import numpy as np import holoviews as hv from holoviews import opts hv.extension('bokeh')
Path element represents one more lines, connecting arbitrary points in two-dimensional space.
Path supports plotting an individual line or multiple subpaths, which should be supplied as a list. Each path should be defined in a columnar format such as NumPy arrays, DataFrames or dictionaries for each column. For a full description of the path geometry data model see the Geometry Data User Guide.
In this example we will create a Lissajous curve, which describe complex harmonic motion:
lin = np.linspace(0, np.pi*2, 200) def lissajous(t, a, b, delta): return (np.sin(a * t + delta), np.sin(b * t), t) path = hv.Path([lissajous(lin, 3, 5, np.pi/2)]) path.opts(color='black', line_width=4)
If you looked carefully the
lissajous function actually returns three columns, respectively for the x, y columns and a third column describing the point in time. By declaring a value dimension for that third column we can also color the Path by time. Since the value is cyclical we will also use a cyclic colormap (
'hsv') to represent this variable:
path = hv.Path([lissajous(lin, 3, 5, np.pi/2)], vdims='time') path.opts(cmap='hsv', color='time', line_width=4)
If we do not provide a
Path elements will cycle colors just like other elements do unlike
Curve a single
Path element can contain multiple lines that are disconnected from each other. A
Path can therefore often useful to draw arbitrary annotations on top of an existing plot.
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
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') overlay = (scene * hv.Path([adultL, adultR, baby]) * hv.Path([baby])) overlay.opts(opts.Path(line_width=4))
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:
N, NLINES = 100, 10 paths = hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :])) paths2 = hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :])) overlay = paths * paths2 overlay.opts(width=600)
For full documentation and the available style and plot options, use