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     "output_type": "stream",
     "text": [
      "zsh:1: command not found: pip\n"
     ]
    }
   ],
   "source": [
    "!pip install xarray numpy matplotlib math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88c6d1ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Polygon, Rectangle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "header",
   "metadata": {},
   "source": [
    "# MAST Geometry Visualisation\n",
    "\n",
    "This notebook demonstrates how to visualise the geometric structures and diagnostic positions in MAST using the geometry data stored in our Zarr datasets.\n",
    "\n",
    "## Overview\n",
    "\n",
    "The geometry data is organized into different groups:\n",
    "- **Magnetics**: Magnetic field probes, flux loops, Mirnov coils, saddle coils\n",
    "- **PF Active**: Poloidal field coil positions and geometry\n",
    "- **PF Passive**: Passive structure components (vessel walls, supports, etc.)\n",
    "- **Soft X-rays**: Camera positions and lines-of-sight\n",
    "- **Wall**: Limiter and wall geometry\n",
    "\n",
    "### Data Structure Notes\n",
    "\n",
    "- Geometry data uses cylindrical coordinates (R, Z, φ) \n",
    "- Each diagnostic has separate geometry channels that may not directly align with data channels\n",
    "- Complete geometry information is preserved even when some diagnostic channels are missing\n",
    "- Data channels use full paths (e.g., 'XMB/SAD/OUT/M01'), geometry channels use simplified names (e.g., 'sad_out_m01')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3ee572c",
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   "source": [
    "First we will import the libraries that will help us plot, including a conversion function that will convert our cylindrical coordinates into Cartesian."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "imports",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cyl_to_cart(r, phi, z):\n",
    "    \"\"\"Convert cylindrical (r, phi, z) to Cartesian (x, y, z) coordinates\"\"\"\n",
    "    if np.max(phi) > 2 * np.pi:\n",
    "        phi = np.deg2rad(phi)\n",
    "    x = r * np.cos(phi)\n",
    "    y = r * np.sin(phi)\n",
    "    return x, y, z"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "magnetics-header",
   "metadata": {},
   "source": [
    "## Magnetic Diagnostics\n",
    "\n",
    "First, let's load the magnetics data and explore the available diagnostic positions.\n",
    "\n",
    "We will load the data directly from S3, and you can see we have data channels and geometry channels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "load-magnetics",
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   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 335MB\n",
       "Dimensions:                                      (\n",
       "                                                  b_field_pol_probe_cc_channel: 5,\n",
       "                                                  time_mirnov: 363200,\n",
       "                                                  b_field_pol_probe_cc_geometry_channel: 40,\n",
       "                                                  b_field_pol_probe_ccbv_channel: 40,\n",
       "                                                  time: 3632,\n",
       "                                                  ...\n",
       "                                                  coordinate: 28,\n",
       "                                                  b_field_tor_probe_saddle_m_geometry_channel: 12,\n",
       "                                                  b_field_tor_probe_saddle_u_geometry_channel: 12,\n",
       "                                                  b_field_tor_probe_saddle_voltage_channel: 12,\n",
       "                                                  flux_loop_channel: 15,\n",
       "                                                  flux_loop_geometry_channel: 44)\n",
       "Coordinates: (12/25)\n",
       "  * b_field_pol_probe_cc_channel                 (b_field_pol_probe_cc_channel) &lt;U13 260B ...\n",
       "  * b_field_pol_probe_cc_geometry_channel        (b_field_pol_probe_cc_geometry_channel) object 320B ...\n",
       "  * b_field_pol_probe_ccbv_channel               (b_field_pol_probe_ccbv_channel) &lt;U10 2kB ...\n",
       "  * b_field_pol_probe_ccbv_geometry_channel      (b_field_pol_probe_ccbv_geometry_channel) object 320B ...\n",
       "  * b_field_pol_probe_obr_channel                (b_field_pol_probe_obr_channel) &lt;U9 684B ...\n",
       "  * b_field_pol_probe_obr_geometry_channel       (b_field_pol_probe_obr_geometry_channel) object 152B ...\n",
       "    ...                                           ...\n",
       "  * flux_loop_channel                            (flux_loop_channel) &lt;U12 720B ...\n",
       "  * flux_loop_geometry_channel                   (flux_loop_geometry_channel) object 352B ...\n",
       "  * time                                         (time) float64 29kB -0.0612 ...\n",
       "  * time_mirnov                                  (time_mirnov) float64 3MB -0...\n",
       "  * time_omaha                                   (time_omaha) float64 58MB -0...\n",
       "  * time_saddle                                  (time_saddle) float64 291kB ...\n",
       "Data variables: (12/46)\n",
       "    b_field_pol_probe_cc_field                   (b_field_pol_probe_cc_channel, time_mirnov) float64 15MB ...\n",
       "    b_field_pol_probe_cc_phi                     (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_cc_r                       (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_cc_z                       (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_ccbv_field                 (b_field_pol_probe_ccbv_channel, time) float64 1MB ...\n",
       "    b_field_pol_probe_ccbv_length                (b_field_pol_probe_ccbv_geometry_channel) float64 320B ...\n",
       "    ...                                           ...\n",
       "    b_field_tor_probe_saddle_u_z                 (b_field_tor_probe_saddle_u_geometry_channel, coordinate) float64 3kB ...\n",
       "    b_field_tor_probe_saddle_voltage             (b_field_tor_probe_saddle_voltage_channel, time_saddle) float64 3MB ...\n",
       "    flux_loop_flux                               (flux_loop_channel, time) float64 436kB ...\n",
       "    flux_loop_r                                  (flux_loop_geometry_channel) float64 352B ...\n",
       "    flux_loop_z                                  (flux_loop_geometry_channel) float64 352B ...\n",
       "    ip                                           (time) float64 29kB ...\n",
       "Attributes:\n",
       "    description:  \n",
       "    imas:         magnetics\n",
       "    label:        Plasma Current\n",
       "    license:      {&#x27;name&#x27;: &#x27;Creative Commons 4.0 BY-SA&#x27;, &#x27;url&#x27;: &#x27;https://crea...\n",
       "    name:         magnetics\n",
       "    uda_name:     AMC_PLASMA CURRENT\n",
       "    units:        A</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-768c27c0-4777-4e60-abe8-2081e9e66c49' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-768c27c0-4777-4e60-abe8-2081e9e66c49' 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'>b_field_pol_probe_cc_channel</span>: 5</li><li><span class='xr-has-index'>time_mirnov</span>: 363200</li><li><span class='xr-has-index'>b_field_pol_probe_cc_geometry_channel</span>: 40</li><li><span class='xr-has-index'>b_field_pol_probe_ccbv_channel</span>: 40</li><li><span class='xr-has-index'>time</span>: 3632</li><li><span class='xr-has-index'>b_field_pol_probe_ccbv_geometry_channel</span>: 40</li><li><span class='xr-has-index'>b_field_pol_probe_obr_channel</span>: 19</li><li><span class='xr-has-index'>b_field_pol_probe_obr_geometry_channel</span>: 19</li><li><span class='xr-has-index'>b_field_pol_probe_obv_channel</span>: 19</li><li><span class='xr-has-index'>b_field_pol_probe_obv_geometry_channel</span>: 19</li><li><span class='xr-has-index'>b_field_pol_probe_omv_geometry_channel</span>: 21</li><li><span class='xr-has-index'>b_field_pol_probe_omv_channel</span>: 3</li><li><span class='xr-has-index'>b_field_tor_probe_cc_channel</span>: 3</li><li><span class='xr-has-index'>b_field_tor_probe_cc_geometry_channel</span>: 36</li><li><span class='xr-has-index'>b_field_tor_probe_omaha_channel</span>: 4</li><li><span class='xr-has-index'>time_omaha</span>: 7264000</li><li><span class='xr-has-index'>b_field_tor_probe_saddle_field_channel</span>: 12</li><li><span class='xr-has-index'>time_saddle</span>: 36320</li><li><span class='xr-has-index'>b_field_tor_probe_saddle_l_geometry_channel</span>: 12</li><li><span class='xr-has-index'>coordinate</span>: 28</li><li><span class='xr-has-index'>b_field_tor_probe_saddle_m_geometry_channel</span>: 12</li><li><span class='xr-has-index'>b_field_tor_probe_saddle_u_geometry_channel</span>: 12</li><li><span class='xr-has-index'>b_field_tor_probe_saddle_voltage_channel</span>: 12</li><li><span class='xr-has-index'>flux_loop_channel</span>: 15</li><li><span class='xr-has-index'>flux_loop_geometry_channel</span>: 44</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-445fed55-4afa-4952-a914-ab98258a4d9f' class='xr-section-summary-in' type='checkbox'  ><label for='section-445fed55-4afa-4952-a914-ab98258a4d9f' class='xr-section-summary' >Coordinates: <span>(25)</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'>b_field_pol_probe_cc_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_channel)</div><div class='xr-var-dtype'>&lt;U13</div><div class='xr-var-preview xr-preview'>&#x27;xmc/CC/MV/201&#x27; ... &#x27;xmc/CC/MV/240&#x27;</div><input id='attrs-c4adad19-4cb8-497c-807b-a641ad2425d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c4adad19-4cb8-497c-807b-a641ad2425d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7794efe-0406-4f26-9a41-bd2437f0d983' class='xr-var-data-in' type='checkbox'><label for='data-b7794efe-0406-4f26-9a41-bd2437f0d983' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;xmc/CC/MV/201&#x27;, &#x27;xmc/CC/MV/210&#x27;, &#x27;xmc/CC/MV/220&#x27;, &#x27;xmc/CC/MV/230&#x27;,\n",
       "       &#x27;xmc/CC/MV/240&#x27;], dtype=&#x27;&lt;U13&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_cc_geometry_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;cc_mv_201&#x27; ... &#x27;cc_mv_240&#x27;</div><input id='attrs-f5458b20-e87e-4e17-b62f-1d2862f59b0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5458b20-e87e-4e17-b62f-1d2862f59b0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c75d5c2-aee0-4a1c-9e35-8625966747bc' class='xr-var-data-in' type='checkbox'><label for='data-4c75d5c2-aee0-4a1c-9e35-8625966747bc' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;cc_mv_201&#x27;, &#x27;cc_mv_202*&#x27;, &#x27;cc_mv_203*&#x27;, &#x27;cc_mv_204*&#x27;, &#x27;cc_mv_205*&#x27;,\n",
       "       &#x27;cc_mv_206*&#x27;, &#x27;cc_mv_207*&#x27;, &#x27;cc_mv_208*&#x27;, &#x27;cc_mv_209*&#x27;, &#x27;cc_mv_210*&#x27;,\n",
       "       &#x27;cc_mv_211*&#x27;, &#x27;cc_mv_212*&#x27;, &#x27;cc_mv_213*&#x27;, &#x27;cc_mv_214*&#x27;, &#x27;cc_mv_215*&#x27;,\n",
       "       &#x27;cc_mv_216*&#x27;, &#x27;cc_mv_217*&#x27;, &#x27;cc_mv_218*&#x27;, &#x27;cc_mv_219*&#x27;, &#x27;cc_mv_220*&#x27;,\n",
       "       &#x27;cc_mv_221*&#x27;, &#x27;cc_mv_222*&#x27;, &#x27;cc_mv_223*&#x27;, &#x27;cc_mv_224&#x27;, &#x27;cc_mv_225&#x27;,\n",
       "       &#x27;cc_mv_226&#x27;, &#x27;cc_mv_227&#x27;, &#x27;cc_mv_228&#x27;, &#x27;cc_mv_229&#x27;, &#x27;cc_mv_230&#x27;,\n",
       "       &#x27;cc_mv_231&#x27;, &#x27;cc_mv_232&#x27;, &#x27;cc_mv_233&#x27;, &#x27;cc_mv_234&#x27;, &#x27;cc_mv_235&#x27;,\n",
       "       &#x27;cc_mv_236&#x27;, &#x27;cc_mv_237&#x27;, &#x27;cc_mv_238&#x27;, &#x27;cc_mv_239&#x27;, &#x27;cc_mv_240&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_ccbv_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_channel)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;AMB_CCBV01&#x27; ... &#x27;AMB_CCBV40&#x27;</div><input id='attrs-fd95eca0-6533-46ca-b6a8-f71c3e285275' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd95eca0-6533-46ca-b6a8-f71c3e285275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-518cf659-c7b0-4db6-a638-25f5d2351d31' class='xr-var-data-in' type='checkbox'><label for='data-518cf659-c7b0-4db6-a638-25f5d2351d31' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;AMB_CCBV01&#x27;, &#x27;AMB_CCBV02&#x27;, &#x27;AMB_CCBV03&#x27;, &#x27;AMB_CCBV04&#x27;, &#x27;AMB_CCBV05&#x27;,\n",
       "       &#x27;AMB_CCBV06&#x27;, &#x27;AMB_CCBV07&#x27;, &#x27;AMB_CCBV08&#x27;, &#x27;AMB_CCBV09&#x27;, &#x27;AMB_CCBV10&#x27;,\n",
       "       &#x27;AMB_CCBV11&#x27;, &#x27;AMB_CCBV12&#x27;, &#x27;AMB_CCBV13&#x27;, &#x27;AMB_CCBV14&#x27;, &#x27;AMB_CCBV15&#x27;,\n",
       "       &#x27;AMB_CCBV16&#x27;, &#x27;AMB_CCBV17&#x27;, &#x27;AMB_CCBV18&#x27;, &#x27;AMB_CCBV19&#x27;, &#x27;AMB_CCBV20&#x27;,\n",
       "       &#x27;AMB_CCBV21&#x27;, &#x27;AMB_CCBV22&#x27;, &#x27;AMB_CCBV23&#x27;, &#x27;AMB_CCBV24&#x27;, &#x27;AMB_CCBV25&#x27;,\n",
       "       &#x27;AMB_CCBV26&#x27;, &#x27;AMB_CCBV27&#x27;, &#x27;AMB_CCBV28&#x27;, &#x27;AMB_CCBV29&#x27;, &#x27;AMB_CCBV30&#x27;,\n",
       "       &#x27;AMB_CCBV31&#x27;, &#x27;AMB_CCBV32&#x27;, &#x27;AMB_CCBV33&#x27;, &#x27;AMB_CCBV34&#x27;, &#x27;AMB_CCBV35&#x27;,\n",
       "       &#x27;AMB_CCBV36&#x27;, &#x27;AMB_CCBV37&#x27;, &#x27;AMB_CCBV38&#x27;, &#x27;AMB_CCBV39&#x27;, &#x27;AMB_CCBV40&#x27;],\n",
       "      dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_ccbv_geometry_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;ccbv01&#x27; &#x27;ccbv02&#x27; ... &#x27;ccbv40&#x27;</div><input id='attrs-588fa335-2746-4657-9d06-20c6d7d8dc3c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-588fa335-2746-4657-9d06-20c6d7d8dc3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b08df07f-54d8-4261-b893-9c93c620f2c3' class='xr-var-data-in' type='checkbox'><label for='data-b08df07f-54d8-4261-b893-9c93c620f2c3' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;ccbv01&#x27;, &#x27;ccbv02&#x27;, &#x27;ccbv03&#x27;, &#x27;ccbv04&#x27;, &#x27;ccbv05&#x27;, &#x27;ccbv06&#x27;, &#x27;ccbv07&#x27;,\n",
       "       &#x27;ccbv08&#x27;, &#x27;ccbv09&#x27;, &#x27;ccbv10&#x27;, &#x27;ccbv11&#x27;, &#x27;ccbv12&#x27;, &#x27;ccbv13&#x27;, &#x27;ccbv14&#x27;,\n",
       "       &#x27;ccbv15&#x27;, &#x27;ccbv16&#x27;, &#x27;ccbv17&#x27;, &#x27;ccbv18&#x27;, &#x27;ccbv19&#x27;, &#x27;ccbv20&#x27;, &#x27;ccbv21&#x27;,\n",
       "       &#x27;ccbv22&#x27;, &#x27;ccbv23&#x27;, &#x27;ccbv24&#x27;, &#x27;ccbv25&#x27;, &#x27;ccbv26&#x27;, &#x27;ccbv27&#x27;, &#x27;ccbv28&#x27;,\n",
       "       &#x27;ccbv29&#x27;, &#x27;ccbv30&#x27;, &#x27;ccbv31&#x27;, &#x27;ccbv32&#x27;, &#x27;ccbv33&#x27;, &#x27;ccbv34&#x27;, &#x27;ccbv35&#x27;,\n",
       "       &#x27;ccbv36&#x27;, &#x27;ccbv37&#x27;, &#x27;ccbv38&#x27;, &#x27;ccbv39&#x27;, &#x27;ccbv40&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_obr_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_channel)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;AMB_OBR01&#x27; ... &#x27;AMB_OBR19&#x27;</div><input id='attrs-b825d7f6-21f4-4296-9beb-d61517ec9b38' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b825d7f6-21f4-4296-9beb-d61517ec9b38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dac2f81-4f96-4b43-9c23-170322869ec8' class='xr-var-data-in' type='checkbox'><label for='data-8dac2f81-4f96-4b43-9c23-170322869ec8' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;AMB_OBR01&#x27;, &#x27;AMB_OBR02&#x27;, &#x27;AMB_OBR03&#x27;, &#x27;AMB_OBR04&#x27;, &#x27;AMB_OBR05&#x27;,\n",
       "       &#x27;AMB_OBR06&#x27;, &#x27;AMB_OBR07&#x27;, &#x27;AMB_OBR08&#x27;, &#x27;AMB_OBR09&#x27;, &#x27;AMB_OBR10&#x27;,\n",
       "       &#x27;AMB_OBR11&#x27;, &#x27;AMB_OBR12&#x27;, &#x27;AMB_OBR13&#x27;, &#x27;AMB_OBR14&#x27;, &#x27;AMB_OBR15&#x27;,\n",
       "       &#x27;AMB_OBR16&#x27;, &#x27;AMB_OBR17&#x27;, &#x27;AMB_OBR18&#x27;, &#x27;AMB_OBR19&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_obr_geometry_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;obr01&#x27; &#x27;obr02&#x27; ... &#x27;obr18&#x27; &#x27;obr19&#x27;</div><input id='attrs-c2cc4e78-f59b-475b-91aa-30dbead1d425' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2cc4e78-f59b-475b-91aa-30dbead1d425' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01a58a04-dd7c-425d-b8aa-7c0b56348527' class='xr-var-data-in' type='checkbox'><label for='data-01a58a04-dd7c-425d-b8aa-7c0b56348527' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;obr01&#x27;, &#x27;obr02&#x27;, &#x27;obr03&#x27;, &#x27;obr04&#x27;, &#x27;obr05&#x27;, &#x27;obr06&#x27;, &#x27;obr07&#x27;, &#x27;obr08&#x27;,\n",
       "       &#x27;obr09&#x27;, &#x27;obr10&#x27;, &#x27;obr11&#x27;, &#x27;obr12&#x27;, &#x27;obr13&#x27;, &#x27;obr14&#x27;, &#x27;obr15&#x27;, &#x27;obr16&#x27;,\n",
       "       &#x27;obr17&#x27;, &#x27;obr18&#x27;, &#x27;obr19&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_obv_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_channel)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;AMB_OBV01&#x27; ... &#x27;AMB_OBV19&#x27;</div><input id='attrs-6e2ee47f-02b0-42d9-919f-5cdcb3c5f361' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e2ee47f-02b0-42d9-919f-5cdcb3c5f361' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d1a9282-14d7-4522-b3d3-50533edfd1a7' class='xr-var-data-in' type='checkbox'><label for='data-6d1a9282-14d7-4522-b3d3-50533edfd1a7' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;AMB_OBV01&#x27;, &#x27;AMB_OBV02&#x27;, &#x27;AMB_OBV03&#x27;, &#x27;AMB_OBV04&#x27;, &#x27;AMB_OBV05&#x27;,\n",
       "       &#x27;AMB_OBV06&#x27;, &#x27;AMB_OBV07&#x27;, &#x27;AMB_OBV08&#x27;, &#x27;AMB_OBV09&#x27;, &#x27;AMB_OBV10&#x27;,\n",
       "       &#x27;AMB_OBV11&#x27;, &#x27;AMB_OBV12&#x27;, &#x27;AMB_OBV13&#x27;, &#x27;AMB_OBV14&#x27;, &#x27;AMB_OBV15&#x27;,\n",
       "       &#x27;AMB_OBV16&#x27;, &#x27;AMB_OBV17&#x27;, &#x27;AMB_OBV18&#x27;, &#x27;AMB_OBV19&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_obv_geometry_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;obv01&#x27; &#x27;obv02&#x27; ... &#x27;obv18&#x27; &#x27;obv19&#x27;</div><input id='attrs-a3d6593c-66aa-43c0-8c14-e32691b6def6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3d6593c-66aa-43c0-8c14-e32691b6def6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b769d9-6192-42ea-abd1-ea4a761892d1' class='xr-var-data-in' type='checkbox'><label for='data-f0b769d9-6192-42ea-abd1-ea4a761892d1' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;obv01&#x27;, &#x27;obv02&#x27;, &#x27;obv03&#x27;, &#x27;obv04&#x27;, &#x27;obv05&#x27;, &#x27;obv06&#x27;, &#x27;obv07&#x27;, &#x27;obv08&#x27;,\n",
       "       &#x27;obv09&#x27;, &#x27;obv10&#x27;, &#x27;obv11&#x27;, &#x27;obv12&#x27;, &#x27;obv13&#x27;, &#x27;obv14&#x27;, &#x27;obv15&#x27;, &#x27;obv16&#x27;,\n",
       "       &#x27;obv17&#x27;, &#x27;obv18&#x27;, &#x27;obv19&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_omv_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_channel)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;xmc/OMV/110&#x27; ... &#x27;xmc/OMV/310&#x27;</div><input id='attrs-ca10c75e-8153-44ac-ba46-15e7701c40b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca10c75e-8153-44ac-ba46-15e7701c40b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac4c789f-2297-4560-8df1-2efe9c4efbfe' class='xr-var-data-in' type='checkbox'><label for='data-ac4c789f-2297-4560-8df1-2efe9c4efbfe' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;xmc/OMV/110&#x27;, &#x27;xmc/OMV/210&#x27;, &#x27;xmc/OMV/310&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_pol_probe_omv_geometry_channel</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;omv_201&#x27; &#x27;omv_202&#x27; ... &#x27;omv_310&#x27;</div><input id='attrs-1f4c5588-c1ae-48a8-900f-8d9948997c9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f4c5588-c1ae-48a8-900f-8d9948997c9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72d41565-c846-47d8-a576-0892fa97a7a8' class='xr-var-data-in' type='checkbox'><label for='data-72d41565-c846-47d8-a576-0892fa97a7a8' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;omv_201&#x27;, &#x27;omv_202&#x27;, &#x27;omv_203&#x27;, &#x27;omv_204&#x27;, &#x27;omv_205&#x27;, &#x27;omv_206&#x27;,\n",
       "       &#x27;omv_207&#x27;, &#x27;omv_208&#x27;, &#x27;omv_209&#x27;, &#x27;omv_210&#x27;, &#x27;omv_211&#x27;, &#x27;omv_212&#x27;,\n",
       "       &#x27;omv_213&#x27;, &#x27;omv_214&#x27;, &#x27;omv_215&#x27;, &#x27;omv_216&#x27;, &#x27;omv_217&#x27;, &#x27;omv_218&#x27;,\n",
       "       &#x27;omv_219&#x27;, &#x27;omv_110&#x27;, &#x27;omv_310&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_cc_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_channel)</div><div class='xr-var-dtype'>&lt;U13</div><div class='xr-var-preview xr-preview'>&#x27;xmc/CC/MT/201&#x27; ... &#x27;xmc/CC/MT/212&#x27;</div><input id='attrs-28c33314-b296-4c9f-aa52-0877f3149cb9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28c33314-b296-4c9f-aa52-0877f3149cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6666c6a8-5c63-4c05-b30b-635279590e7e' class='xr-var-data-in' type='checkbox'><label for='data-6666c6a8-5c63-4c05-b30b-635279590e7e' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;xmc/CC/MT/201&#x27;, &#x27;xmc/CC/MT/206&#x27;, &#x27;xmc/CC/MT/212&#x27;], dtype=&#x27;&lt;U13&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_cc_geometry_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;cc_mt_101&#x27; ... &#x27;cc_mt_312&#x27;</div><input id='attrs-8b6d1dbd-fc70-4039-8f01-8e5de4ff074b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8b6d1dbd-fc70-4039-8f01-8e5de4ff074b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf71c3d5-3fc2-4f55-a5ea-0ac0ff393634' class='xr-var-data-in' type='checkbox'><label for='data-cf71c3d5-3fc2-4f55-a5ea-0ac0ff393634' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;cc_mt_101&#x27;, &#x27;cc_mt_102&#x27;, &#x27;cc_mt_103&#x27;, &#x27;cc_mt_104&#x27;, &#x27;cc_mt_105&#x27;,\n",
       "       &#x27;cc_mt_106&#x27;, &#x27;cc_mt_107&#x27;, &#x27;cc_mt_108&#x27;, &#x27;cc_mt_109&#x27;, &#x27;cc_mt_110&#x27;,\n",
       "       &#x27;cc_mt_111&#x27;, &#x27;cc_mt_112&#x27;, &#x27;cc_mt_201&#x27;, &#x27;cc_mt_202&#x27;, &#x27;cc_mt_203&#x27;,\n",
       "       &#x27;cc_mt_204&#x27;, &#x27;cc_mt_205&#x27;, &#x27;cc_mt_206&#x27;, &#x27;cc_mt_207&#x27;, &#x27;cc_mt_208&#x27;,\n",
       "       &#x27;cc_mt_209&#x27;, &#x27;cc_mt_210&#x27;, &#x27;cc_mt_211&#x27;, &#x27;cc_mt_212&#x27;, &#x27;cc_mt_301&#x27;,\n",
       "       &#x27;cc_mt_302&#x27;, &#x27;cc_mt_303&#x27;, &#x27;cc_mt_304&#x27;, &#x27;cc_mt_305&#x27;, &#x27;cc_mt_306&#x27;,\n",
       "       &#x27;cc_mt_307&#x27;, &#x27;cc_mt_308&#x27;, &#x27;cc_mt_309&#x27;, &#x27;cc_mt_310&#x27;, &#x27;cc_mt_311&#x27;,\n",
       "       &#x27;cc_mt_312&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_omaha_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_omaha_channel)</div><div class='xr-var-dtype'>&lt;U14</div><div class='xr-var-preview xr-preview'>&#x27;/xmo/OMAHA/1LZ&#x27; ... &#x27;/xmo/OMAHA...</div><input id='attrs-f8fa5202-cbda-4769-a731-6ac93817fdf8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8fa5202-cbda-4769-a731-6ac93817fdf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac1108d5-3798-4b1d-9963-2e3fb37a908c' class='xr-var-data-in' type='checkbox'><label for='data-ac1108d5-3798-4b1d-9963-2e3fb37a908c' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;/xmo/OMAHA/1LZ&#x27;, &#x27;/xmo/OMAHA/3LZ&#x27;, &#x27;/xmo/OMAHA/5LZ&#x27;, &#x27;/xmo/OMAHA/6LZ&#x27;],\n",
       "      dtype=&#x27;&lt;U14&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_saddle_field_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_field_channel)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;ASM_SAD/M01&#x27; ... &#x27;ASM_SAD/M12&#x27;</div><input id='attrs-b2900f3e-0aaf-4103-9299-a2cddbbf2ae5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2900f3e-0aaf-4103-9299-a2cddbbf2ae5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01a33b73-9031-44a9-8524-c4d06696a909' class='xr-var-data-in' type='checkbox'><label for='data-01a33b73-9031-44a9-8524-c4d06696a909' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;ASM_SAD/M01&#x27;, &#x27;ASM_SAD/M02&#x27;, &#x27;ASM_SAD/M03&#x27;, &#x27;ASM_SAD/M04&#x27;,\n",
       "       &#x27;ASM_SAD/M05&#x27;, &#x27;ASM_SAD/M06&#x27;, &#x27;ASM_SAD/M07&#x27;, &#x27;ASM_SAD/M08&#x27;,\n",
       "       &#x27;ASM_SAD/M09&#x27;, &#x27;ASM_SAD/M10&#x27;, &#x27;ASM_SAD/M11&#x27;, &#x27;ASM_SAD/M12&#x27;],\n",
       "      dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_saddle_l_geometry_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_l_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;sad_out_l01&#x27; ... &#x27;sad_out_l12&#x27;</div><input id='attrs-3ae07fac-26b8-41cc-8f34-c5a146f79ff5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ae07fac-26b8-41cc-8f34-c5a146f79ff5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5225e41f-217e-4404-90af-2b930d4c53fc' class='xr-var-data-in' type='checkbox'><label for='data-5225e41f-217e-4404-90af-2b930d4c53fc' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;sad_out_l01&#x27;, &#x27;sad_out_l02&#x27;, &#x27;sad_out_l03&#x27;, &#x27;sad_out_l04&#x27;,\n",
       "       &#x27;sad_out_l05&#x27;, &#x27;sad_out_l06&#x27;, &#x27;sad_out_l07&#x27;, &#x27;sad_out_l08&#x27;,\n",
       "       &#x27;sad_out_l09&#x27;, &#x27;sad_out_l10&#x27;, &#x27;sad_out_l11&#x27;, &#x27;sad_out_l12&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_saddle_m_geometry_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_m_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;sad_out_m01&#x27; ... &#x27;sad_out_m12&#x27;</div><input id='attrs-b75a187a-ce2b-4df1-b5c3-28898df912f0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b75a187a-ce2b-4df1-b5c3-28898df912f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5126861-9608-4a69-acf3-8ae9037d1fa7' class='xr-var-data-in' type='checkbox'><label for='data-d5126861-9608-4a69-acf3-8ae9037d1fa7' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;sad_out_m01&#x27;, &#x27;sad_out_m02&#x27;, &#x27;sad_out_m03&#x27;, &#x27;sad_out_m04&#x27;,\n",
       "       &#x27;sad_out_m05&#x27;, &#x27;sad_out_m06&#x27;, &#x27;sad_out_m07&#x27;, &#x27;sad_out_m08&#x27;,\n",
       "       &#x27;sad_out_m09&#x27;, &#x27;sad_out_m10&#x27;, &#x27;sad_out_m11&#x27;, &#x27;sad_out_m12&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_saddle_u_geometry_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_u_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;sad_out_u01&#x27; ... &#x27;sad_out_u12&#x27;</div><input id='attrs-0cfd89fb-edd5-4c79-be12-bdb8893ed3ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0cfd89fb-edd5-4c79-be12-bdb8893ed3ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d42c2d5-661d-4abd-be42-f50a3378cb91' class='xr-var-data-in' type='checkbox'><label for='data-5d42c2d5-661d-4abd-be42-f50a3378cb91' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;sad_out_u01&#x27;, &#x27;sad_out_u02&#x27;, &#x27;sad_out_u03&#x27;, &#x27;sad_out_u04&#x27;,\n",
       "       &#x27;sad_out_u05&#x27;, &#x27;sad_out_u06&#x27;, &#x27;sad_out_u07&#x27;, &#x27;sad_out_u08&#x27;,\n",
       "       &#x27;sad_out_u09&#x27;, &#x27;sad_out_u10&#x27;, &#x27;sad_out_u11&#x27;, &#x27;sad_out_u12&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>b_field_tor_probe_saddle_voltage_channel</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_voltage_channel)</div><div class='xr-var-dtype'>&lt;U15</div><div class='xr-var-preview xr-preview'>&#x27;XMB/SAD/OUT/M01&#x27; ... &#x27;XMB/SAD/O...</div><input id='attrs-7ce84fdb-fca5-4e1c-89a1-6a4f5528d690' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ce84fdb-fca5-4e1c-89a1-6a4f5528d690' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-029f0b23-7a77-4656-84da-3b6e73436757' class='xr-var-data-in' type='checkbox'><label for='data-029f0b23-7a77-4656-84da-3b6e73436757' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;XMB/SAD/OUT/M01&#x27;, &#x27;XMB/SAD/OUT/M02&#x27;, &#x27;XMB/SAD/OUT/M03&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M04&#x27;, &#x27;XMB/SAD/OUT/M05&#x27;, &#x27;XMB/SAD/OUT/M06&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M07&#x27;, &#x27;XMB/SAD/OUT/M08&#x27;, &#x27;XMB/SAD/OUT/M09&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M10&#x27;, &#x27;XMB/SAD/OUT/M11&#x27;, &#x27;XMB/SAD/OUT/M12&#x27;], dtype=&#x27;&lt;U15&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coordinate</span></div><div class='xr-var-dims'>(coordinate)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 22 23 24 25 26 27</div><input id='attrs-5af1aae9-dce7-41df-b737-b837955ea4ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5af1aae9-dce7-41df-b737-b837955ea4ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e90643-1907-4813-9fbf-c78e39738ae3' class='xr-var-data-in' type='checkbox'><label for='data-f2e90643-1907-4813-9fbf-c78e39738ae3' 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'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>flux_loop_channel</span></div><div class='xr-var-dims'>(flux_loop_channel)</div><div class='xr-var-dtype'>&lt;U12</div><div class='xr-var-preview xr-preview'>&#x27;AMB_FL/CC03&#x27; ... &#x27;AMB_FL/P6L/1&#x27;</div><input id='attrs-ee699498-6763-4b92-be2a-68847cc910fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee699498-6763-4b92-be2a-68847cc910fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93e7958c-8d62-4e4f-b14b-340239fdf8df' class='xr-var-data-in' type='checkbox'><label for='data-93e7958c-8d62-4e4f-b14b-340239fdf8df' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;AMB_FL/CC03&#x27;, &#x27;AMB_FL/CC04&#x27;, &#x27;AMB_FL/CC05&#x27;, &#x27;AMB_FL/CC07&#x27;,\n",
       "       &#x27;AMB_FL/CC09&#x27;, &#x27;AMB_FL/P3L/4&#x27;, &#x27;AMB_FL/P3U/1&#x27;, &#x27;AMB_FL/P3U/4&#x27;,\n",
       "       &#x27;AMB_FL/P4L/1&#x27;, &#x27;AMB_FL/P4L/4&#x27;, &#x27;AMB_FL/P4U/4&#x27;, &#x27;AMB_FL/P5L/1&#x27;,\n",
       "       &#x27;AMB_FL/P5L/4&#x27;, &#x27;AMB_FL/P5U/1&#x27;, &#x27;AMB_FL/P6L/1&#x27;], dtype=&#x27;&lt;U12&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>flux_loop_geometry_channel</span></div><div class='xr-var-dims'>(flux_loop_geometry_channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;FL_P2U_1&#x27; ... &#x27;FL_CC010&#x27;</div><input id='attrs-d61f1367-cf24-4a3f-8453-10c94112deb9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d61f1367-cf24-4a3f-8453-10c94112deb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd2af783-4cb0-405d-9fda-6c4981103fc5' class='xr-var-data-in' type='checkbox'><label for='data-dd2af783-4cb0-405d-9fda-6c4981103fc5' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;FL_P2U_1&#x27;, &#x27;FL_P2U_2&#x27;, &#x27;FL_P2U_3&#x27;, &#x27;FL_P2U_4&#x27;, &#x27;FL_P2L_1&#x27;, &#x27;FL_P2L_2&#x27;,\n",
       "       &#x27;FL_P2L_3&#x27;, &#x27;FL_P2L_4&#x27;, &#x27;FL_P3U_1&#x27;, &#x27;FL_P3U_2&#x27;, &#x27;FL_P3U_3&#x27;, &#x27;FL_P3U_4&#x27;,\n",
       "       &#x27;FL_P3L_1&#x27;, &#x27;FL_P3L_2&#x27;, &#x27;FL_P3L_3&#x27;, &#x27;FL_P3L_4&#x27;, &#x27;FL_P4U_1&#x27;, &#x27;FL_P4U_2&#x27;,\n",
       "       &#x27;FL_P4U_3&#x27;, &#x27;FL_P4U_4&#x27;, &#x27;FL_P4L_1&#x27;, &#x27;FL_P4L_2&#x27;, &#x27;FL_P4L_3&#x27;, &#x27;FL_P4L_4&#x27;,\n",
       "       &#x27;FL_P5U_1&#x27;, &#x27;FL_P5U_2&#x27;, &#x27;FL_P5U_3&#x27;, &#x27;FL_P5U_4&#x27;, &#x27;FL_P5L_1&#x27;, &#x27;FL_P5L_2&#x27;,\n",
       "       &#x27;FL_P5L_3&#x27;, &#x27;FL_P5L_4&#x27;, &#x27;FL_P6L_1&#x27;, &#x27;FL_P6L_2&#x27;, &#x27;FL_CC01&#x27;, &#x27;FL_CC02&#x27;,\n",
       "       &#x27;FL_CC03&#x27;, &#x27;FL_CC04&#x27;, &#x27;FL_CC05&#x27;, &#x27;FL_CC06&#x27;, &#x27;FL_CC07&#x27;, &#x27;FL_CC08&#x27;,\n",
       "       &#x27;FL_CC09&#x27;, &#x27;FL_CC010&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0612 -0.061 ... 0.6648 0.665</div><input id='attrs-29c88c6a-2653-417d-bb45-0c2ae7c78b3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29c88c6a-2653-417d-bb45-0c2ae7c78b3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b021d2c-febb-4b10-99c1-d75b951c45ab' class='xr-var-data-in' type='checkbox'><label for='data-3b021d2c-febb-4b10-99c1-d75b951c45ab' 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>s</dd></dl></div><div class='xr-var-data'><pre>array([-0.0612, -0.061 , -0.0608, ...,  0.6646,  0.6648,  0.665 ],\n",
       "      shape=(3632,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_mirnov</span></div><div class='xr-var-dims'>(time_mirnov)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0612 -0.0612 ... 0.6652 0.6652</div><input id='attrs-9805857b-72cf-404e-a1c2-5cbb529344ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9805857b-72cf-404e-a1c2-5cbb529344ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f31a98ba-be72-441e-9a28-75baf3df93f3' class='xr-var-data-in' type='checkbox'><label for='data-f31a98ba-be72-441e-9a28-75baf3df93f3' 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>s</dd></dl></div><div class='xr-var-data'><pre>array([-0.0612  , -0.061198, -0.061196, ...,  0.665194,  0.665196,  0.665198],\n",
       "      shape=(363200,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_omaha</span></div><div class='xr-var-dims'>(time_omaha)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0612 -0.0612 ... 0.6652 0.6652</div><input id='attrs-2839fd66-baf7-4ffe-b172-89f299ef2d0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2839fd66-baf7-4ffe-b172-89f299ef2d0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a787a13-dcd3-4b03-a3d7-406450dd08a7' class='xr-var-data-in' type='checkbox'><label for='data-8a787a13-dcd3-4b03-a3d7-406450dd08a7' 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>s</dd></dl></div><div class='xr-var-data'><pre>array([-0.0612  , -0.0612  , -0.0612  , ...,  0.665199,  0.6652  ,  0.6652  ],\n",
       "      shape=(7264000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_saddle</span></div><div class='xr-var-dims'>(time_saddle)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0612 -0.06118 ... 0.6652 0.6652</div><input id='attrs-eb107a73-573d-4d75-ace8-9cc496c6ac94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb107a73-573d-4d75-ace8-9cc496c6ac94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0245136f-eefa-46c1-9f0e-4081c3c9e2d3' class='xr-var-data-in' type='checkbox'><label for='data-0245136f-eefa-46c1-9f0e-4081c3c9e2d3' 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>s</dd></dl></div><div class='xr-var-data'><pre>array([-0.0612 , -0.06118, -0.06116, ...,  0.66514,  0.66516,  0.66518],\n",
       "      shape=(36320,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2fdf2a5-3e17-4096-b88c-b70e03823c84' class='xr-section-summary-in' type='checkbox'  ><label for='section-b2fdf2a5-3e17-4096-b88c-b70e03823c84' class='xr-section-summary' >Data variables: <span>(46)</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>b_field_pol_probe_cc_field</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_channel, time_mirnov)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-01004f06-e07d-4dd2-bdc4-7d87d7ed9845' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01004f06-e07d-4dd2-bdc4-7d87d7ed9845' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d214eb27-b7b2-4baf-bc1d-bf1f4cfb0c05' class='xr-var-data-in' type='checkbox'><label for='data-d214eb27-b7b2-4baf-bc1d-bf1f4cfb0c05' 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>Centre column poloidal mirnov array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].field.data</dd><dt><span>label :</span></dt><dd>Tesla/sec</dd><dt><span>name :</span></dt><dd>b_field_pol_probe_cc_field</dd><dt><span>uda_name :</span></dt><dd>xmc/CC/MV/201</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[1816000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_cc_phi</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a4687321-59b9-4581-a3e7-3fb636f3e3eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4687321-59b9-4581-a3e7-3fb636f3e3eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3347a63b-1e4d-4965-9ffe-3c2953d0a4ca' class='xr-var-data-in' type='checkbox'><label for='data-3347a63b-1e4d-4965-9ffe-3c2953d0a4ca' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal angle of the centre column poloidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_cc_r</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c3a2b175-057f-4c32-a09c-3f02de449bec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3a2b175-057f-4c32-a09c-3f02de449bec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fcec454-cb94-4be3-8d89-58e590430d62' class='xr-var-data-in' type='checkbox'><label for='data-8fcec454-cb94-4be3-8d89-58e590430d62' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the centre column poloidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_cc_z</span></div><div class='xr-var-dims'>(b_field_pol_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-10e519fc-f67a-4fb1-a1e4-f76898b95eab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10e519fc-f67a-4fb1-a1e4-f76898b95eab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc627bc6-7beb-495c-8e16-e13c6515d3fd' class='xr-var-data-in' type='checkbox'><label for='data-cc627bc6-7beb-495c-8e16-e13c6515d3fd' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the centre column poloidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_field</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_channel, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-39b4fdc0-4dd4-4827-95c7-3eb96d29ec43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39b4fdc0-4dd4-4827-95c7-3eb96d29ec43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a78c3aa-88db-47d7-bf54-4681c37de8d5' class='xr-var-data-in' type='checkbox'><label for='data-4a78c3aa-88db-47d7-bf54-4681c37de8d5' 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>Centre column Bv array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].field.data</dd><dt><span>label :</span></dt><dd>CCBV01</dd><dt><span>name :</span></dt><dd>b_field_pol_probe_ccbv_field</dd><dt><span>uda_name :</span></dt><dd>AMB_CCBV01</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[145280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_length</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17c5292e-2e8b-4a11-a3cc-5967338adf21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17c5292e-2e8b-4a11-a3cc-5967338adf21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5db980ea-57b6-4ce1-a2df-a201ae9c18af' class='xr-var-data-in' type='checkbox'><label for='data-5db980ea-57b6-4ce1-a2df-a201ae9c18af' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Length of the centre column Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].length</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_phi_1</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-af03bc70-6f66-4eab-a7b4-3485213b7e98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af03bc70-6f66-4eab-a7b4-3485213b7e98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ea52763-8143-480d-9311-a5a52f38f1c6' class='xr-var-data-in' type='checkbox'><label for='data-4ea52763-8143-480d-9311-a5a52f38f1c6' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 1 of the centre column Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_phi_2</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e69cd8d-d1c4-4099-a217-2b85b02e06ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e69cd8d-d1c4-4099-a217-2b85b02e06ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37125559-c319-4b1a-a4be-40459aaa8150' class='xr-var-data-in' type='checkbox'><label for='data-37125559-c319-4b1a-a4be-40459aaa8150' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 2 of the centre column Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_r</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f5ee9d7a-389e-4778-8c51-38849b4aa0a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5ee9d7a-389e-4778-8c51-38849b4aa0a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd349380-86e3-4f51-91be-de5b0a21d190' class='xr-var-data-in' type='checkbox'><label for='data-fd349380-86e3-4f51-91be-de5b0a21d190' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the centre column Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_ccbv_z</span></div><div class='xr-var-dims'>(b_field_pol_probe_ccbv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7ab72862-d773-4581-a43a-54d976da9343' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ab72862-d773-4581-a43a-54d976da9343' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e04e7f-1dcf-40f4-8b48-5341c9989b79' class='xr-var-data-in' type='checkbox'><label for='data-65e04e7f-1dcf-40f4-8b48-5341c9989b79' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the centre column Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[40 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_field</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_channel, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6ab6d853-6ec8-48a3-a9bf-00340a07695a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ab6d853-6ec8-48a3-a9bf-00340a07695a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32e0baaa-e180-46dd-b93a-99627651f8c9' class='xr-var-data-in' type='checkbox'><label for='data-32e0baaa-e180-46dd-b93a-99627651f8c9' 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>Outer Br array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].field.data</dd><dt><span>label :</span></dt><dd>OBR01</dd><dt><span>name :</span></dt><dd>b_field_pol_probe_obr_field</dd><dt><span>uda_name :</span></dt><dd>AMB_OBR01</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[69008 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_length</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ec4080d7-1bab-4ad7-8a80-fce202880200' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec4080d7-1bab-4ad7-8a80-fce202880200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73c60688-14e9-4b1e-902f-9ef16d5d3dd8' class='xr-var-data-in' type='checkbox'><label for='data-73c60688-14e9-4b1e-902f-9ef16d5d3dd8' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Length of the outer vessel Br array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.length</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_phi_1</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-485ccb73-33f1-4277-876e-374d81f908e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-485ccb73-33f1-4277-876e-374d81f908e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4710301-07c1-45c5-8658-b27f30b89490' class='xr-var-data-in' type='checkbox'><label for='data-a4710301-07c1-45c5-8658-b27f30b89490' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 1 of the outer vessel Br array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_phi_2</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e90394d2-52af-428c-a906-40d94122a0ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e90394d2-52af-428c-a906-40d94122a0ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3334bd0c-db4c-4387-a354-2ddae1b50e5d' class='xr-var-data-in' type='checkbox'><label for='data-3334bd0c-db4c-4387-a354-2ddae1b50e5d' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 2 of the outer vessel Br array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_r</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3fa0779c-3f33-4ca2-8959-b7dd7a703a87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fa0779c-3f33-4ca2-8959-b7dd7a703a87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abf8b958-e1bf-48f6-b322-c5546a5356e6' class='xr-var-data-in' type='checkbox'><label for='data-abf8b958-e1bf-48f6-b322-c5546a5356e6' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the outer vessel Br array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obr_z</span></div><div class='xr-var-dims'>(b_field_pol_probe_obr_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-897b5d72-a6c4-463e-aa28-7639c7723134' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-897b5d72-a6c4-463e-aa28-7639c7723134' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb35f5c5-df2e-42a1-9037-5922e0d7f0c1' class='xr-var-data-in' type='checkbox'><label for='data-bb35f5c5-df2e-42a1-9037-5922e0d7f0c1' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the outer vessel Br array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_field</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_channel, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a6480524-3615-4756-9181-05ebbecd2878' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6480524-3615-4756-9181-05ebbecd2878' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c78b5a5-ff1d-4821-aa32-f9f032bcb2e0' class='xr-var-data-in' type='checkbox'><label for='data-0c78b5a5-ff1d-4821-aa32-f9f032bcb2e0' 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>Outer Bv array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].field.data</dd><dt><span>name :</span></dt><dd>b_field_pol_probe_obv_field</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[69008 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_length</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1cf5399-a992-4716-afe3-a212f83d1d61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1cf5399-a992-4716-afe3-a212f83d1d61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d116010e-01f4-4990-9b0c-8bc40fcb8b42' class='xr-var-data-in' type='checkbox'><label for='data-d116010e-01f4-4990-9b0c-8bc40fcb8b42' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Length of the outer vessel Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.length</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_phi_1</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b4d65223-7404-4c12-ac6d-1577bfb09fa2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4d65223-7404-4c12-ac6d-1577bfb09fa2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51f28e20-c4d4-446d-8356-a40deb818f8a' class='xr-var-data-in' type='checkbox'><label for='data-51f28e20-c4d4-446d-8356-a40deb818f8a' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 1 of the outer vessel Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_phi_2</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e77746e0-e7b7-4245-a816-b0af110a65cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e77746e0-e7b7-4245-a816-b0af110a65cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03142ee5-841d-4d2d-b893-72c01a136566' class='xr-var-data-in' type='checkbox'><label for='data-03142ee5-841d-4d2d-b893-72c01a136566' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Phi 2 of the outer vessel Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_r</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dfc86014-029b-493f-af3a-add1b3d02f9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfc86014-029b-493f-af3a-add1b3d02f9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fa6416a-a88b-4100-b5fb-eebc92a62404' class='xr-var-data-in' type='checkbox'><label for='data-5fa6416a-a88b-4100-b5fb-eebc92a62404' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the outer vessel Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_obv_z</span></div><div class='xr-var-dims'>(b_field_pol_probe_obv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3f668d2a-75f6-480b-b2a0-06078ba08d53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f668d2a-75f6-480b-b2a0-06078ba08d53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10aab957-9531-4d94-bf13-3c987992eaf8' class='xr-var-data-in' type='checkbox'><label for='data-10aab957-9531-4d94-bf13-3c987992eaf8' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the pickup coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-08-15</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_pickup.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the outer vessel Bv array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMA_OBV_OBR Outer Bv_Br Discrete Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/Centre Column Vertical Bv Arrays - XMA_CCBV.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>pickup</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[19 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_omv_phi</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6c7dc1bb-8f14-44c0-8559-9d4719969ce4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c7dc1bb-8f14-44c0-8559-9d4719969ce4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d9abe7c-c8b4-4aad-87c9-526067333b0d' class='xr-var-data-in' type='checkbox'><label for='data-2d9abe7c-c8b4-4aad-87c9-526067333b0d' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal angle of the Outboard vertical mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[21 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_omv_r</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-38396fd5-bd2d-4648-8ee9-690e7718e3a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38396fd5-bd2d-4648-8ee9-690e7718e3a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-073626c7-6ffc-44a9-b0f0-249897cc419c' class='xr-var-data-in' type='checkbox'><label for='data-073626c7-6ffc-44a9-b0f0-249897cc419c' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the Outboard vertical mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[21 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_omv_voltage</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_channel, time_mirnov)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-abc77514-baf0-4eed-ad35-be8254b7cb73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abc77514-baf0-4eed-ad35-be8254b7cb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f16e2f6-8f02-4e9c-9c36-8cc578fb357a' class='xr-var-data-in' type='checkbox'><label for='data-5f16e2f6-8f02-4e9c-9c36-8cc578fb357a' 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>Outboard vertical mirnov array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].voltage.data</dd><dt><span>label :</span></dt><dd>Volt</dd><dt><span>name :</span></dt><dd>b_field_pol_probe_omv_voltage</dd><dt><span>uda_name :</span></dt><dd>xmc/OMV/110</dd><dt><span>units :</span></dt><dd>V</dd></dl></div><div class='xr-var-data'><pre>[1089600 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_pol_probe_omv_z</span></div><div class='xr-var-dims'>(b_field_pol_probe_omv_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c8158be-6fff-4e4a-ab23-be17d194a612' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c8158be-6fff-4e4a-ab23-be17d194a612' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c35ce5-79fb-46dd-a2c0-d8192ad076bc' class='xr-var-data-in' type='checkbox'><label for='data-f4c35ce5-79fb-46dd-a2c0-d8192ad076bc' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the Outboard vertical mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_pol_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[21 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_cc_field</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_channel, time_mirnov)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0f31b60e-d19a-4dfd-b878-4581c2673a59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f31b60e-d19a-4dfd-b878-4581c2673a59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efd315ef-9376-4c0c-8d0a-f3951c6cfe31' class='xr-var-data-in' type='checkbox'><label for='data-efd315ef-9376-4c0c-8d0a-f3951c6cfe31' 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>Centre column toroidal mirnov array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].field.data</dd><dt><span>label :</span></dt><dd>Tesla/sec</dd><dt><span>name :</span></dt><dd>b_field_tor_probe_cc_field</dd><dt><span>uda_name :</span></dt><dd>xmc/CC/MT/201</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[1089600 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_cc_phi</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-85543cd5-0e38-4bf7-b149-67d0d2f29afb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85543cd5-0e38-4bf7-b149-67d0d2f29afb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fc43021-e24c-4e84-b4ee-3eba28d35294' class='xr-var-data-in' type='checkbox'><label for='data-6fc43021-e24c-4e84-b4ee-3eba28d35294' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal angle of the centre column toroidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[36 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_cc_r</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f9b269dc-7a4f-43a3-a3f8-3e0b3e178164' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9b269dc-7a4f-43a3-a3f8-3e0b3e178164' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e73a0917-b85c-429a-a6bc-d64169a2087a' class='xr-var-data-in' type='checkbox'><label for='data-e73a0917-b85c-429a-a6bc-d64169a2087a' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the centre column toroidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[36 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_cc_z</span></div><div class='xr-var-dims'>(b_field_tor_probe_cc_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-65035f7f-2f2e-4334-bd27-3aa0b4e5deb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65035f7f-2f2e-4334-bd27-3aa0b4e5deb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bd93a26-1e1c-46ec-8efa-928d16e93154' class='xr-var-data-in' type='checkbox'><label for='data-3bd93a26-1e1c-46ec-8efa-928d16e93154' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the mirnov coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_mirnovs.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the centre column toroidal mirnov array</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMC_OMV - Outboard vertical (Bv_Br) Mirnov Arrays.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMV - Centre Column Vertical Array of Bv Mirnovs.pdf, https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/CCMT - CC toroidal Arrays of Bv Mirnovs.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>mirnov</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[36 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_omaha_voltage</span></div><div class='xr-var-dims'>(b_field_tor_probe_omaha_channel, time_omaha)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a60cac2f-bbf4-4dcb-b0b8-54b64fd262b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a60cac2f-bbf4-4dcb-b0b8-54b64fd262b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e07dff10-70b8-4508-bd9a-cf0b0efcba2e' class='xr-var-data-in' type='checkbox'><label for='data-e07dff10-70b8-4508-bd9a-cf0b0efcba2e' 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>High frequency OMAHA toroidal mirnov array</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].voltage.data</dd><dt><span>label :</span></dt><dd>arb</dd><dt><span>license :</span></dt><dd>{&quot;name&quot;: &quot;Creative Commons 4.0 BY-SA&quot;, &quot;url&quot;: &quot;https://creativecommons.org/licenses/by-sa/4.0/&quot;}</dd><dt><span>name :</span></dt><dd>b_field_tor_probe_omaha_voltage</dd><dt><span>uda_name :</span></dt><dd>/xmo/OMAHA/1LZ</dd><dt><span>units :</span></dt><dd>V</dd></dl></div><div class='xr-var-data'><pre>[29056000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_field</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_field_channel, time_saddle)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0ccd1a58-5af1-40cb-97dc-ae2c1c9c16b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ccd1a58-5af1-40cb-97dc-ae2c1c9c16b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07142086-875e-4a85-a067-2708b0691a68' class='xr-var-data-in' type='checkbox'><label for='data-07142086-875e-4a85-a067-2708b0691a68' 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></dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].field.data</dd><dt><span>label :</span></dt><dd>mT</dd><dt><span>name :</span></dt><dd>b_field_tor_probe_saddle_field</dd><dt><span>uda_name :</span></dt><dd>ASM_SAD/M01</dd><dt><span>units :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>[435840 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_l_phi</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_l_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3df2050e-2caf-478c-8400-353bfc03e3c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3df2050e-2caf-478c-8400-353bfc03e3c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62b628e-9e88-4908-81ac-c272b789a02a' class='xr-var-data-in' type='checkbox'><label for='data-b62b628e-9e88-4908-81ac-c272b789a02a' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal points of the lower saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_l_r</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_l_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e7afed2a-2006-49ff-ab53-47528bce3b02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7afed2a-2006-49ff-ab53-47528bce3b02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81446890-fbad-4c38-8437-a38657b2638f' class='xr-var-data-in' type='checkbox'><label for='data-81446890-fbad-4c38-8437-a38657b2638f' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Radial points of the lower saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_l_z</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_l_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-01f16180-05a6-4bcf-88b0-df3939886501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01f16180-05a6-4bcf-88b0-df3939886501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21da0a73-3b3f-409b-b74f-a13576864609' class='xr-var-data-in' type='checkbox'><label for='data-21da0a73-3b3f-409b-b74f-a13576864609' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical positions of the lower saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_m_phi</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_m_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1f6e0cb-c3ad-4533-9218-e82d9cdb7ab0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1f6e0cb-c3ad-4533-9218-e82d9cdb7ab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0bd78ba-e84b-4ddf-ac09-68dfd5de8d51' class='xr-var-data-in' type='checkbox'><label for='data-e0bd78ba-e84b-4ddf-ac09-68dfd5de8d51' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal points of the middle saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_m_r</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_m_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-486f78eb-b09b-440a-b85f-d5f62c028699' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-486f78eb-b09b-440a-b85f-d5f62c028699' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66679897-975a-44d4-9a5e-391538711a4e' class='xr-var-data-in' type='checkbox'><label for='data-66679897-975a-44d4-9a5e-391538711a4e' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Radial points of the middle saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_m_z</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_m_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d02d8a1a-7fdb-48ac-a52d-de97a873e721' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d02d8a1a-7fdb-48ac-a52d-de97a873e721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b560ef27-4bf5-4441-be12-08902afbdbf8' class='xr-var-data-in' type='checkbox'><label for='data-b560ef27-4bf5-4441-be12-08902afbdbf8' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical positions of the middle saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_u_phi</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_u_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-61a23000-4995-48b9-85c7-436cc2f1116c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61a23000-4995-48b9-85c7-436cc2f1116c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e25c4579-c63e-4b0c-89b5-a527fdcc59b9' class='xr-var-data-in' type='checkbox'><label for='data-e25c4579-c63e-4b0c-89b5-a527fdcc59b9' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Toroidal points of the upper saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.phi</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_u_r</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_u_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8eb9cc8c-fc83-4761-9840-0081d9e72cf9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8eb9cc8c-fc83-4761-9840-0081d9e72cf9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2894d86e-0c10-4415-8dee-1f4593d79ee2' class='xr-var-data-in' type='checkbox'><label for='data-2894d86e-0c10-4415-8dee-1f4593d79ee2' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Radial points of the upper saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_u_z</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_u_geometry_channel, coordinate)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-608d4d60-a263-49a0-b072-1f9271a35e94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-608d4d60-a263-49a0-b072-1f9271a35e94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8783bc9-bade-40cb-8a92-030332887f62' class='xr-var-data-in' type='checkbox'><label for='data-b8783bc9-bade-40cb-8a92-030332887f62' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from configuration PDF</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the saddle coils for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-01</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_saddle.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical positions of the upper saddle coils</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.b_field_tor_probe[:].position.z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/XMB_SAD Outer Saddle Coils.pdf</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>saddle coils</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[336 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_field_tor_probe_saddle_voltage</span></div><div class='xr-var-dims'>(b_field_tor_probe_saddle_voltage_channel, time_saddle)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d3a86aa7-cdfd-4517-8749-eaa2606a1d25' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3a86aa7-cdfd-4517-8749-eaa2606a1d25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dd5870b-ff55-4b84-acd1-c86f86a8485e' class='xr-var-data-in' type='checkbox'><label for='data-9dd5870b-ff55-4b84-acd1-c86f86a8485e' 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'></dl></div><div class='xr-var-data'><pre>[435840 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flux_loop_flux</span></div><div class='xr-var-dims'>(flux_loop_channel, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a32a16c6-1381-4999-8634-60557bf5fa99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a32a16c6-1381-4999-8634-60557bf5fa99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2b80675-dd15-4c57-9148-b6f005e96aa3' class='xr-var-data-in' type='checkbox'><label for='data-c2b80675-dd15-4c57-9148-b6f005e96aa3' 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></dd><dt><span>imas :</span></dt><dd>magnetics.flux_loop[:].flux.data</dd><dt><span>label :</span></dt><dd>FL/CC03</dd><dt><span>name :</span></dt><dd>flux_loop_flux</dd><dt><span>uda_name :</span></dt><dd>AMB_FL/CC03</dd><dt><span>units :</span></dt><dd>Wb</dd></dl></div><div class='xr-var-data'><pre>[54480 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flux_loop_r</span></div><div class='xr-var-dims'>(flux_loop_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7543bbc9-96bf-44ef-9703-3366bcc8d08a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7543bbc9-96bf-44ef-9703-3366bcc8d08a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0297edba-b877-4a16-8ba0-0cb33937cb41' class='xr-var-data-in' type='checkbox'><label for='data-0297edba-b877-4a16-8ba0-0cb33937cb41' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from EFIT file</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the fluxloops for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_fluxloops.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Major radius of the flux loops</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.flux_loop[:].position[:].r</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/detectors.dat_M4</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>fluxloops</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[44 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flux_loop_z</span></div><div class='xr-var-dims'>(flux_loop_geometry_channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8910a7b6-b482-4f1a-b35f-4688cc24d9a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8910a7b6-b482-4f1a-b35f-4688cc24d9a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85cd8819-9957-4a76-b4b6-1af759067e83' class='xr-var-data-in' type='checkbox'><label for='data-85cd8819-9957-4a76-b4b6-1af759067e83' 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>calibration :</span></dt><dd>None</dd><dt><span>class_ :</span></dt><dd>magnetics</dd><dt><span>comment :</span></dt><dd>Data sourced from EFIT file</dd><dt><span>configuration :</span></dt><dd>geometry</dd><dt><span>content :</span></dt><dd>geometry of the fluxloops for MAST</dd><dt><span>coordinateSystem :</span></dt><dd>Cylindrical</dd><dt><span>createdBy :</span></dt><dd>James Hodson (xq0472)</dd><dt><span>creationDate :</span></dt><dd>2025-07-08</dd><dt><span>creatorCode :</span></dt><dd>python create_netcdf_fluxloops.py</dd><dt><span>creatorCommitId :</span></dt><dd></dd><dt><span>creatorRepo :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry</dd><dt><span>description :</span></dt><dd>Vertical position of the flux loops</dd><dt><span>device :</span></dt><dd>MAST</dd><dt><span>imas :</span></dt><dd>magnetics.flux_loop[:].position[:].z</dd><dt><span>owner :</span></dt><dd>MAST Data Systems Team</dd><dt><span>revision :</span></dt><dd>0</dd><dt><span>shotRangeStart :</span></dt><dd>0</dd><dt><span>shotRangeStop :</span></dt><dd>40000</dd><dt><span>signedOffBy :</span></dt><dd>lkogan</dd><dt><span>source :</span></dt><dd>https://git.ccfe.ac.uk/MAST-U/mast-geometry/sources/detectors.dat_M4</dd><dt><span>status :</span></dt><dd>development</dd><dt><span>system :</span></dt><dd>fluxloops</dd><dt><span>units :</span></dt><dd>SI, degrees, m</dd><dt><span>version :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[44 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-65ea7075-5cff-44e3-9a3f-8f7db11dd194' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65ea7075-5cff-44e3-9a3f-8f7db11dd194' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52a1c932-c669-4d58-96f0-8aa65283d198' class='xr-var-data-in' type='checkbox'><label for='data-52a1c932-c669-4d58-96f0-8aa65283d198' 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></dd><dt><span>imas :</span></dt><dd>magnetics.ip[:].data</dd><dt><span>label :</span></dt><dd>Plasma Current</dd><dt><span>name :</span></dt><dd>ip</dd><dt><span>uda_name :</span></dt><dd>AMC_PLASMA CURRENT</dd><dt><span>units :</span></dt><dd>A</dd></dl></div><div class='xr-var-data'><pre>[3632 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0708a21b-84b8-4013-8933-f3be840191b5' class='xr-section-summary-in' type='checkbox'  ><label for='section-0708a21b-84b8-4013-8933-f3be840191b5' class='xr-section-summary' >Indexes: <span>(25)</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>b_field_pol_probe_cc_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-487e1f17-9aeb-4374-b781-27dc0d272d40' class='xr-index-data-in' type='checkbox'/><label for='index-487e1f17-9aeb-4374-b781-27dc0d272d40' 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(Index([&#x27;xmc/CC/MV/201&#x27;, &#x27;xmc/CC/MV/210&#x27;, &#x27;xmc/CC/MV/220&#x27;, &#x27;xmc/CC/MV/230&#x27;,\n",
       "       &#x27;xmc/CC/MV/240&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_cc_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_cc_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-32cb2ab8-3bb9-41b9-9add-f8e5ac58518e' class='xr-index-data-in' type='checkbox'/><label for='index-32cb2ab8-3bb9-41b9-9add-f8e5ac58518e' 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(Index([&#x27;cc_mv_201&#x27;, &#x27;cc_mv_202*&#x27;, &#x27;cc_mv_203*&#x27;, &#x27;cc_mv_204*&#x27;, &#x27;cc_mv_205*&#x27;,\n",
       "       &#x27;cc_mv_206*&#x27;, &#x27;cc_mv_207*&#x27;, &#x27;cc_mv_208*&#x27;, &#x27;cc_mv_209*&#x27;, &#x27;cc_mv_210*&#x27;,\n",
       "       &#x27;cc_mv_211*&#x27;, &#x27;cc_mv_212*&#x27;, &#x27;cc_mv_213*&#x27;, &#x27;cc_mv_214*&#x27;, &#x27;cc_mv_215*&#x27;,\n",
       "       &#x27;cc_mv_216*&#x27;, &#x27;cc_mv_217*&#x27;, &#x27;cc_mv_218*&#x27;, &#x27;cc_mv_219*&#x27;, &#x27;cc_mv_220*&#x27;,\n",
       "       &#x27;cc_mv_221*&#x27;, &#x27;cc_mv_222*&#x27;, &#x27;cc_mv_223*&#x27;, &#x27;cc_mv_224&#x27;, &#x27;cc_mv_225&#x27;,\n",
       "       &#x27;cc_mv_226&#x27;, &#x27;cc_mv_227&#x27;, &#x27;cc_mv_228&#x27;, &#x27;cc_mv_229&#x27;, &#x27;cc_mv_230&#x27;,\n",
       "       &#x27;cc_mv_231&#x27;, &#x27;cc_mv_232&#x27;, &#x27;cc_mv_233&#x27;, &#x27;cc_mv_234&#x27;, &#x27;cc_mv_235&#x27;,\n",
       "       &#x27;cc_mv_236&#x27;, &#x27;cc_mv_237&#x27;, &#x27;cc_mv_238&#x27;, &#x27;cc_mv_239&#x27;, &#x27;cc_mv_240&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_cc_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_ccbv_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-723d0a5b-592b-4b56-80c8-cdf4973e9a2c' class='xr-index-data-in' type='checkbox'/><label for='index-723d0a5b-592b-4b56-80c8-cdf4973e9a2c' 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(Index([&#x27;AMB_CCBV01&#x27;, &#x27;AMB_CCBV02&#x27;, &#x27;AMB_CCBV03&#x27;, &#x27;AMB_CCBV04&#x27;, &#x27;AMB_CCBV05&#x27;,\n",
       "       &#x27;AMB_CCBV06&#x27;, &#x27;AMB_CCBV07&#x27;, &#x27;AMB_CCBV08&#x27;, &#x27;AMB_CCBV09&#x27;, &#x27;AMB_CCBV10&#x27;,\n",
       "       &#x27;AMB_CCBV11&#x27;, &#x27;AMB_CCBV12&#x27;, &#x27;AMB_CCBV13&#x27;, &#x27;AMB_CCBV14&#x27;, &#x27;AMB_CCBV15&#x27;,\n",
       "       &#x27;AMB_CCBV16&#x27;, &#x27;AMB_CCBV17&#x27;, &#x27;AMB_CCBV18&#x27;, &#x27;AMB_CCBV19&#x27;, &#x27;AMB_CCBV20&#x27;,\n",
       "       &#x27;AMB_CCBV21&#x27;, &#x27;AMB_CCBV22&#x27;, &#x27;AMB_CCBV23&#x27;, &#x27;AMB_CCBV24&#x27;, &#x27;AMB_CCBV25&#x27;,\n",
       "       &#x27;AMB_CCBV26&#x27;, &#x27;AMB_CCBV27&#x27;, &#x27;AMB_CCBV28&#x27;, &#x27;AMB_CCBV29&#x27;, &#x27;AMB_CCBV30&#x27;,\n",
       "       &#x27;AMB_CCBV31&#x27;, &#x27;AMB_CCBV32&#x27;, &#x27;AMB_CCBV33&#x27;, &#x27;AMB_CCBV34&#x27;, &#x27;AMB_CCBV35&#x27;,\n",
       "       &#x27;AMB_CCBV36&#x27;, &#x27;AMB_CCBV37&#x27;, &#x27;AMB_CCBV38&#x27;, &#x27;AMB_CCBV39&#x27;, &#x27;AMB_CCBV40&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_ccbv_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_ccbv_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0d879b13-2f15-419c-a035-5078c999d588' class='xr-index-data-in' type='checkbox'/><label for='index-0d879b13-2f15-419c-a035-5078c999d588' 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(Index([&#x27;ccbv01&#x27;, &#x27;ccbv02&#x27;, &#x27;ccbv03&#x27;, &#x27;ccbv04&#x27;, &#x27;ccbv05&#x27;, &#x27;ccbv06&#x27;, &#x27;ccbv07&#x27;,\n",
       "       &#x27;ccbv08&#x27;, &#x27;ccbv09&#x27;, &#x27;ccbv10&#x27;, &#x27;ccbv11&#x27;, &#x27;ccbv12&#x27;, &#x27;ccbv13&#x27;, &#x27;ccbv14&#x27;,\n",
       "       &#x27;ccbv15&#x27;, &#x27;ccbv16&#x27;, &#x27;ccbv17&#x27;, &#x27;ccbv18&#x27;, &#x27;ccbv19&#x27;, &#x27;ccbv20&#x27;, &#x27;ccbv21&#x27;,\n",
       "       &#x27;ccbv22&#x27;, &#x27;ccbv23&#x27;, &#x27;ccbv24&#x27;, &#x27;ccbv25&#x27;, &#x27;ccbv26&#x27;, &#x27;ccbv27&#x27;, &#x27;ccbv28&#x27;,\n",
       "       &#x27;ccbv29&#x27;, &#x27;ccbv30&#x27;, &#x27;ccbv31&#x27;, &#x27;ccbv32&#x27;, &#x27;ccbv33&#x27;, &#x27;ccbv34&#x27;, &#x27;ccbv35&#x27;,\n",
       "       &#x27;ccbv36&#x27;, &#x27;ccbv37&#x27;, &#x27;ccbv38&#x27;, &#x27;ccbv39&#x27;, &#x27;ccbv40&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_ccbv_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_obr_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-bbb7a9ae-dc4e-4fcc-aefc-f1df1aec501e' class='xr-index-data-in' type='checkbox'/><label for='index-bbb7a9ae-dc4e-4fcc-aefc-f1df1aec501e' 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(Index([&#x27;AMB_OBR01&#x27;, &#x27;AMB_OBR02&#x27;, &#x27;AMB_OBR03&#x27;, &#x27;AMB_OBR04&#x27;, &#x27;AMB_OBR05&#x27;,\n",
       "       &#x27;AMB_OBR06&#x27;, &#x27;AMB_OBR07&#x27;, &#x27;AMB_OBR08&#x27;, &#x27;AMB_OBR09&#x27;, &#x27;AMB_OBR10&#x27;,\n",
       "       &#x27;AMB_OBR11&#x27;, &#x27;AMB_OBR12&#x27;, &#x27;AMB_OBR13&#x27;, &#x27;AMB_OBR14&#x27;, &#x27;AMB_OBR15&#x27;,\n",
       "       &#x27;AMB_OBR16&#x27;, &#x27;AMB_OBR17&#x27;, &#x27;AMB_OBR18&#x27;, &#x27;AMB_OBR19&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_obr_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_obr_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-41d695b0-890e-48de-b6d4-99b57ae40702' class='xr-index-data-in' type='checkbox'/><label for='index-41d695b0-890e-48de-b6d4-99b57ae40702' 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(Index([&#x27;obr01&#x27;, &#x27;obr02&#x27;, &#x27;obr03&#x27;, &#x27;obr04&#x27;, &#x27;obr05&#x27;, &#x27;obr06&#x27;, &#x27;obr07&#x27;, &#x27;obr08&#x27;,\n",
       "       &#x27;obr09&#x27;, &#x27;obr10&#x27;, &#x27;obr11&#x27;, &#x27;obr12&#x27;, &#x27;obr13&#x27;, &#x27;obr14&#x27;, &#x27;obr15&#x27;, &#x27;obr16&#x27;,\n",
       "       &#x27;obr17&#x27;, &#x27;obr18&#x27;, &#x27;obr19&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_obr_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_obv_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-29a3fde8-7276-47fe-b0d1-c8f34984dd11' class='xr-index-data-in' type='checkbox'/><label for='index-29a3fde8-7276-47fe-b0d1-c8f34984dd11' 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(Index([&#x27;AMB_OBV01&#x27;, &#x27;AMB_OBV02&#x27;, &#x27;AMB_OBV03&#x27;, &#x27;AMB_OBV04&#x27;, &#x27;AMB_OBV05&#x27;,\n",
       "       &#x27;AMB_OBV06&#x27;, &#x27;AMB_OBV07&#x27;, &#x27;AMB_OBV08&#x27;, &#x27;AMB_OBV09&#x27;, &#x27;AMB_OBV10&#x27;,\n",
       "       &#x27;AMB_OBV11&#x27;, &#x27;AMB_OBV12&#x27;, &#x27;AMB_OBV13&#x27;, &#x27;AMB_OBV14&#x27;, &#x27;AMB_OBV15&#x27;,\n",
       "       &#x27;AMB_OBV16&#x27;, &#x27;AMB_OBV17&#x27;, &#x27;AMB_OBV18&#x27;, &#x27;AMB_OBV19&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_obv_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_obv_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-8821f571-2c97-4c30-bcb2-088aea55ea6b' class='xr-index-data-in' type='checkbox'/><label for='index-8821f571-2c97-4c30-bcb2-088aea55ea6b' 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(Index([&#x27;obv01&#x27;, &#x27;obv02&#x27;, &#x27;obv03&#x27;, &#x27;obv04&#x27;, &#x27;obv05&#x27;, &#x27;obv06&#x27;, &#x27;obv07&#x27;, &#x27;obv08&#x27;,\n",
       "       &#x27;obv09&#x27;, &#x27;obv10&#x27;, &#x27;obv11&#x27;, &#x27;obv12&#x27;, &#x27;obv13&#x27;, &#x27;obv14&#x27;, &#x27;obv15&#x27;, &#x27;obv16&#x27;,\n",
       "       &#x27;obv17&#x27;, &#x27;obv18&#x27;, &#x27;obv19&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_obv_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_omv_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-a5d86019-b824-4a01-bdb4-8442ecd75e02' class='xr-index-data-in' type='checkbox'/><label for='index-a5d86019-b824-4a01-bdb4-8442ecd75e02' 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(Index([&#x27;xmc/OMV/110&#x27;, &#x27;xmc/OMV/210&#x27;, &#x27;xmc/OMV/310&#x27;], dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_omv_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_pol_probe_omv_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4667f13c-4362-4ac4-9a8a-3d40221f7daa' class='xr-index-data-in' type='checkbox'/><label for='index-4667f13c-4362-4ac4-9a8a-3d40221f7daa' 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(Index([&#x27;omv_201&#x27;, &#x27;omv_202&#x27;, &#x27;omv_203&#x27;, &#x27;omv_204&#x27;, &#x27;omv_205&#x27;, &#x27;omv_206&#x27;,\n",
       "       &#x27;omv_207&#x27;, &#x27;omv_208&#x27;, &#x27;omv_209&#x27;, &#x27;omv_210&#x27;, &#x27;omv_211&#x27;, &#x27;omv_212&#x27;,\n",
       "       &#x27;omv_213&#x27;, &#x27;omv_214&#x27;, &#x27;omv_215&#x27;, &#x27;omv_216&#x27;, &#x27;omv_217&#x27;, &#x27;omv_218&#x27;,\n",
       "       &#x27;omv_219&#x27;, &#x27;omv_110&#x27;, &#x27;omv_310&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_pol_probe_omv_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_cc_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4a58996f-4e53-423e-a227-d09abef8094e' class='xr-index-data-in' type='checkbox'/><label for='index-4a58996f-4e53-423e-a227-d09abef8094e' 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(Index([&#x27;xmc/CC/MT/201&#x27;, &#x27;xmc/CC/MT/206&#x27;, &#x27;xmc/CC/MT/212&#x27;], dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_cc_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_cc_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1a5b2981-55be-4a30-8739-ad3d042b3c6a' class='xr-index-data-in' type='checkbox'/><label for='index-1a5b2981-55be-4a30-8739-ad3d042b3c6a' 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(Index([&#x27;cc_mt_101&#x27;, &#x27;cc_mt_102&#x27;, &#x27;cc_mt_103&#x27;, &#x27;cc_mt_104&#x27;, &#x27;cc_mt_105&#x27;,\n",
       "       &#x27;cc_mt_106&#x27;, &#x27;cc_mt_107&#x27;, &#x27;cc_mt_108&#x27;, &#x27;cc_mt_109&#x27;, &#x27;cc_mt_110&#x27;,\n",
       "       &#x27;cc_mt_111&#x27;, &#x27;cc_mt_112&#x27;, &#x27;cc_mt_201&#x27;, &#x27;cc_mt_202&#x27;, &#x27;cc_mt_203&#x27;,\n",
       "       &#x27;cc_mt_204&#x27;, &#x27;cc_mt_205&#x27;, &#x27;cc_mt_206&#x27;, &#x27;cc_mt_207&#x27;, &#x27;cc_mt_208&#x27;,\n",
       "       &#x27;cc_mt_209&#x27;, &#x27;cc_mt_210&#x27;, &#x27;cc_mt_211&#x27;, &#x27;cc_mt_212&#x27;, &#x27;cc_mt_301&#x27;,\n",
       "       &#x27;cc_mt_302&#x27;, &#x27;cc_mt_303&#x27;, &#x27;cc_mt_304&#x27;, &#x27;cc_mt_305&#x27;, &#x27;cc_mt_306&#x27;,\n",
       "       &#x27;cc_mt_307&#x27;, &#x27;cc_mt_308&#x27;, &#x27;cc_mt_309&#x27;, &#x27;cc_mt_310&#x27;, &#x27;cc_mt_311&#x27;,\n",
       "       &#x27;cc_mt_312&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_cc_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_omaha_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2ffa0888-3d73-4bfb-98b2-05d34d1dfb0d' class='xr-index-data-in' type='checkbox'/><label for='index-2ffa0888-3d73-4bfb-98b2-05d34d1dfb0d' 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(Index([&#x27;/xmo/OMAHA/1LZ&#x27;, &#x27;/xmo/OMAHA/3LZ&#x27;, &#x27;/xmo/OMAHA/5LZ&#x27;, &#x27;/xmo/OMAHA/6LZ&#x27;], dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_omaha_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_saddle_field_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-775c108a-7bbc-423e-855d-729fd0baa0be' class='xr-index-data-in' type='checkbox'/><label for='index-775c108a-7bbc-423e-855d-729fd0baa0be' 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(Index([&#x27;ASM_SAD/M01&#x27;, &#x27;ASM_SAD/M02&#x27;, &#x27;ASM_SAD/M03&#x27;, &#x27;ASM_SAD/M04&#x27;,\n",
       "       &#x27;ASM_SAD/M05&#x27;, &#x27;ASM_SAD/M06&#x27;, &#x27;ASM_SAD/M07&#x27;, &#x27;ASM_SAD/M08&#x27;,\n",
       "       &#x27;ASM_SAD/M09&#x27;, &#x27;ASM_SAD/M10&#x27;, &#x27;ASM_SAD/M11&#x27;, &#x27;ASM_SAD/M12&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_saddle_field_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_saddle_l_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-58523f03-ea33-4bc0-b12c-eb141e20f201' class='xr-index-data-in' type='checkbox'/><label for='index-58523f03-ea33-4bc0-b12c-eb141e20f201' 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(Index([&#x27;sad_out_l01&#x27;, &#x27;sad_out_l02&#x27;, &#x27;sad_out_l03&#x27;, &#x27;sad_out_l04&#x27;,\n",
       "       &#x27;sad_out_l05&#x27;, &#x27;sad_out_l06&#x27;, &#x27;sad_out_l07&#x27;, &#x27;sad_out_l08&#x27;,\n",
       "       &#x27;sad_out_l09&#x27;, &#x27;sad_out_l10&#x27;, &#x27;sad_out_l11&#x27;, &#x27;sad_out_l12&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_saddle_l_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_saddle_m_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9e5826c5-fad7-4f8d-8a71-c9b976f3cf12' class='xr-index-data-in' type='checkbox'/><label for='index-9e5826c5-fad7-4f8d-8a71-c9b976f3cf12' 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(Index([&#x27;sad_out_m01&#x27;, &#x27;sad_out_m02&#x27;, &#x27;sad_out_m03&#x27;, &#x27;sad_out_m04&#x27;,\n",
       "       &#x27;sad_out_m05&#x27;, &#x27;sad_out_m06&#x27;, &#x27;sad_out_m07&#x27;, &#x27;sad_out_m08&#x27;,\n",
       "       &#x27;sad_out_m09&#x27;, &#x27;sad_out_m10&#x27;, &#x27;sad_out_m11&#x27;, &#x27;sad_out_m12&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_saddle_m_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_saddle_u_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e3461703-a20e-4141-bc62-39a40d47adab' class='xr-index-data-in' type='checkbox'/><label for='index-e3461703-a20e-4141-bc62-39a40d47adab' 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(Index([&#x27;sad_out_u01&#x27;, &#x27;sad_out_u02&#x27;, &#x27;sad_out_u03&#x27;, &#x27;sad_out_u04&#x27;,\n",
       "       &#x27;sad_out_u05&#x27;, &#x27;sad_out_u06&#x27;, &#x27;sad_out_u07&#x27;, &#x27;sad_out_u08&#x27;,\n",
       "       &#x27;sad_out_u09&#x27;, &#x27;sad_out_u10&#x27;, &#x27;sad_out_u11&#x27;, &#x27;sad_out_u12&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_saddle_u_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>b_field_tor_probe_saddle_voltage_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-601500d8-be65-4c04-87df-ef9e6ee5c89d' class='xr-index-data-in' type='checkbox'/><label for='index-601500d8-be65-4c04-87df-ef9e6ee5c89d' 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(Index([&#x27;XMB/SAD/OUT/M01&#x27;, &#x27;XMB/SAD/OUT/M02&#x27;, &#x27;XMB/SAD/OUT/M03&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M04&#x27;, &#x27;XMB/SAD/OUT/M05&#x27;, &#x27;XMB/SAD/OUT/M06&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M07&#x27;, &#x27;XMB/SAD/OUT/M08&#x27;, &#x27;XMB/SAD/OUT/M09&#x27;,\n",
       "       &#x27;XMB/SAD/OUT/M10&#x27;, &#x27;XMB/SAD/OUT/M11&#x27;, &#x27;XMB/SAD/OUT/M12&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;b_field_tor_probe_saddle_voltage_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>coordinate</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e3fc94cc-4f8d-4fbf-b1d1-eab0eca9d966' class='xr-index-data-in' type='checkbox'/><label for='index-e3fc94cc-4f8d-4fbf-b1d1-eab0eca9d966' 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(Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;coordinate&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>flux_loop_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f580981d-b559-4931-9d0f-d6f30878d413' class='xr-index-data-in' type='checkbox'/><label for='index-f580981d-b559-4931-9d0f-d6f30878d413' 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(Index([&#x27;AMB_FL/CC03&#x27;, &#x27;AMB_FL/CC04&#x27;, &#x27;AMB_FL/CC05&#x27;, &#x27;AMB_FL/CC07&#x27;,\n",
       "       &#x27;AMB_FL/CC09&#x27;, &#x27;AMB_FL/P3L/4&#x27;, &#x27;AMB_FL/P3U/1&#x27;, &#x27;AMB_FL/P3U/4&#x27;,\n",
       "       &#x27;AMB_FL/P4L/1&#x27;, &#x27;AMB_FL/P4L/4&#x27;, &#x27;AMB_FL/P4U/4&#x27;, &#x27;AMB_FL/P5L/1&#x27;,\n",
       "       &#x27;AMB_FL/P5L/4&#x27;, &#x27;AMB_FL/P5U/1&#x27;, &#x27;AMB_FL/P6L/1&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;flux_loop_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>flux_loop_geometry_channel</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-48908026-6647-4021-99ca-7688967b2cc9' class='xr-index-data-in' type='checkbox'/><label for='index-48908026-6647-4021-99ca-7688967b2cc9' 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(Index([&#x27;FL_P2U_1&#x27;, &#x27;FL_P2U_2&#x27;, &#x27;FL_P2U_3&#x27;, &#x27;FL_P2U_4&#x27;, &#x27;FL_P2L_1&#x27;, &#x27;FL_P2L_2&#x27;,\n",
       "       &#x27;FL_P2L_3&#x27;, &#x27;FL_P2L_4&#x27;, &#x27;FL_P3U_1&#x27;, &#x27;FL_P3U_2&#x27;, &#x27;FL_P3U_3&#x27;, &#x27;FL_P3U_4&#x27;,\n",
       "       &#x27;FL_P3L_1&#x27;, &#x27;FL_P3L_2&#x27;, &#x27;FL_P3L_3&#x27;, &#x27;FL_P3L_4&#x27;, &#x27;FL_P4U_1&#x27;, &#x27;FL_P4U_2&#x27;,\n",
       "       &#x27;FL_P4U_3&#x27;, &#x27;FL_P4U_4&#x27;, &#x27;FL_P4L_1&#x27;, &#x27;FL_P4L_2&#x27;, &#x27;FL_P4L_3&#x27;, &#x27;FL_P4L_4&#x27;,\n",
       "       &#x27;FL_P5U_1&#x27;, &#x27;FL_P5U_2&#x27;, &#x27;FL_P5U_3&#x27;, &#x27;FL_P5U_4&#x27;, &#x27;FL_P5L_1&#x27;, &#x27;FL_P5L_2&#x27;,\n",
       "       &#x27;FL_P5L_3&#x27;, &#x27;FL_P5L_4&#x27;, &#x27;FL_P6L_1&#x27;, &#x27;FL_P6L_2&#x27;, &#x27;FL_CC01&#x27;, &#x27;FL_CC02&#x27;,\n",
       "       &#x27;FL_CC03&#x27;, &#x27;FL_CC04&#x27;, &#x27;FL_CC05&#x27;, &#x27;FL_CC06&#x27;, &#x27;FL_CC07&#x27;, &#x27;FL_CC08&#x27;,\n",
       "       &#x27;FL_CC09&#x27;, &#x27;FL_CC010&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;flux_loop_geometry_channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c823e688-4146-4b71-99c7-570f502f4317' class='xr-index-data-in' type='checkbox'/><label for='index-c823e688-4146-4b71-99c7-570f502f4317' 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(Index([ -0.06120028719305992,  -0.06100028719305992, -0.060800287193059924,\n",
       "       -0.060600287193059925, -0.060400287193059926,  -0.06020028719305993,\n",
       "        -0.06000028719305993,  -0.05980028719305993,  -0.05960028719305993,\n",
       "        -0.05940028719305993,\n",
       "       ...\n",
       "          0.6631997128069357,    0.6633997128069357,    0.6635997128069357,\n",
       "          0.6637997128069357,    0.6639997128069357,    0.6641997128069357,\n",
       "          0.6643997128069357,    0.6645997128069356,    0.6647997128069357,\n",
       "          0.6649997128069357],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=3632))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_mirnov</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e5e81d76-2712-4fd5-81dd-677688895156' class='xr-index-data-in' type='checkbox'/><label for='index-e5e81d76-2712-4fd5-81dd-677688895156' 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(Index([ -0.06120028719305992,  -0.06119828719305992,  -0.06119628719305992,\n",
       "       -0.061194287193059915,  -0.06119228719305991,  -0.06119028719305991,\n",
       "        -0.06118828719305991,  -0.06118628719305991, -0.061184287193059905,\n",
       "         -0.0611822871930599,\n",
       "       ...\n",
       "          0.6651797128076665,    0.6651817128076665,    0.6651837128076665,\n",
       "          0.6651857128076666,    0.6651877128076665,    0.6651897128076665,\n",
       "          0.6651917128076665,    0.6651937128076666,    0.6651957128076665,\n",
       "          0.6651977128076665],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time_mirnov&#x27;, length=363200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_omaha</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c62f17fb-7ea0-4e7c-b67c-d0b969b87b9c' class='xr-index-data-in' type='checkbox'/><label for='index-c62f17fb-7ea0-4e7c-b67c-d0b969b87b9c' 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(Index([ -0.06120028719305992,  -0.06120018719305992, -0.061200087193059916,\n",
       "        -0.06119998719305991,  -0.06119988719305991,  -0.06119978719305991,\n",
       "       -0.061199687193059904,   -0.0611995871930599,   -0.0611994871930599,\n",
       "       -0.061199387193059895,\n",
       "       ...\n",
       "          0.6651987128278282,    0.6651988128278281,    0.6651989128278282,\n",
       "          0.6651990128278282,    0.6651991128278282,    0.6651992128278281,\n",
       "          0.6651993128278282,    0.6651994128278282,    0.6651995128278282,\n",
       "          0.6651996128278281],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time_omaha&#x27;, length=7264000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_saddle</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-54daaeb4-fd44-4f3e-b2b2-74cf0c74e5fc' class='xr-index-data-in' type='checkbox'/><label for='index-54daaeb4-fd44-4f3e-b2b2-74cf0c74e5fc' 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(Index([ -0.06120028719305992,  -0.06118028719305992,  -0.06116028719305992,\n",
       "       -0.061140287193059924, -0.061120287193059925, -0.061100287193059925,\n",
       "       -0.061080287193059926,  -0.06106028719305993,  -0.06104028719305993,\n",
       "        -0.06102028719305993,\n",
       "       ...\n",
       "          0.6649997128069105,    0.6650197128069105,    0.6650397128069105,\n",
       "          0.6650597128069105,    0.6650797128069105,    0.6650997128069105,\n",
       "          0.6651197128069105,    0.6651397128069105,    0.6651597128069104,\n",
       "          0.6651797128069105],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time_saddle&#x27;, length=36320))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba1bcaca-3d20-4751-9b18-19a33b03fc1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ba1bcaca-3d20-4751-9b18-19a33b03fc1a' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd></dd><dt><span>imas :</span></dt><dd>magnetics</dd><dt><span>label :</span></dt><dd>Plasma Current</dd><dt><span>license :</span></dt><dd>{&#x27;name&#x27;: &#x27;Creative Commons 4.0 BY-SA&#x27;, &#x27;url&#x27;: &#x27;https://creativecommons.org/licenses/by-sa/4.0/&#x27;}</dd><dt><span>name :</span></dt><dd>magnetics</dd><dt><span>uda_name :</span></dt><dd>AMC_PLASMA CURRENT</dd><dt><span>units :</span></dt><dd>A</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 335MB\n",
       "Dimensions:                                      (\n",
       "                                                  b_field_pol_probe_cc_channel: 5,\n",
       "                                                  time_mirnov: 363200,\n",
       "                                                  b_field_pol_probe_cc_geometry_channel: 40,\n",
       "                                                  b_field_pol_probe_ccbv_channel: 40,\n",
       "                                                  time: 3632,\n",
       "                                                  ...\n",
       "                                                  coordinate: 28,\n",
       "                                                  b_field_tor_probe_saddle_m_geometry_channel: 12,\n",
       "                                                  b_field_tor_probe_saddle_u_geometry_channel: 12,\n",
       "                                                  b_field_tor_probe_saddle_voltage_channel: 12,\n",
       "                                                  flux_loop_channel: 15,\n",
       "                                                  flux_loop_geometry_channel: 44)\n",
       "Coordinates: (12/25)\n",
       "  * b_field_pol_probe_cc_channel                 (b_field_pol_probe_cc_channel) <U13 260B ...\n",
       "  * b_field_pol_probe_cc_geometry_channel        (b_field_pol_probe_cc_geometry_channel) object 320B ...\n",
       "  * b_field_pol_probe_ccbv_channel               (b_field_pol_probe_ccbv_channel) <U10 2kB ...\n",
       "  * b_field_pol_probe_ccbv_geometry_channel      (b_field_pol_probe_ccbv_geometry_channel) object 320B ...\n",
       "  * b_field_pol_probe_obr_channel                (b_field_pol_probe_obr_channel) <U9 684B ...\n",
       "  * b_field_pol_probe_obr_geometry_channel       (b_field_pol_probe_obr_geometry_channel) object 152B ...\n",
       "    ...                                           ...\n",
       "  * flux_loop_channel                            (flux_loop_channel) <U12 720B ...\n",
       "  * flux_loop_geometry_channel                   (flux_loop_geometry_channel) object 352B ...\n",
       "  * time                                         (time) float64 29kB -0.0612 ...\n",
       "  * time_mirnov                                  (time_mirnov) float64 3MB -0...\n",
       "  * time_omaha                                   (time_omaha) float64 58MB -0...\n",
       "  * time_saddle                                  (time_saddle) float64 291kB ...\n",
       "Data variables: (12/46)\n",
       "    b_field_pol_probe_cc_field                   (b_field_pol_probe_cc_channel, time_mirnov) float64 15MB ...\n",
       "    b_field_pol_probe_cc_phi                     (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_cc_r                       (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_cc_z                       (b_field_pol_probe_cc_geometry_channel) float64 320B ...\n",
       "    b_field_pol_probe_ccbv_field                 (b_field_pol_probe_ccbv_channel, time) float64 1MB ...\n",
       "    b_field_pol_probe_ccbv_length                (b_field_pol_probe_ccbv_geometry_channel) float64 320B ...\n",
       "    ...                                           ...\n",
       "    b_field_tor_probe_saddle_u_z                 (b_field_tor_probe_saddle_u_geometry_channel, coordinate) float64 3kB ...\n",
       "    b_field_tor_probe_saddle_voltage             (b_field_tor_probe_saddle_voltage_channel, time_saddle) float64 3MB ...\n",
       "    flux_loop_flux                               (flux_loop_channel, time) float64 436kB ...\n",
       "    flux_loop_r                                  (flux_loop_geometry_channel) float64 352B ...\n",
       "    flux_loop_z                                  (flux_loop_geometry_channel) float64 352B ...\n",
       "    ip                                           (time) float64 29kB ...\n",
       "Attributes:\n",
       "    description:  \n",
       "    imas:         magnetics\n",
       "    label:        Plasma Current\n",
       "    license:      {'name': 'Creative Commons 4.0 BY-SA', 'url': 'https://crea...\n",
       "    name:         magnetics\n",
       "    uda_name:     AMC_PLASMA CURRENT\n",
       "    units:        A"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load magnetics geometry data\n",
    "ds_mag = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group=\"magnetics\",\n",
    ")\n",
    "ds_mag"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "saddle-header",
   "metadata": {},
   "source": [
    "### Saddle Coils\n",
    "\n",
    "Saddle coils measure toroidal magnetic field and are positioned at different vertical levels around the tokamak."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "saddle-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract saddle coil positions (lower, middle, upper)\n",
    "saddle_data = {\n",
    "    'Lower': ('b_field_tor_probe_saddle_l', 'blue'),\n",
    "    'Middle': ('b_field_tor_probe_saddle_m', 'green'), \n",
    "    'Upper': ('b_field_tor_probe_saddle_u', 'red')\n",
    "}\n",
    "\n",
    "fig = plt.figure(figsize=(10, 7))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for level, (var_prefix, color) in saddle_data.items():\n",
    "    r = ds_mag[f'{var_prefix}_r']\n",
    "    z = ds_mag[f'{var_prefix}_z'] \n",
    "    phi = ds_mag[f'{var_prefix}_phi']\n",
    "    \n",
    "    x, y, z_cart = cyl_to_cart(r, phi, z)\n",
    "    ax.scatter(x, y, z_cart, c=color, label=f'Saddle {level}', s=20)\n",
    "\n",
    "ax.set_xlabel(\"X (m)\")\n",
    "ax.set_ylabel(\"Y (m)\")\n",
    "ax.set_zlabel(\"Z (m)\")\n",
    "ax.set_title(\"Toroidal Magnetic Field Saddle Probe Positions\")\n",
    "ax.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pickup-header",
   "metadata": {},
   "source": [
    "### Pickup Coils\n",
    "\n",
    "Pickup coils measure poloidal magnetic field. They are arranged in pairs at different toroidal angles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "pickup-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pickup coil data - each type has two toroidal positions\n",
    "pickup_coils = {\n",
    "    'CCBV': ('b_field_pol_probe_ccbv', 'green'),\n",
    "    'OBR': ('b_field_pol_probe_obr', 'blue'),\n",
    "    'OBV': ('b_field_pol_probe_obv', 'pink')\n",
    "}\n",
    "\n",
    "fig = plt.figure(figsize=(10, 7))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for coil_type, (var_prefix, color) in pickup_coils.items():\n",
    "    r = ds_mag[f'{var_prefix}_r']\n",
    "    z = ds_mag[f'{var_prefix}_z']\n",
    "    phi1 = ds_mag[f'{var_prefix}_phi_1']\n",
    "    phi2 = ds_mag[f'{var_prefix}_phi_2']\n",
    "    \n",
    "    # Plot both toroidal positions\n",
    "    x1, y1, z1 = cyl_to_cart(r, phi1, z)\n",
    "    x2, y2, z2 = cyl_to_cart(r, phi2, z)\n",
    "    \n",
    "    ax.scatter(x1, y1, z1, c=color, label=f'{coil_type}1', s=20)\n",
    "    ax.scatter(x2, y2, z2, c=color, label=f'{coil_type}2', s=20, alpha=0.7)\n",
    "\n",
    "ax.set_xlabel(\"X (m)\")\n",
    "ax.set_ylabel(\"Y (m)\")\n",
    "ax.set_zlabel(\"Z (m)\")\n",
    "ax.set_title(\"Poloidal Magnetic Field Pickup Coil Positions\")\n",
    "ax.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "flux-loops-header",
   "metadata": {},
   "source": [
    "### Flux Loops (R-Z cross-section)\n",
    "\n",
    "Flux loops measure poloidal flux and are positioned around different PF coil locations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "flux-loops-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get flux loop data\n",
    "r = ds_mag['flux_loop_r']\n",
    "z = ds_mag['flux_loop_z']\n",
    "channels = ds_mag['flux_loop_geometry_channel']\n",
    "\n",
    "def get_all_flux_loop_coords(channels, r, z, pattern):\n",
    "    \"\"\"Get all R,Z coordinates for flux loops matching a pattern\"\"\"\n",
    "    matching_channels = [ch for ch in channels.values if pattern in ch]\n",
    "    if matching_channels:\n",
    "        r_vals = []\n",
    "        z_vals = []\n",
    "        for channel in matching_channels:\n",
    "            r_vals.append(r.sel(flux_loop_geometry_channel=channel).values)\n",
    "            z_vals.append(z.sel(flux_loop_geometry_channel=channel).values)\n",
    "        return np.array(r_vals), np.array(z_vals)\n",
    "    return None, None\n",
    "\n",
    "# Group flux loops by PF coil region\n",
    "flux_loop_groups = {\n",
    "    \"CC\": \"FL_CC\",      # Central column\n",
    "    \"P2L\": \"FL_P2L\",    # PF coil 2 lower\n",
    "    \"P2U\": \"FL_P2U\",    # PF coil 2 upper\n",
    "    \"P3L\": \"FL_P3L\",    # PF coil 3 lower\n",
    "    \"P3U\": \"FL_P3U\",    # PF coil 3 upper\n",
    "    \"P4L\": \"FL_P4L\",    # PF coil 4 lower\n",
    "    \"P4U\": \"FL_P4U\",    # PF coil 4 upper\n",
    "    \"P5L\": \"FL_P5L\",    # PF coil 5 lower\n",
    "    \"P5U\": \"FL_P5U\",    # PF coil 5 upper\n",
    "    \"P6L\": \"FL_P6L\"     # PF coil 6 lower\n",
    "}\n",
    "\n",
    "flux_loops = {}\n",
    "for label, pattern in flux_loop_groups.items():\n",
    "    r_vals, z_vals = get_all_flux_loop_coords(channels, r, z, pattern)\n",
    "    if r_vals is not None:\n",
    "        flux_loops[label] = (r_vals, z_vals)\n",
    "\n",
    "# Plot flux loop positions\n",
    "plt.figure(figsize=(8, 8))\n",
    "for label, (r_vals, z_vals) in flux_loops.items():\n",
    "    plt.scatter(r_vals.flatten(), z_vals.flatten(), s=15, label=label)\n",
    "\n",
    "plt.xlabel(\"R (m)\")\n",
    "plt.ylabel(\"Z (m)\")\n",
    "plt.title(\"Flux Loop Positions (R-Z View)\")\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.axis('equal')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mirnov-header",
   "metadata": {},
   "source": [
    "### Mirnov Coils\n",
    "\n",
    "Mirnov coils are high-frequency magnetic probes used to measure MHD activity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "mirnov-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Mirnov coil types\n",
    "mirnov_coils = {\n",
    "    'Outer Mirnov': ('b_field_pol_probe_omv', 'blue'),\n",
    "    'CC Poloidal': ('b_field_pol_probe_cc', 'green'),\n",
    "    'CC Toroidal': ('b_field_tor_probe_cc', 'red')\n",
    "}\n",
    "\n",
    "fig = plt.figure(figsize=(10, 7))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for coil_type, (var_prefix, color) in mirnov_coils.items():\n",
    "    r = ds_mag[f'{var_prefix}_r']\n",
    "    z = ds_mag[f'{var_prefix}_z']\n",
    "    phi = ds_mag[f'{var_prefix}_phi']\n",
    "    \n",
    "    x, y, z_cart = cyl_to_cart(r, phi, z)\n",
    "    ax.scatter(x, y, z_cart, c=color, label=coil_type, s=20)\n",
    "\n",
    "ax.set_xlabel(\"X (m)\")\n",
    "ax.set_ylabel(\"Y (m)\")\n",
    "ax.set_zlabel(\"Z (m)\")\n",
    "ax.set_title(\"Mirnov Coil Positions\")\n",
    "ax.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pf-active-header",
   "metadata": {},
   "source": [
    "## Poloidal Field (PF) Active Coils\n",
    "\n",
    "PF coils control the plasma shape and position. Each coil is represented as a collection of rectangular elements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "pf-active-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load PF active coil data\n",
    "ds_pf_active = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group=\"pf_active\",\n",
    ")\n",
    "\n",
    "# Define PF coil groups\n",
    "pf_coils = {\n",
    "    'P2 Inner Lower': ('p2_inner_lower', 'red'),\n",
    "    'P2 Outer Lower': ('p2_outer_lower', 'blue'),\n",
    "    'P2 Inner Upper': ('p2_inner_upper', 'darkred'),\n",
    "    'P2 Outer Upper': ('p2_outer_upper', 'darkblue'),\n",
    "    'P3 Lower': ('p3_lower', 'green'),\n",
    "    'P3 Upper': ('p3_upper', 'darkgreen'),\n",
    "    'P4 Lower': ('p4_lower', 'orange'),\n",
    "    'P4 Upper': ('p4_upper', 'darkorange'),\n",
    "    'P5 Lower': ('p5_lower', 'purple'),\n",
    "    'P5 Upper': ('p5_upper', 'indigo'),\n",
    "    'P6 Lower': ('p6_lower', 'brown'),\n",
    "    'P6 Upper': ('p6_upper', 'chocolate'),\n",
    "    'Solenoid': ('sol', 'black')\n",
    "}\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12, 10))\n",
    "legend_added = set()\n",
    "\n",
    "for coil_name, (var_prefix, color) in pf_coils.items():\n",
    "    r_arr = np.asarray(ds_pf_active[f'{var_prefix}_r'])\n",
    "    z_arr = np.asarray(ds_pf_active[f'{var_prefix}_z'])\n",
    "    w_arr = np.asarray(ds_pf_active[f'{var_prefix}_width'])\n",
    "    h_arr = np.asarray(ds_pf_active[f'{var_prefix}_height'])\n",
    "    \n",
    "    for j, (r, z, w, h) in enumerate(zip(r_arr, z_arr, w_arr, h_arr)):\n",
    "        if np.isnan(r) or np.isnan(z) or np.isnan(w) or np.isnan(h):\n",
    "            continue\n",
    "            \n",
    "        label_for_legend = coil_name if coil_name not in legend_added else \"\"\n",
    "        if coil_name not in legend_added:\n",
    "            legend_added.add(coil_name)\n",
    "\n",
    "        rect = Rectangle((r - w/2, z - h/2), w, h,\n",
    "                        facecolor=color, edgecolor='black', alpha=0.7, \n",
    "                        label=label_for_legend, linewidth=0.5)\n",
    "        ax.add_patch(rect)\n",
    "\n",
    "ax.set_xlim(0, 2.0)\n",
    "ax.set_ylim(-2.2, 2.2)\n",
    "ax.set_xlabel(\"R (m)\")\n",
    "ax.set_ylabel(\"Z (m)\")\n",
    "ax.set_title(\"Poloidal Field Active Coils\")\n",
    "ax.set_aspect('equal')\n",
    "ax.grid(True, alpha=0.3)\n",
    "ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pf-passive-header",
   "metadata": {},
   "source": [
    "## Passive Structure Components\n",
    "\n",
    "Passive structures include vessel components, supports, and other conducting structures. These use the EFIT element geometry description with potential shape angles for parallelograms.\n",
    "\n",
    "The below diagram describes the geometry values stored for PF passive.\n",
    "\n",
    "The `shapeangle2` value is set to 0 when it reaches 90 degrees. At any other positive value between 0-89, the shape will slant outwards."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4cdd5fc",
   "metadata": {},
   "source": [
    "![Passive Structure Diagram](./assets/passive_struct_diagram.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "efit-geometry-functions",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_element_vertices(centreR, centreZ, dR, dZ, a1, a2, version=0.0, close_shape=False, rotate_90=False):\n",
    "    \"\"\"\n",
    "    Convert EFIT description of rectangles/parallelograms to vertices.\n",
    "    Based on the MAST geometry implementation.\n",
    "    \n",
    "    Parameters:\n",
    "    - centreR, centreZ: Center position\n",
    "    - dR, dZ: Width and height\n",
    "    - a1, a2: Shape angles (degrees, 0 for rectangles)\n",
    "    - rotate_90: Swap width/height for special cases\n",
    "    \"\"\"\n",
    "    # Handle special rotation for coil cases (coil cases are inherently rotated by 90 degrees at the source file, so needs to be corrected when plotting)\n",
    "    if rotate_90:\n",
    "        dR, dZ = dZ, dR\n",
    "\n",
    "    # Use absolute values to handle negative dimensions\n",
    "    dR = abs(dR)\n",
    "    dZ = abs(dZ)\n",
    "\n",
    "    if a1 == 0.0 and a2 == 0.0:\n",
    "        # Simple rectangle\n",
    "        rr = [centreR - dR/2, centreR - dR/2, centreR + dR/2, centreR + dR/2]\n",
    "        zz = [centreZ - dZ/2, centreZ + dZ/2, centreZ + dZ/2, centreZ - dZ/2]\n",
    "    else:\n",
    "        # Parallelogram with angles\n",
    "        a1_tan = np.tan(a1 * np.pi / 180.0) if a1 > 0.0 else 0.0\n",
    "        a2_tan = 1.0 / np.tan(a2 * np.pi / 180.0) if a2 > 0.0 else 0.0\n",
    "\n",
    "        rr = [centreR - dR/2 - dZ/2 * a2_tan,\n",
    "              centreR + dR/2 - dZ/2 * a2_tan,\n",
    "              centreR + dR/2 + dZ/2 * a2_tan,\n",
    "              centreR - dR/2 + dZ/2 * a2_tan]\n",
    "        \n",
    "        zz = [centreZ - dZ/2 - dR/2 * a1_tan,\n",
    "              centreZ - dZ/2 + dR/2 * a1_tan,\n",
    "              centreZ + dZ/2 + dR/2 * a1_tan,\n",
    "              centreZ + dZ/2 - dR/2 * a1_tan]\n",
    "        \n",
    "    if close_shape:\n",
    "        rr.append(rr[0])\n",
    "        zz.append(zz[0])\n",
    "        \n",
    "    return (rr, zz)\n",
    "\n",
    "def plot_passive_component(ax, component_name, ds, color, alpha=0.6):\n",
    "    \"\"\"Plot passive component using EFIT geometry calculation\"\"\"\n",
    "    # Get component data\n",
    "    r_vals = np.atleast_1d(ds[f'{component_name}_r'].values)\n",
    "    z_vals = np.atleast_1d(ds[f'{component_name}_z'].values)\n",
    "    w_vals = np.atleast_1d(ds[f'{component_name}_width'].values)\n",
    "    h_vals = np.atleast_1d(ds[f'{component_name}_height'].values)\n",
    "\n",
    "    # Get shape angles (default to 0 if not present)\n",
    "    try:\n",
    "        a1_vals = np.atleast_1d(ds[f'{component_name}_shapeAngle1'].values)\n",
    "        a2_vals = np.atleast_1d(ds[f'{component_name}_shapeAngle2'].values)\n",
    "    except KeyError:\n",
    "        a1_vals = np.zeros_like(r_vals)\n",
    "        a2_vals = np.zeros_like(r_vals)\n",
    "    \n",
    "    plotted_any = False\n",
    "    # Special handling for coil cases\n",
    "    rotate_90 = (component_name == 'coil_cases')\n",
    "    \n",
    "    for i, (r, z, w, h, a1, a2) in enumerate(zip(r_vals, z_vals, w_vals, h_vals, a1_vals, a2_vals)):\n",
    "        if np.isnan(r) or np.isnan(z) or np.isnan(w) or np.isnan(h):\n",
    "            continue\n",
    "        if abs(w) < 1e-6 or abs(h) < 1e-6:\n",
    "            continue\n",
    "\n",
    "        # Get vertices using EFIT method\n",
    "        rr, zz = get_element_vertices(r, z, w, h, a1, a2, rotate_90=rotate_90)\n",
    "\n",
    "        # Create polygon\n",
    "        vertices = list(zip(rr, zz))\n",
    "        polygon = Polygon(vertices, facecolor=color, edgecolor='black',\n",
    "                         alpha=alpha, label=component_name if not plotted_any else '',\n",
    "                         linewidth=0.5)\n",
    "        ax.add_patch(polygon)\n",
    "        plotted_any = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "pf-passive-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load passive structure data\n",
    "ds_pf_passive = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group=\"pf_passive\",\n",
    ")\n",
    "\n",
    "# Define passive structure components\n",
    "passive_components = [\n",
    "    'botcol', 'topcol', 'endcrown_l', 'endcrown_u', 'incon',\n",
    "    'lhorw', 'uhorw', 'mid', 'vertw', 'ring', 'rodgr',\n",
    "    'p2larm', 'p2ldivpl', 'p2uarm', 'p2udivpl', 'coil_cases'\n",
    "]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12, 10))\n",
    "colors = ['red', 'blue', 'green', 'orange', 'purple', 'brown', 'pink',\n",
    "          'gray', 'olive', 'cyan', 'magenta', 'yellow', 'lime', 'navy',\n",
    "          'maroon', 'teal']\n",
    "\n",
    "for i, component in enumerate(passive_components):\n",
    "    if f'{component}_r' not in ds_pf_passive.data_vars:\n",
    "        continue\n",
    "    color = colors[i % len(colors)]\n",
    "    plot_passive_component(ax, component, ds_pf_passive, color)\n",
    "\n",
    "ax.set_xlim(0, 2.2)\n",
    "ax.set_ylim(-2.5, 2.5)\n",
    "ax.set_xlabel('R (m)')\n",
    "ax.set_ylabel('Z (m)')\n",
    "ax.set_title('Passive Structure Components')\n",
    "ax.set_aspect('equal')\n",
    "ax.grid(True, alpha=0.3)\n",
    "ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "xray-header",
   "metadata": {},
   "source": [
    "## Soft X-ray Diagnostics\n",
    "\n",
    "It is useful to plot the line-of-sight X ray cams alongside the limiter.\n",
    "\n",
    "All cameras apart from tangential camera are viewed toroidally when plotted, so if you want to plot the tangential cameras you need to be looking \"down\" from the top of the tokamak instead of the side like we are with all the other cameras. \n",
    "\n",
    "The vertical and tangential cameras also have a LOS that ends at the midpoint (due to the source geometry data). We can extrapolate this to go past the limiter to get a better idea of the LOS up to the limiter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "xray-plot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load soft X-ray and wall data\n",
    "ds_xray = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group=\"soft_x_rays\",\n",
    ")\n",
    "\n",
    "ds_wall = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group=\"wall\",\n",
    ")\n",
    "\n",
    "# Camera configurations\n",
    "cameras = {\n",
    "    'Horizontal Lower': 'horizontal_cam_lower',\n",
    "    'Horizontal Upper': 'horizontal_cam_upper', \n",
    "    'Third Horizontal': 'third_horizontal_cam',\n",
    "    'Inner Vertical': 'inner_vertical_cam',\n",
    "    'Outer Vertical': 'outer_vertical_cam',\n",
    "    'Tangential': 'tangential_cam'\n",
    "}\n",
    "\n",
    "# Create subplot for each camera\n",
    "fig, axes = plt.subplots(2, 3, figsize=(15, 10))\n",
    "axes = axes.flatten()\n",
    "\n",
    "# Get limiter data\n",
    "limiter_r = ds_wall['limiter_r']\n",
    "limiter_z = ds_wall['limiter_z']\n",
    "\n",
    "for i, (cam_name, var_prefix) in enumerate(cameras.items()):\n",
    "    ax = axes[i]\n",
    "    \n",
    "    # Get camera line-of-sight data\n",
    "    try:\n",
    "        origin_r = ds_xray[f'{var_prefix}_origin_r']\n",
    "        origin_z = ds_xray[f'{var_prefix}_origin_z']\n",
    "        endpoint_r = ds_xray[f'{var_prefix}_endpoint_r']\n",
    "        endpoint_z = ds_xray[f'{var_prefix}_endpoint_z']\n",
    "    except KeyError:\n",
    "        ax.text(0.5, 0.5, f'{cam_name}\\nData not available', \n",
    "               transform=ax.transAxes, ha='center', va='center')\n",
    "        ax.set_title(cam_name)\n",
    "        continue\n",
    "    \n",
    "    # Special handling for tangential camera (top-down view)\n",
    "    if cam_name == 'Tangential':\n",
    "        # Plot tokamak cross-section circles\n",
    "        for radius in [0.2, 1.4, 2.0]:\n",
    "            style = \"--\" if radius == 1.4 else \"-\"\n",
    "            circle = plt.Circle((0, 0), radius, fill=False, color=\"black\", \n",
    "                              linestyle=style, alpha=0.5)\n",
    "            ax.add_patch(circle)\n",
    "        \n",
    "        # Plot lines of sight (extrapolated)\n",
    "        scale = 2.0\n",
    "        for j in range(len(origin_r)):\n",
    "            dr = endpoint_r[j] - origin_r[j]\n",
    "            dz = endpoint_z[j] - origin_z[j]\n",
    "            r1 = origin_r[j] + scale * dr\n",
    "            z1 = origin_z[j] + scale * dz\n",
    "            ax.plot([origin_r[j], r1], [origin_z[j], z1], 'r-', alpha=0.7)\n",
    "        \n",
    "        ax.set_xlabel('R (m)')\n",
    "        ax.set_ylabel('R (m)')  # Note: different view\n",
    "        ax.set_title(f'{cam_name} (Top-down view)')\n",
    "        ax.set_xlim(-2.2, 2.2)\n",
    "        ax.set_ylim(-2.2, 2.2)\n",
    "    else:\n",
    "        # Plot limiter outline\n",
    "        ax.plot(limiter_r, limiter_z, 'k-', linewidth=2, alpha=0.7, label='Limiter')\n",
    "        \n",
    "        # Plot lines of sight\n",
    "        extrapolate = 'Vertical' in cam_name\n",
    "        scale = 2.0 if extrapolate else 1.0\n",
    "        \n",
    "        for j in range(len(origin_r)):\n",
    "            if extrapolate:\n",
    "                # Extrapolate for vertical cameras\n",
    "                dr = endpoint_r[j] - origin_r[j]\n",
    "                dz = endpoint_z[j] - origin_z[j]\n",
    "                r1 = origin_r[j] + scale * dr\n",
    "                z1 = origin_z[j] + scale * dz\n",
    "            else:\n",
    "                r1, z1 = endpoint_r[j], endpoint_z[j]\n",
    "            \n",
    "            ax.plot([origin_r[j], r1], [origin_z[j], z1], 'r-', alpha=0.7)\n",
    "        \n",
    "        ax.set_xlabel('R (m)')\n",
    "        ax.set_ylabel('Z (m)')\n",
    "        ax.set_title(cam_name)\n",
    "        ax.set_xlim(0, 2.2)\n",
    "        ax.set_ylim(-2.2, 2.2)\n",
    "    \n",
    "    ax.grid(True, alpha=0.3)\n",
    "    ax.set_aspect('equal')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
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