viresclient

.. image:: https://img.shields.io/pypi/v/viresclient :target: https://pypi.org/project/viresclient/ :alt: PyPI

.. image:: https://img.shields.io/conda/vn/conda-forge/viresclient :target: https://anaconda.org/conda-forge/viresclient :alt: Conda

.. image:: https://readthedocs.org/projects/viresclient/badge/?version=latest :target: http://viresclient.readthedocs.io/ :alt: Documentation Status

.. image:: https://zenodo.org/badge/138034133.svg :target: https://zenodo.org/badge/latestdoi/138034133

::

pip install viresclient

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conda install -c conda-forge viresclient

viresclient_ is a Python package which connects to a VirES server, of which there are two: VirES for Swarm (https://vires.services) and VirES for Aeolus (https://aeolus.services), through the WPS_ interface. This package handles product requests and downloads, enabling easy access to data and models from ESA's Earth Explorer missions, Swarm_ and Aeolus_. This service is provided for ESA by EOX_. For enquiries about the service and problems with accessing your account, please email [e-mail]. For help with usage, please email [e-mail] (for Swarm data) or raise an issue on GitHub_.

.. _viresclient: https://github.com/ESA-VirES/VirES-Python-Client .. _WPS: http://www.opengeospatial.org/standards/wps .. _Swarm: https://earth.esa.int/eogateway/missions/swarm .. _Aeolus: https://earth.esa.int/eogateway/missions/aeolus .. _EOX: https://eox.at/category/vires/ .. _raise an issue on GitHub: https://github.com/ESA-VirES/VirES-Python-Client/issues

For code recipes and more, see Swarm Notebooks_ & Aeolus Notebooks_. To start experimenting right away, viresclient is installed on the "Virtual Research Environment" (VRE), which is a managed Jupyter-based system provided for ESA by EOX. The service is free and open to all, accessible through your VirES account - check the notebooks to read more and get started.

.. _Swarm Notebooks: https://notebooks.vires.services .. _Aeolus Notebooks: https://notebooks.aeolus.services

Data and models are processed on demand on the VirES server - a combination of measurements from any time interval can be accessed. These are the same data that can be accessed by the VirES GUI. viresclient handles the returned data to allow direct loading as a single pandas.DataFrame_, or xarray.Dataset_.

.. _pandas.DataFrame: https://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe .. _xarray.Dataset: http://xarray.pydata.org/en/stable/data-structures.html#dataset

.. code-block:: python

from viresclient import SwarmRequest

Set up connection with server

request = SwarmRequest()

Set collection to use

- See https://viresclient.readthedocs.io/en/latest/available_parameters.html

request.set_collection("SW_OPER_MAGA_LR_1B")

Set mix of products to fetch:

measurements (variables from the given collection)

models (magnetic model predictions at spacecraft sampling points)

auxiliaries (variables available with any collection)

Optionally set a sampling rate different from the original data

request.set_products( measurements=["F", "B_NEC"], models=["CHAOS-Core"], auxiliaries=["QDLat", "QDLon"], sampling_step="PT10S" )

Fetch data from a given time interval

- Specify times as ISO-8601 strings or Python datetime

data = request.get_between( start_time="2014-01-01T00:00", end_time="2014-01-01T01:00" )

Load the data as an xarray.Dataset

ds = data.as_xarray()

::

<xarray.Dataset> Dimensions: (NEC: 3, Timestamp: 360) Coordinates:

• Timestamp (Timestamp) datetime64[ns] 2014-01-01 ... 2014-01-01T00:59:50 Dimensions without coordinates: NEC Data variables: Spacecraft (Timestamp) <U1 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 -1.229 -1.863 -2.496 ... 48.14 48.77 Longitude (Timestamp) float64 -14.12 -14.13 -14.15 ... 153.6 153.6 Radius (Timestamp) float64 6.878e+06 6.878e+06 ... 6.868e+06 F (Timestamp) float64 2.287e+04 2.281e+04 ... 4.021e+04 F_CHAOS-Core (Timestamp) float64 2.287e+04 2.282e+04 ... 4.02e+04 B_NEC (Timestamp, NEC) float64 2.01e+04 -4.126e+03 ... 3.558e+04 B_NEC_CHAOS-Core (Timestamp, NEC) float64 2.011e+04 ... 3.557e+04 QDLat (Timestamp) float64 -11.99 -12.6 -13.2 ... 41.59 42.25 QDLon (Timestamp) float64 58.02 57.86 57.71 ... -135.9 -136.0 Attributes: Sources: ['SW_OPER_MAGA_LR_1B_20140101T000000_20140101T235959_050... MagneticModels: ["CHAOS-Core = 'CHAOS-Core'(max_degree=20,min_degree=1)"] RangeFilters: []

.. image:: https://github.com/ESA-VirES/Swarm-VRE/raw/master/docs/images/VRE_shortest_demo.gif

How to acknowledge VirES

You can reference viresclient directly using the DOI of our zenodo_ record. VirES uses data from a number of different sources so please also acknowledge these appropriately.

.. _zenodo: https://doi.org/10.5281/zenodo.2554162

| "We use the Python package, viresclient [1], to access [...] from ESA's VirES for Swarm service [2]"
| [1] https://doi.org/10.5281/zenodo.2554162
| [2] https://vires.services