ToyTree with barplot

ToyTree + barplot¶

Aligning a tree with data is sometimes easier on one axis versus two. See the (#1) and (#2) for comparison. Here when plotting on one axis the tree coordinates which map to treeheight and the number of tips can be difficult to align with data (e.g., a barplot) since the data values may be much greater than the treeheight. This can be fixed by tranforming the data and the axis labels. The example on a two axes is a bit easier in this case.

In [2]:

import numpy as np
import toytree
import toyplot

# generate a random tree and data
ntips = 20
rseed = 123456
rng = np.random.default_rng(rseed)

# get tree and data
rtre = toytree.rtree.unittree(ntips=ntips, seed=rseed).ladderize()
randomdata = rng.uniform(20, 200, ntips)

# set up a toyplot Canvas with 2 axes: (x1, x2, y1, y2)
canvas = toyplot.Canvas(width=375, height=350)
ax0 = canvas.cartesian(bounds=(50, 200, 50, 300), padding=15, ymin=0, ymax=20)
ax1 = canvas.cartesian(bounds=(225, 325, 50, 300), padding=15, ymin=0, ymax=20)

# add tree to first axes
rtre.draw(axes=ax0);
ax0.show = False

# plot the barplot on the second axes
# (y-axis is range 0-ntips);
# (x-axis is bar values transformed to be 0-1)
# baseline is the space between tipnames and bars
ax1.bars(
    np.arange(ntips),
    randomdata,
    along='y',
);

# style axes
ax1.show = True
ax1.y.show = False
ax1.x.ticks.show = True

import numpy as np import toytree import toyplot # generate a random tree and data ntips = 20 rseed = 123456 rng = np.random.default_rng(rseed) # get tree and data rtre = toytree.rtree.unittree(ntips=ntips, seed=rseed).ladderize() randomdata = rng.uniform(20, 200, ntips) # set up a toyplot Canvas with 2 axes: (x1, x2, y1, y2) canvas = toyplot.Canvas(width=375, height=350) ax0 = canvas.cartesian(bounds=(50, 200, 50, 300), padding=15, ymin=0, ymax=20) ax1 = canvas.cartesian(bounds=(225, 325, 50, 300), padding=15, ymin=0, ymax=20) # add tree to first axes rtre.draw(axes=ax0); ax0.show = False # plot the barplot on the second axes # (y-axis is range 0-ntips); # (x-axis is bar values transformed to be 0-1) # baseline is the space between tipnames and bars ax1.bars( np.arange(ntips), randomdata, along='y', ); # style axes ax1.show = True ax1.y.show = False ax1.x.ticks.show = True