a ` @sXddlmZmZmZddlmZddlmZddlm Z ddlm Z Gddde Z d S) )absolute_importdivisionprint_function)identity)transfer_functions) reductions)corec@s8eZdZdZeeejej ddfddZ d ddZ dS) PipelineaA datashading pipeline callback. Given a declarative specification, creates a callable with the following signature: ``callback(x_range, y_range, width, height)`` where ``x_range`` and ``y_range`` form the bounding box on the viewport, and ``width`` and ``height`` specify the output image dimensions. Parameters ---------- df : pandas.DataFrame, dask.DataFrame glyph : Glyph The glyph to bin by. agg : Reduction, optional The reduction to compute per-pixel. Default is ``count()``. transform_fn : callable, optional A callable that takes the computed aggregate as an argument, and returns another aggregate. This can be used to do preprocessing before passing to the ``color_fn`` function. color_fn : callable, optional A callable that takes the output of ``tranform_fn``, and returns an ``Image`` object. Default is ``shade``. spread_fn : callable, optional A callable that takes the output of ``color_fn``, and returns another ``Image`` object. Default is ``dynspread``. height_scale: float, optional Factor by which to scale the provided height width_scale: float, optional Factor by which to scale the provided width g?c Cs4||_||_||_||_||_||_||_||_dS)N)dfglyphagg transform_fncolor_fn spread_fn width_scale height_scale) selfr r r rrrrrr2lib/python3.9/site-packages/datashader/pipeline.py__init__+szPipeline.__init__NXcCsVtjt||jt||j||d}t|j||j|j}| | |}| |S)a1Compute an image from the specified pipeline. Parameters ---------- x_range, y_range : tuple, optional The bounding box on the viewport, specified as tuples of ``(min, max)`` width, height : int, optional The shape of the image )Z plot_widthZ plot_heightx_rangey_range) r ZCanvasintrrZbypixelr r r rrr)rrrwidthZheightZcanvasZbinsZimgrrr__call__7s  zPipeline.__call__)NNrr) __name__ __module__ __qualname____doc__rcountrtfZshadeZ dynspreadrrrrrrr s    r N) Z __future__rrrZtoolzrrr"rr objectr rrrrs