Nov 12, 2019 · Nov 1, 2019 · Nov 5, 2019 · Nov 6, 2019 · Nov 6, 2019 · Nov 7, 2019
diff --git a/python/imshow.md b/python/imshow.md

 ### Display single-channel 2D image as grayscale

 For a 2D image, `px.imshow` uses a colorscale to map scalar data to colors. The default colorscale is`gray`, ie grayscale images.
 For a 2D image, `px.imshow` uses a colorscale to map scalar data to colors. The default colorscale isthe one of the active template (see [the tutorial on templates](/python/templates/)).

 ```python
 import plotly.express as px
 import plotly.express as px
 import numpy as np
 img = np.arange(100).reshape((10, 10))
 fig = px.imshow(img,colorscale='Viridis')
 fig = px.imshow(img,color_continuous_scale='gray')
 fig.show()
 ```


 The data range and color range are mapped together using the parameters `zmin` and `zmax`, which correspond respectively to the data values mapped to black `[0, 0, 0]` and white `[255, 255, 255]`, or to the extreme colors of the colorscale in the case on single-channel data.

 For single-channel data, the defaults values of `zmin` and `zmax` used by `px.imshow` and `go.Heatmap` are thetheextrema of the data range. For multichannel data, `px.imshow` and `go.Image` use slightly different default values for `zmin` and `zmax`. For `go.Image`, the default value is `zmin=[0, 0, 0]` and `zmax=[255, 255, 255]`, no matter the data type. On the other hand, `px.imshow` adapts the default `zmin` and `zmax` to the data type:
 For single-channel data, the defaults values of `zmin` and `zmax` used by `px.imshow` and `go.Heatmap` are the extrema of the data range. For multichannel data, `px.imshow` and `go.Image` use slightly different default values for `zmin` and `zmax`. For `go.Image`, the default value is `zmin=[0, 0, 0]` and `zmax=[255, 255, 255]`, no matter the data type. On the other hand, `px.imshow` adapts the default `zmin` and `zmax` to the data type:
 - for integer data types, `zmin` and `zmax` correspond to the extreme values of the data type, for example 0 and 255 for `uint8`, 0 and 65535 for `uint16`, etc.
 - for float numbers, the maximum value of the data is computed, and zmax is 1 if the max is smaller than 1, 255 if the max is smaller than 255, etc. (with higher thresholds 2**16 - 1 and 2**32 -1).

 import plotly.graph_objects as go
 from skimage import data
 img = data.camera()
 fig = px.imshow(img)
 fig = px.imshow(img, color_continuous_scale='gray')
 fig.add_trace(go.Contour(z=img, showscale=False,
                         contours=dict(start=0, end=70, size=70, coloring='lines'),
                         line_width=2))
 #### Reference
 See https://plot.ly/python/reference/#image for more information and chart attribute options!


 ```python
 fig = px.imshow
 ```
Original file line number	Diff line number	Diff line change
Expand Up		@@ -77,7 +77,7 @@ fig.show()

		### Display single-channel 2D image as grayscale

		For a 2D image, `px.imshow` uses a colorscale to map scalar data to colors. The default colorscale is`gray`, ie grayscale images.
		For a 2D image, `px.imshow` uses a colorscale to map scalar data to colors. The default colorscale isthe one of the active template (see [the tutorial on templates](/python/templates/)).

		```python
		import plotly.express as px
Expand All		@@ -94,7 +94,7 @@ fig.show()
		import plotly.express as px
		import numpy as np
		img = np.arange(100).reshape((10, 10))
		fig = px.imshow(img,colorscale='Viridis')
		fig = px.imshow(img,color_continuous_scale='gray')
		fig.show()
		```

Expand All		@@ -116,7 +116,7 @@ fig.show()

		The data range and color range are mapped together using the parameters `zmin` and `zmax`, which correspond respectively to the data values mapped to black `[0, 0, 0]` and white `[255, 255, 255]`, or to the extreme colors of the colorscale in the case on single-channel data.

		For single-channel data, the defaults values of `zmin` and `zmax` used by `px.imshow` and `go.Heatmap` are thetheextrema of the data range. For multichannel data, `px.imshow` and `go.Image` use slightly different default values for `zmin` and `zmax`. For `go.Image`, the default value is `zmin=[0, 0, 0]` and `zmax=[255, 255, 255]`, no matter the data type. On the other hand, `px.imshow` adapts the default `zmin` and `zmax` to the data type:
		For single-channel data, the defaults values of `zmin` and `zmax` used by `px.imshow` and `go.Heatmap` are the extrema of the data range. For multichannel data, `px.imshow` and `go.Image` use slightly different default values for `zmin` and `zmax`. For `go.Image`, the default value is `zmin=[0, 0, 0]` and `zmax=[255, 255, 255]`, no matter the data type. On the other hand, `px.imshow` adapts the default `zmin` and `zmax` to the data type:
		- for integer data types, `zmin` and `zmax` correspond to the extreme values of the data type, for example 0 and 255 for `uint8`, 0 and 65535 for `uint16`, etc.
		- for float numbers, the maximum value of the data is computed, and zmax is 1 if the max is smaller than 1, 255 if the max is smaller than 255, etc. (with higher thresholds 216 - 1 and 232 -1).

Expand DownExpand Up		@@ -162,7 +162,7 @@ import plotly.express as px
		import plotly.graph_objects as go
		from skimage import data
		img = data.camera()
		fig = px.imshow(img)
		fig = px.imshow(img, color_continuous_scale='gray')
		fig.add_trace(go.Contour(z=img, showscale=False,
		contours=dict(start=0, end=70, size=70, coloring='lines'),
		line_width=2))
Expand All		@@ -189,7 +189,3 @@ fig.show()
		#### Reference
		See https://plot.ly/python/reference/#image for more information and chart attribute options!


		```python
		fig = px.imshow
		```