.. _ARA_Weather_Experiment:

ARA Weather Collection 
---------------------------------------------

**Platform:** ARA Weather Sensors and Disdrometers

**Resources Needed:** Any compute node.

**Description:** The experiment is designed to demonstrate the use of
ARA weather sensors and disdrometers (as shown in the figure below) to
collect the live weather data. The extracted weather data can be
integrated in your own AraRAN/AraHaul experiment code or can be used
to analyze the weather in standalone mode. More details on the weather
parameters and APIs can be found :ref:`here <ARA_Weather_APIs>`.

.. image:: images/WeatherStation_Deployment.png
   :align: center


**Detailed Steps**

#. Login to `ARA portal <https://portal.arawireless.org/>`_ with your
   username and password. 

   .. note:: If you are a first time user, we highly recommended you
		to try the :ref:`Hello World experiment
		<ARA_Hello_World>` experiment first to get
		familiarized with the portal and experiment workflow.

#. Create a reservation using the *Project -> Reservations ->
   Leases* tab from the dashboard with the following attributes:

      * *Site*: DataCenter
      * *Resource Type*: Compute Node
      * *Device Type*: Compute 
      * *Device ID*: 000 or 001

#. Launch a container using the information provided below. You can
   keep the remaining attributes default or depending on your choice.

       * *Container Image*: ``arawirelesshub/ara-ubuntu:22.04``
       * *Network*: ARA_Shared_Net


   .. note:: Ideally weather data collection can be done on any node
	     (compute, base station, user equipment, AraHaul, etc.)
	     and with any container. For this example, we use the node
	     **DataCenter-Compute-000** and the baseline
	     **ara-ubuntu** to demonstrate the experiment.


#. Once the container is launched, take a note on the floating IP and
   SSH to the container via the ARA jumpbox. Detailed instructions for
   accessing the container via jumpbox can be found :ref:`here
   <ARA_Jumpbox>`. 

#. In the container, run the following commands to install the
   packages and **arawireless** Python library, which includes APIs
   for weather data collection.

   .. code-block:: console

      # apt update
      # apt install python3-pip git -y
      # pip install git+https://gitlab.com/aralab/arasoft/arawireless.git

#. Download the data collection script. 

   .. code-block:: console

      # wget https://gitlab.com/aralab/arasoft/arawireless/-/raw/master/record_weather.py

#. Run the data collection script using the sampling interval and the
   locations in the following format.

   .. code-block:: console

      # python3 record_weather.py <interval in seconds> <site-1> <site-2>

   The following command collects the weather data from WilsonHall
   every 4 seconds. 

   .. code-block:: console

      # python3 record_weather.py 4 AgronomyFarm

   For collecting data from multiple locations, you can append the
   locations at the end of the command. For example, the command below
   collects data from AgronomyFarm as well as WilsonHall.

   .. code-block:: console

      # python3 record_weather.py 4 AgronomyFarm WilsonHall
   

   .. note:: In ARA, the weather sensors and disdrometers sample the
	     weather data every 3-4 seconds. Sampling interval less
	     than 4 may generate redundant data. You can change the
	     sampling interval as per your experiment requirements.

   Execution of the above command creates the following output.

   .. image:: images/Weather_Command.png
      :align: center

   The script runs continuously until you press Ctrl-C. The script
   writes the weather data into CSV files, separately for each
   location. For example, the command generates files
   *AgronomyFarm.csv*, *WilsonHall.csv*, etc. depending on the sites
   we have given. We can run the following command to see content in
   the file.

   .. code-block:: console

      # cat AgronomyFarm.csv


   The command displays the content within the file as follows:


   .. image:: images/Weather_Command_Output.png
      :align: center
      :width: 1000


#. The code *record_weather.py* can be modified according to our needs
   to collect the weather data in standalone mode.

   .. note:: In fact, we can include the following Python code snippet
	     within our AraRAN or AraHaul measurement scripts as well to package our experiments.

	     .. code-block:: python

		from araweather import weather
      
		weather_data = weather.get_current_weather(['WilsonHall'])
		weather.write_to_file(weather_data)