Fast image: add binary_string parameter to imshow

.circleci/config.yml

@@ -405,6 +405,9 @@ jobs:
             if [ "${CIRCLE_BRANCH}" != "doc-prod" ]; then
               pip uninstall -y plotly
               cd ../packages/python/plotly
+              # To be removed after plotly.js release
+              pip install inflect black tox
+              python3 setup.py updateplotlyjsdev --devbranch fast-image
               python3 setup.py install
               cd ../../../doc
             fi
@@ -441,7 +444,9 @@ jobs:
               cd ../..
             fi
             tar -zcf build/html.tgz build/html
-            rm -rf build/html build/ipynb
+            # Do not zip so that reviewers can take a look at doc online
+            # rm -rf build/html build/ipynb
+            rm -rf build/ipynb
             cd ..
 
       - run:

doc/python/imshow.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.2'
-      jupytext_version: 1.4.2
+      jupytext_version: 1.3.0
   kernelspec:
     display_name: Python 3
     language: python
@@ -86,6 +86,26 @@ fig = px.imshow(img)
 fig.show()
 ```
 
+### Passing image data as a binary string
+
+... add explanations here about `use_binary_string` and `contrast_rescaling`
+
+```python
+import plotly.express as px
+import numpy as np
+img = np.arange(15**2).reshape((15, 15))
+fig = px.imshow(img, use_binary_string=True)
+fig.show()
+```
+
+```python
+import plotly.express as px
+import numpy as np
+img = np.arange(13**2, dtype=np.uint8).reshape((13, 13))
+fig = px.imshow(img, use_binary_string=True, contrast_rescaling='dtype')
+fig.show()
+```
+
 ### Choose the colorscale to display a single-channel image
 
 You can customize the [continuous color scale](/python/colorscales/) just like with any other Plotly Express function:
@@ -167,7 +187,7 @@ fig.show()
 
 ### Display multichannel image data with go.Image
 
-It is also possible to use the `go.Image` trace from the low-level `graph_objects` API in order to display image data. Note that `go.Image` only accepts multichannel images. For single images, use [`go.Heatmap`](/python/heatmaps).
+It is also possible to use the `go.Image` trace from the low-level `graph_objects` API in order to display image data. Note that `go.Image` only accepts multichannel images. For single-channel images, use [`go.Heatmap`](/python/heatmaps).
 
 Note that the `go.Image` trace is different from the `go.layout.Image` class, which can be used for [adding background images or logos to figures](/python/images).
 
@@ -308,4 +328,4 @@ fig.show(config={'modeBarButtonsToAdd':['drawline',
 ```
 
 #### Reference
-See https://plotly.com/python/reference/#image for more information and chart attribute options!
+See https://plotly.com/python/reference/#image for more information and chart attribute options!

packages/javascript/plotlywidget/package.json

@@ -33,7 +33,7 @@
     "typescript": "~3.1.1"
   },
   "dependencies": {
-    "plotly.js": "^1.54.6",
+    "plotly.js": "https://83625-45646037-gh.circle-artifacts.com/0/plotly.js.tgz",
     "@jupyter-widgets/base": "^2.0.0 || ^3.0.0",
     "lodash": "^4.17.4"
   },

packages/python/plotly/codegen/resources/plot-schema.json

@@ -16979,6 +16979,12 @@
                     "editType": "none",
                     "description": "Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user-driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a `uid` that stays with it as it moves."
                 },
+                "source": {
+                    "valType": "string",
+                    "role": "info",
+                    "editType": "calc",
+                    "description": "Specifies the URL of the image to be used. The URL must be accessible from the domain where the plot code is run, and can be either relative or absolute."
+                },
                 "z": {
                     "valType": "data_array",
                     "role": "data",