 'jet',
+        cmap: str | Colormap | None = None,
         clim: tuple[float, float] | None = None,
         ocean_floor_colour: str = 'black',
         landmarks: list[Landmark] | None = None,
@@ -774,8 +774,7 @@ def _plot_on_figure(
         if title is not None:
             axes.set_title(title)
 
-        if isinstance(cmap, str):
-            cmap = colormaps[cmap].copy()
+        cmap = pyplot.get_cmap(cmap).copy()
         cmap.set_bad(ocean_floor_colour)
 
         # Find a min/max from the data if clim isn't provided and the data array is not empty.