This example script may also be found at gcpy/examples/plotting/

Single Panel PlottingΒΆ

#!/usr/bin/env python
Global and Regional Single Panel Plots
This example script demonstrates the core single panel plotting
capabilities of GCPy, including global and regional single level plots
as well as global zonal mean plots.

The example data described here is in lat/lon format, but the same code
works equally well for cubed-sphere (GCHP) data.

For full documentation on the plotting capabilities of GCPy
(including full argument lists), please see the GCPy documentation
import xarray as xr
import matplotlib.pyplot as plt
from gcpy.plot.single_panel import single_panel

def main():
    Example routine to create single panel plots.

    # xarray allows us to read in any NetCDF file, the format of
    # GEOS-Chem diagnostics as an xarray Dataset
    dset = xr.open_dataset('GEOSChem.Restart.20160701_0000z.nc4')

    # You can easily view the variables available for plotting
    # using xarray.  Each of these variables has its own xarray
    # DataArray within the larger Dataset container.

    # Most variables have some sort of prefix; in this example all
    # variables are prefixed with 'SpeciesRst_'. We'll select the
    # DataArray for ozone.
    darr = dset.SpeciesRst_O3

    # Printing a DataArray gives a summary of the dimensions and attributes
    # of the data.

    # This Restart file has a time dimension of size 1, with 72 vertical levels,
    #46 latitude indicies, and 72 longitude indices.

    # ==================
    # Single-level Plots
    # ==================

    # gcpy.single_panel is the core plotting function of GCPy, able to
    # create a one panel zonal mean or single level plot.  Here we will
    # create a single level plot of ozone at ~500 hPa.  We must manually
    # index into the level that we want to plot (index 22 in the standard
    # 72-layer and 47-layer GMAO vertical grids).
    slice_500 = darr.isel(lev=22)

    # single_panel has many arguments which can be optionally specified.
    # The only argument you must always pass to a call to single_panel is
    # the DataArray that you want to plot. By default, the created plot
    # includes a colorbar with units read from the DataArray, an
    # automatic title (the data variable name in the DataArray), and
    # an extent equivalent to the full lat/lon extent of the DataArray

    #You can specify a specific area of the globe you would like plotted
    # using the 'extent' argument, which uses the format [min_longitude,
    # max_longitude, min_latitude, max_latitude] with bounds
    # [-180, 180, -90, 90]
    single_panel(slice_500, extent=[50, -90, -10, 60])

    # Other commonly used arguments include specifying a title and a
    # colormap (defaulting to a White-Green-Yellow-Red colormap)
    #You can find more colormaps at
        title='500mb Ozone over the North Pacific',
        extent=[80, -90, -10, 60]

    # ===================
    # Zonal Mean Plotting
    # ===================

    # Use the plot_type argument to specify zonal_mean plotting

    #You can specify pressure ranges in hPa for zonal mean plot
    # (by default every vertical level is plotted)
        pres_range=[0, 100],

# Only execute when we run as a standalone script
if __name__ == '__main__':