docarray.array.mixins.plot module#

class docarray.array.mixins.plot.PlotMixin[source]#

Bases: object

Helper functions for plotting the arrays.

summary()[source]#

Print the structure and attribute summary of this DocumentArray object.

Warning

Calling {meth}`.summary` on large DocumentArray can be slow.

plot_embeddings(title='MyDocumentArray', path=None, image_sprites=False, min_image_size=16, channel_axis=-1, start_server=True, host='127.0.0.1', port=None, image_source='tensor')[source]#

Interactively visualize embeddings using the Embedding Projector.

Parameters:

  • title (str) – the title of this visualization. If you want to compare multiple embeddings at the same time, make sure to give different names each time and set path to the same value.

  • host (str) – if set, bind the embedding-projector frontend to given host. Otherwise localhost is used.

  • port (Optional[int]) – if set, run the embedding-projector frontend at given port. Otherwise a random port is used.

  • image_sprites (bool) – if set, visualize the dots using uri and tensor.

  • path (Optional[str]) – if set, then append the visualization to an existing folder, where you can compare multiple embeddings at the same time. Make sure to use a different title each time .

  • min_image_size (int) – only used when image_sprites=True. the minimum size of the image

  • channel_axis (int) – only used when image_sprites=True. the axis id of the color channel, -1 indicates the color channel info at the last axis

  • start_server (bool) – if set, start a HTTP server and open the frontend directly. Otherwise, you need to rely on return path and serve by yourself.

  • image_source (str) – specify where the image comes from, can be uri or tensor. empty tensor will fallback to uri

Return type:

str

Returns:

the path to the embeddings visualization info.

save_gif(output, channel_axis=-1, duration=200, size_ratio=1.0, inline_display=False, image_source='tensor', skip_empty=False, show_index=False, show_progress=False)[source]#

Save a gif of the DocumentArray. Each frame corresponds to a Document.uri/.tensor in the DocumentArray.

Parameters:

  • output (str) – the file path to save the gif to.

  • channel_axis (int) – the color channel axis of the tensor.

  • duration (int) – the duration of each frame in milliseconds.

  • size_ratio (float) – the size ratio of each frame.

  • inline_display (bool) – if to show the gif in Jupyter notebook.

  • image_source (str) – the source of the image in Document atribute.

  • skip_empty (bool) – if to skip empty documents.

  • show_index (bool) – if to show the index of the document in the top-right corner.

  • show_progress (bool) – if to show a progress bar.

Return type:

None

Returns:

plot_image_sprites(output=None, canvas_size=512, min_size=16, channel_axis=-1, image_source='tensor', skip_empty=False, show_progress=False, show_index=False, fig_size=(10, 10), keep_aspect_ratio=False)[source]#

Generate a sprite image for all image tensors in this DocumentArray-like object.

An image sprite is a collection of images put into a single image. It is always square-sized. Each sub-image is also square-sized and equally-sized.

Parameters:

  • output (Optional[str]) – Optional path to store the visualization. If not given, show in UI

  • canvas_size (int) – the size of the canvas

  • min_size (int) – the minimum size of the image

  • channel_axis (int) – the axis id of the color channel, -1 indicates the color channel info at the last axis

  • image_source (str) – specify where the image comes from, can be uri or tensor. empty tensor will fallback to uri

  • skip_empty (bool) – skip Document who has no .uri or .tensor.

  • show_index (bool) – show the index on the top-right corner of every image

  • fig_size (Optional[Tuple[int, int]]) – the size of the figure

  • show_progress (bool) – show a progressbar while plotting.

  • keep_aspect_ratio (bool) – preserve the aspect ratio of the image by using the aspect ratio of the first image in self.

Return type:

None