Path

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

A Path object is actually a collection of lines, which are all plotted with the same style. Unlike Curve where the y-axis is the dependent variable, a Path consists of lines connecting arbitrary points in two-dimensional space as is not expected to be a function.

In [2]:
%%opts Path (color='black' linewidth=4)
lin = np.linspace(-np.pi,np.pi,300)

def lissajous(t, a,b, delta):
    return (np.sin(a * t + delta), np.sin(b * t))

hv.Path(lissajous(np.linspace(-np.pi, np.pi, 1000),3,5,np.pi/2))
Out[2]:

Unlike Curve as single Path element can contain multiple lines that are disconnected from each other which will all be plotted in the same style. Only by overlaying multiple Path objects do you iterate through the defined color cycle (or any other style options that have been defined). A Path is often useful to draw arbitrary annotations on top of an existing plot.

A Path Element accepts multiple formats for specifying the paths, the simplest of which is passing a list of Nx2 arrays of the x- and y-coordinates, alternative we can pass lists of coordinates. In this example we will create some coordinates representing rectangles and ellipses annotating an RGB image:

In [3]:
%%opts Path (linewidth=4)
angle = np.linspace(0, 2*np.pi, 100)
baby = list(zip(0.15*np.sin(angle),  0.2*np.cos(angle)-0.2))

adultR = [(0.25, 0.45), (0.35,0.35), (0.25, 0.25), (0.15, 0.35), (0.25, 0.45)]
adultL = [(-0.3, 0.4), (-0.3, 0.3), (-0.2, 0.3), (-0.2, 0.4),(-0.3, 0.4)]
scene = hv.RGB.load_image('../assets/penguins.png')

scene * hv.Path([adultL, adultR, baby]) * hv.Path([baby])
Out[3]:

A Path can also be used as a means to display a number of lines with the same sampling along the x-axis at once. If we initialize the Path with a tuple of x-coordinates and stacked y-coordinates, we can quickly view a number of lines at once. Here we will generate a number of random traces each slightly offset along the y-axis:

In [4]:
%%opts Path [fig_size=400 aspect=3]
N, NLINES = 100, 10
hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :])) *\
hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :]))
Out[4]:

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