Installation and First Usage
Contents
Installation and First Usage#
Note
For VRE users (it’s free! read more: Swarm, Aeolus), viresclient is already installed and configured so skip these steps
1. Installation#
Python ≥ 3.6 is required. Testing is primarily on Linux, but macOS and Windows should also work.
It can currently be installed with:
pip install viresclient
Dependencies:
requests
Jinja2
tables
tqdm
cdflib
pandas
xarray
netCDF4
pip will fetch these automatically - if you are using conda, it may be better to install these first using conda instead (where available):
conda install requests jinja2 pytables tqdm pandas xarray netcdf4
pip install viresclient
Recommended setup if starting without Python already#
Install Miniconda: https://docs.conda.io/en/latest/miniconda.html
Create a new conda environment with some recommended packages:
conda create --name myenv scipy matplotlib pandas xarray cartopy jupyter jupyterlab flake8 dask h5py netCDF4 jinja2 pytables tqdm ipywidgets
Activate the new environment (you do this each time you want to use it):
conda activate myenv
Use pip to install viresclient:
pip install viresclient
2. First usage / Configuration#
Note
For Jupyter notebook users:
On creation of a SwarmRequest object, you will automatically be prompted to set a token. Just try:
from viresclient import SwarmRequest
request = SwarmRequest()
and follow the instructions.
A first usage guide is provided as a Jupyter notebook (view). To run the notebook on your computer running Jupyter locally, right click here to download, or use git to get the whole example repository:
git clone https://github.com/Swarm-DISC/Swarm_notebooks.git
Access to the service is through the same user account as on the web interface (https://vires.services/) and is enabled through an access token (essentially a password). To get a token, log in to the website and click on your name on the top right to access the settings (or follow this link). From here, click on “Manage access tokens” and follow the instructions to create a new token.
To set your token in the client, use either the Python interface:
from viresclient import set_token
set_token("https://vires.services/ows")
# (you will now be prompted to enter the token)
or the command line tool:
$ viresclient set_token https://vires.services/ows
Enter access token: r-8-mlkP_RBx4mDv0di5Bzt3UZ52NGg-
$ viresclient set_default_server https://vires.services/ows
See also: see Configuration Details and Access Token Management
3. Example use#
Note
A brief introduction is given here. For more possibilities, see Introduction to notebooks
Choose which collection to access (see Available parameters for Swarm for more options):
import datetime as dt
from viresclient import SwarmRequest
request = SwarmRequest()
request.set_collection("SW_OPER_MAGA_LR_1B")
Next, use .set_products()
to choose a combination of variables to retrieve, specified by keywords.
measurements
are measured by the satellite and members of the specifiedcollection
models
are evaluated on the server at the positions of the satelliteauxiliaries
are additional parameters not unique to thecollection
if
residuals
is set toTrue
then only data-model residuals are returnedoptionally use
sampling_step
to specify a resampling of the original time series (an ISO-8601 duration).
request.set_products(measurements=["F","B_NEC"],
models=["MCO_SHA_2C", "MMA_SHA_2C-Primary", "MMA_SHA_2C-Secondary"],
auxiliaries=["QDLat", "QDLon", "MLT", "OrbitNumber", "SunZenithAngle"],
residuals=False,
sampling_step="PT10S")
Set a parameter range filter to apply. You can add multiple filters in sequence
request.set_range_filter(parameter="Latitude",
minimum=0,
maximum=90)
request.set_range_filter("Longitude", 0, 90)
Specify the time range from which to retrieve data, make the request to the server:
data = request.get_between(start_time=dt.datetime(2016,1,1),
end_time=dt.datetime(2016,1,2))
Transfer your data to a pandas.DataFrame, or a xarray.Dataset, or just save it as is:
df = data.as_dataframe()
ds = data.as_xarray()
data.to_file('outfile.cdf', overwrite=False)
The returned data has columns for:
Spacecraft, Timestamp, Latitude, Longitude, Radius
those specified by
measurements
andauxiliaries
… and model values and residuals, named as:
F_<model_id>
– scalar field
B_NEC_<model_id>
– vector field
F_res_<model_id>
– scalar field residual (F - F_<model_id>
)
B_NEC_res_<model_id>
– vector field residual (B_NEC - B_NEC_<model_id>
)