EFIx_LP_1B (Langmuir probe 2Hz)

Abstract: Access to the electric field instrument langmuir probe data (2Hz) (level 1b product).

%load_ext watermark
%watermark -i -v -p viresclient,pandas,xarray,matplotlib

Python implementation: CPython
Python version       : 3.11.6
IPython version      : 8.18.0

viresclient: 0.12.0
pandas     : 2.1.3
xarray     : 2023.12.0
matplotlib : 3.8.2

from viresclient import SwarmRequest
import datetime as dt
import matplotlib.pyplot as plt

request = SwarmRequest()

EFIx_LP_1B product information

Measurements from the Langmuir Probe (LP) of the Electric Field Instrument (EFI) at 2Hz, for each Swarm spacecraft.

Documentation:

• https://earth.esa.int/web/guest/missions/esa-eo-missions/swarm/data-handbook/level-1b-product-definitions#EFIX_LP_1B_Product

Check what “EFI” data variables are available

request.available_collections("EFI", details=False)

{'EFI': ['SW_OPER_EFIA_LP_1B',
  'SW_OPER_EFIB_LP_1B',
  'SW_OPER_EFIC_LP_1B',
  'SW_FAST_EFIA_LP_1B',
  'SW_FAST_EFIB_LP_1B',
  'SW_FAST_EFIC_LP_1B']}

request.available_measurements("EFI")

['U_orbit',
 'Ne',
 'Ne_error',
 'Te',
 'Te_error',
 'Vs',
 'Vs_error',
 'Flags_LP',
 'Flags_Ne',
 'Flags_Te',
 'Flags_Vs']

Fetch one day of EFI data

request.set_collection("SW_OPER_EFIA_LP_1B")
request.set_products(
    measurements=['U_orbit',
                 'Ne',
                 'Ne_error',
                 'Te',
                 'Te_error',
                 'Vs',
                 'Vs_error',
                 'Flags_LP',
                 'Flags_Ne',
                 'Flags_Te',
                 'Flags_Vs']
)
data = request.get_between(
    dt.datetime(2016,1,1),
    dt.datetime(2016,1,2)
)

data.sources

['SW_OPER_EFIA_LP_1B_20160101T000000_20160101T235959_0602_MDR_EFI_LP']

Load and plot using pandas/matplotlib

df = data.as_dataframe()
df.head()

	Longitude	Radius	Ne_error	Te_error	Vs	Flags_LP	Flags_Te	Flags_Vs	Latitude	Ne	Te	Spacecraft	Vs_error	U_orbit	Flags_Ne
Timestamp
2016-01-01 00:00:00.196999936	92.799630	6833853.41	28365.234486	-245.895850	-2.201	1	10	20	-72.511716	126188.4	2945.204213	A	9.999990e+09	7604.407	10
2016-01-01 00:00:00.696000000	92.813943	6833854.00	28725.923124	-259.711123	-2.193	1	10	20	-72.543238	127792.9	2891.969742	A	9.999990e+09	7604.397	10
2016-01-01 00:00:01.196999936	92.828370	6833854.59	29787.432673	-247.826218	-2.200	1	10	20	-72.574886	132515.3	2921.955198	A	9.999990e+09	7604.388	10
2016-01-01 00:00:01.696000000	92.842799	6833855.18	31005.243307	-239.714158	-2.194	1	10	20	-72.606406	137933.0	2936.736557	A	9.999990e+09	7604.379	10
2016-01-01 00:00:02.196999936	92.857342	6833855.77	31225.718904	-257.759606	-2.190	1	10	20	-72.638051	138913.8	2870.090847	A	9.999990e+09	7604.370	10

df.plot(y=["Ne", "Te", "Vs"], subplots=True, figsize=(20,5));

df.plot(x="Latitude", y="Ne");

Load as xarray

ds = data.as_xarray()
ds

<xarray.Dataset>
Dimensions:     (Timestamp: 172776)
Coordinates:
  * Timestamp   (Timestamp) datetime64[ns] 2016-01-01T00:00:00.196999936 ... ...
Data variables: (12/15)
    Spacecraft  (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    Longitude   (Timestamp) float64 92.8 92.81 92.83 ... -95.37 -95.37 -95.37
    Radius      (Timestamp) float64 6.834e+06 6.834e+06 ... 6.823e+06 6.823e+06
    Te_error    (Timestamp) float64 -245.9 -259.7 -247.8 ... -408.5 -403.6
    Flags_LP    (Timestamp) uint8 1 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1
    Latitude    (Timestamp) float64 -72.51 -72.54 -72.57 ... 31.65 31.69 31.72
    ...          ...
    Ne_error    (Timestamp) float64 2.837e+04 2.873e+04 ... 1.458e+04 1.445e+04
    Vs          (Timestamp) float64 -2.201 -2.193 -2.2 ... -2.244 -2.239 -2.243
    Flags_Te    (Timestamp) uint8 10 10 10 10 10 10 10 ... 10 10 10 10 10 10 10
    Flags_Vs    (Timestamp) uint8 20 20 20 20 20 20 20 ... 20 20 20 20 20 20 20
    Vs_error    (Timestamp) float64 1e+10 1e+10 1e+10 ... 1e+10 1e+10 1e+10
    Flags_Ne    (Timestamp) uint8 10 10 10 10 10 10 10 ... 10 10 10 10 10 10 10
Attributes:
    Sources:         ['SW_OPER_EFIA_LP_1B_20160101T000000_20160101T235959_060...
    MagneticModels:  []
    AppliedFilters:  []

xarray.Dataset

• Dimensions:
  • Timestamp: 172776
• Coordinates: (1)
  • Timestamp
    (Timestamp)
    datetime64[ns]
    2016-01-01T00:00:00.196999936 .....

    description :

    Time stamp

    array(['2016-01-01T00:00:00.196999936', '2016-01-01T00:00:00.696000000',
           '2016-01-01T00:00:01.196999936', ..., '2016-01-01T23:59:58.696000000',
           '2016-01-01T23:59:59.196999936', '2016-01-01T23:59:59.696000000'],
          dtype='datetime64[ns]')

• Data variables: (15)
  • Spacecraft
    (Timestamp)
    object
    'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'

    units :

    -

    description :

    Spacecraft identifier (values: 'A', 'B', 'C' or '-' if not available).

    array(['A', 'A', 'A', ..., 'A', 'A', 'A'], dtype=object)

  • Longitude
    (Timestamp)
    float64
    92.8 92.81 92.83 ... -95.37 -95.37

    units :

    deg

    description :

    Position in ITRF - Longitude

    array([ 92.7996303,  92.8139434,  92.8283701, ..., -95.369626 ,
           -95.3696651, -95.3697041])

  • Radius
    (Timestamp)
    float64
    6.834e+06 6.834e+06 ... 6.823e+06

    units :

    m

    description :

    Position in ITRF - Radius

    array([6833853.41, 6833854.  , 6833854.59, ..., 6822824.68, 6822821.24,
           6822821.74])

  • Te_error
    (Timestamp)
    float64
    -245.9 -259.7 ... -408.5 -403.6

    units :

    K

    description :

    Error estimate of plasma electron temperature (Te)

    array([-245.89585004, -259.71112264, -247.82621788, ..., -396.96304581,
           -408.46046478, -403.64152422])

  • Flags_LP
    (Timestamp)
    uint8
    1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1

    units :

    -

    description :

    Flags indicating the source/method of LP measurements (Ne, Te, Vs)

    array([1, 1, 1, ..., 1, 1, 1], dtype=uint8)

  • Latitude
    (Timestamp)
    float64
    -72.51 -72.54 ... 31.69 31.72

    units :

    deg

    description :

    Position in ITRF - Latitude

    array([-72.5117157, -72.5432384, -72.5748862, ...,  31.6548053,
            31.6869228,  31.7189122])

  • Ne
    (Timestamp)
    float64
    1.262e+05 1.278e+05 ... 6.43e+04

    units :

    cm-3

    description :

    Plasma density (electron)

    array([126188.4, 127792.9, 132515.3, ...,  64617.9,  64852.5,  64298.7])

  • Te
    (Timestamp)
    float64
    2.945e+03 2.892e+03 ... 2.545e+03

    units :

    K

    description :

    Plasma electron temperature

    array([2945.20421293, 2891.96974223, 2921.95519825, ..., 2568.06791336,
           2526.61671558, 2545.17018937])

  • U_orbit
    (Timestamp)
    float64
    7.604e+03 7.604e+03 ... 7.634e+03

    units :

    m/s

    description :

    Spacecraft velocity in the ITRF

    array([7604.407, 7604.397, 7604.388, ..., 7633.896, 7633.891, 7633.889])

  • Ne_error
    (Timestamp)
    float64
    2.837e+04 2.873e+04 ... 1.445e+04

    units :

    cm-3

    description :

    Error estimate of plasma density (Ne)

    array([28365.23448584, 28725.92312432, 29787.43267282, ...,
           14525.12819323, 14577.86255232, 14453.38408684])

  • Vs
    (Timestamp)
    float64
    -2.201 -2.193 ... -2.239 -2.243

    units :

    V

    description :

    Spacecraft potential

    array([-2.201, -2.193, -2.2  , ..., -2.244, -2.239, -2.243])

  • Flags_Te
    (Timestamp)
    uint8
    10 10 10 10 10 ... 10 10 10 10 10

    units :

    -

    description :

    Flags characterizing the electron temperature measurement

    array([10, 10, 10, ..., 10, 10, 10], dtype=uint8)

  • Flags_Vs
    (Timestamp)
    uint8
    20 20 20 20 20 ... 20 20 20 20 20

    units :

    -

    description :

    Flags characterizing the spacecraft potential measurement

    array([20, 20, 20, ..., 20, 20, 20], dtype=uint8)

  • Vs_error
    (Timestamp)
    float64
    1e+10 1e+10 1e+10 ... 1e+10 1e+10

    units :

    V

    description :

    Error estimate of spacecraft potential (Vs)

    array([9.99999e+09, 9.99999e+09, 9.99999e+09, ..., 9.99999e+09,
           9.99999e+09, 9.99999e+09])

  • Flags_Ne
    (Timestamp)
    uint8
    10 10 10 10 10 ... 10 10 10 10 10

    units :

    -

    description :

    Flags characterizing the plasma density measurement

    array([10, 10, 10, ..., 10, 10, 10], dtype=uint8)

• Indexes: (1)
  • Timestamp
    PandasIndex

    PandasIndex(DatetimeIndex(['2016-01-01 00:00:00.196999936',
                      '2016-01-01 00:00:00.696000',
                   '2016-01-01 00:00:01.196999936',
                      '2016-01-01 00:00:01.696000',
                   '2016-01-01 00:00:02.196999936',
                      '2016-01-01 00:00:02.696000',
                   '2016-01-01 00:00:03.196999936',
                      '2016-01-01 00:00:03.696000',
                   '2016-01-01 00:00:04.196999936',
                      '2016-01-01 00:00:04.696000',
                   ...
                   '2016-01-01 23:59:55.196999936',
                      '2016-01-01 23:59:55.696000',
                   '2016-01-01 23:59:56.196999936',
                      '2016-01-01 23:59:56.696000',
                   '2016-01-01 23:59:57.196999936',
                      '2016-01-01 23:59:57.696000',
                   '2016-01-01 23:59:58.196999936',
                      '2016-01-01 23:59:58.696000',
                   '2016-01-01 23:59:59.196999936',
                      '2016-01-01 23:59:59.696000'],
                  dtype='datetime64[ns]', name='Timestamp', length=172776, freq=None))

• Attributes: (3)

  Sources :

  ['SW_OPER_EFIA_LP_1B_20160101T000000_20160101T235959_0602_MDR_EFI_LP']

  MagneticModels :

  []

  AppliedFilters :

  []

fig, (ax1, ax2) = plt.subplots(figsize=(10, 5), nrows=2, sharex=True)
def subplot(_ax, da):
    """Plot a given DataArray on a given axes"""
    _ax.plot(da)
    _ax.set_ylabel(f"{da.name} [{da.units}]")
for var, ax in zip(("Ne", "Te"), (ax1, ax2)):
    subplot(ax, ds[var])