Package: viresclient
pip install viresclientconda install -c conda-forge viresclientviresclientis a Python package which connects to a VirES server, of which there are two:VirES for Swarm(https://vires.services) andVirES for Aeolus(https://aeolus.services), through theWPSinterface. This package handles product requests and downloads, enabling easy access to data and models from ESA’s Earth Explorer missions,SwarmandAeolus. This service is provided for ESA byEOX. For enquiries about the service and problems with accessing your account, please emailinfo@vires.services. For help with usage, please emailashley.smith@ed.ac.uk(for Swarm data) orraise an issue on GitHub.For code recipes and more, seeSwarm Notebooks&Aeolus Notebooks. To start experimenting right away,viresclientis 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.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.viresclienthandles the returned data to allow direct loading as a singlepandas.DataFrame, orxarray.Dataset.fromviresclientimportSwarmRequest# Set up connection with serverrequest=SwarmRequest()# Set collection to use# - See https://viresclient.readthedocs.io/en/latest/available_parameters.htmlrequest.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 datarequest.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 datetimedata=request.get_between(start_time="2014-01-01T00:00",end_time="2014-01-01T01:00")# Load the data as an xarray.Datasetds=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:    []How to acknowledge VirESYou can referenceviresclientdirectly using the DOI of ourzenodorecord. VirES uses data from a number of different sources so please also acknowledge these appropriately.“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