Xarray Plotting Examples

This is an example of how to use some different aspects of ACT’s plotting tools as well as Xarray’s tools.

sgpceilC1.b1 backscatter on 20190101, sgpceilC1.b1 backscatter on 20190101
from arm_test_data import DATASETS
import matplotlib.pyplot as plt

import act

# Set up plot space ahead of time
fig, ax = plt.subplots(3, figsize=(10, 7))

# Plotting up high-temporal resolution 2D data can be very slow at times.
# In order to increase the speed, the data can be resampled to a courser
# resolution prior to plotting.  Using Xarray's resample and selecting
# the nearest neighbor will greatly increase the speed.
filename_ceil = DATASETS.fetch('sgpceilC1.b1.20190101.000000.nc')
ds = act.io.arm.read_arm_netcdf(filename_ceil)
ds = ds.resample(time='1min').nearest()

# These data can be plotted up using the existing xarray functionality
# which is quick and easy
ds['backscatter'].plot(x='time', ax=ax[0])

# or using ACT
display = act.plotting.TimeSeriesDisplay(ds)
display.assign_to_figure_axis(fig, ax[1])
display.plot('backscatter')

# When using ACT, the axis object can also be manipulated using normal
# matplotlib calls for more personalized customizations
display = act.plotting.TimeSeriesDisplay(ds)
display.assign_to_figure_axis(fig, ax[2])
display.plot('backscatter')
display.axes[-1].set_ylim([0, 1500])

plt.show()

Total running time of the script: (0 minutes 1.407 seconds)

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