xr.plot infers sequential colormap on diverging levels

[mathause]

MCVE Code Sample

import numpy as np
import xarray as xr

data = np.random.randn(10, 10)
data = np.abs(data)

da = xr.DataArray(data)

# returns a diverging colormap
da.plot(vmax=2, center=0, extend="both")

# returns a sequential colormap
da.plot(levels=[-2, -1, 0, 1, 2], extend="both")

Expected Output

A diverging colormap, maybe?

Problem Description

I was surprised by getting the viridis colormap until I realised that my data must all be positive and the colormap is infered from the data and not from levels. However, when specifying the range via vmax=2, center=0 it is not inferred from the data.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.12.14-lp151.28.25-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2

xarray: 0.14.0+44.g4dce93f1
pandas: 0.25.2
numpy: 1.17.3
scipy: 1.3.1
netCDF4: 1.5.0.1
pydap: None
h5netcdf: 0.7.4
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.4.2
nc_time_axis: 1.2.0
PseudoNetCDF: None
rasterio: 1.0.22
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 2.6.0
distributed: 2.6.0
matplotlib: 3.1.1
cartopy: 0.17.0
seaborn: 0.9.0
numbagg: None
setuptools: 41.4.0
pip: 19.3.1
conda: None
pytest: 5.2.2
IPython: 7.9.0
sphinx: 2.2.1

[dcherian]

hmm... it's also weird if you specified vmax=2, vmin=-2. For some reason, auto-inferred colormaps are disabled in that case.

Here's where you should look if you want to jump in :)

xarray/xarray/plot/utils.py

Lines 141 to 154 in 810345c

	def _determine_cmap_params(
	plot_data,
	vmin=None,
	vmax=None,
	cmap=None,
	center=None,
	robust=False,
	extend=None,
	levels=None,
	filled=True,
	norm=None,
	):
	"""
	Use some heuristics to set good defaults for colorbar and range.

[shoyer]

It might be worth taking a look at updating our heuristics. They were originally copied from seaborn, but seaborn has since updated them to something a little different.