Demo EFIx_LP_1B (langmuir probe 2Hz)¶
Authors: Ashley Smith
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
2021-01-24T15:45:39+00:00
CPython 3.7.6
IPython 7.11.1
viresclient 0.7.1
pandas 0.25.3
xarray 0.15.0
matplotlib 3.1.2
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']}
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)
)
[1/1] Processing: 100%|██████████| [ Elapsed: 00:01, Remaining: 00:00 ]
Downloading: 100%|██████████| [ Elapsed: 00:00, Remaining: 00:00 ] (16.076MB)
data.sources
['SW_OPER_EFIA_LP_1B_20160101T000000_20160101T235959_0501_MDR_EFI_LP']
Load and plot using pandas/matplotlib¶
df = data.as_dataframe()
df.head()
| Radius | Longitude | Flags_Ne | Ne | Flags_LP | Te_error | Vs | Latitude | U_orbit | Flags_Te | Spacecraft | Vs_error | Ne_error | Te | Flags_Vs | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Timestamp | |||||||||||||||
| 2016-01-01 00:00:00.197000027 | 6833852.72 | 92.799630 | 20 | 126188.4 | 1 | 9.999990e+09 | -2.201 | -72.511716 | 7604.407 | 20 | A | 9.999990e+09 | 9.999990e+09 | 2945.20 | 20 |
| 2016-01-01 00:00:00.696000099 | 6833853.09 | 92.813944 | 20 | 127792.9 | 1 | 9.999990e+09 | -2.193 | -72.543238 | 7604.398 | 20 | A | 9.999990e+09 | 9.999990e+09 | 2891.97 | 20 |
| 2016-01-01 00:00:01.197000027 | 6833853.91 | 92.828370 | 20 | 132515.3 | 1 | 9.999990e+09 | -2.200 | -72.574886 | 7604.389 | 20 | A | 9.999990e+09 | 9.999990e+09 | 2921.96 | 20 |
| 2016-01-01 00:00:01.696000099 | 6833854.27 | 92.842799 | 20 | 137933.0 | 1 | 9.999990e+09 | -2.194 | -72.606406 | 7604.380 | 20 | A | 9.999990e+09 | 9.999990e+09 | 2936.74 | 20 |
| 2016-01-01 00:00:02.197000027 | 6833855.09 | 92.857342 | 20 | 138913.8 | 1 | 9.999990e+09 | -2.190 | -72.638051 | 7604.371 | 20 | A | 9.999990e+09 | 9.999990e+09 | 2870.09 | 20 |
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] 2016-01-01T00:00:00.197000027 ... 2016-01-01T23:59:59.696000099
Data variables:
Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
Radius (Timestamp) float64 6.834e+06 6.834e+06 ... 6.823e+06 6.823e+06
Longitude (Timestamp) float64 92.8 92.81 92.83 ... -95.37 -95.37 -95.37
Te (Timestamp) float64 2.945e+03 2.892e+03 ... 2.527e+03 2.545e+03
Flags_Ne (Timestamp) uint8 20 20 20 20 20 20 20 ... 20 20 20 20 20 20 20
Ne (Timestamp) float64 1.262e+05 1.278e+05 ... 6.485e+04 6.43e+04
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
Te_error (Timestamp) float64 1e+10 1e+10 1e+10 ... 1e+10 1e+10 1e+10
Vs (Timestamp) float64 -2.201 -2.193 -2.2 ... -2.244 -2.239 -2.243
Latitude (Timestamp) float64 -72.51 -72.54 -72.57 ... 31.65 31.69 31.72
U_orbit (Timestamp) float64 7.604e+03 7.604e+03 ... 7.634e+03 7.634e+03
Flags_Te (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
Ne_error (Timestamp) float64 1e+10 1e+10 1e+10 ... 1e+10 1e+10 1e+10
Flags_Vs (Timestamp) uint8 20 20 20 20 20 20 20 ... 20 20 20 20 20 20 20
Attributes:
Sources: ['SW_OPER_EFIA_LP_1B_20160101T000000_20160101T235959_050...
MagneticModels: []
RangeFilters: []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])
