Analysis of Cluster data

Analysis of Cluster data#

In this example we will access Cluster data via a HAPI server (not from VirES)

For more information about HAPI, see http://hapi-server.org/

import datetime as dt

from swarmpal.io import create_paldata, PalDataItem
from swarmpal.toolboxes import tfa

Fetching data#

We can access HAPI data in an almost identical way as from VirES, instead using PalDataItem.from_hapi.

Here we will use the AMDA service to get the data. This might change in the future.

Available HAPI data can be browsed at http://hapi-server.org/servers, to quickly look at the data or to generate code snippets using the Python hapiclient package - the inputs to hapiclient can be used in PalDataItem.from_hapi (hapiclient is used underneath within SwarmPAL). For example:

data_params = dict(
    server="https://csatools.esac.esa.int/HapiServer/hapi",
    dataset="C3_CP_FGM_SPIN",
    parameters="B_vec_xyz_gse",
    start="2015-03-29T17:00:00",
    stop="2015-03-29T19:00:00",
    pad_times=(dt.timedelta(hours=3), dt.timedelta(hours=3)),
)
data = create_paldata(PalDataItem.from_hapi(**data_params))
print(data)

HAPIError: Problem with https://csatools.esac.esa.int/HapiServer/hapi/data?id=C3_CP_FGM_SPIN&parameters=B_vec_xyz_gse&time.min=2015-03-29T14:00:00Z&time.max=2015-03-29T22:00:00Z&format=binary. Server responded with non-200 HTTP status (500) and an invalid JSON in response body. If problem persists, a contact email for the server may be listed at http://hapi-server.org/servers/

Processing#

p1 = tfa.processes.Preprocess()
p1.set_config(
    dataset="C3_CP_FGM_SPIN",
    timevar="time_tags",
    active_variable="B_vec_xyz_gse",
    active_component=2,
    sampling_rate=1 / 4,
)
p2 = tfa.processes.Clean()
p2.set_config(
    window_size=300,
    method="iqr",
    multiplier=1,
)
p3 = tfa.processes.Filter()
p3.set_config(
    cutoff_frequency=0.1,
)
p4 = tfa.processes.Wavelet()
p4.set_config(
    min_frequency=1,
    max_frequency=25,
    dj=0.1,
)

p1(data)
p2(data)
p3(data)
p4(data);

Plotting#

tfa.plotting.quicklook(data, extra_x=None);
Contents