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   "id": "91c4ae4d-2b0e-4de5-b759-4c9fc9d072b1",
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   "source": [
    "# Extensions\n",
    "\n",
    "The wrapper class functionalities can be extended using composition or inheritance.\n",
    "\n",
    "The concept of composition adds a component to a composite class. The relationship is such, that the composite class does not know the component class but wise versa. This allows to add additional functionality without changing the original code. Adding components to an existing wrapper class will be called \"registering\" here.\n",
    "\n",
    "Concretely, four different so-called accessory classes are implemented:\n",
    "- `Vector`\n",
    "- `Magnitude`\n",
    "- `normalize`\n",
    "- `to_units`\n",
    "\n",
    "These accessories interfaces must be activated by an import call. They generally are designed such, that they are called on a dataset or group with respective arguments, which prepares a the action being performed when data is selected. Best is, to learn by example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a1cbc998-a747-4370-b362-d04c4d6508be",
   "metadata": {
    "tags": []
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    {
     "data": {
      "text/plain": [
       "using(\"h5py\")"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import h5rdmtoolbox as h5tbx\n",
    "h5tbx.use(None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3edcad1-6c32-4d07-a581-1aa57f917259",
   "metadata": {},
   "source": [
    "## 1. Vector\n",
    "The `Vector` extension returns a `xr.Dataset`. First specify which of the datasets from the HDF5 should be contained in the resulting `xr.Dataset`. Then, index the data array using numpy notation or `sel()` or `isel()`. Only then, the data is loaded from the file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7eecb901-7e7c-473d-848c-409e1f0a0e8c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from h5rdmtoolbox.extensions import vector  # make `Vector` appear as a property of groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "aa41f9f9-64d2-4d3d-8cd3-4cbcca88ae88",
   "metadata": {
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   "outputs": [
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       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
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       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
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       "\n",
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       ".xr-header > ul {\n",
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       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
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       "\n",
       ".xr-dim-list:after {\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "  background-color: var(--xr-background-color-row-even);\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
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       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
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       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (y: 2, x: 3)\n",
       "Coordinates:\n",
       "  * y        (y) int32 2 3\n",
       "  * x        (x) int32 1 2 3\n",
       "Data variables:\n",
       "    xvel     (y, x) float64 0.842 0.7745 0.5654 0.3707 0.5854 0.5751\n",
       "    yvel     (y, x) float64 0.904 0.9084 0.4555 0.5522 0.2687 0.0386\n",
       "Attributes:\n",
       "    long_name:  x vel\n",
       "    units:      m/s</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-3beb8de2-2854-4a9b-b817-1a6c1199d7bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3beb8de2-2854-4a9b-b817-1a6c1199d7bc' 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'>y</span>: 2</li><li><span class='xr-has-index'>x</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c81bb01d-4b97-43eb-8580-e5339834d852' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c81bb01d-4b97-43eb-8580-e5339834d852' class='xr-section-summary' >Coordinates: <span>(2)</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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>2 3</div><input id='attrs-46b09b8a-0116-4fe6-bd41-564ea6886101' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46b09b8a-0116-4fe6-bd41-564ea6886101' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70f1315a-30de-4b03-9769-36a51910ae58' class='xr-var-data-in' type='checkbox'><label for='data-70f1315a-30de-4b03-9769-36a51910ae58' title='Show/Hide data 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([2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-ea632cd7-88aa-4edc-bad8-9df9fcc3f4c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea632cd7-88aa-4edc-bad8-9df9fcc3f4c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b038d369-bf3f-496e-916f-a881fe9bfbca' class='xr-var-data-in' type='checkbox'><label for='data-b038d369-bf3f-496e-916f-a881fe9bfbca' title='Show/Hide data 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, 3])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f1d5b2c-7d92-4ee2-a9f4-e37b75531678' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7f1d5b2c-7d92-4ee2-a9f4-e37b75531678' class='xr-section-summary' >Data variables: <span>(2)</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>xvel</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.842 0.7745 ... 0.5854 0.5751</div><input id='attrs-49515c3c-22c6-42b8-806b-80d3e75716f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49515c3c-22c6-42b8-806b-80d3e75716f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca3370c3-04b6-44bc-98cf-f9fa01e357bb' class='xr-var-data-in' type='checkbox'><label for='data-ca3370c3-04b6-44bc-98cf-f9fa01e357bb' title='Show/Hide data 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>long_name :</span></dt><dd>x vel</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([[0.84196634, 0.77451326, 0.56544457],\n",
       "       [0.37066316, 0.58540776, 0.57506951]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>yvel</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.904 0.9084 ... 0.2687 0.0386</div><input id='attrs-b5f1dd1b-76b5-4673-845d-f1ed5a97955d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5f1dd1b-76b5-4673-845d-f1ed5a97955d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3976e314-555e-4085-8b28-4ecba0c1fe05' class='xr-var-data-in' type='checkbox'><label for='data-3976e314-555e-4085-8b28-4ecba0c1fe05' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([[0.90404063, 0.90843006, 0.45548196],\n",
       "       [0.55215745, 0.2687463 , 0.03860232]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d31457fa-57c8-4cfc-815d-411257d7d365' class='xr-section-summary-in' type='checkbox'  ><label for='section-d31457fa-57c8-4cfc-815d-411257d7d365' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f62cc4f3-a2c4-40ca-85f1-a483c7bc7da0' class='xr-index-data-in' type='checkbox'/><label for='index-f62cc4f3-a2c4-40ca-85f1-a483c7bc7da0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([2, 3], dtype=&#x27;int32&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-197bc467-3853-4c04-991b-6aba967fa2b3' class='xr-index-data-in' type='checkbox'/><label for='index-197bc467-3853-4c04-991b-6aba967fa2b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;x&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-201acae8-b817-41da-997a-2a122b392e58' class='xr-section-summary-in' type='checkbox'  checked><label for='section-201acae8-b817-41da-997a-2a122b392e58' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x vel</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (y: 2, x: 3)\n",
       "Coordinates:\n",
       "  * y        (y) int32 2 3\n",
       "  * x        (x) int32 1 2 3\n",
       "Data variables:\n",
       "    xvel     (y, x) float64 0.842 0.7745 0.5654 0.3707 0.5854 0.5751\n",
       "    yvel     (y, x) float64 0.904 0.9084 0.4555 0.5522 0.2687 0.0386\n",
       "Attributes:\n",
       "    long_name:  x vel\n",
       "    units:      m/s"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "with h5tbx.File() as h5:\n",
    "    \n",
    "    h5.create_dataset('x', data=[1, 2, 3], make_scale=True, attrs={'units': 'm'})\n",
    "    h5.create_dataset('y', data=[1, 2, 3, 4], make_scale=True, attrs={'units': 'm'})\n",
    "    h5.create_dataset('u', data=np.random.random((4, 3)), attach_scales=('y', 'x'),\n",
    "                     attrs=dict(units='m/s', long_name='x vel'))\n",
    "    h5.create_dataset('v', data=np.random.random((4, 3)), attach_scales=('y', 'x'),\n",
    "                     attrs=dict(units='m/s'))\n",
    "    \n",
    "    vec = h5.Vector(xvel='u', yvel='v')[1:3]\n",
    "vec"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3cddc5a-d646-4d20-a2ce-b024fa10e9c2",
   "metadata": {},
   "source": [
    "## 2. Magnitude\n",
    "Similar to `Vector`, the `Magnitude` accessory takes two or more datasets and calculates the magnitude from them. Again, data is only loaded after the involved dtasets are specified. If unit attributes are given, the calculation will check for mismatching units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "42047c6b-7d4d-4b3b-88af-697df2444672",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from h5rdmtoolbox.extensions import magnitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0700f532-2443-4ed0-8f78-697c5e42385a",
   "metadata": {},
   "outputs": [],
   "source": [
    "with h5tbx.File(h5.hdf_filename) as h5:\n",
    "    mag = h5.Magnitude('u', 'v', name='mag')[1:3, 0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0f017c63-70c1-4007-9a55-6d5de6e3997b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1e3c3d71cd0>"
      ]
     },
     "execution_count": 6,
     "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": [
    "mag.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb9894f1-3e62-4199-9e20-0209ce1f5975",
   "metadata": {},
   "source": [
    "## 3 Normalization\n",
    "\n",
    "Data is generally stored in one form (and physical unit) in the HDF5 file. However, in some scientific cases, data may be required in a normalized value.\n",
    "\n",
    "Consider the following example of a velocity dataset. The accessory `normalize` allows to normalize the data values or the coordinates.\n",
    "\n",
    "We will show two scenarios: Either the data values are normalized or the attached coordinates, too (or both)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8d4ed2f8-3e47-4534-aa11-8e51a09703c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from h5rdmtoolbox.extensions import normalize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "008c140e-2127-47de-81fe-c1559484fa47",
   "metadata": {},
   "source": [
    "Normalize the data by various reference values, here `x_ref` and `phi`. Note, that a unit may be provided:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "144da84f-5bd6-44d1-a24e-e55ebc4ecbae",
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-details {\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;x/x_ref/phi&#x27; ()&gt;\n",
       "0.3333\n",
       "Attributes:\n",
       "    units:    </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'>'x/x_ref/phi'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-eb76bef1-2d1a-4cac-9cd8-1f8b91a029be' class='xr-array-in' type='checkbox' ><label for='section-eb76bef1-2d1a-4cac-9cd8-1f8b91a029be' 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>0.3333</span></div><div class='xr-array-data'><pre>array(0.33333333)</pre></div></div></li><li class='xr-section-item'><input id='section-432d3915-8252-4d33-ad04-2ca6e559259d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-432d3915-8252-4d33-ad04-2ca6e559259d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-15f0eca4-7582-4f70-9794-174f4a6075e4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-15f0eca4-7582-4f70-9794-174f4a6075e4' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-4dc0654d-047f-49f2-9923-4fb94d408194' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4dc0654d-047f-49f2-9923-4fb94d408194' 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></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'x/x_ref/phi' ()>\n",
       "0.3333\n",
       "Attributes:\n",
       "    units:    "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with h5tbx.File() as h5:\n",
    "    h5.create_dataset('x', data=[1, 2, 3], make_scale=True, attrs={'units': 'm'})\n",
    "    h5.create_dataset('y', data=[1, 2, 3, 4], make_scale=True, attrs={'units': 'm'})\n",
    "    h5.create_dataset('u', data=np.random.random((4, 3)), attach_scales=('y', 'x'))\n",
    "    h5.create_dataset('v', data=np.random.random((4, 3)), attach_scales=('y', 'x'))\n",
    "\n",
    "    x_norm = h5.x.normalize(x_ref='2 m', phi=3)[1]\n",
    "\n",
    "x_norm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc22af39-e75b-4c05-b991-20af9a4616c0",
   "metadata": {},
   "source": [
    "Now, let's normalize the velocity \"u\" **and its coordinate** x:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a6b8c83e-9c97-475a-903d-3478ffd92eee",
   "metadata": {},
   "outputs": [],
   "source": [
    "with h5tbx.File(h5.hdf_filename) as h5:\n",
    "    u_norm = h5.u.normalize(u_ref='2 m/s', name='uu').x(x_ref='2 m', phi=3, name='epsilon').isel(y=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "99ac8eff-1069-45c2-b943-e2efd3cec0f5",
   "metadata": {},
   "outputs": [
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       "  display: contents;\n",
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       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;uu&#x27; (epsilon: 3)&gt;\n",
       "0.4961 0.08902 0.3291\n",
       "Coordinates:\n",
       "    y        int32 1\n",
       "  * epsilon  (epsilon) float64 0.1667 0.3333 0.5\n",
       "Attributes:\n",
       "    units:    s/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'>'uu'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>epsilon</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-41369b42-fff3-4f30-8143-06443556a19a' class='xr-array-in' type='checkbox' ><label for='section-41369b42-fff3-4f30-8143-06443556a19a' 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>0.4961 0.08902 0.3291</span></div><div class='xr-array-data'><pre>array([0.49607756, 0.08901571, 0.32906417])</pre></div></div></li><li class='xr-section-item'><input id='section-f89b6423-4dfe-4199-89c7-12155af4050b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f89b6423-4dfe-4199-89c7-12155af4050b' class='xr-section-summary' >Coordinates: <span>(2)</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>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-41e3df2b-ad49-4294-8568-6af76d19f197' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41e3df2b-ad49-4294-8568-6af76d19f197' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cce30664-4da3-4028-9a0c-be58d53cef24' class='xr-var-data-in' type='checkbox'><label for='data-cce30664-4da3-4028-9a0c-be58d53cef24' title='Show/Hide data 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)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>epsilon</span></div><div class='xr-var-dims'>(epsilon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1667 0.3333 0.5</div><input id='attrs-eb4a093d-a96b-4747-aedc-12056f674680' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb4a093d-a96b-4747-aedc-12056f674680' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14270b25-bcb8-4bc9-9907-193b3ea11d5c' class='xr-var-data-in' type='checkbox'><label for='data-14270b25-bcb8-4bc9-9907-193b3ea11d5c' title='Show/Hide data 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/m</dd></dl></div><div class='xr-var-data'><pre>array([0.166667, 0.333333, 0.5     ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24118e7d-a171-4017-af2b-ee37f8dcd470' class='xr-section-summary-in' type='checkbox'  ><label for='section-24118e7d-a171-4017-af2b-ee37f8dcd470' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>epsilon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-be55e009-ac7f-4404-835c-df3d3bc6ab56' class='xr-index-data-in' type='checkbox'/><label for='index-be55e009-ac7f-4404-835c-df3d3bc6ab56' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.16666666666666666, 0.3333333333333333, 0.5], dtype=&#x27;float64&#x27;, name=&#x27;epsilon&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55ecc5db-f022-45d8-8d04-3794d673abdf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55ecc5db-f022-45d8-8d04-3794d673abdf' 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>s/m</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'uu' (epsilon: 3)>\n",
       "0.4961 0.08902 0.3291\n",
       "Coordinates:\n",
       "    y        int32 1\n",
       "  * epsilon  (epsilon) float64 0.1667 0.3333 0.5\n",
       "Attributes:\n",
       "    units:    s/m"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "u_norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b3f9c0dc-e6e1-46ad-980f-dd120302b53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1e3c3e36670>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "u_norm.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fc1218a-d6fa-43cb-b579-7f2eae77350d",
   "metadata": {},
   "source": [
    "## 4. Converting units\n",
    "\n",
    "The accessory \"to_units\" will convert the selected data to the desired units. This assumes, that the unit attribute is called \"units\". It is also possible to change the units of \n",
    "attached dimensions. In the following examples this is done.\n",
    "\n",
    "Note, that not the dataset values itself changes in the file, but whatever data is accessed by the following slice operation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e614bf4a-556b-44c0-ac00-11a5113e5cb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from h5rdmtoolbox.extensions import units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "76cf75b0-3935-42ec-a3b6-0165db7d8264",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
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       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
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       "\n",
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       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
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       "\n",
       ".xr-header {\n",
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       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
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       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
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       "\n",
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       "\n",
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       "  display: contents;\n",
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       "\n",
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       "  display: none;\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
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       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; (x: 1)&gt;\n",
       "-4.5e+03\n",
       "Coordinates:\n",
       "  * x        (x) float64 -4.5e+03\n",
       "Attributes:\n",
       "    units:    mm/s</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'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 1</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-09373053-b337-4f78-8806-4ee43dab9a39' class='xr-array-in' type='checkbox' ><label for='section-09373053-b337-4f78-8806-4ee43dab9a39' 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>-4.5e+03</span></div><div class='xr-array-data'><pre>array([-4500.])</pre></div></div></li><li class='xr-section-item'><input id='section-6b103190-d1c5-4c2e-9cea-f984c2de158b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6b103190-d1c5-4c2e-9cea-f984c2de158b' 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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.5e+03</div><input id='attrs-22989ca5-1911-40ab-af2e-28d09ac121c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22989ca5-1911-40ab-af2e-28d09ac121c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88eb8e8a-670c-4030-85a1-69fe1a739fee' class='xr-var-data-in' type='checkbox'><label for='data-88eb8e8a-670c-4030-85a1-69fe1a739fee' title='Show/Hide data 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>mm</dd></dl></div><div class='xr-var-data'><pre>array([-4500.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77156855-b361-4bc4-afb1-42cc1787cb32' class='xr-section-summary-in' type='checkbox'  ><label for='section-77156855-b361-4bc4-afb1-42cc1787cb32' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4c615dfd-192e-4006-af86-64f03c668f3b' class='xr-index-data-in' type='checkbox'/><label for='index-4c615dfd-192e-4006-af86-64f03c668f3b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-4500.0], dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b3e9dab8-0e4f-4e94-8aa4-09fa7e1de427' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b3e9dab8-0e4f-4e94-8aa4-09fa7e1de427' 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>mm/s</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'u' (x: 1)>\n",
       "-4.5e+03\n",
       "Coordinates:\n",
       "  * x        (x) float64 -4.5e+03\n",
       "Attributes:\n",
       "    units:    mm/s"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with h5tbx.File(mode='w') as h5:\n",
    "    h5.create_dataset('x', data=[1, -4.5, 5.71], attrs={'units': 'm'},\n",
    "                          make_scale=True)\n",
    "    ds = h5.create_dataset('u', data=[1, -4.5, 5.71], attrs={'units': 'm/s'},\n",
    "                           attach_scale='x')\n",
    "    u_mm = h5.u.to_units('mm/s', x='mm')[1:2]\n",
    "u_mm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17ff27c3-3ffd-48fb-90f8-4df6ad49231b",
   "metadata": {},
   "source": [
    "## 5. Ontology accessory (under development)\n",
    "\n",
    "The idea of the `onto` accessory is to quickly enrich a group with FAIR metadata, e.g. by adding a person to an HDF5 file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ba32eeff-b2bf-4ace-9246-4de59268624d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from h5rdmtoolbox.extensions import onto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "59f87182-795d-4a50-a308-2aa736d2e571",
   "metadata": {},
   "outputs": [
    {
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       "\r\n",
       ".h5grp-sections > li > input:checked + label:before {\r\n",
       "    content: '-';\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dim-list {\r\n",
       "    display: inline-block !important;\r\n",
       "    list-style: none;\r\n",
       "    padding: 0;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dim-list li {\r\n",
       "    display: inline-block;\r\n",
       "    padding: 0;\r\n",
       "    margin: 0;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dim-list:before {\r\n",
       "    content: '(';\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dim-list:after {\r\n",
       "    content: ')';\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dim-list li:not(:last-child):after {\r\n",
       "    content: ',';\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-has-index {\r\n",
       "    text-decoration: underline;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-var-list {\r\n",
       "    list-style: none;\r\n",
       "    padding: 0;\r\n",
       "    margin: 0;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-var-list > li {\r\n",
       "    background-color: #fcfcfc;\r\n",
       "    overflow: hidden;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-var-list > li:nth-child(odd) {\r\n",
       "    background-color: #efefef;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-var-list li:hover {\r\n",
       "    background-color: rgba(3, 169, 244, .2);\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-var-list li > span {\r\n",
       "    display: inline-block;\r\n",
       "}\r\n",
       "\r\n",
       "input.h5tb-varname-in + label {\r\n",
       "    width: 140px;\r\n",
       "    padding-left: 0;\r\n",
       "    font-weight: bold;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dataset {\r\n",
       "    width: 100px;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-attributevalue {\r\n",
       "    width: 100px;\r\n",
       "    text-align: left;\r\n",
       "    color: #888;\r\n",
       "    white-space: nowrap;\r\n",
       "    font-size: 12px;\r\n",
       "}\r\n",
       "\r\n",
       "input.h5tb-varname-in + label:before {\r\n",
       "    content: ' ';\r\n",
       "    display: inline-block;\r\n",
       "    font-size: 11px;\r\n",
       "    width: 15px;\r\n",
       "    padding-left: 2px;\r\n",
       "    padding-right: 2px;\r\n",
       "    text-align: center;\r\n",
       "    color: #aaa;\r\n",
       "    text-decoration: none !important;\r\n",
       "}\r\n",
       "\r\n",
       "input.h5tb-varname-in:enabled + label:hover:before {\r\n",
       "    color: #000;\r\n",
       "}\r\n",
       "\r\n",
       "input.h5tb-varname-in:checked + label:before {\r\n",
       "    color: #ccc;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-dims {\r\n",
       "    width: 280px;\r\n",
       "    white-space: nowrap;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-attr-list {\r\n",
       "    list-style: none;\r\n",
       "    background-color: rgba(0,0,0,.0);\r\n",
       "    padding-bottom: 6px;\r\n",
       "    color: #6a6c73;\r\n",
       "}\r\n",
       "\r\n",
       ".h5tb-attr-list li,\r\n",
       ".h5tb-attr-list li:hover {\r\n",
       "    background-color: rgba(0,0,0,.0);\r\n",
       "}\r\n",
       "\r\n",
       "\r\n",
       "/* Tooltip container */\r\n",
       ".tooltip {\r\n",
       "position: relative;\r\n",
       "display: inline-block;\r\n",
       "cursor: pointer;\r\n",
       "}\r\n",
       "\r\n",
       "/* Tooltip text */\r\n",
       ".tooltip .tooltiptext {\r\n",
       "visibility: hidden;\r\n",
       "width: 300px;\r\n",
       "background-color: #555;\r\n",
       "color: #fff;\r\n",
       "text-align: center;\r\n",
       "border-radius: 6px;\r\n",
       "padding: 5px;\r\n",
       "position: absolute;\r\n",
       "z-index: 1;\r\n",
       "bottom: 125%;\r\n",
       "left: 50%;\r\n",
       "margin-left: -60px;\r\n",
       "opacity: 0;\r\n",
       "transition: opacity 0.3s;\r\n",
       "}\r\n",
       "\r\n",
       "/* Show the tooltip on hover */\r\n",
       ".tooltip:hover .tooltiptext {\r\n",
       "visibility: visible;\r\n",
       "opacity:  1;\r\n",
       "}</style></head>\n",
       "<div class='h5tb-warp'>\n",
       "\n",
       "              <ul style=\"list-style-type: none;\" class=\"h5grp-sections\">\n",
       "                    <li>\n",
       "                        <input id=\"group-ds--18234236200\" type=\"checkbox\" checked>\n",
       "                        <label style=\"font-weight: bold\" for=\"group-ds--18234236200\">\n",
       "                        /<span>(1)</span></label>\n",
       "                  \n",
       "<ul class=\"h5tb-attr-list\">\n",
       "                    </ul>\n",
       "\n",
       "              <ul style=\"list-style-type: none;\" class=\"h5grp-sections\">\n",
       "                    <li>\n",
       "                        <input id=\"group-ds-John_Doe-18235145400\" type=\"checkbox\" >\n",
       "                        <label style=\"font-weight: bold\" for=\"group-ds-John_Doe-18235145400\">\n",
       "                        John_Doe<a href=\"https://www.w3.org/ns/prov/Person\" target=\"_blank\" class=\"tooltip\"> <img class=\"size_of_img\" src=\"https://github.com/matthiasprobst/h5RDMtoolbox/blob/dev/h5rdmtoolbox/data/type_icon.png?raw=true\" alt=\"IRI_ICON\" width=\"16\" height=\"16\" /> <span class=\"tooltiptext\">@type: https://www.w3.org/ns/prov/Person</span></a><a href=\"https://orcid.org/0000-0000-0000-0000\" target=\"_blank\" class=\"tooltip\"> <img class=\"size_of_img\" src=\"https://github.com/matthiasprobst/h5RDMtoolbox/blob/dev/h5rdmtoolbox/data/id_icon.png?raw=true\" alt=\"IRI_ICON\" width=\"16\" height=\"16\" /> <span class=\"tooltiptext\">@id: https://orcid.org/0000-0000-0000-0000</span></a><span>(0)</span></label>\n",
       "                  \n",
       "<ul class=\"h5tb-attr-list\"><li style=\"list-style-type: none; font-style: italic\">first_name<a href=\"http://xmlns.com/foaf/0.1/firstName\" target=\"_blank\" class=\"tooltip\"> <img class=\"size_of_img\" src=\"https://github.com/matthiasprobst/h5RDMtoolbox/blob/dev/h5rdmtoolbox/data/iri_icon.png?raw=true\" alt=\"IRI_ICON\" width=\"16\" height=\"16\" /> <span class=\"tooltiptext\">http://xmlns.com/foaf/0.1/firstName</span></a>: John</li><li style=\"list-style-type: none; font-style: italic\">last_name<a href=\"http://xmlns.com/foaf/0.1/lastName\" target=\"_blank\" class=\"tooltip\"> <img class=\"size_of_img\" src=\"https://github.com/matthiasprobst/h5RDMtoolbox/blob/dev/h5rdmtoolbox/data/iri_icon.png?raw=true\" alt=\"IRI_ICON\" width=\"16\" height=\"16\" /> <span class=\"tooltiptext\">http://xmlns.com/foaf/0.1/lastName</span></a>: Doe</li><li style=\"list-style-type: none; font-style: italic\">orcid_id<a href=\"http://w3id.org/nfdi4ing/metadata4ing#orcidId\" target=\"_blank\" class=\"tooltip\"> <img class=\"size_of_img\" src=\"https://github.com/matthiasprobst/h5RDMtoolbox/blob/dev/h5rdmtoolbox/data/iri_icon.png?raw=true\" alt=\"IRI_ICON\" width=\"16\" height=\"16\" /> <span class=\"tooltiptext\">http://w3id.org/nfdi4ing/metadata4ing#orcidId</span></a>: <a href=\"https://orcid.org/0000-0000-0000-0000\"><img alt=\"ORCID logo\" src=\"https://info.orcid.org/wp-content/uploads/2019/11/orcid_16x16.png\" width=\"16\" height=\"16\" />https://orcid.org/0000-0000-0000-0000</a></li>\n",
       "                    </ul>\n",
       "</li>\n",
       "</ul>\n",
       "</li>\n",
       "</ul>\n",
       "</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with h5tbx.File() as h5:\n",
    "    g = h5.onto.create_person(orcid_id='https://orcid.org/0000-0000-0000-0000',\n",
    "                          first_name='John',\n",
    "                          last_name='Doe')\n",
    "    h5.dump()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7730172-11e8-47f0-93b1-9bc47aa0e1dd",
   "metadata": {},
   "source": [
    "## Custom accessory\n",
    "\n",
    "Besides the already implemented ones, users can register custom accessories, too. In the following example, we add \"device\" as a \"property with methods\". So \"device\" appears as a property which has a method \"add\". Such an implementation facilitates the interaction with HDF data, too. Note, that this \"property-like\" accessory is available for all `Dataset` objects from now on in this session:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "41f5c2c1-7de5-4e1c-b44e-4d350328f7ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "from h5rdmtoolbox import register_accessor\n",
    "\n",
    "@register_accessor('device', h5tbx.Dataset, overwrite=True)\n",
    "class DeviceProperty:\n",
    "    \"\"\"Device Accessor class\"\"\"\n",
    "\n",
    "    def __init__(self, ds):\n",
    "        self._ds = ds\n",
    "        self._device_name = 'NoDeviceName'\n",
    "        \n",
    "    def add(self, new_device_name):\n",
    "        \"\"\"adds the attribute device_name to the dataset\"\"\"\n",
    "        self._ds.attrs['device_name'] = new_device_name\n",
    "        \n",
    "    @property\n",
    "    def name(self):\n",
    "        return self._ds.attrs['device_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2af29af0-aa80-4887-bd6f-8c93d719f2e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'h5rdmtoolbox.wrapper.core.Dataset'>\n",
      "my device\n"
     ]
    }
   ],
   "source": [
    "with h5tbx.File() as h5:\n",
    "    ds = h5.create_dataset('test', shape=(2,))\n",
    "    print(type(ds))\n",
    "    ds.device.add('my device')\n",
    "    print(ds.device.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c569c3ff-aa88-4bf9-968f-5a3c210ac6b2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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