Usage¶
Start by importing Atmospheric data Community Toolkit.
import act
The Atmospheric data Community Toolkit comes with modules for loading ARM datasets. The main dataset object that is used in ACT is based off of an extension of the xarray.Dataset<http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html> object. In particular ACT adds a DatasetAccessor that stores the additional properties required by act in the .act property of a Dataset. For example, if we want to access the name of the datastream, we simply do:
import act
the_ds = act.io.arm.read_arm_netcdf(act.tests.sample_files.EXAMPLE_SONDE_WILDCARD)
print(the_ds.act.datastream)
To load ARM-standard files into, the arm.io.arm.read_arm_netcdf routine is used.
This takes in a string with wildcards allowed or a list of files for ACT to read.
Currently, there is support for ACT to concatenate multiple netCDF files along a time
dimension if all of the files follow the same format. This allows for the easy
reading of multi-file datasets, such as the examples provided in the
sphx_glr_source_auto_examples_plot_sonde.py.
In addition, ACT has a TimeSeriesDisplay object that makes plotting the data in a timeseries easy. The TimeSeriesDisplay object supports multipanel plots with ease. The following code will plot a 3 panel time series plot from the dataset in the code snippet above.
display = act.plotting.TimeSeriesDisplay(met)
display.add_subplots((3,), figsize=(15, 10))
display.plot("alt", subplot_index=(0,))
display.plot("temp_mean", subplot_index=(1,))
display.plot("rh_mean", subplot_index=(2,))
plt.show()
In addition, the figure and axes handles of each subplot are stored in the TimeSeriesDisplay object as TimeSeriesDisplay.fig and TimeSeriesDisplay.ax. Therefore, standard matplotlib routines can then be used to modify the properties of each plot if the user desires further customization.
Finally, ACT is able to download data from the ARM archive given that a user’s username and token are provided.
act.discovery.get_data(
"userName", "XXXXXXXXXXXXXXXX", "sgpmetE13.b1", "2017-01-14", "2017-01-20"
)
The preceding example will download the sgpmetE13.b1 dataset in netCDF format from 2017-01-14 to 2017-01-20 and store the dataset in an output folder named ‘sgpmetE13.b1.’ This output folder can also be specified by the user.