Merge pull request #3028 from wxmann/support-floats-in-image-range

Support floats in image_range

src/metpy/plots/declarative.py

@@ -1043,9 +1043,12 @@ def _cmap_obj(self):
     def _norm_obj(self):
         """Return the normalization object.
 
-        Converts the tuple image range to a matplotlib normalization instance.
+        If `image_range` is a matplotlib normalization instance, returns it, otherwise converts
+        the tuple image range to a matplotlib normalization instance.
 
         """
+        if isinstance(self.image_range, plt.Normalize):
+            return self.image_range
         return plt.Normalize(*self.image_range)
 
     def clear(self):
@@ -1302,7 +1305,7 @@ class ColorfillTraits(MetPyHasTraits):
     For example, the Blue-Purple colormap from Matplotlib can be accessed using 'BuPu'.
     """
 
-    image_range = Union([Tuple(Int(allow_none=True), Int(allow_none=True)),
+    image_range = Union([Tuple(Float(allow_none=True), Float(allow_none=True)),
                          Instance(plt.Normalize)], default_value=(None, None))
     image_range.__doc__ = """A tuple of min and max values that represent the range of values
     to color the rasterized image.

tests/plots/test_declarative.py

@@ -7,6 +7,7 @@
 from io import BytesIO
 import warnings
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import pytest
@@ -613,6 +614,60 @@ def test_colorfill(cfeature):
     return pc.figure
 
 
+@pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.0062)
+def test_colorfill_with_image_range(cfeature):
+    """Test that we can use ContourFillPlot with image_range bounds."""
+    data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
+
+    contour = FilledContourPlot()
+    contour.data = data
+    contour.level = 700 * units.hPa
+    contour.field = 'Temperature'
+    contour.colormap = 'coolwarm'
+    contour.colorbar = None
+    contour.image_range = (273.15, 350)
+
+    panel = MapPanel()
+    panel.area = (-110, -60, 25, 55)
+    panel.layers = [cfeature.STATES]
+    panel.plots = [contour]
+
+    pc = PanelContainer()
+    pc.panel = panel
+    pc.size = (8, 8)
+    pc.draw()
+
+    return pc.figure
+
+
+@pytest.mark.mpl_image_compare(
+    remove_text=True, tolerance=0.0062, filename='test_colorfill_with_image_range.png'
+)
+def test_colorfill_with_normalize_instance_image_range(cfeature):
+    """Test that we can use ContourFillPlot with image_range bounds."""
+    data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
+
+    contour = FilledContourPlot()
+    contour.data = data
+    contour.level = 700 * units.hPa
+    contour.field = 'Temperature'
+    contour.colormap = 'coolwarm'
+    contour.colorbar = None
+    contour.image_range = plt.Normalize(vmin=273.15, vmax=350)
+
+    panel = MapPanel()
+    panel.area = (-110, -60, 25, 55)
+    panel.layers = [cfeature.STATES]
+    panel.plots = [contour]
+
+    pc = PanelContainer()
+    pc.panel = panel
+    pc.size = (8, 8)
+    pc.draw()
+
+    return pc.figure
+
+
 @pytest.mark.mpl_image_compare(remove_text=True, tolerance=0.)
 def test_colorfill_horiz_colorbar(cfeature):
     """Test that we can use ContourFillPlot with a horizontal colorbar."""