HoloViews is designed to work with scientific and engineering data, which is often in the form of discrete samples from an underlying continuous system. Imaging data is one clear example: measurements taken at a regular interval over a grid covering a two-dimensional area. Although the measurements are discrete, they approximate a continuous distribution, and HoloViews provides extensive support for working naturally with data of this type.
2D Continuous spaces#
In this user guide we will show the support provided by HoloViews for working with two-dimensional regularly sampled grid data like images, and then in subsequent sections discuss how HoloViews supports one-dimensional, higher-dimensional, and irregularly sampled data with continuous coordinates.
import numpy as np import holoviews as hv from holoviews import opts hv.extension('bokeh') np.set_printoptions(precision=2, linewidth=80) opts.defaults(opts.HeatMap(cmap='fire'), opts.Layout(shared_axes=False))