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import numpy as np
import holoviews as hv
hv.extension('plotly')
A GridSpace
is a two-dimensional dictionary of HoloViews objects presented onscreen as a grid. In one sense, due to the restriction on it's dimensionality, a GridSpace
may be considered a special-case of HoloMap
. In another sense, GridSpace
may be seen as more general as a GridSpace
can hold a HoloMap
but the converse is not permitted; see the Building Composite Objects user guide for details on how to compose containers.
Using the sine_curve
function below, we can declare a two-dimensional dictionary of Curve
elements, where the keys are 2-tuples corresponding to (phase, frequency) values:
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def sine_curve(phase, freq):
xvals = [0.1* i for i in range(100)]
return hv.Curve((xvals, [np.sin(phase+freq*x) for x in xvals]))
phases = [0, np.pi/2, np.pi, 3*np.pi/2]
frequencies = [0.5, 0.75, 1.0, 1.25]
curve_dict_2D = {(p,f):sine_curve(p,f) for p in phases for f in frequencies}
We can now pass this dictionary of curves to GridSpace
:
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gridspace = hv.GridSpace(curve_dict_2D, kdims=['phase', 'frequency'])
gridspace
Other than the difference in the visual semantics, whereby GridSpaces
display their contents together in a two-dimensional grid, GridSpaces
are very similar to HoloMap
s (see the HoloMap
notebook for more information).
One way to demonstrate the similarity of these two containers is to cast our gridspace
object to HoloMap
and back to a GridSpace
:
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hmap = hv.HoloMap(gridspace)
hmap + hv.GridSpace(hmap)