{
"cells": [
{
"cell_type": "markdown",
"id": "956e8dc7-6518-49f1-ba69-f2b3e26421b6",
"metadata": {},
"source": [
"# EFIxIDM (Ion drifts & effective masses)"
]
},
{
"cell_type": "markdown",
"id": "5dd310e4-c8f7-4bb4-a925-24386289ffc6",
"metadata": {},
"source": [
"> Abstract: Access to the `EFIxIDM` products from the SLIDEM project.\n",
"\n",
"See also:\n",
"- More notebooks: https://nbviewer.org/github/pacesm/jupyter_notebooks/tree/master/EFI_TII/EFIxIDM_00_data_access.ipynb\n",
"- Product documentation: https://earth.esa.int/eogateway/documents/20142/2860886/SLIDEM_Product_Definition.pdf"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0f28bd4f-c79f-4b1c-8a7e-153885266777",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:10.866492Z",
"iopub.status.busy": "2025-06-21T21:46:10.866318Z",
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"shell.execute_reply": "2025-06-21T21:46:10.871378Z"
}
},
"outputs": [],
"source": [
"SERVER_URL = 'https://vires.services/ows'"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "62048561-5816-49fc-94e2-4bd99a9bb260",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:10.874199Z",
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"shell.execute_reply": "2025-06-21T21:46:11.574851Z"
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Python implementation: CPython\n",
"Python version : 3.11.6\n",
"IPython version : 8.18.0\n",
"\n",
"viresclient: 0.12.3\n",
"pandas : 2.1.3\n",
"xarray : 2023.12.0\n",
"matplotlib : 3.8.2\n",
"\n"
]
}
],
"source": [
"# Display important package versions used\n",
"%load_ext watermark\n",
"%watermark -i -v -p viresclient,pandas,xarray,matplotlib"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "33c1bd0d-3166-42a8-9be0-a93c95a4e3f1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:11.578273Z",
"iopub.status.busy": "2025-06-21T21:46:11.577675Z",
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"shell.execute_reply": "2025-06-21T21:46:11.770852Z"
}
},
"outputs": [],
"source": [
"import datetime as dt\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import xarray as xr\n",
"# Control the HTML display of the datasets\n",
"xr.set_options(display_expand_attrs=False, display_expand_coords=True, display_expand_data=True)\n",
"\n",
"from viresclient import SwarmRequest"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f5cbe7c9-f904-4936-86d5-35a163ffc9fd",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:11.773810Z",
"iopub.status.busy": "2025-06-21T21:46:11.773639Z",
"iopub.status.idle": "2025-06-21T21:46:12.375333Z",
"shell.execute_reply": "2025-06-21T21:46:12.374864Z"
}
},
"outputs": [],
"source": [
"request = SwarmRequest(SERVER_URL)"
]
},
{
"cell_type": "markdown",
"id": "1364f43b-b2c4-40c5-b899-578ba9eed531",
"metadata": {
"tags": []
},
"source": [
"## What data is available?"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "78eb7107-86d4-4576-a834-503e248d39e9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:12.377532Z",
"iopub.status.busy": "2025-06-21T21:46:12.377363Z",
"iopub.status.idle": "2025-06-21T21:46:12.383219Z",
"shell.execute_reply": "2025-06-21T21:46:12.382661Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"{'EFI_IDM': ['SW_PREL_EFIAIDM_2_', 'SW_PREL_EFIBIDM_2_', 'SW_PREL_EFICIDM_2_']}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"request.available_collections(\"EFI_IDM\", details=False)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "57a02063-fd2e-4b35-b663-9b70c9db037e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:12.385106Z",
"iopub.status.busy": "2025-06-21T21:46:12.384923Z",
"iopub.status.idle": "2025-06-21T21:46:12.388097Z",
"shell.execute_reply": "2025-06-21T21:46:12.387565Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Latitude_GD', 'Longitude_GD', 'Height_GD', 'Radius_GC', 'Latitude_QD', 'MLT_QD', 'V_sat_nec', 'M_i_eff', 'M_i_eff_err', 'M_i_eff_Flags', 'M_i_eff_tbt_model', 'V_i', 'V_i_err', 'V_i_Flags', 'V_i_raw', 'N_i', 'N_i_err', 'N_i_Flags', 'A_fp', 'R_p', 'T_e', 'Phi_sc']\n"
]
}
],
"source": [
"print(request.available_measurements(\"EFI_IDM\"))"
]
},
{
"cell_type": "markdown",
"id": "b87948d1-3c26-4255-9323-a97b85f3088e",
"metadata": {},
"source": [
"Notes for the listed available variables:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "66b0a478-69e5-4c3c-a6cf-928cccd01084",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:12.389909Z",
"iopub.status.busy": "2025-06-21T21:46:12.389565Z",
"iopub.status.idle": "2025-06-21T21:46:12.392919Z",
"shell.execute_reply": "2025-06-21T21:46:12.392430Z"
}
},
"outputs": [],
"source": [
"idm_vars = [\n",
" # Positional information in geodetic (GD) and geocentric (GC) frames\n",
" # redundant with VirES variables Latitude, Longitude, Radius (in geocentric frame)\n",
" \"Latitude_GD\", \"Longitude_GD\", \"Height_GD\", \"Radius_GC\",\n",
" # Quasi-dipole magnetic latitude and local time\n",
" # redundant with VirES auxiliaries, QDLat & MLT\n",
" \"Latitude_QD\", \"MLT_QD\",\n",
" # Satellite velocity in NEC frame\n",
" \"V_sat_nec\",\n",
" # Estimated ion effective mass, uncertainty, and validity flags\n",
" \"M_i_eff\", \"M_i_eff_err\", \"M_i_eff_Flags\",\n",
" # Effective masses from ruhlik et al. (2015) topside empirical model\n",
" \"M_i_eff_tbt_model\",\n",
" # Along-track ion drift velocity, uncertainty, validity flags, and velocity without detrending\n",
" \"V_i\", \"V_i_err\", \"V_i_Flags\", \"V_i_raw\",\n",
" # Ion density, uncertainty, and validity flags\n",
" \"N_i\", \"N_i_err\", \"N_i_Flags\",\n",
" # Modified-OML faceplate area, and Langmuir spherical probe radius\n",
" \"A_fp\", \"R_p\",\n",
" # Electron temperature, and spacecraft floating potential\n",
" \"T_e\", \"Phi_sc\",\n",
"]"
]
},
{
"cell_type": "markdown",
"id": "43566335-a428-437f-bb8f-f2bac2e7d768",
"metadata": {
"tags": []
},
"source": [
"## Fetching and plotting data"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "42d1ac20-42e5-4bab-8bae-d025587758eb",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:12.394534Z",
"iopub.status.busy": "2025-06-21T21:46:12.394372Z",
"iopub.status.idle": "2025-06-21T21:46:20.068587Z",
"shell.execute_reply": "2025-06-21T21:46:20.068039Z"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b913481728604b6cbd4917ab0e18d8ea",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Processing: 0%| | [ Elapsed: 00:00, Remaining: ? ] [1/1] "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "dcd6bc5ce9ac42099a0cc49bf034cb00",
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"text/plain": [
"Downloading: 0%| | [ Elapsed: 00:00, Remaining: ? ] (38.772MB)"
]
},
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"output_type": "display_data"
}
],
"source": [
"start = dt.datetime(2016, 1, 2)\n",
"end = dt.datetime(2016, 1, 3)\n",
"\n",
"request = SwarmRequest(SERVER_URL)\n",
"request.set_collection(\"SW_PREL_EFIAIDM_2_\")\n",
"request.set_products(\n",
" measurements=idm_vars,\n",
" auxiliaries=[\"OrbitNumber\", \"OrbitDirection\", \"MLT\"]\n",
")\n",
"data = request.get_between(start, end)"
]
},
{
"cell_type": "markdown",
"id": "c0d9e566-7564-4d38-b070-6a67e121a797",
"metadata": {},
"source": [
"Data can be loaded as either a pandas dataframe or a xarray dataset."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "29d9590f-5696-4d6a-87db-5d360cf96b67",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:20.070891Z",
"iopub.status.busy": "2025-06-21T21:46:20.070563Z",
"iopub.status.idle": "2025-06-21T21:46:25.014842Z",
"shell.execute_reply": "2025-06-21T21:46:25.014246Z"
}
},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>OrbitDirection</th>\n",
" <th>MLT_QD</th>\n",
" <th>OrbitNumber</th>\n",
" <th>A_fp</th>\n",
" <th>V_i_raw</th>\n",
" <th>V_i_Flags</th>\n",
" <th>N_i_Flags</th>\n",
" <th>M_i_eff</th>\n",
" <th>Height_GD</th>\n",
" <th>Spacecraft</th>\n",
" <th>...</th>\n",
" <th>N_i</th>\n",
" <th>V_sat_nec</th>\n",
" <th>MLT</th>\n",
" <th>Latitude</th>\n",
" <th>T_e</th>\n",
" <th>Radius</th>\n",
" <th>Longitude</th>\n",
" <th>Phi_sc</th>\n",
" <th>M_i_eff_Flags</th>\n",
" <th>V_i</th>\n",
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],
"text/plain": [
" OrbitDirection MLT_QD OrbitNumber A_fp \\\n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 1 17.699699 11819 -1.0 \n",
"2016-01-02 00:00:00.696000000 1 17.699779 11819 -1.0 \n",
"2016-01-02 00:00:01.196999936 1 17.699859 11819 -1.0 \n",
"2016-01-02 00:00:01.696000000 1 17.699939 11819 -1.0 \n",
"2016-01-02 00:00:02.196999936 1 17.700020 11819 -1.0 \n",
"\n",
" V_i_raw V_i_Flags N_i_Flags M_i_eff \\\n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 -100000.0 65537 1 -1.0 \n",
"2016-01-02 00:00:00.696000000 -100000.0 65537 1 -1.0 \n",
"2016-01-02 00:00:01.196999936 -100000.0 65537 1 -1.0 \n",
"2016-01-02 00:00:01.696000000 -100000.0 65537 1 -1.0 \n",
"2016-01-02 00:00:02.196999936 -100000.0 65537 1 -1.0 \n",
"\n",
" Height_GD Spacecraft ... N_i \\\n",
"Timestamp ... \n",
"2016-01-02 00:00:00.196999936 450611.260628 A ... -1.0 \n",
"2016-01-02 00:00:00.696000000 450616.006079 A ... -1.0 \n",
"2016-01-02 00:00:01.196999936 450620.775650 A ... -1.0 \n",
"2016-01-02 00:00:01.696000000 450625.534017 A ... -1.0 \n",
"2016-01-02 00:00:02.196999936 450630.316542 A ... -1.0 \n",
"\n",
" V_sat_nec \\\n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 [7633.863553943817, -6.920940102624664, 11.954... \n",
"2016-01-02 00:00:00.696000000 [7633.856932675894, -6.63003468935507, 11.9539... \n",
"2016-01-02 00:00:01.196999936 [7633.850269983615, -6.337677392264973, 11.952... \n",
"2016-01-02 00:00:01.696000000 [7633.843611009006, -6.046047719097451, 11.951... \n",
"2016-01-02 00:00:02.196999936 [7633.836910386861, -5.752962995448166, 11.950... \n",
"\n",
" MLT Latitude T_e \\\n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 17.155861 31.751028 2660.305569 \n",
"2016-01-02 00:00:00.696000000 17.155920 31.783018 2640.667985 \n",
"2016-01-02 00:00:01.196999936 17.155981 31.815135 2629.307430 \n",
"2016-01-02 00:00:01.696000000 17.156040 31.847124 2626.466513 \n",
"2016-01-02 00:00:02.196999936 17.156099 31.879242 2645.862873 \n",
"\n",
" Radius Longitude Phi_sc \\\n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 6.822807e+06 -95.369735 -2.263921 \n",
"2016-01-02 00:00:00.696000000 6.822801e+06 -95.369768 -2.267120 \n",
"2016-01-02 00:00:01.196999936 6.822795e+06 -95.369800 -2.271875 \n",
"2016-01-02 00:00:01.696000000 6.822789e+06 -95.369831 -2.277763 \n",
"2016-01-02 00:00:02.196999936 6.822783e+06 -95.369860 -2.265846 \n",
"\n",
" M_i_eff_Flags V_i \n",
"Timestamp \n",
"2016-01-02 00:00:00.196999936 1 -100000.0 \n",
"2016-01-02 00:00:00.696000000 1 -100000.0 \n",
"2016-01-02 00:00:01.196999936 1 -100000.0 \n",
"2016-01-02 00:00:01.696000000 1 -100000.0 \n",
"2016-01-02 00:00:02.196999936 1 -100000.0 \n",
"\n",
"[5 rows x 29 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = data.as_dataframe()\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e803eaa7-e36b-4af2-a087-99eeea2fcc14",
"metadata": {
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"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
"Dimensions: (Timestamp: 171434, V_sat_nec_dim1: 3)\n",
"Coordinates:\n",
" * Timestamp (Timestamp) datetime64[ns] 2016-01-02T00:00:00.1969999...\n",
"Dimensions without coordinates: V_sat_nec_dim1\n",
"Data variables: (12/29)\n",
" Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'\n",
" OrbitDirection (Timestamp) int8 1 1 1 1 1 1 1 1 ... -1 -1 -1 -1 -1 -1 -1\n",
" MLT_QD (Timestamp) float64 17.7 17.7 17.7 ... 5.63 5.63 5.63\n",
" OrbitNumber (Timestamp) int32 11819 11819 11819 ... 11834 11834 11834\n",
" A_fp (Timestamp) float64 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0\n",
" V_i_raw (Timestamp) float64 -1e+05 -1e+05 ... -1e+05 -1e+05\n",
" ... ...\n",
" T_e (Timestamp) float64 2.66e+03 2.641e+03 ... 1.73e+03\n",
" Radius (Timestamp) float64 6.823e+06 6.823e+06 ... 6.826e+06\n",
" Longitude (Timestamp) float64 -95.37 -95.37 -95.37 ... 81.23 81.23\n",
" Phi_sc (Timestamp) float64 -2.264 -2.267 ... -1.901 -1.919\n",
" M_i_eff_Flags (Timestamp) uint32 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
" V_i (Timestamp) float64 -1e+05 -1e+05 ... -1e+05 -1e+05\n",
"Attributes: (3)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b2e8cc53-aced-411e-b8bf-9dc93d82c7af' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b2e8cc53-aced-411e-b8bf-9dc93d82c7af' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Timestamp</span>: 171434</li><li><span>V_sat_nec_dim1</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-96ad357d-ddbc-4bcf-8173-7e583cbb12d6' class='xr-section-summary-in' type='checkbox' checked><label for='section-96ad357d-ddbc-4bcf-8173-7e583cbb12d6' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Timestamp</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-01-02T00:00:00.196999936 .....</div><input id='attrs-6b5db667-c948-4b13-ba35-0c4b60d7e917' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b5db667-c948-4b13-ba35-0c4b60d7e917' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6d013c9-f146-4fc6-9766-b8d492f0835d' class='xr-var-data-in' type='checkbox'><label for='data-e6d013c9-f146-4fc6-9766-b8d492f0835d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>UT</dd></dl></div><div class='xr-var-data'><pre>array(['2016-01-02T00:00:00.196999936', '2016-01-02T00:00:00.696000000',\n",
" '2016-01-02T00:00:01.196999936', ..., '2016-01-02T23:59:58.696000000',\n",
" '2016-01-02T23:59:59.196999936', '2016-01-02T23:59:59.696000000'],\n",
" dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24828810-af44-47b1-92cb-521bbf0d992f' class='xr-section-summary-in' type='checkbox' ><label for='section-24828810-af44-47b1-92cb-521bbf0d992f' class='xr-section-summary' >Data variables: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Spacecraft</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'</div><input id='attrs-71cc83de-2805-4b44-ac64-6a8d422c54c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71cc83de-2805-4b44-ac64-6a8d422c54c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce1ad08e-cef3-48e9-b883-147d6672e92f' class='xr-var-data-in' type='checkbox'><label for='data-ce1ad08e-cef3-48e9-b883-147d6672e92f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>description :</span></dt><dd>Spacecraft identifier (values: 'A', 'B', 'C' or '-' if not available).</dd></dl></div><div class='xr-var-data'><pre>array(['A', 'A', 'A', ..., 'A', 'A', 'A'], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OrbitDirection</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 ... -1 -1 -1 -1 -1 -1</div><input id='attrs-108bd6de-40f9-416c-9637-9d8a3a62dd8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-108bd6de-40f9-416c-9637-9d8a3a62dd8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64090835-0b23-4c3f-bec6-58d936def48b' class='xr-var-data-in' type='checkbox'><label for='data-64090835-0b23-4c3f-bec6-58d936def48b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>description :</span></dt><dd>Orbit direction in geographic coordinates (values: 1 - ascending, -1 - descending, 0 - undefined)</dd></dl></div><div class='xr-var-data'><pre>array([ 1, 1, 1, ..., -1, -1, -1], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MLT_QD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.7 17.7 17.7 ... 5.63 5.63 5.63</div><input id='attrs-66d67030-69b1-43ff-acf1-09cf536a2fb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66d67030-69b1-43ff-acf1-09cf536a2fb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31637ef5-a54e-42d3-991e-61def86f8953' class='xr-var-data-in' type='checkbox'><label for='data-31637ef5-a54e-42d3-991e-61def86f8953' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hour</dd><dt><span>description :</span></dt><dd>Magnetic local time.</dd></dl></div><div class='xr-var-data'><pre>array([17.69969892, 17.69977863, 17.69985885, ..., 5.62979165,\n",
" 5.62984713, 5.62989804])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OrbitNumber</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>11819 11819 11819 ... 11834 11834</div><input id='attrs-16bea30e-a274-4539-90d5-8560cb122b84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16bea30e-a274-4539-90d5-8560cb122b84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4649dde6-6630-472a-a560-a5e7951fb73c' class='xr-var-data-in' type='checkbox'><label for='data-4649dde6-6630-472a-a560-a5e7951fb73c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>description :</span></dt><dd>Orbit number (set to -1 if not available)</dd></dl></div><div class='xr-var-data'><pre>array([11819, 11819, 11819, ..., 11834, 11834, 11834], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_fp</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-a938d8af-8654-4766-81d6-774f0b038058' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a938d8af-8654-4766-81d6-774f0b038058' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfecdd3b-d873-48a7-bceb-d855ef292e86' class='xr-var-data-in' type='checkbox'><label for='data-dfecdd3b-d873-48a7-bceb-d855ef292e86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2</dd><dt><span>description :</span></dt><dd>Modified-OML EFI faceplate area.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_i_raw</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1e+05 -1e+05 ... -1e+05 -1e+05</div><input id='attrs-cc6875ff-f1bb-4f21-86e7-72d678bd41ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc6875ff-f1bb-4f21-86e7-72d678bd41ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbb3d453-649a-40cd-833d-fa66538ff5b0' class='xr-var-data-in' type='checkbox'><label for='data-fbb3d453-649a-40cd-833d-fa66538ff5b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion along-track drift without high-latitude detrending.</dd></dl></div><div class='xr-var-data'><pre>array([-100000., -100000., -100000., ..., -100000., -100000., -100000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_i_Flags</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>65537 65537 65537 ... 65537 65537</div><input id='attrs-09338211-a686-40d5-a221-0915a7b5be35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09338211-a686-40d5-a221-0915a7b5be35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b56f76ec-5364-4162-85b9-3ba57b9a1043' class='xr-var-data-in' type='checkbox'><label for='data-b56f76ec-5364-4162-85b9-3ba57b9a1043' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd> </dd><dt><span>description :</span></dt><dd>Ion along-track drift validity flag.</dd></dl></div><div class='xr-var-data'><pre>array([65537, 65537, 65537, ..., 65537, 65537, 65537], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_i_Flags</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-a324bf94-dc2d-4af7-86f5-c8cac4ef7af7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a324bf94-dc2d-4af7-86f5-c8cac4ef7af7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b789c465-a789-4f0b-bbbe-66c722313d3e' class='xr-var-data-in' type='checkbox'><label for='data-b789c465-a789-4f0b-bbbe-66c722313d3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd> </dd><dt><span>description :</span></dt><dd>Ion density validity flag.</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>M_i_eff</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-92b80f19-a8f8-45cc-8327-0c4e8b3d2c8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92b80f19-a8f8-45cc-8327-0c4e8b3d2c8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd56c21d-fa0a-4cf9-8387-60e0622f41cb' class='xr-var-data-in' type='checkbox'><label for='data-dd56c21d-fa0a-4cf9-8387-60e0622f41cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>a.m.u.</dd><dt><span>description :</span></dt><dd>Ion effective mass.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Height_GD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.506e+05 4.506e+05 ... 4.488e+05</div><input id='attrs-a224fb4c-fd92-4881-a397-3d72a85a37bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a224fb4c-fd92-4881-a397-3d72a85a37bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3ff7631-abc2-4f20-9749-e790d7a5e6fc' class='xr-var-data-in' type='checkbox'><label for='data-d3ff7631-abc2-4f20-9749-e790d7a5e6fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Height above WGS84 reference ellipsoid.</dd></dl></div><div class='xr-var-data'><pre>array([450611.26062783, 450616.0060794 , 450620.7756498 , ...,\n",
" 448838.64927267, 448840.60759022, 448842.61679218])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude_GD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-95.37 -95.37 ... 81.23 81.23</div><input id='attrs-c99f326b-71d1-4183-936c-28afad07608e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c99f326b-71d1-4183-936c-28afad07608e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7b0c3ab-7581-47bc-a536-1ac810483dc8' class='xr-var-data-in' type='checkbox'><label for='data-e7b0c3ab-7581-47bc-a536-1ac810483dc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Geodetic longitude.</dd></dl></div><div class='xr-var-data'><pre>array([-95.36973484, -95.36976808, -95.36980033, ..., 81.23327223,\n",
" 81.23270128, 81.23213248])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>R_p</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-3b425c5b-0df6-4a4f-a8a2-2c69e0a62a4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b425c5b-0df6-4a4f-a8a2-2c69e0a62a4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6349abf-9d6e-45eb-87d6-e63160a8df23' class='xr-var-data-in' type='checkbox'><label for='data-d6349abf-9d6e-45eb-87d6-e63160a8df23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Modified-OML Langmuir spherical probe radius.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>M_i_eff_tbt_model</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-a53a8a9d-cc3f-4fca-8d10-dbf9fce1d4a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a53a8a9d-cc3f-4fca-8d10-dbf9fce1d4a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e81ef150-8d82-4304-97a3-c648def2a2c5' class='xr-var-data-in' type='checkbox'><label for='data-e81ef150-8d82-4304-97a3-c648def2a2c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>a.m.u.</dd><dt><span>description :</span></dt><dd>Ion effective mass from Truhlik et al. (2015) topside empirical model.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_i_err</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-2676c5fe-b4a1-4cf2-9a3f-3291b7355af3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2676c5fe-b4a1-4cf2-9a3f-3291b7355af3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9be0e90a-a753-4e6c-b0dd-d9df5196a1b3' class='xr-var-data-in' type='checkbox'><label for='data-9be0e90a-a753-4e6c-b0dd-d9df5196a1b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion along-track drift uncertainty.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>M_i_eff_err</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-736f5d5a-97dc-4194-bc79-e664546d16f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-736f5d5a-97dc-4194-bc79-e664546d16f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a74296f-05ee-418c-a793-96c8ca928da9' class='xr-var-data-in' type='checkbox'><label for='data-0a74296f-05ee-418c-a793-96c8ca928da9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>a.m.u.</dd><dt><span>description :</span></dt><dd>Ion effective mass uncertainty.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude_QD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>41.45 41.48 41.52 ... 1.418 1.383</div><input id='attrs-7d945ada-3ec7-4aff-8d75-31453a4e869a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d945ada-3ec7-4aff-8d75-31453a4e869a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a6145d5-a5be-4be7-a01c-f7e5ab432f7e' class='xr-var-data-in' type='checkbox'><label for='data-5a6145d5-a5be-4be7-a01c-f7e5ab432f7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Quasi-dipole magnetic latitude.</dd></dl></div><div class='xr-var-data'><pre>array([41.45241687, 41.48416211, 41.51603308, ..., 1.45330483,\n",
" 1.41792872, 1.38274452])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radius_GC</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.822e+06 6.822e+06 ... 6.82e+06</div><input id='attrs-e6162b12-09cb-4af7-bd83-b2828ba2ca25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6162b12-09cb-4af7-bd83-b2828ba2ca25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-169ec266-016f-4495-a4c0-b8b21d23b69a' class='xr-var-data-in' type='checkbox'><label for='data-169ec266-016f-4495-a4c0-b8b21d23b69a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Geocentric radius.</dd></dl></div><div class='xr-var-data'><pre>array([6821611.26062783, 6821616.0060794 , 6821620.7756498 , ...,\n",
" 6819838.64927267, 6819840.60759022, 6819842.61679218])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude_GD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.91 31.94 31.98 ... 8.765 8.733</div><input id='attrs-4bae3b06-4ece-4859-b9d0-e63d42b6fadb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bae3b06-4ece-4859-b9d0-e63d42b6fadb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df5ba2f8-cd02-45f3-a7da-268c9ddf3f9b' class='xr-var-data-in' type='checkbox'><label for='data-df5ba2f8-cd02-45f3-a7da-268c9ddf3f9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Geodetic latitude.</dd></dl></div><div class='xr-var-data'><pre>array([31.91207375, 31.94415197, 31.97635859, ..., 8.79751087,\n",
" 8.76521142, 8.73304066])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_i_err</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-17d980ec-5805-4235-ae57-b0c5755717e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17d980ec-5805-4235-ae57-b0c5755717e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c30501e-b0e8-43c0-8be6-58b5938bd0b7' class='xr-var-data-in' type='checkbox'><label for='data-3c30501e-b0e8-43c0-8be6-58b5938bd0b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>cm^-3</dd><dt><span>description :</span></dt><dd>Ion density unertainty.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_i</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0</div><input id='attrs-f7d538c1-a1ad-41e7-accd-6e7047cbf730' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7d538c1-a1ad-41e7-accd-6e7047cbf730' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5df06cf2-9980-4f62-b8fc-53fdcfd6ea2a' class='xr-var-data-in' type='checkbox'><label for='data-5df06cf2-9980-4f62-b8fc-53fdcfd6ea2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>cm^-3</dd><dt><span>description :</span></dt><dd>Ion density.</dd></dl></div><div class='xr-var-data'><pre>array([-1., -1., -1., ..., -1., -1., -1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_sat_nec</span></div><div class='xr-var-dims'>(Timestamp, V_sat_nec_dim1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.634e+03 -6.921 ... -134.1 -11.06</div><input id='attrs-07ad04f3-a434-4efd-94de-88c5e7ffc5ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07ad04f3-a434-4efd-94de-88c5e7ffc5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b281d6b-9c8c-4315-a278-5d4c48e648e7' class='xr-var-data-in' type='checkbox'><label for='data-0b281d6b-9c8c-4315-a278-5d4c48e648e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Satellite velocity in north, east, centre (NEC) reference frame.</dd></dl></div><div class='xr-var-data'><pre>array([[ 7.63386355e+03, -6.92094010e+00, 1.19549946e+01],\n",
" [ 7.63385693e+03, -6.63003469e+00, 1.19539629e+01],\n",
" [ 7.63385027e+03, -6.33767739e+00, 1.19529218e+01],\n",
" ...,\n",
" [-7.63539032e+03, -1.34203948e+02, -1.10608847e+01],\n",
" [-7.63538737e+03, -1.34277941e+02, -1.10581550e+01],\n",
" [-7.63539441e+03, -1.34101155e+02, -1.10646767e+01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MLT</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.16 17.16 17.16 ... 5.09 5.09</div><input id='attrs-b097ae8d-4923-4c83-b795-a078d68f0035' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b097ae8d-4923-4c83-b795-a078d68f0035' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b9b4a05-947c-4f5c-b841-6ab593a6e0b1' class='xr-var-data-in' type='checkbox'><label for='data-9b9b4a05-947c-4f5c-b841-6ab593a6e0b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>h</dd><dt><span>description :</span></dt><dd>Magnetic local time</dd></dl></div><div class='xr-var-data'><pre>array([17.1558609 , 17.15592003, 17.15598106, ..., 5.0902462 ,\n",
" 5.09028435, 5.0903244 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.75 31.78 31.82 ... 8.711 8.679</div><input id='attrs-c013339b-7dd8-40e3-8a9d-fe59bac8ee16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c013339b-7dd8-40e3-8a9d-fe59bac8ee16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa491971-25f6-452a-90be-9fb2573c88ad' class='xr-var-data-in' type='checkbox'><label for='data-aa491971-25f6-452a-90be-9fb2573c88ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>description :</span></dt><dd>Position in ITRF - Latitude</dd></dl></div><div class='xr-var-data'><pre>array([31.7510283 , 31.78301756, 31.81513508, ..., 8.74334151,\n",
" 8.71123476, 8.679256 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_e</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.66e+03 2.641e+03 ... 1.73e+03</div><input id='attrs-21606f7d-5cfe-40e2-b651-ecdb18fa7c32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21606f7d-5cfe-40e2-b651-ecdb18fa7c32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cd35cd6-5b8a-4745-97b5-2af6a9b837bb' class='xr-var-data-in' type='checkbox'><label for='data-8cd35cd6-5b8a-4745-97b5-2af6a9b837bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>description :</span></dt><dd>Electron temperature.</dd></dl></div><div class='xr-var-data'><pre>array([2660.30556858, 2640.66798456, 2629.3074302 , ..., 1746.81846795,\n",
" 1727.68927125, 1729.64708117])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radius</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.823e+06 6.823e+06 ... 6.826e+06</div><input id='attrs-f037d0f5-4c49-4739-82b2-7c5d5c24ada4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f037d0f5-4c49-4739-82b2-7c5d5c24ada4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f7174fa-fbd0-4796-89cf-b9d198a4b418' class='xr-var-data-in' type='checkbox'><label for='data-0f7174fa-fbd0-4796-89cf-b9d198a4b418' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Position in ITRF - Radius</dd></dl></div><div class='xr-var-data'><pre>array([6822806.78263443, 6822800.81805651, 6822794.82872387, ...,\n",
" 6826479.29864009, 6826484.86713811, 6826490.45934109])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-95.37 -95.37 ... 81.23 81.23</div><input id='attrs-38e61297-b919-45b3-99fc-eca909885b45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38e61297-b919-45b3-99fc-eca909885b45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dde2ad8-c8df-460b-a982-db294fbb13cb' class='xr-var-data-in' type='checkbox'><label for='data-3dde2ad8-c8df-460b-a982-db294fbb13cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>description :</span></dt><dd>Position in ITRF - Longitude</dd></dl></div><div class='xr-var-data'><pre>array([-95.36973484, -95.36976808, -95.36980033, ..., 81.23327223,\n",
" 81.23270128, 81.23213248])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Phi_sc</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.264 -2.267 ... -1.901 -1.919</div><input id='attrs-e89e51e4-0537-45bd-aae6-74c201be6f87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e89e51e4-0537-45bd-aae6-74c201be6f87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6f7cccc-514a-406f-877b-a5f015349bd1' class='xr-var-data-in' type='checkbox'><label for='data-c6f7cccc-514a-406f-877b-a5f015349bd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>description :</span></dt><dd>Spacecraft floating potential with respect to plasma potential far from satellite.</dd></dl></div><div class='xr-var-data'><pre>array([-2.26392126, -2.26712036, -2.2718749 , ..., -1.91993833,\n",
" -1.90059781, -1.91922581])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>M_i_eff_Flags</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-89972823-3619-4fb0-ac48-957e497b0f7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89972823-3619-4fb0-ac48-957e497b0f7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9aa2bc3-d985-47b0-a29c-2194eee207ee' class='xr-var-data-in' type='checkbox'><label for='data-f9aa2bc3-d985-47b0-a29c-2194eee207ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd> </dd><dt><span>description :</span></dt><dd>Ion effective mass validity flag.</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_i</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1e+05 -1e+05 ... -1e+05 -1e+05</div><input id='attrs-7d1cadcb-393e-457f-83fe-f77e1b650535' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d1cadcb-393e-457f-83fe-f77e1b650535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4981640f-bb6d-4afd-be49-f6d2ddecc628' class='xr-var-data-in' type='checkbox'><label for='data-4981640f-bb6d-4afd-be49-f6d2ddecc628' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion along-track drift.</dd></dl></div><div class='xr-var-data'><pre>array([-100000., -100000., -100000., ..., -100000., -100000., -100000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4ac92e92-a069-45c3-ae64-178480994026' class='xr-section-summary-in' type='checkbox' ><label for='section-4ac92e92-a069-45c3-ae64-178480994026' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Timestamp</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-09cd3ac6-b4a7-4e2b-91ca-aa0e6d4b3d06' class='xr-index-data-in' type='checkbox'/><label for='index-09cd3ac6-b4a7-4e2b-91ca-aa0e6d4b3d06' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2016-01-02 00:00:00.196999936',\n",
" '2016-01-02 00:00:00.696000',\n",
" '2016-01-02 00:00:01.196999936',\n",
" '2016-01-02 00:00:01.696000',\n",
" '2016-01-02 00:00:02.196999936',\n",
" '2016-01-02 00:00:02.696000',\n",
" '2016-01-02 00:00:03.196999936',\n",
" '2016-01-02 00:00:03.696000',\n",
" '2016-01-02 00:00:04.196999936',\n",
" '2016-01-02 00:00:04.696000',\n",
" ...\n",
" '2016-01-02 23:59:55.196999936',\n",
" '2016-01-02 23:59:55.696000',\n",
" '2016-01-02 23:59:56.196999936',\n",
" '2016-01-02 23:59:56.696000',\n",
" '2016-01-02 23:59:57.196999936',\n",
" '2016-01-02 23:59:57.696000',\n",
" '2016-01-02 23:59:58.196999936',\n",
" '2016-01-02 23:59:58.696000',\n",
" '2016-01-02 23:59:59.196999936',\n",
" '2016-01-02 23:59:59.696000'],\n",
" dtype='datetime64[ns]', name='Timestamp', length=171434, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81b190fd-78d9-40f5-b7f6-564e89d2914b' class='xr-section-summary-in' type='checkbox' ><label for='section-81b190fd-78d9-40f5-b7f6-564e89d2914b' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Sources :</span></dt><dd>['SW_OPER_AUXAORBCNT_20131122T132146_20250622T234324_0001', 'SW_OPER_MODA_SC_1B_20160101T000000_20160101T235959_0502', 'SW_OPER_MODA_SC_1B_20160102T000000_20160102T235959_0502', 'SW_OPER_MODA_SC_1B_20160103T000000_20160103T235959_0502', 'SW_PREL_EFIAIDM_2__20160102T000000_20160102T235959_0301']</dd><dt><span>MagneticModels :</span></dt><dd>[]</dd><dt><span>AppliedFilters :</span></dt><dd>[]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (Timestamp: 171434, V_sat_nec_dim1: 3)\n",
"Coordinates:\n",
" * Timestamp (Timestamp) datetime64[ns] 2016-01-02T00:00:00.1969999...\n",
"Dimensions without coordinates: V_sat_nec_dim1\n",
"Data variables: (12/29)\n",
" Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'\n",
" OrbitDirection (Timestamp) int8 1 1 1 1 1 1 1 1 ... -1 -1 -1 -1 -1 -1 -1\n",
" MLT_QD (Timestamp) float64 17.7 17.7 17.7 ... 5.63 5.63 5.63\n",
" OrbitNumber (Timestamp) int32 11819 11819 11819 ... 11834 11834 11834\n",
" A_fp (Timestamp) float64 -1.0 -1.0 -1.0 ... -1.0 -1.0 -1.0\n",
" V_i_raw (Timestamp) float64 -1e+05 -1e+05 ... -1e+05 -1e+05\n",
" ... ...\n",
" T_e (Timestamp) float64 2.66e+03 2.641e+03 ... 1.73e+03\n",
" Radius (Timestamp) float64 6.823e+06 6.823e+06 ... 6.826e+06\n",
" Longitude (Timestamp) float64 -95.37 -95.37 -95.37 ... 81.23 81.23\n",
" Phi_sc (Timestamp) float64 -2.264 -2.267 ... -1.901 -1.919\n",
" M_i_eff_Flags (Timestamp) uint32 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
" V_i (Timestamp) float64 -1e+05 -1e+05 ... -1e+05 -1e+05\n",
"Attributes: (3)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds = data.as_xarray()\n",
"ds"
]
},
{
"cell_type": "markdown",
"id": "337c05b9-a184-4e86-b271-ab4102eafb12",
"metadata": {},
"source": [
"An initial preview of the data:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "e522ac07-5593-4cfb-9b40-3128c4faf797",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:25.201762Z",
"iopub.status.busy": "2025-06-21T21:46:25.201500Z",
"iopub.status.idle": "2025-06-21T21:46:29.509686Z",
"shell.execute_reply": "2025-06-21T21:46:29.509181Z"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x700 with 8 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(nrows=4, sharex=True, figsize=(10, 7))\n",
"axes_r = [ax.twinx() for ax in axes]\n",
"# Plot quantity (left axis) and error (right axis) for each quantity\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"M_i_eff\", ax=axes[0], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"M_i_eff_err\", ax=axes_r[0], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"V_i\", ax=axes[1], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"V_i_err\", ax=axes_r[1], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"N_i\", ax=axes[2], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"N_i_err\", ax=axes_r[2], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"T_e\", ax=axes[3], s=1, linewidths=0)\n",
"fig.subplots_adjust(hspace=0)\n",
"\n",
"# Add legend to identify each side\n",
"blue = mpl.patches.Patch(color=\"tab:blue\", label=\"Quantities\")\n",
"orange = mpl.patches.Patch(color=\"tab:orange\", label=\"Errors\")\n",
"axes[0].legend(handles=[blue, orange])\n",
"\n",
"# # Generate additional ticklabels for x-axis\n",
"# Use time xticks to get dataset vars at those xticks\n",
"locx = axes[-1].get_xticks()\n",
"times = mpl.dates.num2date(locx)\n",
"times = [t.replace(tzinfo=None) for t in times]\n",
"_ds_xticks = ds.reindex({\"Timestamp\": times}, method=\"nearest\")\n",
"# Build ticklabels from dataset vars\n",
"xticklabels = np.stack([\n",
" _ds_xticks[\"Timestamp\"].dt.strftime(\"%H:%M\").values,\n",
" np.round(_ds_xticks[\"Latitude\"].values, 2).astype(str),\n",
" np.round(_ds_xticks[\"Longitude\"].values, 2).astype(str),\n",
"])\n",
"xticklabels = [\"\\n\".join(row) for row in xticklabels.T]\n",
"# Add labels to first xtick\n",
"_xt0 = xticklabels[0].split(\"\\n\")\n",
"xticklabels[0] = f\"Time: {_xt0[0]}\\nLat: {_xt0[1]}\\nLon: {_xt0[2]}\"\n",
"axes[-1].set_xticks(axes[-1].get_xticks())\n",
"axes[-1].set_xticklabels(xticklabels)\n",
"axes[-1].set_xlabel(\"\")\n",
"# Adjust title\n",
"sources = \"\\n\".join([i for i in ds.attrs[\"Sources\"] if \"IDM\" in i])\n",
"title = \"\".join([\n",
" f\"Swarm {ds['Spacecraft'].data[0]} ion effective mass and drift, \",\n",
" ds[\"Timestamp\"].dt.date.data[0].isoformat(),\n",
" f\"\\n{sources}\"\n",
"])\n",
"fig.suptitle(title);"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
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"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
},
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