diff --git a/examples/adcp_example.ipynb b/examples/adcp_example.ipynb
index e24299a20..cdcfaea21 100644
--- a/examples/adcp_example.ipynb
+++ b/examples/adcp_example.ipynb
@@ -29,13 +29,14 @@
     "6. **Saving and Loading DOLfYN datasets**\n",
     "\n",
     "7. **Turbulence Statistics**\n",
-    "    1. TI\n",
+    "    1. Turbulence Intensity (TI)\n",
     "    2. Power Spectral Densities\n",
-    "    3. TKE Dissipation Rate\n",
-    "    4. TKE Componenets\n",
-    "    5. ADCP Noise\n",
-    "    6. TKE Production\n",
-    "    7. TKE Balance \n",
+    "    3. Instrument Noise\n",
+    "    4. TKE Dissipation Rate\n",
+    "    5. Noise-corrected TI\n",
+    "    6. TKE Componenets\n",
+    "    7. TKE Production\n",
+    "    8. TKE Balance \n",
     "\n",
     "\n",
     "Begin your analysis by importing the requisite tools:"
@@ -52,7 +53,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\Users\\mcve343\\Anaconda3\\lib\\site-packages\\xarray\\backends\\cfgrib_.py:29: UserWarning: Failed to load cfgrib - most likely there is a problem accessing the ecCodes library. Try `import cfgrib` to get the full error message\n",
+      "c:\\Users\\mcve343\\anaconda3\\envs\\tsdat-pipelines\\lib\\site-packages\\xarray\\backends\\cfgrib_.py:29: UserWarning: Failed to load cfgrib - most likely there is a problem accessing the ecCodes library. Try `import cfgrib` to get the full error message\n",
       "  warnings.warn(\n"
      ]
     }
@@ -510,26 +511,26 @@
        "    coord_sys:             earth\n",
        "    fs:                    1\n",
        "    has_imu:               1\n",
-       "    beam_angle:            25</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-f69eecd5-9a97-436b-9aae-72e3246c1d4e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f69eecd5-9a97-436b-9aae-72e3246c1d4e' 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'>time</span>: 55000</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fb6fe242-7dd8-456d-bb67-8fe006eb4180' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fb6fe242-7dd8-456d-bb67-8fe006eb4180' class='xr-section-summary' >Coordinates: <span>(12)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-d1f6305f-f90e-4135-bba1-dd0ba444cc58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1f6305f-f90e-4135-bba1-dd0ba444cc58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c688c0-2583-45a4-9b50-3dd38bc3ed9b' class='xr-var-data-in' type='checkbox'><label for='data-63c688c0-2583-45a4-9b50-3dd38bc3ed9b' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+       "    beam_angle:            25</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-32696568-6d41-402b-a612-0b7216025509' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-32696568-6d41-402b-a612-0b7216025509' 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'>time</span>: 55000</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7ef5388a-8163-465d-a4fc-6750aa6416f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7ef5388a-8163-465d-a4fc-6750aa6416f3' class='xr-section-summary' >Coordinates: <span>(12)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-06ba5ddd-81e5-474d-9636-d0a35d73f2c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ba5ddd-81e5-474d-9636-d0a35d73f2c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541da3ac-3e7b-473d-ae3b-a884ce605504' class='xr-var-data-in' type='checkbox'><label for='data-541da3ac-3e7b-473d-ae3b-a884ce605504' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
        "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
        "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-9e6feeff-bcac-483a-ad8c-be92c4789389' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e6feeff-bcac-483a-ad8c-be92c4789389' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b757786-f914-492c-ae46-e806099cf76e' class='xr-var-data-in' type='checkbox'><label for='data-1b757786-f914-492c-ae46-e806099cf76e' 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-48b4d064-3f41-40ed-8113-60e8a78625d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48b4d064-3f41-40ed-8113-60e8a78625d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb54a43f-26a7-430d-877c-5d1f4029c46c' class='xr-var-data-in' type='checkbox'><label for='data-bb54a43f-26a7-430d-877c-5d1f4029c46c' 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-7b2d2669-5cef-4d7c-998f-9fac17c3f457' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b2d2669-5cef-4d7c-998f-9fac17c3f457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13c4100c-28a0-4425-a560-3ffbe176ee62' class='xr-var-data-in' type='checkbox'><label for='data-13c4100c-28a0-4425-a560-3ffbe176ee62' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-29ef1ab4-9001-4dcd-8460-dc3a1e0f243e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29ef1ab4-9001-4dcd-8460-dc3a1e0f243e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d1c7073-4b7e-441e-bb03-462d79aff00b' class='xr-var-data-in' type='checkbox'><label for='data-4d1c7073-4b7e-441e-bb03-462d79aff00b' 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-841251a7-34da-4b1a-976f-38684ec3d503' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-841251a7-34da-4b1a-976f-38684ec3d503' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f161a0aa-f99e-4aa4-97bc-59169bbe95f5' class='xr-var-data-in' type='checkbox'><label for='data-f161a0aa-f99e-4aa4-97bc-59169bbe95f5' 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-69b6ad0a-b32c-496e-a4dd-e7dd7ae61288' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69b6ad0a-b32c-496e-a4dd-e7dd7ae61288' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6ba9520-ff9f-4719-a305-c02c5cc9bbe6' class='xr-var-data-in' type='checkbox'><label for='data-c6ba9520-ff9f-4719-a305-c02c5cc9bbe6' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
        "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3c91de47-5922-4c88-9c12-8ef08f9a57e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c91de47-5922-4c88-9c12-8ef08f9a57e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e987a66-b617-419a-bda1-090fc67354ea' class='xr-var-data-in' type='checkbox'><label for='data-7e987a66-b617-419a-bda1-090fc67354ea' 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-c88fcae9-6a19-4241-91c2-942e51b36fb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c88fcae9-6a19-4241-91c2-942e51b36fb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e096af11-96b1-4ca9-a498-9549b4ada7a4' class='xr-var-data-in' type='checkbox'><label for='data-e096af11-96b1-4ca9-a498-9549b4ada7a4' 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-a6a7cd15-2c4a-4266-a32b-8d19656c3eb4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6a7cd15-2c4a-4266-a32b-8d19656c3eb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3ab052e-25ff-45c0-9886-fd6e7237e8cf' class='xr-var-data-in' type='checkbox'><label for='data-f3ab052e-25ff-45c0-9886-fd6e7237e8cf' 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-b51900cf-04cc-4cd7-b93d-7fa6e3fab6bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b51900cf-04cc-4cd7-b93d-7fa6e3fab6bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06ae108d-7266-487d-a7e1-9f754a2083db' class='xr-var-data-in' type='checkbox'><label for='data-06ae108d-7266-487d-a7e1-9f754a2083db' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-925d3c35-49c4-48ce-a777-9a6319616235' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-925d3c35-49c4-48ce-a777-9a6319616235' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1fc1108-1711-466f-b81f-d9675cebbea3' class='xr-var-data-in' type='checkbox'><label for='data-a1fc1108-1711-466f-b81f-d9675cebbea3' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-a2b9f4f7-8b03-4c35-b853-90a3d54b41cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2b9f4f7-8b03-4c35-b853-90a3d54b41cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23155b8e-a91c-4b51-87c0-353a637c3993' class='xr-var-data-in' type='checkbox'><label for='data-23155b8e-a91c-4b51-87c0-353a637c3993' 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-aec677a5-0c13-478f-8ba0-676ce0d6e08c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aec677a5-0c13-478f-8ba0-676ce0d6e08c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d48c3cc8-091c-4507-925c-acfcca5b32a5' class='xr-var-data-in' type='checkbox'><label for='data-d48c3cc8-091c-4507-925c-acfcca5b32a5' 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-bd437f0b-0d56-46f2-a31c-b5369985f561' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd437f0b-0d56-46f2-a31c-b5369985f561' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5265a25-9546-4330-865b-ab5c40434c8f' class='xr-var-data-in' type='checkbox'><label for='data-b5265a25-9546-4330-865b-ab5c40434c8f' 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-d20eb24c-ef3c-4cc7-be62-f64e7f4f3e2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d20eb24c-ef3c-4cc7-be62-f64e7f4f3e2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab6162d0-e6da-4624-9671-5e9c07295451' class='xr-var-data-in' type='checkbox'><label for='data-ab6162d0-e6da-4624-9671-5e9c07295451' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-15a23381-0faf-4dfd-bed5-903323acf155' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a23381-0faf-4dfd-bed5-903323acf155' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88262298-1109-46ed-9fb0-e5d2b775ce3c' class='xr-var-data-in' type='checkbox'><label for='data-88262298-1109-46ed-9fb0-e5d2b775ce3c' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
        "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
        "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-b317b6aa-e93a-4b45-983a-3b7931537c6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b317b6aa-e93a-4b45-983a-3b7931537c6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4d84c84-4936-42a3-967d-efa427265c25' class='xr-var-data-in' type='checkbox'><label for='data-f4d84c84-4936-42a3-967d-efa427265c25' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-ba0fb0b5-ba95-4302-a1d6-49a2c104e25a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba0fb0b5-ba95-4302-a1d6-49a2c104e25a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ebec3c8-6c7d-48a3-bb9b-6815c0ecb839' class='xr-var-data-in' type='checkbox'><label for='data-0ebec3c8-6c7d-48a3-bb9b-6815c0ecb839' 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>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
        "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-f80bfaf8-a9b7-4125-8fa5-5a6a8cc2bcf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f80bfaf8-a9b7-4125-8fa5-5a6a8cc2bcf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72833946-2c87-486f-bb4e-c086f8d83fd3' class='xr-var-data-in' type='checkbox'><label for='data-72833946-2c87-486f-bb4e-c086f8d83fd3' 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>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-a14aff8b-f1ed-4976-b254-7326ada113dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a14aff8b-f1ed-4976-b254-7326ada113dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f2ecbe6-2486-4090-8397-318f8c17b11e' class='xr-var-data-in' type='checkbox'><label for='data-1f2ecbe6-2486-4090-8397-318f8c17b11e' 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>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-60a7d102-c02e-40e7-bd87-93737c6fa53e' class='xr-section-summary-in' type='checkbox'  ><label for='section-60a7d102-c02e-40e7-bd87-93737c6fa53e' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-b6338355-132c-40ec-86b5-3f75b29e12e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6338355-132c-40ec-86b5-3f75b29e12e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8ae8f20-8319-4617-985b-85009797825e' class='xr-var-data-in' type='checkbox'><label for='data-b8ae8f20-8319-4617-985b-85009797825e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-8e68face-c215-4844-8bdb-ff0bb7a46b01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e68face-c215-4844-8bdb-ff0bb7a46b01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efdc1942-a91a-43b2-9f75-809885fa230f' class='xr-var-data-in' type='checkbox'><label for='data-efdc1942-a91a-43b2-9f75-809885fa230f' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-80d6dc4a-8264-4dc7-ae46-be4c67154b34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80d6dc4a-8264-4dc7-ae46-be4c67154b34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-062c9a4f-e072-42e5-ae84-c6be905eed87' class='xr-var-data-in' type='checkbox'><label for='data-062c9a4f-e072-42e5-ae84-c6be905eed87' 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-ee921148-0f95-406e-a136-ca4b39ab5f3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee921148-0f95-406e-a136-ca4b39ab5f3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f66cf61e-a451-40b5-af02-bac98571d285' class='xr-var-data-in' type='checkbox'><label for='data-f66cf61e-a451-40b5-af02-bac98571d285' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3e7c7540-b4fe-4645-9556-dd771f8d9a40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e7c7540-b4fe-4645-9556-dd771f8d9a40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f36a5183-1a4c-4ef3-af12-3ec78959ce94' class='xr-var-data-in' type='checkbox'><label for='data-f36a5183-1a4c-4ef3-af12-3ec78959ce94' 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>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-023ef750-1615-47b0-8815-2f1a7d26ba13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-023ef750-1615-47b0-8815-2f1a7d26ba13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20970197-eb29-4792-bde9-887d120ba3de' class='xr-var-data-in' type='checkbox'><label for='data-20970197-eb29-4792-bde9-887d120ba3de' 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>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-22696727-e324-447b-a0cf-dea4b4939d7d' class='xr-section-summary-in' type='checkbox'  ><label for='section-22696727-e324-447b-a0cf-dea4b4939d7d' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-9799948b-8231-4e11-b977-ecc91599822f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9799948b-8231-4e11-b977-ecc91599822f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-125a477a-4d0b-4041-bdf7-3ac70828f2a0' class='xr-var-data-in' type='checkbox'><label for='data-125a477a-4d0b-4041-bdf7-3ac70828f2a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-c66b2dae-7154-4b6a-8f6a-de0893948522' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c66b2dae-7154-4b6a-8f6a-de0893948522' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdf3f8b5-d763-47bf-8895-b2d991f0e496' class='xr-var-data-in' type='checkbox'><label for='data-cdf3f8b5-d763-47bf-8895-b2d991f0e496' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-0dcb711a-233d-4d76-8c93-74ef9852272b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0dcb711a-233d-4d76-8c93-74ef9852272b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e38a941-9d7f-4e9d-98b0-56fc131d287d' class='xr-var-data-in' type='checkbox'><label for='data-8e38a941-9d7f-4e9d-98b0-56fc131d287d' 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-94914321-a11e-4e2a-93ed-d39cda9a12da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94914321-a11e-4e2a-93ed-d39cda9a12da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b247396-6302-4268-a629-e7f9fbd7d264' class='xr-var-data-in' type='checkbox'><label for='data-2b247396-6302-4268-a629-e7f9fbd7d264' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
        "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
        "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-f61153c7-a8c9-4a99-833c-0c1f7367ed64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f61153c7-a8c9-4a99-833c-0c1f7367ed64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a1f674f-9c3a-4e09-9208-19fd189c7eaf' class='xr-var-data-in' type='checkbox'><label for='data-1a1f674f-9c3a-4e09-9208-19fd189c7eaf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-3e99a1ed-e30c-426e-bf9b-2b2b86456574' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e99a1ed-e30c-426e-bf9b-2b2b86456574' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8be2a7c-3c84-44b0-98a4-eb3627fd00a1' class='xr-var-data-in' type='checkbox'><label for='data-c8be2a7c-3c84-44b0-98a4-eb3627fd00a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
        "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
        "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
        "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
        "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
-       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-37d96910-d68a-40e5-b4e8-cf25cd374c32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37d96910-d68a-40e5-b4e8-cf25cd374c32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae23decb-a928-4da3-aa1d-d530fe683244' class='xr-var-data-in' type='checkbox'><label for='data-ae23decb-a928-4da3-aa1d-d530fe683244' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-7080d368-46e9-4eb5-ab60-697c3e60de23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7080d368-46e9-4eb5-ab60-697c3e60de23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69d5683f-aed1-45ff-9270-2422b43cf321' class='xr-var-data-in' type='checkbox'><label for='data-69d5683f-aed1-45ff-9270-2422b43cf321' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-1bf938ed-ac88-41b8-a99b-261ced2eaa54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bf938ed-ac88-41b8-a99b-261ced2eaa54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a2cd2a5-2081-4d54-bbd7-8a8d3c26afa2' class='xr-var-data-in' type='checkbox'><label for='data-3a2cd2a5-2081-4d54-bbd7-8a8d3c26afa2' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-fa745711-ca3e-47f2-941c-5fbb9a97693a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa745711-ca3e-47f2-941c-5fbb9a97693a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af6d0f97-26f8-4c8a-b8b8-7d96d0c6d4e6' class='xr-var-data-in' type='checkbox'><label for='data-af6d0f97-26f8-4c8a-b8b8-7d96d0c6d4e6' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-9ccd310e-24b0-416e-a4b0-48106a7eb37c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ccd310e-24b0-416e-a4b0-48106a7eb37c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8885968a-f639-4bd3-87e4-7c439056642a' class='xr-var-data-in' type='checkbox'><label for='data-8885968a-f639-4bd3-87e4-7c439056642a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-8ad86f8b-8661-44d5-974d-21ab5bf46ee9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ad86f8b-8661-44d5-974d-21ab5bf46ee9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b727184b-12f4-4bc4-b754-fbb63f8972b9' class='xr-var-data-in' type='checkbox'><label for='data-b727184b-12f4-4bc4-b754-fbb63f8972b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-bb53204d-f9b3-4da2-8250-5dade7d0a2a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb53204d-f9b3-4da2-8250-5dade7d0a2a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f15c617-2b4d-4647-90fc-b10f0385678a' class='xr-var-data-in' type='checkbox'><label for='data-1f15c617-2b4d-4647-90fc-b10f0385678a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-1f74491f-6470-42d6-b9f4-da6170cd0c3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f74491f-6470-42d6-b9f4-da6170cd0c3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b86c8ddc-2a20-405a-a911-c44a77521e77' class='xr-var-data-in' type='checkbox'><label for='data-b86c8ddc-2a20-405a-a911-c44a77521e77' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-ea110f04-6604-48ce-aa37-3ef4995b5a7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea110f04-6604-48ce-aa37-3ef4995b5a7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffa5fa07-c95e-4ccd-b060-faa94c3d72d2' class='xr-var-data-in' type='checkbox'><label for='data-ffa5fa07-c95e-4ccd-b060-faa94c3d72d2' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-a1637cc4-6e6a-4176-829a-ddb0be9669d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1637cc4-6e6a-4176-829a-ddb0be9669d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26d19708-761f-47cf-81b4-ac76c7459731' class='xr-var-data-in' type='checkbox'><label for='data-26d19708-761f-47cf-81b4-ac76c7459731' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-31feafb8-a06b-434c-8b1a-5fa317082e6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31feafb8-a06b-434c-8b1a-5fa317082e6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e846b8b8-0e31-4fae-9d7d-056c8723a7aa' class='xr-var-data-in' type='checkbox'><label for='data-e846b8b8-0e31-4fae-9d7d-056c8723a7aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-ae5ea8d3-341e-4df0-830e-03221ffeeeeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae5ea8d3-341e-4df0-830e-03221ffeeeeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ebe0237-f83c-4dc7-a684-18b18eeb0ba3' class='xr-var-data-in' type='checkbox'><label for='data-3ebe0237-f83c-4dc7-a684-18b18eeb0ba3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
        "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
        "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
        "        ...,\n",
@@ -560,7 +561,7 @@
        "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
        "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
        "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-8913578d-5ecf-4c8b-a4ab-919aac213176' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8913578d-5ecf-4c8b-a4ab-919aac213176' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a223e247-8c61-453d-bc75-aff03c6b336d' class='xr-var-data-in' type='checkbox'><label for='data-a223e247-8c61-453d-bc75-aff03c6b336d' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-7bbd1c06-7f8c-408a-acae-265e5db9a770' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bbd1c06-7f8c-408a-acae-265e5db9a770' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94892884-cb11-4c15-ac2c-36a7aac52a45' class='xr-var-data-in' type='checkbox'><label for='data-94892884-cb11-4c15-ac2c-36a7aac52a45' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
        "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
        "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
        "        ...,\n",
@@ -590,7 +591,7 @@
        "        ...,\n",
        "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
        "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
-       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-24d83e28-3e82-4248-8366-0cb33af2a425' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24d83e28-3e82-4248-8366-0cb33af2a425' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1612972-0a4d-4266-bc10-0b63b4fb4588' class='xr-var-data-in' type='checkbox'><label for='data-a1612972-0a4d-4266-bc10-0b63b4fb4588' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-3a788d16-1b79-47b0-bc08-f34666d72729' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a788d16-1b79-47b0-bc08-f34666d72729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-557503a5-d74a-45c4-befb-23801b61b0a2' class='xr-var-data-in' type='checkbox'><label for='data-557503a5-d74a-45c4-befb-23801b61b0a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
        "        [ 74,  92,  96, ..., 100,  97, 100],\n",
        "        [100, 100,  99, ...,  99, 100, 100],\n",
        "        ...,\n",
@@ -620,7 +621,7 @@
        "        ...,\n",
        "        [100,  99,  96, ...,  98, 100, 100],\n",
        "        [100, 100, 100, ...,  94,  93,  95],\n",
-       "        [100,  98,  99, ...,  98,  98,  96]]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-b629947a-346f-45a2-81e1-83f14fbc29f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b629947a-346f-45a2-81e1-83f14fbc29f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f3dc533-87ca-4a2b-9219-11a850667c88' class='xr-var-data-in' type='checkbox'><label for='data-4f3dc533-87ca-4a2b-9219-11a850667c88' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+       "        [100,  98,  99, ...,  98,  98,  96]]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-d3614c88-e21b-4da7-8cc9-776a97d1bdbd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3614c88-e21b-4da7-8cc9-776a97d1bdbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80296778-6075-4d98-aaa5-315d4e68e1b2' class='xr-var-data-in' type='checkbox'><label for='data-80296778-6075-4d98-aaa5-315d4e68e1b2' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
        "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
        "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
        "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
@@ -640,47 +641,47 @@
        "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
        "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
        "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-9f1fa606-4197-41ac-9c9f-93abe23a38ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f1fa606-4197-41ac-9c9f-93abe23a38ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd1678d4-0bd1-40c4-a9c2-1f124a45b452' class='xr-var-data-in' type='checkbox'><label for='data-cd1678d4-0bd1-40c4-a9c2-1f124a45b452' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-24652fb5-52d1-4311-a4e8-551af06f5808' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24652fb5-52d1-4311-a4e8-551af06f5808' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5636b34-5302-489a-a86c-a527a39f4beb' class='xr-var-data-in' type='checkbox'><label for='data-c5636b34-5302-489a-a86c-a527a39f4beb' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
        "        -0.00292969, -0.00195312],\n",
        "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
        "         0.00097656,  0.00097656],\n",
        "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00195312, -0.00292969]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-2484dd10-042b-41f4-8553-6570528df331' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2484dd10-042b-41f4-8553-6570528df331' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24f81c1b-bdff-44b4-b3d3-6fa59d1c0953' class='xr-var-data-in' type='checkbox'><label for='data-24f81c1b-bdff-44b4-b3d3-6fa59d1c0953' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+       "        -0.00195312, -0.00292969]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-02a61a2b-5adc-4065-ad35-ed52f6737943' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02a61a2b-5adc-4065-ad35-ed52f6737943' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d69e369f-ba34-4b70-94de-85d58f796f85' class='xr-var-data-in' type='checkbox'><label for='data-d69e369f-ba34-4b70-94de-85d58f796f85' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
        "         0.6247864 ,  0.62490845],\n",
        "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
        "        -0.03564453, -0.03561401],\n",
        "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
        "        -0.04360962, -0.04360962],\n",
        "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-65afec1f-eb31-4415-b0f7-9069a533ab06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65afec1f-eb31-4415-b0f7-9069a533ab06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56576752-97a4-4d5c-b005-3e098e245c16' class='xr-var-data-in' type='checkbox'><label for='data-56576752-97a4-4d5c-b005-3e098e245c16' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-2e9042b5-f862-4163-a045-7388f0cf8be5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e9042b5-f862-4163-a045-7388f0cf8be5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf3c786f-d6ee-44b9-bb68-1966af29114f' class='xr-var-data-in' type='checkbox'><label for='data-bf3c786f-d6ee-44b9-bb68-1966af29114f' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-93e0830b-be4a-412b-92b2-f3deec50e3be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93e0830b-be4a-412b-92b2-f3deec50e3be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c8c4c0b-e215-4b59-8c8a-289d242c27f0' class='xr-var-data-in' type='checkbox'><label for='data-8c8c4c0b-e215-4b59-8c8a-289d242c27f0' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-a4f82b39-0196-482e-a658-a0bce674365c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4f82b39-0196-482e-a658-a0bce674365c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-787e868c-a11f-4987-aca2-98c9f01bfaf2' class='xr-var-data-in' type='checkbox'><label for='data-787e868c-a11f-4987-aca2-98c9f01bfaf2' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-b5870ca8-1627-4fba-ad85-1319d049e96a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5870ca8-1627-4fba-ad85-1319d049e96a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3f8ac23-5b90-4335-8c74-2ef2e5e00d95' class='xr-var-data-in' type='checkbox'><label for='data-c3f8ac23-5b90-4335-8c74-2ef2e5e00d95' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-bd053d6a-787f-419f-9d99-5c074a8366b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd053d6a-787f-419f-9d99-5c074a8366b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-666f1ba3-d496-46b0-a418-54ea78205445' class='xr-var-data-in' type='checkbox'><label for='data-666f1ba3-d496-46b0-a418-54ea78205445' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
        "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
        "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-af4d2c4f-29ea-4411-8e4c-cbe056336931' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af4d2c4f-29ea-4411-8e4c-cbe056336931' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec831b6e-a267-4d8e-a786-219e2dd916d1' class='xr-var-data-in' type='checkbox'><label for='data-ec831b6e-a267-4d8e-a786-219e2dd916d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-31606597-e80f-42da-983e-b49dc6f4f10c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31606597-e80f-42da-983e-b49dc6f4f10c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35451ac-d6a0-4027-a077-d7a3d8907066' class='xr-var-data-in' type='checkbox'><label for='data-b35451ac-d6a0-4027-a077-d7a3d8907066' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
        "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
        "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
        "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
        "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
-       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-c446acd1-db44-440e-8f49-dfa6088ae462' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c446acd1-db44-440e-8f49-dfa6088ae462' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b860357b-9137-4e48-bc54-5dc44aea788e' class='xr-var-data-in' type='checkbox'><label for='data-b860357b-9137-4e48-bc54-5dc44aea788e' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-111070cb-840f-40dd-8fc9-26c59d53d0be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-111070cb-840f-40dd-8fc9-26c59d53d0be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e848115-de5c-4aba-9264-5d25e800bdac' class='xr-var-data-in' type='checkbox'><label for='data-3e848115-de5c-4aba-9264-5d25e800bdac' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-55022d21-af3c-4bbc-8a7d-8ff6d16218b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55022d21-af3c-4bbc-8a7d-8ff6d16218b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb580410-4bcf-4b4f-967d-6fcf54ecd94b' class='xr-var-data-in' type='checkbox'><label for='data-fb580410-4bcf-4b4f-967d-6fcf54ecd94b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-a63f5811-90ee-4fbf-bd4e-6ca031f61b30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a63f5811-90ee-4fbf-bd4e-6ca031f61b30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2db8cf4-a4c4-4384-b017-f34b4881be16' class='xr-var-data-in' type='checkbox'><label for='data-a2db8cf4-a4c4-4384-b017-f34b4881be16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-93b1d74f-5cdd-4016-8020-0c3c08682b12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93b1d74f-5cdd-4016-8020-0c3c08682b12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e82c03bc-f11e-476b-9c11-7a851561eec9' class='xr-var-data-in' type='checkbox'><label for='data-e82c03bc-f11e-476b-9c11-7a851561eec9' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-be82150a-6d3e-4dc9-824a-f388648baeb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be82150a-6d3e-4dc9-824a-f388648baeb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-022ebb33-10ad-4920-8b32-29de14c65f5c' class='xr-var-data-in' type='checkbox'><label for='data-022ebb33-10ad-4920-8b32-29de14c65f5c' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-6bab972c-9546-4c29-9ad8-d74013cdea27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bab972c-9546-4c29-9ad8-d74013cdea27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21714e6d-842d-4024-8c88-d8bd39e896ae' class='xr-var-data-in' type='checkbox'><label for='data-21714e6d-842d-4024-8c88-d8bd39e896ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-f7b69d25-5e03-46b3-8088-c62b0a53e0ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7b69d25-5e03-46b3-8088-c62b0a53e0ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6771dd73-8b46-403f-b33b-8d27538b917f' class='xr-var-data-in' type='checkbox'><label for='data-6771dd73-8b46-403f-b33b-8d27538b917f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
        "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
        "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
        "       ...,\n",
        "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
        "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
        "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-710992c2-912a-4523-83e2-5c0eeb7ca8ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-710992c2-912a-4523-83e2-5c0eeb7ca8ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3544cdc1-2e2d-451f-8a90-a6b2dc2460f3' class='xr-var-data-in' type='checkbox'><label for='data-3544cdc1-2e2d-451f-8a90-a6b2dc2460f3' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-b3a3a9fa-3443-414e-a3b7-4b975dea63bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3a3a9fa-3443-414e-a3b7-4b975dea63bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5652828-b6b4-4bc2-8b64-eb6d3f7e58c7' class='xr-var-data-in' type='checkbox'><label for='data-d5652828-b6b4-4bc2-8b64-eb6d3f7e58c7' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
        "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
        "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
        "       ...,\n",
        "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
        "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
-       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-4ec3e904-3ffe-4493-a94a-2729842b3337' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ec3e904-3ffe-4493-a94a-2729842b3337' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-650d7316-7453-495a-8a01-ee8340791796' class='xr-var-data-in' type='checkbox'><label for='data-650d7316-7453-495a-8a01-ee8340791796' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-daafecdd-60c3-409a-bf60-8aa046e7b0ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-daafecdd-60c3-409a-bf60-8aa046e7b0ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0b380e-9202-42f2-a2d6-8ab702301bd9' class='xr-var-data-in' type='checkbox'><label for='data-bf0b380e-9202-42f2-a2d6-8ab702301bd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
        "       [ 97,  94,  98, ...,  97,  95,  97],\n",
        "       [100, 100, 100, ...,  93, 100,  96],\n",
        "       ...,\n",
        "       [100, 100, 100, ..., 100, 100,  98],\n",
        "       [100, 100, 100, ...,  99, 100,  98],\n",
-       "       [100, 100, 100, ...,  99,  94, 100]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-4f5d3373-ad7f-4eeb-b6b0-e46314108206' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f5d3373-ad7f-4eeb-b6b0-e46314108206' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73bcee81-faa9-40cf-b629-27a0247bbc02' class='xr-var-data-in' type='checkbox'><label for='data-73bcee81-faa9-40cf-b629-27a0247bbc02' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+       "       [100, 100, 100, ...,  99,  94, 100]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-cfdf2fa5-cc12-4f58-9ebf-8fa153f65300' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfdf2fa5-cc12-4f58-9ebf-8fa153f65300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c820902d-039b-4b9b-927e-2cf8eb79b91d' class='xr-var-data-in' type='checkbox'><label for='data-c820902d-039b-4b9b-927e-2cf8eb79b91d' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
        "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
        "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
        "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
@@ -700,24 +701,24 @@
        "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
        "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
        "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-f8191cdc-149f-4017-8bd5-62c6a8a9099b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8191cdc-149f-4017-8bd5-62c6a8a9099b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26a98365-2024-4ee6-8702-0d5b646fe52a' class='xr-var-data-in' type='checkbox'><label for='data-26a98365-2024-4ee6-8702-0d5b646fe52a' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-b0d33004-4362-4dc4-a3dc-6c5fbd8e6419' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d33004-4362-4dc4-a3dc-6c5fbd8e6419' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bea08383-7fd1-400a-bef7-86632f8b77ac' class='xr-var-data-in' type='checkbox'><label for='data-bea08383-7fd1-400a-bef7-86632f8b77ac' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
        "        -0.00195312, -0.00390625],\n",
        "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
        "         0.        ,  0.00097656],\n",
        "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00292969, -0.00195312]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-b00ca89f-6816-4366-809c-5c5efbf52302' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b00ca89f-6816-4366-809c-5c5efbf52302' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8356dc84-a9a3-4217-8d90-e8b1bee7d970' class='xr-var-data-in' type='checkbox'><label for='data-8356dc84-a9a3-4217-8d90-e8b1bee7d970' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+       "        -0.00292969, -0.00195312]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-67c2cad4-6171-415b-9f18-59a5c00ad8ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67c2cad4-6171-415b-9f18-59a5c00ad8ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e85f4521-42d6-49a8-aa4b-86d42fb0d376' class='xr-var-data-in' type='checkbox'><label for='data-e85f4521-42d6-49a8-aa4b-86d42fb0d376' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
        "         0.6247864 ,  0.62490845],\n",
        "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
        "        -0.03564453, -0.03561401],\n",
        "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
        "        -0.04360962, -0.04360962],\n",
        "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-12e99f55-6fdc-43a2-a2c4-f920ae3da01a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12e99f55-6fdc-43a2-a2c4-f920ae3da01a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da45c4c0-877f-4d08-81d5-41165c00a9a6' class='xr-var-data-in' type='checkbox'><label for='data-da45c4c0-877f-4d08-81d5-41165c00a9a6' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-1ff58a4d-7b29-443f-bccf-b701f5a539aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ff58a4d-7b29-443f-bccf-b701f5a539aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58b50a4e-1982-46ae-93de-f41b914da088' class='xr-var-data-in' type='checkbox'><label for='data-58b50a4e-1982-46ae-93de-f41b914da088' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-25b0d6d6-0feb-4e0f-9cef-8013123b2129' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25b0d6d6-0feb-4e0f-9cef-8013123b2129' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87999965-8729-4541-a6c2-b12170ac4874' class='xr-var-data-in' type='checkbox'><label for='data-87999965-8729-4541-a6c2-b12170ac4874' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-ec566afd-483e-4d29-84bb-3290fbd2a332' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec566afd-483e-4d29-84bb-3290fbd2a332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60a3041b-c4ce-4551-ae18-5c865dd129f4' class='xr-var-data-in' type='checkbox'><label for='data-60a3041b-c4ce-4551-ae18-5c865dd129f4' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-bfe6c267-0d8c-41a8-a766-bd557ec04bb7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfe6c267-0d8c-41a8-a766-bd557ec04bb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a94c16a2-78d0-4ae3-b5f3-8163083cd2cf' class='xr-var-data-in' type='checkbox'><label for='data-a94c16a2-78d0-4ae3-b5f3-8163083cd2cf' 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, 0, 0, ..., 0, 0, 1], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-ef4c74ad-af5f-4eb8-a8b1-790ba0b6d42f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef4c74ad-af5f-4eb8-a8b1-790ba0b6d42f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eee33642-d268-4ac7-ac17-3acee333c060' class='xr-var-data-in' type='checkbox'><label for='data-eee33642-d268-4ac7-ac17-3acee333c060' 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-       "       -12.500001], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-c87e1be5-e407-4aa3-a65d-b79aa02d8ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c87e1be5-e407-4aa3-a65d-b79aa02d8ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aea0d5c-e331-4799-9230-0ec3832afa88' class='xr-var-data-in' type='checkbox'><label for='data-7aea0d5c-e331-4799-9230-0ec3832afa88' 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-74a4bf50-c130-404e-83a5-2ce6187f8080' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74a4bf50-c130-404e-83a5-2ce6187f8080' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-695895e9-a1d4-4e87-8ad5-ae63044601a7' class='xr-var-data-in' type='checkbox'><label for='data-695895e9-a1d4-4e87-8ad5-ae63044601a7' 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-       "       -6.45     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-2323224d-c148-4d59-93a1-d2187ca15981' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2323224d-c148-4d59-93a1-d2187ca15981' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fafabb4-b619-4f63-b3dc-e232015f321f' class='xr-var-data-in' type='checkbox'><label for='data-3fafabb4-b619-4f63-b3dc-e232015f321f' 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>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-548187fa-c159-424c-895a-d6929abe60f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-548187fa-c159-424c-895a-d6929abe60f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d1f734f-d4cd-4a44-9025-b010eaa795fd' class='xr-var-data-in' type='checkbox'><label for='data-7d1f734f-d4cd-4a44-9025-b010eaa795fd' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-537b58a0-2a60-4382-9b37-e5fe8c5b2071' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-537b58a0-2a60-4382-9b37-e5fe8c5b2071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-542e2915-cf07-47cc-ac85-5a4587bc63b1' class='xr-var-data-in' type='checkbox'><label for='data-542e2915-cf07-47cc-ac85-5a4587bc63b1' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-e24693a2-f2e7-4636-944e-5187cd2eb5c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e24693a2-f2e7-4636-944e-5187cd2eb5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d942e7d-941b-4663-8401-c881ae9c2333' class='xr-var-data-in' type='checkbox'><label for='data-8d942e7d-941b-4663-8401-c881ae9c2333' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-4464f765-d06f-44a2-a57f-07dfa9de6825' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4464f765-d06f-44a2-a57f-07dfa9de6825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04d1bc49-0e19-47d2-82b5-b8346d3f6fb8' class='xr-var-data-in' type='checkbox'><label for='data-04d1bc49-0e19-47d2-82b5-b8346d3f6fb8' 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, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-0c19ffd9-52d0-4474-bdc3-efdf7834f90a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c19ffd9-52d0-4474-bdc3-efdf7834f90a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4da2c31d-511f-4821-aafc-58ddcd51496f' class='xr-var-data-in' type='checkbox'><label for='data-4da2c31d-511f-4821-aafc-58ddcd51496f' 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, 0, 0, ..., 0, 0, 1], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-47165076-4109-4754-9d12-0299c5b69d04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47165076-4109-4754-9d12-0299c5b69d04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d2fe888-606c-4198-b5fb-272f79b036d7' class='xr-var-data-in' type='checkbox'><label for='data-9d2fe888-606c-4198-b5fb-272f79b036d7' 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+       "       -12.500001], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-36348d5f-cbc6-4481-80e1-df26409123dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36348d5f-cbc6-4481-80e1-df26409123dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33829b96-45e5-46f9-a7f5-b72c54b46fa7' class='xr-var-data-in' type='checkbox'><label for='data-33829b96-45e5-46f9-a7f5-b72c54b46fa7' 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-ffc81d10-e5b6-4b24-a41d-46daca3237be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffc81d10-e5b6-4b24-a41d-46daca3237be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce5b0ff5-0131-4157-9878-085106a635aa' class='xr-var-data-in' type='checkbox'><label for='data-ce5b0ff5-0131-4157-9878-085106a635aa' 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+       "       -6.45     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-9bae6af3-7d73-4528-8711-252d28108b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bae6af3-7d73-4528-8711-252d28108b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-972a8d17-b1f9-43cc-93fe-54cb7542857a' class='xr-var-data-in' type='checkbox'><label for='data-972a8d17-b1f9-43cc-93fe-54cb7542857a' 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>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
        "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
        "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-88e5fa67-6dc6-4538-a5f6-a958cdbd52bd' class='xr-section-summary-in' type='checkbox'  ><label for='section-88e5fa67-6dc6-4538-a5f6-a958cdbd52bd' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;alt&quot;: false, &quot;alt_raw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;alt&quot;: false, &quot;alt_raw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
+       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5114684c-3013-4101-acba-b90d77a72c86' class='xr-section-summary-in' type='checkbox'  ><label for='section-5114684c-3013-4101-acba-b90d77a72c86' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -858,7 +859,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277cb323c40>"
+       "<matplotlib.collections.QuadMesh at 0x233ec6a68c0>"
       ]
      },
      "execution_count": 5,
@@ -867,7 +868,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1265,11 +1266,11 @@
        "Coordinates:\n",
        "  * range    (range) float64 1.2 1.7 2.2 2.7 3.2 ... 12.7 13.2 13.7 14.2 14.7\n",
        "Attributes:\n",
-       "    units:    m</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8a34c8e4-b5c8-4d5e-a7b9-f733f3fbee2e' class='xr-array-in' type='checkbox' checked><label for='section-8a34c8e4-b5c8-4d5e-a7b9-f733f3fbee2e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "    units:    m</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-337fe36a-e5b4-4ba7-80cd-f929edbfe174' class='xr-array-in' type='checkbox' checked><label for='section-337fe36a-e5b4-4ba7-80cd-f929edbfe174' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-30d87afc-f11b-485e-bccd-4f55a85f04ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30d87afc-f11b-485e-bccd-4f55a85f04ef' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-ced8d517-4f51-4d33-a33c-1a115fcb96b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ced8d517-4f51-4d33-a33c-1a115fcb96b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04430071-6165-4594-b9a7-849b9b68c608' class='xr-var-data-in' type='checkbox'><label for='data-04430071-6165-4594-b9a7-849b9b68c608' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-b402e24c-b79a-49fe-acec-c5345fac65fd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b402e24c-b79a-49fe-acec-c5345fac65fd' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-65fe5f28-3925-45c7-a9b3-151ec63c70f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65fe5f28-3925-45c7-a9b3-151ec63c70f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1975dfb-4d16-4498-b12c-8cda28a55303' class='xr-var-data-in' type='checkbox'><label for='data-b1975dfb-4d16-4498-b12c-8cda28a55303' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d24f3cc1-38ab-45ad-858f-e68892bc294d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d24f3cc1-38ab-45ad-858f-e68892bc294d' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div></li></ul></div></div>"
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7d1962d-4904-4e43-9889-d0afd4b9e957' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7d1962d-4904-4e43-9889-d0afd4b9e957' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'range' (range: 28)>\n",
@@ -1323,7 +1324,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277cb623d60>"
+       "<matplotlib.collections.QuadMesh at 0x233ed9aab90>"
       ]
      },
      "execution_count": 9,
@@ -1332,7 +1333,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1367,7 +1368,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277cb215f10>"
+       "<matplotlib.collections.QuadMesh at 0x233818d3b80>"
       ]
      },
      "execution_count": 10,
@@ -1376,7 +1377,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1417,7 +1418,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277cd148b20>"
+       "<matplotlib.collections.QuadMesh at 0x233819ec820>"
       ]
      },
      "execution_count": 12,
@@ -1426,7 +1427,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1918,7 +1919,7 @@
        "    h_deploy:                  0.6\n",
        "    declination:               15.8\n",
        "    declination_in_orientmat:  1\n",
-       "    principal_heading:         11.1898</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-8af22c64-cd6c-4d66-8b95-9bc5b8bc54ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8af22c64-cd6c-4d66-8b95-9bc5b8bc54ca' 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'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9c348034-ad79-497a-9aff-319f7bd8f6f7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9c348034-ad79-497a-9aff-319f7bd8f6f7' class='xr-section-summary' >Coordinates: <span>(10)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-fc860f03-0190-4b21-b235-d6283bafc502' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fc860f03-0190-4b21-b235-d6283bafc502' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1927c724-267c-4d9c-bdb5-f54cae03b70b' class='xr-var-data-in' type='checkbox'><label for='data-1927c724-267c-4d9c-bdb5-f54cae03b70b' 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;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
+       "    principal_heading:         11.1898</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-133252a1-db9d-47dd-80c3-81e2200ee809' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-133252a1-db9d-47dd-80c3-81e2200ee809' 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'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a5369a3a-1b94-4ce3-b004-3a65374af772' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a5369a3a-1b94-4ce3-b004-3a65374af772' class='xr-section-summary' >Coordinates: <span>(10)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-fdb41928-5f1e-46c5-9914-04780672f479' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fdb41928-5f1e-46c5-9914-04780672f479' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97e5eae9-6bb6-403f-b064-5b736648b9b7' class='xr-var-data-in' type='checkbox'><label for='data-97e5eae9-6bb6-403f-b064-5b736648b9b7' 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;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
        "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
        "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
        "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
@@ -2009,9 +2010,9 @@
        "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
        "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
        "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-5853e6ef-fdba-4466-bcda-8a951cda1eea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5853e6ef-fdba-4466-bcda-8a951cda1eea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebe717f8-1c35-4ed6-a1df-f3c5cef11df0' class='xr-var-data-in' type='checkbox'><label for='data-ebe717f8-1c35-4ed6-a1df-f3c5cef11df0' 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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-2c660bc7-0f27-4c2b-af76-ea6ad256e316' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c660bc7-0f27-4c2b-af76-ea6ad256e316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bc571a5-734f-4bc5-8592-84b186b91b5b' class='xr-var-data-in' type='checkbox'><label for='data-9bc571a5-734f-4bc5-8592-84b186b91b5b' 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([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-630d41d2-a6a4-4ecf-a655-09aab3662274' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-630d41d2-a6a4-4ecf-a655-09aab3662274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e15396ca-0eb3-40ff-88c1-0db03e3534e1' class='xr-var-data-in' type='checkbox'><label for='data-e15396ca-0eb3-40ff-88c1-0db03e3534e1' 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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-9ff69c9e-aca5-4f4c-a5eb-13dab8872801' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ff69c9e-aca5-4f4c-a5eb-13dab8872801' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a77e00b-3ba3-458b-a60a-90ab42fdf783' class='xr-var-data-in' type='checkbox'><label for='data-7a77e00b-3ba3-458b-a60a-90ab42fdf783' 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([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-1b43c1be-d00d-4caf-85f4-274aa633bce9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b43c1be-d00d-4caf-85f4-274aa633bce9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa99c7cb-1564-43d0-8e35-58865cd4056c' class='xr-var-data-in' type='checkbox'><label for='data-fa99c7cb-1564-43d0-8e35-58865cd4056c' 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;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-fbecdd19-7043-4403-b921-4f2c76f86628' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbecdd19-7043-4403-b921-4f2c76f86628' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb508707-9e17-4cc5-8260-4d03e23a53e8' class='xr-var-data-in' type='checkbox'><label for='data-bb508707-9e17-4cc5-8260-4d03e23a53e8' 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([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-2d5c1ec9-b859-4a50-9543-fc228fb1737a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2d5c1ec9-b859-4a50-9543-fc228fb1737a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f24b857f-39dc-42aa-bb6e-d50e7a883046' class='xr-var-data-in' type='checkbox'><label for='data-f24b857f-39dc-42aa-bb6e-d50e7a883046' 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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-5a5e13b3-dd72-4070-af73-dcfb6180684b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a5e13b3-dd72-4070-af73-dcfb6180684b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a812d9d3-ede4-4a34-ac67-fa740d3d0053' class='xr-var-data-in' type='checkbox'><label for='data-a812d9d3-ede4-4a34-ac67-fa740d3d0053' 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;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-9ef4d8d4-89ef-49d6-b776-5a125d5c5176' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ef4d8d4-89ef-49d6-b776-5a125d5c5176' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e409c010-d633-4525-8d76-d4845ae3bfd7' class='xr-var-data-in' type='checkbox'><label for='data-e409c010-d633-4525-8d76-d4845ae3bfd7' 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;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-2a8b8577-c8ea-407d-8514-f9af32be27da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a8b8577-c8ea-407d-8514-f9af32be27da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eb1bbce-a831-4241-9001-2eee62d0e49c' class='xr-var-data-in' type='checkbox'><label for='data-5eb1bbce-a831-4241-9001-2eee62d0e49c' 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;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-2acb6330-5418-4cd4-be5b-fe9d29e57a29' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acb6330-5418-4cd4-be5b-fe9d29e57a29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3536fa4-69ed-4ef4-b24e-41c1865b0c67' class='xr-var-data-in' type='checkbox'><label for='data-a3536fa4-69ed-4ef4-b24e-41c1865b0c67' 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;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-223045f9-f93d-4c22-8fc4-390d06fd70e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-223045f9-f93d-4c22-8fc4-390d06fd70e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc01cac6-4b47-48c6-ac17-63573baa177a' class='xr-var-data-in' type='checkbox'><label for='data-bc01cac6-4b47-48c6-ac17-63573baa177a' 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([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-dfa06d5c-96d9-4ccd-805f-daae54a85c00' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfa06d5c-96d9-4ccd-805f-daae54a85c00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05673cc4-d554-461e-805c-8bef3272b725' class='xr-var-data-in' type='checkbox'><label for='data-05673cc4-d554-461e-805c-8bef3272b725' 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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-0423372a-10e9-4759-9828-9388c895160e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0423372a-10e9-4759-9828-9388c895160e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-563998dd-52ec-473c-a653-f49cf371ddf4' class='xr-var-data-in' type='checkbox'><label for='data-563998dd-52ec-473c-a653-f49cf371ddf4' 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;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-4a0ba938-b3b3-4f65-b0d7-6efecdb8a972' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a0ba938-b3b3-4f65-b0d7-6efecdb8a972' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1660104-f5c2-4a82-8d04-3e28913408ee' class='xr-var-data-in' type='checkbox'><label for='data-f1660104-f5c2-4a82-8d04-3e28913408ee' 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;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-3140f7f1-be97-4592-a853-cdef163c4a62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3140f7f1-be97-4592-a853-cdef163c4a62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26835414-a4d0-49d6-b9a2-82aec4a3bd42' class='xr-var-data-in' type='checkbox'><label for='data-26835414-a4d0-49d6-b9a2-82aec4a3bd42' 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;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
        "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
        "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
        "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
@@ -2102,9 +2103,9 @@
        "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
        "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
        "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-96819b38-4617-428c-8493-4969341e9611' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96819b38-4617-428c-8493-4969341e9611' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1bb90a8b-0cb0-443d-b5c7-ab47c0b82bc3' class='xr-var-data-in' type='checkbox'><label for='data-1bb90a8b-0cb0-443d-b5c7-ab47c0b82bc3' 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([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-df7f4375-55de-4281-ae37-b213609a5c10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df7f4375-55de-4281-ae37-b213609a5c10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0980afa7-8f1b-4f62-b1c2-d658bfd89b6d' class='xr-var-data-in' type='checkbox'><label for='data-0980afa7-8f1b-4f62-b1c2-d658bfd89b6d' 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([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d226fb89-2f73-4f70-9fea-65a05a1eb6a9' class='xr-section-summary-in' type='checkbox'  ><label for='section-d226fb89-2f73-4f70-9fea-65a05a1eb6a9' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-31544dcc-68d9-4eb7-9800-ffd4b78045e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31544dcc-68d9-4eb7-9800-ffd4b78045e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90ce2268-d34b-48b0-b8a6-2c018fa2915a' class='xr-var-data-in' type='checkbox'><label for='data-90ce2268-d34b-48b0-b8a6-2c018fa2915a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-38ce552b-2d5d-4e63-af27-e6f81fcf524f' class='xr-section-summary-in' type='checkbox'  ><label for='section-38ce552b-2d5d-4e63-af27-e6f81fcf524f' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-594a5249-7a80-4e54-9145-2b86c7b2566e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-594a5249-7a80-4e54-9145-2b86c7b2566e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7d4124f-3c9c-4cd0-8064-fa2153cb7c8e' class='xr-var-data-in' type='checkbox'><label for='data-c7d4124f-3c9c-4cd0-8064-fa2153cb7c8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
        "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
        "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
        "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
@@ -2134,9 +2135,9 @@
        "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
        "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
        "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
-       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-2c909705-a921-49c6-b39d-6ce994acbcaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c909705-a921-49c6-b39d-6ce994acbcaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0edabdfa-0765-44e1-a873-0c76e4efdb30' class='xr-var-data-in' type='checkbox'><label for='data-0edabdfa-0765-44e1-a873-0c76e4efdb30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380287, 0.04201568,\n",
+       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-6e725727-8910-4037-bb72-52c44c616a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e725727-8910-4037-bb72-52c44c616a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-688e6457-2f22-43fa-b23e-fdb786dd000b' class='xr-var-data-in' type='checkbox'><label for='data-688e6457-2f22-43fa-b23e-fdb786dd000b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380287, 0.04201568,\n",
        "        0.0463443 ],\n",
-       "       [0.04002878, 0.04084467, 0.03949426, ..., 0.04000184, 0.04028782,\n",
+       "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
        "        0.03873245],\n",
        "       [0.04025545, 0.03514179, 0.04270847, ..., 0.0391249 , 0.03997382,\n",
        "        0.04237254],\n",
@@ -2146,7 +2147,7 @@
        "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
        "               nan],\n",
        "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-       "               nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-18d86a6c-b872-4fce-be97-5ae524d9ec3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18d86a6c-b872-4fce-be97-5ae524d9ec3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-156cf57a-04a2-4da5-a7cc-9d1138be6430' class='xr-var-data-in' type='checkbox'><label for='data-156cf57a-04a2-4da5-a7cc-9d1138be6430' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
+       "               nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-b2ece7b5-2dfe-43ef-a7dd-faa61ebdae67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2ece7b5-2dfe-43ef-a7dd-faa61ebdae67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ea1821-c8c5-4ac0-8d49-1f7e286475a0' class='xr-var-data-in' type='checkbox'><label for='data-66ea1821-c8c5-4ac0-8d49-1f7e286475a0' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
        "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
        "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
        "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
@@ -2182,7 +2183,7 @@
        "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
        "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
        "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
-       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-da205975-4f3d-4d63-811d-59e0120ff71b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da205975-4f3d-4d63-811d-59e0120ff71b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-019ee291-fd15-444b-8be5-1b714282dbea' class='xr-var-data-in' type='checkbox'><label for='data-019ee291-fd15-444b-8be5-1b714282dbea' 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
+       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-bfe04067-aa5a-44ca-ad05-697740086330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe04067-aa5a-44ca-ad05-697740086330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c50795c-9d1f-4adb-af9d-b3f5d569be74' class='xr-var-data-in' type='checkbox'><label for='data-1c50795c-9d1f-4adb-af9d-b3f5d569be74' 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
        "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
        "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
        "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
@@ -2212,7 +2213,7 @@
        "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
        "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
        "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
-       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.37 72.4 72.38 ... -197.1 -197.1</div><input id='attrs-b6e18459-9f1a-4917-b1e9-35b99f66c371' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6e18459-9f1a-4917-b1e9-35b99f66c371' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30f5e308-252a-4b1f-b031-98f2a1206115' class='xr-var-data-in' type='checkbox'><label for='data-30f5e308-252a-4b1f-b031-98f2a1206115' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.37276  ,   72.39944  ,   72.379776 ,   72.385994 ,\n",
+       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.37 72.4 72.38 ... -197.1 -197.1</div><input id='attrs-7bac8a1b-bdfb-4301-8aa8-b554031cff64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bac8a1b-bdfb-4301-8aa8-b554031cff64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-665fea40-a1e1-4443-a8b5-63cb277fd624' class='xr-var-data-in' type='checkbox'><label for='data-665fea40-a1e1-4443-a8b5-63cb277fd624' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.37276  ,   72.39944  ,   72.379776 ,   72.385994 ,\n",
        "          72.37942  ,   72.413605 ,   72.43177  ,   72.45011  ,\n",
        "          72.497116 ,   72.43014  ,   72.43194  ,   72.453735 ,\n",
        "          72.393135 ,   72.4087   ,   72.404724 ,   72.42861  ,\n",
@@ -2252,7 +2253,7 @@
        "        -197.08583  , -197.11584  , -197.09117  , -197.04416  ,\n",
        "        -197.06387  , -197.09052  , -197.1295   , -197.00752  ,\n",
        "        -197.01785  , -197.01918  , -197.12917  , -197.05185  ,\n",
-       "        -197.11319  , -197.1045   , -197.05385  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3584 -0.361 ... 9.714 9.712</div><input id='attrs-b2de9ca3-cadf-4a66-83ec-cd976cbb3423' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2de9ca3-cadf-4a66-83ec-cd976cbb3423' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-511d68e2-0ac3-4a63-935a-809299f3f858' class='xr-var-data-in' type='checkbox'><label for='data-511d68e2-0ac3-4a63-935a-809299f3f858' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.3583813 , -0.36095354, -0.3586304 , -0.3615403 , -0.35910898,\n",
+       "        -197.11319  , -197.1045   , -197.05385  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3584 -0.361 ... 9.714 9.712</div><input id='attrs-0511766b-a9a7-49b5-805e-491eb3a60a64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0511766b-a9a7-49b5-805e-491eb3a60a64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48fda031-3b8e-46ab-84bc-e605d29176a6' class='xr-var-data-in' type='checkbox'><label for='data-48fda031-3b8e-46ab-84bc-e605d29176a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.3583813 , -0.36095354, -0.3586304 , -0.3615403 , -0.35910898,\n",
        "        -0.36007115, -0.36138585, -0.36137566, -0.36312702, -0.3628571 ,\n",
        "        -0.36111298, -0.35912383, -0.35871395, -0.35686025, -0.35600632,\n",
        "        -0.3580915 , -0.35734007, -0.35655504, -0.35646495, -0.35440227,\n",
@@ -2292,7 +2293,7 @@
        "         9.714537  ,  9.71484   ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
        "         9.715718  ,  9.711742  ,  9.710465  ,  9.712621  ,  9.713371  ,\n",
        "         9.715622  ,  9.71599   ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
-       "         9.712365  ,  9.7141695 ,  9.711615  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-65ce808a-dc0e-4bad-99b4-de10f386d5fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65ce808a-dc0e-4bad-99b4-de10f386d5fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2375a7be-67df-44bc-9651-e1ffa2dd2174' class='xr-var-data-in' type='checkbox'><label for='data-2375a7be-67df-44bc-9651-e1ffa2dd2174' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
+       "         9.712365  ,  9.7141695 ,  9.711615  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-d04dba24-8113-408c-9da0-f431c3c9941b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d04dba24-8113-408c-9da0-f431c3c9941b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfb5c49a-80a7-4ec2-94fb-f2fe6ef00ccd' class='xr-var-data-in' type='checkbox'><label for='data-bfb5c49a-80a7-4ec2-94fb-f2fe6ef00ccd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
        "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
        "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
        "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
@@ -2322,7 +2323,7 @@
        "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
        "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
        "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
-       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-b8dda7ff-cf62-439b-94b8-8f9da58dce9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8dda7ff-cf62-439b-94b8-8f9da58dce9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bf0c2ee-fc5f-4070-b65d-9c7f19363942' class='xr-var-data-in' type='checkbox'><label for='data-6bf0c2ee-fc5f-4070-b65d-9c7f19363942' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
+       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-591e10df-84b1-4914-84be-22f73c94bb87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-591e10df-84b1-4914-84be-22f73c94bb87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3daf7e3-e4e8-4ab1-8eeb-30463eb02ebd' class='xr-var-data-in' type='checkbox'><label for='data-f3daf7e3-e4e8-4ab1-8eeb-30463eb02ebd' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
        "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
        "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
        "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
@@ -2352,7 +2353,7 @@
        "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
        "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
        "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-136af0fe-a145-4d43-9496-e9088fcaff9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-136af0fe-a145-4d43-9496-e9088fcaff9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e78ea994-027c-460d-85a2-1c7ab28c7b42' class='xr-var-data-in' type='checkbox'><label for='data-e78ea994-027c-460d-85a2-1c7ab28c7b42' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-da80209a-8954-4229-bcf3-d43fb6717038' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da80209a-8954-4229-bcf3-d43fb6717038' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11467ab6-60d2-49cb-8a47-65bf192fc0eb' class='xr-var-data-in' type='checkbox'><label for='data-11467ab6-60d2-49cb-8a47-65bf192fc0eb' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2362,7 +2363,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-83d3919f-bf71-4137-8bcc-7c0fae06281f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83d3919f-bf71-4137-8bcc-7c0fae06281f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9166811-2252-46c4-ba31-92ebaa1658ce' class='xr-var-data-in' type='checkbox'><label for='data-b9166811-2252-46c4-ba31-92ebaa1658ce' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-25b24123-0764-4422-b108-8ffd07bc603c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25b24123-0764-4422-b108-8ffd07bc603c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2b21dc9-f732-4f21-8bc8-6da2252cf46e' class='xr-var-data-in' type='checkbox'><label for='data-e2b21dc9-f732-4f21-8bc8-6da2252cf46e' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2402,7 +2403,7 @@
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.02006 0.008163 ... nan nan</div><input id='attrs-1c8dd732-f3ee-48fb-bbf4-fe95efae947c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c8dd732-f3ee-48fb-bbf4-fe95efae947c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-209ae3dc-4c63-4a07-b03b-23312853445c' class='xr-var-data-in' type='checkbox'><label for='data-209ae3dc-4c63-4a07-b03b-23312853445c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.02006463,  0.00816293,  0.01909002, ..., -0.09305979,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.02006 0.008163 ... nan nan</div><input id='attrs-78e9ac18-eb45-415e-bedb-bb71f4ee7f24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78e9ac18-eb45-415e-bedb-bb71f4ee7f24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5273878d-ad39-4714-a056-e051f22c7dc2' class='xr-var-data-in' type='checkbox'><label for='data-5273878d-ad39-4714-a056-e051f22c7dc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.02006463,  0.00816293,  0.01909002, ..., -0.09305979,\n",
        "         -0.0984674 , -0.10511392],\n",
        "        [-0.01089326, -0.02103911, -0.00067545, ..., -0.11341628,\n",
        "         -0.11851331, -0.1263721 ],\n",
@@ -2442,7 +2443,7 @@
        "        [        nan,         nan,         nan, ...,         nan,\n",
        "                 nan,         nan],\n",
        "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-bf1682ab-ef66-4c6f-a6ff-4878dffd07f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf1682ab-ef66-4c6f-a6ff-4878dffd07f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34164c3b-179a-44a6-8c33-3cbf393aac4f' class='xr-var-data-in' type='checkbox'><label for='data-34164c3b-179a-44a6-8c33-3cbf393aac4f' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
+       "                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-75f7aac9-9789-4120-8400-6f22e4c4c6d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75f7aac9-9789-4120-8400-6f22e4c4c6d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f62c6d36-cbdb-432c-a16b-7f0cd9251f09' class='xr-var-data-in' type='checkbox'><label for='data-f62c6d36-cbdb-432c-a16b-7f0cd9251f09' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
        "         81.68667 ],\n",
        "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
        "         77.528336],\n",
@@ -2482,7 +2483,7 @@
        "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
        "               nan],\n",
        "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-7d67e1dc-4132-4c9b-bd78-93582048a520' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d67e1dc-4132-4c9b-bd78-93582048a520' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d061f202-58a4-4476-a846-f03a85d07078' class='xr-var-data-in' type='checkbox'><label for='data-d061f202-58a4-4476-a846-f03a85d07078' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
+       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-d427a1e2-1229-4dbd-ac10-7d4248a204df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d427a1e2-1229-4dbd-ac10-7d4248a204df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a49a2bdf-61ef-4b5e-9d0f-8ab28829e6bc' class='xr-var-data-in' type='checkbox'><label for='data-a49a2bdf-61ef-4b5e-9d0f-8ab28829e6bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
        "         92.06333 ],\n",
        "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
        "         96.03333 ],\n",
@@ -2522,7 +2523,7 @@
        "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
        "          0.      ],\n",
        "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-890922ba-1cd2-4e6d-9ca4-4bf5737d0c71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-890922ba-1cd2-4e6d-9ca4-4bf5737d0c71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ee5c392-4410-45c6-8fe6-1a7bb2c1d057' class='xr-var-data-in' type='checkbox'><label for='data-2ee5c392-4410-45c6-8fe6-1a7bb2c1d057' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.7431791e-02,  5.6972340e-02,  5.8299202e-02, ...,\n",
+       "          0.      ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-4a95fc5e-9df2-4d49-a008-4b98f9526876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a95fc5e-9df2-4d49-a008-4b98f9526876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-715a3c78-aa58-4742-95c4-63e8abc7b17a' class='xr-var-data-in' type='checkbox'><label for='data-715a3c78-aa58-4742-95c4-63e8abc7b17a' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.7431791e-02,  5.6972340e-02,  5.8299202e-02, ...,\n",
        "          5.8192708e-02,  5.8561362e-02,  5.8551285e-02],\n",
        "        [ 9.9830043e-01,  9.9832368e-01,  9.9824858e-01, ...,\n",
        "          9.9825412e-01,  9.9823499e-01,  9.9823463e-01],\n",
@@ -2541,7 +2542,7 @@
        "        [ 8.4546916e-03,  8.6972397e-03,  8.6324373e-03, ...,\n",
        "          7.3541482e-03,  7.3939036e-03,  7.3861168e-03],\n",
        "        [ 9.9162728e-01,  9.9160415e-01,  9.9164975e-01, ...,\n",
-       "          9.9366748e-01,  9.9369282e-01,  9.9368775e-01]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002153 -0.002034 ... -0.002598</div><input id='attrs-0f809383-08f1-4cda-a7a8-7ff1c6948862' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f809383-08f1-4cda-a7a8-7ff1c6948862' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9f7ea3e-907d-4ef3-923c-9c85fbb2dce0' class='xr-var-data-in' type='checkbox'><label for='data-d9f7ea3e-907d-4ef3-923c-9c85fbb2dce0' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00215301, -0.00203405, -0.00207394, -0.00210115, -0.00192078,\n",
+       "          9.9366748e-01,  9.9369282e-01,  9.9368775e-01]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002153 -0.002034 ... -0.002598</div><input id='attrs-c1a0b894-d766-46fb-9bdb-a009b9accc12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1a0b894-d766-46fb-9bdb-a009b9accc12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3984c3a-0894-4db8-be59-510d309977ff' class='xr-var-data-in' type='checkbox'><label for='data-a3984c3a-0894-4db8-be59-510d309977ff' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00215301, -0.00203405, -0.00207394, -0.00210115, -0.00192078,\n",
        "        -0.00193777, -0.00191335, -0.00199152, -0.00207278, -0.00194206,\n",
        "        -0.00204757, -0.00200068, -0.00199218, -0.00199336, -0.00199541,\n",
        "        -0.00195642, -0.002004  , -0.00198927, -0.00192089, -0.00190773,\n",
@@ -2581,7 +2582,7 @@
        "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
        "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
        "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
-       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-22fb1ddf-3e8c-49a4-9a40-19eda98af257' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22fb1ddf-3e8c-49a4-9a40-19eda98af257' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-663ab120-c4bd-47c0-8fa4-b3746ae06885' class='xr-var-data-in' type='checkbox'><label for='data-663ab120-c4bd-47c0-8fa4-b3746ae06885' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
+       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-92af0ff3-2e4f-4545-9408-0fd9f0f378f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92af0ff3-2e4f-4545-9408-0fd9f0f378f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da59470d-4141-4619-8c83-6b60c4266526' class='xr-var-data-in' type='checkbox'><label for='data-da59470d-4141-4619-8c83-6b60c4266526' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
        "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
        "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
        "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
@@ -2621,7 +2622,7 @@
        "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
        "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
        "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
-       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-fcac2c6f-8326-45e8-ad85-f3f2d16fe146' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcac2c6f-8326-45e8-ad85-f3f2d16fe146' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f80ab11c-8393-45eb-813d-b1ca5da2ab1f' class='xr-var-data-in' type='checkbox'><label for='data-f80ab11c-8393-45eb-813d-b1ca5da2ab1f' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
+       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-f2112aaf-b1ba-427f-a973-0372b70a8da7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2112aaf-b1ba-427f-a973-0372b70a8da7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46270ac4-1cdf-4244-b198-21f7918c1668' class='xr-var-data-in' type='checkbox'><label for='data-46270ac4-1cdf-4244-b198-21f7918c1668' 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
        "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
        "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
        "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
@@ -2657,7 +2658,7 @@
        "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
        "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
        "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-cb37cefc-eb29-40b9-a8bd-17784a3f6535' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb37cefc-eb29-40b9-a8bd-17784a3f6535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72a22a13-e0de-4e18-9514-02a5cef7cac0' class='xr-var-data-in' type='checkbox'><label for='data-72a22a13-e0de-4e18-9514-02a5cef7cac0' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
+       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-9bff76b7-855f-4c60-bc2e-bcee8046c900' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bff76b7-855f-4c60-bc2e-bcee8046c900' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aac9be2c-5f2f-4480-bb61-bb7aea172938' class='xr-var-data-in' type='checkbox'><label for='data-aac9be2c-5f2f-4480-bb61-bb7aea172938' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
        "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
        "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
        "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
@@ -2687,7 +2688,7 @@
        "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
        "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
        "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
-       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.4 72.39 72.43 ... -197.1 -197.1</div><input id='attrs-aa1a0867-bde0-4b74-be6a-f48626acd9e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa1a0867-bde0-4b74-be6a-f48626acd9e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-254d63fc-3383-4d9b-875f-f01e99cf3205' class='xr-var-data-in' type='checkbox'><label for='data-254d63fc-3383-4d9b-875f-f01e99cf3205' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.3957   ,   72.39208  ,   72.42783  ,   72.42615  ,\n",
+       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.4 72.39 72.43 ... -197.1 -197.1</div><input id='attrs-b2cd30f3-104c-4306-9c6f-b0b3cf01fa59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2cd30f3-104c-4306-9c6f-b0b3cf01fa59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6abd0003-2ab9-4b3b-b994-8a996c8850f7' class='xr-var-data-in' type='checkbox'><label for='data-6abd0003-2ab9-4b3b-b994-8a996c8850f7' 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.3957   ,   72.39208  ,   72.42783  ,   72.42615  ,\n",
        "          72.44187  ,   72.41524  ,   72.461914 ,   72.493645 ,\n",
        "          72.45924  ,   72.46602  ,   72.43278  ,   72.44255  ,\n",
        "          72.46903  ,   72.422035 ,   72.40729  ,   72.41101  ,\n",
@@ -2727,7 +2728,7 @@
        "        -197.10716  , -197.18983  , -197.15218  , -197.12483  ,\n",
        "        -197.06255  , -197.14517  , -197.12418  , -197.05786  ,\n",
        "        -197.08685  , -197.11751  , -197.07716  , -197.07918  ,\n",
-       "        -197.19186  , -197.1385   , -197.14885  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3595 -0.3604 ... 9.714 9.713</div><input id='attrs-ad5e4509-1d1d-49e4-826e-775848c76d96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad5e4509-1d1d-49e4-826e-775848c76d96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fe5aa34-8080-4112-b4bd-34635489238b' class='xr-var-data-in' type='checkbox'><label for='data-2fe5aa34-8080-4112-b4bd-34635489238b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.35945004, -0.36040476, -0.35942063, -0.36224607, -0.3606849 ,\n",
+       "        -197.19186  , -197.1385   , -197.14885  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3595 -0.3604 ... 9.714 9.713</div><input id='attrs-352f4a0b-f879-4ea7-8ee4-23c27d4e34d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-352f4a0b-f879-4ea7-8ee4-23c27d4e34d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3033afff-0219-46a6-9cf1-8fbb01f25c18' class='xr-var-data-in' type='checkbox'><label for='data-3033afff-0219-46a6-9cf1-8fbb01f25c18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.35945004, -0.36040476, -0.35942063, -0.36224607, -0.3606849 ,\n",
        "        -0.36077246, -0.361926  , -0.3607621 , -0.3633263 , -0.36385658,\n",
        "        -0.36013916, -0.3583838 , -0.3592216 , -0.35633823, -0.35704008,\n",
        "        -0.35671657, -0.35852   , -0.35691682, -0.3556908 , -0.3539107 ,\n",
@@ -2767,7 +2768,7 @@
        "         9.714553  ,  9.715958  ,  9.714808  ,  9.717874  ,  9.716309  ,\n",
        "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
        "         9.715256  ,  9.714936  ,  9.714808  ,  9.711726  ,  9.711886  ,\n",
-       "         9.713675  ,  9.714042  ,  9.71278   ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-400a4c49-e105-48bf-8050-4267c6517a5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-400a4c49-e105-48bf-8050-4267c6517a5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02f2c62e-7be4-49be-93bd-ae1cf0b15567' class='xr-var-data-in' type='checkbox'><label for='data-02f2c62e-7be4-49be-93bd-ae1cf0b15567' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "         9.713675  ,  9.714042  ,  9.71278   ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-1805b5d9-3ba1-4ea3-bda2-8e19ecfeebe3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1805b5d9-3ba1-4ea3-bda2-8e19ecfeebe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495e50c1-1f71-41ab-8506-7acc8058930a' class='xr-var-data-in' type='checkbox'><label for='data-495e50c1-1f71-41ab-8506-7acc8058930a' 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2777,7 +2778,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-fdf8020a-078c-4db9-8292-60af8e1f50c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdf8020a-078c-4db9-8292-60af8e1f50c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af18c24c-eb08-40ea-aa7f-f5b662083557' class='xr-var-data-in' type='checkbox'><label for='data-af18c24c-eb08-40ea-aa7f-f5b662083557' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-78fa7be5-80c1-45b6-9705-2bc2ff8cbbe9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78fa7be5-80c1-45b6-9705-2bc2ff8cbbe9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-579172bb-9bf9-4a39-b360-642ed7577c5b' class='xr-var-data-in' type='checkbox'><label for='data-579172bb-9bf9-4a39-b360-642ed7577c5b' 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2817,7 +2818,7 @@
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-af0c7ee5-9924-41ba-bfd3-2bdc1435d4f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af0c7ee5-9924-41ba-bfd3-2bdc1435d4f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-066eea93-c5bd-4f83-a5fd-f19917b57ed6' class='xr-var-data-in' type='checkbox'><label for='data-066eea93-c5bd-4f83-a5fd-f19917b57ed6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-5ff9feba-c64d-4162-8c84-cdf460ac80dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ff9feba-c64d-4162-8c84-cdf460ac80dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55061f20-1323-48e0-871e-36c33e4c7dff' class='xr-var-data-in' type='checkbox'><label for='data-55061f20-1323-48e0-871e-36c33e4c7dff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
        "        -0.02035667, -0.01573333],\n",
        "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
        "        -0.00658667, -0.00238   ],\n",
@@ -2829,7 +2830,7 @@
        "       [        nan,         nan,         nan, ...,         nan,\n",
        "                nan,         nan],\n",
        "       [        nan,         nan,         nan, ...,         nan,\n",
-       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-088bac65-6156-4132-9b31-60adf0be9af4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-088bac65-6156-4132-9b31-60adf0be9af4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a80a35ba-1e49-4191-8738-e3a72a4f508b' class='xr-var-data-in' type='checkbox'><label for='data-a80a35ba-1e49-4191-8738-e3a72a4f508b' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
+       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-6141b941-68f0-4fc7-ac33-85eeff1fff6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6141b941-68f0-4fc7-ac33-85eeff1fff6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f221ce37-8c5c-4fcb-9221-b01e693d66bf' class='xr-var-data-in' type='checkbox'><label for='data-f221ce37-8c5c-4fcb-9221-b01e693d66bf' 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
        "        81.745   ],\n",
        "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
        "        78.045   ],\n",
@@ -2841,7 +2842,7 @@
        "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
        "              nan],\n",
        "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "              nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-d331358d-8056-43ea-9f82-d17ef0f040e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d331358d-8056-43ea-9f82-d17ef0f040e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdf90c3c-3a65-4882-a1a9-1d7531424182' class='xr-var-data-in' type='checkbox'><label for='data-fdf90c3c-3a65-4882-a1a9-1d7531424182' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
+       "              nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-3cd96b63-33c1-4f2f-b003-37d141c3a1af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cd96b63-33c1-4f2f-b003-37d141c3a1af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4597a20-08eb-4119-a9a8-6f0b5b046b6f' class='xr-var-data-in' type='checkbox'><label for='data-d4597a20-08eb-4119-a9a8-6f0b5b046b6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
        "        92.61667 ],\n",
        "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
        "        96.57667 ],\n",
@@ -2853,7 +2854,7 @@
        "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
        "         0.      ],\n",
        "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "         0.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-dc95da07-d2ce-4724-a499-f98047bffdd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc95da07-d2ce-4724-a499-f98047bffdd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c348c68c-f1af-425d-b9fb-8f9c903fe05b' class='xr-var-data-in' type='checkbox'><label for='data-c348c68c-f1af-425d-b9fb-8f9c903fe05b' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
+       "         0.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-19625e80-eacc-46d1-831f-5b9bd14140f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19625e80-eacc-46d1-831f-5b9bd14140f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea5d5bd8-3563-4e5d-bce9-c194036b0f0e' class='xr-var-data-in' type='checkbox'><label for='data-ea5d5bd8-3563-4e5d-bce9-c194036b0f0e' 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
        "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
        "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
        "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
@@ -2873,7 +2874,7 @@
        "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
        "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
        "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002097 -0.002078 ... -0.002637</div><input id='attrs-07060b4b-cf95-49ec-b4cd-ae2bafbeaa8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07060b4b-cf95-49ec-b4cd-ae2bafbeaa8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e82838b7-0bde-4a56-a63d-7a7b4c6a463a' class='xr-var-data-in' type='checkbox'><label for='data-e82838b7-0bde-4a56-a63d-7a7b4c6a463a' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00209712, -0.00207796, -0.00199299, -0.00203929, -0.00193438,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002097 -0.002078 ... -0.002637</div><input id='attrs-5d94588f-8932-43c8-92e9-577df1cd62c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d94588f-8932-43c8-92e9-577df1cd62c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52c177b3-8efe-4b7f-9824-ea4127dbbe99' class='xr-var-data-in' type='checkbox'><label for='data-52c177b3-8efe-4b7f-9824-ea4127dbbe99' 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00209712, -0.00207796, -0.00199299, -0.00203929, -0.00193438,\n",
        "        -0.00196708, -0.0019927 , -0.00204398, -0.00193731, -0.0020106 ,\n",
        "        -0.00205254, -0.00204932, -0.00204045, -0.00204494, -0.0020428 ,\n",
        "        -0.00195406, -0.00208406, -0.0020402 , -0.00199256, -0.00194318,\n",
@@ -2913,7 +2914,7 @@
        "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
        "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
        "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
-       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-63fa9c28-4d78-4669-acc0-1771e7d5375a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63fa9c28-4d78-4669-acc0-1771e7d5375a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef3b0087-1dc2-4e48-aed9-1ccea7b4a6b8' class='xr-var-data-in' type='checkbox'><label for='data-ef3b0087-1dc2-4e48-aed9-1ccea7b4a6b8' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
+       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-f30e59ac-8b5b-4246-a451-0be05acd9473' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f30e59ac-8b5b-4246-a451-0be05acd9473' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de625746-3de8-4314-a1c8-cf9192af45bb' class='xr-var-data-in' type='checkbox'><label for='data-de625746-3de8-4314-a1c8-cf9192af45bb' 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
        "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
        "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
        "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
@@ -2953,7 +2954,7 @@
        "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
        "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
        "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
-       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-e3665e58-1ba1-4039-9ed0-11a06e0c3276' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3665e58-1ba1-4039-9ed0-11a06e0c3276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f7c761c-f2df-40ea-ba7f-8e7b9ec7bce3' class='xr-var-data-in' type='checkbox'><label for='data-8f7c761c-f2df-40ea-ba7f-8e7b9ec7bce3' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-e5d165c4-e1f9-4b34-9781-616441b36054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5d165c4-e1f9-4b34-9781-616441b36054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89566368-b1fe-4a19-b6d7-be0fcdfa69dc' class='xr-var-data-in' type='checkbox'><label for='data-89566368-b1fe-4a19-b6d7-be0fcdfa69dc' 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
@@ -2967,7 +2968,7 @@
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-278caf69-1d6a-431b-b5c0-079ddc54adaf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-278caf69-1d6a-431b-b5c0-079ddc54adaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0a1b3f7-87d1-44ab-aa82-8bf3be1cafa1' class='xr-var-data-in' type='checkbox'><label for='data-f0a1b3f7-87d1-44ab-aa82-8bf3be1cafa1' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4399d7cc-4b23-4d52-b2c6-330eeb26dfe8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4399d7cc-4b23-4d52-b2c6-330eeb26dfe8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5a41c9c-af19-4468-83b0-66f75d436d8c' class='xr-var-data-in' type='checkbox'><label for='data-a5a41c9c-af19-4468-83b0-66f75d436d8c' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2977,7 +2978,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-98346b4c-5d26-4e2e-b0fd-20f586b46a3e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98346b4c-5d26-4e2e-b0fd-20f586b46a3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ceaa855-c6c9-47ec-8ac4-5982ee3848be' class='xr-var-data-in' type='checkbox'><label for='data-2ceaa855-c6c9-47ec-8ac4-5982ee3848be' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-46885536-b819-4246-9c20-2e7450aace7e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46885536-b819-4246-9c20-2e7450aace7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b66eeb5-4199-4992-a535-8e717feb9a90' class='xr-var-data-in' type='checkbox'><label for='data-5b66eeb5-4199-4992-a535-8e717feb9a90' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2987,7 +2988,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-9be1a428-0f8f-41d2-9f52-99b96cfde51e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9be1a428-0f8f-41d2-9f52-99b96cfde51e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ffdd787-4337-4b5d-8fdb-b65940a04b12' class='xr-var-data-in' type='checkbox'><label for='data-4ffdd787-4337-4b5d-8fdb-b65940a04b12' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3d5a5ad1-3ab2-4cc4-a843-542b5edf1fbd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d5a5ad1-3ab2-4cc4-a843-542b5edf1fbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b7a5f4a-0f8f-47d8-870f-eda96dd2b361' class='xr-var-data-in' type='checkbox'><label for='data-8b7a5f4a-0f8f-47d8-870f-eda96dd2b361' 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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2997,7 +2998,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-47cbc2fd-07c9-4384-a0e4-03ca4c723f45' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-47cbc2fd-07c9-4384-a0e4-03ca4c723f45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64d98ba7-8d6e-40c3-8520-56b2a34c7e08' class='xr-var-data-in' type='checkbox'><label for='data-64d98ba7-8d6e-40c3-8520-56b2a34c7e08' 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([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-68280b1c-5735-4846-8cb3-b757883ef257' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68280b1c-5735-4846-8cb3-b757883ef257' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-877e8efa-e09e-45b3-905f-11387551b627' class='xr-var-data-in' type='checkbox'><label for='data-877e8efa-e09e-45b3-905f-11387551b627' 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([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
        "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
        "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
        "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
@@ -3033,7 +3034,7 @@
        "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
        "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
        "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
-       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-f1e2da88-e49d-4ddc-8744-44b0b2d379a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1e2da88-e49d-4ddc-8744-44b0b2d379a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4abad920-f627-49f7-b086-cc427704d3af' class='xr-var-data-in' type='checkbox'><label for='data-4abad920-f627-49f7-b086-cc427704d3af' 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
+       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-e33ead4d-67db-467f-918b-fd602a898965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e33ead4d-67db-467f-918b-fd602a898965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08abf030-07fa-4e6f-9f4f-12b2b80c5737' class='xr-var-data-in' type='checkbox'><label for='data-08abf030-07fa-4e6f-9f4f-12b2b80c5737' 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
        "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
        "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
        "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
@@ -3063,7 +3064,7 @@
        "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
        "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
        "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
-       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-dd0d34f6-33e7-4261-876a-e0cd37912b87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd0d34f6-33e7-4261-876a-e0cd37912b87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f093781b-750a-4bf1-8fb5-a88b593c5eac' class='xr-var-data-in' type='checkbox'><label for='data-f093781b-750a-4bf1-8fb5-a88b593c5eac' 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
+       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-34708eee-0909-42f3-b448-c01e8c115774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34708eee-0909-42f3-b448-c01e8c115774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3c5e09b-6992-4d4d-b212-5e6bc9b338a4' class='xr-var-data-in' type='checkbox'><label for='data-c3c5e09b-6992-4d4d-b212-5e6bc9b338a4' 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
        "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
        "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
        "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
@@ -3099,7 +3100,7 @@
        "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
        "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
        "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
-       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-bf18aa15-1562-42e6-bce9-8ca37e1c8635' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf18aa15-1562-42e6-bce9-8ca37e1c8635' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26a99f69-9a2b-4fba-9379-1216849d83a4' class='xr-var-data-in' type='checkbox'><label for='data-26a99f69-9a2b-4fba-9379-1216849d83a4' 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
+       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-2b74bc41-c130-4608-be11-7c24a1e4f467' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b74bc41-c130-4608-be11-7c24a1e4f467' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b8a23a-750f-456d-a0dc-577634aa12ab' class='xr-var-data-in' type='checkbox'><label for='data-f0b8a23a-750f-456d-a0dc-577634aa12ab' 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
        "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
        "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
        "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
@@ -3135,7 +3136,7 @@
        "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
        "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
        "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
-       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-25147518-1221-4527-955b-60cd701f376d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25147518-1221-4527-955b-60cd701f376d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1029cb68-a454-4c89-b26c-7cd373ef4d35' class='xr-var-data-in' type='checkbox'><label for='data-1029cb68-a454-4c89-b26c-7cd373ef4d35' 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>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
+       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-f0ffca4e-634c-4604-a73c-a39ffcb3de93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0ffca4e-634c-4604-a73c-a39ffcb3de93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3baf935a-b0f8-4dfa-b30b-e05bc641911e' class='xr-var-data-in' type='checkbox'><label for='data-3baf935a-b0f8-4dfa-b30b-e05bc641911e' 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>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
        "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
        "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
        "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
@@ -3171,7 +3172,7 @@
        "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
        "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
        "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
-       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-ba514666-3cee-40ce-ac0d-3049ae20977a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba514666-3cee-40ce-ac0d-3049ae20977a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93611a8-db96-45a9-8a85-50ca4db0873b' class='xr-var-data-in' type='checkbox'><label for='data-a93611a8-db96-45a9-8a85-50ca4db0873b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Depth to Seafloor</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
+       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-75dbd849-b29e-4497-920e-3a9f77cee3ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75dbd849-b29e-4497-920e-3a9f77cee3ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da9984a4-7ab4-4c79-8055-17b61150baef' class='xr-var-data-in' type='checkbox'><label for='data-da9984a4-7ab4-4c79-8055-17b61150baef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Depth to Seafloor</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
        "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
        "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
        "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
@@ -3207,7 +3208,7 @@
        "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
        "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
        "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
-       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-66eda5d7-65dd-484e-8919-c04de8040cd6' class='xr-section-summary-in' type='checkbox'  ><label for='section-66eda5d7-65dd-484e-8919-c04de8040cd6' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;alt&quot;: false, &quot;alt_raw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;alt&quot;: false, &quot;alt_raw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>h_deploy :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
+       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d033b4d2-5fe1-48fb-adaa-fac0731a998b' class='xr-section-summary-in' type='checkbox'  ><label for='section-d033b4d2-5fe1-48fb-adaa-fac0731a998b' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>h_deploy :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -3311,7 +3312,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x277cbcec9d0>"
+       "<matplotlib.colorbar.Colorbar at 0x23381c571f0>"
       ]
      },
      "execution_count": 18,
@@ -3320,7 +3321,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 2 Axes>"
       ]
@@ -3359,7 +3360,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 2 Axes>"
       ]
@@ -3420,7 +3421,7 @@
     "Most functions related to turbulence statistics in MHKiT-DOLfYN have the papers they originate from referenced in their docstrings.\n",
     "\n",
     "### 7.1 Turbulence Intensity\n",
-    "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this is simply calculated as `<raw dataset>.velds.I`\n",
+    "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this can be simply calculated as `<raw dataset>.velds.I`, but be aware that this will be a conservative estimate. Another function, `turbulence_intensity`, is capable of subtracting instrument noise from this parameter and is discussed below. The noise-subtracted TI is more accurate and typically 1-2% lower than the non-noise-subtracted estimation.\n",
     "\n"
    ]
   },
@@ -3432,7 +3433,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277a943d4f0>"
+       "<matplotlib.collections.QuadMesh at 0x23383d2c940>"
       ]
      },
      "execution_count": 21,
@@ -3441,7 +3442,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3517,7 +3518,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 2 Axes>"
       ]
@@ -3602,11 +3603,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance.\n",
+    "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.3 Instrument Noise\n",
     "\n",
-    "### 7.3 TKE Dissipation Rate\n",
+    "The next thing we want to do is calculate the instrument's Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
     "\n",
-    "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, and the frequency range of the isotropic cascade."
+    "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8."
    ]
   },
   {
@@ -3615,11 +3623,29 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Frequency range of isotropic turubulence cascade\n",
+    "ds_avg[\"noise_5m\"] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra_5m\"], pct_fN=0.9)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.4 TKE Dissipation Rate\n",
+    "\n",
+    "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, the frequency range of the isotropic cascade, and the instrument's noise."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Frequency range of isotropic turubulence cascade in same units as PSD frequency vector\n",
     "f_rng = [0.2, 0.5]\n",
     "# Dissipation rate\n",
     "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
-    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng\n",
+    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
     ")"
    ]
   },
@@ -3632,7 +3658,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3640,21 +3666,27 @@
     "\n",
     "spec = [None] * len(ds.range)\n",
     "e = [None] * len(ds.range)\n",
+    "n = [None] * len(ds.range)\n",
     "\n",
     "for r in range(len(ds[\"range\"])):\n",
     "    # Calc spectra from each depth bin using the 5th beam\n",
     "    spec[r] = avg_tool.power_spectral_density(\n",
     "        ds[\"vel_b5\"].isel(range_b5=r), freq_units=\"Hz\"\n",
     "    )\n",
+    "    \n",
+    "    # Calculate doppler noise from spectra from each depth bin\n",
+    "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
+    "    \n",
     "    # Calc dissipation rate from each spectra\n",
     "    e[r] = avg_tool.dissipation_rate_LT83(\n",
-    "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng\n",
-    "    )  # Hz\n",
+    "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
+    "    )\n",
     "\n",
     "ds_avg[\"auto_spectra\"] = xr.concat(spec, dim=\"range\")\n",
+    "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
     "ds_avg[\"dissipation_rate\"] = xr.concat(e, dim=\"range\")\n",
     "\n",
-    "del spec, e  # save memory"
+    "del spec, n, e  # save memory"
    ]
   },
   {
@@ -3669,7 +3701,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3691,27 +3723,27 @@
    "source": [
     "If we plot the dissipation rate below in a colormap, we can see that the profile map has a lot of missing data. One of the reasons is that the 1 Hz sampling rate doesn't provide enough information needed to make dissipation rate estimations, and the other part is that turbulence measurements push the boundaries of what ADCPs are capable of.\n",
     "\n",
-    "Also, 5x10^-4 $m^2/s^3$ sounds reasonable for a dissipation rate estimate for the 1.25 m/s current speeds measured here. They can be a magnitude or two greater for faster flow speeds and depend heavily on bathymetry and regional hydrodynamics."
+    "Also, 1x10^-4 to 3x10^-4 $m^2/s^3$ is reasonable for a dissipation rate estimate for the 1 - 1.5 m/s current speeds measured here. They can be a magnitude greater for faster flow speeds, typically increase closer to the seafloor, and depend heavily on bathymetry and regional hydrodynamics."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277db518b20>"
+       "<matplotlib.collections.QuadMesh at 0x233920e4070>"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3724,56 +3756,48 @@
     "ds_avg[\"dissipation_rate\"].plot(cmap=\"turbo\", ylim=(0, 11))"
    ]
   },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.4 Turbulent Kinetic Energy (TKE) Components\n",
-    "\n",
-    "The next parameters we'll find here are the vertical TKE component and the total TKE magnitude. Since we're using the vertical beam on the ADCP, we'll directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
-    "\n",
-    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. Since we're using a 5-beam ADCP, we can calculate the total TKE as well using `total_turbulent_kinetic_energy`, which is a wrapper around the 5-beam variance function.\n",
-    "\n",
-    "#### Quick ADCP lesson before we dive in:\n",
-    "\n",
-    "There are a couple caveats to calculating Reynolds stress tensor components:\n",
-    "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unkowns, 5 knowns)\n",
-    "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
-    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly.\n",
-    "\n",
-    "That being said, even if we don't know which direction the 3 TKE components ($\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$) are oriented, we can still combine them and get the total TKE magnitude."
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### 7.5 ADCP Noise\n",
+    "### 7.5 Noise-Corrected Turbulence Intensity\n",
     "\n",
-    "The first thing we want to do is calculate the Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
-    "\n",
-    "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8.\n",
-    "\n",
-    "Because ADCP noise is a function of range as well as flow speed and instrument frequency, we'll use a for loop to measure the noise from each spectra:"
+    "Now that we've calculated the noise floor for each ping, we can recalculate TI and include subtracting instrument noise using the `turbulence_intensity` function. If we subtract this from the non-noise corrected function, we can see there's a large difference\n",
+    "at slower slow speeds, but the average difference is about 0.008 (0.8%). Notice this will also remove measurements where noise is \n",
+    "high."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'TI Difference')"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Setting up \"for\" loop\n",
-    "n = [None] * len(ds.range)\n",
-    "\n",
-    "for r in range(len(ds.range)):\n",
-    "    # Calculate doppler noise from spectra from each depth bin\n",
-    "    n[r] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra\"][r], pct_fN=0.9)\n",
-    "\n",
-    "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
+    "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
     "\n",
-    "del n  # save memory"
+    "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
+    "plt.title(\"TI Difference\")"
    ]
   },
   {
@@ -3781,12 +3805,27 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now that we know the Doppler noise level, we can use that as input for the TKE functions. We'll first calculate the vertical TKE component, using the function `turbulent_kinetic_energy`, inputting our raw vertical beam data and the noise floors we calculated above for each ensemble."
+    "### 7.6 Turbulent Kinetic Energy (TKE) Components\n",
+    "\n",
+    "The next parameters we'll find here are the vertical TKE component and the total TKE magnitude. Since we're using the vertical beam on the ADCP, we'll directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
+    "\n",
+    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. Since we're using a 5-beam ADCP, we can calculate the total TKE as well using `total_turbulent_kinetic_energy`, which is a wrapper around the 5-beam variance function.\n",
+    "\n",
+    "#### Quick 5-beam ADCP lesson before we dive in:\n",
+    "\n",
+    "There are a couple caveats to calculating Reynolds stress tensor components:\n",
+    "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unkowns, 5 knowns)\n",
+    "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
+    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly.\n",
+    "\n",
+    "That being said, even if we don't know which direction the 3 TKE components ($\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$) are oriented, we can still combine them and get the total TKE magnitude.\n",
+    "\n",
+    "We'll first calculate the vertical TKE component, using the function `turbulent_kinetic_energy`, inputting our raw vertical beam data and the noise floors we calculated above for each ensemble."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3805,15 +3844,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:383: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
-      "  warnings.warn(\"    The beam-variance algorithms assume the instrument's \"\n"
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:401: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+      "  warnings.warn(\n"
      ]
     }
    ],
@@ -3833,22 +3872,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x277de4bfcd0>"
+       "<matplotlib.collections.QuadMesh at 0x23392108820>"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3879,7 +3918,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 7.6 TKE Production\n",
+    "### 7.7 TKE Production\n",
     "\n",
     "Though it can't be found from this deployment, we'll go over how to estimate TKE Production. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
     "\n",
@@ -3894,17 +3933,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:383: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
-      "  warnings.warn(\"    The beam-variance algorithms assume the instrument's \"\n",
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:391: UserWarning:     100.0 % of measurements have a tilt greater than 5 degrees.\n",
-      "  warnings.warn(f\"    {pct_above_thresh} % of measurements have a tilt \"\n"
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:401: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+      "  warnings.warn(\n",
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:411: UserWarning:     100.0 % of measurements have a tilt greater than 5 degrees.\n",
+      "  warnings.warn(\n"
      ]
     }
    ],
@@ -3939,7 +3978,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3956,14 +3995,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 7.7 TKE Balance \n",
+    "### 7.8 TKE Balance \n",
     "\n",
     "We can plot TKE Production and compare it to our dissipation rate calculations to get an understanding of the TKE balance. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates aren't accurate because our stress components aren't aligned with the flow, so if we plot them, we see drastic differences (1x10^-3 $m^2/s^3$ is quite large) profile here."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -3972,13 +4011,13 @@
        "Text(0.5, 1.0, 'TKE Balance')"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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ltVodxktLS1N79uxRLVq00ONVrFhRrVq1SqWkpOSId/78edWtWzc9rG1p3ry5+u9//6tOnDihMjMz9fDDhg3Tw/Tp00ddu3ZNZWRk6IvZbFZJSUlq79696umnn1YGg0ENGjQoX/tstVrVtWvX1Pz585WPj4+ezwMPPKCOHj2qMjIy8kwjKSlJzZkzR48bFBSkVq9erc9SfrtLly6pZs2aKUDVrl1brVq1SiUlJamjR4+qQYMGqYoVK6pNmzY5jLty5Url6+ur5+Xt7a3q1KmjfH191SuvvKLPxg6ohx56SG3fvl2P++mnn9odb5PJpAA1fvx4lZCQYLetS5cuavfu3Xrc2bNn6+FvX7p165Zj5nallHrxxRf1MBUqVFBBQUHq+++/V0ppM8N/8skn+vYaNWqovXv3KrPZbJfG//73PxUQEKDPuH/gwAGVkpKi1q5dq+rWrau6d++url27Zvd5njt3TnXv3l1Pe/To0ery5cvKarUqi8Wizp49a3f+DRs2TJ81XghR8khFS5QKV69edfgjmn2ZOXNmjnjnzp3LM96iRYv08KdOncozPKAWLlyoXn31VfW3v/0tX+FvX7755pt87fe0adNyTcfX1zfPNJxVQGrXru00jtlsVjNmzFAtW7ZUQUFBqmzZsuruu+9WL730krpw4UKu+f32228qNjZWVahQQZUpU0a1adNGf1xPeHi46tu3r9q7d6/DuB9++KEKDw9X/v7+6p577lHLli1TSmmP2QkICFCjRo1SBw4ccBh3586d6tFHH1UhISHKz89PNW/eXM2aNSvHY3lsUlJS1IABA1RAQICKioqye6RQjRo1HB6zAQMG5Ejn2LFjavTo0So8PFz5+vqqatWqqa5du6olS5bYVciVUurbb791+lmuWrXK7jFKty/79+/P9bgLIYqHQSnp4BdCCCGEcAcZoyWEEEII4SZS0RJCCCGEcBOpaAkhhBBCuIlUtIQQQggh3EQqWkIIIYQQbiIVLSGEEEIIN/Eq7gJ4AqvVytmzZylbtmyhH24rhBDir0EpxfXr16levbr+VAJ3SEtLy/PZn/nh4+OjP4tUFD2paOXD2bNnCQ0NLe5iCCGE8CCnTp1y28PC09LSqOjvz40iSKtq1aokJCRIZctNpKKVD2XLlgW0L01QUFAxl0YIIURJlpycTGhoqP7b4Q5ms5kbwNNeBnxdSCcdmHH+PGazWSpabiIVrXywdRcGBQVJRUsIIUS+3ImhJv4G8HMhH6M8HMbtZDC8EEIIIYSbSIuWEEII4aG8DNpS6PhFVxThhBxjIYQQwkOZDNpS6PhFVxThhHQdCiGEEEK4ibRoCSGEEB5KWrRKPqloCSGEEB7KZFAuVrTkrkN3k65DIYQQQgg3kRYtIYQQwkOZXLzrULoO3U8qWkIIIYSHMhldHKMlPYduJ12HQgghhBBuIi1aQgghhIeSuw5LPqloCSGEEB5KKloln1S0hBBCCA8lFa2ST8ZoCSGEEEK4ibRoCSGEEB5K7jos+aSiJYQQQngoI65VtIxS0XI76ToUQgghhHATadESQgghPJTLg+FdiCvyR1q0hBBCCA9lNLq+FJbZbOaNN96gXr16REREEBMTw8aNGwuczvnz5xk5ciTh4eGEhYXRt29fTp48mWuc5cuXc8899xAeHk6TJk2YPXt2nvmkpaXx4YcfUqdOHY4fP55r2Pj4eDp37kzZsmUJCAigTZs2LF68uCC7pZOKlhBCCCEKJD09nfvvv5/PP/+ctWvX8ueffzJmzBi6dOnCsmXL8p1OQkIC0dHRXL16lQMHDnD06FGqV69OdHQ0f/zxh8M4EydO5IknnmD69OkcO3aMpUuXMnHiRMaOHeswfGpqKm+//TZ33XUXTz75JCdOnMi1TAsWLKBLly789NNPpKWlkZqaytatW4mLi+PZZ5/N977ZSEVLCCGE8FC2rkNXlsIYP3488fHxzJ07l1q1agEQGxtL7969GTJkCAkJCXmmYbFYiI2NxWw2M3fuXPz9/TGZTEyfPh0/Pz/69OlDRkaGXZyVK1cybdo0Jk+eTExMDAD169dn6tSpzJw5k6VLlzrMZ/DgwcTHx2PMownv0qVLjBkzhkmTJnHu3DkyMjLYtWsX0dHRALzzzjv88MMP+TpGNlLREkIIITxUcVS0jh8/zgcffEDDhg1p2bKl3bZBgwaRmprKhAkT8kxn0aJF7Nq1i9jYWAICArL2yWQiLi6Offv2MWfOHH291WrlhRdewGAwMGTIELu0+vfvj8lkYty4cVgsFrttZcuWpVKlSkRERFCxYsVcy/TFF1/w2muv8corr1C1alUAmjdvzpo1awgJCQG0Fq+CkIqWEEIIIfJtyZIlZGZm0qZNmxzbWrVqBcCKFSu4fPlyruksXLgQwGE6rVu3BuDTTz/V1+3YsYMjR44QERFB5cqV7cIHBgbSqFEjzpw5w5o1a5zm6efnl2uZfHx8GD16dI71lSpV4vHHHwe0Vq+C8NiK1urVq2nTpg2fffZZruF+/fVXHnzwQcLCwqhbty7jx4/n5s2bd6aQQgghhBuZjK4vBbV69WoAwsPDc2wLCQmhRo0amM1mtmzZ4jSN1NRU1q9f7zSdxo0bA7B7926uXbuWZ77Z48THxzvN12DIvQlv9OjRTrsXIyMjAahdu3auadzO4ypaS5cupVWrVjz00ENs3bo117CrVq2iTZs2dO7cmYSEBHbt2sWWLVvo3LkzN27cuEMlFkIIIdzDaHB9Kajdu3cDULNmTYfby5UrB8CePXucpnHw4EHS0tKcpmNLQynFvn37iixfVyQmJgLQs2fPAsXzuIpWdHQ0Gzdu1GuWzpw6dYoBAwbQqVMnxo0bB0BwcDBz5sxh27ZtPP/883eiuEIIIYTbGI0GTC4sxls1reTkZLslPT3dYX5paWmkpKQAWRWb2wUHBwNZFRNHsne/OUrHlkb2dGxxXMnXFT/++CONGzeme/fuBYrncRWt8PBwfH19adasWa7hXn75Za5fv84TTzxht75evXrcc889fPTRRxw8eNCdRRVCCCE8QmhoKMHBwfoybdo0h+Gyj7sqU6aMwzC2rjdbi1Vh0snefWdLxxbHlXwLa+/evWzevJkPPvggzzsXc5SryEtzh+Q2oC0jI0Ofx8PZIDulVL4mOBNCCCFKqqLqOjx16hRJSUn64uyuQR8fH/21Uo4flGg2mwH0u/QKk44tjezp2OK4km9hPfPMM4wfP5527doVOK7HVrRyG9C2adMmkpOT8fX1pUaNGjm252fAnBBCCFHSFdVg+KCgILvF19fXYX4hISF6hcfZWGfb4PXcplKwTZ3gLB1bGtnTscVxJd/CeO+99wgMDOTVV18tVHyPrWjlxjZgzlElC7L6d/fv359jvg3QZry9vb9aCCGE+KszmUw0bNgQgLNnzzoMc+HCBQCaNm3qNJ2oqCi9wcRROrY0fHx8aNCgAQBNmjRxOd+C2rBhAytWrGDx4sWYTKZCpVEqK1r5HTCXmZlJUlJSju3Tpk2z66sODQ11W1mFEEKIwiqOuw5tg8EPHDiQY1tiYiJJSUkEBATk2s1Wvnx5fbJTR+kcPXoUgPbt2+uTmeaWb/Y4PXr0yO+u5OrAgQNMnjyZFStWOB0Xlh+lsqKV3wFz4HjQ3IQJE+z6qk+dOuWeggohhBAuKI55tIYNG4bRaHT4AGnbtEu9evVy2v1oM2LECIBc0+nfv7++rkuXLoSFhXHw4MEck4Zeu3aNgwcPEhYWpk926orDhw8zevRoli5dSvny5XNsz88jhmxKZUUrvwPmwPGgOV9f3xz91UIIIYTQJu4cMWIE+/fvzzFn1bx58/D392fKlCn6uvj4eFq1asX7779vF3bQoEE0btyYpUuX2jV6mM1mFi9eTFRUFAMHDtTXe3l5MW3aNKxWqz6rvM2CBQuwWq289tpruXbxZWZmAjgcNmRz+PBhhg4dyoIFC+zGkgHcvHmTd955h88//9xp/NuVyopWfgfMBQQE5DkdvxBCCFFSGQ3aXFiFXvKYKd2Z6dOn06JFC0aNGsWVK1dQSjFz5kxWrVrF/Pnz7WZvf/vtt9m+fTuTJk2yS8Pb25svvviCzMxMxo0bR2ZmJqmpqQwdOhSr1cry5cvx9va2i9O3b19GjhzJ1KlT9YlMN23axKRJk3jmmWeIi4tzWuaEhAQuXrwIwLZt2xyG2bdvH+3bt2fPnj00b96cihUr6kv58uUJDAzk2WeftWtpy4tXvkN6kOIYMCeEEELcaYUdZ5U9fmEEBAQQHx/P5MmTiY6Oxmg0EhUVxY4dO/TfYJu4uDg2btzI4MGDc6QTFRXF1q1befHFF4mMjMTb25tu3bqxd+/eHM8ztJk1axZRUVH069eP9PR0qlSpwvz583Odsb127dqcPXtWb9EaOHAgzz//PGvWrNHrAmfPnqVDhw5cvXoVcN5Y07JlS+rWrZvnMbIplRWtjh074uPjw8WLF0lMTMxxq2dRD5gTQggh/mrKli3LjBkzmDFjRq7hBgwYwIABA5xuj4yM5Msvv8x3vgaDgTFjxjBmzJh8xzlx4kSeYapXr86VK1fynWZ+lcquw6CgIPr27Qs4H2RnNBrp06fPnS6aEEIIUWSKYzC8KBiPPcR5DWibMmUKAQEBzJ8/3279b7/9xq+//srw4cPzfF6iEEIIUZIZXBmfZTRgcKXfUeSLR1a0bt68qQ+CczagLSIigo8//pjVq1ezYMECAE6ePMnAgQO57777ePfdd+9YeYUQQgh3KI55tETBeFxFq1+/flSsWJH9+/cDMHv2bCpUqMBHH32UI+yAAQNYs2YNH374IeHh4TzwwAMMGjSIn376yaXJx4QQQggh8sPjBsMvXry4QOG7du1K165d3VQaIYQQovgYjdpS6PiOp5sURcjjKlpCCCGE0NjGWhU6vlS03M7jug6FEEIIITyFtGgJIYQQHkq6Dks+qWgJIYQQHkoqWiWfdB0KIYQQQriJtGgJIYQQHkoGw5d8UtESQgghPJTR4GLXobXoyiIck65DIYQQQgg3kRYtIYQQwkO53HUozS1uJxUtIYQQwkMZXLzr0CAVLbeTipYQQgjhoQxGAwYXWrSkouV+coiFEEIIIdxEWrSEEEIID+XyhKXS3OJ2UtESQgghPJQMhi/55BALIYQQQriJtGgJIYQQHkoGw5d8UtESQgghPJSM0Sr55BALIYQQQriJtGgJIYQQHkq6Dks+qWgJIYQQHspocPGuw8JHFfkkdVkhhBBCCDeRFi0hhBDCQxmMrnX/Sdeh+0lFSwghhPBQRpMBo8mFrkNrERZGOCQVLSGEEMJDyWD4kk8OsRBCCCGEm0iLlhBCCOGhDCYDBhe6Dg3Sdeh2UtESQgghPJWLXYfSr+V+coiFEEIIIdxEWrSEEEIIDyV3HZZ8UtESQgghPJSM0Sr5pOtQCCGEEMJNpEVLCCGE8FAGA67No2VQRVga4YhUtIQQQggP5XLXoQtxRf5I16EQQgghhJtIRUsIIYTwULYWLVeWwjKbzbzxxhvUq1ePiIgIYmJi2LhxY4HTOX/+PCNHjiQ8PJywsDD69u3LyZMnc42zfPly7rnnHsLDw2nSpAmzZ8/OM5+0tDQ+/PBD6tSpw/Hjx/MMX5g8HJGuQyGEEMJDGUxGDKbCt5kYTIWLl56eTo8ePbhw4QJr166lVq1aLFu2jC5durBw4UJiY2PzlU5CQgLt2rWjTZs2HDhwAB8fH5577jmio6PZtGkT9erVyxFn4sSJzJw5k2+++YaYmBgOHTpE+/bt2bdvH++//36O8KmpqcyaNYv33nuPU6dO5atcBc0jN9KiJYQQQnio4mrRGj9+PPHx8cydO5datWoBEBsbS+/evRkyZAgJCQl5pmGxWIiNjcVsNjN37lz8/f0xmUxMnz4dPz8/+vTpQ0ZGhl2clStXMm3aNCZPnkxMTAwA9evXZ+rUqcycOZOlS5c6zGfw4MHEx8djNOZd7SlMHrmRipYQQggh8u348eN88MEHNGzYkJYtW9ptGzRoEKmpqUyYMCHPdBYtWsSuXbuIjY0lICBAX28ymYiLi2Pfvn3MmTNHX2+1WnnhhRcwGAwMGTLELq3+/ftjMpkYN24cFovFblvZsmWpVKkSERERVKxYMdcyFTaP3EhFSwghhPBQxdGitWTJEjIzM2nTpk2Oba1atQJgxYoVXL58Odd0Fi5cCOAwndatWwPw6aef6ut27NjBkSNHiIiIoHLlynbhAwMDadSoEWfOnGHNmjVO8/Tz88u1TEWRx+2koiWEEEJ4KIPRxYpWIebgWr16NQDh4eE5toWEhFCjRg3MZjNbtmxxmkZqairr1693mk7jxo0B2L17N9euXcsz3+xx4uPjneZrMOS+v0WRx+2koiWEEEL8xSUnJ9st6enpTsPu3r0bgJo1azrcXq5cOQD27NnjNI2DBw+SlpbmNB1bGkop9u3bV2T55sUdechdhwXQtk43TIach8xo0poirZY0u/W7L2/OEbZF5S4A7Lr4IwDR1R7U0vAJAsDkXwmArYcKdleDEEKIgmtWoa3+2tE1G3Jet3NLx1ka7lJUdx2GhobarZ8yZQovvfRSjvBpaWmkpKQAWZWO2wUHBwOQmJjoNN9Lly7prx2lY0sjezq2OK7kmxd35CEVLSGEEMJDFdXM8KdOnSIoKEhf7+vr6zB89nFXZcqUcRjGdmefrcWqMOlkvzvQlo4tjiv55sUdeUhFSwghhPiLCwoKsqtoOePj46O/VsrxcxLNZjOgjdcqbDq2NLKnY4vjSr55cUceMkZLCCGE8FQmg+tLAYSEhOiVkRs3bjgMYxu8nttUClWrVtVfO0rHlkb2dGxxXMk3L+7IQypaQgghhIe609M7mEwmGjZsCMDZs2cdhrlw4QIATZs2dZpOVFSUfgego3Rsafj4+NCgQQMAmjRp4nK+eXFHHlLREkIIIUS+de/eHYADBw7k2JaYmEhSUhIBAQG0a9fOaRrly5fXJzt1lM7Ro0cBaN++vT6ZaW75Zo/To0eP/O5KDu7IQypaQgghhIey3XXoylJQw4YNw2g0OnyA9NatWwHo1auX0wH1NiNGjADINZ3+/fvr67p06UJYWBgHDx60u2sRtC69gwcPEhYWpk92WhjuyEMqWkIIIYSnMro4PqsQE5ZGRkYyYsQI9u/fn2M+qXnz5uHv78+UKVP0dfHx8bRq1SrHw5gHDRpE48aNWbp0qd1dfGazmcWLFxMVFcXAgQP19V5eXkybNg2r1arPKm+zYMECrFYrr732GiaT8ydlZ2ZmAjh9hE5R5HG7Ul/R2rx5Mw888ABVq1YlNDSUevXqMWXKFJdu/xRCCCFKguJ6qPT06dNp0aIFo0aN4sqVKyilmDlzJqtWrWL+/Pl2M6u//fbbbN++nUmTJtml4e3tzRdffEFmZibjxo0jMzOT1NRUhg4ditVqZfny5Xh7e9vF6du3LyNHjmTq1Kn6RKabNm1i0qRJPPPMM8TFxTktc0JCAhcvXgRg27ZtTsO5kocjpXp6h2XLltGvXz/+9a9/8b///Q9vb292795Nz549+fHHH4mPj7e7xVQIIYQQeQsICCA+Pp7JkycTHR2N0WgkKiqKHTt26APKbeLi4ti4cSODBw/OkU5UVBRbt27lxRdfJDIyEm9vb7p168bevXtzPGvQZtasWURFRdGvXz/S09OpUqUK8+fPp2fPnk7LW7t2bc6ePau3aA0cOJDnn3+eNWvWOBzYXpg8nDEoZ5NFeLj09HRq1KhBixYt+P777+22ff755wwePJgPP/yQ0aNH55lWcnIywcHBNC7fSmaGF0KIUsQdM8PbfjOSkpLyNTdVYdjyuDIlnCC//Hdj5UgnzULIy8fcWta/ulLborVv3z4uX77ssKbavHlzAPbv33+HSyWEEEIUnaKaGV64T6kdo2W7HdRRP+z169cB1+baEEIIIYTIS6mtaDVo0IDIyEg2btzInDlz7LatWLGCxo0b8/jjjxdT6YQQQogicIdnhhcFV2orWgaDgU8++QQfHx9Gjx6t36a5ZcsWdu3axbp165zO8ZGenk5ycrLdIoQQQpQ0xTGPliiYUjtGC6BDhw58+eWX9OnTh0GDBrFjxw68vLz4/vvvc50DY9q0abz88st3sKRCCCGEKI1KdUUL4KGHHuKtt97i6NGjvP/++/j5+REdHU2/fv2cxpkwYQLjxo3T3ycnJxMaGnoniiuEEELkn9HF7r9CTFgqCqbUV7TeeustIiMjGTNmDG3atGHgwIH079+fxMRExowZ4zCOr6+vw27Fzcd/ICbsAad53X5rcPbbhm8PY9vm5a/NE2IwafmZ/CoA0Cp8iNN8fjn2md37DjHaGLT1G4blCGtL5/Y4QghRGLlNh2CbrsZiTrJb72jahNvDegdq/8zaprrZduTjHHmafIIB2HlutcMyOcont235DWub1sHRdkfX+TvK1XFWMkbL7Up15+z06dP56quvePTRRwHo06cPS5cuxWg0MnbsWLZs2VLMJRRCCCFEaVZqK1onTpzgn//8Jw8++KDd+kceeYQ33ngDpZSMwxJCCOHZ5K7DEq/UVrRWr15Nenq6wyn8n376aSpVqsT27duLoWRCCCFEETEaXF+EW5XaipbZbAbg9OnTObZ5eXlRp04dec6hEEIIz2Yyur4Ityq1R/ihhx7CZDKxfPly/SGSNklJSRw6dIhevXoVU+mEEEII8VdQaitadevW5d///jeHDh3iiSeeIClJu7Pl/Pnz9OvXj9q1a/P6668XcymFEEIIF8gYrRKv1Fa0AJ555hlWr17N2bNnCQsLo3bt2sTExNC8eXN+/vlnypcvX9xFFEIIIQrP6GIlS8ZouV2pn0frgQce4IEHnM99JYQQQgjhLqW+oiWEEEKUWjJhaYknFS0hhBDCU7k6RYN0HbpdqR6jJYQQQghRnKRFSwghhPBQymRAudD950pckT9S0RJCCCE8lXQdlnjSdSiEEEII4SbSoiWEEEJ4KOk6LPmkoiWEEEJ4KiOu9U1Jv5bbSUWrANrW6YbJkHXIjCY/u+3NKrS1W7/78mYAWlTuooeJrvag3Tbbe5/y9QDwCqoJgPnqoRz5m/wr2b2/t/5YALYeej9H2Ja14wDYfmJR3jt2yz01HwNgx+mvAGjfcjoAG7c/l+80bLrGavu3dlnbAscVQuTNdu2wKRPaUX/t7DtruxbtuvgjkHXNgqxrkm2dd2AokHUNsV1Tbr/uZWcxJ9m9dxTWVm5lSQfAy78yAAaTLwCZKadzxLGlY4vjjKP9cbQtu9vDZQ97+zZHYR3FtajMPMMVFWVyrVVKmYqwMMIhqcsKIYQQQriJtGgJIYQQnsrg4l2HBhmj5W5S0RJCCCE8lDIaUC5UtFyJK/JHug6FEEIIIdxEWrSEEEIID6WM2uJKfOFeUtESQgghPJRUtEo+OcRCCCGEEG4iLVpCCCGEh5KZ4Us+qWgJIYQQHkq6Dks+OcRCCCGEEG4iLVpCCCGEh5IWrZJPKlpCCCGEh5KKVsknFS0hhBDCQ1kNYHWhsmSVsfBuJ3VZIYQQQgg3kRYtIYQQwkNJ12HJJ4dYCCGE8FBWo+tLYZnNZt544w3q1atHREQEMTExbNy4scDpnD9/npEjRxIeHk5YWBh9+/bl5MmTucZZvnw599xzD+Hh4TRp0oTZs2cXaR4nTpzgiSeeoGbNmtSqVYvQ0FCGDh3KqVOnCrx/0qJVQLsvb9Zft6jcBQCDyVdbYUkDYNfFH+22G32C9DiZNy8C0KxCWwC8/CvfChMAQPrFvQCY/CvpcSw3LwFgvvK7XVmMPoF27++p+Zj+2iuwJgBtGj13K41EAH459pnTfdtx+iu79xu3P+c0bF7WLmtb6LglWbfHf9Nf/zAvCoBO3b8E4KfvexVLmYT7RFd7EACLOQmw//4XVPbv5+3ftduvJcqSDmRdSxzZeW61XbqWtCt5lsGWnu36Y/IJdho2I8X+B8VWJkds5bexHaeWtePs8su+zVZuqzk5z/RvL7ft7+2fh6PPx2jyc5hGbm5Px1l+juLkJ/3SID09nR49enDhwgXWrl1LrVq1WLZsGV26dGHhwoXExsbmK52EhATatWtHmzZtOHDgAD4+Pjz33HNER0ezadMm6tWrlyPOxIkTmTlzJt988w0xMTEcOnSI9u3bs2/fPt5//32X8zhy5Aj33nsv9913H3v27KFixYpcvHiRuLg4oqOj2bp1K+Hh4fk+VtKiJYQQQngoW9ehK0thjB8/nvj4eObOnUutWrUAiI2NpXfv3gwZMoSEhIQ807BYLMTGxmI2m5k7dy7+/v6YTCamT5+On58fffr0ISMjwy7OypUrmTZtGpMnTyYmJgaA+vXrM3XqVGbOnMnSpUtdzmPcuHFYrVa++OILKlasCEDlypX57LPPuHjxIhMmTCjQsZKKlhBCCOGhlIvdhoWpaB0/fpwPPviAhg0b0rJlS7ttgwYNIjU1NV+VkUWLFrFr1y5iY2MJCAjQ15tMJuLi4ti3bx9z5szR11utVl544QUMBgNDhgyxS6t///6YTCbGjRuHxWIpdB4AP/30E5GRkXbhAUJDQ6lYsSL79+/Pc9+yy3fXYUGayQrCYDDw559/uiVtIYQQQhStJUuWkJmZSZs2bXJsa9WqFQArVqzg8uXLVKhQwWk6CxcuBHCYTuvWrQH49NNPGTVqFAA7duzgyJEj1K1bl8qVK9uFDwwMpFGjRuzbt481a9bwt7/9rVB5AAQEBPD777+TnJxMUFDW0B+r1UpqaipNmzZ1uk+O5Luidfz48QIlnF8Gg0ziIYQQQhSGMiqUUbkUv6BWr9bGBzpqgAkJCaFGjRqcOXOGLVu28PDDDztMIzU1lfXr1ztNp3HjxgDs3r2ba9euUa5cuVzztcXZt28f8fHx/O1vfytUHgAPP/wwc+bM4cknn+Tzzz/Xw3///feYTCamTJniMH9n8t1oGBERgdVqLfLFXS1lQgghRGlXVHcdJicn2y3p6c5vTti9ezcANWvWdLjdVmHZs2eP0zQOHjxIWlqa03RsaSil2LdvX6HyLUweAFOnTiU0NJQFCxYwduxYrFYrFy9eZNq0aaxbt87hAP3c5LtFy10tT9KiJYQQQhSv0NBQu/dTpkzhpZdeyhEuLS2NlJQUIKuicrvgYO1u1sTERKf5Xbp0SX/tKB1bGtnTscXJb76FyQOgatWqxMfH06VLF2bOnMnp06cJDg7mf//7H+XLl3e6T87ku6KlVOGbJosjXSGEEKK0c3UuLFvcU6dO2Y1H8vX1dRj+8uXL+usyZco4DGM0aonaWpMKk44tjezp2OLkN9/C5GETERHBwoULWbJkCfPnz+fatWtUqFCBt956yy5efuQ7dPaBYkXJXekKIYQQpZ3VqFxeAIKCguwWZxUtHx8f/bWzhhKz2Qxo47WcySsdWxrZ07HFyW++hcnD5scff+Tbb7/lvffeY/PmzVSvXp23336b/v37Y7Vane6XI/muaD377LMFSvh2n332mVvSFUIIIf6qbA+VLvRSwNE7ISEhegXmxo0bDsNcu3YNQJ+DypGqVavqrx2lY0sjezq2OPnNtzB5AGzZsoXevXvr9ZNGjRqxYcMGqlSpwpIlS3jzzTed7pcjd2QercTERJ588sk7kZUQQggh3MRkMtGwYUMAzp496zDMhQsXAHKdBiEqKkofo+0oHVsaPj4+NGjQAIAmTZoUKN/C5GG1WhkxYgQtWrSwG9dVt25dVq5ciZeXF2+88Uau3aK3c7mi9fPPP/OPf/yDhx56iM6dO9OpUye7pV27djRs2LBAhRJCCCFE3oqq67AgunfvDsCBAwdybEtMTCQpKYmAgADatWvnNI3y5cvrk506Sufo0aMAtG/fXp84NLd8s8fp0aNHofM4dOgQv//+e455ukCbd+uhhx4iOTmZQ4cOOd2327n0rMP//ve//P3vfwfyHtQudxcKIYQQRauoBsMXxLBhw/j3v//t8AHSW7duBaBXr15Ox3nZjBgxgl9++YWNGzfSu3dvh+n0799fX9elSxfCwsI4ePAgly5dolKlrGcCX7t2jYMHDxIWFqZPRFqYPGzjtk6fPu2wzJGRkYD9+K+8uNSi9fLLLwPQrVs3lixZwrp164iPj7dbfvrppwJP7iWEEEKIkikyMpIRI0awf//+HHNlzZs3D39/f7vf/fj4eFq1apXjgc+DBg2icePGLF261K7Xy2w2s3jxYqKiohg4cKC+3svLi2nTpmG1WvUZ320WLFiA1Wrltddew2QyFTqPJk2aEB4ezvbt2zl27FiOff/ll19o0KCB3n2aHy5VtK5du0aZMmX4+uuviY2NpWPHjsTExNgtHTp0YMqUKVSpUsWVrIQQQghxG6vB9aUwpk+fTosWLRg1ahRXrlxBKcXMmTNZtWoV8+fPt5uM/O2332b79u1MmjTJLg1vb2+++OILMjMzGTduHJmZmaSmpjJ06FCsVivLly/H29vbLk7fvn0ZOXIkU6dO1ScZ3bRpE5MmTeKZZ54hLi7OpTyMRiPz5s3D29ub2NhYjhw5AkB6ejoTJkxgz549zJ8/v0DHyqWKVteuXQkODs5xIBw5fPiwK1kJIYQQ4jZa16ErY7QKl29AQADx8fG0bt2a6OhoIiMjWbduHTt27MjRRRcXF0fZsmV5/PHHc6QTFRXF1q1buXDhApGRkTRt2pRy5cqxd+9epzOwz5o1i5deeol+/foRERHB+PHjmT9/Pu+8847D8AXNo23btmzfvp277rqLtm3bUrNmTe666y7OnTvHr7/+SnR0dIGOlUG5MGPo8ePHadOmDStWrNAfJOlMt27d+OGHHwqbVbFKTk4mODiYxuVbYTJkDWsz+WizyiqL9qgCk7/WX2y5qc1Ga7VozZRe/lmD6mxhLeYkALwDtdl4fcrXB8B89ZBdWgBbD9k3t9rcU/Mxu7DbjnycI0zryJFOt+WlVfgQAH459pnd+s4fZL1eV0JuJm25POtxEdt75z4u4E7p9rY218oPz2ZdyTp1WQxAZrLW/79x+3MA3Ft/LJD1WduOPYDBpO1P+hVtMGdw1BMArN8wzC6/jh2znskVHz8IgPuaTATAr6Y2ZiH12I92+WTXtqk2FGDzHsdd/dHVHgRg57nVDrc70qxC2xzrdl/enK+4tvIApCfuBcBqTgZg18Uf7dL3r6rtn9G7rB7Hth8tKnexi2PjaH9sYZ25Pd+C7E9ubi9jbmWzXVduv/6UvSvrxy3tgvaoEtv33pbe7Yw+WRNUbj+xCICWtePs3js7fo7Kf3vZbOlnpJzSw9q22a5btuuLLY3br6PZ8779fLId+9zOTUfnoKM0HMWxbcsrjdvDWlQm+6/+QlJSkt0koEXJ9rv064EWlC1ryjuCE9evW2jeaJdby/pX51KLVp06ddi0aRNvvfWWPiX/7ZRSbNmyhfj4eFeyEkIIIcRtlIvPOVR3ZJKnvzaX7jpUSrFixQr2799v98wgIYQQQrif1aCwGgr/KDtX4or8cami9eyzz/Lee+/l63mFMr2DEEIIIf5qXGo0tI28f+qppzh16hQWiwWr1Wq3WCwWfvzxxwI/hFEIIYQQubMYXV+Ee7nUouXn50dISAjvvfee0zAGg4FOnTrRpUvug0yFEEIIUTDFMWGpKBiXDvGoUaOwWq356jpcvny5K1kJIYQQ4ja2MVquLMK9XKpoTZo0iR49erBo0aI8w9avX9+VrIQQQgghPI5LXYebNm1i+PDhvP/++wQHB1O2bNkcYTIzM9m+fbvTp23fKZmZmSxZsoRvvvkGLy8vatasyYgRIwgLCyvWcgkhhBCF5eo4Kxmj5X4uVbSGDRumPwvof//7X5EUyB1+/fVXBg4cSP369Xn33XepXbt2cRdJCCGEcJmVwj9GxxZfuJdLFa1//etfPP7441SrVo3atWs7fFJ3RkYGhw4d4urVq65kVWj/+9//6NevHy+++KI83FoIIYQQd5RLFa0BAwYwe/Zs4uPjc52+4dKlS8XSRbdhwwb69u3L8OHDpZIlhBCi1LG62HUodx26n0sVLaPRyMsvv0xmZiY+Pj5Ow1WqVIkZM2a4klWBXbhwgUcffZRq1aoxffr0O5q3EEIIcSdYDS52Hcpc4m6X77rsn3/+6XB9hw4dcq1k2QwfPrxA6brqxRdf5OrVq4wfPx4/Pz+35CGEEEIIkZt8V7R69OjhlgK4I93Tp08zb948fH19iYyMZOTIkcTExBAaGkqXLl346aefijxPIYQQ4k6zGFxfhHvlu6KVn0lJC8Md6S5fvhylFD4+Pmzbto3XXnuNDRs28Mknn7Bz5066du3KF1984TR+eno6ycnJdosQQghR0thmhndlEe6V70PsrodCuyPdDRs2ADB06FAmTZpExYoVAa31bPr06VitVkaMGMGlS5ccxp82bRrBwcH6EhoaWuRlFEIIIUTpl+/B8BcuXGDYsGFF3gJ18eLFIk0PtK5DgBo1auTYNmDAAJ577jmSkpJYunQpTz75ZI4wEyZMYNy4cfr75ORkQkNDMRr9MBqzDpmypDvMf9fFHwFoVqEtAAZT1rQXVrPWOrb78mYAWoUPASAjOUH7m3IqR9q2ML8c+wyA6GoP2oXZcforAO5rMlGPs2Xf6wBsO/KxwzLmhy2/263LecjumO5/PwLA959G2q3f3jvn1CJ3SsdPtL/xI7S/99YfC4Dxn+8C0K3/Tj3szaG9ASj7zR67NLYeet/uvVdgdf11RpJ2btjOmQ5tP3JYDlNQVadlTDu9Dcg6Z9q31G4Q2bj9OT2M0SfAafzsbOcfwM5zq4Gsc91WxttlX986ciSQdW7a4hpN2lhK2/fHK7imHseSdhmAzJTTDtP3qxatbU/O2t6mkbZvXoE17cpt9AmyK3t2Jv9KWn43tX/CbN/d27/rzvYzuxaVu9jtj+09gH/1dgBYM67blcnGJ6RBjvS8gyPs3t/+3e7U/Uv9tVeAdv7Yrh22fW1ZO+5WWtpd4JkpWRNJ246Pb6W77d7b8rXF9QrMuq4qixmAMqGdAUg9te5WGO2YewfVuRUuPVsc7bV/9dZAzs/fJvsxsR07L//KdmFscb0DQ+3eQ9ZnZPIJtovj7LqdPZ/8fL6355P9O5CcnExwcHBu0YqMq91/0nXofvmuaF2/fp25c+cWeQHc0aJl6+oLCgrKsc3f35+OHTuycuVKDh486DC+r6+vwznBhBBCiJJE7jos+fJd0YqPj3dnOYpUpUqVOHz4sNOxVTVrav9tWa0yJ64QQgjPZTEYsLjQYOFKXJE/+a5oxcTEuLMcRSo6OpotW7Zw4MABh9tt0z3cddddd7JYQgghhPiLKZX3G/Tr1w+AtWvXkpmZmWN7QkICRqORRx555A6XTAghhCg6tq5DVxbhXqWyotW6dWseffRRzp49y4IFC+y2Xbx4ke+++44RI0ZQp06d4imgEEIIUQSst7oOC7tYpevQ7UplRQtg7ty5REVFMXbsWDZt2gTAlStXGDx4MM2aNePdd98t5hIKIYQQorQrtRWt4OBgNm3axKBBg+jTpw916tShU6dOtG/fnnXr1sljeYQQQng8mRm+5HPpodIlXbly5fjggw/44IMPirsoQgghRJHTxlkVvrYkY7Tcr9S2aAkhhBBCFLdS3aIlhBBClGYyj1bJVyQtWhs2bOCpp56if//++rr4+HjefPNNzp07VxRZCCGEEOI2FgwuL8K9XGrRUkoxfPhwPvvsMwAqVKigb+vYsSMGg4H77ruPt956i969e7tUUCGEEEIIT+NSi9bbb7/N3LlzMRgMVKlSBZPJZLe9Q4cOvPjii/Tr148ff/zRpYIKIYQQwp711lxYrizCvVyqaH366ad069aNs2fPcvbsWcqVK5cjTNeuXbFarbz88suuZCWEEEKI21gwurwI93Kp6/D8+fP88ssvegXL4KBmbLFYAPj1119dyUoIIYQQt7G6OBheWrTcz6WqbJ06dRy2YmW3YsUKAPz9/V3JSgghhBDC47jUotWqVSu++eYbHnroIYfbd+7cyauvvorBYKBz586uZFUiWS1pdu8N5mSH4ZQl3WkalpuXtL/mJACMJm3G+h2nv9LD3Ft/rF2cnedWO0xry77X9dcta8cBkJFyCoDdlzc7LUN+de27DYC1S1q7nBZA23lWADY/nv/6/vefRhZJ3vlV7ejPAPgGXQTgeOVHcoSJH2H/3rfK3QCsH6iNWex0PVrfdrr+HwDUX54CQNfH1gOw9qsOAHR+4GsAytTtpsex3LgMwP3jtDIoiznPcrdvOV0rS7UWANw4sgqAX4595jTOxu3PAdCichcg6/y2nTvOzrvsYWyaVWhrt9723lFYm10X7cdxGr0D9NcmP+1GG9v3xZaed2AoAF7V6mvhytfMipOYAEDG1WNA1r63azHN6X5sP7EIyPr+2N7npnXkSADSrxwAsvbP5F8JgHtqPpZj/7r13wmA+cxeu/27Pd9OXRbrcQIbajcUZVw8CGSdK+lndwPgX6+7Hnbz970A6ND2I7t0bOl2H6qlkbp3pR7HO/Jv2gtLBpB1nvnXbg9A2mnt+5/93LSmadc8yw3tcwmocz+QdS7Z8jWYvPU46lb63jWaAuB7QSt/Zspp7X3FJtp+Je7LKltwhPY3qI6WX9rlW2lp11bbsbadHwDR1R4kO6NPUI4wt7N9Rrefvza5XUeL4hpbGFaMWF1oM3Elrsgflypa//rXv2jbti2HDh2iVy/ti202m/njjz9YsmQJ7777Ljdv3iQwMJBXXnmlSAoshBBCCI3Mo1XyuVTRqlmzJitWrKBv376MHz8epZRdF6FSimrVqrFkyRLq1avncmGFEEIIITyJyzPDN2vWjN9//50VK1YQHx/PyZMnyczMpFq1arRv355+/frJ+CwhhBDCDVy9c1DuOnS/InkEj5eXF7GxscTGxhZFckIIIYTIB6lolXwuHeGHH34432FXrVpF3759eeyxx/j000/1aR+EEEIIIUorlypahw4dwmKxsHXrVpYvX87KlStJSEjIEW7hwoU88sgjVK5cmalTp3LixAnatWvHtWvXXMleCCGE+EvLNJhcXgrLbDbzxhtvUK9ePSIiIoiJiWHjxo0FTuf8+fOMHDmS8PBwwsLC6Nu3LydPnsw1zvLly7nnnnsIDw+nSZMmzJ49u8jzyG7Dhg2MGDGCXr168dxzzxEfH5/vuC51HZ45c4bq1auTmJhot75Dhw58/PHH1K1bF4B33nkHgPHjx1OzZk2mTp3Kiy++yKOPPlqgwgohhBAiixWDS91/1kI+VDo9PZ0ePXpw4cIF1q5dS61atVi2bBldunRh4cKF+R5KlJCQQLt27WjTpg0HDhzAx8eH5557jujoaDZt2uTwRrqJEycyc+ZMvvnmG2JiYjh06BDt27dn3759vP/++0WSh83FixcZPnw4x48f56OPPqJNmzb5P0i3uNSidfPmTS5duoRSivLly9O0aVPuvvtudu7cSZs2bfTa4h9/aHMHVatWTY/7zDPPsGHDBpYsWeJKEYQQQoi/rEyMLi+FMX78eOLj45k7dy61atUCIDY2lt69ezNkyBCHvVu3s1gsxMbGYjabmTt3Lv7+/phMJqZPn46fnx99+vQhIyPDLs7KlSuZNm0akydPJiYmBoD69eszdepUZs6cydKlS13Ow+bw4cO0bNkSq9XKtm3bClXJAhcrWqDddbhu3ToSExPZtWsXv/76K+fOneOxxx7Tn2948+ZNALuHTlepUoWqVasyb948V4sghBBCiDvk+PHjfPDBBzRs2JCWLVvabRs0aBCpqalMmDAhz3QWLVrErl27iI2NJSAg2wTFJhNxcXHs27ePOXPm6OutVisvvPACBoOBIUOG2KXVv39/TCYT48aNsxsDXtA8bM6fP0/37t2pWLEiy5cvp0yZMnnujzMuVbRMJhPff/89HTt2tFtfpkwZZsyYwc8//4xSCqWUXSXLpmzZsvIMRCGEEKKQLJhcXgpqyZIlZGZmOmzhadWqFaA9fu/y5cu5prNw4UIAh+m0bq09geTTTz/V1+3YsYMjR44QERFB5cqV7cIHBgbSqFEjzpw5w5o1awqdB2hzgPbu3ZuTJ08yb948/Pz8ct2PvLhU0apatSoVK1Z0uC0lJYWMjAysVu0xK47m0kpOTubq1auuFEEIIYT4y8rE5PJSUKtXa4/jCg8Pz7EtJCSEGjVqYDab2bJli9M0UlNTWb9+vdN0GjduDMDu3bv1G+dyyzd7HNvY78LkATB//ny2bNlCbGwsjRo1croP+eVSRat27drMmDEjx/qjR48SGxvL3Xffrfd93v7w6cTERC5cuEBwcLArRRBCCCGEi5KTk+2W9HTnz+jdvVt7PmXNmjUdbrf93u/Zs8dpGgcPHiQtLc1pOrY0lFLs27evUPkWJg+AqVOnAtClSxf++c9/cv/991OrVi2io6P56KOPUEo53S9HXKpojRs3jnHjxtGgQQN69+5N7969ueeee2jQoAGBgYGsX7+eadOyHuCalJSkv54/fz4A99xzjytFEEIIIf6yimowfGhoKMHBwfqS/bc7u7S0NFJSUoCcDSg2tgaU22ckyO7SpayHeztKJ3sjjC0dW5z85luYPPbs2cPRo0cxGAxs3bqVwYMH89133/HDDz+Qnp7O6NGjGT16tNP9csSl6R0ee+wxpk6dypQpU/Q7C0G782DhwoUsWbKEYcOGAfDEE08QGxtLp06d8PLy4l//+hcGg4GhQ4e6UgQhhBDiL8tayHFWWfG14T2nTp0iKChIX+/r6+swfPZxV84GiBuNWuXN1ppUmHRsaWRPxxYnv/kWJo8NGzYA0KRJE7tB8vXr1+fLL7+kQYMGfPzxxzz88MM88MADTvcvO5cfwTNx4kT69u3Lt99+i9ls5t577+Xee+8FYMCAAbRv356TJ09y3333cePGDZ555hnmzJmDUorY2Fh69erlahGEEEII4YKgoCC7ipYzPj4++mtnXWhmsxnQxmsVNh1bGtnTscXJb76FyeP06dMA1KhRI0f4u+66i86dO7N27Vrmzp175ypaABEREYwZM8bhttDQUEJDQwEICAjgk08+Ydy4cSQkJNCtW7eiyF4IIYT4S8pUJkyq8C1amcpaoPAhISH4+PhgNpu5ceOGwzC2geXObpYD7WY6mxs3buQYr519cLotnapVq/L777/nO9/C5JGcnAzgtNL54IMPsnbtWg4ePOhs13IokopWfgwfPlyfIr9+/frUr1//TmXtdrsvbwagReUudn+NJu2WUGXJGlRotdg3pdq22dJoWTsOgDaNntPDGExarTy62oO33vva/d1+YlGOMtnW3Vt/bOF2yoG1S1rnWNd6iXazw7a+3gVOb/PjRfcw06arsr54e/6mzZVS5+JKABoF7wVgte+UAqd7rm7eE9TVOr8KgJNV/waAX+vHAGicNBeA/aOfyBZam4G4/WktTpn2Q+zSWrdGe35ox46f6+vMw/oD8NNA7WLaqYt2W3P3Mdp/XhlHfgHAu1YTPY5/BW3gZ/qfPwPwy7HP7PK5p6ZWRq/ArAGiaZe0qVZ8guvaxbGdz7Zz13auAjSr0DbHOsg6921xC+OnH/vpr1uFD9HKVl67blhuamMv/Kq0AMDgp33mBu+s7g5vv0AA4uMHARBzrzZjdJnmvQG4/5/XAfhuatkceXsHhwFwX5OJAGzZ97rTcpaprU1vYzVrF+jWkSPty3br+9uh7Ud6HL8OAwDwLVcJgO8/rO0wbZ+mWcdPpWrnuDGokl2YzbfOmU6zstbd/3/ntPQbaf/MGippcbrGap/T2mXa53b/c1lpqSTtDnB1QxtLGxCk/UgZK2mTUQbWuTtHWbv/SyuTl5+2j9ad2l1mnR/Sbq/3uacHAN6JF/U4GSe1QcfGhlp6Za5pZbTeyBpPA1mfNYBvTW0sr+WaNgm20Uf7vC03tXE1vhUbamkn/anH2XlOu0PNdt00+Wv7arvmZt7UypT9HLVdU21s5/ft728/34tTJkZMLnQdZlKw5w6bTCYaNmzInj17OHv2rMMwFy5cAKBp06ZO04mKisJgMKCU4uzZszkqQbY0fHx8aNCgAaB15/3000/5zrcweVS69V2xVbhuZxtUb5tRIT/c/thui8VCfHy8PvhdCCGEEJ6re/fuABw4cCDHtsTERJKSkggICKBdu3ZO0yhfvrw+2amjdI4ePQpA+/bt9YlGc8s3e5wePXoUOo/o6Ohc87DNqXXXXXc53bfbuVTRslgsTJ06lYYNGxIYGIjJZMqx+Pj40KVLF7uZWoUQQgjhuuKYR2vYsGEYjUaHD5DeunUrAL169XI6oN5mxIgRALmm079/f31dly5dCAsL4+DBg3Z3FILWDXjw4EHCwsL0iUgLk0fXrl0JCQnhxIkT/P777zni2B4t9Nhjj+W6b9m5VNEaM2YMU6ZM4dChQ6SmpuqzwDtahBBCCFG0LC5Wsgpzx2JkZCQjRoxg//79OebKmjdvHv7+/kyZkjVUIz4+nlatWuV44POgQYNo3LgxS5cutbtD0Ww2s3jxYqKiohg4cKC+3svLi2nTpmG1WvUZ320WLFiA1Wrltddes3sSTUHzCAgI0Mv+1ltv5dj3+fPn07hxY7vKWV5cqmgtWqSNA/rXv/7FyZMn9Zngb1927tyJt3fBx/AIIYQQwrlM5eXyUhjTp0+nRYsWjBo1iitXrqCUYubMmaxatYr58+fbzcT+9ttvs337diZNmmSXhre3N1988QWZmZmMGzeOzMxMUlNTGTp0KFarleXLl+eoO/Tt25eRI0cydepUfZLRTZs2MWnSJJ555hni4uJczmPs2LEMGjSIefPm8f7776OUIjMzk4kTJ3Ly5ElWrFiBl1f+j5tLg+HLlStHmTJleOmll3IN17x5c71vVQghhBCeLSAggPj4eCZPnkx0dDRGo5GoqCh27NhBkyZN7MLGxcWxceNGBg8enCOdqKgotm7dyosvvkhkZCTe3t5069aNvXv35nieoc2sWbOIioqiX79+pKenU6VKFebPn0/Pnj0dhi9MHp999hl33303//nPf3jttdeoWLEi7dq1Y+/evVSpUqVAx8qlitazzz7LpEmTMJvNdvNVOOJsllkhhBBCFE4mJowu3XVY+Lhly5ZlxowZDh/Fl92AAQMYMGCA0+2RkZF8+eWX+c7XYDAwZswYp9NKFUUeRqORZ599lmeffTbfcZym5Urkp556iri4OD788MM8w3bu3NmVrIQQQghxm0xlcnkR7uVSi9b8+fO57777+Oijj7BarQ4nJ8vMzOTnn3/m4sWLDlIQQgghhCi9XKpovfvuu/pgtF9++cVpOKUUBoPBlayEEEIIcZtMjC52Hbp9Os2/PJcqWpMnT6Z3797ce++91KlTB29v7xwVqrS0NH799Vd9YjAhhBBCFA2LC3cOavFljkt3c6mi9dhjj9G1a1e+//77XMOlpaUVeJS+EEIIIYSnc7nN8PXXXyczM9Pp9j179mA0Glm6dKmrWQkhhBAiGxkMX/K5/FDpFi1a5Lq9bNmydOjQgZUrV7qalRBCCCGyseCF0YWfcksBHyotCs7litaVK1fYsmULSUlJOZ5mbbVaSUxMZO/evQwaNCjPLkYhhBBCiNLEpYrWjh076N69O0lJSbmGU0rx66+/upKVEEIIIW6TqUwYXOj+k65D93OpovXyyy+TkpJCTEwMNWvW5KeffqJr1652Yb799lt69erFoEGDXCqoEEIIIexlKqOLFS2Z3sHdXKpobd++nR9++IEOHToA8NprrxETE0Pbtm31MHPnzmXDhg20bt3apYKWBFZrGl7eFbJWWNLsthtMvnbvlSXd7i+AyScYgBaVu2hp3paGV2ANAH4+MF1fd2/9sQDsPLcagFbhQwD45dhndnHvqflYVj7+lQDITDmdx17l7b4mEwEwepcFoMy9WZXmbf+pCUD0V9p+7HzMzy5u91ez9v37ydrxaTtP62Iuc1EB8MPzplzTcKTu5jMAHG2rHa/y5wJyhDle+ZFbrx7Jse121U78BMC52p3yDHu7k1X/BkD31zMAOH3rIQgHgp/IEXZlhvY98Kv3EQDfTbef5LfTLO2vb4se+rrrZbR0u72tTZ2iLNr7zOP77OIaygbrrzPraJ+/bxntM+vWfycAP3wRDYDVnHwrrXScsZ1Puy7+CECzCm1zhNl9ebPde1sY78BQADJSTuUI17K29tDX7ScWOcy3U5fFAPz0Yz99na2cJv/yt/7eOr9vnNcC+Pprf1Ov63EMDRoB0KGtdqx967YHICVGe9jt8bt/v5XfAT2OLU/voFpaPkHVAYi5930ANmwdm6O83rXu1v5e3GcX17eBdiKoG7da/E1Zl1tVRjvHT7cPAqDL+9p3wevk5VuJag+5PZF1GlD9UG0A1j2p/Y2Zrezi/jQ2+9Q61QDoOkPbtvZpbVvtndrd33W2HwOgbJes61mN+FvnYkQYABca3wSgwkntHLoUpu1H9VM/6nF8HtKOpcGq/VjfldEKAKOvVv4k7VAQdDIsK06Ils+VRlqckLRb18LTCdqxuXENyDr2AMaAEC0fk5auJVn73L0CtTDe1aK0cKc2cDuvQO0a5VtF+5xs51LmTW0Sbdv5DRBd7cEc8SHr/HX0HShuFrwwuDRGy+URRCIPLlVlAwMD9UoWwNChQ5k9e7ZdmEGDBrFy5UpmzpzpSlZCCCGEEB7HpYpWcHAwiYmJ+vtq1aqhlGL37t1ZGRiNeHl5MX36dEdJCCGEEKKQLMrk8iLcy6U2wx49etCqVSvat29P8+bNeeqpp5gwYQIPPvggM2fOpFatWrz99ttcuXIlxx2JQgghhHBNpjKBDIYv0VyqaL344ousXr2aefPmsXjxYv7xj39Qv359/vGPf/DQQw/ZPY7nscceyyUlIYQQQojSx6WKVlBQENu3b+f7778nNDQUk0mrGT/77LOUK1eOjz76CKvVSvfu3fnnP/9ZJAUWQgghhMaivDC49KxDGQzvbi4d4QsXLrBmzRoefvhhKlSoYLdt2LBhDBs2zKXCCSGEEMI56Tos+VwaDN+tWzeGDx/OM888U1TlEUIIIYQoNVyqaF26dAmAhx9+uEgK427ffPMNBoOBzz77rLiLIoQQQrjMqowu3XFolQlL3c6lIzxjxgxCQkLo2bNnnmEjIyNdycplly9f5u9//3uxlkEIIYQoShbl5fIi3MulilafPn346quvePLJJ/njjz8chklLS+PDDz/k2LFjrmTlslGjRpGSklKsZRBCCCHEX4tLVdng4GC98jJnzpwiKZA7LFy4kAsXLvDoo4/y+eefF3dxhBBCiCJhcXEwvExY6n4utWj9/e9/RymVr6W4nDlzhokTJzJv3jyMRumLFkIIUXrIzPAln0s1j6effpqQkBAOHz5MRkYGVqs1x2KxWFi7dq3d5KV30rBhw5gyZQphYWF5BxZCCCE8iFWZXF6Ee7nUdVizZk2efPJJ6tat6zSMwWCgc+fOxTIz/KxZs/Dz82Po0KEFipeenk56err+Pjk5uaiLJoQQQoi/AJdvN3j55ZfzFW7p0qWuZlUgf/75J//+97/Ztm1bgeNOmzYt3/slhBBCFBeLMro4RkuG1Lhbqbyv02q1MnjwYN59910qV65c4PgTJkxg3Lhx+vvk5GRCQ0MBsJiTnMbbeW41AC0qd7FbbzD56q+NPkEAbD+xyC5MdLUHAQiM+FuOdDOS/rR771O+nt37VuFDANhx+it9XevIkXZlKgzbfvhXbwfApl0TcoTp/o8TWj4f1tbev54BwPcTvW8VPjNbaO04bH7c8Rf7WuXLt17V0Ne1S30XgAs74gA4HFMVgKNta9jFjR+R9VotbgGAod8uxzt2S7WjP+uvz9XtZLft3hvvA1DZOxGA//m84jSdxklzAdg/8QkAIhJ/BGCs+g6A5afj9LBnQ7WK/3vtHKf102jtb/dXy+rrLtQ5DsDNQO1crr5FOxeN1bWW5O//UxOAjp9kpWPx1sZFlvHxAcDaUjsmXXqu1eLeOg+3HflYj2M7j0z+FQFQFq1Vt2Vtrfy7L28G7M9v27ltO8+MJj8t39AYAK4fXp5jH30rNrF7b0vX5qcf+wHQ+YGv9XW28tp4B2tDAbyDamnlKBeslblS1hMqLIHa5W395lEAdOyo3QiT8cgWAKJ9LgDwvx+zPltbnr4NOtvlt26NNldg177bbu131qXTEHW3Fuektl+mCnUAuNlG+3w2PqENm2i5PFsreYWrANS8978AHAnpBUC1Klrc82GntLTDdutx7u60CoDG370HQGKHA9qGTO279jJv6mEPZEQAcLS1dkKNVa8CENVYO17pSvvcfr8UrcepekjbZ3Og9t43Zj4AfyS018pi1X7M/y90ph5nflmt3Mk3teNurnar/BHa96bC6RAAksIsepzEtqna8Sl/EgCTuREAQcFRABivXtf+XknU42SeOwKAVzVtmiBl0a4z3LpkGG8dN9t5AVnns+0cNXoH4Ijt2msX9tZ5bNOsQluHcUsCqzLpn01h4wv3KpUVrbfeeov69evna34vR3x9ffH19c07oBBCCCFELkpdRWvfvn189tln7Nixo7iLIoQQQriV1cXpHaRFy/1KXefse++9xx9//EFQUBAGg8FumTdvHgBPPPEEBoOBIUOGFG9hhRBCCBdYldHlRbhXqWvRqly5MvXq1XO47dy5cyQnJ1O1alWCg4OpVq3aHS6dEEIIIf5KSl1Fa9q0aUybNs3htiFDhjBv3jymTZsmrVlCCCE8nlImlAvdf67EFflT6ipaQgghxF+F1WoCV+46dCGuyB/pnBVCCCGEcBNp0RJCCCE8lFJGlAsD2l2JK/LnL1XR+uyzz/jss8+KuxhCCCFEkbBajWAtfGXJ6kJckT9/qYqWEEIIUZpoLVquDIaXipa7yREWQgghhHATqWgJIYQQnkoZXV8KyWw288Ybb1CvXj0iIiKIiYlh48aNBU7n/PnzjBw5kvDwcMLCwujbty8nT57MNc7y5cu55557CA8Pp0mTJsyePbvI88ju9OnTlC9fvlBTQ0lFSwghhPBQymp0eSmM9PR07r//fj7//HPWrl3Ln3/+yZgxY+jSpQvLli3LdzoJCQlER0dz9epVDhw4wNGjR6levTrR0dH88ccfDuNMnDiRJ554gunTp3Ps2DGWLl3KxIkTGTt2bJHlkZ1SiqFDh3Lt2rV871d2UtESQgghRIGMHz+e+Ph45s6dS61atQCIjY2ld+/eDBkyhISEhDzTsFgsxMbGYjabmTt3Lv7+/phMJqZPn46fnx99+vQhIyPDLs7KlSuZNm0akydPJiYmBoD69eszdepUZs6cydKlS13O43YffvghW7duLcjhsSMVLSGEEMJT2SYsdWUpoOPHj/PBBx/QsGFDWrZsabdt0KBBpKamMmHChDzTWbRoEbt27SI2NpaAgAB9vclkIi4ujn379jFnzpysXbVaeeGFFxw+q7h///6YTCbGjRuHxWIpdB63O3LkCG+99RaTJk3Kc3+ckYqWEEII4amKYYzWkiVLyMzMpE2bNjm2tWrVCoAVK1Zw+fLlXNNZuHAhgMN0WrduDcCnn36qr9uxYwdHjhwhIiKCypUr24UPDAykUaNGnDlzhjVr1hQ6j+wsFguPP/4477zzDlWrVs11X3Ij0zsUwObjPxAT9oD+fvflzQ7DGUy+AChLOgBGnyB9m1dgDQDuazIRAO8grcl157nVAMTc+77ddgCLOQmAlrXjAPApXx+A6GoP2uWXndGnLADNKrTNtayO2NK1WtJupaX9F9Cpy2IAfvqxn/PIaWYAur+cqaURUkbf1OV9BcCBbjsB8E2uAMDxluFaPhbtP6uWy9P1ONt7P6Olt0Vr2q0Rsh+AKn9GANDzkcEAzDn/uB5n3t+0C8fPPAbAf06MAaB51U0ArPadAsC5ullfvJYpHwAwKHAVAFsDvrPbrbtXXwfgsQef0NetTukIwPV07TPtcPPfAPh5VQFgxXkt/4aVdmZLqQsAh+/df+t9Y7t8+mc+p70495S+zietjF2YtV91sHvffeQxABIfraCvK39OO+csZ7RtlkjtouTTUPvv0/fEzwDcWz9rTIN/aDsAMpNOA1nnambKGQDuqantT/bzzXbe2uy6+CMAnbp/abfedh4C+IY0whHbeXd7mgBeAdW1vxXq2v+tHAaA8vXRAnpn/XduStX+q73//y5pYStqYUN9vwXgS+/XtO3jr+pxjGW146TSbmjva2vnWfc3tPN57RLtwnz/hCQ9TmJ9LZ+KiZ0ASIoOASC9zE0A6l9dAUBKZDM9TvtG/wXg1+vaOv+I7dr6Fq8AcMCs7d+ew4/pccakHgJgWeXzAEyNsP8Pu+uxm/rrcyEnAHgkRIvvh/a9fDXlG60stz7C1ypn/ed/tGU9ACxe2ndtfMBKAN6sop0HnSqsA6DljbN6nJ/8TwHwRNmPAZhesbOWRlPtPPA9pF0rTjX6U48T1khL98jR+7Wy1tUGJKeEaOdvQFIgAMEHfPQ4JrN2TbBe1s5F7/raeWw+t1cLUEmLa/Quq8fxDtI+b0ua9mNvTbsGZJ2/Jp9gu/cAJv9KQNa12/ZX2Fu9WvuOhoeH59gWEhJCjRo1OHPmDFu2bOHhhx92mEZqairr1693mk7jxtq1cffu3Vy7do1y5crlmq8tzr59+4iPj+dvf/tbofLI7s0336Ru3br06tXLpTk4pUVLCCGE8FTF0HW4e/duAGrWrOlwu63CsmfPHqdpHDx4kLS0NKfp2NJQSrFv375C5VuYPGz27t3L3LlzmTlzptN9yC9p0RJCCCE8lXLtodLcmuw0OTnZbrWvry++vjl7S9LS0khJSQHI0QJkExystRYmJiY6zfbSpUv6a0fp2NLIno4tTn7zLUweoE1b8fjjj/PJJ5/YhSksadESQggh/uJCQ0MJDg7Wl2nTpjkMl33cVZkyZRyGMRq1qoWtNakw6djSyJ6OLU5+8y1MHgD/+te/6NSpEx07dnRa/oKQFi0hhBDCU1kNLj3rEKsBgFOnThEUlDWe2FFrFoCPT9bYOaWUwzBmszYmMCQkxGm2eaVjSyN7OrY4+c23MHn8/PPPrFmzhu3btzste0FJi5YQQgjhoQxWk8sLQFBQkN3irKIVEhKiV2Bu3LjhMIxtYs+KFSs6LXf2u/gcpZN9clBbOrY4+c23oHncuHGD4cOH89lnn+Hn5+e07AUlFS0hhBDCQxmUyeWlIEwmEw0bNgTg7NmzDsNcuHABgKZNmzpNJyoqCoPB4DQdWxo+Pj40aNAAgCZNmhQo34Lm8dVXX3Hw4EFatGiBwWCwW554QrvjfN68eRgMBurUqeN0324nFS0hhBBC5Fv37t0BOHDgQI5tiYmJJCUlERAQQLt27ZymUb58eX2yU0fpHD16FID27dvrE43mlm/2OD169ChUHoGBgdSrV8/hYmsdCwoK0p/tmF9S0RJCCCE8ldXo+lJAw4YNw2g0OnyAtO1RNb169XLa/WgzYsQIgFzT6d+/v76uS5cuhIWFcfDgQbs7CkHrBjx48CBhYWH6RKQFzePRRx/l0KFDDhfbzQG2MOvWrct137KTipYQQgjhoYpqjFZBREZGMmLECPbv359jrqx58+bh7+/PlClT9HXx8fG0atWK999/3y7soEGDaNy4MUuXLrW7689sNrN48WKioqIYOHCgvt7Ly4tp06ZhtVr1Gd9tFixYgNVq5bXXXsNkMhU6D3eQipYQQgghCmT69Om0aNGCUaNGceXKFZRSzJw5k1WrVjF//ny7mdjffvtttm/fnuN5gd7e3nzxxRdkZmYybtw4MjMzSU1NZejQoVitVpYvX463t7ddnL59+zJy5EimTp2qTzK6adMmJk2axDPPPENcXJzLeRQ1md5BCCGE8FAGiwmDpfATlhY2bkBAAPHx8UyePJno6GiMRiNRUVHs2LFDH7RuExcXx8aNGxk8eHCOdKKioti6dSsvvvgikZGReHt7061bN/bu3ZvjeYY2s2bNIioqin79+pGenk6VKlWYP38+PXv2dBi+MHkUJaloCSGEEB7KaDVidGkercLHLVu2LDNmzGDGjBm5hhswYAADBgxwuj0yMpIvv/zS6fbbGQwGxowZw5gxY/Idp6B53G7IkCEMGTKkUHGl61AIIYQQwk2kRUsIIYTwUAarsVAD2rPHF+4lFS0hhBDCQxmU0aXKkkFJRcvd5AgLIYQQQriJtGgVQNs63dh3ZZvT7c0qtAXAOzAUAMtNbUI17+AwPYx3+dxnk7Watecxbdn3eo5trcKHAKCs6QAYTNpkcCb/Sg7SuQ7A7subAYiu9qBWJnOS3XpHfEK0xx2YrxwEwKu8Vv7UYz8A0PmBrKegezfXnm7e8RPtvVeIts10Utv3pEZZdfkrVRMBqHJEe3zDhUa/AtDi+loAfG/2A+Bm1y/0ODX2RwMQVqORlnfDOQBsrNIBgOd/PgfAiVY/6HGSbjWjxySfAuC7SnsBuNvnDwBubLtPOwYNsx4oWsn3IQBCM64BYJ1RD4AXn9NmFa7ZpS4Ata2JepwyplQAMi5on+nEstpnluGvPfLhGcszADzHV3qclillAYisq8Xtnv71rbIdAmDr1UcACHow62GsGeHrAcg8Xf/WmvLYqVIFgOSKWY+YuBmYAkDdPbUBMHvfeqCqSfs8Nu/R5rixnVMAprLVtPyu/gmAd1AtLd+UMzjTonIXAHZd/BHI+g74VWruNM62Ix/bvbfFuf2ctN5MynqdoZ3PXpW1c9FQtpy2/pJWNsOt/Tp5zzU9TuWECgAYQ7T9uvig9uyyFLN23kUkLQOgZmRvPY5vZe3zZtevdmW50Ej7zt0/7goA372TdadS7Z1HAAipoZ0Hl2tc1PJtok1o2K3cTwAsP9dAj5N567En1lvn6vgQ7ZjcfVX73L4or63fXe6CHqfOdgsA1bprx7rv37WZrve8o33GFc9nPUD3zypa2Lo1fwagz1Xt/Aofo322QX208zn4oWQ9Tq97JwJQ2XAVgO4ntGO+sqqWzz9P7wDgRLbH1/1+pSkArdNXafvebjUA/1dhPgBvPqQdJ59LoXqcVIt2jVCmDADSy2nXCi+zdj27XEsrY93UZnqcMlZtH9UV7fujUrXrpE+1uwEwpGrzI5kCs91BZtHS96kSpcUxa985o0+gFufW9dP219k6La00u7e2cxayzltn57G7Ga0mjC50HeJKXJEvUtESQgghPJQ2RsuFrkMZo+V2UtESQgghPJTBYsLowjxayoW4In+kKiuEEEII4SbSoiWEEEJ4KFcnLFXSdeh2UtESQgghPJSM0Sr55AgLIYQQQriJtGgJIYQQHspoMbo4GF7aW9xNKlpCCCGEh5IxWiWfHGEhhBBCCDeRFi0hhBDCQxmtRowudP9Ji5b7SUVLCCGE8FBy12HJJ0dYCCGEEMJNpEVLCCGE8FBGiwGjxVDo+MqFuCJ/pKIlhBBCeCi567Dkk4qWEEII4aGMVgNGqwstWi7EFfkjVVkhhBBCCDeRFq0C2Hz8B7v3zSq0BWD35c12f++p+ZjTNCwpFwHwrngXABmJh+3imPwrAdCm0XN6nJ8PTAfAak4GIO38aQB8KzUFIDPlDADtWkxzmq/B5GtXRpsWlbvor40+QQD4V28DgPnKQQCUORUAv+ottXLcTMpKIC0dAJ992jpDuWC79C/WOqO/VkYLAEmVMgCotq8FADUfWAvA0db/AyA5tbIex7vKnwCcauSnlelmJACdKqzTAhzV/vx64249ziN+2wG4b2Wmlk/ceQDiLmmB+ze/H4AXb36rx/ln2jcA/BKsHf8/lu0GIOrZKgB8njBWK1utID3Oeze/AODBgNYA/O5fEYCnvrkMQJmObwPQ4Li3HucU2jH8sdyTANQ6qW17Nlorv7dROzYprb7T4yzwewuA+OjaANx7oz0A/vO1Mp3teAMAi3eGHsfLbAXgTI9AABLrbQSgztb7AOj+8k1u51Wrkfb38lG79d7BYQBkJCUAoCzpOeLm5fbzDrK+PyYf7ZxpWTsOgDJ1bp2Tlqz9MXqX1V6Ybl2yypTR1levA8CJVtr5p4xWPY7FWwFwM8AMQM2d2rE4zSAAwg6VA+BSRIoep+pJ7X/PS30aAlDhuD8AFxps1bb/qB2Lu1df1+OY610C4FgrrUw3yycC0Lecdl43VccA2Be2To+z6Wx3AOpW2gtA6wvaZ1j3oHY+RHbQvjcjQz/S41hna+dVr17adejiYa0M6bcOSWJVix624g2tleItX+0cva59/fn3cu0aMvBPLd/PqmSdm4Zbhy5d2w3WN9b+1vPSyl/pJe27WGXkXXqccg2069mlLru0Y/GDFvnhE1cA8K2lXZNeYYIeJ8r/EABnMzoC4JVSDoCbwVqc/2v4MgBLDi/S4/hU1j470wXtu0xYHS1uRe07p8poO2i9eVWP4xVUk+yMARW0MOe0z9t2TbRd9yDrGms7x70CtTQsV7Tzy2jSrkNWS5oex3Ye27bdaQaLa9M7WGVmeLeTipYQQgjhoQwWAwYXBrS7Elfkj1RlhRBCCCHcRFq0hBBCCA9lVK4NhjcqadFyN6loCSGEEB5Kug5LPuk6FEIIIYRwE2nREkIIITyUq/NouRJX5I9UtIQQQggPZbBoiyvxhXuV6q5DpRQff/wxd999N35+foSEhNCzZ0927txZ3EUTQgghxF9Aqa5ojRw5klGjRrFv3z4yMzO5evUqX3/9NW3atOGrr74q7uIJIYQQLrF1HbqyCPcqtRWtb7/9lhUrVjBv3jySk5NJS0tj5cqVVKpUiYyMDJ544gkSExOLu5hCCCFEodm6Dl1ZhHuV2orWZ599xtq1axk8eDBly5bFy8uLnj17smiR9liH5ORkvv7662IupRBCCFF4Bqvri3CvUlvRateuHU2bNs2xvnPnzjRr1gyAS5cu3eFSCSGEEOKvpNRWtMaMGeN0W2Sk9mDi2rVr36niCCGEEEXOYFUYLC4sVlXcu1Dq/SWnd0hMTMTX15f777/f4fb09HTS09P198nJyXeqaEIIIUS+udr9J12H7ldqW7ScSU1NZevWrQwfPpxy5co5DDNt2jSCg4P1JTQ09M4WUgghhBClwl+uojV79mzKli3LK6+84jTMhAkTSEpK0pdTp07dwRIKIYQQ+eNSt+GtRbjXX6rr8PLly7z22mvMmzePkJAQp+F8fX3x9fXNsb5tnW6YDFmHbPflzQ7jG32CAFAWrfvRcvOyvs32OvPGObs4trBZ4bKmnmhWoa3D/No0es4ursHkrW8r2/wJu7A7TmvzhkVXexAAk38lu7IC+ITU1/JOu+Jwv278uVpLu9GArHKnpWkvQspr769c1cLeUx2Aet+W1cOeaH8dgHT/VLt0915rDkCfSl8CsOTov/RtLe7+DIAalVYBsCxhCAAPhscDsOheHwAmWv6rx4k6o80Ls+sh7bNa9O16AP7+YCsAXkz5FoD6CT56nOC1t473CO3P7yczAHjg90wADjV6F4C+iUey8vlE29dnJ70JQLhZ+2wN6VpbfJPHtbDprzfQ43gHnQeg3ida2MvbLwLQ6X/a9oG+O7T8ArI+l6aPJ2hxZ2rv/5b5uXYMHogCoGU1bf8ylUmPczKtFgD+Ju1Y9/A/BMBPAVqZy557GADfilF6HKpUBsCnWhNtPwLKAaD++FFLP+Ws9j7buWq1aJ+/7Ry1yTonc36Pbj+fW4UPAbLORUuKdkxM/uX1OJa0W98hb+0zy6gZrIVJ1e5NL3tV+5xOt96gx0n3vwsAc4B23t0M1I7JtRonAai51U+Lmxigx8mopv3vmdhaO98y/NoD4JVcQVsfo5XpYr1f9Th+idq57t/4By2flKoAtLD+qaVvMQMwymelHmdCmXAA7vHfC0C/jNEA7Dv1PgDJBu37ma6yztFdz2hlqG3RztWwfzQE4CXf+wDYXeFuPeyyG7O08pfR3rdfp+1X877acZu/UjsP/lY9697+Pytrr4NvfaWTTf4ARBrOAOAToh2vyyFZfU39grXjtPZPbV25A60B+K2D9uOdadDOSV//rOEXPydrYUIPaJ/PpVoXtH0N0b4bN9Dy8crMOp+t3tp32qusVn51VotjKHfr/a1wypKhx/GqXBcA80ltgmqvChFaHJN2TL2Dw7id0Vu7XqWZtfIafbT3RpPfrfe3vpfmrDi2c9z2t0XlLlismTnSdhur0hZX4gu3+ku1aP3973/n+eefdzo2SwghhBD5YzabeeONN6hXrx4RERHExMSwcePGAqdz/vx5Ro4cSXh4OGFhYfTt25eTJ0/mGmf58uXcc889hIeH06RJE2bPnl2kecTHx9O5c2fKli1LQEAAbdq0YfHixQXeN/gLVbRef/11atWqxXPPPVfcRRFCCCGKRHF1Haanp3P//ffz+eefs3btWv7880/GjBlDly5dWLZsWb7TSUhIIDo6mqtXr3LgwAGOHj1K9erViY6O5o8//nAYZ+LEiTzxxBNMnz6dY8eOsXTpUiZOnMjYsWOLJI8FCxbQpUsXfvrpJ9LS0vSx3XFxcTz77LP53jebv0RFa8GCBfzxxx+8++67xV0UIYQQoujYug5dWQph/PjxxMfHM3fuXGrV0rrlY2Nj6d27N0OGDCEhISHPNCwWC7GxsZjNZubOnYu/vz8mk4np06fj5+dHnz59yMjIsIuzcuVKpk2bxuTJk4mJiQGgfv36TJ06lZkzZ7J06VKX8rh06RJjxoxh0qRJnDt3joyMDHbt2kV0dDQA77zzDj/88EOBjlWpr2h99dVXrFy5kjlz5mAw2D/TyWKxyEB3IYQQogCOHz/OBx98QMOGDWnZsqXdtkGDBpGamsqECRPyTGfRokXs2rWL2NhYAgKyxkqaTCbi4uLYt28fc+bM0ddbrVZeeOEFDAYDQ4YMsUurf//+mEwmxo0bh8WSNfawoHl88cUXvPbaa7zyyitUraqNt2zevDlr1qzRx3YvWLAgH0cpS6muaK1cuZJ58+axcOFCvLzsx/2fP3+eIUOGcOzYsWIqnRBCCOEii9X1pYCWLFlCZmYmbdq0ybGtVSvtpqMVK1Zw+fLlHNuzW7hwIYDDdFq31m6a+PTTT/V1O3bs4MiRI0RERFC5cmW78IGBgTRq1IgzZ86wZs2aQufh4+PD6NGjc4StVKkSjz/+OFDwp8qU2orWwoULiY2NZePGjdSoUYOKFSvqS1BQENWqVWPDhg20b9++uIsqhBBCFI7V6vpSQKtXa3egh4eH59gWEhJCjRo1MJvNbNmyxWkaqamprF+/3mk6jRs3BmD37t1cu3Ytz3yzx4mPjy90HqNHj8ZodFw1KuxTZUplRWv16tUMGjSIzMxMrl27xuXLl+2W69e1273j4uJydCcKIYQQHsPqYmvWrYpWcnKy3ZL96Si32717NwA1a9Z0uN02GfiePXucpnHw4EHSbk0P5CgdWxpKKfbt21eofAuTR24SE7WpVXr27Jln2OxK5TxaDz74INZC1NKFEEKIv6Lbn4AyZcoUXnrppRzh0tLSSElJAXD6dJXgYG1+M1vFxJHs3W+O0rGlkT0dW5z85luYPHLz448/0rhxY7p3755n2OxKZUVLCCGE+CswWK0YXGhYsMU9deoUQUFZEyU7mrQbsBt3VaZMGYdhbF1vttakwqSTvfvOlo4tTn7zLUwezuzdu5fNmzezfv16p12LzkhFSwghhPBUhRzQbhcfCAoKsqtoOePjk/W0AqUcTw1hNmtT5+f2BJa80rGlkT0dW5z85luYPJx55plnGD9+PO3atcs1nCOlcoyWEEIIIYpeSEiIXoG5ceOGwzC2geUVK1Z0mo5t6gRn6djSyJ6OLU5+8y1MHo689957BAYG8uqrrzoNkxupaAkhhBCe6g7fdWgymWjYUHvO5tmzZx2GuXBBexZl06ZNnaYTFRWl34zmKB1bGj4+PjRooD0vtkmTJgXKtzB53G7Dhg2sWLGCxYsXYzKZHIbJi1S0hBBCCE9lsYLF4sJS8G5H22DwAwcO5NiWmJhIUlISAQEBuXazlS9fXp/s1FE6R48eBaB9+/b6RKO55Zs9To8ePQqdR3YHDhxg8uTJrFixwum4sPyQipYQQggh8m3YsGEYjUaHD5DeunUrAL169XI6oN5mxIgRALmm079/f31dly5dCAsL4+DBgzkmDb127RoHDx4kLCxMn4i0MHnYHD58mNGjR7N06VLKly+fY3t+HjFkIxUtIYQQwlMVw4SlkZGRjBgxgv379+eYK2vevHn4+/szZcoUfV18fDytWrXi/ffftws7aNAgGjduzNKlS+3u+jObzSxevJioqCgGDhyor/fy8mLatGlYrVZ9xnebBQsWYLVaee211+y6+AqaB2iVrKFDh7JgwQK7cV4AN2/e5J133uHzzz/P59GSuw4LZPPxH+hULy7PcJkppwHYdfHHHNtaVO4CgNFHu7vDYNJq/MqiTQ5nuanV0nec/irPfH4+MB2AlrXjbqWR9WBMg48fAPc1mQhA+qW9dnG9AqvfelVdX5eRlHBrW43byugNgG/FuwHwqZ/1KAMVfCtM6k0ArGFaeqYMrV88o7K/HtYvRftCJ9U5qK04rz1CwZweCMD6G9p/IeaQ83qcCK+TAFQ2XAUguLz23oL2RdpijQKgvXG/HqfKOe04HKyq3WVivKwd2+/+eAKAAXW2AVBua5Iex3rrCfZBN7VyRw/XHpJ6+dY35J9bTwBw850jehzj/VqYkdu1sm1trKXx47hfAdh36x+uYf/M+n+mWZ0dWtlGVdDKsFHb17YJ2rG5GqTlX9UnRY9TtruWzx9ltabtt69rj4EwXdMuAME1kwG4Yc1q+r63rJbPNUtZANbuHQNA5cj1WtkTtUl7fardrcc50V5bV/WnPwHwC9cm5bPsvQJknavZ7b682e697fy2mpNzhLXxDgy1C2s7z7yDwuzKlPJ71sNhbelZL2nPJvU6eOtCWlM7BuW/186LMw2q6HFq/abN3ny8qdY9UP7crXzStNmdrcHadySxVtZ/xqYM7Vz3OdocAN9UbZ+rHasDwPXy2jEy+KbqcfxuaOdv4qV6AJQpdwaApZaOAGw/0xmAJ+p8rMcxn78LgK1lmtsdm2X9te/LkpWLAEiNWaFvW5SplXecSXtcyNqe2nm+9zttgK7JmnWeJcZ8CMAlP+0ETmimnV8numizY4+O0G57n1WnnB7nk6S+AIQHateB0ebvALhxq1UiM1Y7D09VzrpT67tUrWto/VJtn20/fT96a9/LLde1bhtzYi09jtcV7TMqe0Y711NvXUMiNt4DwH8f1H6go7Zdz3ZktNdpu1YB4NtIO3csf2jXNWOVOgB4V7xLj5F5WfvOmq9qn7/BW/t+mPy0754lTTsGN89v0+MEN9B+cG3XYxurRfuBNpkqafsQmDX5pe16bzFnu56oTO4YWxegK/ELYfr06ezYsYNRo0axZs0aypcvz3/+8x9WrVrFwoUL7WZif/vtt9m+fTu///47Y8eO1dd7e3vzxRdf0KFDB8aNG8f777+P2WxmxIgRWK1Wli9fjre3t12+ffv2JT4+nqlTp9KpUyeaNGnCpk2bmDRpEs888wxxcfa/0QXNY9++fXTr1o2UlBSaN7f/flosFpKTk7FarRw5coT8koqWEEIIIQokICCA+Ph4Jk+eTHR0NEajkaioKHbs2KEPWreJi4tj48aNDB48OEc6UVFRbN26lRdffJHIyEi8vb3p1q0be/fuzfE8Q5tZs2YRFRVFv379SE9Pp0qVKsyfP9/pjO35zePs2bN06NCBq1e1f56d3d3YsmVL6tatm6/jBFLREkIIITyWslpQLrRoKWvh45YtW5YZM2YwY8aMXMMNGDCAAQMGON0eGRnJl19+me98DQYDY8aMYcyYMfmOk588qlevzpUrV/KdZn5JRUsIIYTwVFaLtrgSX7iVVLSEEEIIT1VMY7RE/sldh0IIIYQQbiItWkIIIYSnslpd7Dp04TmJIl+koiWEEEJ4KkumtrgSX7iVdB0KIYQQQriJtGgJIYQQHkpZXJzeQQbDu51UtIQQQghPZc3UFlfiC7eSrkMhhBBCCDeRFi0hhBDCU1ldHAwvLVpuJxUtIYQQwkMpiwVlLHxlScZouZ90HQohhBBCuIm0aAkhhBCeSgbDl3hS0RJCCCE8lSUTXOg6lAlL3c+glFLFXYiSLjk5meDgYJKSkggKCiru4gghhCjB7sRvhi2PmB4r8PIOKHQ6mRk32PDto/L75kYyRksIIYQQwk2k61AIIYTwUMqSiTJmuBRfuJdUtIQQQghPJYPhSzzpOhRCCCGEcBNp0RJCCCE8lLJmoCwudB1aCx9X5I9UtIQQQghPZckAgwuVJRcqaSJ/pOtQCCGEEMJNpEVLCCGE8FDKkolyoUVL7jp0P6loCSGEEB5KWc0oq8ml+MK9pOtQCCGEEMJNpEVLCCGE8FSWDDC48FMug+HdTipaQgghhIdSlgyUwYWuQ6louZ1UtIQQQggPpaxmlKXwo4BkjJb7yRgtIYQQQgg3kRYtIYQQwkMpSwYK6TosyaSiJYQQQngoZTGjXOicUhbpOnQ36ToUQgghhHATadESQgghPJSymlEGg0vxhXtJRUsIIYTwUFrXoQsVLek6dDvpOhRCCCGEcBNp0RJCCCE8lHbXoSstWnLXobtJRUsIIYTwUMqajkK5EF+6Dt1Nug6FEEIIIdxEWrSEEEIIT2VJR6nCt2ghLVpuV+pbtMxmM2+88Qb16tUjIiKCmJgYNm7cWNzFEkIIIVymLGaUJd2FRSpa7laqW7TS09Pp0aMHFy5cYO3atdSqVYtly5bRpUsXFi5cSGxsbHEXUQghhCg0ZUlHKWvh41tlMLy7leoWrfHjxxMfH8/cuXOpVasWALGxsfTu3ZshQ4aQkJBQzCUUQgghRGlWaitax48f54MPPqBhw4a0bNnSbtugQYNITU1lwoQJxVQ6IYQQwnWudRtqi3CvUtt1uGTJEjIzM2nTpk2Oba1atQJgxYoVXL58mQoVKtzp4gkhhBAuUxazi12HmUVYGuFIqW3RWr16NQDh4eE5toWEhFCjRg3MZjNbtmy500UTQgghxF9EqW3R2r17NwA1a9Z0uL1cuXKcOXOGPXv28PDDD9ttS09PJz09qzk1KSkJgOTkZDeVVgghRGlh+61wadqFfMqw3MBqNRU6vkVZirA0wpFSWdFKS0sjJSUF0CpUjgQHBwOQmJiYY9u0adN4+eWXc6wPDQ0tukIKIYQo1a5fv67/1hQ1Hx8fqlatyu/nd7qcVtWqVfHx8SmCUglHSmVF6/Lly/rrMmXKOAxjNGq9pmlpaTm2TZgwgXHjxunvrVYrV65coUKFChgMhX+m1J2SnJxMaGgop06dIigoqLiL4zLZn5JN9qdkk/2585RSXL9+nerVq7stDz8/PxISEjCbXZ8Hy8fHBz8/vyIolXCkVFa0stfMnTXd2k7OkJCQHNt8fX3x9fW1W+esZawkCwoKKrEXosKQ/SnZZH9KNtmfO8tdLVnZ+fn5SQXJA5TKwfAhISF6ZevGjRsOw1y7dg2AihUr3qliCSGEEOIvplRWtEwmEw0bNgTg7NmzDsNcuHABgKZNm96pYgkhhBDiL6ZUVrQAunfvDsCBAwdybEtMTCQpKYmAgADatWt3p4vmdr6+vkyZMiVH96enkv0p2WR/SjbZHyGKl0HdiftPi8GRI0eoX78+jRo1Yt++fXbbVq1axcMPP8zgwYOZN29eMZVQCCGEEKVdqW3RioyMZMSIEezfv589e/bYbZs3bx7+/v5MmTKleAonhBBCiL+EUtuiBdpA+JiYGLy8vFizZg3ly5fnP//5D8899xwLFy6kd+/exV1EIYQQQpRipXJ6B5uAgADi4+OZPHky0dHRGI1GoqKi2LFjB02aNCnu4gkhhBCilCvVLVpCCCGEEMWp1I7REkIIIYQoblLREqKQEhIS2LVrFxaL5z+U1dawLQ3cQghRtKSiVQJZrdbiLkKRunHjBq+++mqOaTY81c2bN3njjTd4/fXXyczMxGQyFXeRXJKamkpSUhKARzzLMy+ZmZnFXYQiJdcDITxbqR4M74nmzp3Lzz//jJ+fH3fffTcdO3YkIiKiuIvlkpUrVzJlyhRMJhNhYWGULVu2uIvkkiVLlpCRkcGsWbPw8vLsr9C0adNYunQpZcqUISkpibFjx9KzZ0+qVKmCUsrjKl7//ve/2bJlC+XLl6dFixZ0796dyMhIAI/cH7keCFEKKFEi/PLLL6pZs2bKYDDYLWFhYerbb79VVqu1uItYaK+++qoyGAyqWbNmav369cVdHJfs3r1bNWvWTG3evFkppZTFYinmEhXOtm3bVMOGDdUDDzygduzYoebOnau6d++uDAaDmjhxosft15kzZ1SHDh1Uz5491Q8//KCGDRumKlWqpIKDg9WUKVPUzZs3i7uIBSLXAyFKD+k6LAEuXrzI2LFj2bNnD1FRUTz55JM0b96c4OBgjh8/zowZM3JMuuoJbGOXrl69So0aNdi7dy+LFy/m4sWLxVyywlu1ahUNGzbkvvvuA8Bo9Myv0Ny5c+nduzerV68mOjqaIUOGMG/ePJo0acI333zDpUuXiruIBbJ+/XqCgoJYuXIlXbt2Zfbs2XzxxRfUqVOHV155haeffprExMTiLma+yPVAiNLFM38lSgl1a+Dxd999x44dO3jllVfYt28fM2fOZMuWLcydO5dKlSqxYcMGfvvtN7s4nsBWCblx4wZt27YlOjqaZcuWsXnzZo/aD5vk5GQ+/vhjmjVrBkBaWloxl6hwfv31Vz755BPat28PZO1HlSpVGD16NAkJCQQGBhZnEQts5syZVK5cGcjany5duvDRRx9hMBj45JNPeOuttzhz5kxxFjNXcj0QonSSilYxso0X2bJlC/fddx+TJk0CtP/8fH19eeSRR3jxxRdJT09n48aNxVnUQjEYDNy8eZMrV64wadIkHnroIa5cucL8+fM5duxYcRevwP744w8uX77MvffeC4Cfnx8Ax48f5+rVqx4zCPvw4cN4e3uTnp4OgI+Pj76tSpUqxMTEEBAQ4BGDsK1WK9evX+fs2bM59kcpRevWrZk6dSoACxYsYMmSJcVW1rzI9UCI0kkqWsXEarXqP2TVqlVj7Nix+oXWZDLp2/r27UtkZCQnTpwgPT29xA7mdfSjbLVa8ff35+rVq2RkZNCvXz/atGnDt99+yw8//KD/MJbE/2Yd7c/hw4dJT08nICAAgPj4eNq1a0enTp1o3Lgx/fv3Z926dXe6qPmS/XyrV68eGRkZLFy4kLNnz9p1fyql9KcmeEK3qNFoJD09neTkZHbs2MGZM2cwGo0opfTz6umnn6Zz586cP3+epUuXsm3btmIutWO28paG64Ejnnw9EMIVJf9KWgokJCTwyiuv8N///peVK1eSmZmJ0WjUf8iUg7uhjEYjVquV6tWr06xZM8xmM76+viXiIuRsf25nNBq5du0a169fp0aNGkRGRtK/f398fHyYN2+e3v1R3D8Wee2P7ZifPXsWgHPnzvH222/z7rvv0rNnT7p164afnx/Lly8nLi6O999/H7PZXCz7AnmfbxEREfTt25dFixbRr18/Pv74Yw4cOMDVq1dJTk7mgQceKLayO3L+/Hl+/vlngBxzliml9DsML126pLf0GAwGjEYjFosFf39/nn76aSpUqMBvv/3G2rVrycjIuOP7YeNsf7J/DzzpepDb55Odp1wPhChyd3r0/V/NtGnTVK1atdSzzz6runbtqvz8/FTjxo3Vf//7X5WZmamUUurq1avqwIEDOeLa7ix6+eWX1eDBg0vEnUa57Y+NrZxWq1XduHFDPfLII+rYsWNKKaUuXryoHnvsMWUwGNS//vUvPc6+ffvu7I7cUpD9ee6555TBYFDTpk1TixYtstt+8uRJde+99yqDwaAaNGigVq5cecf3Ranc9yf7+XPp0iXVoUMHuzva6tevr6pWrarKly+vOnTooMaNG6fi4+P1O/aK405Es9msevXqpcLDw5XZbFZKqRzfg5s3b6qBAwcqg8GgnnrqKZWYmOgwrUGDBimDwaA6d+6sDh065PayO5Lb/tj+JiUlecz1ID+fj40nXA+EcAepaLnR8ePHVY8ePewumqtXr1bly5dXBoNBPf300+rMmTN5pjNq1Cj1f//3f24saf7kZ3/OnTunlFJ6JfLo0aOqXr16dul8+eWXqmbNmioiIkKNHz9eVatWTbVv316dP3/+zu2MKtj+KKXUxx9/rAwGg6pYsaJaunSpUkqp9PR0vQLy22+/qa5duyqj0aiGDx+ukpKSStz+nD17Vt92/fp1tXXrVvXOO++ozp07q+HDh6tBgwap5s2bK29vb2UwGJS3t7caMGCAun79ulLK+Y+ou8ycOVOVKVNGGQwG9e9//1spZV/hs5Vn1qxZymAwqMjISLVp0ya7NGzn4rZt25SXl5fy9fVV27Zts4t/p+S1P/lRUq4HShV8f0ry9UAId5GKlhtNmDBBv6iYzWb9oj5nzhxVr149ZTAY1LBhw5zGt/1AjB49Wi1btkwppf0w2NK5evWqG0ufU0H3JzMzUx06dEgNGDBAmc1mlZqaqm/r3bu3XWvKM888oy5fvlyi9+e7775TlStXVvXq1dP/4779h3rp0qWqTp06qkmTJne8olXQ/cle9q1bt6otW7YopbQK2B9//KGmTZumWrRooQwGg/7DficrJvHx8apPnz7q0UcfVQaDQVWtWlWdOnVKKZX13bCVx2KxqOrVqyuDwaCee+45p8c+Li5OGQwGNWnSpDuzE9nkZ39yU9KuBwXdH4vFUqKvB0K4i1S03CQzM1N1795dtWvXTt24cUMplfWf3o0bN9SsWbNUQECAMhgM6osvvlBK5fwRs12shg4dqn766Se7bSkpKeqbb75RaWlp7t4VvSwF3R+llNq8ebNq27at/v7cuXNq+PDh+gXVx8dHTZgw4Y7sQ3YF2Z+FCxcqpZTas2ePqlevnvL391dvvvmm3Q+F7bNLTk5WQ4cOVQaDQR08eLBE7o+j823SpEnql19+sYunlFKnTp1SDRs2VMHBwSohIeEO7Y3mxIkTSimta7BPnz7KYDCo0aNH5whn+5589NFHymAwqAoVKqjvvvvObj9sYbZu3aoMBoMaNGhQvio3RSm/++NMSboeKFW4/dmyZUuJvB4I4U4yGN4NlFKYTCYyMjK4cuUKKSkpQNZdXGXKlOGhhx5i0KBBAEyYMIGLFy9iMBjsBreaTCauXr3KjRs39CkFbL799ltmzZqFr69vid0fgDNnzvDggw8C8MorrxAaGsqcOXOIjIzk4Ycfxmq1cuDAAQ4fPuz2/XB1f2yPQElLS+O7775j//79epq2z65s2bJER0cTEBBwRz4bV/bHYDBgsVhIS0tj586d7Nixwy5eZmYmNWvWZOTIkVitVv2usDvFNi+Wn58fEydOxM/Pj48//jjHwGvbsyYHDRpEy5YtuXLlCp988gmHDh3S07KFqVatGrVr1+bmzZt3/BmV+d0fZ0rK9cCmMPtz7ty5Enc9EMLtirOWV5rdvHlTxcTEKIPBoL777jullFIZGRl2YbZv364iIyOVwWBQr776qlIqZ5P7oUOH1D/+8Q+7dWvWrFHh4eHK399f/f77727ciywF3Z+XXnpJKaV1pVWvXl2FhYUpg8GgypYtq8aPH69SU1PV1atXVefOnZWfn59677337FqIStr+TJkyRSmlDdKtWrWqMhgMauTIker48eN63PT0dKWUUosXL1Z16tTRxzWVxP2xnW9KaV1OVapUsetys1qtevwVK1aoChUqqAsXLtyhvXFs0qRJymAwqPvvv19fd/tA8l9++cWu++n06dNKqaxjkZqaqmrXrq1eeeWVO1z6nHLbH2dKyvXAkfx8PitWrCiR1wMh3EkqWoWQ18XQ1mUxdepUZTAYVIcOHRyGu3HjhnrjjTeUwWBQ/v7++t1S2cddLFu2TP+RP3jwoOrXr5/+Q9KtW7ci+fFz1/5cvXpVff3116pcuXLKYDCouLg4tXv3brs4c+bMUd7e3qpmzZpq//79Lu+LO/fn4sWLSimlZsyYoapXr66MRqMaMGBAjsG/L774onrzzTfzVZb8cPf5ZjabVceOHVWdOnXUihUrcsR7/vnn7e4Ic1Vhj8n58+dVeHi4XXdu9n9MbOm+++67qnr16srb21s99dRTdmlcvHhRNWvWLMeAeVe4a38c5VESrgfO5Gd/Fi1apCpUqHBHrwdCFDepaBVAUlKSmjZtmj6WxRnbhWrt2rUqJCREGQwG9fXXXyulcl54fv31VxUdHa0MBoN67733cqTxxhtvqCVLlqh///vf+p1gISEhas6cOSV+f2bPnq2uXLminnvuOfXVV1/ZhbPdCp6YmKiGDRumPvrooxK/P2+//bZSSmsVWbRokQoNDdV/4GbMmKEOHDigRo4cqVq1aqX27t1b4vdnxowZSints3jzzTeVn5+fqlGjhpo/f746d+6cSkpKUsOHD1dNmjRRO3bsuGP7k5s5c+Yog8GgGjVqpFJSUpRSWRVN29/09HT13Xff6T/6I0aMUBs2bFBms1kNHTpUDR48uEjGZ7l7f7IrSdeD3DjbH1v5T548qV544YU7cj0QoqSQilY+ffDBB8rf318ZDIZ8z/Fy6NAh9cADDyiDwaB69Oihd19k/48xOTlZTZgwQZlMJjVmzBi9+0kprQXi/vvvV1WqVNH/a33++eeLZMDrndgfWxdH9u2OWiCKotXnTn0+tjmllNIqLRMmTFA1atRQtWrVUrVq1VKjR4+2C+Mp+3P58mU1Y8YMVblyZWUwGFSTJk1UpUqV1KhRo4ptfxy5efOm6tixo133p7PpBA4dOqRef/11FRERoe655x7VoEEDNXr06GL7/jhSkP0padcDR/KzP3fieiBESSIVrTysXbtWNWzYUL+w3Xvvverw4cP5jv/WW2+pcuXKqcDAQDV79uz/b+++Y6uq/z+Ovz4ttFBpoWxqWZZdZEUIUNB8GYIoQ5CSIqgkigJhCH8Q9giEpSEETKRgEZPKkKkNQ0ELhVYFGYosGVqGUChcZkvpva/fH/3dQ6+0dNDbe2lfj8RI7zzPNhze9/QMko+veLZu3crAwEB26dKF5KMVzalTp6z37dWrF//6669nsid7U1Hz5M/H6d69e7x06ZLLOaoKy1M/H6dz585x3759jIuL49mzZ58uhk/fk5Pdu3fTGMPg4GCeOXOG5JNPj3D//n1evnw5X+esy4sne7xxfZCT/PRomJLSRIPWExw6dMg6JD4sLIzLly/P97lqnCuSP//8k927d6cxhi1btrRW9pmZmdZjbDYbGzZsyEaNGtFms1mvsWDBAlauXJk7d+58ZnvceW4fb+opin84vKmnKDxNT16cp9B47733SOb9/ff0zycv+enxpvVBXgr68xEpyTRoPUFKSgorVKjAMWPGPNWn4djYWIaHh7useJycn/QiIyMf24nZecRUUfFUj7tWsurJWUnrycnJkydZsWJFGmO4e/fuIn3t3Hi6x1vXBznxxM9HxFtp0MqF3W5namoqhw0bZm3+LijnP2B37tzhF198QT8/PxpjuHz5cusw+oyMDGZmZrJt27bWkV3uOJGiJ3vccY089TyupPXkZe7cuTTGsGPHjrTZbFyyZAmPHTvmlvdST8EVZ4+IN9Og9QQ2m41NmjThsWPH6HA4+Msvv3Dbtm1MTEzk2bNnXQai/PxjtWLFCgYHB9Pf358TJkyw9umJj4/na6+9xuTkZLe1kOrJi3qKVlH3ZGe323nlyhXr0kI+Pj5s1KgRT506VdQZFvXknyd6RLxVqR60nCuSnFYiztsGDRrELl26sHPnztYOnsZkXVh4wIABXLduXYHe8/fff2dkZCSDg4PZvHlzduvWjeHh4dy4caN61KOeAkhMTGRAQADr1avHDRs2FPp1nNTj3T0iz6pSN2g5f70SGxtrnb08N2lpaezZs6d1RI7znDXZvzYm69pxBTmLcUZGBs+ePcukpCSuX79ePepRTwHPAn769Gk2bNiQH3/8caFbSPV4e49ISVDqBi0y6wzGbdq0Ydu2bXO8kG72r8ePH8/g4GCOHTuWSUlJ3L17N0+cOMFPP/2UvXv3pjGGDRo0YHx8fLF3OKlHPcXJG3rS0tKs/c7UU7J7RJ51pW7QunDhgnX4u5+fH0ePHp3jiR2dkpKSePLkyRxfKz09nTNmzGBAQADHjx9P0j07Fj+JetRTnNSjHhEpmFI1aNntdv7000+Mi4vjokWLWKtWLYaGhlqXK3nSYe4Oh8NayWT/c2pqKsePH89atWq5P+A/1POIetxPPY+oR0Tyq1QNWiSt88WkpqZy8uTJNMZw4MCBvHbtGsnCfWI7fPgw+/Xrx3/++adIlzU/1JM39RQd9eRNPSKSnQ9KmZCQEABA5cqV8eabb+Kll17Cjh07sGnTJgCAj0/BvyWBgYG4efMm6tSpU6TLmh/qyZt6io568qYeEcmu1A1aAEASAPDiiy/i3XffRXp6OmJjY3H69GkAgMPhKNDrBQQEoHfv3kW+nPmlnidTT9FSz5OpR0SyK5WDljEGAODv748ePXqgZ8+e2L9/P9asWQPgyZ/6clpJJSQkoGXLlu5Z2HxQzyPqcT/1PKIeEclLqRy0sgsLC8M777yDihUrYt26ddi3bx+A3D/1OVdSd+/eBQB88803uHjxIrp06VI8C5wH9ainOKlHPSKSBw/uH/ZU/rtT59NcGPfKlSv86KOPaIzh8OHDmZaWlutrfvvtt2zUqBFbt27NkJAQRkVF8cKFC4V+byf15E496smLenLnDT0ipVkZTw96BXXq1CksWLAA5cuXB0n0798f3bp1szaXF0aNGjUwaNAg7N69G1u3bkX37t3x1ltv5fjYCxcugCQCAgKwdOlS9O/fv9DvC6gnP9SjntyoJ2+e7BERPDtbtDIzMzlu3DiGhoZy4sSJnDp1qnVdrkWLFpHM+9Dl7BdJdXJ+qrt9+zZnz55NYwz79OnDf//917rf+Z/T1atX1aMe9ahHPSKSp2dm0Fq4cCFff/11l5XAsWPHGB4ezsDAQN69ezfX59rtdpcVSU4rJJI8cuQIIyIiGBAQwCVLlli3P3jwwHqdoqKeR9SjnoJSzyPe2CMij3j9oGW325mSksLGjRtz4cKFJLMukutcsXzyyScMCgrib7/99thzHQ6Hy0rnwIEDHDBgALdt25bj/glpaWmMjo5mQEAAa9euzalTp/J///sfN27cqB71qEc96hGRAvP6QYskjx8/zrJly3LPnj0ks1ZOzk9fJ0+eZLVq1Xj58uVcn5+SksLRo0dbV6P/8MMPmZ6e7vIY5+udPXuW9evXpzGGNWrUYHR0tHrUox71qEdECuWZGLQSExNZrlw5RkZGutzucDj4/fffc+TIkdbm7/9asGABa9WqRWMMfX19OXv27Ce+19ixY2mM4cyZM4ts+f9LPY+oRz0FpZ5HvLFHRFx5zaC1a9cuHj16lOfPn7euNu/8FHbz5k126dKFxhgOHjyYe/bs4a1bt0iS8fHxPHr0qMtrOTebHzp0yPqUN3ToUGsHUDLn/Rj27t3LcePGFck1vdSjHvWop6T2iEj+eXzQOnLkCDt37sz27duza9euDAwMZO/evXn48GGXlcWuXbvYs2dPGmNYtmxZhoSE8I033mB4eDg7d+7M0aNHc+nSpUxOTnZ5/UmTJlmb5MmsFVBu56Qpip1B1aMe9ainpPaISMF5dNC6d+8eBwwYwGXLlpHMOgR5/vz5rFy5MsuXL8/p06e7PN5ms3HevHns168f69evz+rVq7NFixb09/enj48PjTGsUqUK58yZw5SUFJfn/nfHUfWoRz3qUY+IuJtHB62NGzcyNDSUly5dsm5LT0/nd999Z20SX7x48WMrFZK8desWt2/fTjJrZ9I1a9Zw2LBh1vNmzZrF27dvk8z9cGf1qEc96lGPiLiTRwYt56btCRMmsGnTpi63Of8/Z84cGmNYu3ZtLl261Hquc/P3mjVrXM4F47R9+3Z26tSJdevW5YkTJ9za4aQe9ain8NTj3T0i8nQ8tkXLbrczMjKSvr6+1goj+2HNDx484CuvvEJjDNu3b8+9e/dajyHJqKgo6/wvmZmZ1qe6hw8fcsOGDTTGMCEhQT3qUY961CMiHuPjocv+wMfHBzVr1oTD4cDOnTsBZF053sfHB3a7HX5+fpg0aRKqV6+Ow4cPY8uWLXjw4IF1dfnz588jNjbWep6vry8AoEyZMqhevTqqVauGcuXKqUc96lGPekTEYzwyaJn/v0BqWFgYfH198fPPP+PixYvW/c6VSo8ePdC3b19kZGRg3759OHjwIAAgPT0dfn5+2LJlCw4cOGC9XmZmJgDg6tWrCA8PR9OmTdWjHvWoRz0i4jke3JrGrVu30hjDOnXqWDt+Ojk3lR89epRVq1ZlmTJluHLlSmsfh8WLF9MYw+bNm/PQoUO8f/8+yazDpNu1a8fVq1cXbwzVo57ipR71iIj38/h5tJo0aUJjDEeNGsXU1NQcHzNixAgaYxgVFeVye1RUFAMCAujj48OePXuyU6dODAsL47p164pj0XOknkfU437qeUQ9IuKNDEl6covaunXrEBUVhaCgIKxduxavvvqqtZ+C3W6Hr68vzp8/j7CwMNSsWRMHDx5ESEgIAOD+/fs4ceIEdu3ahbS0NFSrVg2jRo3yZI561FOs1KMeEfFynp70MjIy2KlTJxpjOGDAAJ45c8blfofDQYfDwX79+vH555/n3bt3cz3zsTdQj3qKk3rUIyLezSM7w2dXtmxZzJ8/HwCwadMmxMbG4tq1awCyPvEZY2CMQe3atWGMwYMHD6ydQ72RetRTnNSjHhHxbh4ftAAgIiIC06ZNAwAsX74cMTExALKOzklPTwcAXLp0CU2aNEGlSpU8tZj5ph7vph7vph4RKVE8vUnNKS0tjTNnzmRQUBCNMVy2bJl1ZE56ejojIyO5b98+Dy9l/qnHu6nHu6lHREoKrxm0nOLi4timTRsaY9ihQwfOmjWLzZo14wcffMC7d+96evEKTD3eTT3eTT0i8qzz+FGHOXn48CHi4uKQnJyM5ORk9OrVC127dvX0YhWaeryberybekTkWeZ1gxbJErUzqHq8m3q8m3pE5FnnFTvDZ5d9JeRlM2ChqMe7qce7qUdEnnVet0VLREREpKTwui1aIiIiIiWFBi0RERERN9GgJSIiIuImGrRERERE3ESDloiIiIibaNASERERcRMNWiIiIiJuokFLRERExE00aImIiIi4iQYtERERETfRoCUiAIBVq1YhKCgIq1at8vSiiIiUGBq0RAQAsGHDBty5cwcbN2709KKIiJQYGrRESqG9e/c+dtvYsWPRtm1bjBkzxgNLJCJSMhmS9PRCiEjxcTgcaNmyJf744w9PL4qISImnLVoipcy8efNw7NgxTy+GiEipoC1aIqVITEwM3n//fZCE/uqLiLiftmiJlBILFy7EvHnzrAGrQYMGaNCgASZPnox79+5hxYoVaNOmDWbOnOnyvNu3b2P27NmoVKkSAODGjRsYNmwYgoKCULduXXz55ZfWY+Pj4xEREYGAgAC0bt0aSUlJOS7L8ePHERUVhebNm6NChQpo0aIFYmJi3JEtIuJZFJFSBQCz/9U/fvw4o6KiWK5cOQLgjBkzrPuio6NZv3596zmpqals1qwZQ0JCrMf7+PgwKSmJmzdvpr+/P2vXrk1fX18CYJUqVWiz2Vzef8eOHaxXrx4TEhJIkhcuXGCrVq0IgDNnziyW74GISHHRFi2RUq5p06b4+uuv8fbbbz9239ChQxEXF2d9PW3aNERHR+PSpUu4du0aOnToAIfDgSlTpmDNmjU4ffo0kpOT8ffffyM0NBSpqanYvn279fzU1FQMHjwY8+fPR6dOnQAAoaGhiI6OBgDMnj0bZ86ccXOxiEjx0aAlIgCAGjVqPHZbuXLlEBYWZn09f/58REREAAAqVKiAkSNHAgBsNhvWrl2LOnXqAMgannr37g0ASE5Otp4fExODO3fuoG/fvi7v06JFCwBZR0Ru3ry5CKtERDyrjKcXQES8Q9myZXO83d/f3/pzYGCgy30hISHW7cYYl/uqVq0KAEhLS7Nu+/HHH0ESrVq1eux9qlSpAgBISUkp+MKLiHgpDVoiUmg+PrlvFHfex2xHNyYnJ6Ny5co4efKk25dNRMQb6FeHIlJsMjMzce3aNdhsNk8viohIsdCgJSLFplatWiCJ9evX53g/ScTHxxfvQomIuJEGLREpNi+//DIAYMqUKTh37txj969evRqXL18u7sUSEXEbDVoipUz58uUBAOnp6S63Z2RkAAAePnzocnv2rzMzM13uczgcAAC73f7Y+zj3zcr+/OHDh+O5557D9evX0aFDB3z++ec4f/48Tp8+bZ1QtU+fPoVNExHxOhq0REqZ8PBwAMD+/ftx//59zJ07Fw6HAwkJCQCAhIQEl8HJeTsAHDhwwOW1nL/mO3PmDK5fv27dnpmZicTERABAUlKS9XqhoaGIiYlBmTJlkJKSghEjRuCFF15A48aNMX36dKxcuRIVKlQo+mgREQ/RtQ5FSplff/0VQ4YMgc1mw5AhQ9C/f3/07dsXN27csB4THByMH374AZ999hm++uora1Dy9fVF9+7dsX79ejRs2BBXr161nuPv74+JEyeic+fOGDhwoMsO75UqVUJiYiKaNm0KIGv4mjVrFhITE+FwONCxY0fMmTMH7dq1K55vgohIMdGgJSIiIuIm+tWhiIiIiJto0BIRERFxEw1aIiIiIm6iQUtERETETTRoiYiIiLiJBi0RERERN9GgJSIiIuImGrRERERE3ESDloiIiIibaNASERERcRMNWiIiIiJuokFLRERExE00aImIiIi4iQYtERERETf5Pz4LsViLHBt9AAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3988,7 +4027,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -4037,7 +4076,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,
diff --git a/examples/data/dolfyn/test_data/Sig1000_IMU_bin.nc b/examples/data/dolfyn/test_data/Sig1000_IMU_bin.nc
deleted file mode 100644
index 2b0dcbbdc..000000000
Binary files a/examples/data/dolfyn/test_data/Sig1000_IMU_bin.nc and /dev/null differ
diff --git a/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc b/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc
new file mode 100644
index 000000000..4f5ffec15
Binary files /dev/null and b/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_bin.nc b/examples/data/dolfyn/test_data/vector_data01_bin.nc
index baa0dba0b..a88effa0d 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_bin.nc and b/examples/data/dolfyn/test_data/vector_data01_bin.nc differ
diff --git a/mhkit/dolfyn/adp/turbulence.py b/mhkit/dolfyn/adp/turbulence.py
index 504de30f7..d85f365ab 100644
--- a/mhkit/dolfyn/adp/turbulence.py
+++ b/mhkit/dolfyn/adp/turbulence.py
@@ -111,8 +111,10 @@ def __init__(
         n_fft_coh : int
           Number of data points to use for coherence and cross-spectra ffts
           Default: `n_fft_coh`=`n_fft`
-        noise : float, list or numpy.ndarray
-          Instrument's doppler noise in same units as velocity
+        noise : float or array-like
+          Instrument noise level in same units as velocity. Typically
+          found from `adp.turbulence.doppler_noise_level`.
+          Default: None.
         orientation : str, default='up'
           Instrument's orientation, either 'up' or 'down'
         diff_style : str, default='centered_extended'
@@ -348,9 +350,10 @@ def doppler_noise_level(self, psd, pct_fN=0.8):
         N2 = psd.sel(freq=f_range) * psd.freq.sel(freq=f_range)
         noise_level = np.sqrt(N2.mean(dim="freq"))
 
+        time_coord = psd.dims[0]  # no reason this shouldn't be time or time_b5
         return xr.DataArray(
             noise_level.values.astype("float32"),
-            dims=["time"],
+            coords={time_coord: psd.coords[time_coord]},
             attrs={
                 "units": "m s-1",
                 "long_name": "Doppler Noise Level",
@@ -869,7 +872,7 @@ def check_turbulence_cascade_slope(self, psd, freq_range=[0.2, 0.4]):
 
         return m, b
 
-    def dissipation_rate_LT83(self, psd, U_mag, freq_range=[0.2, 0.4]):
+    def dissipation_rate_LT83(self, psd, U_mag, freq_range=[0.2, 0.4], noise=None):
         """
         Calculate the TKE dissipation rate from the velocity spectra.
 
@@ -882,6 +885,10 @@ def dissipation_rate_LT83(self, psd, U_mag, freq_range=[0.2, 0.4]):
         f_range : iterable(2)
           The range over which to integrate/average the spectrum, in units
           of the psd frequency vector (Hz or rad/s)
+        noise : float or array-like
+          Instrument noise level in same units as velocity. Typically
+          found from `adp.turbulence.doppler_noise_level`.
+          Default: None.
 
         Returns
         -------
@@ -918,6 +925,17 @@ def dissipation_rate_LT83(self, psd, U_mag, freq_range=[0.2, 0.4]):
             raise Exception("U_mag should be 1-dimensional (time)")
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
+        if noise is not None:
+            if np.shape(noise)[0] != np.shape(psd)[0]:
+                raise Exception("Noise should have same first dimension as PSD")
+        else:
+            noise = np.array(0)
+
+        # Noise subtraction from binner.TimeBinner._psd_base
+        psd = psd.copy()
+        if noise is not None:
+            psd -= noise**2 / (self.fs / 2)
+            psd = psd.where(psd > 0, np.min(np.abs(psd)) / 100)
 
         freq = psd.freq
         idx = np.where((freq_range[0] < freq) & (freq < freq_range[1]))
diff --git a/mhkit/dolfyn/adv/turbulence.py b/mhkit/dolfyn/adv/turbulence.py
index 4e231cc33..83ae80a7a 100644
--- a/mhkit/dolfyn/adv/turbulence.py
+++ b/mhkit/dolfyn/adv/turbulence.py
@@ -24,8 +24,10 @@ class ADVBinner(VelBinner):
     n_fft_coh : int
       Number of data points to use for coherence and cross-spectra fft's.
       Optional, default `n_fft_coh` = `n_fft`
-    noise : float, list or numpy.ndarray
-      Instrument's doppler noise in same units as velocity
+        noise : float or array-like
+          Instrument noise level in same units as velocity. Typically
+          found from `adv.turbulence.doppler_noise_level`.
+          Default: None.
     """
 
     def __call__(self, ds, freq_units="rad/s", window="hann"):
@@ -263,7 +265,7 @@ def doppler_noise_level(self, psd, pct_fN=0.8):
 
         return xr.DataArray(
             noise_level.values.astype("float32"),
-            dims=["dir", "time"],
+            coords={"S": psd["S"], "time": psd["time"]},
             attrs={
                 "units": "m/s",
                 "long_name": "Doppler Noise Level",
@@ -337,7 +339,7 @@ def check_turbulence_cascade_slope(self, psd, freq_range=[6.28, 12.57]):
 
         return m, b
 
-    def dissipation_rate_LT83(self, psd, U_mag, freq_range=[6.28, 12.57]):
+    def dissipation_rate_LT83(self, psd, U_mag, freq_range=[6.28, 12.57], noise=None):
         """
         Calculate the dissipation rate from the PSD
 
@@ -351,6 +353,10 @@ def dissipation_rate_LT83(self, psd, U_mag, freq_range=[6.28, 12.57]):
           The range over which to integrate/average the spectrum, in units
           of the psd frequency vector (Hz or rad/s).
           Default = [6.28, 12.57] rad/s
+        noise : float or array-like
+          Instrument noise level in same units as velocity. Typically
+          found from `adv.turbulence.calc_doppler_noise`.
+          Default: None.
 
         Returns
         -------
@@ -390,6 +396,18 @@ def dissipation_rate_LT83(self, psd, U_mag, freq_range=[6.28, 12.57]):
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
 
+        if noise is not None:
+            if np.shape(noise)[0] != 3:
+                raise Exception("Noise should have same first dimension as velocity")
+        else:
+            noise = np.array([0, 0, 0])[:, None, None]
+
+        # Noise subtraction from binner.TimeBinner.calc_psd_base
+        psd = psd.copy()
+        if noise is not None:
+            psd -= noise**2 / (self.fs / 2)
+            psd = psd.where(psd > 0, np.min(np.abs(psd)) / 100)
+
         freq = psd.freq
         idx = np.where((freq_range[0] < freq) & (freq < freq_range[1]))
         idx = idx[0]
diff --git a/mhkit/dolfyn/binned.py b/mhkit/dolfyn/binned.py
index 0be5a771d..0bdb00f73 100644
--- a/mhkit/dolfyn/binned.py
+++ b/mhkit/dolfyn/binned.py
@@ -421,7 +421,7 @@ def _psd_base(
 
         for slc in slice1d_along_axis(dat.shape, -1):
             out[slc] = psd_1D(dat[slc], n_fft, fs, window=window, step=step)
-        if noise != 0:
+        if np.any(noise):
             out -= noise**2 / (fs / 2)
             # Make sure all values of the PSD are >0 (but still small):
             out[out < 0] = np.min(np.abs(out)) / 100
diff --git a/mhkit/dolfyn/velocity.py b/mhkit/dolfyn/velocity.py
index d5f7c5920..24b14d375 100644
--- a/mhkit/dolfyn/velocity.py
+++ b/mhkit/dolfyn/velocity.py
@@ -803,6 +803,60 @@ def autocovariance(self, veldat, n_bin=None):
 
         return da
 
+    def turbulence_intensity(self, U_mag, noise=0, thresh=0, detrend=False):
+        """
+        Calculate noise-corrected turbulence intensity.
+
+        Parameters
+        ----------
+        U_mag : xarray.DataArray
+          Raw horizontal velocity magnitude
+        noise : numeric
+          Instrument noise level in same units as velocity. Typically
+          found from `<adv or adp>.turbulence.doppler_noise_level`.
+          Default: None.
+        thresh : numeric
+          Theshold below which TI will not be calculated
+        detrend : bool (default: False)
+          Detrend the velocity data (True), or simply de-mean it
+          (False), prior to computing TI.
+        """
+
+        if "xarray" in type(U_mag).__module__:
+            U = U_mag.values
+        if "xarray" in type(noise).__module__:
+            noise = noise.values
+
+        if detrend:
+            up = self.detrend(U)
+        else:
+            up = self.demean(U)
+
+        # Take RMS and subtract noise
+        u_rms = np.sqrt(np.nanmean(up**2, axis=-1) - noise**2)
+        u_mag = self.mean(U)
+
+        ti = np.ma.masked_where(u_mag < thresh, u_rms / u_mag)
+
+        dims = U_mag.dims
+        coords = {}
+        for nm in U_mag.dims:
+            if "time" in nm:
+                coords[nm] = self.mean(U_mag[nm].values)
+            else:
+                coords[nm] = U_mag[nm].values
+
+        return xr.DataArray(
+            ti.data.astype("float32"),
+            coords=coords,
+            dims=dims,
+            attrs={
+                "units": "% [0,1]",
+                "long_name": "Turbulence Intensity",
+                "comment": f"TI was corrected from a noise level of {noise} m/s",
+            },
+        )
+
     def turbulent_kinetic_energy(self, veldat, noise=None, detrend=True):
         """
         Calculate the turbulent kinetic energy (TKE) (variances
@@ -814,11 +868,12 @@ def turbulent_kinetic_energy(self, veldat, noise=None, detrend=True):
           Velocity data array from ADV or single beam from ADCP.
           The last dimension is assumed to be time.
         noise : float or array-like
-          A vector of the noise levels of the velocity data with
-          the same first dimension as the velocity vector.
+          Instrument noise level in same units as velocity. Typically
+          found from `<adv or adp>.turbulence.doppler_noise_level`.
+          Default: None.
         detrend : bool (default: False)
           Detrend the velocity data (True), or simply de-mean it
-          (False), prior to computing tke. Note: the psd routines
+          (False), prior to computing TKE. Note: the PSD routines
           use detrend, so if you want to have the same amount of
           variance here as there use ``detrend=True``.
 
@@ -892,7 +947,7 @@ def power_spectral_density(
         freq_units="rad/s",
         fs=None,
         window="hann",
-        noise=None,
+        noise=0,
         n_bin=None,
         n_fft=None,
         n_pad=None,
@@ -913,10 +968,9 @@ def power_spectral_density(
         window : string or array
           Specify the window function.
           Options: 1, None, 'hann', 'hamm'
-        noise : float or array-like
-          A vector of the noise levels of the velocity data with
-          the same first dimension as the velocity vector.
-          Default = 0.
+        noise : numeric or array
+          Instrument noise level in same units as velocity.
+          Default: 0 (ADCP) or [0, 0, 0] (ADV).
         n_bin : int (optional)
           The bin-size. Default: from the binner.
         n_fft : int (optional)
@@ -938,8 +992,6 @@ def power_spectral_density(
         n_fft = self._parse_nfft(n_fft)
         if "xarray" in type(veldat).__module__:
             vel = veldat.values
-        if "xarray" in type(noise).__module__:
-            noise = noise.values
         if ("rad" not in freq_units) and ("Hz" not in freq_units):
             raise ValueError("`freq_units` should be one of 'Hz' or 'rad/s'")
 
@@ -964,16 +1016,19 @@ def power_spectral_density(
         ).astype("float32")
 
         # Spectra, if input is full velocity or a single array
-        if len(vel.shape) == 2:
-            if not vel.shape[0] == 3:
-                raise Exception(
+        if len(vel.shape) >= 2:
+            if vel.shape[0] != 3:
+                raise ValueError(
                     "Function can only handle 1D or 3D arrays."
                     " If ADCP data, please select a specific depth bin."
                 )
-            if (noise is not None) and (np.shape(noise)[0] != 3):
-                raise Exception("Noise should have same first dimension as velocity")
+            if np.array(noise).any():
+                if np.size(noise) != 3:
+                    raise ValueError("Noise is expected to be an array of 3 scalars")
             else:
+                # Reset default to list of 3 zeros
                 noise = np.array([0, 0, 0])
+
             out = np.empty(
                 self._outshape_fft(vel[:3].shape, n_fft=n_fft, n_bin=n_bin),
                 dtype=np.float32,
@@ -996,10 +1051,9 @@ def power_spectral_density(
             }
             dims = ["S", "time", "freq"]
         else:
-            if (noise is not None) and (len(np.shape(noise)) > 1):
-                raise Exception("Noise should have same first dimension as velocity")
-            else:
-                noise = np.array(0)
+            if np.array(noise).any() and np.size(noise) > 1:
+                raise ValueError("Noise is expected to be a scalar")
+
             out = self._psd_base(
                 vel,
                 fs=fs,
diff --git a/mhkit/tests/dolfyn/test_analysis.py b/mhkit/tests/dolfyn/test_analysis.py
index 68853e637..da10f5449 100644
--- a/mhkit/tests/dolfyn/test_analysis.py
+++ b/mhkit/tests/dolfyn/test_analysis.py
@@ -92,22 +92,29 @@ def test_adv_turbulence(self):
         dat = tv.dat.copy(deep=True)
         bnr = avm.ADVBinner(n_bin=20.0, fs=dat.fs)
         tdat = bnr(dat)
-        acov = bnr.autocovariance(dat.vel)
+        acov = bnr.autocovariance(dat["vel"])
 
         assert_identical(tdat, avm.turbulence_statistics(dat, n_bin=20.0, fs=dat.fs))
 
-        tdat["stress_detrend"] = bnr.reynolds_stress(dat.vel)
-        tdat["stress_demean"] = bnr.reynolds_stress(dat.vel, detrend=False)
+        tdat["stress_detrend"] = bnr.reynolds_stress(dat["vel"])
+        tdat["stress_demean"] = bnr.reynolds_stress(dat["vel"], detrend=False)
         tdat["csd"] = bnr.cross_spectral_density(
-            dat.vel, freq_units="rad", window="hamm", n_fft_coh=10
+            dat["vel"], freq_units="rad", window="hamm", n_fft_coh=10
         )
-        tdat["LT83"] = bnr.dissipation_rate_LT83(tdat.psd, tdat.velds.U_mag)
-        tdat["SF"] = bnr.dissipation_rate_SF(dat.vel[0], tdat.velds.U_mag)
+        tdat["LT83"] = bnr.dissipation_rate_LT83(tdat["psd"], tdat.velds.U_mag)
+        tdat["noise"] = bnr.doppler_noise_level(tdat["psd"], pct_fN=0.8)
+        tdat["LT83_noise"] = bnr.dissipation_rate_LT83(
+            tdat["psd"], tdat.velds.U_mag, noise=tdat["noise"]
+        )
+        tdat["SF"] = bnr.dissipation_rate_SF(dat["vel"][0], tdat.velds.U_mag)
         tdat["TE01"] = bnr.dissipation_rate_TE01(dat, tdat)
         tdat["L"] = bnr.integral_length_scales(acov, tdat.velds.U_mag)
         slope_check = bnr.check_turbulence_cascade_slope(
             tdat["psd"][-1].mean("time"), freq_range=[10, 100]
         )
+        tdat["psd_noise"] = bnr.power_spectral_density(
+            dat["vel"], freq_units="rad", noise=[0.06, 0.04, 0.01]
+        )
 
         if make_data:
             save(tdat, "vector_data01_bin.nc")
@@ -117,13 +124,22 @@ def test_adv_turbulence(self):
         assert_allclose(tdat, load("vector_data01_bin.nc"), atol=1e-6)
 
     def test_adcp_turbulence(self):
-        dat = tr.dat_sig_i.copy(deep=True)
+        dat = tr.dat_sig_tide.copy(deep=True)
+        dat.velds.rotate2("earth")
+        dat.attrs["principal_heading"] = apm.calc_principal_heading(
+            dat.vel.mean("range")
+        )
         bnr = apm.ADPBinner(n_bin=20.0, fs=dat.fs, diff_style="centered")
         tdat = bnr.bin_average(dat)
-        tdat["dudz"] = bnr.dudz(tdat.vel)
-        tdat["dvdz"] = bnr.dvdz(tdat.vel)
-        tdat["dwdz"] = bnr.dwdz(tdat.vel)
-        tdat["tau2"] = bnr.shear_squared(tdat.vel)
+
+        tdat["dudz"] = bnr.dudz(tdat["vel"])
+        tdat["dvdz"] = bnr.dvdz(tdat["vel"])
+        tdat["dwdz"] = bnr.dwdz(tdat["vel"])
+        tdat["tau2"] = bnr.shear_squared(tdat["vel"])
+        tdat["I"] = tdat.velds.I
+        tdat["ti"] = bnr.turbulence_intensity(dat.velds.U_mag, detrend=False)
+        dat.velds.rotate2("beam")
+
         tdat["psd"] = bnr.power_spectral_density(
             dat["vel"].isel(dir=2, range=len(dat.range) // 2), freq_units="Hz"
         )
@@ -137,6 +153,9 @@ def test_adcp_turbulence(self):
         tdat["tke"] = bnr.total_turbulent_kinetic_energy(
             dat, noise=tdat["noise"], orientation="up", beam_angle=25
         )
+        tdat["ti_noise"] = bnr.turbulence_intensity(
+            dat.velds.U_mag, detrend=False, noise=tdat["noise"]
+        )
         # This is "negative" for this code check
         tdat["wpwp"] = bnr.turbulent_kinetic_energy(dat["vel_b5"], noise=tdat["noise"])
         tdat["dissipation_rate_LT83"] = bnr.dissipation_rate_LT83(
@@ -144,6 +163,12 @@ def test_adcp_turbulence(self):
             tdat.velds.U_mag.isel(range=len(dat.range) // 2),
             freq_range=[0.2, 0.4],
         )
+        tdat["dissipation_rate_LT83_noise"] = bnr.dissipation_rate_LT83(
+            tdat["psd"],
+            tdat.velds.U_mag.isel(range=len(dat.range) // 2),
+            freq_range=[0.2, 0.4],
+            noise=tdat["noise"],
+        )
         (
             tdat["dissipation_rate_SF"],
             tdat["noise_SF"],
@@ -155,10 +180,22 @@ def test_adcp_turbulence(self):
         slope_check = bnr.check_turbulence_cascade_slope(
             tdat["psd"].mean("time"), freq_range=[0.4, 4]
         )
+        tdat["psd_noise"] = bnr.power_spectral_density(
+            dat["vel"].isel(dir=2, range=len(dat.range) // 2),
+            freq_units="Hz",
+            noise=0.01,
+        )
 
         if make_data:
-            save(tdat, "Sig1000_IMU_bin.nc")
+            save(tdat, "Sig1000_tidal_bin.nc")
             return
 
+        with pytest.raises(Exception):
+            bnr.calc_psd(dat["vel"], freq_units="Hz", noise=0.01)
+
+        with pytest.raises(Exception):
+            bnr.calc_psd(dat["vel"][0], freq_units="Hz", noise=0.01)
+
         assert np.round(slope_check[0].values, 4), -1.0682
-        assert_allclose(tdat, load("Sig1000_IMU_bin.nc"), atol=1e-6)
+
+        assert_allclose(tdat, load("Sig1000_tidal_bin.nc"), atol=1e-6)