Xarray plot types

Xarray plot types

Scott Wales, CLEX CMS

Let’s look at the different types of plots that are available using Xarray.

As usual we’ll start with some data from NCI

%matplotlib inline

import xarray
datapath = "http://dapds00.nci.org.au/thredds/dodsC/rr3/CMIP5/output1/CSIRO-BOM/ACCESS1-0/amip/mon/atmos/Amon/r1i1p1/latest/tas/tas_Amon_ACCESS1-0_amip_r1i1p1_197901-200812.nc"
data = xarray.open_dataset(datapath)
tas = data.tas.isel(time=0)

Calling .plot() on a xarray dataarray is a quick way to make a plot. It will choose a plot type based on the array dimension - if you get a histogram try reducing the number of dimensions using .sel() or .isel()

<matplotlib.collections.QuadMesh at 0x7fb91828f240>

There are four basic plot types for 2d data

  • pcolormesh - colourised image

  • imshow - colourised image

  • contourf - filled contours

  • contour - empty contours

pcolormesh and imshow are basically the same, but imshow has more control over the colours - you can for instance specify different arrays for the red, green and blue components

import matplotlib.pyplot as plt

for i in range(4):
    ax[i] = plt.subplot(2,2,i+1)

<matplotlib.contour.QuadContourSet at 0x7fb918102ef0>

By default the plots come with a colour bar and title, however you can disable those in order to replace them with your own

tas.plot.pcolormesh(levels=7, add_colorbar=True, add_labels=False)

plt.suptitle("Surface Temperature (K)")
plt.tick_params(bottom=False, labelbottom=False, left=False, labelleft=False)

You can also specify the axis to create a plot on, which is useful for subplots and cartopy projections.

Note that while pyplot’s imshow() function only shows a rectangular image cartopy’s projections still work to project the data onto a globe

import cartopy.crs as ccrs

ax = [
    plt.subplot(121, projection=ccrs.Orthographic()),
    plt.subplot(122, projection=ccrs.Orthographic(central_longitude=90)),

tas.plot.pcolormesh(ax=ax[0], transform=ccrs.PlateCarree(), add_colorbar=False, add_labels=False)

tas.plot.imshow(ax=ax[1], transform=ccrs.PlateCarree(), add_colorbar=False, add_labels=False)
<cartopy.mpl.feature_artist.FeatureArtist at 0x7fb901d736a0>