===== Usage ===== Start by importing Atmospheric data Community Toolkit. .. code-block:: python 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 `_ 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: .. code-block:: python 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 :ref:`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. .. code-block:: python 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 given that a user's username and token are provided. To obtain an ARM username and token, you must first create an `ARM account `_ by providing an email and following the setup instructions. Once you have an ARM account, you can receive your token associated with your account by logging in `here `_ and clicking on the login to receive your account access token button. Once you have your username and token, you can provide them in the example code block below: .. code-block:: python 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.