Hvplot gridspace unnormalized?

hvPlot
, ,
1

Holoviews and hvplot made it easy to overlay multiple datasets in plots.

I am trying to make a faceted grid and overlay two datasets.
However, the basic faceted grid from GridSpace created with hvplot do not conform to my expectations. I was trying to emulate xarray’s FacetGrid.

In the example code below I am plotting 3 x 2 grid with data using xarray FacetGrid and hvplot.
The data increase proportionally across the columns and is inverted across the row.
The xarray plot displays the data correctly, showing the data with increasing ranges.

However with the gridspace and hvplot, I am finding that all plots do not share the same range.

Please see the example code below

import numpy as np
import xarray as xr

import holoviews as hv
from holoviews import opts
import hvplot.xarray

hv.extension('matplotlib')
hv.notebook_extension(display_formats=['html', 'svg'])
hv.output(fig='svg')

# Dimensions
reps = xr.DataArray(np.arange(5), dims='reps', name='reps')
horizon = xr.DataArray([1, -1], dims='horizon', name='horizon')
vertical = xr.DataArray(np.arange(1, 4), dims='vertical', name='vertical')

x = xr.DataArray(np.random.randn(len(reps)),
                 dims=['reps'],
                 name='x')
y = vertical * horizon * x
y.name = 'y'

# Merge x, y
data = xr.merge([x, y])

# Assign coords
data = data.assign_coords(reps=reps, vertical=vertical, horizon=horizon)

data.plot.scatter(x='x', y='y', row='horizon', col='vertical')

data.hvplot.scatter(x='x', y='y', row='vertical', col='horizon', groupby=[])
2

Going further I like to see gridspace to share axes either along row or column or both like
matplotlib.subplots’s sharex/sharey kwargs that have the following options:

sharex, sharey : bool or {‘none’, ‘all’, ‘row’, ‘col’}, default: False
Controls sharing of properties among x ( sharex ) or y ( sharey ) axes:

  • True or ‘all’: x- or y-axis will be shared among all subplots.
  • False or ‘none’: each subplot x- or y-axis will be independent.
  • ‘row’: each subplot row will share an x- or y-axis.
  • ‘col’: each subplot column will share an x- or y-axis.