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Running
on
Zero
File size: 2,725 Bytes
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from __future__ import annotations
from toolz import identity
from . import transfer_functions as tf
from . import reductions
from . import core
class Pipeline:
"""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,
antialias=self.glyph.antialiased)
img = self.color_fn(self.transform_fn(bins))
return self.spread_fn(img)
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