Use x and y parameters for Image trace in imshow (for RGB or binary_s…

…tring=True) (#2761)

* take x and y into account when using Image trace

* x and y parameters are now used for Image trace in imshow

* raise ValueError when x and y don't have numerical dtype for Image trace

* better error message

* black

packages/python/plotly/plotly/express/_imshow.py

@@ -204,23 +204,19 @@ def imshow(
     args = locals()
     apply_default_cascade(args)
     labels = labels.copy()
+    img_is_xarray = False
     # ----- Define x and y, set labels if img is an xarray -------------------
     if xarray_imported and isinstance(img, xarray.DataArray):
-        if binary_string:
-            raise ValueError(
-                "It is not possible to use binary image strings for xarrays."
-                "Please pass your data as a numpy array instead using"
-                "`img.values`"
-            )
+        img_is_xarray = True
         y_label, x_label = img.dims[0], img.dims[1]
         # np.datetime64 is not handled correctly by go.Heatmap
         for ax in [x_label, y_label]:
             if np.issubdtype(img.coords[ax].dtype, np.datetime64):
                 img.coords[ax] = img.coords[ax].astype(str)
         if x is None:
-            x = img.coords[x_label]
+            x = img.coords[x_label].values
         if y is None:
-            y = img.coords[y_label]
+            y = img.coords[y_label].values
         if aspect is None:
             aspect = "auto"
         if labels.get("x", None) is None:
@@ -330,6 +326,42 @@ def imshow(
                 _vectorize_zvalue(zmin, mode="min"),
                 _vectorize_zvalue(zmax, mode="max"),
             )
+        x0, y0, dx, dy = (None,) * 4
+        error_msg_xarray = (
+            "Non-numerical coordinates were passed with xarray `img`, but "
+            "the Image trace cannot handle it. Please use `binary_string=False` "
+            "for 2D data or pass instead the numpy array `img.values` to `px.imshow`."
+        )
+        if x is not None:
+            x = np.asanyarray(x)
+            if np.issubdtype(x.dtype, np.number):
+                x0 = x[0]
+                dx = x[1] - x[0]
+            else:
+                error_msg = (
+                    error_msg_xarray
+                    if img_is_xarray
+                    else (
+                        "Only numerical values are accepted for the `x` parameter "
+                        "when an Image trace is used."
+                    )
+                )
+                raise ValueError(error_msg)
+        if y is not None:
+            y = np.asanyarray(y)
+            if np.issubdtype(y.dtype, np.number):
+                y0 = y[0]
+                dy = y[1] - y[0]
+            else:
+                error_msg = (
+                    error_msg_xarray
+                    if img_is_xarray
+                    else (
+                        "Only numerical values are accepted for the `y` parameter "
+                        "when an Image trace is used."
+                    )
+                )
+                raise ValueError(error_msg)
         if binary_string:
             if zmin is None and zmax is None:  # no rescaling, faster
                 img_rescaled = img
@@ -355,13 +387,24 @@ def imshow(
                 compression=binary_compression_level,
                 ext=binary_format,
             )
-            trace = go.Image(source=img_str)
+            trace = go.Image(source=img_str, x0=x0, y0=y0, dx=dx, dy=dy)
         else:
             colormodel = "rgb" if img.shape[-1] == 3 else "rgba256"
-            trace = go.Image(z=img, zmin=zmin, zmax=zmax, colormodel=colormodel)
+            trace = go.Image(
+                z=img,
+                zmin=zmin,
+                zmax=zmax,
+                colormodel=colormodel,
+                x0=x0,
+                y0=y0,
+                dx=dx,
+                dy=dy,
+            )
         layout = {}
-        if origin == "lower":
+        if origin == "lower" or (dy is not None and dy < 0):
             layout["yaxis"] = dict(autorange=True)
+        if dx is not None and dx < 0:
+            layout["xaxis"] = dict(autorange="reversed")
     else:
         raise ValueError(
             "px.imshow only accepts 2D single-channel, RGB or RGBA images. "

packages/python/plotly/plotly/tests/test_core/test_px/test_imshow.py

@@ -5,6 +5,7 @@
 from PIL import Image
 from io import BytesIO
 import base64
+import datetime
 from plotly.express.imshow_utils import rescale_intensity
 
 img_rgb = np.array([[[255, 0, 0], [0, 255, 0], [0, 0, 255]]], dtype=np.uint8)
@@ -204,6 +205,37 @@ def test_imshow_labels_and_ranges():
     with pytest.raises(ValueError):
         fig = px.imshow([[1, 2], [3, 4], [5, 6]], x=["a"])
 
+    img = np.ones((2, 2), dtype=np.uint8)
+    fig = px.imshow(img, x=["a", "b"])
+    assert fig.data[0].x == ("a", "b")
+
+    with pytest.raises(ValueError):
+        img = np.ones((2, 2, 3), dtype=np.uint8)
+        fig = px.imshow(img, x=["a", "b"])
+
+    img = np.ones((2, 2), dtype=np.uint8)
+    base = datetime.datetime(2000, 1, 1)
+    fig = px.imshow(img, x=[base, base + datetime.timedelta(hours=1)])
+    assert fig.data[0].x == (
+        datetime.datetime(2000, 1, 1, 0, 0),
+        datetime.datetime(2000, 1, 1, 1, 0),
+    )
+
+    with pytest.raises(ValueError):
+        img = np.ones((2, 2, 3), dtype=np.uint8)
+        base = datetime.datetime(2000, 1, 1)
+        fig = px.imshow(img, x=[base, base + datetime.timedelta(hours=1)])
+
+
+def test_imshow_ranges_image_trace():
+    fig = px.imshow(img_rgb, x=[1, 11, 21])
+    assert fig.data[0].dx == 10
+    assert fig.data[0].x0 == 1
+    fig = px.imshow(img_rgb, x=[21, 11, 1])
+    assert fig.data[0].dx == -10
+    assert fig.data[0].x0 == 21
+    assert fig.layout.xaxis.autorange == "reversed"
+
 
 def test_imshow_dataframe():
     df = px.data.medals_wide(indexed=False)