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Merge branch 'imshow-animation' of https://github.com/plotly/plotly.py into imshow-animation
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doc/python/imshow.md

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*Introduced in plotly 4.11*
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For three-dimensional image datasets, obtained for example by MRI or CT in medical imaging, one can explore the dataset by representing its different planes as facets. The `facet_col` argument specifies along which axes the image is sliced through to make the facets. With `facet_col_wrap` , one can set the maximum number of columns. For image datasets passed as xarrays, it is also possible to give an axis name as a string for `facet_col`.
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For three-dimensional image datasets, obtained for example by MRI or CT in medical imaging, one can explore the dataset by representing its different planes as facets. The `facet_col` argument specifies along which axis the image is sliced through to make the facets. With `facet_col_wrap`, one can set the maximum number of columns. For image datasets passed as xarrays, it is also possible to specify the axis by its name (label), thus passing a string to `facet_col`.
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It is recommended to use `binary_string=True` for facetted plots of images in order to keep a small figure size and a short rendering time.
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packages/python/plotly/plotly/express/_imshow.py

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else:
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raise ValueError(
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"px.imshow only accepts 2D single-channel, RGB or RGBA images. "
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"An image of shape %s was provided"
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"An image of shape %s was provided."
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"Alternatively, 3-D single or multichannel datasets can be"
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"visualized using the `facet_col` or `animation_frame` arguments."
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% str(img.shape)

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