Gridspace

Title
GridSpace Container
Dependencies
Matplotlib
Backends
Matplotlib
Bokeh
In [1]:
import numpy as np
import holoviews as hv
hv.extension('matplotlib')

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.

GridSpace holds two-dimensional dictionaries

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:

In [2]:
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 :

In [3]:
gridspace = hv.GridSpace(curve_dict_2D, kdims=['phase', 'frequency'])
gridspace
Out[3]:

GridSpace is similar to HoloMap

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 :

In [4]:
hmap = hv.HoloMap(gridspace)
hmap + hv.GridSpace(hmap)
Out[4]:

Download this notebook from GitHub (right-click to download).