View source for EMD-API: EMD-WRF On-Demand

[[Category:EMD-API]]
== Introduction ==
[[File:EMDAPI_451x303.jpg|thumb|400px|right]]The EMD-API: EMD-WRF On-Demand is a part of EMD-API. It provides a unified interface to the EMD-WRF mesoscale on-demand services - aimed at detailed time-series analysis. EMD-API helps consultants, analysts and scientists working with high-resolution climate data in achieving their goals in an efficient way. It has the following key-features: 

* '''Global data delivery - and calculated on-demand''': All models in the EMD-API - EMD-WRF On-Demand has a global footprint - and are executed on-demand at the High-Performance computing (HPC) facilities at EMD
* '''Multipla model configurations''': EMD-API - EMD-WRF On-Demand provides access more multiple model configurations aimed at single points or larger areas - and even a special configuration aimed at icing calculations. 
* '''Unified interface''': The unified interface which allows for integration to internal processes and tools - and also very efficient uncertainty analysis with gigabytes of data easily accessed. 
* '''Trusted datasets''': EMDAPI builds upon the trusted data-bases and data-sources that have been used through the [http://help.emd.dk/mediawiki/index.php?title=Main_Page online-data services] in windPRO for more than a decade. 
* '''Built on open standards''': EMDAPI is a [https://en.wikipedia.org/wiki/Representational_state_transfer REST] based service that implements the [https://swagger.io/specification/ OpenAPI] standard]. 
* '''Available from any development tool''': Access to the climate databases is available from your preferred development platform - C#, R, python, html, java, php, scala and swift. Just use the OpenAPI tools to generate the client software for your preferred platform.

== Access ==
To see more documentation and to access the data-services, please visit the API through the following URL's:

* EMD-API Overview (Wiki) - [https://help.emd.dk/mediawiki/index.php?title=Category%3AEMD-API here].
* EMD-API Main Page (API) - [https://api.emd.dk here].
* EMD-API Climate Data UI (API) -  [https://api.emd.dk/emd-wrf-od here].

Any technical questions on our climate databases can be addressed to our Senior Technical Specialist - Morten Lybech Thøgersen: [mailto:mlt@emd.dk mlt@emd.dk].

== Data Model - EMD-API: EMD-WRF On-Demand ==
The EMD-API: EMD-WRF On-Demand -services is documented in a REST based API using the OpenAPI Specification. You can view the interfaces and download the interfaces as json or yaml, [https://api.emd.dk/emd-wrf-od here]. The service provides the following functionality:

* ''List Models'': Full list of available models including their ID’s and other meta-data
* ''Information on used and purchased credits'': Request information of completed, cancelled or pending calculations for your company account.
* ''Place Order'':  Order a mesoscale time-series data for any location whith any model (dataset) - given any latitude-longitude location). You can decide which period to download.
* ''Order Status'': Request progress for an order - and eventually recieve the download URL for the order. Options: [PENDING, CANCELLED OR SUCCESS]., 
* ''Cancel Order'': Cancel an order that has not started yet (status must be PENDING)

== Python - Installation == 
[[Image:EgmondAanZee.jpg|thumb|400px|right|Data nodes near the Egmond Aan Zee Offhore ]]The simplest way to use the EMDAPI with python is to install the client software in a virtual environment. If you are using CONDA or [https://docs.conda.io/en/latest/miniconda.html MINICONDA], we recommend that you create a new virtual environment and use a recent 3.x version of python. When the virtual environment is created, then activate the environment.

''Open your Anaconda Prompt. Copy-paste the following lines:''
<pre>
conda create -n emdapiclient python=3.8.5
conda activate emdapiclient
</pre>

Install the required packages needed in order to do data-science and use the examples provided within the jupyter notebooks. We have have validated this setup using specific package versions (used in the commands below). 

''In the  Anaconda Prompt, copy-paste the following lines, one by one:''
<pre>
conda install -c conda-forge pandas=1.1.0 numpy=1.19.1
conda install -c conda-forge matplotlib=3.3.1 basemap=1.2.2 basemap-data-hires=1.2.2 
conda install -c conda-forge jupyter=1.0.0 ipykernel=5.3.4 
conda install -c conda-forge python-wget
</pre>

Download the [https://help.emd.dk/mediawiki/images/7/73/20201206_python_client_generated.zip zipped-file] holding the OpenAPI python client. <br>
Unpack the file and install it within your virtual environment:

''In the Anaconda Prompt: Move to the folder, where you have unpacked the zipped file. Copy-paste the following line:''
<pre>
python setup.py install
</pre>

Make sure that the new emdapi virtual enviroment (python-kernel) is available to be used with jupyter-notebook environment:
<pre>
python -m ipykernel install --user --name=emdapiclient
</pre>

== Python - Jupyter Notebooks for Demonstration and Test ==

In order to test your setup and learn to use the EMDAPI, we suggest that you download the jupyter-notebook examples that we have created - [https://help.emd.dk/mediawiki/images/c/c5/20201206_EMDAPI_JupyterNotebooks.zip here].<br>
Unpack the zip files and run the command below in your terminal or command-shell.<br>
If jupyter prompts for you to select another python-kernel, then select the emdapiclient kernel (may also be selected directly from the 'Kernel' drop-down menu).

''In the Anaconda Prompt: Move to the folder, where you have saved the jupyter-notebook examples. Copy paste the following line to open jupyter notebook from where you can open the examples.'' 
<pre>
jupyter notebook
</pre>

Within the internet-browser (and jupyter user-interface), run select the notebook file (*.ipynb). <br>
Then work your way through through each example provided. Each jupyter notebook holds a separate topic:

# ''emdapi_availability.ipynb'' Demonstration of login to the system, then check which datasets are available at a specific location.
# ''emdapi_correlation.ipynb'': Correlation analysis (R2), check which climate datasets correlates the best against the Egmond Aan Zee data
# ''emdapi_random.ipynb'': Download climate data from any part of the world.

== Client Software Other Languages and Tools ==
REST and OpenAPI is easily consumed from a lot of software tools. It is perfectly possible that your preferred language is supported. OpenAPI works well with languages such as - but not limited to - C#, R, python, java, php, scala and swift. Just download the YAML or JSON service description and use the [https://editor.swagger.io/ Swagger Editor] or [https://github.com/OpenAPITools/openapi-generator OpenAPI Generator] to generate the client libraries for your preferred software. Then you are ready to integrate towards your preferred systems and workflows.

To generate the client libries yourself - one possible process is to:

# Download the OpenAPI (openapi.yaml or openapi.json) description files - [https://api.emd.dk/climate-data/openapi.yaml here-yaml] or [https://api.emd.dk/climate-data/openapi.json here-json]
# Load it into the swagger editor - [https://editor.swagger.io here]
# Choose to "Generate Client" from the drop-down menu within the swagger editor.