Merge pull request #1885 from plotly/imshow_px

Move imshow closer to px pattern

Author: nicolaskruchten

Diff for: packages/python/plotly/plotly/express/_doc.py

@@ -283,7 +283,7 @@
     ],
     title=["str", "The figure title."],
     template=[
-        "str or Plotly.py template object",
+        "or dict or plotly.graph_objects.layout.Template instance",
         "The figure template name or definition.",
     ],
     width=["int (default `None`)", "The figure width in pixels."],

Diff for: packages/python/plotly/plotly/express/_imshow.py

@@ -1,4 +1,6 @@
 import plotly.graph_objs as go
+from _plotly_utils.basevalidators import ColorscaleValidator
+from ._core import apply_default_cascade
 import numpy as np  # is it fine to depend on np here?
 
 _float_types = []
@@ -54,7 +56,19 @@ def _infer_zmax_from_type(img):
             return 2 ** 32
 
 
-def imshow(img, zmin=None, zmax=None, origin=None, colorscale=None):
+def imshow(
+    img,
+    zmin=None,
+    zmax=None,
+    origin=None,
+    color_continuous_scale=None,
+    color_continuous_midpoint=None,
+    range_color=None,
+    title=None,
+    template=None,
+    width=None,
+    height=None,
+):
     """
     Display an image, i.e. data on a 2D regular raster.
 
@@ -74,16 +88,38 @@ def imshow(img, zmin=None, zmax=None, origin=None, colorscale=None):
         zmin and zmax correspond to the min and max values of the datatype for integer
         datatypes (ie [0-255] for uint8 images, [0, 65535] for uint16 images, etc.). For
         a multichannel image of floats, the max of the image is computed and zmax is the
-        smallest power of 256 (1, 255, 65535) greater than this max value, 
+        smallest power of 256 (1, 255, 65535) greater than this max value,
         with a 5% tolerance. For a single-channel image, the max of the image is used.
 
     origin : str, 'upper' or 'lower' (default 'upper')
         position of the [0, 0] pixel of the image array, in the upper left or lower left
         corner. The convention 'upper' is typically used for matrices and images.
 
-    colorscale : str
-        colormap used to map scalar data to colors (for a 2D image). This parameter is not used for
-        RGB or RGBA images.
+    color_continuous_scale : str or list of str
+        colormap used to map scalar data to colors (for a 2D image). This parameter is
+        not used for RGB or RGBA images. If a string is provided, it should be the name
+        of a known color scale, and if a list is provided, it should be a list of CSS-
+        compatible colors.
+
+    color_continuous_midpoint : number
+        If set, computes the bounds of the continuous color scale to have the desired
+        midpoint.
+
+    range_color : list of two numbers
+        If provided, overrides auto-scaling on the continuous color scale, including
+        overriding `color_continuous_midpoint`.
+
+    title : str
+        The figure title.
+
+    template : str or dict or plotly.graph_objects.layout.Template instance
+        The figure template name or definition.
+
+    width : number
+        The figure width in pixels.
+
+    height: number
+        The figure height in pixels, defaults to 600.
 
     Returns
     -------
@@ -101,21 +137,33 @@ def imshow(img, zmin=None, zmax=None, origin=None, colorscale=None):
     In order to update and customize the returned figure, use
     `go.Figure.update_traces` or `go.Figure.update_layout`.
     """
+    args = locals()
+    apply_default_cascade(args)
+
     img = np.asanyarray(img)
     # Cast bools to uint8 (also one byte)
     if img.dtype == np.bool:
         img = 255 * img.astype(np.uint8)
 
     # For 2d data, use Heatmap trace
     if img.ndim == 2:
-        if colorscale is None:
-            colorscale = "gray"
-        trace = go.Heatmap(z=img, zmin=zmin, zmax=zmax, colorscale=colorscale)
+        trace = go.Heatmap(z=img, zmin=zmin, zmax=zmax, coloraxis="coloraxis1")
         autorange = True if origin == "lower" else "reversed"
         layout = dict(
             xaxis=dict(scaleanchor="y", constrain="domain"),
             yaxis=dict(autorange=autorange, constrain="domain"),
         )
+        colorscale_validator = ColorscaleValidator("colorscale", "imshow")
+        range_color = range_color or [None, None]
+        layout["coloraxis1"] = dict(
+            colorscale=colorscale_validator.validate_coerce(
+                args["color_continuous_scale"]
+            ),
+            cmid=color_continuous_midpoint,
+            cmin=range_color[0],
+            cmax=range_color[1],
+        )
+
     # For 2D+RGB data, use Image trace
     elif img.ndim == 3 and img.shape[-1] in [3, 4]:
         if zmax is None and img.dtype is not np.uint8:
@@ -127,8 +175,17 @@ def imshow(img, zmin=None, zmax=None, origin=None, colorscale=None):
             layout["yaxis"] = dict(autorange=True)
     else:
         raise ValueError(
-            "px.imshow only accepts 2D grayscale, RGB or RGBA images. "
+            "px.imshow only accepts 2D single-channel, RGB or RGBA images. "
             "An image of shape %s was provided" % str(img.shape)
         )
+
+    layout_patch = dict()
+    for v in ["title", "height", "width"]:
+        if args[v]:
+            layout_patch[v] = args[v]
+    if "title" not in layout_patch and args["template"].layout.margin.t is None:
+        layout_patch["margin"] = {"t": 60}
     fig = go.Figure(data=trace, layout=layout)
+    fig.update_layout(layout_patch)
+    fig.update_layout(template=args["template"], overwrite=True)
     return fig

Diff for: packages/python/plotly/plotly/tests/test_core/test_px/test_imshow.py

@@ -50,9 +50,10 @@ def test_origin():
 
 def test_colorscale():
     fig = px.imshow(img_gray)
-    assert fig.data[0].colorscale[0] == (0.0, "rgb(0, 0, 0)")
-    fig = px.imshow(img_gray, colorscale="Viridis")
-    assert fig.data[0].colorscale[0] == (0.0, "#440154")
+    plasma_first_color = px.colors.sequential.Plasma[0]
+    assert fig.layout.coloraxis1.colorscale[0] == (0.0, plasma_first_color)
+    fig = px.imshow(img_gray, color_continuous_scale="Viridis")
+    assert fig.layout.coloraxis1.colorscale[0] == (0.0, "#440154")
 
 
 def test_wrong_dimensions():