Source code for datashader.pipeline

from __future__ import absolute_import, division, print_function

from toolz import identity

from . import transfer_functions as tf
from . import reductions
from . import core


[docs]class Pipeline(object): """A 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 """ def __init__(self, df, glyph, agg=reductions.count(), transform_fn=identity, color_fn=tf.shade, spread_fn=tf.dynspread, width_scale=1.0, height_scale=1.0): self.df = df self.glyph = glyph self.agg = agg self.transform_fn = transform_fn self.color_fn = color_fn self.spread_fn = spread_fn self.width_scale = width_scale self.height_scale = height_scale def __call__(self, x_range=None, y_range=None, width=600, height=600): """Compute 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 """ canvas = core.Canvas(plot_width=int(width*self.width_scale), plot_height=int(height*self.height_scale), x_range=x_range, y_range=y_range) bins = core.bypixel(self.df, canvas, self.glyph, self.agg) img = self.color_fn(self.transform_fn(bins)) return self.spread_fn(img)