Quadmesh#
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import hvplot.xarray # noqa
import xarray as xr
ds = xr.tutorial.open_dataset('rasm')
ds
<xarray.Dataset> Dimensions: (time: 36, y: 205, x: 275) Coordinates: * time (time) object 1980-09-16 12:00:00 ... 1983-08-17 00:00:00 xc (y, x) float64 ... yc (y, x) float64 ... Dimensions without coordinates: y, x Data variables: Tair (time, y, x) float64 ... Attributes: title: /workspace/jhamman/processed/R1002RBRxaaa01a/l... institution: U.W. source: RACM R1002RBRxaaa01a output_frequency: daily output_mode: averaged convention: CF-1.4 references: Based on the initial model of Liang et al., 19... comment: Output from the Variable Infiltration Capacity... nco_openmp_thread_number: 1 NCO: netCDF Operators version 4.7.9 (Homepage = htt... history: Fri Aug 7 17:57:38 2020: ncatted -a bounds,,d...
quadmesh
can be slower that image
, but it allows you to plot values on an irregular grid by representing each value as a polygon.
ds.Tair.hvplot.quadmesh(x='xc', y='yc', geo=True, widget_location='bottom')
To reduce the render time or the size of the saved plot, use rasterize
to aggregate the values to the pixel. It is recommended that when rasterizing geo plots, you project before rasterizing, by setting project=True
.
ds.Tair.hvplot.quadmesh(x='xc', y='yc', geo=True, widget_location='bottom', rasterize=True, project=True)
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Download this notebook from GitHub (right-click to download).