Add plotly as a backend

astrowidgets/plotly.py

@@ -0,0 +1,158 @@
+import ipywidgets as ipw
+from astro_image_display_api.image_viewer_logic import ImageViewerLogic
+import astropy.visualization as apviz
+import numpy as np
+from astropy.nddata import NDData
+import plotly.graph_objects as go
+import plotly.express as px
+
+def docs_from_super_if_missing(cls):
+    """
+    Decorator to copy the docstrings from the interface methods to the
+    methods in the class.
+    """
+    for name, method in cls.__dict__.items():
+        if not name.startswith("_"):
+            if method.__doc__:
+                continue
+            interface_method = getattr(ImageViewerLogic, name, None)
+
+            if interface_method:
+                method.__doc__ = interface_method.__doc__
+    return cls
+
+@docs_from_super_if_missing
+class ImageWidget(ipw.VBox, ImageViewerLogic):
+    def __init__(self, *args, display_width=500, display_aspect_ratio=1):
+        super().__init__(*args)
+        print('Initializing ImageWidget')
+        self._set_up_catalog_image_dicts()
+
+        self._astro_im = go.FigureWidget(data=[go.Heatmap(z=np.zeros((10, 10)))])
+        self._default_cuts = apviz.MinMaxInterval()
+        self._default_stretch = None
+
+        self._data = None
+        self._wcs = None
+
+        # Use this to manage whether or not to send changes in zoom level
+        # to the viewer.
+        self._viewport_change_source_is_gui = False
+
+        # Provide an Output widget to which prints can be directed for
+        # debugging.
+        self._print_out = ipw.Output()
+
+        self.marker = {'color': 'red', 'radius': 20, 'type': 'square'}
+        self._cuts = apviz.AsymmetricPercentileInterval(1, 99)
+
+        self._cursor = ipw.HTML('Coordinates show up here')
+
+        self.children = [self._astro_im, self._cursor]
+
+    def _interval_and_stretch(self, stretch=None, cuts=None):
+        """
+        Stretch and normalize the data before sending to the viewer.
+        """
+        interval = cuts or self._default_cuts
+        intervaled = interval(np.asarray(self._data))
+
+        stretch = stretch or self._default_stretch
+        if stretch:
+            stretched = stretch(intervaled)
+        else:
+            stretched = intervaled
+
+        return stretched
+
+    def _send_data(self, reset_view=True, stretch=None, cuts=None):
+        if self._data is not None:
+            print('Sending data to viewer')
+            fig = px.imshow(
+                self._interval_and_stretch(stretch=stretch, cuts=cuts)
+            )
+            print('Data sent to viewer', fig.data)
+            self._astro_im.add_trace(fig.data[0])
+
+
+    @property
+    def _current_image_label(self):
+        """
+        Image label for the most recently loaded image
+        """
+        return list(self._images.keys())[-1]
+
+    def set_stretch(self, value, image_label=None, **kwargs):
+        super().set_stretch(value, image_label=image_label, **kwargs)
+        self._send_data(stretch=value)
+
+    def set_cuts(self, value, image_label=None, **kwargs):
+        super().set_cuts(value, image_label=image_label, **kwargs)
+        self._send_data(cuts=self.get_cuts(image_label=image_label))
+
+    @property
+    def viewer(self):
+        return self._astro_im
+
+    # The methods, grouped loosely by purpose
+    def load_image(self, image, image_label=None, **kwargs):
+        super().load_image(image, image_label=image_label, **kwargs)
+        data = self.get_image(image_label=image_label)
+
+        self._data = data.data if isinstance(data, NDData) else data
+        self._send_data()
+
+    def set_colormap(self, cmap_name, image_label=None, **kwargs):
+        super().set_colormap(cmap_name, image_label=image_label, **kwargs)
+        self._astro_im.set_color(bqcolors(cmap_name, reverse=False))
+
+    def load_catalog(
+        self,
+        table,
+        **kwargs
+    ):
+        super().load_catalog(table, **kwargs)
+        catalog_label = kwargs.pop("catalog_label", None)
+        this_catalog = self.get_catalog(catalog_label=catalog_label)
+        self._astro_im.plot_named_markers(
+            this_catalog["x"],
+            this_catalog["y"],
+            str(catalog_label),
+            **self.get_catalog_style(catalog_label=catalog_label)
+        )
+
+    def set_catalog_style(
+            self,
+            catalog_label=None,
+            shape="circle",
+            color="red",
+            size=5,
+            **kwargs
+        ):
+        super().set_catalog_style(
+            catalog_label=catalog_label,
+            shape=shape,
+            color=color,
+            size=size,
+            **kwargs
+        )
+        this_catalog = self.get_catalog(catalog_label=catalog_label)
+
+        self._astro_im.plot_named_markers(
+            this_catalog["x"],
+            this_catalog["y"],
+            str(catalog_label),
+            color=color,
+            size=size**2,  # bqplot expects size in pixels squared
+            shape=shape,
+        )
+
+    @property
+    def print_out(self):
+        """
+        Return an output widget for display in the notebook which
+        captures any printed output produced by the viewer widget.
+
+        Intended primarily for debugging.
+        """
+        return self._print_out