Histogram comparison between flox and xhistogram

histogram_fight.ipynb

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   "source": [
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import dask"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "id": "c11a64b9-b864-4939-ba14-aea9b31645fc",
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   "outputs": [],
   "source": [
    "from typing import Hashable, Iterable, Union, Tuple, List"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "08e2c5e2-40da-4fbe-923f-fe4167c7933e",
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   "source": [
    "from xhistogram.xarray import histogram as xhist_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "931e3ff5-1ad4-4ea1-9008-f7a146d43694",
   "metadata": {},
   "outputs": [],
   "source": [
    "from flox.xarray import xarray_reduce"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05ea8eb4-64c4-4836-adfd-d03c712316c3",
   "metadata": {},
   "source": [
    "## API"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea561838-c6d4-4d5f-9c3b-6ad1c705fe10",
   "metadata": {},
   "source": [
    "Define the function signature which we want the flox implementation to support.\n",
    "\n",
    "(Note I've changed `range` -> `bin_range` compared to xhistogram's API because range is a reserved function in python.)"
   ]
  },
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   "source": [
    "# bin types which xhistogram supports, aspirational for flox implementation\n",
    "_ALLOWED_BINS_TYPES = Union[int, str, np.ndarray, xr.DataArray, None]\n",
    "\n",
    "\n",
    "def flox_histogram(\n",
    "    *dataarrays : xr.DataArray,\n",
    "    dim : Union[Hashable, Iterable[Hashable]] = None,\n",
    "    bins : Union[_ALLOWED_BINS_TYPES, List[_ALLOWED_BINS_TYPES]] = None,\n",
    "    bin_range : Union[Tuple[float, float], List[Tuple[float, float]]] = None,\n",
    "    weights : xr.DataArray = None,\n",
    "    density : bool = False,\n",
    "    keep_attrs : bool = None,\n",
    ") -> xr.DataArray:\n",
    "    \"\"\"\n",
    "    Histogram applied along specified dimensions.\n",
    "    \n",
    "    Requires flox to be installed.\n",
    "    \n",
    "    If the supplied arguments are chunked dask arrays it will use\n",
    "    `dask.array.blockwise` (or flox equivalent) internally to parallelize over all chunks.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    dataarrays : xarray.DataArray objects\n",
    "        Input data. The number of input arguments determines the dimensionality of\n",
    "        the histogram. For example, two arguments produce a 2D histogram.\n",
    "    dim : str or tuple of strings, optional\n",
    "        Dimensions over which which the histogram is computed. The default is to\n",
    "        compute the histogram of the flattened array. i.e. over all dimensions.\n",
    "    bins :  int, str, numpy array or DataArray, or a list of ints, strs, arrays and/or DataArrays, optional\n",
    "        If a list, there should be one entry for each item in ``args``.\n",
    "        The bin specifications for each entry:\n",
    "          * If int, the number of bins.\n",
    "          * If str; the method used to automatically calculate the optimal bin\n",
    "            width, as defined by `np.histogram_bin_edges`.\n",
    "          * If a numpy array, the bin edges. Must be 1D.\n",
    "          * If a DataArray, the bin edges. The DataArray can be multidimensional,\n",
    "            but must contain the output bins dimension (named as `[var]_bins`\n",
    "            for a given input variable named `var`), and must not have any\n",
    "            dimensions shared with the `dim` argument. If supplied this DataArray\n",
    "            will be present as a coordinate on the output.\n",
    "          * If a list of ints, strs, arrays and/or DataArrays; the bin specification\n",
    "            as above for every argument in ``args``.\n",
    "          * If not supplied (or any elements of the list are `None`) then bins\n",
    "            will be automatically calculated by `np.histogram_bin_edges`.\n",
    "        When bin edges are specified, all but the last (righthand-most) bin include\n",
    "        the left edge and exclude the right edge. The last bin includes both edges.\n",
    "        A ``TypeError`` will also be raised if ``args`` contains dask arrays and\n",
    "        ``bins`` are not specified explicitly via arrays or DataArrays, because\n",
    "        other bin specifications trigger loading of the entire input data.\n",
    "    bin_range : (float, float) or a list of (float, float), optional\n",
    "        If a list, there should be one entry for each item in ``args``.\n",
    "        The range specifications are as follows:\n",
    "          * If (float, float); the lower and upper range(s) of the bins for all\n",
    "            arguments in ``args``. Values outside the range are ignored. The first\n",
    "            element of the range must be less than or equal to the second. `range`\n",
    "            affects the automatic bin computation as well. In this case, while bin\n",
    "            width is computed to be optimal based on the actual data within `range`,\n",
    "            the bin count will fill the entire range including portions containing\n",
    "            no data.\n",
    "          * If a list of (float, float); the ranges as above for every argument in\n",
    "            ``args``.\n",
    "          * If not provided, range is simply ``(arg.min(), arg.max())`` for each\n",
    "            arg.\n",
    "    weights : xarray.DataArray, optional\n",
    "        An array of weights, able to be broadcast to match the input data.\n",
    "        If supplied each value in the input data only contributes its associated\n",
    "        weight towards the bin count (instead of 1). If `density` is True, the\n",
    "        weights are normalized, so that the integral of the density over the range\n",
    "        remains 1. NaNs in the weights input will fill the entire bin with\n",
    "        NaNs. If there are NaNs in the weights input call ``.fillna(0.)``\n",
    "        before running ``hist()``.\n",
    "    density : bool, optional\n",
    "        If ``False``, the result will contain the number of samples in\n",
    "        each bin. If ``True``, the result is the value of the\n",
    "        probability *density* function at the bin, normalized such that\n",
    "        the *integral* over the range is 1. Note that the sum of the\n",
    "        histogram values will not be equal to 1 unless bins of unit\n",
    "        width are chosen; it is not a probability *mass* function.\n",
    "    keep_attrs : bool, optional\n",
    "        If True, the attributes (``attrs``) will be copied from the first original\n",
    "        object passed to the new one.  If False (default), the new object will be\n",
    "        returned without attributes.\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    hist : xarray.DataArray\n",
    "        The values of the histogram. \n",
    "        \n",
    "        See `density` and `weights` for a description of the possible semantics.\n",
    "        The returned dataarray will have one additional coordinate for each\n",
    "        dataarray supplied, named as `[var]_bins`, which contains the positions\n",
    "        of the centres of each bin, varing along a new dimension of the same name.\n",
    "        All other coordinates will be retained, unless they depend on a dimension\n",
    "        which has been reduced along, in which case they will be dropped.\n",
    "        \n",
    "    Examples\n",
    "    --------\n",
    "    \n",
    "    See Also\n",
    "    --------\n",
    "    DataArray.hist\n",
    "    Dataset.hist\n",
    "    numpy.histogramdd\n",
    "    numpy.histogram_bin_edges\n",
    "    dask.array.blockwise\n",
    "    flox.xarray.xarray_reduce\n",
    "    \"\"\"\n",
    "    return _flox_histogram(\n",
    "        *dataarrays, \n",
    "        dim=dim,\n",
    "        bins=bins,\n",
    "        bin_range=bin_range,\n",
    "        weights=weights,\n",
    "        density=density,\n",
    "        keep_attrs=keep_attrs,\n",
    "    )"
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  {
   "cell_type": "markdown",
   "id": "57c51f16-90aa-46d3-a883-96ae0a6a4751",
   "metadata": {},
   "source": [
    "## Implementation using flox"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f999ce54-5a76-4155-afac-ebf1c9c1a71e",
   "metadata": {},
   "source": [
    "Now worry about actual implementation using flox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "81d66faa-7408-4414-a37e-fd94c90ad45f",
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   "source": [
    "def _flox_histogram(\n",
    "    *dataarrays,\n",
    "    dim,\n",
    "    bins,\n",
    "    bin_range,\n",
    "    weights,\n",
    "    density,\n",
    "    keep_attrs,\n",
    "):\n",
    "    \n",
    "    # TODO argument checking\n",
    "    \n",
    "    if weights is None:\n",
    "        weights = xr.DataArray(1)\n",
    "    \n",
    "    # TODO handle multi-dimensional bins here\n",
    "    bin_intervals = tuple(pd.IntervalIndex.from_breaks(b) for b in bins)\n",
    "    \n",
    "    result = xarray_reduce(\n",
    "        weights,                        # weights\n",
    "        *dataarrays,                    # variables we want to bin\n",
    "        func=\"count\",                   # count occurrences falling in bins\n",
    "        expected_groups=bin_intervals,  # bins for each variable\n",
    "        dim=dim,                        # broadcast dimensions\n",
    "    )\n",
    "    \n",
    "    if density:\n",
    "        # TODO should this happen inside the reduction instead?\n",
    "        result = _normalize(result)  # TODO not implemented yet\n",
    "    \n",
    "    binned_variable_names = [da.name for da in dataarrays]\n",
    "    result.name = \"_\".join([\"histogram\"] + binned_variable_names)\n",
    "    \n",
    "    # Rename binned dimensions e.g. \"x\" -> \"x_bins\"\n",
    "    # This is just to make comparison with xhistogram results easier\n",
    "    result = result.rename(**{dim_name: dim_name + \"_bin\" for dim_name in binned_variable_names})\n",
    "    \n",
    "    # TODO keep attrs\n",
    "    \n",
    "    return result"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
   "id": "05881846-5eda-4928-a0b6-f5c75f70b170",
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   "source": [
    "arr = np.ones((4, 12))\n",
    "labels1 = np.array(np.linspace(0, 10, 12))\n",
    "labels2 = np.array([1, 2, 2, 1])\n",
    "\n",
    "da = xr.DataArray(\n",
    "    arr, dims=(\"x\", \"y\"), coords={\"labels2\": (\"x\", labels2), \"labels1\": (\"y\", labels1)}\n",
    ")\n",
    "da_chunked = da.chunk(x=2, y=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3302da8f-f717-4c69-9e64-80516bde0aa0",
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    "tags": []
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   "source": [
    "# flox_result = xarray_reduce(\n",
    "#     da,\n",
    "#     da.labels1,\n",
    "#     da.labels2,\n",
    "#     func=\"count\",\n",
    "#     expected_groups=(\n",
    "#         pd.IntervalIndex.from_breaks([-0.5, 4.5, 6.5, 8.9]),  # labels1\n",
    "#         pd.IntervalIndex.from_breaks([0.5, 1.5, 1.9]),  # labels2\n",
    "#     ),\n",
    "# )\n",
    "# flox_result"
   ]
  },
  {
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   "id": "eddada1c-73f0-404e-8ba9-a0848e428df2",
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       "}\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;histogram_labels1_labels2&#x27; (labels1_bin: 3, labels2_bin: 2)&gt;\n",
       "dask.array&lt;reshape, shape=(3, 2), dtype=int64, chunksize=(3, 2), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * labels1_bin  (labels1_bin) object (-0.5, 4.5] (4.5, 6.5] (6.5, 8.9]\n",
       "  * labels2_bin  (labels2_bin) object (0.5, 1.5] (1.5, 1.9]</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'>'histogram_labels1_labels2'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>labels1_bin</span>: 3</li><li><span class='xr-has-index'>labels2_bin</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2f8d64ec-f298-4544-a817-7bc53372be6e' class='xr-array-in' type='checkbox' checked><label for='section-2f8d64ec-f298-4544-a817-7bc53372be6e' 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>dask.array&lt;chunksize=(3, 2), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 48 B </td>\n",
       "                        <td> 48 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3, 2) </td>\n",
       "                        <td> (3, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">3</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-fc1264fb-2de4-4dac-aefa-7d789f9ffda2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fc1264fb-2de4-4dac-aefa-7d789f9ffda2' 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'>labels1_bin</span></div><div class='xr-var-dims'>(labels1_bin)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(-0.5, 4.5] (4.5, 6.5] (6.5, 8.9]</div><input id='attrs-08f274cb-765d-4903-a09a-b90e3a5c921f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08f274cb-765d-4903-a09a-b90e3a5c921f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81154016-e347-49d6-a30d-53e87e7db5fc' class='xr-var-data-in' type='checkbox'><label for='data-81154016-e347-49d6-a30d-53e87e7db5fc' title='Show/Hide data 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([Interval(-0.5, 4.5, closed=&#x27;right&#x27;), Interval(4.5, 6.5, closed=&#x27;right&#x27;),\n",
       "       Interval(6.5, 8.9, closed=&#x27;right&#x27;)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>labels2_bin</span></div><div class='xr-var-dims'>(labels2_bin)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(0.5, 1.5] (1.5, 1.9]</div><input id='attrs-e7798ed9-2201-4ed8-89ff-ffcaca344e87' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7798ed9-2201-4ed8-89ff-ffcaca344e87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ba31473-e61e-407f-b614-5694a84a7825' class='xr-var-data-in' type='checkbox'><label for='data-1ba31473-e61e-407f-b614-5694a84a7825' title='Show/Hide data 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([Interval(0.5, 1.5, closed=&#x27;right&#x27;), Interval(1.5, 1.9, closed=&#x27;right&#x27;)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6845c39c-eb87-4cbf-b17a-c1dcac8ef03e' class='xr-section-summary-in' type='checkbox'  ><label for='section-6845c39c-eb87-4cbf-b17a-c1dcac8ef03e' 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>labels1_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-918dbe42-84aa-4f3c-b84d-bb543d901865' class='xr-index-data-in' type='checkbox'/><label for='index-918dbe42-84aa-4f3c-b84d-bb543d901865' 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([(-0.5, 4.5], (4.5, 6.5], (6.5, 8.9]], dtype=&#x27;object&#x27;, name=&#x27;labels1_bin&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>labels2_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8ed182bf-ee17-455c-85c7-e08bcf168424' class='xr-index-data-in' type='checkbox'/><label for='index-8ed182bf-ee17-455c-85c7-e08bcf168424' 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([(0.5, 1.5], (1.5, 1.9]], dtype=&#x27;object&#x27;, name=&#x27;labels2_bin&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35d0257c-cf03-4326-a42f-8cd74ac4d7a1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-35d0257c-cf03-4326-a42f-8cd74ac4d7a1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'histogram_labels1_labels2' (labels1_bin: 3, labels2_bin: 2)>\n",
       "dask.array<reshape, shape=(3, 2), dtype=int64, chunksize=(3, 2), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * labels1_bin  (labels1_bin) object (-0.5, 4.5] (4.5, 6.5] (6.5, 8.9]\n",
       "  * labels2_bin  (labels2_bin) object (0.5, 1.5] (1.5, 1.9]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flox_result = flox_histogram(\n",
    "    da_chunked.labels1, \n",
    "    da_chunked.labels2,\n",
    "    bins=[\n",
    "        [-0.5, 4.5, 6.5, 8.9], \n",
    "        [0.5, 1.5, 1.9]\n",
    "    ],\n",
    ")\n",
    "flox_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c5dbbe6c-9dab-4b85-9ef9-67b9c5a6fefc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flox_result.data.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "761f0dfe-65cf-4dff-b0d5-1f069ebd8b53",
   "metadata": {},
   "source": [
    "## Test against xhistogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cc4f09cf-4559-4428-8ca5-d7f1ba1cd287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --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",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  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",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
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       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  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",
       "}\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;histogram_labels1_labels2&#x27; (labels1_bin: 3, labels2_bin: 2)&gt;\n",
       "dask.array&lt;sum-aggregate, shape=(3, 2), dtype=int64, chunksize=(3, 2), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * labels1_bin  (labels1_bin) float64 2.0 5.5 7.7\n",
       "  * labels2_bin  (labels2_bin) float64 1.0 1.7</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'>'histogram_labels1_labels2'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>labels1_bin</span>: 3</li><li><span class='xr-has-index'>labels2_bin</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9f5037d3-67ed-40f9-8b10-b5d84bd92f27' class='xr-array-in' type='checkbox' checked><label for='section-9f5037d3-67ed-40f9-8b10-b5d84bd92f27' 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>dask.array&lt;chunksize=(3, 2), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 48 B </td>\n",
       "                        <td> 48 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3, 2) </td>\n",
       "                        <td> (3, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">3</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-5568d48d-82c4-48d6-8748-fa8cf3ac983b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5568d48d-82c4-48d6-8748-fa8cf3ac983b' 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'>labels1_bin</span></div><div class='xr-var-dims'>(labels1_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0 5.5 7.7</div><input id='attrs-f8d49280-791f-497c-83cf-5170c8e7fa93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8d49280-791f-497c-83cf-5170c8e7fa93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e81afdac-bc30-46ee-b031-c0d1377779ad' class='xr-var-data-in' type='checkbox'><label for='data-e81afdac-bc30-46ee-b031-c0d1377779ad' title='Show/Hide data 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([2. , 5.5, 7.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>labels2_bin</span></div><div class='xr-var-dims'>(labels2_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.7</div><input id='attrs-3a215e6a-a5c3-4a66-9858-2e7e1062640f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a215e6a-a5c3-4a66-9858-2e7e1062640f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38105629-d1e2-47ad-8fb9-8b099f94a1b2' class='xr-var-data-in' type='checkbox'><label for='data-38105629-d1e2-47ad-8fb9-8b099f94a1b2' title='Show/Hide data 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. , 1.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1f237cd5-2593-44da-b4af-4ea4a059a96d' class='xr-section-summary-in' type='checkbox'  ><label for='section-1f237cd5-2593-44da-b4af-4ea4a059a96d' 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>labels1_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-06ec3897-220c-42dd-a0dd-75aee8aa8884' class='xr-index-data-in' type='checkbox'/><label for='index-06ec3897-220c-42dd-a0dd-75aee8aa8884' 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(Float64Index([2.0, 5.5, 7.7], dtype=&#x27;float64&#x27;, name=&#x27;labels1_bin&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>labels2_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2dfc5be7-17af-4bbd-806d-d954882ec763' class='xr-index-data-in' type='checkbox'/><label for='index-2dfc5be7-17af-4bbd-806d-d954882ec763' 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(Float64Index([1.0, 1.7], dtype=&#x27;float64&#x27;, name=&#x27;labels2_bin&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-94d30caa-fe77-476f-89b9-1436eb19f8ac' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-94d30caa-fe77-476f-89b9-1436eb19f8ac' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'histogram_labels1_labels2' (labels1_bin: 3, labels2_bin: 2)>\n",
       "dask.array<sum-aggregate, shape=(3, 2), dtype=int64, chunksize=(3, 2), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * labels1_bin  (labels1_bin) float64 2.0 5.5 7.7\n",
       "  * labels2_bin  (labels2_bin) float64 1.0 1.7"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhist_result = xhist_histogram(\n",
    "    da_chunked.labels1, \n",
    "    da_chunked.labels2, \n",
    "    bins=[\n",
    "        np.array([-0.5, 4.5, 6.5, 8.9]), \n",
    "        np.array([0.5, 1.5, 1.9]),\n",
    "    ],\n",
    ")\n",
    "xhist_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "acd6d4f5-c398-48bb-b282-985528a35bb5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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r3mqMiIjIHL799ls8/fTTvKhvh8mTJ+PJJ59EdHS02FGIugTrQfuxHtyL46f9OH7oYTif2o/ziYiIyLzYeCEiIjJRTU0N4uPjERkZKXYUqxEZGYldu3ahrq5O7ChEZsV60HGsB//B8dNxHD90P5xPHcf5REREZD5svBAREZkoPj4e9fX1WLp0qdhRrMaKFStw584d7Nu3T+woRGbFetBxrAf/wfHTcRw/dD+cTx3H+URERGQ+3OOFiIjIRAsWLIBer4darRY7ilWZNWsWvL29sWvXLrGjEJkN60HnsB78guOnczh+qC2cT53D+URERGQW3OOFiIjIFHq9HocPH8bs2bPFjmJ1Zs+ejYyMDPAzIGQrWA86j/WA48cUHD90N86nzuN8IiIiMg82XoiIiEyQn5+PiooKhISEiB3F6oSEhKC0tBQFBQViRyEyC9aDzmM94PgxBccP3Y3zqfM4n4iIiMyDjRciIiITZGRkwNfXF4GBgWJHsTpBQUHw8vJCenq62FGIzIL1oPNYDzh+TMHxQ3fjfOo8ziciIiLzYOOFiIjIBMeOHcOUKVMgkUjEjmJ1HBwcMHnyZOTk5IgdhcgsWA86j/WA48cUHD90N86nzuN8IiIiMg82XoiIiEzw888/89OUJnj88cdRVFQkdgwis2A9MI291wOOH9PY+/ih1jifTMP5REREZDo2XoiIiDpJr9fj3LlzGDlypNhRrNbIkSNx+vRpbuBKVo/1wHT2XA84fkxnz+OHWuN8Mh3nExERkenYeCEiIuqkCxcuoKGhwewX9nq9Hp9//jnGjRuHPn36oHfv3hg/fjw2bNiA2tpa4/M2bdoEiUSCPXv23HOM5scSEhKM30tOToZEIsHGjRuRkZGByZMnw83NDf7+/li/fr3xeZ9//jlGjhwJFxcXPPbYY1CpVGb9/VoaOXIkampqcPXq1S57DaLuwHpgOnuuBxw/prPn8UOtcT6ZjvOJiIjIdI5iByAiIrJWFy9eBAAEBASY9bi///3v8ac//anV93Jzc5GbmwtnZ2e8/vrrJh3/2LFjePvtt6HT6QAAtbW1+P3vf48ePXqguLgYf/zjH43PLSoqwtKlSzF8+HCMGTPGpNdty7BhwwD88iaJv7+/2Y9P1F1YD0xnz/WA48d09jx+qDXOJ9NxPhEREZmOK16IiIg6qbq6GgDg6elp1uMmJCTAzc0NcXFxqKysRE1NDU6cOIG33noL7u7uJh9/9+7deP3113Hx4kXcuXMHe/bsgZOTEz788EN8+eWX2LRpE0pLS1FWVoY333wTBoMBn332mRl+s3s1/9vdvn27S45P1F1YD0xnz/WA48d09jx+qDXOJ9NxPhEREZmOK16IiIg66c6dO3B1dYWjo3n/nA4aNAgAEB4ebjz26NGjMXr0aLMcPywsrNWF+qJFixAeHo64uDj85S9/werVq42Pffrpp9i0aRMKCwvN8tp369mzJxwdHY1vkhBZK9YD09lzPeD4MZ09jx9qjfPJdJxPREREpuOKFyIiok66ffu2WT7heLfPPvsMBoMBjz76KF566SX84x//QH5+vtmOP23atHu+N2TIEADA1KlTW31fKpVi4MCBKCkpMdvr383d3Z2fqCSrx3pgHvZaDzh+zMNexw+1xvlkHpxPREREpmHjhYiIqJPq6urQs2dPsx939OjR+PnnnxEdHY2hQ4ciKysLYWFh+NWvfoUff/zR+DwHh1/+jBsMhjaz3Y+Li8s935NIJA98rK3XMBc3N7dWm9ISWSPWA/Ow13rA8WMe9jp+qDXOJ/PgfCIiIjINbzVGRETUSa6urg+8gDaFo6Mjpk6davyEY21tLUaOHInVq1fj3//+NwDA19cXwC8bn94tPT29S3J1hZqami55g4SoO7EemIe91gOOH/Ow1/FDrXE+mQfnExERkWm44oWIiKiTuuoWDJMnT8ZXX32FwsJC1NXVoaqqCsnJySgrK8P58+eNzwsMDAQAbNy4EYcOHUJdXR0uXryIN998EwkJCWbP1VXu3LkDDw8PsWMQmYT1wDzstR5w/JiHvY4fao3zyTw4n4iIiEzDFS9ERESd5OHhgbq6Ouh0OrNu4JqXl4ecnJw2H3vxxReN/x0QEICFCxciPj4eM2bMMH7f0dERkZGRiImJMVumrlJbWwudTscLe7J6rAems+d6wPFjOnseP9Qa55PpOJ+IiIhMxxUvREREndSrVy8AQFVVlVmP+69//QuvvfYaAgMD4erqCh8fHwQHB2PTpk347LPPWj138+bN+PWvfw1vb2+4uLhg0qRJ0Gq192zCaqma/+2a/y2JrBXrgensuR5w/JjOnscPtcb5ZDrOJyIiItNJBEEQxA5BRERkjc6ePYvhw4fj+++/x/jx48WOY5WOHj2KKVOm4PLly/D39xc7DlGnsR6Yzp7rAceP6ex5/FBrnE+m43wiIiIymY4rXoiIiDpp6NCh6NGjB4qKisSOYrWKiorg5uaGQYMGiR2FyCSsB6az53rA8WM6ex4/1Brnk+k4n4iIiEzHxgsREVEnSaVSDBs2jBf2JigqKsKIESMgkUjEjkJkEtYD09lzPeD4MZ09jx9qjfPJdJxPREREpmPjhYiIyASPPfYYCgsLxY5htU6dOoWRI0eKHYPILFgPTGPv9YDjxzT2Pn6oNc4n03A+ERERmY6NFyIiIhNMmDABWVlZ4JZpHWcwGJCdnY2JEyeKHYXILFgPOo/1gOPHFBw/dDfOp87jfCIiIjIPNl6IiIhMMGPGDJSWluLUqVNiR7E6+fn5KCsrQ0hIiNhRiMyC9aDzWA84fkzB8UN343zqPM4nIiIi83AUOwAREZE1Gzt2LHr37o309HQEBgaKHceqpKenw9fXF0888YTYUYgAAGfOnMHChQvRu3dv9O/fHz4+PvD29oaXlxe8vb3v+fLy8mr186wHncd6wPFjCo4fuhvnU+dxPhEREZmHRODaWyIiIpMsWLAABoMBSUlJYkexKrNnz0afPn2we/dusaMQAQAEQYC3tzcqKioAAE5OTnBwcIAgCNDpdDAYDK2eL5FI4OnpiT59+sDX1xeDBg1CZWUlevbsyXrQQawHv+Dfk87h+KG2cD51DucTERGRWei44oWIiMhEixYtwgsvvIBbt27Bx8dH7DhWoaSkBBkZGdi5c6fYUYiMJBIJwsLCoFKpoNPp0NTU9MDnC4KAyspKVFZWokePHvjyyy/x008/sR50EOvBf/DvScc1j5+PPvoIKpUKt2/fRkNDA6qrq1FbW4uGhgZUVFSgoaEBtbW1KC8vR319PaqqqnDnzh00NDTg9u3b6NWrFy5dugRHR14i2wrOp45jPSYiIjIfnlUSERGZaOHChXj11Vexe/duvPbaa2LHsQrbt2+Hm5sb5s2bJ3YUolZkMlm7P+UrlUphMBjwxhtv4I9//CN69OiBESNGsB50EOvBf/DvScc1j5+lS5fipZdeQnJyMgDA2dkZEokEAKDX6yEIAvR6fZvHcHBwwIIFC9h0sTGcTx23fft29OzZE56entBqta0eq6+vR11dXavvNTU14c6dO62+ZzAYMH78eIwfP77L8xIREVky3mqMiIioHdq6sGxsbERNTQ0A4N1338XFixdx7NgxMeJZnTFjxmDChAn4+uuvxY5C1MrFixcxdOjQhz7P0dERfn5++O677zB16tRWj61cuRJFRUWsB+3EetAax0/HtBw/giDgb3/7G9566y0AgE6na9cxJBIJYmNjERER0ZVRSQScTx0zZswYPP300/D29sann36K9rxd5OTkZPxvg8EAvV6PvLw8BAUFdWVUInaam1IAACAASURBVCIiS6dzEDsBERGR2H744Qf07t0bHh4e8PDwgJubGyQSSasvZ2dneHl5tfry8/PDsGHDsGrVKixZsgT/+te/kJeXJ/avY/GOHTuGkydPIioqSuwoRACAn376CRs3boRcLseoUaMe+FypVAqJRIJVq1bh1KlT9zRdAOD5559nPWgn1oN7cfy0393jRyKR4De/+Q2OHTuGgQMHtnpD+EGkUilmz57dlVFJJJxP7dc8n1auXIlPPvkEe/fuhZub20NXgjU1NRm/9Ho9hgwZwqYLERERuOKFiIgIADB8+HCcPXu2wz/34osv4osvvoCTkxOeeuopDBkyBHv27OmChLZDLpejrKwMOTk5YkchO1VaWorMzExotVocOHAAV65cgbu7OyZOnAiZTIa8vDwkJCSgsbGx1c85OTnB29sb27dvx8yZMx/4GqwH7cN60DaOn/Z50Pi5ffs2XnnlFXz33XeQSCT3/eS+g4MDnnjiCeTk5KBnz55dHZlEwPnUPm3Np7NnzyI8PBynT5++7636WnJ2dsZ///d/43//93+7MioREZE14IoXIiIiAFi1alW77+0ulUrh4OCA9evX45tvvjF+ovb3v/894uPj8dNPP3VlVKt28uRJ7N+/H//zP/8jdhSyI7W1tdBqtXjnnXcwfvx4+Pn5Yfny5cjNzcXy5cuRmpqK8vJypKamYt26dVi+fDmampqMP+/g8Mspc3h4OAoLCx/adAFYD9qD9eD+OH4e7mHjx8PDA9u3b8e2bdvg4uJy39UvEokEP/74I3x8fKBQKPDNN9/g+vXrXRmduhnn08Pdbz49+uijyMvLa/eqxMbGRiiVyq6ISEREZHW44oWIiAjAtWvX4O/v/9B7WTs6OqJnz56Ij4+/581Xg8GAUaNGISgoCNu3b+/KuFZr0aJFuHDhAnJzc42bHhOZm16vx4kTJ6DVaqHVapGVlYWGhgYEBARAJpNBJpMhNDQUvXr1avPnq6ur4eXlBb1eDycnJ3h4eGDr1q0IDw9vdwbWg4djPbg/jp+H68j4KSoqglKpxKlTp9rc9yUvLw8//vgjNBoNkpOTcfv2bQQGBkKhUEAulyM4OJhj1IpxPj1ce+bTN998g9deew3A/fdPkkqlWL58OaKiohASEmL84AIREZEd0rHxQkREBKChoQFBQUEPvJWCk5MTAgICsH//fgQEBLT5nLi4OCiVSmRlZSE4OLgrI1ud9PR0zJw5E2q1GnK5XOw4ZGPOnz9vbLRotVpUVFSgX79+mDp1KmQyGebOnYtBgwa1+3hPP/00vv/+ezz77LP45ptv4OPj0+FMrAf3x3rwcBw/99eZ8dPQ0ID//u//xueffw6JRAKDwQAACAwMREFBgfF59fX1OHLkCNRqNeLj43H16lUMHjwYYWFhkMvlmD17Nnr06NElvxd1Hc6n++vIfMrNzcX8+fNRWlraamUo8Mt58uTJk1FaWopTp05h0KBBiIiIgFKpxKRJk9i8JCIie8PGCxER2S9BEJCdnY2YmBjExsaiqqoKgiC0uepFKpVCJpNh9+7d8PT0fOBx582bh8uXLyMvL6/dG/vausbGRowZMwYjRoxAQkKC2HHIBty6dQsZGRnQarVISUnBxYsX4ebmhkmTJhlXtYwdO7bTb/T89a9/ha+vL5YtW2ZSTtaDe7EetB/Hz71MHT9JSUmIiopCbW0tAGDdunUP3I+ioKAAGo0GarUa2dnZcHV1RUhICBQKBcLDw+Hn59fp34W6F+fTvTozn8rKyrBkyRJkZGQYG5jNfvzxRzzxxBMoKCiASqVCbGyssQmzcOFCKJVKriAjIiJ7wcYLERHZnytXrmDHjh3YvHkzzpw5g8DAQCiVSkRERGD8+PFoaGi452fWrVuHjz/+uF23TDhz5gyefPJJfPzxx/jd737XFb+C1fnkk0/wf//3fygoKMAjjzwidhyyQnV1dTh69KhxRUt+fj4kEgnGjBljbLRMnToVzs7OYkdthfXgXqwH7cfxcy9zjJ+rV69iyZIlyM7Oxr///W889dRT7fq5y5cvIzk5GWq1GqmpqdDpdBgzZgzkcjkWL16MwMDATuWh7sH5dK/Ozie9Xo/33nsPn3zyiXEF2bBhw3D27Nl7ntvchNm9ezd+/vln+Pv749lnn2UThoiIbJ0OAhERkR2orKwUtm3bJshkMkEikQheXl7CmjVrhKysrFbPW7p0qeDk5CQAEKRSqeDk5CTExMR0+PU++OADoWfPnsKPP/5orl/BauXn5wsuLi7CJ598InYUsiJ6vV44fvy4sH79ekEmkwkuLi4CACEgIEBYs2aNEBsbK1RUVIgds11YD/6D9aDjOH7+w5zjR6fTCRs2bBAMBkOnfr6mpkZISkoS1qxZI/j5+Rnr09q1a4XU1FShsbHR5IxkfpxP/2GO+ZSUlCS4u7sLAIT33nvvoc//6aefhPfff18YOXKkAEDw9/cX1q5dK2RlZXV6LhIREVmoJq54ISIim6XX65GRkYHo6GjExcXBYDBAJpMhKioKCxYsaPM2E8nJyZgzZw4cHR3h4+OD/fv3IygoqMOvrdPpMGPGDJSWluL48ePw8PAwx69kde7cuYOnnnoK/fr1Q1paGqRSqdiRyILduHHDuLfC/v37UVZWhr59+2L69OmQyWQICwvD4MGDxY7ZYawHv2A96Jji4mJkZGTg0KFDyMvLQ3V1NcePhY4fvV6PEydOQK1WQ6VSobCwEF5eXpg5cybkcjnmz5//0NuUUvdgPf6FOefTuXPnsGjRInz33Xf41a9+1e6fa14Js3PnTpw+fRqDBw/GggULuBKGiIhsBW81RkREtqegoAAxMTHYunUrbt26hUmTJiEqKgpLly5Fr169HvizOp0OAwcOxNChQ5GYmIh+/fp1OsfVq1cRFBSEWbNmYceOHZ0+jjV77rnnkJqaivz8fAwYMEDsOGRh7ty5g2PHjhlvH5abm4uePXti8uTJZtmnxZKwHrAePExZWRkOHTqEjIwMHDx40HjLno8++ghRUVEcP1Y0fs6fPw+1Wg2NRoPMzEwIgoAJEyZAoVBg4cKFGD58uNgR7RrrsfnnU319PVxcXDr9881NmB07duDMmTMYMmQI5s+fzyYMERFZMzZeiIjINly9ehVxcXHYunUrTp48icceewxLlixBVFQUAgICOnSsgwcPYvr06ejRo4fJufbt2weFQoE//elPePPNN00+njX5+OOP8d577yE5ORkymUzsOGQBdDodTp48aWy0ZGZmwmAwtNqn5ZlnnjHL3LNErAesBy1VV1fj8OHDSE9PR0pKCgoLCwEATk5OaGxsBADIZDIcPHgQDg4OHD9WOn7Ky8uRlpYGtVqNpKQkVFVVITAwEAqFAnK5nG8qi4TzyXLn04OaMFOmTBE7HhERUXux8UJERNaruroaCQkJiImJQXp6Ojw9PaFUKhEZGWlRb2R88cUXeOONN7B582asWrVK7DjdIiYmBitXrsTGjRuxdu1aseOQiM6fP29stBw8eBDV1dUICAgwNlpmzpwJLy8vsWN2G9YD+60HtbW1yM7OxpEjR5CRkYHs7GzodDo4OzsbGy3NpFIpfHx88NNPP8HHx8f4fY4f6x4/Op0Ox44dg0ajQXx8PM6cOYO+ffsiLCwMCoUCc+bMgbu7u9gx7Qbnk+XPp+YmzHfffYezZ8/ikUceQXh4OJswRERkDdh4ISIi69Jy35b4+HjodDrMmjULUVFRmD9/PpydncWO2KZ33nkHGzZsQEJCAubOnSt2nC6lVquxcOFCvPvuu/jwww/FjkPdrKSkBIcPH4ZWq8X+/ftx9epVeHt7IyQkBDKZDLNmzcLQoUPFjikq1gP788Ybb+Crr766b6PlblKpFJmZmQgODr7nMY4f21FQUACNRgO1Wo3s7Gy4uLggODgYcrkcSqXS4m+pZgs4n6xHcxNm+/btOHfuHIYOHQqFQsEmDBERWSo2XoiIyDo079uybds2FBcXY9y4cYiMjMSKFStafRrYUgmCgNWrV2PHjh347rvvsGjRIrEjdYndu3cjKioKq1atwldffSV2HOoGNTU1yMnJMa5qycvLg1QqxejRoyGXy6FQKBAUFAQHBwexo1oM1gP7c/LkSYwfPx46ne6hz3VwcMD69evx9ttvt/k4x49tunnzJg4cOACNRoMDBw6gtrYWQUFBxjo6btw4sSPaJM4n69TchImJicH58+eNTZioqCjOFSIishQ6CERERBbq2rVrwsaNG4WgoCABgDB48GBh3bp1wpkzZ8SO1ikGg0H4r//6L0EqlQpffvml2HHM7vPPPxccHByEtWvXCnq9Xuw41EV0Op1w/PhxYf369YJMJhOcnZ0FAEJAQICwZs0aITY2VqiurhY7psWzl3oQFRUlVFRUiB3HInzwwQeCVCoVANz3y8nJSQgLCxMMBsMDj2Uv48de/57U1tYKqampwtq1a4UBAwYIAIRHHnlEWLNmjZCUlCQ0NDSIHdGmcD5Zt+PHjwtr164VBg4cKAAQAgMDhffff18oLCwUOxoREdm3JjZeiIjIotTW1gqxsbGCXC4XHB0dhd69ewuRkZFCamrqQ9+IshZ/+MMfBIlEIrz77ruCTqcTO47JmpqahDfffFOQSCTCp59+KnYc6gLnzp0Tvv76a0GpVAq9e/cWAAh+fn6CUqkUvv76a+HatWtiR7Ratl4Prl+/LvTv31947733hLKyMrHjiaqpqUl48sknBUdHxzabLlKpVPDz8xNu3brV7mPa+vghQdDr9cLx48eF999/Xxg3bpwgkUgENzc3QS6XC9u2bRPKy8vFjmgzOJ+sm16vF7Kyslo1LNmEISIiEbHxQkRE4mu+UFqzZo3g4eEhSKVSQSaTCdu2bRNqamrEjtclNm/eLLi4uAgzZswQrl+/LnacTrty5YowZcoUwdXVVYiJiRE7DplJaWmpEBsbK6xZs0YYPHiwAEBwd3cXZDKZsH79euH48eNiR7Qptl4PXn75ZQGA4OrqKqxbt04oKSkRMaW4/vSnPwkSieS+jZejR492+Ji2Pn6otQsXLghff/21IJfLBWdnZ0EqlQrBwcHC+vXrhVOnTokdz+pxPtmGlk2Y/v37t2rCcJ4QEVE3aeIeL0REJJrCwkLExsZi27ZtuHjxonHflmXLlsHX11fseF0uPz8fS5YsQXV1NaKjozF79myxI3XIvn378Pzzz8PHxwexsbEYNWqU2JGok2pra5Gdnd3mPi0ymQwymQzTpk2Dk5OT2FFtli3XgwsXLmD48OHQ6/VwdHSEVCrFyy+/jLfffhsDBw4UMXX3KS0txauvvor4+HiMHTsWJ06cgF6vNz7u4OCADRs24De/+U2njm/L44fur6amBunp6VCpVNBoNKioqEBAQIBxX5jp06fD0dFR7JhWh/PJthgMBmRnZ0OlUkGlUuHGjRsIDAyEUqnEsmXLMHLkSLEjEhGRbeIeL0RE1L3KysqEr7/+WggODhYACP7+/sK6deuEoqIisaOJoqqqSli6dKkgkUiEFStWCDdu3BA70kNdvXpVWLx4sQBAiIqKEm7fvi12JOqgu/dp6dGjxz37tFRWVood0+7Ycj1YsWKF4OTk1GovE0dHR+G5554TTp8+3c2pu1dsbKzQt29fYciQIUJqauo9txxzcnIS5s6da/LtNG15/NDD6XQ6ISsrS1i3bp3w2GOPCQAEb29vITIyUoiNjRWqqqrEjmhVOJ9sU8uVMH5+fq1WwtjrtQgREXUZ3mqMiIi6Xl1dnZCUlCQolUrByclJ8PT0tLl9W0yVmJgoDBkyRPD09BT++te/Co2NjWJHukdDQ4Pwl7/8RfDw8BCGDRsm7Nu3T+xI1AEt92nx8vISAAi+vr7GfVouX74sdkT6/2yxHhQWFrZ5iy0nJydBKpUKzz33nM3d/qWkpERYtGiRIJFIhDVr1gjV1dXGx/Lz8wWpVCpIJBLB399fqKioMNvr2uL4oY47d+6csHHjRkEmkwmOjo6Ci4uLIJPJhI0bNwpXrlwRO57V4HyyXc3NyrVr1wr9+vVr1YSx9Q8EEBFRt2DjhYiIukbLfVt69erVat+WO3fuiB3PItXU1Ajvvvuu4OzsLAwePFj4+9//LtTV1YkdS6ipqRE2btwoDBo0SHBxcRHee+89oba2VuxY9BA3b9407tMydOhQAYDQs2fPVvu0sPFpuWyxHoSHh7da9XJ3A0YikQhz584VcnNzu/i36HqxsbGCj4+PcZVLW95//33B2dm5S/ZMssXxQ51369YtYdu2bYJSqRR69eplfIN53bp1QlZWFv8WPATnk+1r2YTx9fVt1YQ5c+aM2PGIiMg6sfFCRETmderUKeH9998XAgICjBct69evF4qLi8WOZjUuXbokvP7664Krq6vg5+cnfPTRR6KsRrh48aLwhz/8QfD19RV69uwp/Pa3vxWuXr3a7TmofZqamoy3mRk3bpzg4OAgSKVSYdy4ccK6deuE1NRUob6+XuyY1EG2VA++//77NpsuLb8cHR0FiUQihIeHC/n5+V3023SdB61yuVtDQ4OQmJjYpXlsafyQedTV1QmpqanC2rVrhUGDBhlXP0ZGRgpJSUn8O/EAnE/2gU0YIiIykyaJIAhC1+4jQ0REtq6iogIqlQrR0dHIzs7GgAEDsGjRIqxatQpjxowRO57VKikpwYYNG7BlyxaUl5dj+vTpiIyMRHh4OLy8vLrkNcvKypCQkICYmBgcPnwYffv2xerVq/G73/0Offv27ZLXpM47f/48tFottFotkpOTcfv2bQQEBEAmkxm/+vTpI3ZMMgNbqQczZ87E4cOHodPp7vscBwcHuLm5IT09HePHj+9s/G6nUqnw6quvws3NDZs2bYJMJhM7kpGtjB8yv4KCAmg0GqjVamRnZ8PV1RUhISFQKBQIDw+Hn5+f2BEtDueT/dDr9cjJyYFKpcLOnTtx8+ZNBAYGQqlUIjIyEsOGDRM7IhERWS4dGy9ERNQpDQ0NSElJQUxMDBITEyGVSiGXyxEZGYk5c+bA0dFR7Ig2o7GxEQcOHEBMTAw0Gg2ampowZswYhISEYMaMGRg3bhz69evXqWMXFxcjNzcX6enpSE9Pxw8//ABnZ2eEh4cjMjISoaGhcHJyMvNvRJ1VXFyMrKwsaLVaaDQaXL9+HX379sX06dMhk8kQGhqKIUOGiB2TupC114NDhw5hxowZ931cKpXC1dUV6enpeOqpp0x6re5SUlKC1157DfHx8XjxxRfx5z//GR4eHmLHapO1jx/qWqWlpUhOToZKpUJqaiqampoQFBQEuVwOhUKBcePGiR3RonA+2ZeWTZgdO3bg1q1bxiZMVFQUAgICxI5IRESWhY0XIiLqmNzcXERHR2PHjh0oLy/HpEmTEBUVheXLl8Pd3V3seDavsrIShw4dQkZGBtLS0lBYWAhBENC7d2+MGDECI0aMwIABA+Du7m78AoA7d+4Yv65fv46ioiKcPn0aVVVVkEgkeOKJJxASEoKQkBBMnz4dvXr1Evk3JeCX/2/Hjh0zrmrJzc2Fq6srgoODjStagoKC4ODgIHZUEoG11oOJEyfi+PHj0Ov1rb5vjU2X5lUu7u7u2LRpE2bOnCl2pHaz1vFD3aO2thZpaWnQaDRISkpCcXExAgICjE2YadOm8Y3/Fjif7Iter0dGRgaio6ORlJSE27dvY9KkSVAqlVAqlRgwYIDYEYmISHxsvBAR0cNdvnwZO3fuxKZNm3D27Fnjp7tWrVrFT9eL7ObNm/jpp59QVFSEoqIinDlzBsXFxcaL+Nu3b0MikbS60Pfz88PIkSMxYsQIjBw5EqNGjYK3t7fYvwoB0Ol0OHnypLHRkpmZCb1ej6CgIGOjZcqUKXBxcRE7Klmgh9WDO3fuAIDo9WDfvn2Qy+WtvieVSmEwGPDxxx/jnXfe6dLXN4eSkhK8+uqr2Lt3r8Wvcmkvaxk/1P0MBgPy8/OhVquh0WiQm5sLLy8vzJw5E3K5HPPnz4enp6fYMS0Kz8/sR/NdAFQqFRITE3Hnzh02YYiICGDjhYiI7qeyshJJSUmIiYlBWloa/Pz8jEvpeasJ67Fz5044OTkhIiJC7Ch0Hy33aUlJSUFVVVWrfVpCQkL4xgvZnCeffBKFhYXQ6/VwdHSEq6srFi5ciO3btyM6OhrLly8XO+J9WfMqFyJzOH/+vLEJk5mZCYPBgIkTJ0KhUODZZ5/FiBEjxI5o8Xh+Zpse1IRZvHgx+vfvL3ZEIiLqPmy8EBHRf7RcNh8XFweDwQCFQsF9W6yYXC6Ho6MjEhISxI5C/19JSQkOHz4MrVaLAwcO4MqVK3B3d8fEiRONzRY2N8nWxcbGYunSpXBwcICHhwcOHTqE0aNH45133sGf//xnxMTEYNmyZWLHbMUWV7kQmaq8vBxpaWlQq9VISkpCVVUVAgMDoVAoIJfLMXnyZN4Osw08P7N99fX1SE1NhUqlQkJCAmpqaoxNmCVLlsDPz0/siERE1LXYeCEiov/s27Jr1y7cunXLuG/LsmXL+KaSFauoqDBu6lpaWorevXuLnMg+1dbWIjs727iqJS8vD1KpFKNHjzY2WnivfLI3er0ew4cPR0VFBTIzM/Hkk08CAARBwG9/+1t88cUX2L59O5YuXSpy0l9wlQvRwzVvPq7RaLB3716cPn0affv2RVhYGBQKBebMmcP9AMHzM3vEJgwRkV1i44WIyF5duXIFO3bswJYtW3D69Gk8/vjjWLx4MVauXImhQ4eKHY/M4J///CdeeeUV43+vWrVK5ET2Qa/X48SJE8ZGS1ZWFhoaGlrdPiw0NJQb5JLdi4+Px/DhwzFq1KhW3xcEAb/5zW/w1VdfYffu3Xj22WdFSnjvKpe//OUvfOOYqJ0KCgqg0WigVquRk5ODHj16IDg4GHK53K73vuD5mX1r2YTZu3cv6urqMHHiRCiVSixdutTYlCMiIqvHxgsRkT2pqqpCYmKicd+WPn36ICIiApGRkZgyZYrY8cjMnnnmGWRnZ0MikWDq1KlIT08XO5LNarlPi1arRUVFBfz8/PDMM89AJpNh3rx5GDhwoNgxiayGIAhYu3Ytvv76a8TGxmLBggXdnkGlUuGVV16Bh4cHNm/ejJCQkG7PQGQrbt68iQMHDkCj0eDAgQOora1FUFAQ5HI5FAoFxo4dC4lEInbMbsHzM2pWV1cHrVbbZhNm2bJl8PX1FTsiERF1HhsvRES2ruW+LfHx8dDpdJg1axaioqKwYMEC3t7IRl2/fh3+/v4wGAwAAAcHB1y7do23MjCTmzdv4tChQ9BqtTh48CAuXboENzc3TJo0ybiqxZ7eRCLqCoIg4I033sA333wDlUqF+fPnd8vrlpSU4JVXXkFCQgJXuRB1gbq6Ohw9ehRqtRpxcXG4du0ahgwZgtDQUMjlcoSGhsLZ2VnsmF2C52d0Py2bMPHx8aivr2cThojIurHxQkRkqwoKChATE4Nvv/0WJSUlGDduHCIjI/Hcc8/B29tb7HjUxTZs2IB169ZBp9MBABwdHbFhwwa88cYbIiezTs1vEjWvaMnPz4dEIsGYMWOMjZapU6fa7BtFRGIRBAGvv/46Nm3ahNjY2C5vvjSvcunVqxc2bdrEVS5E3aCgoAAqlQoajQZ5eXno2bMnZsyYAYVCgfnz59vUrZd4fkbt8aAmzPLly9G3b1+xIxIR0cOx8UJEZEuuXbuGPXv24Ntvv8WJEycwZMgQLF26FC+++CKGDRsmdjzqRmPGjMEPP/yA5j/zEokE48aNw/fffy9yMutgMBiQn59vbLQcOXIE9fX1rfZpmTVrFjfEJeoGLZsvKpUK4eHhZn8NrnIhsgyXLl3CwYMHoVarkZKSAr1ej4kTJ0KhUCA8PByPP/642BFNwvMz6qja2lqkpaVBpVIhLi4ODQ0NxibMihUr4OPjI3ZEIiJqGxsvRETWrq6uDhqNBtHR0UhOToa7uzsUCgWioqIwc+ZM3urIDp07dw6PPvpom4+dOXPmvo/Zu5b7tKSnp6OsrAy+vr6YNm0aZDIZwsLCMHjwYLFjEtklQRDw2muvYfPmzdizZw8UCoXZjt1ylcvmzZsxY8YMsx2biDqvpqYG6enp0Gg0SExMRElJCQICAoz7wkyfPh2Ojo5ix2w3np+RqWpra7Fv3z5ER0cjNTUVADBr1iwolUrMnz8fnp6eIickIqIW2HghIrJGBoMB2dnZiImJwY4dO9DU1GTct2X+/Pm83ZGd+/DDD/HRRx+hqamp1fednJzwwQcf4N133xUpmWW5c+cOjh07Zmy25ObmomfPnpg8eTL3aSGyQIIg4NVXX8WWLVvM0nwpLi7GK6+8gsTERK5yIbJwer0eOTk50Gg0SEpKwqlTp+Dt7Y2QkBDI5XIsWLAAvXr1EjvmA/H8jMypsrISSUlJUKlUSElJgUQiMTZhrGE+EBHZATZeiIisSfM9sL/99ltcunTJuG8L7/VLLQ0fPhxnz55t87FHH30UZ86c6eZElkGn0+HkyZPGRktmZiYMBkOrfVqeeeYZ9OjRQ+yoRHQfgiDglVdewdatWxEXFwe5XN6p43CVC5F1O3/+PNRqNTQaDQ4dOgRHR0dMmTIFcrkcCxcuhL+/v9gR78HzM+oqdzdhHBwcIJPJ2IQhIhIXGy9ERJbuxo0biI2NRUxMDHJzc+Hv74/ly5dj9erVGD58uNjxyMLk5eVh3LhxD3zODz/8gFGjRnVTInG1vH3YwYMHUV1d3WqflpkzZ8LLy0vsmETUAS2bL/Hx8Zg3b167f5arXIhsT1lZGdLT06FWq5GYmIjq6moEBgZCoVBALpcjODhY9NWrPD+j7lJRUQG1Wt1mE+bZZ5+Fh4eH2BGJiOwFGy9ERJaovr4earXauG+Lm5sbwsPDuW8LPdTbb7+Nv/3tb2hsbGzzcScnJ7z11lv4Wix7hQAAIABJREFU+OOPuzlZ9yguLkZWVha0Wi327duHa9euwcfHBzNmzIBMJsOsWbMwdOhQsWMSkYkMBgN+/etfY9euXYiLi2tX84WrXIhsX319PY4cOQK1Wo29e/fiypUr8PX1RWhoKJRKJWbPni3KylZ7Pz8jcbRswhw8eBBSqZRNGCKi7sPGCxGRpWi5b8vOnTtRW1uLGTNmIDIyEhEREejZs6fYEcnCCYKAgQMH4saNGw98Xv/+/XHt2jWbaODV1NQgJyfHuKolLy8PPXr0wJQpU4yrWoKCguDg4CB2VCIyM4PBgFWrVkGlUiEpKQkymazN53GVC5H9KigogEajgVqtRnZ2NlxdXRESEgKFQgGFQoH+/ft3eQZ7PD8jy1NeXg6NRmNswjg6OmLmzJlQKpVYuHAh/y4SEZkfGy9ERGI7deoUdu/ejejoaFy4cAGBgYGIiorC888/j379+okdj6zI4cOHMW3aNDg5ORkbDc1/5psv4g0GA5qamnD06FFMnjxZtKydpdfrceLECWOj5fDhw2hsbGx1+7CwsDB+go/ITuj1eqxatQp79uyBWq3GzJkzWz2uUqnw8ssvo3fv3ti0aRNXuRDZsdLSUiQnJ0OlUiE1NRVNTU0ICgqCXC6HQqF46K3AOssezs/IurAJQ0TULdh4ISISQ3l5Ofbs2YPo6GgcPXoUAwcOxKJFi/DrX/8ao0ePFjseWamUlBSkp6e3+l5CQgIcHBwQHh7e6vuzZs265w1KS9Vyn5bU1FRUVlaif//+xlUtcrkcAwYMEDsmEYlEr9fj+eefR3x8PNRqNUJCQlBcXIyXX34ZSUlJXOVCRPeora1FWlqacTXMjRs3MHToUMyaNQtyuRxhYWFwcnIyy2vZ6vkZ2YaysjLs27cPKpUKycnJcHJyMjZhFi1aBDc3N7EjEhFZKzZeiIi6S0NDA1JSUhATE4OEhAQ4OjpCLpcjMjISc+fOhVQqFTsi2aCIiAg4Ojpi165dYkdpt9LSUmRmZkKr1SI5ORmXL1+Gu7s7Jk6caFzV0lWfSiUi69Sy+fLWW2/h73//O3r37o3Nmzdj+vTpYscjIgtmMBiQn58PtVoNjUaD3Nxc9OnTx/jhjvDwcPTu3dusr2mN52dk++5uwjg7OyMkJIRNGCKizmHjhYioq+Xm5iI6OhrfffcdKioqEBISgsjISC7jpm5hDRf2tbW1yM7ObrVPi1QqxejRo42NluZbdBAR3c+1a9cwceJEXL16FXK5HLt27eKbRETUYRcuXEBqairUajUOHjwIg8GAiRMnQqFQYMGCBRg5cqTJr2EN52dk327duoX9+/dDpVLhwIED6NGjh7EJw/1HiYjahY0XIqKucOnSJezatQv//Oc/ce7cOeO+LStXroSfn5/Y8ciOWOKF/d37tGRlZaGhoaHVPi2zZ8+Gp6en2FGJyEq03Mtl6NChyMnJgUaj4Z4uRGSSiooKaLVaqNVqqNVqVFZWIiAgAHK5HEqlEpMnTzbu29IRlnh+RnQ/t27dQnx8PKKjo5GTkwMPDw+Eh4dDqVQiNDQUzs7OYkckIrJEbLwQEZlLZWUlkpKSEBMTg7S0NPTv3x8RERFYuXIlxo4dK3Y8slOWcmHfcp+WtLQ0lJeXo1+/fpg6dSpkMhnmzJkDf39/UTMSkfW5ceMGXn75ZajVarz44ovYsGEDXFxcEBkZicTEROzbt4+3GiMis9Dr9cambkJCAoqKiuDj44M5c+ZAoVAgLCwMHh4e7TqWpZyfEXXU1atXERcXB5VKhezsbHh6ekKhULAJQ0R0LzZeiIhM0djYiIMHDyImJgaJiYlwcHCAQqFAZGQk5syZA0dHR7Ejkp0T68L+1q1byMjIgFarRWpqKi5cuAA3NzdMmjTJuKpl7NixkEgk3ZqLiGxHy1Uud+/lotfr8dxzzxn3bGDzhYjM7fz581Cr1VCpVMjJyUGPHj0QHBwMuVyOiIgIDBw48L4/y8YL2QI2YYiIHoiNFyKizmjet2Xnzp0oKyvDpEmTEBUVhWXLlrX7k25E3aG7Luzr6upw9OhR46qW/Px8SCQSjBkzxthomTp1Ki/AiMhkba1yaWsvl5bNl3379mHatGkipCUie9C8H4ZGo0FycjJu376NwMBAKJVKKBSKez5swsYL2ZorV64gPj7e2ITp3bu38ZZ8YWFh3KuRiOwRGy9ERO115coV7NixA1u2bMHp06fx+OOPY/HixVi5ciWGDh0qdjyiNnXlhX3L24c1v8nQcp8WmUyGPn36mP11ich+tVzlsmXLloc2U5qamrB48WKkpqZi//79mDp1ajclJSJ71fxhFLVajbi4OFy7dg1DhgxBaGgo5HI5Zs+ejRUrVrDxQjbr8uXL2Lt3L5swRGTv2HghInqQqqoqJCYmGvdt6dOnDyIiIhAZGYkpU6aIHY/ooczZeLlx4waOHDkCrVYLjUaD69evo2/fvpg+fTpkMhlCQ0MxZMgQM6QmImqteZWLRqPBCy+8cN9VLm1pbr6kp6fj4MGDmDhxYhenJSL6j4KCAqhUKmg0GuTl5cHV1RWenp4YOHAgNBoN+vXrJ3ZEoi5zdxOmT58+mDdvHpswRGQP2HghIrqbXq9HRkYGoqOjERcXB4PBAJlMhqioKCxYsIAnh2RVTGm83LlzB8eOHTOuasnNzYWrqyuCg4ONK1qCgoLg4ODQBcmJiH7RvMqlT58+2Lx5c6duGdbY2IjFixcjIyMDKSkpmDBhQhckJSJ6sEuXLuHgwYP44IMPUFJSAolEgokTJ0KhUCA8PByPP/642BGJusylS5eQkJDQZhOG+6MSkQ1i44WIqFlBQQFiYmLw7bff4ubNm5g0aRKUSiWee+45eHt7ix2PqFM60njR6XQ4efKksdGSmZkJvV6PoKAgY6NlypQpcHFx6YbkRGTvbty4gZdeegn79u3r8CqXtjQ2NkKpVCIzMxMHDx5k84WIRBMREQGJRIKoqChoNBokJiaipKQEAQEBkMvlUCgUmDZtGj/wRTbr4sWLSExMhEqlwtGjR+Ht7Y25c+eyCUNEtoSNFyKyb9euXcOePXuwdetWnDx5EiNHjsTSpUsRGRmJYcOGiR2PyGQPa7y03KclJSUFVVVVrfZpCQkJYeORiLqdSqXCSy+9BC8vL2zZssVse7O0bL6kpKTg6aefNstxiYg64u7zM71ejxMnTkCtVkOlUqGwsBDe3t4ICQmBXC7HggUL0KtXL5FTE3UNNmGIyEax8UJE9qeurg4ajQbR0dE4cOAAevXqBaVSicjISAQHB0MikYgdkchs7r6wLykpweHDh6HVanHgwAFcuXIFHh4emDBhAmQyGRQKBQIDA0VOTUT2ytyrXNrS2NiIiIgIHD58mM0XIhJFez4Yo1arodFokJmZCUEQMGHCBCiVSixcuBD+/v7dnJioe1y4cAFJSUnGJoyPjw/mzJkDpVKJuXPnQiqVih2RiKi92HghIvtgMBiQnp6O6Oho7N27F01NTZg1axaioqIwf/58ODs7ix2RqEssWLAAVVVVmDBhArRaLfLy8iCVSjF69Gjjqpbp06fzk2REJLquWuXSlsbGRixatAhHjhxBSkoKnnrqqS57LSKiu3XkVrBlZWVIT0+HWq1GYmIiqqurERgYCIVCAblczg+Okc06f/48VCoVoqOjUVhYiIEDB2LRokVQKpWYPHky95kkIkvHxgsR2bbmfVu2bduG4uJijBs3DpGRkVixYgV8fHzEjkdkds23qmi+fVh6ejoMBkOr24eFhobydhVEZDGuX7+Ol19+2bjK5bPPPkPPnj27/HXZfCEisXSk8dKSTqfDsWPHoFKpsHfvXly5cgW+vr4IDQ2FQqHA3Llzzb5KkMgSFBQUQKVSITY2FqdOncKgQYOwcOFCKJVKNh+JyFKx8UJEtuf69evGT8bk5eVh8ODBWLZsGVavXo3hw4eLHY/I7Fru06LValFRUQE/Pz8888wzOHfuHAYNGoTExESxYxIRtSIIAmJiYvDb3/62W1a5tKWhoQGLFi3C0aNHkZqaivHjx3fr6xORfeps4+VuBQUF0Gg0UKvVyM7OhouLC2bOnAmFQgGFQoH+/fubKTGR5WhuwuzevRs///wz/P398eyzz7IJQ0SWho0XIrIN9fX1UKvViI6ORnJyMtzd3aFQKBAVFYWZM2fy5Itsys2bN3Ho0CFotVocPHgQly5dgpubGyZNmmRc1TJ27FhIJBKzXdgTEZnTpUuX8OKLLyItLa1bV7m0pWXzRavVYty4caLkICL70RXnZ6WlpUhOToZGo8H+/ftRV1eHoKAgyOVyKBQK1jaySc1NmF27dqGoqIhNGCKyJGy8EJH1MhgMyM7ORkxMDHbu3Ina2lrMmDEDkZGRiIiIEO0NHCJzq6urM74hqNVqkZ+fD4lEgjFjxhgbLVOnTm1zryI2XojIkgiCgH/+859466230K9fP2zevLnbV7m0pa6uDuHh4cjNzUVqairfoCSiLtXV52d1dXXQarXG1TA3btzA0KFDMWvWLMjlcoSGhnKPS7I5dzdhBg8ejAULFrAJQ0RiYeOFiKzPqVOnsHv3bkRHR+PChQsIDAxEVFQUVq1aBV9fX7HjEZnMYDAgPz/f2Gg5cuQI6uvrW+3TMnv2bHh6ej70WGy8EJGluHTpEl544QWkp6eLvsqlLXV1dVAoFDh58iTS09MxatQosSMRkY3qzvOz5vNKtVoNjUaD3Nxc9OnTBzKZDHK5HOHh4ejdu3eX5yDqTs1NmJ07d+L06dMYMmQI5s+fzyYMEXUnNl6IyDqUl5djz549iI6OxtGjR42b6a1evRpPPvmk2PGITNZyn5a0tDSUl5fD19cX06ZNg0wmQ1hYGAYPHtzh47LxQkRiu3uVy5YtW/DMM8+IHatNtbW1UCgU+PHHH5GWlsbmCxF1CTHPzy5cuIDU1FSo1WqkpKRAr9dj4sSJUCgUWLBgAUaOHNntmYi6UnMTZseOHThz5gybMETUXdh4ISLLVV9fj9TUVMTExCAhIQGurq6YP38+920hm3D79m3861//Mn768Pz58+jZsycmT558zz4tpmDjhYjE1LzK5dChQ3jzzTfxwQcfwMXFRexYD9Sy+ZKeno4nnnhC7EhEZGMs5fysoqICWq0WarUaarUalZWVCAgIMO4LM336dDg6Ooqakcicmpsw3333Hc6ePYtHHnkE4eHhUCqVmDJlitjxiMi2sPFCRJaled+W5pOhyspK474tixYtgpubm9gRiTpFp9Ph5MmTxlUthw4dgiAIrfZpeeaZZ9CjRw+zvq6lXNgTkX1pucrF398fW7duxdNPPy12rHarra2FXC5HQUEB0tLS2HwhIrOyxPMzvV6PnJwcaDQaJCQkoKioCD4+PpgzZw4UCgXCwsLg4eEhdkwis2luwmzfvh3nzp3D0KFDoVAo2IQhInNh44WILENRURF27txpPOlp3rdl5cqV8PPzEzseUae0vH1YcnIybt++3WqfFplMhj59+nRpBku8sCci23b3KpcPP/zQ7E3l7tCy+ZKeno5f/epXYkciIhthDedn58+fN67MPnToEBwdHTFlyhTI5XJERERg4MCBYkckMpvmJkxMTAzOnz/PJgwRmQMbL0QknoqKCqhUKkRHRyM7Oxv9+/dHREQEnn/+eQQFBYkdj6jDiouLkZWVBa1Wi3379uHatWvw8fHBjBkzIJPJMHv2bDzyyCPdmskaLuyJyDZY+yqXttTW1mLevHkoLCxk84WIzMbazs9u3bqF/fv3Q6PRGD9MFBgYCIVCAblczn0yyKYUFBQgJiYG27dvx7Vr1xAYGAilUonFixcjMDBQ7HhEZD3YeCGi7tXQ0ICUlBTExMQgMTERUqkUcrkckZGRmDNnDu8hTFalpqYGOTk5xlUteXl5cHFxQXBwsHFFS1BQEBwcHETLaG0X9kRknS5evIgXXngBmZmZVr3KpS01NTWYN28efv75Z6Snp/NNFyIymTWfn9XX1+PIkSNQq9WIj4/H1atXMWTIEISGhkIul2P27Nk2U//JvrW8DfqePXtw/fp1YxNmyZIlePzxx8WOSESWjY0XIuoeubm5iI6Oxo4dO1BeXo5JkyYhKioKy5cvh7u7u9jxiNpFr9fjxIkTxkbL4cOH0djY2GoT0ilTpljUxtHWfGFPRJav5SqXwYMHY+vWrXjqqafEjmV2bL4QkTnZ0vlZQUEBNBoN1Go1srOz4erqipCQECgUCoSHh/O20WQTWjZhVCoVbty4YWzCLF26FI899pjYEYnI8rDxQkRd5/Lly9i5cyc2b96MM2fOGE9Mnn/++W6/3RJRZ7XcpyUlJQVVVVXo378/pkyZAplMBrlcjgEDBogd875s6cKeiCyLLa9yaUtNTQ3mzp2LoqIiZGRk8JOuRNRptnp+dvnyZSQnJ0OtViM1NRU6nQ5jxoyBXC7nbZrIZjyoCbNs2TKMHDlS7IhEZBnYeCEi86qsrERSUhJiYmKQlpYGLy8vLFq0CJGRkdyUjqxCaWkpMjMzodVqkZycjMuXL8Pd3R0TJ0403j5s3LhxYsdsN1u9sCci8djLKpe2VFdXIzQ0FBcvXkR6ejqbL0TUKfZwflZbW4u0tDRoNBokJSWhuLi41SrxadOmwcnJSeyYRCZp2YSJjY1FcXGxsQmzfPlyjBgxQuyIRCQeNl6IyHR6vR4ZGRmIjo5GXFwcDAYDFAoFIiMjERYWxhNqsmi1tbXIzs5utU+LVCrF6NGjjY0Wa74wtIcLeyLqPva2yqUtVVVVCA0NxbVr15CRkYFHH31U7EhEZGXs7fys+Xa9arUaKpUKhYWF8PLywsyZMyGXyzF//nx4enqKHZPIJC2bMLt370ZJSQmbMET2jY0XIuq8goICxMTEYOvWrbh165Zx35alS5eiV69eYscjatPd+7RkZWWhoaEBAQEBxkZLaGiozYxhe7uwJ6Ku0bzK5c0338SQIUPsapVLW1o2Xw4dOoRhw4aJHYmIrIi9n5+dP38earUaGo0GmZmZEAQBEyZMgFKpxLPPPovBgweLHZHIJHq9Hjk5OW02YVasWIHhw4eLHZGIuh4bL0TUMVevXkVcXBy2bt2KkydP4rHHHsOSJUsQFRWFgIAAseMRtanlPi1arRYVFRXo168fpk6dCplMhrlz52LQoEFix+wS9n5hT0Smu3jxIlavXo3Dhw/b7SqXtlRVVWH27Nm4ceMGMjIy2Hwhonbj+dl/lJeXIy0tDWq1GklJSaiqqkJgYCAUCgXkcjmCg4MhkUjEjknUaS2bMLt27UJpaamxCfPcc89x5SyR7WLjhSzf559/LnYEizd37twuvdivrq5GQkKCcd+W3r17Q6lUWvW+LWfOnEFycrLYMSyaRCLB66+/LnaMTrl16xYyMjKg1WqRkpKCixcvws3NDZMmTTKuahk7dmyXXMQdOHAAZ8+eNftxO2vLli1wcHDA888/L3YUoxEjRiA0NFTsGESt8HyjbYIg4NNPPwUA/OMf/8D8+fNFTtS1Onp+UFtbiy+++AL19fV49913IZVKuzCdZbDm8wOyXzw/ezhLOD/T6XQ4duwYVCoVEhIScPnyZfTt2xdhYWFQKBSYM2cO3N3dRc14N54/PFxXv19hTVo2YXbu3ImbN28amzCRkZGi/DtZWn20RJZQH8kqsfFCls1gMEAqlcLT05OfrLyP0tJSqFQqREREmPW4LfdtiY+Ph06nw6xZsxAVFYUFCxZY7X4XzXbt2oVly5bB19dX7CgWqaGhAdXV1TAYDGJHaZe6ujocPXrUuKIlPz8fEokEY8aMMTZapk6dCmdn5y7PsmjRIuzbt89i7lPd/P/QwcFB5CS/qKqqwvz587F7926xoxAZ8XzjwfR6PcrKyrrkfMPSdOb8QBAENDU1dcvfGLFZ2/kBUTOenz2YpZ6fFRQUQKPRQK1WIzs7Gy4uLggODoZcLodSqcSAAQNEzcfzh4f7f+zdeVzUdf4H8NfMgNwoKt73Xaio5IGohIJKgloKaF5leayV7bq1mLpa5lZWu2Xa5VGBlgJeKAmiWSqKCmag4nohpqKAIIpyDvP5/dFPVlIRcGY+8515PR8PH4/dmWHmFfP9fufFvL+Hob6vMAdVDWGMeUYRU9s+mhpT3T6SImitZCcgqo7Vq1fzg/oB7hY9fbp73ZawsDBcu3YNHh4e+Ne//oUJEyagYcOGen0t2VQqFbKysmTHMEkbNmzA888/LztGle49N3RCQgKKi4srrtMSGhoKPz8/1KtXT0o2FrOHGzNmjOwIRA/FvvFghugbpoz94OGU0A+IHob97OFMtZ+5ubnBzc0NoaGhyMnJQWxsLGJiYrBgwQLMmTMHPXv2REBAAAIDA+Hh4SEtJ/vDg1laf6gpjUaDAQMGYMCAAfjPf/6DxMRErF27Fp9++ineeecdeHh4YNKkSRg7diyaN29u0CzcPj6cqW4fSRk4eCEiZGZmIioqCmFhYTh27BhatWqFKVOm4OWXX+b5RslkXL16FQkJCdi9ezdiYmKQmZkJV1dXPP3001i2bBmGDRuG1q1by45JRERERER65urqismTJ2Py5MkVR7tv374dq1atwjvvvIM2bdpg6NChCAgIwLBhwyziKEQyH/cOYT777DPEx8cjKioKixYtwpw5c+Dp6YmgoCCTONKLiKqPgxciC1VUVISYmBiEh4cjLi4Ojo6OCAwMxIcffoghQ4bwAoYk3e3bt3Ho0KGK04cdPXoUdnZ28PLywuzZs+Hr64uePXuazCkaiIiIiIjI8Ozs7CpOJ/zJJ5/g2LFjFUfCr1y5Eg4ODvDx8UFQUBBGjhwp7Sh4otqwsbFBYGAgAgMDUVJSUjGEWbhwYaUhTHBwMJo2bSo7LhFVgd9WEVkQnU6HhIQEzJgxA40aNcLEiRMBAGvWrEFmZibCw8Ph6+vLoQtJodVqcfToUSxduhR+fn6oX78+hg0bht27d8PX1xe7du1CXl4edu3ahdDQUHh4eHDoQkRERERkwdRqNTw8PPD2228jOTkZFy5cwH/+8x8AwLRp09CwYUMMGDAAS5cuxX//+1/JaYlq5u4QJjw8HFlZWdi6dSvatWuHhQsXokWLFhgwYACWLVuGq1evyo5KRA/AI16ILEBaWhoiIyMRFhaGjIwMeHh4YMmSJby4PEmXnp5ecUTLzp07cevWrYrrtEyfPh1DhgxB/fr1ZcckIiIiIiIFaNOmDaZPn47p06fjzp072LNnD6KiovDBBx9g7ty5aNeuXcV1YZ5++mlYWfFrMVIGW1vbiiNhiouLsWvXLkRFReGf//xnpSNhQkJC0KRJE9lxiQgcvBCZrdzcXGzatAnh4eE4cOAAWrZsieeffx5Tp05Fp06dZMcjC5WVlYV9+/Zh9+7d2LFjBy5fvgwnJyd4e3vjo48+gp+fH9q2bSs7JhERERERKZyDg0PFF9Xl5eVITExETEwMoqOj8dlnn6Fhw4bw9/dHYGAghg8fDicnJ9mRiaqlqiHM3//+d/Tr1w9BQUEYN24cGjduLDsukcXi4IXIjBQXF2P79u0IDw/Hzp07YW9vj5EjR+Ltt9/mdVtIijt37iAxMbHiqJZff/0VGo0G7u7umDBhAnx9fbmnGRERERERGdS9Fy//4IMPkJ6eXnFdmOeffx5WVlYYMGAAAgICMGbMGLRo0UJ2ZKJquXcIU1RUhN27dyMqKgoLFizgEIZIMp4cn8gM/Pe//8WMGTPQuHFjjB8/HsXFxVi9ejWuXLnC67aQUZWXl993nRY/Pz9ERUXBw8MDERERyMvLQ3JyMj744AP4+vpy6EJEREREREbVrl07vP7669i1axeuXbuGr7/+Gi4uLli4cCFatmwJNzc3zJ07FwkJCRBCyI5LVC12dnYV14TJzs7Gli1b0K5dO8yfPx/NmzevuCZMdna27KhEFoHfdhGZgcWLF6Njx46YN28eXnjhBe7FQEZ173Vadu3ahfz8fDRp0gQDBw7E8uXLMWLECDRv3lx2TCIiIiIiovs0aNAAkydPxuTJk1FcXIyEhARs374d33//PZYuXYpWrVph+PDhCAgIwNChQ2FjYyM7MtEj3R3CBAYG4uuvv644Emb+/PmVjoQpKSnhzpBEBsI1i8gMfP7555g2bZrsGGQhcnJy8Msvv2D37t3YuXMnLl68CAcHB3h6emLu3Lnw9fWFh4eH7JhEREREREQ1YmtrC19fX/j6+mLZsmU4efIkYmJisH37dqxatQp2dnYYPHgwAgMDERAQIDsuUbXcO4RZsWIFtm/fjsjISISGhqJ+/foYOHCg7IhEZomDFyIz4OLiIjsCmbGioiIcOHCg0nVa1Go1evTogXHjxsHX1xeDBg1CnTp1ZEclIiIiIiLSGzc3N7i5uSE0NBS///47YmJisG3bNsyePRuzZs2SHY+oxpydnTFhwgRMmDABN2/eREhIiOxIRGaLgxciInqowYMH4+DBgygpKYGbmxt8fX3xzjvvwNvbG46OjrLjERERERERGUWrVq0wa9YszJo1CwUFBYiLi0NwcLDsWES1VrduXTg4OMiOQWS2OHghIqKHatGiBVauXAk/Pz80bdpUdhwiIiIiIiLpnJycMGbMGNkxiIjIhHHwQkREDxUeHi47AhERERERERERkaKoZQcgMpSysjJ06tQJkydPrnT7xYsXsWLFCgwbNgw2NjZQqVSIi4vT62snJCTAz88PdevWhZOTE7y9vREfH//Ax6lUKuzcuVOvr0+G9bBlC6j+e19bXLbMG7dbRMoja72tyfNzvTUO9gMi8yRr3eZ23ryxP5A54PaR6BEEkQkrLy8XAERUVFSNf3bZsmXCyspKnD17ttLtjRs3FgAq/YuNjdVXZBEXFyc0Gs19r6FSqURkZOR9j/fz8xPdunUT5eXlNX6tx/n9WLr169cLlUpVq5992LJV0/decgyUAAAgAElEQVS+poy5bD3O78fSPffccyI4OLhWP2sJ263H+f0QGYoS+0ZNn599o3rYD6rGfkBKZYh+Zuh125jbefaz2mF/qJol9Qcl4/axatw+0mMo4xEvZJZKS0vxr3/9C6NHj0aHDh0q3demTRu88soriIuLw7Rp0/T+ujNmzEB5eTnmzJmDnJwc3LhxA++++y6EEJg1axZu375d6WfeeOMNHD9+HFFRUXrNQobxsGWrNu99TV+Xy5Z543aLSHlkrbe1eX6ut4bFfkBknmSt2wC38+aM/YHMAbePRNUgb+hD9Gi13UNi/fr1AoDYtm1blY975ZVX9LoHyY8//igAiEGDBt1333PPPScAiHXr1lW6XavViqZNm4qnn366xq/HPUhqr7Z7bD5s2arNe18Txl62uEdr7dV2jxhL2W5xjyEyRUrrG7V5fvaN6mE/qBr7ASmVvvuZodftPzP0dp79rHbYH6pmSf1Bybh9rBq3j/QYeMQLmafw8HDY2dlh+PDhRn3dffv2AQAmTJhw330TJ04EAOzdu7fS7RqNBqNGjcIvv/yC33//3fAh6bE8bNmqzXtfE1y2zB+3W0TKI2u9rQ2ut4bFfkBknmSt27XBdVs52B/IHHD7SPRoHLyQ2dFqtdi/fz969eoFa2tro772uXPnAABdu3a9777u3btXesy9+vXrBwDYs2ePAdPR46pq2arte19dXLbMG7dbRMojc72tLa63hsF+QGSeZK7btcV12/SxP5A54PaRqHo4eCGzk5aWhtu3b8Pd3d3or33r1i0AQP369e+77+5tN2/evO++Hj16AAASExMNmI4eV1XLVm3f++rismXeuN0iUh6Z621tcb01DPYDIvMkc92uLa7bpo/9gcwBt49E1cPBC5mdq1evAgAaNmxo9NcWQtTqPldXVwD/y06mqaplq7bvfXVx2TJv3G4RKY/M9ba2uN4aBvsBkXmSuW7XFtdt08f+QOaA20ei6uHghcxOfn4+AMDJycnor123bl0AQF5e3n333bhxo9Jj7uXs7Azgf9nJNFW1bNX2va8uLlvmjdstIuWRud7WFtdbw2A/IDJPMtft2uK6bfrYH8gccPtIVD0cvJDZqVevHoD/Hd5oTB06dAAAnDhx4r77UlNTKz3mXncPs3RxcTFgOnpcVS1btX3vq4vLlnnjdotIeWSut7XF9dYw2A+IzJPMdbu2uG6bPvYHMgfcPhJVDwcvZHaaNm0KALh+/brRX3vQoEEAgO+///6++9atW1fpMfe6m/VudjJNVS1btX3vq4vLlnnjdotIeWSut7XF9dYw2A+IzJPMdbu2uG6bPvYHMgfcPhJVDwcvZHaefPJJODo64rfffjP6a/v6+qJVq1bYt28f/v73v+P69eu4efMmlixZgs2bN6Nhw4YYPXr0fT93N2u/fv2MHZlqoKplq7bvfXVx2TJv3G4RKY/M9ba2uN4aBvsBkXmSuW7XFtdt08f+QOaA20eiahJEJqy8vFwAEFFRUTX6ueHDhwtbW1tRXFx8330TJkwQAB7678+v5eXlJQCIY8eOVeu1Y2NjhUajue95VSqViIiIeODPzJw5UwAQGRkZNfrvrO3vh4RYv369UKlUNf65qpatmr73prxs1fb3Q0I899xzIjg4uMY/Zynbrdr+fogMSYl9o6bPLwT7RnWwH1SN/YCUyhD9zNDrtjG38+xntcP+UDVL6g9Kxu1j1bh9pMdQxiNeyCxNmjQJxcXF2LFjx2M/l06nAwBYWVlV6/HDhw/HL7/8giFDhsDJyQkODg4YOHAg4uLiEBwcfN/jy8vLER0djUGDBqF169aPnZcMq6plq6bvPZctuhe3W0TKI3O9rSmut4bFfkBknmSu2zXFdVs52B/IHHD7SFQNskc/RFWp7R4SJSUlwtXVVTz77LOP/fr16tUTbm5uQqfTPdZzPczOnTsFALF+/foa/yz3IKm92u6xaSnLFvdorb3a7hFjKcsW9xgiU8S+UTVL6hvsB1VjPyClYj+rGvtZ7bA/VM2S+oOScftYNW4f6THwiBcyT3Xq1MH8+fOxbds2nD17ttbPc+LECeTn52Pu3LlQqVR6TPg/H3/8Mbp27YqgoCCDPD/pF5ctMhQuW0TKw/WW7uKyQGSeuG6TIXC5InPA5Zjo0Th4IbM1a9YstGvXDosXL671cyQkJKB169YYN26cHpP9z4EDB7Br1y58/PHH0Gg0BnkN0j8uW2QoXLaIlIfrLd3FZYHIPHHdJkPgckXmgMsxUdUMc/I8IhNgbW2NM2fOPNZzzJo1C7NmzdJTovt5eXlBCGGw5yfD4LJFhsJli0h5uN7SXVwWiMwT120yBC5XZA64HBNVjUe8EBERERERERERERER6QkHL0RERERERERERERERHrCwQsREREREREREREREZGecPBCRERERERERERERESkJxy8EBERERERERERERER6QkHL0RERERERERERERERHrCwQsREREREREREREREZGecPBCRERERERERERERESkJxy8EBERERERERERERER6QkHL0RERERERERERERERHrCwQsREREREREREREREZGecPBCRERERERERERERESkJxy8EBERERERERERERER6QkHL0RERERERERERERERHpiJTsAUXXExsbi6tWrsmOYHCGE7AiKt3z5ctkRTNKvv/4qO4KinT17lsvWQ5w/fx6dO3eWHYPogdg3HswS+wa34Q/GfkBKxn72cOxnj4f94cEssT8oFbePD8ftIz0ODl7IpKlUKjRq1AgxMTGIiYnRy3PqdDqo1eZzsFejRo1ga2srO4bi2NrawtXVFUuWLDHaaypt2WvcuLHsCIpUr149XLlyxajLltL07dtXdgSiSgzRN8yNpfQNGf2gtmT1CvYDUiL2s0djP6s5JfYHY392WEp/UDJz2D4KIaBSqQz2/Nw+Um2pBEfQZEE2b96M9evXIyoqSnYUsjA//fQTEhMTsWDBAtlRyMLExsbC2toavr6+sqMQ0UMsWLBA0X/skhzDhg3Dpk2b4OjoKDsKEdUQ+xnJsnDhQgwYMABDhw6VHYVIL4QQCA4ORnh4OOzs7GTHIbqXVjm7XhM9hqKiIrz88ssYM2YMnnrqKdlxyMJcvHgRwcHBKC0tlR2FLND69evxww8/yI5BRA+RnJyM999/Hzdv3pQdhRTm8OHDmDdvnuwYRFQL7Gcki1arxfPPP4/Lly/LjkKkFyqVCqdOnYKfnx8KCgpkxyGqhIMXMnsnT55Ejx49sGbNGgDgXkVkVMXFxRg9ejTy8vJ4jlsyuuLiYmzatAkREREoKiqSHYeI/kSn02H69OnQ6XRIT0+XHYcUpLS0FLdu3cKKFSuwd+9e2XGIqAbYz0im8vJy5ObmYtSoUSgpKZEdh0gv2rdvjwMHDmDgwIG4fv267DhEFTh4IbMWHh6Op556quLLDGdnZ/Ts2VNyKrIks2bNwokTJ2BlZYXy8nLZccjCbN++HUVFRSgqKkJcXJzsOET0J6tXr0ZKSgpUKhUHL1Qj169fr9ihY/Lkybhz547kRERUXexnJJNOp4NGo0Fqaipmz54tOw6RXnTq1AkajQZpaWkYOHAgrl27JjsSEQAOXshMFRQUYPz48ZgyZQqKi4uh1Wqh0WgwdOhQRV3cnJRt5cqV+PbbbyuWPx7xQsa2du1aaDQaaDQafP/997LjENE98vLy8I9//AM6nQ7W1ta4cOGC7EikIFlZWQD+OK95ZmYmQkNDJScioupiPyOZ7g5etFotVq5ciW+++UZ2JKLH1r59e6hUKpSVleH8+fPo3bs3d2oik8BvoMnsHD16FN26dcOmTZvuu48XkCNjOXbsGF577bVKt+l0OklpyBLl5+cjLi4OWq0WWq0W27Zt4zUkiExIaGgoCgsLAfzx5TkHL1QTOTk5Ff9bq9Xiiy++wK5duyQmIqLqYD8j2f78N+nMmTORnJwsKQ2RfnTo0AFarRYAUFZWhmvXrmHAgAE4c+aM5GRk6Th4IbMhhMCyZcvQr18/XLlyBWVlZZXuLy8v5/VdyCjy8vIQGBh4X6nl4IWMadOmTZWWufLyckRHR0tMRER3JScnY82aNRVdpaysjH8YUo1kZ2dXOopbrVbjxRdf5EVliUwc+xnJ9qC/UUeOHMnrYpCidejQodL/12q1yMnJgaenJ1JSUiSlIuLghcxEbm4uRowYgTlz5lTsPfRnrVq1Qtu2bSWkI0ui0+kQHByM7OzsSsuhEIKDFzKqtWvXVus2IjIunU6H6dOnQ6PRVLr97NmzkhKREuXk5MDKyqri/5eXlyMrKwtz586VmIqIHoX9jGT789+k5eXluH79OsaOHctrkpJitWrVCtbW1pVu02q1uHXrFgYOHIjExERJycjScfBCinf48GG4u7tj9+7dD/1i29raGiNGjDByMrJEb731Fn755Zf7jrgCwCJLRnPt2jXs37+/0jKn0+nw888/V1wXgIjk+Prrr/Hbb7/dt5PIlStX+DlB1ZaTkwOVSlXpNq1Wiy+//JKnHCMyUexnZAp0Ot191x4tKytDQkICFi1aJCkV0eNRq9Vo0aLFfbdrtVoUFhZi8ODB2L17t4RkZOk4eCFFi46OhpeXFzIzMx/4RfddWq0WQ4YMMWIyskTR0dH46KOPHvrFGY94IWPZsGFDpVPQ3Gvjxo1GTkNEd+Xm5uKtt9667wsP4I+ucuXKFQmpSImys7Mf2Dd4yjEi08V+RqbgYX+TlpeX47333nvgtXKJlOCJJ564b6cU4I9lu7S0FM888wxP7UhGx8ELKdrIkSPx6aefok6dOvcdVngvlUqFwYMHGzEZWZozZ85gwoQJD72fpxojYwoPD3/g8qbT6RAeHi4hEREBwD/+8Q/cuXPnofenp6cbMQ0p2bVr1x54at3y8nJkZ2cjNDRUQioiqgr7GZmCR/1NOmnSJJw6dcpIaYj0p1OnTg/9XlCn00Gr1WLs2LEcdJNRcfBCiqZSqfDqq6/i1KlT6N2790P3IHJ3d4eLi4uR05GlKCgowIgRI1BaWvrAvZjv4ilkyBjOnz+P33777YF/VAkhkJSUhIyMDOMHI7JwSUlJ+Pbbbx/4ZTkAaDQaDl6o2q5evfrQ+8rKyvDVV18hPj7eiImIqCrsZ2QqHnSqsbuEENBqtXj22Wer3FGEyBR16NChyu9j1Go1tFotli1bhtu3bxsxGVkyDl7ILLRt2xb79+9Hjx49oFarK11stE6dOnjmmWckpiNzN336dJw7d+6RgxUe8ULGsH79+krbwD+zsrJCRESEERMRkU6nw4wZM6DRaB76GCsrK1y4cMGIqUjJsrOzq7xfpVLhpZde4hcLRCaC/YxMxaP+Ji0vL8fp06cxc+ZMIyUi0o/27ds/8BIEarUaKpUKHTt2RGRkJPbt2wdHR0cJCckScfBCZmPbtm04duwYli9fji5dulR8uVFaWgpfX1/J6cicff755wgLC4Ofnx80Gg00Gs195xYVQlS59wWRvoSHh1d5zauysjKEhYUZMRERffXVVzh27NhDj3YB/lg3z507Z8RUpGR5eXkPvP3uDkg6nQ7FxcXYsWOHkZMR0YOwn5GpeNARLyqVquJv2KeeegqffvopPv74Y0kJiWqnQ4cOlf7/3YGLjY0NIiIikJaWhqCgoAdeB4bIUDh4IbOQk5ODGTNmYPr06Zg1axaOHj2KuXPnQq1Ww9bWFp6enrIjkhmrX78+Jk+ejLi4OFy6dAkvvvgihBBQqVSwtraGWq2GTqfjqcbI4FJSUnD27NlHPu7UqVM4efKkERIREQA4OztjypQp6NSpU8Ufe1ZWVpWOgNHpdDhz5oysiKQgxcXFKCwsBPDHl2V396LXaDQYMWIE/v3vf+PEiRPIzs5GcHCwzKhEBPYzMi13By93Pz9UKhWEEHj55ZeRmZmJw4cP4/XXX0fjxo1lRyWqkTZt2lR0a7VajVatWmHx4sUoLi6GnZ0dBy4kxcOPdSVSkJkzZ8LBwQEfffQRgD9OL7ZkyRKMHDkSP/zwA2xsbCQnJEvRtGlTFBQUYNCgQVi3bh0iIyOxbt26h57TmUifTpw4AR8fn0rLWlpaGlQqFZ544omK29RqNY4fPw43NzcZMYkszsSJEzFx4kQAf1wXLDY2FiEhIfD29sbZs2eRmZkJADy/P1VLTk4OAMDOzg4DBgyAn58fdDod5s+fj/DwcNSrV09yQiK6F/sZmRKdTgedTodevXph4sSJCAoKQkhICO7cuYMmTZrIjkdUa1ZWVmjZsiVKS0vx7rvvYvLkybCyssLRo0cxb948PPPMMw+9LjSRoagEz31DCvfNN99g2rRp2LNnD7y9vWXHIQtXWFiIxo0bY+nSpZg1a1bF7enp6cjIyMDgwYMlpiNLNHbsWFhZWWHDhg2yoxDR/9u0aROCg4ORn58PJycn5OTkICkpCcnJyZg3b16V1wEgunHjBtLS0tCnTx9YW1sDAHJzc9GoUSNs2bIFI0eOlJyQiB6F/Yxk2b17N9q3b4+2bdtW3PbZZ59hwYIFyMrKgp2dncR0RI9n9+7dGDRoEOrUqVNx24kTJ+Du7o6IiAiMHTtWYjqyQFqO+kjRLl++jDfeeAN/+9vfOHQhk7B9+3YUFRVhzJgxlW5v164dhy5ERAQASEpKwpNPPgknJycAgKurK5555hksXLiQQxd6JBcXF3h5eVUMXQCgQYMG6NatG37++WeJyYiIyNT5+vpWGroAQHBwMAoLCxEbGyspFZF++Pr6Vhq6AEDXrl0RHByMBQsW8PTvZHQcvJBi3T0PaePGjfHuu+/KjkMEAIiIiICPjw/PiUtERA+VlJSE3r17y45BZmbw4MHYs2eP7BhERKQwTZo0wYABAxARESE7CpFBLF68GOfPn8f69etlRyELw8ELKdaKFSvw008/ISwsjIfDkkkoKChAXFwcQkJCZEchIiITJYTAr7/+ysEL6d3gwYNx/PhxZGVlyY5CREQKExISgpiYGNy+fVt2FCK969ixIyZOnIh33nkHZWVlsuOQBeHghRQpPT0d8+bNw/z589GnTx/ZcYgAANHR0dBqtXj22WdlRyEiIhN1+vRp5Ofnc/BCeuft7Q0rKyvs3btXdhQiIlKYoKAglJaW4scff5Qdhcgg3n77bfz+++8ICwuTHYUsCAcvpDg6nQ4vvPACOnbsiHnz5smOQ1QhIiICfn5+aNCggewoRERkopKSkmBjY4Nu3brJjkJmxsnJCR4eHrzOCxER1VjDhg3h4+PD042R2WrdujWmTp2Kd999FyUlJbLjkIXg4IUUZ+nSpThy5AjCwsLuu2gWkSz5+fmIj4/nacaIiKhKSUlJcHd3h42NjewoZIZ4nRciIqqtkJAQ7NixAzdv3pQdhcgg/vnPfyInJwerVq2SHYUsBAcvpChpaWlYvHgx3n33Xe4pSiZl8+bNUKlUGDVqlOwoRERkwo4cOcLTjJHB+Pj44MyZM7h8+bLsKEREpDDPPfcchBDYtm2b7ChEBtGsWTPMmDED7733HgoLC2XHIQvAwQspRllZGSZPnoxevXphzpw5suMQVRIREQF/f3/UrVtXdhQiIjJRZWVlSE1N5eCFDGbAgAGwtbXlUS9ERFRjLi4u8PPz4+nGyKzNmzcPt2/fxhdffCE7ClkADl5IMd555x2cOnUK3333HTQajew4RBWuX7+OPXv28DRjRERUpePHj6OoqIiDFzIYW1tb9OvXj9d5ISKiWgkJCUF8fDxyc3NlRyEyCFdXV7zyyitYunQpCgoKZMchM8fBCynC0aNH8eGHH+Ljjz9Gx44dZcchqmTjxo2oU6cOAgICZEchIiITduTIETg5OaFLly6yo5AZ8/HxwU8//SQ7BhERKdDo0aNhZWWFrVu3yo5CZDChoaHQarVYtmyZ7Chk5jh4IZNXXFyMKVOmwNvbGzNnzpQdh+g+ERERCAgIgKOjo+woRERkwpKSkuDh4QG1mhWcDGfw4MG4dOkSzp07JzsKEREpjJOTE4YPH87TjZFZq1evHl5//XV8/PHHyMvLkx2HzBj/6iOTN3fuXFy+fBlr1qyBSqWSHYeokmvXrmH//v08zRgRET1SUlISTzNGBte3b184OjryOi9ERFQrISEh2LNnD7KysmRHITKYOXPmwMrKCp988onsKGTGOHghk5aQkIDly5dj+fLlaNWqlew4RPeJjIyEvb09/P39ZUchIiITVlhYiFOnTnHwQgZnbW2NAQMG8DovRERUK4GBgbC1tcXmzZtlRyEyGGdnZ7zxxhv49NNPkZ2dLTsOmSkOXshk3blzBy+88AICAgIwadIk2XGIHigiIgKjRo2CnZ2d7ChERGTCfv31V2i1WvTp00d2FLIAPj4+2LNnD4QQsqMQEZHC2NvbIyAggKcbI7P32muvwcHBAR999JHsKGSmOHghk/X666/j5s2bWLlypewoRA906dIlJCYm8jRjRET0SEeOHIGrqytat24tOwpZgMGDByM7OxsnT56UHYWIiBQoJCQE+/fvx5UrV2RHITIYBwcHzJ07FytWrOCyTgbBwQuZpPj4eHzzzTf48ssv0bhxY9lxiB4oIiICdevWhZ+fn+woRERk4nh9FzKmnj17wsXFhdd5ISKiWvH394eTkxM2btwoOwqRQc2cOROurq744IMPZEchM8TBC5mc/Px8vPTSS5gwYQLGjh0rOw7RQ0VERODZZ5+FjY2N7ChERGTiOHghY9JoNPD29uZ1XoiIqFZsbW0RGBjI042R2bO1tcW8efOwcuVKXLhwQXYcMjMcvJDJmTlzJnQ6HZYtWyY7CtFDpaen4+jRozzNGBERPVJeXh7S09N5fRcyKh8fH/zyyy8oLy+XHYWIiBQoJCQEhw4dQkZGhuwoRAb10ksvoUWLFnjvvfdkRyEzw8ELmZQtW7YgMjISq1evRv369WXHIXqoiIgINGjQAEOGDJEdhYiITFxSUhKEEHjqqadkRyELMnjwYOTn5+PYsWOyoxARkQINGzYMLi4uPN0YmT1ra2ssWLAA3377LU6fPi07DpkRDl7IZGRnZ2PmzJmYMWMG/P39ZcchqlJERATGjBkDKysr2VGIiMjEJSUloXXr1mjUqJHsKGRB3Nzc0KRJE17nhYiIasXa2hqjR4/m6cbIIkyePBkdO3bEkiVLZEchM8LBC5mMmTNnwsHBAR9++KHsKERVOn36NFJSUniaMSIiqpakpCSeZoyMTqVS4emnn+Z1XoiIqNZCQkKQnJyMs2fPyo5CZFAajQYLFy7EDz/8gNTUVNlxyExw8EIm4ZtvvkF0dDS+/fZbODk5yY5DVKUNGzagSZMmGDRokOwoRESkAMnJyejdu7fsGGSBfHx8sG/fPpSWlsqOQkRECjRkyBA0atQIUVFRsqMQGVxISAi6deuGd999V3YUMhMcvJB0ly9fxt///nfMmTMH3t7esuMQPVJkZCSCgoKg0WhkRyEiIhN3+fJlZGZmcvBCUgwePBiFhYU4cuSI7ChERKRAGo0Gzz33HE83RhZBrVZj0aJF2LRpE6+RR3rBwQtJJYTAyy+/jKZNm2Lx4sWy4xA9UmpqKtLS0niaMSIiqpakpCSo1Wr06tVLdhSyQB06dEDr1q15nRciIqq1kJCQir+Diczds88+i969e2PhwoWyo5AZ4OCFpFq+fDl++uknhIWFwc7OTnYcokeKiIhAy5Yt4enpKTsKEREpQFJSEjp37gxnZ2fZUchC+fj48DovRERUa4MGDULz5s0RGRkpOwqRUbz99tuIiYlBYmKi7CikcBy8kDTnz5/H/PnzMX/+fJ5+gxQjKioKwcHBUKu5+SQiokdLSkpCnz59ZMcgC+bj44ODBw+isLBQdhQiIlIgtVqNMWPGYMOGDbKjEBmFv78/Bg0axKNe6LHxm0OSQqfT4YUXXkDHjh0xf/582XGIqiU5ORlnz57lacaIiKhahBA4evQodzAhqXx9fVFaWoqDBw/KjkJERAoVEhKC06dPIyUlRXYUIqNYsmQJdu/ezaOG6bFw8EJSfPDBB0hKSkJYWBisra1lxyGqloiICLRt2xZPPfWU7ChERKQAZ8+exY0bNzh4IamaNWuGTp068YsDIiKqNU9PT7Ru3RoRERGyoxAZxcCBAzFkyBD885//lB2FFIyDFzK6kydP4t1338WSJUvQrVs32XGIqkUIgY0bN2LcuHFQqVSy4xARkQIkJSWhTp06cHd3lx2FLNzgwYOxZ88e2TGIiEihVCoVgoKCEBERASGE7DhERvH+++/j4MGDiIuLkx2FFEoluMXUKyEEMjMzkZGRgWvXriEnJwe5ubkV/4qKigAAN2/ehE6nq/g5W1vbiovL16tXDw0bNkSDBg0q/rVq1Qpt2rRB3bp1pfx36UtZWRk8PT1hY2ODffv2QaPRyI5EJiA/Px8ZGRm4dOlSpfUlJycHN2/eBAAUFRWhuLi44mc0Gk3FhYrt7e0rrS8NGzZEkyZN0LZtWzRt2lQvg5LExET0798fv/32G79AI+lKSkpw8eJFXLx4EdnZ2cjNzUVeXl7FuqPValFeXo5bt24hLy8PAFC/fn04OztDo9HAysqq0jrToEEDNGrUCK1bt0br1q1Rp04dyf+FRPolq5/99a9/xYEDB5CUlGT4/0iiKkRGRmLChAnIzc2t6E+PooR+RmRK2M/I3CUnJ6N3795ISkrSy1kg+P0ZKUFAQACuXbuGpKQkk+gu7GeKouXgpZZKSkpw8uRJpKamIjU1FSdPnkRGRgYuXryIkpKSise5uLjA1dW1YoG+++FQt27dShfnLi4urvhQyc/Pr/SBc++FMF1cXNCmTRu0b98e3bt3R7du3dC9e3e0bdtWESvH/PnzsWzZMhw7dgwdO3aUHYeMSAiB9PT0inXm+PHjOH/+PDIyMpCfn1/xOHt7+4ri5OrqWi6LZaEAACAASURBVFGW7OzsYGtrW/G4u3+0AEBhYWHF+nL9+nXcuHGj4nE2NjZo06YN2rRpg65du1asM08++SRsbGyqnf+vf/0r4uLi8N///vdxfxVE1Zabm4uUlBQcP34cqampOH36NC5cuICrV69W7GlmbW193x/pVlZWlcrVXbdu3UJ5eTm0Wm2lknb9+nVotVoAf1w8s2nTpmjbti26dOmCbt26oVu3bnB3d0f9+vWN/jsgqglT62eTJk2Cu7s7vvjiCyP9BogeLDc3F40aNUJ0dDQCAgIqbld6PyOSgf2MLFnHjh0xevRofPTRR9X+GVPrZ0r5/oxMQ2pqKnr27IlNmzZh9OjRRnlN9jOzwcFLdaWnp+PgwYM4ePAgEhIScOrUKWi1Wtja2sLNzQ1du3ZFu3bt0LZtW7Rp06ZiUqiPIzqKioqQkZFR6d/Zs2eRkpKCCxcuQAgBZ2dn9O7dG15eXujfvz88PT2rvTebsRw9ehSenp747LPPMHPmTNlxyMDy8/ORmJiIgwcP4sCBA0hOTkZBQQHUajXatWuH7t27o2PHjhUb9TZt2qB169YV5epxlJeXIzMzExcuXEBGRgYuXLiA9PR0nDhxAmlpaSguLoaVlRXc3Nwq1hkvLy+0adPmgc+n0+nQqlUrvPTSS3jnnXceOx/Rg5SVleHYsWMV68yhQ4dw+fJlAEDDhg3h7u6OJ554ouIz5u4606BBA728/vXr13Hx4sWKdSYjIwOnTp1CSkoKcnNzAQAtW7aEp6cnvLy84OXlBXd3d1hZWenl9Ylqw9T7mYODA7p27Yphw4aZbD8jy+Hu7o6BAwdixIgRZtHPiIyB/Yyosvnz52Pt2rW4ePHiQ4cXpt7PlPD9GZmWsWPH4vTp00hJSak0BNQXc/r+jCrh4OVh8vLyEB8fj7i4OMTHx+Pq1auwsbGBh4cH+vfvj969e1cs+DJPl1VQUIATJ04gJSUFhw4dwsGDB3H27FloNBq4u7tj2LBhGD58OPr37y+1fBUXF8PDwwPNmjVDfHw89y4wQ2VlZThw4ADi4uKwc+dOpKamQqfToXPnzvD09ISnpyfc3d3h5uYGR0dHaTm1Wi3Onj2L1NRUHDlyBImJiTh69ChKS0vRvHlzDB06FMOHD4efnx9cXFwAAHv37sXTTz+NEydOwM3NTVp2Mj+nT59GbGws4uLisH//fhQWFqJhw4bw9PRE//790atXL3Tr1g1NmzaVmjMzMxPHjx/H0aNHKwphXl4eHBwcMGjQIPj7+2P48OE8kpEMjv2MqGbu7WdbtmzBuXPnzKafERkK+xnRw6WmpsLd3R0HDhxA//79AbCfkfk7efIkunfvju+//x7jxo177Ocz5+/PqBIOXu514cIFREZGIjo6GkeOHIFKpYKXlxeGDRuGQYMGwcPDo9KhWqYqKysLiYmJ+OmnnxAXF4dz586hbt268PPzw5gxYxAYGAgHBwejZnr99dcRFhaG1NRUtGrVyqivTYZTUFCAbdu2YfPmzdi9ezdu3bqFTp06wd/fHz4+Pujfvz9cXV1lx3ykoqIiJCcnY9++fYiLi8OhQ4cghEC/fv0watQonDp1CklJSTh+/LjsqKRwOp0OCQkJiIqKwo8//ogLFy6gfv368PPzg5+fH7y8vNC5c2eTH04LIXDq1CkcOHAA8fHx2L17N/Lz89G+fXuMGDECwcHB8PT0NMjeQGR52M+IasZS+llwcDBat24tOyaZAfYzopp54okn4OXlhY4dO7KfkcWYOHEijhw5grS0tFoN5tjPLBIHL5cuXUJkZCQiIiKQlJSEBg0aYPTo0fD394evr69ZXIzr7NmziIuLQ0xMDPbs2YM6dergmWeeQUhICAICAgz+YZiQkABvb2989913mDRpkkFfiwyvqKgI27ZtQ2RkJGJjY6HVajFkyBAEBATA398f7dq1kx3xseXn52PXrl2IjY1FdHQ0bty4AXd3d0yePBnBwcFo3ry57IikMAcPHkRERAQ2btyIzMxMdO3ateKzpm/fvlL3/NIHrVaLxMTEinUmLS0NLVq0QFBQEEJCQtC3b1/ZEUlh2M8M38/IvFhqP+vbty+Cg4PZz6hW2M/Yz6hm7vazsLAwHD9+nP2MLMq5c+fwxBNPYNWqVXjhhReq9TPsZxbfz7QQFqi8vFzs2rVLBAUFCSsrK1GvXj0xadIksW3bNlFaWio7nkHl5uaKsLAwERAQIKytrUXdunXF9OnTxW+//WaQ1ysoKBDt27cXo0aNMsjzk/GkpaWJ0NBQ0aBBA6HRaISXl5f49NNPRVZWluxoBqXVasX+/fvF7Nmzhaurq1Cr1cLX11dERkaKsrIy2fHIhN24cUN8/fXXonv37gKAaNu2rQgNDRUnT56UHc3gTpw4IRYtWiS6dOkiAIguXbqIDz74QOTk5MiORiaM/cx4/YzMB/sZ+xnVDPsZ+xnVDPsZ+xn9z0svvSRat24tSkpKqnwc+xn72f8rs6jBy9WrV8WCBQtE06ZNhVqtFkOHDhVRUVGPXGHMVWZmpnj//fdF+/btBQDRv39/sW7dOr1+eE6dOlU0bNhQXLt2TW/PScZTUlIiwsLCRN++fQUA0alTJ/Hhhx+a/YfFwxQXF4uIiAjh6+sr1Gq1aN68uVi0aBGXb6okMTFRjBs3TtjY2AhnZ2cxc+ZMcfToUdmxpDly5IiYNm2acHJyEra2tmLixIniyJEjsmORCWE/q8wY/YyUjf2sMvYzqg72s8rYz+hR2M8qYz8jIYS4ePGisLGxEV9++eV997GfVcZ+JoSwlMHL8ePHxYsvvihsbGxE48aNxfz580V6errsWCZDp9OJ3bt3i+DgYGFlZSVatmwpPvroI5Gfn/9Yz7tz506hUqlEVFSUnpKSseTl5Yn3339fNGvWTFhbW4vx48eLn3/+Weh0OtnRTMa5c+fEW2+9JVxdXYWtra2YNm2aSEtLkx2LJCkvLxebNm0S/fv3FwBE7969xZo1a8Tt27dlRzMZBQUFYtWqVaJXr14CgBg0aJCIjo4W5eXlsqORJOxnVTNUPyPlYj97NPYzuhf72aOxn9GfsZ9Vjf2MXnnlFdGsWTNRWFgohGA/qw4L7mfmPXg5fPiw8Pf3FyqVSjzxxBNi1apVoqioSHYsk5aRkSH+9re/CScnJ+Hs7CxCQ0PF9evXa/w8N27cEC1atBCTJk0yQEoylKysLDFnzhzh6Ogo6tatK958801x6dIl2bFMWmFhofjqq69Ep06dhEqlEoGBgRa995ylKSsrE998843o0KGDUKvVYtSoUWLv3r2yY5m8PXv2iBEjRgiVSiU6d+4swsPDhVarlR2LjIT9rOb01c9ImdjPao79zLKxn9UO+5llYz+rOfYzy5SZmSns7OzEkiVL2M9qyAL7mXkOXo4dOyYCAwMFAOHp6SliYmI4aayh/Px88cEHHwhXV1fh7OwsFi5cKG7cuFHtnw8JCRHNmjUTeXl5BkxJ+pKbmyveeust4ejoKJo0aSL+/e9/i1u3bsmOpSjl5eVi69atonfv3kKlUonnnntOHD9+XHYsMpDy8nKxbt060bFjR2FtbS1efvllcfr0admxFOfkyZNiypQpwsrKSjzxxBMiIiKCe1iaMfazx/e4/YyUhf3s8bGfWRb2M/1gP7Ms7GePj/3MsuTm5oqxY8cKBwcH9rNasqB+Zl6Dl/T0dBEUFCRUKpXw8PAQP/74o+xIildQUCD+9a9/CRcXF+Hi4iKWLl0qiouLq/yZzZs3C5VKJXbs2GGklFRbhYWFYsmSJcLZ2Vk0bNhQfPjhh+LOnTuyYymaTqcT0dHRwt3dXajVavH888+Lixcvyo5FehQTEyOefPJJodFoxOTJk8X58+dlR1K806dPi/Hjxwu1Wi26d+8u4uPjZUciPWI/07/a9DNSDvYz/WM/M3/sZ/rHfmbe2M/0j/3MvLGf6Z8F9DPzGLzcunVLvPXWW8LW1lZ07txZbNmyhRN6PcvPzxcLFiwQ9vb2okOHDmLLli0PfFxWVpZo1KiR+Mtf/mLkhFRTERERok2bNsLR0VEsXryYE3o90+l0IjIyUnTo0EHY29uLhQsX8kNZ4dLS0sSwYcMEADFmzBhx6tQp2ZHMzvHjxyv2uBs5cqQ4c+aM7Ej0GNjPDK+6/YyUg/3MsNjPzA/7meGxn5kX9jPDYz8zP+xnhmXG/Uz5g5fw8HDRtGlT4eLiIj755BNRWloqO5JZ+/3338W4ceOESqUSQ4YMue9iSM8++6xo27YtN0ImLDU1VQwcOFCoVCoxefJkceXKFdmRzFpxcbFYunSpcHZ2Fi1atBAbNmyQHYlq6ObNm2L27NnC2tpa9OjRQ/zyyy+yI5m9+Ph44ebmJurUqSPefPNNXgRXgdjPjOtR/YxMH/uZcbGfKR/7mfGxnykf+5lxsZ8pH/uZcZlhP1Pu4CU9PV0MHTpUqNVqMXPmTJGTkyM7kkVJSEgQvXr1EjY2NmLx4sWipKRErF69WqjVapZeE1VcXCwWLFggrK2tRd++fcWRI0dkR7Io165dE1OnThUqlUoEBASI33//XXYkqoZt27aJFi1aiIYNG4qVK1fy/NZGVFZWJlasWCFcXFxEmzZtRFxcnOxIVA3sZ3I9qJ+RaWM/k4v9TJnYz+RhP1Mm9jO52M+Uh/1MLjPqZ8obvGi1WvHJJ58IBwcH8eSTT4qDBw/KjmSxysrKxMcffyzs7e1F165dRceOHcUbb7whOxY9wP79+0WXLl2Eo6OjWLZsGf84kWjv3r2iU6dOwsnJSaxYsYLvhYnKysoS48aNEwDEhAkTRHZ2tuxIFuvq1ati7NixAoCYNGmSuH79uuxI9ADsZ6bjz/3s0KFDsiPRQ7CfmQ72M2VgPzMd7GfKwH5mOtjPlIP9zHSYQT9T1uDl4sWLwtvbW1hbW4vQ0FBepMpE3Lv3xCuvvMLpvQkpKysTixYtEhqNRvj7+4uMjAzZkUgIUVRUJBYtWiTq1KkjfHx8xKVLl2RHonvExcWJpk2bimbNmvF8vCYkJiZGtGzZUjRq1EjExMTIjkP3YD8zTff2s9mzZ7OfmRD2M9PEfmba2M9ME/uZ6WI/M03sZ6aL/cw0KbyfKWfw8v3334u6deuKrl27ipSUFNlx6E90Op344osvhL29vejbt684e/as7EgW79SpU6JXr17C0dFRrF69WnYceoDk5GTRpUsXUb9+fREVFSU7jsW7c+eOmDlzpgAgXnjhBV6rygTl5+eL8ePHC5VKJV5//XVRVFQkO5LFYz8zbexnpof9zPSxn5kW9jPTx35metjPTBv7melhPzN9Cu1npj94KSgoEBMmTBAqlUrMnj2bH+ImLi0tTfTs2VM4OjqKsLAw2XEs1sqVK4W9vb3o06ePOHPmjOw4VIU7d+6IGTNmCABi6tSporCwUHYki5SSklLxIR4ZGSk7Dj3C2rVrhbOzs+jWrZs4deqU7DgWif1MWdjPTAP7mXKwn5kG9jNlYT+Tj/1MWdjPTAP7mXIosJ+Z9uDl9OnTws3NTbi6uorY2FjZcaiaSkpKxJw5c4RKpRKzZs3ioZNGVFRUVHEBqnnz5onS0lLZkaiatm7dKurXry969Ogh0tPTZcexKOvWrRP29vZi0KBBSjts1aKlp6eLfv36CScnJ7Fx40bZcSwK+5kysZ/Jw36mXOxn8rCfKRP7mTzsZ8rEfiYP+5lyKaifme7gZfv27aJevXqiV69e4sKFC7LjUC1ER0eLunXrCg8PD54b0QguXbok+vTpI5ydncXmzZtlx6FauHjxoujdu7dwdnYWW7dulR3H7JWVlYnQ0FABQEyfPp1FS4Huvod39+rje2h47GfKx35mXOxnysd+ZlzsZ8rHfmZ87GfKx35mXOxnyqeQfmZ6gxedTicWL14sVCqVePnll3kBMIVLS0sTXbp0EU2aNBGHDx+WHcds7d+/XzRs2FB07dqVh0YqXGFhoZg0aZJQq9Xiww8/lB3HbOXm5gpvb2/h4OAg1q9fLzsOPabvvvtO2NnZiaFDh4r8/HzZccwS+5l5YT8zDvYz88F+ZhzsZ+aF/czw2M/MC/uZcbCfmQ8F9DPTGryUlJSIF154QVhZWYkvvvhCdhzSk1u3bolnnnlG2Nvbc5JsAOvXrxe2trZi9OjR4vbt27LjkJ588sknQqPRiBkzZoiysjLZcczKuXPnROfOnUWrVq14sUkzkpycLJo1aya6desmLl68KDuOWWE/M0/sZ4bFfmae2M8Mh/3MPLGfGQ77mXliPzMs9jPzZML9zHQGL7du3RLDhw8Xjo6OYvv27bLjkJ5ptVrx6quvCpVKJRYtWiQ7jtn49NNPhVqtFrNnzxbl5eWy45CexcbGCicnJ+Hn58e9xPTk0KFDolGjRqJ79+48X7gZunLliujZs6do2rSpSEpKkh3HLLCfmTf2M8NgPzNv7Gf6x35m3tjP9I/9zLyxnxkG+5l5M9F+ZhqDl2vXrolu3bqJ5s2bi2PHjsmOQwb00UcfCbVaLd544w2h0+lkx1EsnU4nXn31VaHRaMTy5ctlxyEDOnLkiGjSpIno1auXyMnJkR1H0Xbs2CHs7OxEQECAKCgokB2HDOTmzZvCz89PODo6ip9++kl2HEVjP7Mc7Gf6wX5mOdjP9If9zDKwn+kP+5nlYD/TD/Yzy2GC/Uz+4OXSpUuic+fOolOnTuL333+XHYeM4PvvvxdWVlZi5syZnDLXglarFVOnThV16tQRGzdulB2HjOD8+fOibdu2ws3NTWRmZsqOo0ibNm0SderUES+++KLQarWy45CBlZaWivHjxwtbW1sRExMjO44isZ9ZHvazx8N+ZnnYzx4f+5llYT97fOxnlof97PGwn1keE+tnZWpIlJGRgaeffhpqtRo///wzWrZsKTMOGcnzzz+PLVu24LvvvsPEiROh1WplR1KM8vJyTJ06Fd9//z0iIyMxZswY2ZHICNq1a4eDBw9CpVKhf//+OH/+vOxIirJhwwaMGzcOU6dOxerVq6HRaGRHIgOztrbGunXrMHHiRIwePRpr166VHUlR2M8sE/tZ7bGfWSb2s8fDfmZ52M8eD/uZZWI/qz32M8tkcv1M1sgnPT1dtGjRQnh4eIjr16/LikESxcXFCXt7ezFu3Dju4VQNZWVlYsyYMcLR0VHs2bNHdhySICsrS7i7u4vWrVvz4pTVFB4eLtRqtfjHP/4hOwpJoNPpxOzZs4VGoxEbNmyQHUcR2M+I/axm2M+I/azm2M8sG/tZzbGfEftZzbCfkYn0szKVEEIYe9hz+fJlDBo0CC4uLvjpp59Qr149Y0cgE7Fnzx4EBARg/PjxWL16NVQqlexIJkmn02HKlCnYvHkz4uLiMHDgQNmRSJK8vDz4+PigqKgIe/fuRdOmTWVHMlkbN27EuHHj8Oabb+L999+XHYck+tvf/obPP/8cmzZtQmBgoOw4Jov9jO5iP6se9jO6i/2s+tjP6C72s+phP6O72M+qh/2M7jKBfqY1+uAlJycH3t7e0Ol02Lt3Lxo3bmzMlycTFB8fj5EjR2LatGlYvny57DgmRwiBWbNm4ZtvvsHWrVvh7+8vOxJJxu3oo3G7QvcSQuAvf/kLvv32W25HH4LbFfozbkerxn5Gf8bt6KNxu0L3Yj97NG5X6M+4Ha0a+xn9meTtqNao13i5desWfH19odVq8fPPP/NDgwAAQ4cOxbp16/Dll19i4cKFsuOYnNDQUKxZswYbN27khwYBAFxdXREfH4+SkhIEBATgzp07siOZlH379mHUqFGYOHEiPvvsM9lxyASoVCp88cUXCAoKQlBQEA4fPiw7kklhP6MHYT+rGvsZ/Rn7WdXYz+jP2M+qxn5GD8J+VjX2M/oz2f3MaEe8lJWVYcSIETh58iQSExPRqlUrY7wsKciaNWswbdo0rFmzBi+++KLsOCbhiy++wKuvvop169bh+eeflx2HTMz58+fh6emJvn37YuvWrbwoKYDTp0+jf//+8PHxQUREBH8nVIlWq8Xo0aORlJSExMREtGvXTnYk6djP6FHYz+7HfkZVYT+7H/sZVYX97H7sZ/Qo7Gf3Yz+jqkjqZ1oY62oyf/nLX4S9vb04fPiwsV6SFGj+/PnC2tpaxMfHy44i3Y4dO4SVlZVYsmSJ7Chkwo4cOSLs7e3F9OnTZUeRLicnR3Ts2FH07t1b3LlzR3YcMlF37twRffr0EV26dBG5ubmy40jHfkbVwX72P+xnVB3sZ//DfkbVwX5WGfsZVQf72f+wn1F1SOhnZUYZvLz33ntCo9GI7du3G+PlSMF0Op0YP368qFu3rjhx4oTsONL8+uuvwtHRUUydOlV2FFKAqKgooVarxX/+8x/ZUaQpKioS/fr1E+3btxfZ2dmy45CJu3LlimjZsqXw9vYWJSUlsuNIw35G1cV+9gf2M6oJ9jP2M6oZ9rM/sJ9RdbGf/YH9jGrCyP2szOCnGtuxYwcCAwPx6aef4rXXXjPkS5GZKCkpwZAhQ5CdnY0jR46gXr16siMZVW5uLp566im0b98esbGxsLa2lh2JFODDDz/EvHnzsHPnTgwZMkR2HKObOnUqtmzZgkOHDqFz586y45ACpKamwsvLC1OmTMGKFStkxzE69jOqKfYz9jOqOfYz9jOqGfYz9jOqGfYz9jOqOSP2M61BBy8ZGRl46qmn4O/vj7Vr1xrqZcgMZWVlwcPDAz179kR0dDTUarXsSEah0+kwYsQIpKWlITk5Ga6urrIjkYKMGzcOu3btQnJyMtq2bSs7jtF89dVXmDVrFjZt2oRnn31WdhxSkK1bt+K5556zuHMjs59RbbGfsZ9RzbGfsZ9RzbCfsZ9RzbCfsZ9RzRmpnxlu8FJUVIQBAwagvLwcBw8ehL29vSFehszYoUOH4O3tjQULFuCf//yn7DhGMW/ePHzyySfYt28fevfuLTsOKcydO3fQr18/WFlZ4eDBg7Czs5MdyeAOHz4Mb29vzJ07F2+//bbsOKRAb775JlasWIGEhAR4eHjIjmNw7Gf0uNjP2M+oZtjP3pYdhxSI/Yz9jGqG/Yz9jGrGSP3McIOXqVOnYtu2bUhOTkabNm0M8RJkAT7//HPMnj0bu3btwuDBg2XHMagdO3YgICAAq1evxtSpU2XHIYU6c+YM+vTpgwkTJuDzzz+XHcegbty4AXd3d3Tr1g3bt2+3mD17SL+0Wi2GDRuGixcv4tixY3BycpIdyaDYz0gf2M+Iaob9jKhm2M+Iao79jKhmjNDPDDN42bJlC8aMGYMtW7Zg1KhR+n56sjDjxo1DQkICUlJS0KBBA9lxDCInJwfdu3eHn58fwsPDZcchhdu0aROCgoIQHR2NwMBA2XEMZvz48di3bx9SU1PNdttAxpGdnY3u3bvD398f3377rew4BsN+RvrEfkZUM+xnRDXDfkZUc+xnRDVj4H6m/8HLlStX4O7ujrFjx+Krr77S51OThcrPz4e7uzs8PDywefNm2XH0TgiBUaNG4bfffkNKSgpcXFxkRyIzMGXKFMTGxiI1NRVNmjSRHUfvvvvuO0ydOhU//vgj/P39ZcchMxAbG4sRI0bghx9+wLhx42TH0Tv2M9I39jOimmM/I6oZ9jOimmE/I6o5A/Yz/Q5edDodhg4disuXL+Po0aNwcHDQ11OThduzZw/8/PywatUqszuM8Msvv8Rrr72GvXv3wsvLS3YcMhMFBQXo0aMHOnfujB9//BEqlUp2JL1JT09Hjx49MG3aNPz73/+WHYfMyCuvvIL169cjJSUFLVu2lB1Hb9jPyFDYz4hqhv2MqObYz4hqhv2MqGYM2M/0O3j56quv8Nprr+HQoUMWcQE0Mq4333wTq1atwsmTJ9G8eXPZcfTi4sWL6Nq1K15//XUsWbJEdhwyM4mJiRg4cCBWrVqFF198UXYcvRBCwNfXFzk5OUhKSoKNjY3sSGRGioqK0KtXL7Rr1w4//vij7Dh6w35GhsR+RlQz7GdENcN+RlRz7GdENWOgfqa/wUtmZibc3Nwwc+ZMvP/++/p4SqJKioqK0L17d3Tu3BkxMTGy4+jFyJEjcebMGfz222+wtbWVHYfM0F//+lesXbsWaWlpaNy4sew4j23NmjWYPn06EhIS4OnpKTsOmaHExEQMGPB/7N13fM13///x58kiIkYSe+8QBDEiMWvFaqmRS9uora3+dLkuvS79ouu6XO3V4tKqkdboQESrFDFrxa4RI1IlVlEiBEFkvH5/9JZcyHDeyfmc9xnP++3mHz0+75c0b+dxzjvnnHb4+uuv8dxzz+kep8jYZ2Q09hmROvYZkRr2GZEa9hmROgP6zHIHL/3798fx48dx5MgReHp6WuKSRLls3boVTz31FKKiojBw4EDd4xTJ119/jWHDhmHbtm1o166d7nHIQd29exdNmjRBq1atsHTpUt3jFMmVK1fQqFEjDB8+nG9hQYZ6+eWXER0djRMnTqBcuXK6xykS9hlZA/uMSA37jEgd+4xIDfuMSI0BfWaZg5fo6GgMHjwYmzdvRufOnS0xGFG+Ro4ciXXr1iE+Ph6lS5fWPU6hXL9+Hf7+/ggPD8dnn32mexxycOvWrUOvXr3w008/oXfv3rrHKbTw8HDs378fR48e5Xsgk6FSUlIQEBCArl27YuHChbrHKTT2GVkT+4xIDfuMSA37jEgd+4xIjYX7rOgHL/fu3UPDhg3RqVMnu77zI/uRnJyM+vXrY9iwYfjPf/6je5xCefXVV7FixQokJCSgVKlSuschJxAeHo5Dhw7h2LFj8PDw0D2Osq1bt6Jz5852/+QE2Y/ly5cjPDwcu3fvRps2bXSPo4x9RtbGPiNSxz4jUsM+I1LDPiNSZ8E+K/rBy/vvv4+PPvoICQkJqFy5clEuRWS2zz//HG+++SaOHj2K+vXr6x5HyYkTJxAYGIh58+Y5zAdqku27NkZCmQAAIABJREFUcOEC/P398e6772LChAm6x1GSlZWF1q1bo2zZsti4caPucciJdO7cGbdv38a+ffvg4uKiexwl7DPSgX1GpIZ9RqSOfUakhn1GpMaCfVa0g5fff/8dDRo0wKRJk/D3v/+9KIMQKcnMzETz5s1Rs2ZNrFq1Svc4SsLCwnD16lUcOHDA7kKR7NvkyZMxY8YMJCQkoFKlSrrHMdu8efMwbtw4HD58GAEBAbrHISdy5MgRBAUFYcGCBYiIiNA9jtnYZ6QL+4xIHfuMSA37jEgN+4xInYX6rGgHL8OHD8fWrVsRHx+P4sWLF/YyRIWyadMmdOvWDZs2bUKXLl10j2OWtWvXok+fPti2bRvat2+vexxyMqmpqfD390fv3r0xZ84c3eOY5c6dO6hbty7Cw8Mxc+ZM3eOQExo7dizWrFmDU6dO2c2Hn7LPSCf2GZEa9hmROvYZkRr2GZEaC/VZ4Q9eTp06hUaNGmHBggV44YUXCjsAUZGEhYUhOTkZe/fuhclk0j1OgUQEbdq0QeXKlbFy5Urd45CTioyMxCuvvIKTJ0+idu3ausd5on/+85/417/+hdOnT6N8+fK6xyEndOXKFdSpUwcffvghXn/9dd3jPBH7jGwB+4xIDfuMSA37jEgd+4xIjQX6rPAHL0OGDMHBgwdx4sQJuLq6FuYSREX2yy+/oFWrVlizZg169uype5wCff/99xg4cCAOHjyIZs2a6R6HnFRmZiYCAgIQEhKCr776Svc4BUpJSUHt2rUxbtw4vPfee7rHISf217/+FYsWLcKZM2dQsmRJ3eMUiH1GtoB9RqSGfUakjn1GpIZ9RqTGAn1WuIOX48ePo2nTpli6dCkGDRpUmIWJLObpp5/GpUuXsH//fps9tc/KykKLFi1Qv359REVF6R6HnNzXX3+N4cOH4/jx42jQoIHucfI1depUzJgxA4mJiShbtqzucciJJSUloXbt2njnnXfwt7/9Tfc4+WKfkS1hnxGpYZ8RqWGfEaljnxGpKWKfFe7gJTw8HAkJCTh48CA/3Ii0O3z4MFq0aIEff/wRffv21T1OnpYvX44hQ4YgLi4OjRo10j0OObnMzEw0btwYrVq1wuLFi3WPk6eUlBTUqFEDEyZMwDvvvKN7HCJMmjQJc+fOxblz5+Dl5aV7nDyxz8iWsM+I1LDPiNSxz4jUsM+I1BSxz9QPXhITE1GvXj18++23CA8PV12QyBB9+vTB7du3sW3bNt2j5Ck4OBhVq1ZFdHS07lGIAAALFy7EmDFj8Ntvv6F69eq6x8nl448/xvvvv4/z58+jTJkyuschQnJyMqpXr45p06bh1Vdf1T1OLuwzskXsMyI17DMiNewzInXsMyI1ReizDOXj9unTp6Nq1aoYMGCA6h8lMsxbb72F7du3Y+/evbpHyWXHjh3Yu3cv3nrrLd2jEOV4/vnnUaFCBXz22We6R8klPT0dn332GUaPHs0H9WQzfHx8MHToUHz66afIzMzUPU4u7DOyRewzIjXsMyI17DMidewzIjVF6TOlg5cbN25gwYIFeP311+Hm5qa8GJFROnfujNatW2P69Om6R8nlk08+QUhICNq2bat7FKIc7u7uGDduHObOnYuUlBTd4zwiKioKly5dwvjx43WPQvSICRMm4Pz581i5cqXuUR7BPiNbxT4jUsM+I1LHPiNSwz4jUlOUPlM6eImMjISrqytGjhyptAiRNbz++utYsWIFzp8/r3uUHKdPn8bq1avx5ptv6h6FKJexY8ciKysLCxcu1D3KI2bMmIGBAweiRo0aukchekTt2rXRt29fzJgxQ/coj2CfkS1jnxGpYZ8RqWGfEaljnxGpKWyfmX3wIiKYP38+XnzxRXh7e6vOR2S4QYMGoVy5cliwYIHuUXJERkaicuXK6Nevn+5RiHIpW7YsnnvuOcydO1f3KDmOHDmCAwcOYNy4cbpHIcrTuHHjsHPnThw/flz3KADYZ2T72GdEathnROrYZ0Rq2GdEagrbZ2YfvPz88884deoURowYoTwckTW4ubkhIiICkZGRNvH+rhkZGVi8eDFGjBgBV1dX3eMQ5Wn06NGIj4/H7t27dY8CAJgzZw78/f0RGhqqexSiPHXp0gV169bFl19+qXsUAOwzsn3sMyJ17DMiNewzIjXsMyJ1hekzsw9e5s+fj+DgYAQGBhZqOCJrGDNmDH7//Xds2LBB9yhYtWoVrly5wtgim9ayZUs0b94ckZGRukdBamoqvvvuO4wZMwYmk0n3OER5MplMGDZsGBYvXoy0tDTd47DPyC6wz4jUsM+I1LDPiNSxz4jUFKbPzDp4SU5Oxg8//IDRo0cXejgia6hTpw46duxoEz/p8uWXX6J79+58H2SyeSNHjsSyZctw+/ZtrXNERUUhLS0NERERWucgepLhw4cjJSVF+4e4ss/IXrDPiNSxz4jUsM+I1LDPiNSp9plZBy/ff/89XFxcMGjQoCINR2QNQ4cOxZo1a3Dr1i1tMyQlJWHjxo0YOnSothmIzDVkyBA8ePAAq1at0jrH0qVL0bt3b/j5+Wmdg+hJKleujK5du2LJkiVa52CfkT1hnxGpYZ8RqWGfEaljnxGpUe0zsw5eli1bhl69evFDwcgu9O/fH1lZWfjxxx+1zfD999/D3d0dffv21TYDkbl8fHzQrVs3LFu2TNsMSUlJ2LJlC8LDw7XNQKRi8ODBiImJQUpKirYZ2GdkT9hnRGrYZ0Tq2GdEathnRGpU++yJBy/Xrl3D1q1bMXjw4CIPR2QNZcqUQbdu3RAVFaVthmXLlqF3794oWbKkthmIVAwePBjr16/HjRs3tKwfHR0NDw8P9O7dW8v6RKr69+8PANoepLDPyN6wz4jUsc+I1LDPiNSwz4jUqfTZEw9evv/+e8YW2Z3w8HBs2LBBy4OUq1evYtu2bXxpMdmVZ555BiaTSdvbWSxfvhy9e/eGl5eXlvWJVOl+kMI+I3vEPiNSwz4jUsM+I1LHPiNSo9JnTzx4WbVqFcLCwhhbZFeefvppiAjWr19v9bXXrl0Ld3d39OrVy+prExVWmTJl0KVLFy0P7G/evInt27djwIABVl+bqCgGDBiAzZs34+7du1Zfm31G9oh9RqSGfUakjn1GpIZ9RqRGpc8KPHi5f/8+tm7dip49e1psOCJrKF26NNq2bYuYmBirr71u3Tp07NiRsUV2p2fPnti0aRPS09Otuu7GjRshIujWrZtV1yUqqrCwMKSlpWHr1q1WXZd9RvaKfUakjn1GpIZ9RqSGfUakztw+K/DgZdu2bbh79y66d+9u0eGIrCEsLAzr16+HiFhtzczMTGzatAlhYWFWW5PIUnr37o1bt25h9+7dVl03JiYGbdq0gY+Pj1XXJSqqihUrolmzZli3bp1V12WfkT1jnxGpYZ8RqWGfEaljnxGpMbfPCjx4iYmJQZMmTVC9enWLDkdkDT179sSVK1dw6NAhq625Z88eJCcn86dcyC7VqlULdevWtepPumS/pJl7huxVWFgY1qxZY9U12Wdkz9hnRGrYZ0Tq2GdEathnRGrM7bMCD142bdqEHj16WHQwImsJDAxEpUqVsHHjRqutuWnTJtSsWRMNGjSw2ppEltSzZ0+r7pn4+Hj8/vvvvK8huxUWFobExEQkJiZabU32Gdkz9hmROvYZkRr2GZEa9hmROnP6LN+Dlxs3buDEiRPo0KGDxQcjsgaTyYR27dohNjbWamvu3LkT7du3t9p6RJbWvn17HD58GHfu3LHKejt37oSXlxeaN29ulfWILK1NmzYoXry41e5r2Gdk79hnROrYZ0Rq2GdEathnROrM6bN8D1527doFEUFwcLAhwxFZQ2hoKGJjY5GVlWX4WpmZmdi3bx9CQ0MNX4vIKKGhocjIyMDevXutsl5sbCyCg4Ph5uZmlfWILK1YsWJo0aKF1R6ksM/IEbDPiNSwz4jUsM+I1LHPiNSY02cFHrw0aNAA5cqVM2Q4ImsIDQ1FcnIyEhISDF8rLi4Ot27d4h0H2bXKlSujZs2aVn2Qwj1D9i40NBQ7d+60ylrsM3IE7DMiNewzInXsMyI17DMiNeb0Wb4HL7t370ZISIghgxFZS7NmzeDl5WWVBym7d+9G6dKl0ahRI8PXIjJSu3btsGvXLsPXuXr1Kk6fPo22bdsavhaRkUJDQ3HixAncvHnT8LXYZ+QI2GdE6thnRGrYZ0Rq2GdE6p7UZ3kevIgIDh06hJYtWxo2GJE1uLm5ITAwEIcPHzZ8rUOHDiEoKAguLvmeZxLZhaCgIBw8eNDwdQ4dOgQR4X0N2b2WLVsiKysLR44cMXQd9hk5CvYZkTr2GZEa9hmRGvYZkbon9Vme3+Hnz5/HzZs30bRpU8MGI7KWpk2bIi4uzvB1jhw5wj1DDqFJkya4du0arly5Yug6cXFxqFKlCvz8/Axdh8hoVapUga+vr+H3NewzciTsMyI17DMiNewzInXsMyI1T+qzPA9ejhw5ApPJhCZNmhg6HJE1NGnSBHFxcRARw9bIysrCiRMnuGfIIQQGBgIAjh49aug6cXFxjC1yGI0bNzZ8z7DPyJGwz4jUsM+I1LHPiNSwz4jUPKnP8jx4iYuLQ82aNVGqVCnjJiOykiZNmiAlJQUXLlwwbI1Tp04hNTWVD1LIIfj5+aFixYqG/6QLH9iTI2natKlVngxjn5GjYJ8RqWGfEaljnxGpYZ8RqXlSn+V58HLy5El+wBE5jICAAADAiRMnDFvj5MmTMJlMaNiwoWFrEFlTQEAA4uPjDbt+VlYWEhISeF9DDiMgIMDQ+xmAfUaOhX1GpI59RqSGfUakhn1GpK6gPsvz4CUxMRG1a9c2dCgia/Hx8UGZMmVw9uxZw9Y4c+YMKlSoAC8vL8PWILKmWrVqITEx0bDrX7p0CWlpabyvIYdRq1Yt3Lp1C8nJyYatwT4jR8I+I1LHPiNSwz4jUsM+I1JXUJ/lefBy9uxZ1KxZ08iZiKyqZs2ahj5IOXfuHGrVqmXY9YmszegH9tkhx/sachTZ9wFG7xvuGXIk7DMiNewzIjXsMyJ17DMiNUoHL/fv38eVK1d4x0EOpVatWoae2CcmJnLPkEOpVasWLly4gIyMDEOuf/bsWXh4eKBy5cqGXJ/I2mrUqAEXFxfDHqSwz8gRsc+I1LDPiNSwz4jUsc+I1BTUZ7kOXs6fP4+srCxuAnIoRv902Llz57hnyKHUqlULGRkZuHjxoiHXP3v2LKpXrw4XlzxfeElkdzw8PFClShXD7mvYZ+SI2GdEathnRGrYZ0Tq2GdEagrqs1xFdfnyZQBAlSpVjJ+sADExMTCZTJgxY4bWOQpr4cKFMJlMiI6O1j0KAahcuTKuXLli2PUvX76s/SfDuGfIkrK/n43aN1euXNG+ZwDuG7KsSpUq4Y8//jDk2uwzy+CesS3sM9vHPWNb2Gf2gfvGtrDPbB/3jG1hn9k+7hnbUlCf5Tp4uX79OkwmE3x8fIyfjKxm586dMJlM+OCDD7T8ed18fX2RlJRkyLVFBMnJyfD19TXk+qQH98yf38/Xr1835PpJSUnw8/Mz5Nqkj7PvGz8/P8Pua9hnjsnZ9wz7jFRxz7DPSJ2z7xv2Galy9j3DPiNV3DP591meBy+lSpWCu7u78ZMRWYmfnx/u3buHe/fuWfzaKSkpyMjI4IMUciheXl7w9PQ07IH99evXGVvkcHx9fQ3dM+wzcjTsMyI17DMidewzIjXsMyI1BfVZngcv3ADkaIz86bDsa/JBCjkaox+k8L6GHI2fnx/3DJEC9hmROvYZkRr2GZEa9hmRuvz6LNfBy40bN1C2bFmrDGWuzZs3IyQkBCVKlED58uUxevRoXLt27ZHbPPz+fNu2bUPHjh3h7e2Nli1bAgDu3buHd999Fw0bNkTx4sVRunRpdOnSBevXr8+13vbt2/H888+jbt26KFasGMqVK4e+ffsiNjY2121v3ryJV199FZUqVYKnpydatmyJn376Kd+/i4hg4cKF6NChA8qUKQNvb2+0atUK8+fPR0ZGhvIMmZmZmDVrFoKCglC2bFmUKVMGLVu2xKeffoq7d+8CAD744AO0b98eAPB///d/MJlMOb/MYc6fV/n66pD9j3pycrLFr33jxg0AsKmXF3PPcM9Ygo+PjyF7BuB9DcB98zhH2DfcM9wz2bhnzMM+457Jxj1jPt7XcN9k474xD/cM90w27hnzsM+4Z7Jxz5gv3/saecz48eOlffv2j/+21a1bt04AyKBBg8TV1VUAPPLL399fbt++neft3dzccm7XvHlzSUtLk9DQ0FzXACAmk0m++OKLnOtcvnw5z9sBEDc3N9m2bVvObe/duyfNmjXL85rh4eECQJYvX55z+6ysrJzfz+vXxo0blWf461//mu9tZ82aJSIi77//fr63MceT/rzK11eXc+fOCQDZu3evxa+9fft2ASCXL1+2+LVVcM9wz1ha69atZcKECYZcu2LFivLf//7XkGur4L7hvrGkjz/+WGrUqGHItdln3DOPc4Q9wz7jnsnGPWM+9hn3TTbuG/Owz7hnsnHPmId9xj2TjXvGfPn0WXqur8JLL70kXbp0sc5UBcj+pgYgw4YNk1OnTsmdO3dk+/bt0qRJEwEg77zzTp63HzFihCQkJEhGRoaIiHzyyScCQKpXry6rV6+WlJQUOX/+vEydOlVcXFykePHiOZv+ypUr0q1bN1m9erVcuHBBHjx4IH/88YdERUWJl5eX9OzZM2fNjz76SABIgwYNZNOmTXL79m05c+aMvPLKKzmzPLwJIiMjBYD4+vrKnDlz5Pz583Lnzh3Zv3+/jBo1SrZu3ao8Q7169cTLy0tWrFghN2/elNTUVDl8+LBMmDBBFixYkHO7HTt2CAB5//33C/X/o6A/r/L11SX7H5bt27db/NqbNm0SAHL9+nWLX1sF9wz3jKW1b99exo8fb8i1fXx8ZM6cOYZcWwX3DfeNJc2cOVMqVapkyLXZZ9wzebH3PcM+457Jxj1jPvYZ90027hvzsM+4Z7Jxz5iHfcY9k417xnz59Fnug5fhw4c/8kXWJfubunXr1pKVlfXIfzt9+rS4u7uLv79/rtsHBwfnun1wcLAAkN27d+daZ8yYMQJA5s6dm/N7Bw4ckEGDBknlypUfOckEIFWrVs25XZs2bcRkMsmxY8dyXbdLly65NkH79u0F+N8pY0HMnaFz585Sr149SU9PL/B6Rm4C1a+vDsnJyQJANm3aZPFrr127VgA8chquA/cM94yldenSRcaOHWvItb28vOSrr74y5NoquG+4byxpzpw54uPjY8i12WfcM6p/3h72DPuMeyYb94z52GfcN9m4b8zDPuOeycY9Yx72GfdMNu4Z8+XTZ+m5PuPlwYMH8PDwePy3tenevXuu94WrXbs26tevj9OnT+e6fdeuXXPd/rfffoOvry+Cg4Nz3b5Pnz45twGAXbt2ISQkBMuXL8elS5ceeQ884M/3lXv4ulWqVEFAQECu64aFheX6vZMnT6Js2bLo2rVrfn9d5RmmT5+OrKws1K1bF2PHjsXs2bNx6NChAq9vaSpfX12yv6fT0tIsfu3sa9rKvuGe4Z6xlGLFihmyZwDe13DfqLOHfePh4cE9wz0DgHvGXOwz7pls3DPmY59x32TjvjEP+4x7Jhv3jHnYZ9wz2bhnzJdfn+U6eMnKyoKLS67fthvZHwL1OHM/1GfatGl48OABpkyZgt9++w337t1DVlYWRAQNGjSw5KgWmSEwMBAnT57E4sWLUatWLezYsQNhYWEICAjA0aNHrTIvYP7XVxdXV1cAyPUPiiVkZWUBgN3uG+4Z7pn8uLq6IjMz05Br876G+6YwbH3fcM/kj3uGeyYv7LP8cc9wz+SH9zX5477hvskL90z+uGe4Z/LCPssf9wz3TH7yu6/J9Z3u7u6O9PR0qwxljg0bNkBEHvm9M2fO4Ndff0WdOnXMukbdunWRlJSEffv25fpva9euzblN9rUrVKiAqVOnok6dOihevDhMJhNOnz6NU6dO5bru77//juPHj+e6bkxMTK7f8/f3x40bN7B58+YC51WZAQDc3NzQoUMHvP3221iyZAkSExNx69YtjBw5Muc22f+oFfYfzoL+vMrXV5cHDx4A+PME0tKyT+ptZd9wz3DPWEpaWpohewbgfQ33Td7sfd88ePCAe4Z7Jgf3zJOxz7hnHsY9Yx72GffNw7hvnox9xj3zMO6ZJ2Ofcc88jHvGPPn1Wa6Dl2LFiuVsMluwb98+jBw5Er/99htSU1Oxc+dO9O/fH+np6Rg4cKBZ1xg0aBAAIDw8HGvXrsWtW7dw8eJFvP/++5g3bx6KFSuGp59+GgBQvXp1XL16FZ999hlSUlKQkpKCtWvXolevXjkns9kGDBgAEcGAAQOwZcsW3LlzB4mJiRg3blye3+gvvvgiAGDIkCGYP38+Ll68iNTUVPzyyy8YM2YMtm3bpjxDSEgI5syZgxMnTuDevXtISUlBTEwMrl+/jjNnzuTczsfHBwCwY8cOXL9+3ayv28MK+vMqX19dsl/uZeQdh63sG+4Z7hlLMfKl87yv4b7Ji73vm7S0NO4Z7hkA3DPmYp9xz2TjnjEf+4z7Jhv3jXnYZ9wz2bhnzMM+457Jxj1jvnz77PFPfRk3bpx06tTJMp8sUwTZH1w0cOBAcXV1feSDfgCIv7//Ix/GlH376dOn57pWWlqahISE5LpG9q8vvvgi57YrV67M8zbNmzeXxo0bi6+vb85t7927J82aNct1W5PJJOHh4bk+6CgzM1MGDhyY7xzZH4CkMkOxYsXyvd748eNzbpeRkSFVqlTJdRtzFfTnVb6+uly8eFEAyK5duyx+7Z9//lkAyNWrVy1+bRXcM9wzlta2bVt54403DLl2uXLl5PPPPzfk2iq4b7hvLOnTTz995MMILYl9xj2TF3vfM+wz7pls3DPmY59x32TjvjEP+4x7Jhv3jHnYZ9wz2bhnzJdPn6Xn+iq8+eab0rZtW+tMVYCHv6k3bNggrVu3Fk9PT/Hz85ORI0fm2qQFbQIRkbt378qUKVOkQYMG4uHhId7e3tK5c2dZt25drtt+++230rRpU/H09JRKlSrJ2LFjJTk5WYKCgh75BhQRuXHjhrzyyitSoUIFKV68uDRv3lxWrlwpCxYsyLUJRESysrJk3rx5EhwcLF5eXlKqVClp3bq1REZGSnp6uvIMhw8flnHjxkmjRo1yvj6hoaESGRkpmZmZj6y9e/duadeunXh5eSlvgif9eZWvrw5nzpwRAHLgwAGLX3vXrl0CQC5cuGDxa6vgnuGesbSgoCCZOHGiIdeuWrVqvt971sR9w31jSdOmTZM6deoYcm32GfdMfux5z7DPuGeycc+Yj33GfZON+8Y87DPumWzcM+Zhn3HPZOOeMV8+fZZuEnn0zeymTp2K6OhoHDt2DESO4tChQ2jRogVOnTpl8ff+O378OBo3bozjx4+jUaNGFr02kU716tXDiBEj8Pe//93i127UqBHCw8MxZcoUi1+bSJd//OMfiImJwcGDBy1+bfYZOSL2GZE69hmRGvYZkRr2GZG6fPosI9dnvPj6+iIpKcl6kxFZQfZ7BPr6+lr82tnXLMz7GBLZsqSkJEP2DPDnvuGeIUdj9J5hn5GjYZ8RqWOfEalhnxGpYZ8RqcvvvibPg5fk5GQ89kIYckCHDx+GyWR64q9+/frpHrXIkpKS4OrqitKlS1v82r6+vjCZTAwuJ+BMeyYjIwMpKSmGPUjx8/NjbDkJZ9o3169fh5+fnyHXZp85D2faM+wzsgRn2jPsM7IUZ9o37DOyBGfaM+wzsgRn2jMF9Vmugxc/Pz+kp6fj1q1bVhmOyBquX78OHx8fuLjk+pYvMnd3d3h7e/NBCjmU7AcQRj5IYWyRozHyJyrZZ+SI2GdEathnROrYZ0Rq2GdEagrqM7fHfyP7RlevXjXkdJNsR7NmzZzmJzOMjC3gz31z7do1w65PtsGZ9kz297ORD1KMeJ9lsj3OtG+MfmAPsM+cAfeM5bDPnIMz7Rn2GVmKM+0b9hlZAveM5bDPnIMz7ZmC+izX8WW1atUAAOfPnzd4LCLrOXv2LGrUqGHY9atXr849Qw7l3LlzAP53n2Bp1apV454hh3P+/HlUr17dkGuzz8gRsc+I1LDPiNSxz4jUsM+I1BTUZ7kOXsqVK4eSJUvi7Nmzhg9GZC2JiYmoWbOmYdevWbMmEhMTDbs+kbUlJibCx8fHsJ/cqlmzJq5fv86X5ZPDuHr1Ku7cuYNatWoZcn32GTki9hmRGvYZkRr2GZE69hmRmoL6LM837KtRowbvOMihJCYmGhZbwJ93HNwz5EiM3jPZ1+a+IUeR/eDByH3DPiNHwz4jUsM+I1LDPiNSxz4jUlPQnsnz4KVWrVrcBOQw0tPT8fvvvxt+x3Hu3Dmnef9Ccnxnz541fM+YTCbe15DDSExMhJubG6pWrWrYGuwzciTsMyJ17DMiNewzIjXsMyJ1BfVZngcvdevWxcmTJw0dishaTp8+jczMTNStW9ewNerVq4f79+/nvK8fkb379ddfDd0zJUqUQKVKlZCQkGDYGkTW9Ouvv6JGjRpwd3c3bA32GTkS9hmROvYZkRr2GZEa9hmRuoL6LM+DlyZNmuD48ePIzMw0dDAia4iLi4OrqysaNmxo2BpNmjSByWRCXFycYWsQWcuDBw+QkJCApk2bGrpO06ZNcfToUUPXILKWuLg4BAYGGroG+4wcCfuMSA37jEgd+4xIDfuMSM2T+izPg5fAwEDcu3cPv/32m6HDEVnD0aNHUb9+fXh6ehq2hre3N2rWrMk7DnII8fHxePDggVUe2HPPkKM4evQomjRpYuga7DNyJOwzIjXsMyJ17DMiNewzIjVP6rM8D14CAgLg5ubGTUAOIS4uzvAHKMCfwcWnSIcJAAAgAElEQVSfDiNHcPToURQrVgz169c3dJ2mTZvm3EkR2bN79+7h9OnThj+wZ5+RI2GfEalhnxGpYZ8RqWOfEal5Up/lefBSvHhx1KtXD0eOHDF0OCJriIuLMzy2gD8fpBw+fNjwdYiMFhcXB39/f0PfCxn4c888ePAA8fHxhq5DZLSjR48iMzPT8Acp7DNyJOwzIjXsMyI17DMidewzIjVP6rM8D14AoE2bNti9e7dhgxFZw6VLl3D27FkEBwcbvlabNm1w6tQpXLt2zfC1iIwUGxtrlT3TqFEjlC5dGnv27DF8LSIj7dq1C76+voZ+CGU29hk5AvYZkTr2GZEa9hmRGvYZkbon9Vm+By+hoaHYu3cvMjIyDBmMyBpiY2Ph5uaG1q1bG75WSEgITCYTH6SQXUtLS8PBgwcRGhpq+Fqurq5o3bo1YmNjDV+LyEixsbEIDQ2FyWQyfC32GTkC9hmRGvYZkTr2GZEa9hmRGnP6rMCDl9TUVL5ckuxabGwsAgMD4e3tbfhaZcqUQcOGDfkgheza/v37cf/+fbRr184q64WGhnLPkN3btWuXVZ4MA9hn5BjYZ0Rq2GdE6thnRGrYZ0RqzOmzfA9e/P394ePjw01Ads2asQXwQQrZv127dqFSpUqoVauWVdYLCQnBmTNncPnyZausR2RpiYmJuHTpEkJCQqyyHvuMHAH7jEgN+4xIDfuMSB37jEiNOX2W78GLyWRChw4dsHnzZkOGIzJacnIyDh48iA4dOlhtzY4dO2Lfvn24ffu21dYksqTNmzejY8eOVluvbdu28PDw4H0N2a1NmzbBy8sLrVq1ssp67DOyd+wzInXsMyI17DMiNewzInXm9Fm+By8A0KNHD2zevBlpaWkWHYzIGjZs2ACTyYSuXbtabc3u3bsjIyMDW7ZssdqaRJaSmpqK7du3IywszGprlixZEu3atUNMTIzV1iSypHXr1qFz584oVqyY1dZkn5E9Y58RqWGfEaljnxGpYZ8RqTG3zwo8eOnduzdSU1Oxc+dOiw5HZA0xMTEICQlB6dKlrbamn58fgoKC+CCF7NLPP/+MtLQ0dO/e3arrhoWFYf369cjKyrLqukRFlf1AwZpPhgHsM7Jv7DMiNewzIjXsMyJ17DMiNeb2WYEHL9WqVUPDhg25CcjuiAg2bNhg9dgCgJ49e2LNmjVWX5eoqGJiYtC8eXNUqlTJquuGhYUhKSkJv/zyi1XXJSqq2NhYpKSkWP2+hn1G9op9RqSOfUakhn1GpIZ9RqTO3D4r8OAFAHr16oVVq1ZZbDAia9i/fz8uX76Mnj17Wn3tnj174sKFC4iLi7P62kSFJSL46aeftOyZJk2aoHr16ryvIbuzevVq1K9fH3Xq1LH62uwzskfsMyI17DMidewzIjXsMyI1Kn32xIOXgQMH4tdff8Xhw4ctMhyRNSxbtgx16tRBs2bNrL52mzZtUKNGDURFRVl9baLC2rNnD86dO4dBgwZpWX/AgAHcM2RXRATR0dHa9gz7jOwR+4xIDfuMSA37jEgd+4xIjUqfPfHgpU2bNqhZsyaWL19ukeGIjCYiWLFiBYYMGaJlfZPJhIEDB2Lp0qVa1icqjKioKDRo0ACBgYFa1h88eDAfpJBd2b17N86dO4fw8HAt67PPyN6wz4jUsc+I1LDPiNSwz4jUqfTZEw9eHt4EImKRAYmMtGvXLq2xBfz5IOX06dM4dOiQthmIzCUi+P7777XumewHKfxJF7IXy5Ytg7+/P5o0aaJlffYZ2Rv2GZEa9hmROvYZkRr2GZEa1T574sELAISHh+PMmTPYv39/kYYjsoalS5eiYcOGaNy4sbYZWrVqhVq1amHJkiXaZiAy144dO3D+/HltL8kH/nyQMmjQID5IIbuQkZGB6OhorQ9QAPYZ2Rf2GZEa9hmRGvYZkTr2GZEa1T4z6+ClZcuWCAgIwJdfflmk4YiMdv/+fXz33XcYNmyY1jlMJhOGDh2KxYsXIz09XessRE8SGRmJli1bao0tABg+fDgSExOxZcsWrXMQPcm6detw+fJlvPDCC1rnYJ+RvWCfEaljnxGpYZ8RqWGfEalT7TOzDl4AYNSoUfjuu+9w+/btQg9HZLTo6GjcunULERERukfBqFGjkJSUhFWrVukehShfKSkpWLFiBUaNGqV7FDRs2BAhISGYP3++7lGIChQZGYkuXbqgbt26ukdhn5FdYJ8RqWGfEaljnxGpYZ8RqSlMn5l98DJs2DBkZmby/V3JpkVGRuLpp59GpUqVdI+CqlWrokePHnyQQjbtm2++gclk0vZheo8bPXo0fvjhB1y7dk33KER5unLlCtatW4eRI0fqHgUA+4zsA/uMSA37jEgN+4xIHfuMSE1h+szsg5cyZcrg2Wefxdy5cws1HJHREhISsH37dpuJLeDPBykbN27EmTNndI9ClKf58+dj8ODBKFWqlO5RAPz5wXqenp5YuHCh7lGI8hQZGYlSpUqhf//+ukcBwD4j28c+I1LHPiNSwz4jUsM+I1JXmD4z++AFAMaNG4f9+/djx44dysMRGW369OmoU6cOwsLCdI+So0+fPqhevTpmzpypexSiXDZt2oQjR45g3LhxukfJUaJECYwYMQKfffYZ39+VbE5aWho+//xzjBo1CsWKFdM9Tg72Gdky9hmRGvYZkRr2GZE69hmRmsL2mUlEROUPhIaGoly5cli5cqXSQkRGunr1KmrWrIlPPvkEL7/8su5xHjFjxgxMmjQJ58+fh6+vr+5xiHKEhYUhPT0dmzdv1j3KIy5evIjatWtjwYIFeP7553WPQ5QjMjISr7zyCs6cOYOqVavqHucR7DOyRewzInXsMyI17DMiNewzInWF7LMMpVe8AMBbb72FVatWIT4+XvWPEhnm888/h6enJ4YOHap7lFxGjhwJDw8PzJs3T/coRDmOHTuGDRs24K233tI9Si5Vq1bFgAED8NFHH0HxZwOIDCMimD59Ol544QWbe1APsM/INrHPiNSwz4jUsM+I1LHPiNQUpc+UD16eeeYZ1KlTBzNmzFBejMgIqampmD17Nl599VV4eXnpHicXb29vjBkzBrNmzcL9+/d1j0MEAPj444/RsGFD9OzZU/coeXrrrbcQFxdncz/tSc7rp59+Qnx8PN544w3do+SJfUa2hn1GpI59RqSGfUakhn1GpK4ofaZ88OLq6oqJEydi4cKFSExMVF6QyNJmzZqFtLQ0/L//9/90j5Kv119/HTdv3sScOXN0j0KEX3/9Fd9++y3+/ve/w2Qy6R4nTy1btkS3bt0wdepU3aMQQUTw7rvvom/fvmjSpInucfLEPiNbwz4jUsM+I1LDPiNSxz4jUlPUPlP+jBcASE9PR8OGDdGxY0d8+eWXyosSWcqdO3dQu3ZtjBkzBh988IHucQo0YcIELF68GGfOnEHJkiV1j0NO7LnnnsMvv/yC48ePw83NTfc4+dq/fz/atGmDtWvX2tSH/pHz+eGHHzBgwAAcPHgQzZo10z1OvthnZCvYZ0Tq2GdEathnRGrYZ0Tqithn6p/xAgDu7u6YPHkyFi1ahISEhMJcgsgiPv30Uzx48ABvvvmm7lGe6O2338b9+/cxe/Zs3aOQEzt+/DiWLVuG999/36Yf1ANAq1at0KtXL7zzzjt8L3HSJvunKQcMGGDTD+oB9hnZDvYZkRr2GZEa9hmROvYZkRpL9FmhXvECAJmZmWjcuDGaNWuGJUuWFGpxoqJISkpCvXr18MYbb2Dy5Mm6xzHLpEmTMHfuXPz2228oU6aM7nHICT377LM4ffo0Dh06BBeXQp29W9XBgwfRsmVLrFixAv3799c9Djmh7777DhEREYiLi0NAQIDucZ6IfUa6sc+I1LHPiNSwz4jUsM+I1FmgzzIKffACACtXrsSzzz6LnTt3IiQkpLCXISqUcePG4YcffkBCQgK8vb11j2OWmzdvol69eoiIiMCnn36qexxyMj///DOeeuoprF271mY/tDUvzz33HPbt24fjx4+jWLFiuschJ3L37l00bNgQXbp0wVdffaV7HLOxz0gn9hmRGvYZkRr2GZE69hmRGgv1WdEOXgCgR48eSEpKwv79++3ip3PIMZw4cQKBgYGYP38+hg0bpnscJXPmzMH48eNx9OhRNGjQQPc45CQyMzPRokULVKtWDT/99JPucZRcvHgR/v7+mDx5Mv72t7/pHoecyNSpU/Hpp58iISEBlSpV0j2OEvYZ6cA+I1LDPiNSxz4jUsM+I1JjwT4r+sFL9gaOjIzEiy++WJRLEZnNnoPFnh9gkf364osv8Nprr9ltsNjzAyyyT/b+hBL7jHRgnxGpYZ8RqWGfEaljnxGpsWCfFf3gBQBefvllrFy5EvHx8XzfPTLc8uXLER4ebtcv0d2yZQu6dOmCVatWoW/fvrrHIQeXlJSEhg0b2vVLdO/evQt/f3907twZixYt0j0OOYHBgwfj0KFDOHbsmN2+hQr7jKyJfUakhn1GpI59RqSGfUakxsJ9ZpmDl5SUFDRq1Ai9e/fGvHnzino5onylpKQgICAAPXv2xPz583WPUyTPP/88tm7dihMnTqB06dK6xyEHFhERgS1bttj999pPP/2Evn37Yv369ejevbvucciBrVmzBn369LH77zX2GVkL+4xIHfuMSA37jEgN+4xInYX7zDIHLwCwbNkyDBkyBBs3bkSXLl0scUmiXEaNGoU1a9bgxIkTKFu2rO5xiiQpKQmNGjVCeHg4Zs2apXscclDr169HWFgYVq5ciWeeeUb3OEU2cOBAHDhwAMeOHUPJkiV1j0MO6NatWwgICMBTTz3lED+9yz4ja2CfEalhnxGpYZ8RqWOfEakxoM8sd/ACAM888wzi4+Nx5MgReHp6WuqyRACArVu34qmnnsKyZcswaNAg3eNYxNdff41hw4Zhx44ddvuyT7JdqampaNy4MVq3bo1ly5bpHsciLl++jICAAAwfPhyffPKJ7nHIAY0bNw7Lly/HiRMn4Ofnp3sci2CfkZHYZ0Rq2GdE6thnRGrYZ0RqDOozyx68XLx4EY0bN8aLL76ImTNnWuqyREhJSUGzZs0QGBiIlStX6h7Honr27InTp0/j4MGD/AkxsqixY8ciOjoax48fR8WKFXWPYzFfffUVxowZgy1btqBDhw66xyEHsmHDBoSFheGbb77Bc889p3sci2GfkVHYZ0Tq2GdEathnRGrYZ0TqDOozyx68AP/74KZVq1ahT58+lrw0ObEXXngBGzduxJEjRxzqAQoA/PHHHwgMDESfPn0QGRmpexxyECtXrkT//v2xdOlShIeH6x7H4gYPHozdu3fjyJEj8PHx0T0OOYCkpCQ0bdoUoaGhWL58ue5xLI59RkZgnxGpYZ8RqWGfEaljnxGpMbDPLH/wAjj2Jifr++abbzB06FCsXr0avXv31j2OIX788Uf069fPYR+EkXVdunQJgYGB6Nevn91/iF5+sh+EhYSEIDo6Wvc45AD69euHX375xaGfLGKfkSWxz4jUsM+I1LHPiNSwz4jUGNxnxhy8ZL+srVGjRli9ejVcXFwsvQQ5idOnTyMoKMgpXn6b/bK2Q4cOoXr16rrHITuVmZmJHj164Pz58w7/8tvstx346quvMGzYMN3jkB2bPXs2xo8f7/Bvj8I+I0thnxGpYZ8RqWOfEalhnxGpsUKfGXPwAgC7d+9Gp06dMGnSJEyePNmIJcjB3b17F23btoWbmxtiY2NRvHhx3SMZKjU1FcHBwShevDh27Njh8H9fMsY//vEPTJ8+HTt37kRQUJDucQw3ceJEzJo1C7GxsWjevLnuccgO7dmzBx07dsQ//vEPTJkyRfc4hmOfUVGxzxz770vGYJ8RqWGfEalhnzn235eMYYU+M+7gBQA+//xzjB8/HqtXr0avXr2MWoYc1LBhw7B69Wrs378ftWvX1j2OVZw6dQqtW7dG3759sXjxYt3jkJ358ccf0b9/f8yfPx8jR47UPY5VZGZmonfv3jh58iQOHDgAPz8/3SORHfnjjz/QsmVLNGrUCGvXroWrq6vukayCfUZFwT5jn5Ea9hn7jNSwz9hnpI59xj4jNVbqM2MPXgDgxRdfxE8//eRUm5+K7r///S/efPNNrF27Ft27d9c9jlWtWrUK/fr1w9y5czF69Gjd45CdSEhIQOvWrTFkyBDMmTNH9zhWde3aNQQFBSEgIABr1qzhy/PJLBkZGejWrRsuXLiA/fv3o2zZsrpHsir2GRUG+4x9RmrYZ+wzUsM+Y5+ROvYZ+4zUWLHPjD94uXfvHkJDQ5GWlobY2FiUKVPGyOXIAcTExKBv375477338Pe//133OFpMnjwZ//73vxETE4POnTvrHodsXFJSEkJCQuDr64utW7eiWLFiukeyuv3796NDhw546aWXMH36dN3jkB0YO3Ysvv32W+zatQtNmzbVPY7Vsc9IFfuMfUZq2GfsM1LHPmOfkRr2GfuM1Fi5z4w/eAGAS5cuITg4GLVr18b69eudMjrJPMePH0doaCh69eqFb7/9FiaTSfdIWogIIiIisHr1auzcuRNNmjTRPRLZqPv376Nr1674/fffsWfPHlSoUEH3SNosX74cf/nLXzB9+nSMHz9e9zhkw6ZNm4ZJkyZhxYoV6Nevn+5xtGGfkbnYZ39in5G52Gf/wz4jc7HP/sQ+I3Oxz/7EPiNzaegz6xy8APwHgZ4sOzBq1aqFDRs2OH1g8AEbPQkDIzc+YKMn4RNAj2Kf0ZOwzx7FPqMnYZ/lxj6jJ2GfPYp9Rk/CPnsU+4yeRFOfWe/gBfjfS+D++te/4p///Ke1liU7kJycjM6dOyMjI4MvqX1I9kvgSpUqhc2bN6N06dK6RyIb8sYbb2D27Nl8Se1jxowZg++++w7r169HaGio7nHIhmzZsgW9e/fG2LFjMWPGDN3j2Az2GeWHfZY39hkVhH2WN/YZ5Yd9ljf2GeWHfZY39hkVRFOfZUCsbNGiReLi4iIffvihtZcmG3Xr1i1p3bq1VK9eXc6dO6d7HJtz+vRpqVy5soSGhsqdO3d0j0M2YvLkyeLq6ipLly7VPYrNSU9Pl/79+0vp0qXlwIEDuschG7Fr1y4pWbKkDBkyRDIzM3WPY3PYZ/Q49lnB2GeUF/ZZ/thnlBf2WcHYZ/Q49lnB2GeUF419lm71gxcRkS+//FJMJpN8/PHHOpYnG3L37l3p1KmTlC9fXuLj43WPY7MSEhKkQoUK0qVLF7l3757ucUizGTNmiMlkknnz5ukexWalpaVJr169pEyZMnLo0CHd45BmR44cER8fH3n66aflwYMHusexWewzysY+Mw/7jB7GPnsy9hk9jH1mHvYZZWOfmYd9Rg/T3Gd6Dl5ERD766CMxmUwye/ZsXSOQZqmpqdKjRw/x9fWVo0eP6h7H5h08eFDKlCkjvXr14p2HE5s5c6aYTCaZOXOm7lFsXmpqqnTo0EEqVqwox48f1z0OaXLkyBEpX768dO3alf92moF9RuwzNewzEmGfqWCfkQj7TBX7jNhnathnJGITfabv4EVE5IMPPuDJvZNKSUmRDh06iJ+fn/zyyy+6x7Ebe/bskbJly0qXLl34skkn9OGHH/LfTEUpKSnSrl07/lvjpPbu3Ss+Pj7y1FNP8d9MBewz58U+Kxz2mXNjn6ljnzk39lnhsM+cF/uscNhnzs1G+kzvwYuIyOeffy4uLi4yceJE3aOQlSQnJ0twcLBUqFBB4uLidI9jd44dOyaVKlWSVq1ayfXr13WPQ1YyZcoU3Sf1dis1NVW6d+8upUuXltjYWN3jkJVs27ZNSpUqJb169ZK7d+/qHsfusM+cD/usaNhnzol9VnjsM+fEPisa9pnzYZ8VDfvMOdlQn+k/eBERmT9/vri4uMhrr73GD1RzcOfPn5fGjRtLjRo15NSpU7rHsVvx8fFSpUoVad68uVy6dEn3OGSgjIwMeemll8TNzU0WL16sexy7df/+fXn66aelZMmSsm7dOt3jkMFWrlwpnp6eMnjwYL5neBGwz5wH+8wy2GfOg31mGewz58I+swz2mfNgn1kG+8x52GCfpbvABowaNQpLlizB3LlzMXDgQNy9e1f3SGSAQ4cOITg4GACwY8cO1K1bV/NE9svf3x87duzA3bt3ERwcjGPHjukeiQxw584dPP3001i8eDGWL1+OiIgI3SPZrWLFiiE6OhoDBgxA3759MW/ePN0jkUFmzpyJAQMGYOjQofjuu+/g7u6ueyS7xT5zDuwzy2GfOQf2meWwz5wH+8xy2GfOgX1mOewz52Czfab76Odhu3fvlnLlyknr1q3lypUruschC1q/fr2UKlVKunTpIjdu3NA9jsNITk6WTp06ibe3t6xdu1b3OGRBly5dkqCgIPH19ZWdO3fqHsehzJgxQ0wmk4wfP54/JeZAMjIyZPz48WIymWTKlCm6x3Eo7DPHxT4zBvvMcbHPjMM+c0zsM+OwzxwX+8wY7DPHZcN9ZhtvNfawX3/9VerWrSs1a9bkh0Y5gKysLPnPf/4jrq6uMmLECL6k2AD379+X559/Xtzd3WXWrFm6xyEL2LNnj1StWlUaNmwoZ86c0T2OQ1q8eLF4eHhI//79JSUlRfc4VETJycnSq1cvKV68uERFRekexyGxzxwL+8x47DPHwz4zHvvMsbDPjMc+cyzsM+OxzxyPjfeZ7R28iIhcu3ZNunbtKp6enrJw4ULd41Ah3b59WwYPHixubm7y8ccf6x7HoWVlZcn7778vLi4uEhERwQ8qtGNz5syRYsWKSa9evSQ5OVn3OA5t+/btUrFiRfH395cTJ07oHocK6fDhw1KnTh2pWrWq7NmzR/c4Do195hjYZ9bDPnMc7DPrYZ85BvaZ9bDPHAP7zHrYZ47DDvrMNg9eRP58SerEiRPFZDLJyy+/LGlpabpHIgUnT56UgIAAKVeunGzevFn3OE5j3bp14uPjI82aNZPTp0/rHocU3Lt3T4YPHy4mk0kmT57Mt1iwkosXL0rbtm3F29tbli9frnscUvT1119LiRIlpFOnTnyLBSthn9k39pke7DP7xT7Tg31m39hn1sc+s2/sMz3YZ/bLjvrMdg9eskVHR4u3t7c0b96cP/FiJ7788kspWbKktG7dWs6fP697HKdz5swZadasmZQuXVq++eYb3eOQGeLi4qRx48ZSpkwZWb16te5xnE5aWpq88sorAkDGjh0rqampukeiJ7h165YMGzZMTCaTvPnmm5Kenq57JKfDPrM/7DO92Gf2h32mF/vM/rDP9GOf2R/2mV7sM/tjZ32W7gIbN2DAAMTFxaFEiRJo0aIFZs6cCRHRPRblISUlBc899xxGjRqFESNGYMeOHahWrZrusZxOrVq1sHv3brz00ksYOnQoBg8ejBs3bugei/IgIpg3bx6Cg4NRsmRJHDhwAH369NE9ltPx8PDA559/jhUrViA6OhpBQUE4ePCg7rEoH/v370dQUBDWrFmDr7/+Gvfv38e9e/d0j+V02Gf2g31mG9hn9oN9ZhsyMjLg4+ODxYsXs8/swMN9tnLlSnzyySdwc3PTPZbTYZ/ZD/aZbWCf2Q+77TOdxz4q0tPT5Z133hFXV1fp06ePXLx4UfdI9JB169ZJ1apVpUqVKnxppA1Zt26dVKxYUWrUqCGbNm3SPQ495Ny5c9KjRw9xc3OT9957TzIyMnSPRCJy4cIF6dy5s3h4eMiHH37IDzS0IWlpaTJlyhRxc3OTHj16yOXLl0VEpFOnTlK1alX+G6cJ+8y2sc9sE/vMdrHPbMOGDRukSpUq0q1bNxFhn9my/PqM9GKf2Tb2mW1in9kuO+4z23+rscft2LFD6tatK6VLl5bZs2fb8vu4OYWrV6/K888/LwAkPDxckpKSdI9Ej7l69ao8++yzYjKZZNiwYXL9+nXdIzm1zMxMmTlzppQsWVL8/f1l9+7dukeix2RmZspHH30knp6eEhgYKPv27dM9ktOLjY2VRo0aiZeXl8ycOVOysrJy/tusWbMEgJhMJhk7dqzcunVL46TOi31mW9hnto99ZlvYZ7YhJSVFRo4cKSaTSQDIF198kfPf2Ge2p6A+I9vAPrMt7DPbxz6zLQ7QZ/Z38CIicvfuXZk4caK4ublJu3bt5Pjx47pHcjpZWVmyaNEi8fPzk2rVqtnD++o5vRUrVkilSpWkQoUKsmTJEt3jOKUjR45ImzZtxN3dXf7v//5P7t+/r3skKsCpU6ekc+fO4urqKm+88Ybcvn1b90hO5+bNmzJu3DhxcXGRHj16yJkzZ3Ld5uLFizlP0Li7u0vlypVlw4YNGqYl9pl+7DP7wz7Tj31mG2JiYqRixYri7u6e8wMVeb16gn2mnzl9RraDfaYf+8z+sM/0c5A+s8+Dl2wHDx6UoKAgcXd3l9dee02Sk5N1j+QU9u3bJ23bthUXFxd59dVX5fXXX5e4uDjdY9ETxMfHy8SJE2X06NFiMpmkQ4cOcvDgQd1jOYVr167Jyy+/LK6urhIcHCxHjx7VPRKZKSsrSyIjI6Vs2bJSqVIlWbhwIX9SzAoyMzNl3rx5Ur58efHz85PFixcXePugoKCcwxcXFxcBIAMGDGAXaMI+0+PxPuOrv+zHjRs32GcasM9sQ0pKiowaNUpMJlPOfbjJZJLg4OB8/wz7TA/VPiPbwj7Tg8+f2Sc+f6aPg/WZfR+8iIhkZGTI3Llzc+78Z8+eLenp6brHcki///67vPjii+Li4iLt27eXX375RUREPv30U/Hy8pKlS5dqnpDy8+2330qJEiXkv//9r4iI7N27V4KDg8XFxUVGjx4tf/zxh+YJHdODBw9kxowZOQ8KFyxYwAeFduratWvy0ksviaurq7Rq1Up27dqleySHtW3bNmnevLm4u7vL+PHjzXpQ+O9//zvnJ2Szf7m7u4ufn5+sWrXKCmIF1UQAACAASURBVFPT49hn1pNfn5H9YZ9ZB/vMdjz+KpfsX25ubjJ9+vQn/nn2mfUUps/I9rDPrIfPn9kvPn+mh4P2mf0fvGS7ffu2TJkyRYoVKya1atWSuXPn2tOH7di0pKQkmTJlinh7e0vVqlVl0aJFj7x/6759+3Ii+fXXX+cdtw158OCBjB8/Puf/z8Mn9FlZWRIVFSU1atQQLy8vmThxIt+/0kIyMzMlKipK6tWrl/PgJCUlRfdYZAHx8fESFhYmAKRr1658gtOC4uLiZNCgQWIymaRLly5KPwl25syZR56wyf718Ktf+O+bHuwz4zypz8g+sc+Mwz6zHTdv3sz1KpfHf6m8fRX7zDhF6TOyXewz4/D5M/vF58/0cPA+c5yDl2ynTp2SiIgIcXV1lYCAAImOjuaD0EJKTk6WSZMmibe3t5QvX14++eQTuXv3bq7bpaeni6enpwAQV1dXCQkJyfP9eMm6Ll26JG3bthU3NzcBIF5eXnnG1J07d2TatGni6+srpUuXlqlTpzrSP3JWlZmZKUuWLBF/f39xc3OT4cOHS2Jiou6xyACrV6+WFi1aiMlkkkGDBvG9kovgyJEj0q9fPzGZTNK6dWuJiYkp1HUaNWqU5xM3D7/65ccff7Tw9GQu9pnlmNtnZN/YZ5bDPrMt69aty/NVLg//atq0aaGuzT6zHEv1Gdk29pnl8Pkz+8bnz6zPSfrM8Q5essXHx+fcgdStW1dmzJjBB6VmunTpkkyZMkXKlCkjPj4+MmXKlCf+Q9KpU6dHPty4XLlyEhsba6WJ6XE7duwQPz+/Rz6cslu3bgX+mdu3b8u0adOkbNmy4u3tLePHj5dz585ZaWL7dv/+fVm0aJE0bNhQXFxcZNCgQZKQkKB7LLKCjRs3SvPmzcXFxUX69OkjGzdu1D2S3dixY4f06dNHTCaTNG7cWKKioor0QO/dd98VDw+PfJ/Eyf6J2mHDhsnNmzct+Dchc02bNk2io6PZZ4VUmD4j+8c+K7y8+mzp0qUyceJE3aM5peTkZBk6dOgj98n5/bDEhx9+WKS12GeFZ+k+I/vA588Kj8+f2T8+f2ZdTvb8meMevGQ7duyYDB8+XIoVKyYVKlSQDz74QK5evap7LJu0f/9+ee6558TNzU2qVasmH3/8sdkP6KdOnfrIE16urq7i4uIi06ZNM3hqetzcuXPFzc1NXF1dc/5/eHh4mP0A5saNG/Kvf/1LKleuLO7u7hIREcEPEcvHlStX5N1335Xy5ctL8eLFZfTo0RIfH697LLKyzMxMWbFihYSEhAgAadOmjURFRcmDBw90j2Zz0tLSZMmSJRIUFCQApEOHDrJq1SqLPKA/evRovk/iPP7rgw8+sMDfhsyVlZUlr732mgDIOfRin5mvKH1GjoN9Zr6C+iwpKUkAyIQJE/hkspVNnTrV7PtpS/Q0+8x8RvYZ2Rf2mfn4/Jlj4PNn1uOkz585/sFLtj/++EOmTJkivr6+4uHhIX369JGoqCinfx/LlJQUmTt3rrRo0UIASGBgoCxatEg5SDdv3pxnNJtMJvnLX/4id+7cMehvQNnu3r0rEREROT858fiv7du3K10vLS1NoqKipFWrVgJAGjVqJNOmTXP697HMzMyUjRs3yqBBg8Td3V1Kly4t48ePl4sXL+oejWzAgQMHJCIiQtzc3KRChQoyfvx4OXr0qO6xtEtISJCJEydK+fLlc3761IgPwK1Vq1a+T+K4ubmJp6enLFmyxOLrUv4yMjJkxIgRAkB8fHxy/Xf2Wd4s1WfkeNhneVPpM29vbwEgERERfG99K1uxYoV4eXkV+DZj9erVs/i67LO8WavPyP6wz/LG588cB58/sw4+f+ZEBy/Z7t69K4sWLZJ27doJAKlZs6ZMnjxZjh07pns0q0lLS5M1a9ZIRESEeHp6ipeXlwwbNqxIL21MTU3NeS/EvJ7s8vf3l99++82Cfwt62KlTp3LeFzG/l+zfu3ev0Nffvn27DB06NOf75cUXX5R169Y51RNAcXFxMmnSJKlevbqYTCbp2LGjfP3110X6upLjOnfunEyZMkWqVauW8/0yf/58SUpK0j2a1Vy7dk3mzJkj7du3z7m/fe+99+TChQuGrfn222/n+XZjbm5uUr9+fae6r7cF9+/fl379+uX8BFmbNm3yvS37zJg+I8fGPitcn2U/Yebi4iLPPvuspKWlWXFiSkhIkIYNGz7y08UP/5Tx5MmTDVubfaanz8h+sc/4/Jkj4vNnxuPzZzmc7+DlYfHx8fLWW29JlSpVBIAEBATIe++955Afwnf//n2JiYmRESNGSNmyZcVkMknbtm3liy++sNjbVWQ/iMnvzqNEiRLy/fffW2Qt+p/Vq1dLyZIlC/zJsYKe7FJx48YN+eyzz6RNmzZiMpnE19dXRo8eLRs3bnTIO5GjR4/KlClTpGHDhgJAqlWrJn/7298c+f0nycIyMjJkzZo1MnDgQPH09BR3d3cJCwuTBQsWOOSD/KtXr0pkZKR0794959/98PBwiYmJkczMTMPX37dvX773QYcOHTJ8ffqfO3fuSNeuXXOeWHNzc5MRI0aY9WfZZ5btM3J87DO1Psv+HIPsf5s6duwot2/fNnhqetjBgwdznvB6/KeNDx8+bPj67DPr9hk5BvYZnz9zBHz+zDh8/ixPzn3wki0zM1N27Ngh48ePl0qVKgkAqVixokREREhUVJTdfghvYmKizJ07VwYNGiSlS5fOebnblClT5NSpUxZfb8KECU/8YGOTySSTJ09m4FlARkaGTJo0SUwmU4EfUOnh4SFvv/22xdc/d+6czJgxQ0JDQ8VkMkmJEiWka9euMmPGDDl79qzF17OG1NT/z96dx0VV738cfw8DmuSCgqVZuWXuZpgbuGTmklYu2S2jTMukq1Zaee3Xtc3s2s20TMqUNDVFBDVzxSU1A0XBFcRw18olF9RwA2bm90dXblyXBIf5zgyv5+PBH86M57xdZr7nvD8zZ846li9f7nj55ZcdlStXdkhyBAUFOfr16+f48ccfuc4xbsi5c+cc8+fPdzzzzDMOf39/h4+Pj6NRo0aOoUOHOpYvX+6Rlzux2WyO5ORkx4cffuh48MEHHb6+vo6bbrrJ8fDDDzumTp3qOHPmjEvz2O12R4UKFXJPWG666SbH119/7QgJCXHUq1fPcfbsWZfmKaoyMjIcTZo0yfMusmLFijlGjhyZr+1wfAbkH8dnf2348OGO4sWL5ym4goODvbJwd0eZmZmOOnXqOJo2beqYOHGio3jx4rnrxe233+7yPByfAfnD8Zlz0J+5Fv2Z89GfXZdsi8PhcAi5bDabNmzYoCVLliguLk4bN26U1WpVo0aNFBISohYtWigkJES33nqr6ah52O12paWlKSEhIfdn7969KlmypNq2bauOHTvqoYceUuXKlQstw/z589W1a1dd67+Uj4+PKlSooCVLlqhBgwaFlqUo2Lx5szp16qTffvtNdrv9mo9duHChOnfuXGhZ9u3bl/ucWblypc6ePau77rpLoaGhuT+1a9eWxWIptAwFceTIESUkJCg+Pl5r167Vpk2bZLfb1bhx49znTOPGjeXj42M6KrzMmTNntGLFCsXFxSkuLk4///yzypYtq5CQEIWGhqpFixa67777VKJECdNR8zh37pySkpJynzNr167VqVOnVLlyZXXs2FEdO3bUgw8+qJIlSxrLOGjQII0dO1Y1atTQvHnzVKdOHf3888+699571aVLF02aNMlYtqLg6NGjatu2rXbu3Kns7Ozc2y0Wi2bPnq3u3bsXaLscnwH5x/HZlc2aNUs9e/bMc87i5+enqlWratWqVbrtttuc9UfBFfTu3VsLFizQpk2bVLlyZaWkpKhbt27as2ePXn/9dY0aNcpYNo7PgPzh+Kzg6M9ci/7sxtGfFUgOg5e/8Ntvv+n777/P/c+Vmpoqm82mypUrq379+qpXr57uuece1a1bV9WrV5e/v3+hZzp69Kh27dqllJQUbdu2TSkpKUpNTdXp06dVqlQpNWvWTKGhoWrVqpVCQ0NVrFixQs8kSSdPnlRQUNAVFw6r1Sq73a6+ffvq448/VunSpV2SydudOXNGw4YNU0REhKxWq3Jyci57jMVi0cmTJxUQEOCSTBcvXlR8fLzWrFmjhIQErV+/XpmZmQoICMjznKlXr55q1KihW265pdAznT17Vnv27FFqamru8yY1NVUHDx6U1WpV/fr11aJFC7Vo0UJt27ZVUFBQoWcC/iw1NVUrV67U2rVrFR8fr19//VV+fn6qXbu26tevr/r166tBgwaqXbu2br/9dvn6+hZqnpycHP38889KS0vLs9akp6crOztbd9xxR+6JVNu2bVW7du1CzZMfa9asUWRkpMaPH5+nYFi0aJEeeeQRTZ48Wb179zYX0IsdOHBA999/v3799dc8Q5dLUlJSVK9ePafsi+MzIH84PvuvzZs3Kzg4+LLb/fz8VKFCBa1evVrVqlVzyr6QV2RkpMLDwzVv3jw9+uijubdnZmaqX79+evnll9WsWTODCfPi+AzIH47Prh/9mevRn10f+jOnYvCSX2fOnNG6deu0efPmyw50JOmWW25R1apVVbVqVd12220KDAxUUFCQgoKCFBgYmFsC3XzzzXle0DMzM5WdnS2Hw6ETJ07k+Tl+/LgOHDigffv2ad++fTp37pwkqUyZMrkHfPfcc4+aNGmiBg0ayGq1uv4v5j9q1Kih3bt357nNYrGoUqVKmjZtmtq0aWMomXdLSEhQWFiYDhw4cNl9tWvXVlpamoFUf8jJydHWrVuVlJSkrVu3KiUlRSkpKTpz5oykP54Ll54zlStXVmBgYO7zJjAwUOXKlZPFYpGfn1+eEjUrK0tnz56V9Mfz59Jz5dLPoUOHcp8zx44dk/THCXWtWrVyT5KCg4PVrFkzlSpVyvV/McA1HDhwQGvXrs3znPn5558lSb6+vrrjjjtynzMVK1bMfd5c+rm0vpQtWzZ3mw6HQ6dOnZL0xwHeyZMnc583J06c0OHDh3PXml9++SX3QPTOO+/MXWsaNmyokJAQ3XHHHS7+G7l+Dofjqu8OGjp0qD777DOtW7dODRs2dHEy7/bTTz/p/vvv18mTJ684dLFYLDp79myhvUuY4zMgf4ry8VlmZqZKly59xbLLz89PAQEBWrlypdMGxfhDSkqKmjVrpsGDB2vEiBFXfMy11nB3wPEZkD8cn10b/ZkZ9GfueXzmpRi8OENWVpZ27tyZ+5/00s+RI0d04sQJHTt2TKdPn87XNn19ffMcpFWuXFlVqlRR1apVVaVKFVWvXt0tL0vx4osvavLkycrOzpavr68cDocCAgJ03333KS4uznQ8r9ahQwdt3rxZGRkZkv54wfbz81N4eLjGjRtnON3l9u/frz179mj//v3at2+f9u/fr4MHD+Y5aLrSOxCuJSAgQOXLl1dgYKAqVKiQ+3ypWrWqqlWrpho1avAOY3isjIwMpaen5z5f9u3bp4MHD+ro0aO5z5lLJxbXy9/fP3edqVChgu688848z5uaNWu67N0+rpCTk6MHHnhAR44cUXJyMu8ec5KNGzeqXbt2+v3336/6ul2hQgUdPnzYpbk4PgPyr6gcnwUFBenEiRNXvM/X11f+/v5atmyZmjZt6tJc3iozM1ONGzfWrbfeqhUrVhT6J0NcieMzIH84Pvsv+jNz6M/c8/jMCzF4cZWcnBydOnUqd0p59uxZZWVl5d5fsmRJ+fn5yWq1qmzZsh5bBk2fPl29evWSxWJRcHCwpkyZohMnTuj+++/XjBkz1LNnT9MRvdK0adPUp08f/fDDDypTpox69+6tLVu2yOFwKCoqSk8++aTpiAVy+vRpnTp1SjabTdnZ2crMzMy9r1ixYrr55pslSaVLl1bZsmV5NzGKvPPnzysjI0MXLlyQpNwDSemPd09dOkkvUaKEAgIC3O4a5a5w5MgR3XvvvWrdurWio6NNx/F4q1evVufOnZWVlXXNg/3WrVtr9erVrgt2nYrK8RngTN5wfBYaGqq1a9de9X6r1aqbbrpJS5YsUcuWLV2YzDs9/fTTWr58uTZv3lwkv0OH4zMgf4rK8Rn9mRn0Z+57fOaFGLzAuQ4cOKC6detq5MiRGjBgQO6XKr344ouaM2eO0tLSVL58ecMpvcvx48dVp04dPfHEE7mTeZvNpnHjxumf//yndu7cqUqVKhlOCQDuY+XKlWrfvr0+//xzhYeHm47jsRwOh8LDw/XVV1/J19f3ipcYk/74mHrfvn31xRdfuDghAFxZv379NGXKlGu+btlsNvXr109ffPGFW1/+yt1FRETolVdeUVxcnNq1a2c6DgC4Dfoz16M/g4sxeIHzHTp06LJ3Mp05c0Z169ZV27ZtNWXKFDPBvFRYWJhWr16ttLQ0lSlTJs99V/q3AABIb7/9tj766COtXbv2il+yjOu3Y8cOvfXWW5o7d+4Vv6jSz89PH330kQYNGmQoIQDkNWrUKA0bNizPO6ilPy5Xc+mylGPGjNE999xjKKF3SE5OVosWLfTmm2/q7bffNh0HANwO/Zlr0Z/BxRi8wHUWLlyoRx55REuXLlX79u1Nx/EKcXFxeuihhzRv3jx16dLFdBwA8Bh2u10dO3bU3r17tXHjxssOvJF/GzZsULdu3XTo0KHc8vKShQsXqnPnzgbTAcB/zZs3T926dcv99aXXrAoVKmj+/Plq3LixwXTe4dSpU2rUqJEqV66s5cuXc0kTAMgH+jPnoz+DATk+phOg6Hj44Yf12GOPKTw8PM+1BlEw586d04ABA/Tkk0+yaABAPvn4+Oibb77R+fPn1atXL/E+lBvn7++vI0eO6K233lLDhg0lKfeSCTVq1DAZDQDyuPvuuyUp9xJiDRs21D//+U8dO3Ys9xroKDiHw6Hnn39e586dU1RUFEMXAMgn+jPnoj+DKQxe4FIRERE6ffq03nvvPdNRPN6bb76pU6dO6dNPPzUdBQA80q233qqoqCgtWrQo9xq/KLhhw4apXr16evfdd5WUlKR58+bp7rvvlq+vr6pWrWo6HgDkql69uqxWq2rVqqX58+crKSlJw4cPV7169fTOO++YjufxxowZo/nz5ysmJkYVKlQwHQcAPBL9mfPQn8EULjUGl5s4caL69++vxMRE3XfffabjeKQNGzYoJCREkZGR6tOnj+k4AODRRowYoeHDh2v16tUKCQkxHccjJSUlqWnTplq4cKE6deqUe7vdbldcXFye2wDAHSxevFgdO3bM/WSeJH333Xfq1q2bEhMT1aRJE4PpPNf69evVqlUrDR8+XEOHDjUdBwA8Gv3ZjaM/g0F8xwtcz+FwqF27djp27JiSk5Pl5+dnOpJHycnJUePGjRUQEKCVK1fmXiIBAFAwdrtdnTt31vbt27V582YFBgaajuRxHnzwQV24cEHx8fGmowDADQkJCVGZMmW0ZMkS01E8TkZGhoKDg1WnTh0tXLiQ8xQAuEH0ZzeG/gyG8R0vcD2LxaLx48dr165dGj16tOk4HmfkyJFKT09XZGQkiwYAOIGPj49mzJghHx8fPfvss3zfSz6tWbNG33//vUaMGGE6CgDcsA8//FBxcXFavXq16SgexeFwqE+fPrLZbJo6dSrnKQDgBPRnN4b+DKbxiRcY869//UvDhw/Xli1bVKtWLdNxPMLOnTt1zz33aPjw4RoyZIjpOADgVRITE9W6dWuNGDGC19h8CAkJUUBAgBYvXmw6CgA4Rbt27XT+/Hk+xZcP//rXv/Tuu+9q1apVCg0NNR0HALwK/Vn+0Z/BDXCpMZiTk5OjJk2aqHTp0lq1ahXT579gt9t1//3368yZM0pKSuIjpgBQCEaNGqU333xTK1euVMuWLU3HcXvz5s1T9+7d+T4EAF4lOTlZTZo00YIFC9S5c2fTcdzeDz/8oAcffFCjRo3SoEGDTMcBAK9Df5Y/9GdwEwxeYFZSUpKaN2+uL7/8Un379jUdx62NHz9eL7/8shITE9WoUSPTcQDAKzkcDnXv3l3JycnatGmTypcvbzqS27Lb7QoODtbdd9+tmJgY03EAwKm6deumPXv2aMuWLfLx4QrdV/Pbb7/p3nvvVaNGjfTdd99RBgJAIaE/u370Z3ATDF5g3muvvaZJkyZp+/btqlSpkuk4bunw4cOqU6eOwsPD9eGHH5qOAwBeLSMjQ40aNVK1atW0dOlSWa1W05Hc0vTp09W7d2+lpKSodu3apuMAgFNt375dDRo0UFRUlJ544gnTcdyS3W7XQw89pPT0dG3atEnlypUzHQkAvBr92V+jP4MbYfAC886dO6cGDRro3nvvVWxsrOk4bqlbt27aunWrUlJSdPPNN5uOAwBeLykpSS1bttSwYcM0bNgw03HcTnZ2tmrXrq1WrVpp8uTJpuMAQKF45plntH79eqWlpcnX19d0HLfz7rvv6sMPP1RCQgLvKAYAF6A/+2v0Z3AjOXxmGsb5+/tr4sSJmjNnjr799lvTcdxObGysvvvuO02cOJFFAwBcpHHjxvroo4/0zjvvaPny5abjuJ1Jkybp559/ZigFwKu9//77OnDggKZOnWo6ittZtWqVRowYoU8++YShCwC4CP3ZtdGfwd3wiRe4jWeffVbLly9XWlqaAgICTMdxC6dPn1bdunXVsWNHffXVV6bjAECRExYWpu+//16bNm3SbbfdZjqOW7hw4YJq1Kihbt266bPPPjMdBwAK1d///nctWLBAu3btUokSJUzHcQtHjx5Vw4YN1apVK82aNct0HAAocujPLkd/BjfEJ17gPsaMGSObzab/+7//Mx3Fbbz22muy2WwaNWqU6SgAUCR9+eWXCggIUFhYmGw2m+k4biEiIkIZGRl68803TUcBgEL39ttvKyMjQxMnTjQdxS3YbDaFhYWpVKlSioyMNB0HAIok+rPL0Z/BHTF4gdsIDAzUJ598ogkTJujHH380Hce4H374QZMnT9Znn32msmXLmo4DAEVSqVKlFBMTo/Xr1+u9994zHce4zMxMjRo1Sq+88ooqVKhgOg4AFLqKFStqwIABGjFihH7//XfTcYwbNmyYEhISNGvWLJUuXdp0HAAokujP8qI/g7viUmNwO126dNFPP/2krVu36qabbjIdx4iLFy+qYcOGql69uhYuXGg6DgAUeRMmTFD//v21ePFidejQwXQcY959912NHTtWe/bsUbly5UzHAQCXOHHihKpVq6YhQ4YU6e+2WrJkiR5++GFFRkbqueeeMx0HAIo8+jP6M7g1LjUG9zNu3DgdPnxY//rXv0xHMebdd9/VoUOH9OWXX5qOAgCQFB4errCwMD311FM6cOCA6ThGHD9+XJ988omGDBnC0AVAkRIYGKhXX31VH3/8sU6ePGk6jhE///yzevXqpSeeeIKhCwC4Cfoz+jO4Nz7xArf02Wef6bXXXlNSUpIaNmxoOo5Lbdu2Tffdd5/Gjh2rv//976bjAAD+4+zZs2rSpIlKly6tNWvWyM/Pz3Qkl3r99dc1bdo07dmzR6VKlTIdBwBcKjMzU9WrV9dzzz2nkSNHmo7jUtnZ2WrTpo1OnTql9evX6+abbzYdCQDwH/Rn9GdwWzkMXuCW7Ha7WrZsqZycHK1du1ZWq9V0JJew2Wxq1qyZfH19lZCQIB8fPpQGAO5k+/btatKkiQYOHKh///vfpuO4zKFDh1SjRg2NHDlSL7/8suk4AGDE6NGj9dZbb2nXrl2qVKmS6Tgu8+qrr2rixInasGGD6tSpYzoOAOBP6M/oz+C2uNQY3JOPj48mTZqkrVu3KiIiwnQcl/nkk0+0bds2TZo0iUUDANxQ3bp1FRkZqVGjRmnevHmm47jM8OHDVb58eYWHh5uOAgDGDBgwQEFBQfrwww9NR3GZhQsX6tNPP9UXX3zB0AUA3BD9Gf0Z3BefeIFbe/vttzV69GilpKSoWrVqpuMUqv3796t+/foaMmSI3n77bdNxAADX8Nxzz2nevHnauHGjqlatajpOodq3b59q1aqlL7/8Un369DEdBwCMmjhxogYOHKiffvrJ689PDhw4oODgYPXo0UMTJkwwHQcAcA30Z4Db4VJjcG8XL15UcHCw7rzzTi1ZssR0nELVoUMHHTx4UFu2bFHx4sVNxwEAXMOFCxfUvHlz+fn5KT4+XsWKFTMdqdCEhYUpOTlZ27dvl6+vr+k4AGCUzWZT3bp11axZM02ZMsV0nEJz8eJFhYaGKisrS+vXr1eJEiVMRwIAXAP9GeB2uNQY3Fvx4sU1adIkLVu2TDNmzDAdp9BMmTJFK1as0FdffcWiAQAe4KabblJMTIzS09P1j3/8w3ScQpOamqro6GiNGDGCoQsASLJarXr77bc1ffp0paWlmY5TaF599VWlp6crJiaGoQsAeAD6M8D98IkXeIT+/fsrJiZGaWlpuuWWW0zHcarjx4+rTp066tmzp8aOHWs6DgAgH2JiYvTkk08qNjZWjz32mOk4TtelSxft379fmzdv5trJAPAfdrtdjRo1UvXq1TV79mzTcZwuJiZ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NRwEAAAAAAG6E/gzugv7Mvhi82Mz69eslScHBwYaTANcmODhYTqdTGzZsMB0FAAAAAAC4EfozuAv6M/ti8GIzmzZtUv369eXn52c6CnBN6tatK39/f6WmppqOAgAAAAAA3Aj9GdwF/Zl9MXixmdTUVLVp08Z0DMAlWrduzYEDAAAAAAC4FP0Z3An9mT0xeLGZjRs3KigoyHQMwCWCgoK0adMm0zEAAAAAAIAboT+DO6E/sycGLzbidDq1c+dOBQYGmo4CuERgYKC2bdtmOgYAAAAAAHAT9GdwN/Rn9sTgxUYyMjJ0/vx5NW7c2HQUwCUaN26sEydO6MiRI6ajAAAAAAAAN0B/BndDf2ZPDF5sJC0tTZLUqFEjw0kA17jw33J6errZIAAAAAAAwC3Qn8Hd0J/ZE4MXG0lPT5ePj4/q1KljOgrgEg0aNJCnp2f+L0UAAAAAAADXgv4M7ob+zJ4YvNjI3r171bBhQ3l48NcG9+Dj46O6dety4AAAAAAAAC5BfwZ3Q39mT6xANnLgwAHVrVvXdAwlJCTI4XDogw8+MB2lWCZPniyHw6FZs2aZjgJJdevW1cGDB03HAIBSkZOTo+bNm+vhhx8ucP/evXv10UcfqVevXqpQoYIcDocSEhJc+t6JiYnq2bOnqlWrpipVqui2227TokWLLrmdw+HQwoULXfr+AOBuLremS4Vfc4uLNR0ALo/+zDXoz8oW+jP7YfBiI0eOHJGfn5/pGHCxC/8YevPNN4083zQ/Pz++HAxAuTFhwgSlpaXp1VdfLXD/rbfeqmeeeUaLFi1Sdna2y9934cKFuv3227VkyRKdOHFCp06d0sqVKxUeHq7Y2NgC24aGhqpnz5568cUX5XQ6XZ4FANzF5db0oqy5xcGaDgBXRn/mnujP6M/shsGLjRw5ckT+/v6mYwAu5e/vz4EDQLmQnZ2tt956S/3791fTpk0LPBYQEKARI0YoISFBQ4cOdfn7Dhs2THl5efrrX/+qw4cP69ixY3rjjTdkWZaGDx+uU6dOFXjOCy+8oNTUVJcUhADgji63phdnzS3q+7KmA8CV0Z/BHdGf2Q+DFxvJzMxkYg+34+fnp8zMTNMxAKDEzZkzR4cOHbrkJWm+//77/EuN+fj4uPR9lyxZor1796pbt25699135e/vr+rVq+vll1/WPffco8zMTM2bN6/Ac3r06KE6dero008/dWkWAHAXl1vTi7PmFgVrOgBcHf0Z3BH9mf0weLGR48ePq0aNGqZjFLB06VJ16dJF1113na6//noNHTpUhw8fLrDN769puWLFCt12222qUqWKgoODJUlnz57VP//5T7Vs2VIVK1ZUtWrV1KNHj0teh3jlypUaPHiwmjZtqgoVKqhWrVqKiIhQUlLSRdseP35cTz/9tOrUqSNfX18FBwfrm2++ueyfxbIsTZ48Wd26dVP16tVVpUoV3XLLLZo0aZJyc3OLnCEvL0/jx49Xhw4dVKNGDVWvXl3BwcF67733dObMGUnSm2++qa5du0qSXnnlFTkcjvxbYRTm+UXZvybUrFlTx44dMx0DAEpcVFSUfH19FR4eXqrvu3LlSknS4MGDL3rswQcflCStWLGiwP2enp7q16+fvvvuO+3bt6/kQwKAzVxuTS/OmlsUrOkAcHX0Z/Rnf0R/BiMs2MYNN9xgffjhh6ZjWPHx8ZYkKzIy0vL09LQkFbi1aNHCOnny5CW39/Lyyt+uffv21vnz562QkJCLXkOS5XA4rAkTJuS/zoEDBy65nSTLy8vLWrFiRf62Z8+etdq1a3fJ1xw0aJAlyYqNjc3f3ul05t9/qdvixYuLnOHFF1+87Lbjx4+3LMuy3njjjctuUxhXe35R9q8p//nPf6yGDRuajgEAhTZjxgzL4XAU6Tk5OTlW5cqVrZCQkKtuO2LECEuSFR8fX9yIBdx7772WJCspKemix3bv3m1Jsrp3737RY5MnT7YkWV9++WWR3q84+wcATMnLy7vo3wZXc6U1vbhrbmGV9ppenP0DAKbRn9Gf/RH9GQzI4YwXG8nOznb55UeuRWxsrB566CHt2rUr/wsd27Rpo+3bt2vMmDGX3P7hhx/Wjh07lJubq/Xr1+ujjz5SUlKSGjRooLi4OGVlZWnfvn0aPXq0HA6HnnvuOR08eFCS5HA41LNnT8XFxWn//v3Kzs7Wr7/+qpiYGFWoUEHvvPNO/nuNHz9eGzZs0E033aQlS5bo5MmT2rNnj5566inNnDnzomxffPGFZs6cKT8/P3366afat2+fTp06pXXr1unxxx+Xt7d3kTPMnTtXlSpV0uzZs3X8+HGdPn1aGzZs0AsvvKDKlStLkl5++WWtWrVKkvKvy3zhVhhXe35R9q8pPj4+On/+vNEMAFDStm7dqlOnTqlt27al/t4nTpyQ9NsnpP7own1ZWVkXPdauXTtJ0po1a0owHQDYz5XW9OKuuYXFmg4AV0d/Rn/2R/RnMMHLdAAU3vnz58vUgaNjx4764osv8k/L69q1q+bOnasWLVpo1qxZeuONNwps36lTJ3322WcFTuO78AWPM2fOVKdOnSRJVatW1WuvvaaMjAxNnDhR8+fP1xNPPKHatWvrX//6l8aMGaNhw4bp0KFDBU5hTE1Nzf/fs2fPlsPh0OzZs9WqVStJUuXKlfXxxx9rx44dWrp0aYFsX331lSQpOjpaYWFh+fcHBwfnn9IpqUgZ6tevL0nq27evvLx++79a27ZtS7V0K8r+NaVChQrKzs429v4AUBoOHDggSUa+5PNK/xi50mO1atWS9H/ZAQC/udKaXtw1t7BY0wHg6ujP6M+Kiv4MJYEzXmykrE3s77zzzouupdi4cWM1b95cP/3000Xbh4WFXbT97t275efnl7+o/d5dd92Vv40krV69Wl26dFFsbKwyMjIKLNjSb9di/P3r1qtXL/+g8XuXurb+9u3bVaNGjQIHjUspSob3339fTqdTTZs21bBhw/TJJ58oJSXliq/vakXZv6YwsQdQHhw/flySVKVKlVJ/72rVqkmSjh49etFjF64RfGGb36tataqk/8sOAPjNldb04q65hcWaDgBXR39Gf1ZU9GcoCQxebMTpdMrDw75/ZX5+fpe8v7BfhPXOO+8oOztbr732mnbv3q2zZ8/K6XTKsizddNNNrozqkgxt27bV9u3bFRUVpUaNGmnVqlUKDw9Xq1atCkz2S1ph968pnp6eysvLMx0DAEpU9erVJf3fJWJKU9OmTSVJmzdvvuixTZs2Fdjm9y5cqqasfTEpAJh2pTW9uGtuYbGmA8DV0Z/RnxUH/Rlczb6rUDnk7e2tnJwc0zHyLVq06KLT2ffs2aOdO3eqSZMmhXqNpk2bKjMzUz/88MNFjy1YsCB/mwuvXbt2bY0ePVpNmjRRxYoV5XA49NNPP2nXrl0Xve4vv/yiLVu2XPS6CQkJF93XokULHTt27KJTKP+oKBkkycvLS926ddOoUaM0Y8YMpaWl6cSJExoyZEj+Nhd+Gfjj9L+wrvT8ouxfU86fP68KFSoYzQAAJa1OnTqSpMzMzFJ/727dukmSpk2bdtFjU6dOLbDN713IeiE7AOA3V1rTi7vmFhZrOgBcHf0Z/dml0J+htDF4sZGydi2/H374QUOGDNHu3bt1+vRpJSYm6u6771ZOTo4GDBhQqNeIjIyUJA0aNEgLFizQiRMn9PPPP+uNN97QxIkTVaFCBfXt21eS1KBBAx06dEgfffSRsrKylJWVpQULFqhPnz5yOp0FXvfee++VZVm69957tWzZMp06dUppaWkaMWLEJQ8Of/7znyVJ999/vyZNmqSff/5Zp0+f1o8//qgnnnhCK1asKHKGLl266NNPP9XWrVt19uxZZWVlKSEhQUeOHNGePXvyt7vwJZirVq3SkSNHCrXffu9Kzy/K/jUlOzubAwcAtxcYGKjKlStrw4YNpf7eYWFhatCggVauXKnnn39emZmZysrK0ptvvqk5c+bI399f/fv3v+h5F7Je6nR7ACjPrrSmF3fNLSzWdAC4Ovoz+rNLoT9DqbNgG7Vq1bI+/vhj0zGs+Ph4S5I1YMAAy9PT05JU4NaiRQvr5MmTF23//vvvX/Ra58+ft7p06XLRa1y4TZgwIX/buXPnXnKb9u3bW61bt7b8/Pzytz179qzVrl27i7Z1OBzWoEGDLElWbGxs/vZ5eXnWgAEDLptj8eLFRc5QoUKFy77eX/7yl/ztcnNzrXr16l20TWFd6flF2b+mvPfee1b9+vVNxwCAQpsxY4blcDiK/Lzw8HCrYsWK1rlz5y56bPDgwZddq/94zLIsywoJCbEkWSkpKYV67/j4+Esesx0OhzVz5sxLPufJJ5+0JFnp6elF+nMWd/8AgAl5eXmXXGev5kprelHX3LK8phd3/wCASfRn9GeXQn+GUpbDGS82UtYm9iEhIYqPj1fHjh3l6+srf39/DRkyRCtXrlTlypUL9Ro+Pj5asmSJXnvtNd10003y8fFRlSpV1L17d8XHx+vJJ5/M37Zfv36aNm2agoKC5Ovrqzp16mjYsGFaunTpRRPfihUravny5Ro+fLhq166tihUrqn379vr6668v+eVgHh4eiomJ0cSJE9WpUydVqlRJVatWVceOHfXZZ5/p9ttvL3KGtWvXasSIEQoMDMzfPyEhIfrss8/0/vvv52/n6empWbNmKTQ0VJUqVSrs7i/U84uyf01hYg+gvHjooYd07ty5/FPVr8WFT4l5eXkVavvw8HB999136tGjh6pUqaJKlSqpa9euSkhI0MCBAy/aPi8vT/PmzVO3bt3UsGHDa84LAO7mSmt6Uddc1nQAcC36M/qzS6E/Q2lzWNYfLjKIMiswMFCDBg3Sa6+9ZjoK4DJ///vftXDhQq1fv950FAAolOjoaD3wwAMXnSJ/NdnZ2apfv75CQ0M1Z86cYr+/0+mUn5+f6tWrp9TU1BL5EshFixapV69emjFjhu67774iPbe4+wcATHA6nfL09FR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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhist_result.data.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "23eb90e0-6ad7-44aa-abe5-99b3d5ad1dcd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xhist_result.variable.equals(flox_result.variable)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5e29a06-1f0c-42f1-be7c-4fd243d06113",
   "metadata": {},
   "source": [
    "## More tests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6832dc44-685f-40f6-8da7-918794ddb04c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "arr = np.random.gamma(4, size=(5, 10, 45, 90))\n",
    "#da = xr.DataArray(name=\"T\", data=arr, dims=[\"t\", \"z\", \"x\", \"y\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "faef9574-204e-4b7c-a4fd-a1225d65358c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#da.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2955f41a-740f-4dfd-b38a-1719a0667f1a",
   "metadata": {},
   "source": [
    "## Real example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b99af38-82da-4d07-8faa-72f438b9683a",
   "metadata": {},
   "source": [
    "[Example from xhistogram's documentation](https://xhistogram.readthedocs.io/en/latest/tutorial.html#Real-Data-Example)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "83a12d06-3c17-4333-aefb-1d8ffde14c1e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:153: SerializationWarning: Ambiguous reference date string: 1-1-1 00:00:0.0. The first value is assumed to be the year hence will be padded with zeros to remove the ambiguity (the padded reference date string is: 0001-1-1 00:00:0.0). To remove this message, remove the ambiguity by padding your reference date strings with zeros.\n",
      "  warnings.warn(warning_msg, SerializationWarning)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:209: CFWarning: this date/calendar/year zero convention is not supported by CF\n",
      "  cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:710: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/core/indexing.py:524: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  return np.asarray(array[self.key], dtype=None)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:153: SerializationWarning: Ambiguous reference date string: 1-1-1 00:00:0.0. The first value is assumed to be the year hence will be padded with zeros to remove the ambiguity (the padded reference date string is: 0001-1-1 00:00:0.0). To remove this message, remove the ambiguity by padding your reference date strings with zeros.\n",
      "  warnings.warn(warning_msg, SerializationWarning)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:209: CFWarning: this date/calendar/year zero convention is not supported by CF\n",
      "  cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:710: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/core/indexing.py:524: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  return np.asarray(array[self.key], dtype=None)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:153: SerializationWarning: Ambiguous reference date string: 1-1-1 00:00:0.0. The first value is assumed to be the year hence will be padded with zeros to remove the ambiguity (the padded reference date string is: 0001-1-1 00:00:0.0). To remove this message, remove the ambiguity by padding your reference date strings with zeros.\n",
      "  warnings.warn(warning_msg, SerializationWarning)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:209: CFWarning: this date/calendar/year zero convention is not supported by CF\n",
      "  cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/coding/times.py:710: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)\n",
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/core/indexing.py:524: SerializationWarning: Unable to decode time axis into full numpy.datetime64 objects, continuing using cftime.datetime objects instead, reason: dates out of range\n",
      "  return np.asarray(array[self.key], dtype=None)\n"
     ]
    },
    {
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       "\n",
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       "\n",
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       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
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       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
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       "  padding: 0 !important;\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",
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       "\n",
       ".xr-has-index {\n",
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       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
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       "\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       "\n",
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       ".xr-var-dims,\n",
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       "\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\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",
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       "\n",
       ".xr-var-data > table {\n",
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       "}\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.Dataset&gt;\n",
       "Dimensions:  (time: 1, lev: 102, lat: 36, lon: 72)\n",
       "Coordinates:\n",
       "  * time     (time) object -0001-01-15 00:00:00\n",
       "  * lev      (lev) float64 0.0 5.0 10.0 15.0 ... 5.2e+03 5.3e+03 5.4e+03 5.5e+03\n",
       "  * lat      (lat) float64 -87.5 -82.5 -77.5 -72.5 -67.5 ... 72.5 77.5 82.5 87.5\n",
       "  * lon      (lon) float64 -177.5 -172.5 -167.5 -162.5 ... 167.5 172.5 177.5\n",
       "Data variables:\n",
       "    tmn      (time, lev, lat, lon) float32 ...\n",
       "    smn      (time, lev, lat, lon) float32 ...\n",
       "    omn      (time, lev, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    long_name:  statistical mean sea water temperature [degc] </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-05614083-2dbf-4daf-b91e-dfe6bd0caa99' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-05614083-2dbf-4daf-b91e-dfe6bd0caa99' 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>: 1</li><li><span class='xr-has-index'>lev</span>: 102</li><li><span class='xr-has-index'>lat</span>: 36</li><li><span class='xr-has-index'>lon</span>: 72</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2852f53d-1820-416c-ab61-b217062fa93a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2852f53d-1820-416c-ab61-b217062fa93a' class='xr-section-summary' >Coordinates: <span>(4)</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'>object</div><div class='xr-var-preview xr-preview'>-0001-01-15 00:00:00</div><input id='attrs-1126efc7-c4f0-4132-a69f-fef15504abde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1126efc7-c4f0-4132-a69f-fef15504abde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93f3875b-3c53-496b-afe6-bbe9018fed3a' class='xr-var-data-in' type='checkbox'><label for='data-93f3875b-3c53-496b-afe6-bbe9018fed3a' title='Show/Hide data 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>grads_dim :</span></dt><dd>t</dd><dt><span>grads_mapping :</span></dt><dd>linear</dd><dt><span>grads_size :</span></dt><dd>1</dd><dt><span>grads_min :</span></dt><dd>00z15jan0000</dd><dt><span>grads_step :</span></dt><dd>1yr</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>minimum :</span></dt><dd>00z15jan0000</dd><dt><span>maximum :</span></dt><dd>00z15jan0000</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(-1, 1, 15, 0, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 5.4e+03 5.5e+03</div><input id='attrs-28365399-1f60-41ee-abe5-01f34193e748' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28365399-1f60-41ee-abe5-01f34193e748' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c23fabb8-88df-4160-9acb-abacac18d443' class='xr-var-data-in' type='checkbox'><label for='data-c23fabb8-88df-4160-9acb-abacac18d443' title='Show/Hide data 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>grads_dim :</span></dt><dd>z</dd><dt><span>grads_mapping :</span></dt><dd>levels</dd><dt><span>units :</span></dt><dd>millibar</dd><dt><span>long_name :</span></dt><dd>altitude</dd><dt><span>minimum :</span></dt><dd>0.0</dd><dt><span>maximum :</span></dt><dd>5500.0</dd><dt><span>resolution :</span></dt><dd>54.455444</dd></dl></div><div class='xr-var-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-87.5 -82.5 -77.5 ... 82.5 87.5</div><input id='attrs-2804e295-5c0d-4f87-8f26-27885b2de1a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2804e295-5c0d-4f87-8f26-27885b2de1a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d14e5c-47c1-484f-becd-8c6b01406aa0' class='xr-var-data-in' type='checkbox'><label for='data-d3d14e5c-47c1-484f-becd-8c6b01406aa0' title='Show/Hide data 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>grads_dim :</span></dt><dd>y</dd><dt><span>grads_mapping :</span></dt><dd>linear</dd><dt><span>grads_size :</span></dt><dd>36</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>minimum :</span></dt><dd>-87.5</dd><dt><span>maximum :</span></dt><dd>87.5</dd><dt><span>resolution :</span></dt><dd>5.0</dd></dl></div><div class='xr-var-data'><pre>array([-87.5, -82.5, -77.5, -72.5, -67.5, -62.5, -57.5, -52.5, -47.5, -42.5,\n",
       "       -37.5, -32.5, -27.5, -22.5, -17.5, -12.5,  -7.5,  -2.5,   2.5,   7.5,\n",
       "        12.5,  17.5,  22.5,  27.5,  32.5,  37.5,  42.5,  47.5,  52.5,  57.5,\n",
       "        62.5,  67.5,  72.5,  77.5,  82.5,  87.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-177.5 -172.5 ... 172.5 177.5</div><input id='attrs-1984d9b9-97ef-4bc6-be1e-445597ac11f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1984d9b9-97ef-4bc6-be1e-445597ac11f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52cd9d96-119a-4e48-b95d-165c590b2ccc' class='xr-var-data-in' type='checkbox'><label for='data-52cd9d96-119a-4e48-b95d-165c590b2ccc' title='Show/Hide data 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>grads_dim :</span></dt><dd>x</dd><dt><span>grads_mapping :</span></dt><dd>linear</dd><dt><span>grads_size :</span></dt><dd>72</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>minimum :</span></dt><dd>-177.5</dd><dt><span>maximum :</span></dt><dd>177.5</dd><dt><span>resolution :</span></dt><dd>5.0</dd></dl></div><div class='xr-var-data'><pre>array([-177.5, -172.5, -167.5, -162.5, -157.5, -152.5, -147.5, -142.5, -137.5,\n",
       "       -132.5, -127.5, -122.5, -117.5, -112.5, -107.5, -102.5,  -97.5,  -92.5,\n",
       "        -87.5,  -82.5,  -77.5,  -72.5,  -67.5,  -62.5,  -57.5,  -52.5,  -47.5,\n",
       "        -42.5,  -37.5,  -32.5,  -27.5,  -22.5,  -17.5,  -12.5,   -7.5,   -2.5,\n",
       "          2.5,    7.5,   12.5,   17.5,   22.5,   27.5,   32.5,   37.5,   42.5,\n",
       "         47.5,   52.5,   57.5,   62.5,   67.5,   72.5,   77.5,   82.5,   87.5,\n",
       "         92.5,   97.5,  102.5,  107.5,  112.5,  117.5,  122.5,  127.5,  132.5,\n",
       "        137.5,  142.5,  147.5,  152.5,  157.5,  162.5,  167.5,  172.5,  177.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d5ce9aa9-ba35-4a93-9b95-f428bd6a6677' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5ce9aa9-ba35-4a93-9b95-f428bd6a6677' class='xr-section-summary' >Data variables: <span>(3)</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>tmn</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1dc97ee-5b96-4016-939a-8af9249bf330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1dc97ee-5b96-4016-939a-8af9249bf330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ed30f3b-96ee-42ab-bd0c-61a716802e7d' class='xr-var-data-in' type='checkbox'><label for='data-8ed30f3b-96ee-42ab-bd0c-61a716802e7d' title='Show/Hide data 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>statistical mean sea water temperature [degc] </dd></dl></div><div class='xr-var-data'><pre>[264384 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smn</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-908d19b3-401f-4e70-89ce-e9047d2158a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-908d19b3-401f-4e70-89ce-e9047d2158a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b41de786-6283-4985-a490-e0a19b51e955' class='xr-var-data-in' type='checkbox'><label for='data-b41de786-6283-4985-a490-e0a19b51e955' title='Show/Hide data 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>statistical mean salinity [unitless] </dd></dl></div><div class='xr-var-data'><pre>[264384 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>omn</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9415e285-ef6e-44ea-bcb7-e0c80376d28c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9415e285-ef6e-44ea-bcb7-e0c80376d28c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-774ee01b-967f-4a3b-b330-2541cad053af' class='xr-var-data-in' type='checkbox'><label for='data-774ee01b-967f-4a3b-b330-2541cad053af' title='Show/Hide data 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>statistical mean dissolved oxygen [ml/l] </dd></dl></div><div class='xr-var-data'><pre>[264384 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-680cb8cf-b9b7-4f97-8c77-7548831d7926' class='xr-section-summary-in' type='checkbox'  ><label for='section-680cb8cf-b9b7-4f97-8c77-7548831d7926' class='xr-section-summary' >Indexes: <span>(4)</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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-808b430b-c7c7-4aad-8ce8-5b5577ba8b31' class='xr-index-data-in' type='checkbox'/><label for='index-808b430b-c7c7-4aad-8ce8-5b5577ba8b31' 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(CFTimeIndex([-0001-01-15 00:00:00],\n",
       "            dtype=&#x27;object&#x27;, length=1, calendar=&#x27;standard&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-12ede45f-4772-4fd3-9864-801fa48c5724' class='xr-index-data-in' type='checkbox'/><label for='index-12ede45f-4772-4fd3-9864-801fa48c5724' 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(Float64Index([   0.0,    5.0,   10.0,   15.0,   20.0,   25.0,   30.0,   35.0,\n",
       "                40.0,   45.0,\n",
       "              ...\n",
       "              4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0,\n",
       "              5400.0, 5500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;, length=102))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bdc6c262-8b35-427f-8544-7a61375fb07a' class='xr-index-data-in' type='checkbox'/><label for='index-bdc6c262-8b35-427f-8544-7a61375fb07a' 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(Float64Index([-87.5, -82.5, -77.5, -72.5, -67.5, -62.5, -57.5, -52.5, -47.5,\n",
       "              -42.5, -37.5, -32.5, -27.5, -22.5, -17.5, -12.5,  -7.5,  -2.5,\n",
       "                2.5,   7.5,  12.5,  17.5,  22.5,  27.5,  32.5,  37.5,  42.5,\n",
       "               47.5,  52.5,  57.5,  62.5,  67.5,  72.5,  77.5,  82.5,  87.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-54f580a8-d64f-4213-92a2-a1a7dc0cacb6' class='xr-index-data-in' type='checkbox'/><label for='index-54f580a8-d64f-4213-92a2-a1a7dc0cacb6' 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(Float64Index([-177.5, -172.5, -167.5, -162.5, -157.5, -152.5, -147.5, -142.5,\n",
       "              -137.5, -132.5, -127.5, -122.5, -117.5, -112.5, -107.5, -102.5,\n",
       "               -97.5,  -92.5,  -87.5,  -82.5,  -77.5,  -72.5,  -67.5,  -62.5,\n",
       "               -57.5,  -52.5,  -47.5,  -42.5,  -37.5,  -32.5,  -27.5,  -22.5,\n",
       "               -17.5,  -12.5,   -7.5,   -2.5,    2.5,    7.5,   12.5,   17.5,\n",
       "                22.5,   27.5,   32.5,   37.5,   42.5,   47.5,   52.5,   57.5,\n",
       "                62.5,   67.5,   72.5,   77.5,   82.5,   87.5,   92.5,   97.5,\n",
       "               102.5,  107.5,  112.5,  117.5,  122.5,  127.5,  132.5,  137.5,\n",
       "               142.5,  147.5,  152.5,  157.5,  162.5,  167.5,  172.5,  177.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5c27898-bd41-4c91-9e06-eb70bd0bf2ce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f5c27898-bd41-4c91-9e06-eb70bd0bf2ce' 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>long_name :</span></dt><dd>statistical mean sea water temperature [degc] </dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 1, lev: 102, lat: 36, lon: 72)\n",
       "Coordinates:\n",
       "  * time     (time) object -0001-01-15 00:00:00\n",
       "  * lev      (lev) float64 0.0 5.0 10.0 15.0 ... 5.2e+03 5.3e+03 5.4e+03 5.5e+03\n",
       "  * lat      (lat) float64 -87.5 -82.5 -77.5 -72.5 -67.5 ... 72.5 77.5 82.5 87.5\n",
       "  * lon      (lon) float64 -177.5 -172.5 -167.5 -162.5 ... 167.5 172.5 177.5\n",
       "Data variables:\n",
       "    tmn      (time, lev, lat, lon) float32 ...\n",
       "    smn      (time, lev, lat, lon) float32 ...\n",
       "    omn      (time, lev, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    long_name:  statistical mean sea water temperature [degc] "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Temp_url = 'http://apdrc.soest.hawaii.edu:80/dods/public_data/WOA/WOA13/5_deg/annual/temp'\n",
    "Salt_url = 'http://apdrc.soest.hawaii.edu:80/dods/public_data/WOA/WOA13/5_deg/annual/salt'\n",
    "Oxy_url = 'http://apdrc.soest.hawaii.edu:80/dods/public_data/WOA/WOA13/5_deg/annual/doxy'\n",
    "\n",
    "ds = xr.merge([\n",
    "    xr.open_dataset(Temp_url)['tmn'],\n",
    "    xr.open_dataset(Salt_url)['smn'],\n",
    "    xr.open_dataset(Oxy_url)['omn'],\n",
    "    ])\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e57c9cdc-4d12-4a41-b3fc-1253e8a67495",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# bins for salinity and temperature\n",
    "sbins = np.arange(31,38, 0.025)\n",
    "tbins = np.arange(-2, 32, 0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a2955925-e6d3-46f3-b018-f51419ae51b1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hTSw_xhist = xhist_histogram(ds.smn, ds.tmn, bins=[sbins, tbins])#, weights=dVol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6f8e217d-3a30-4d30-8cc2-5b3f755b1eb5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  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",
       "}\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;histogram_smn_tmn&#x27; (smn_bin: 279, tmn_bin: 339)&gt;\n",
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) float64 31.01 31.04 31.06 31.09 ... 37.91 37.94 37.96\n",
       "  * tmn_bin  (tmn_bin) float64 -1.95 -1.85 -1.75 -1.65 ... 31.65 31.75 31.85</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'>'histogram_smn_tmn'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>smn_bin</span>: 279</li><li><span class='xr-has-index'>tmn_bin</span>: 339</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-79c65a20-2dd6-4b88-aca3-88bd4c1c4eba' class='xr-array-in' type='checkbox' checked><label for='section-79c65a20-2dd6-4b88-aca3-88bd4c1c4eba' 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 0 0 3 2 0 0 0 0 0 1 2 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0</span></div><div class='xr-array-data'><pre>array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])</pre></div></div></li><li class='xr-section-item'><input id='section-c0f63c4f-db81-4033-a63c-a6336dd32fc3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c0f63c4f-db81-4033-a63c-a6336dd32fc3' 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'>smn_bin</span></div><div class='xr-var-dims'>(smn_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.01 31.04 31.06 ... 37.94 37.96</div><input id='attrs-bce8fddf-03e1-489c-a1c3-09347e4f8a32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bce8fddf-03e1-489c-a1c3-09347e4f8a32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a573a4fd-4072-4eb6-9696-d1be07011a8e' class='xr-var-data-in' type='checkbox'><label for='data-a573a4fd-4072-4eb6-9696-d1be07011a8e' title='Show/Hide data 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>statistical mean salinity [unitless] </dd></dl></div><div class='xr-var-data'><pre>array([31.0125, 31.0375, 31.0625, ..., 37.9125, 37.9375, 37.9625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>tmn_bin</span></div><div class='xr-var-dims'>(tmn_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.95 -1.85 -1.75 ... 31.75 31.85</div><input id='attrs-859bcae3-bdec-409d-9c52-d19b2f604995' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-859bcae3-bdec-409d-9c52-d19b2f604995' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9a5934b-b56d-40ea-a1f7-49ca54d89ce1' class='xr-var-data-in' type='checkbox'><label for='data-a9a5934b-b56d-40ea-a1f7-49ca54d89ce1' title='Show/Hide data 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>statistical mean sea water temperature [degc] </dd></dl></div><div class='xr-var-data'><pre>array([-1.95, -1.85, -1.75, ..., 31.65, 31.75, 31.85])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ff6c423-7c40-4051-b2f1-de5348a8da66' class='xr-section-summary-in' type='checkbox'  ><label for='section-9ff6c423-7c40-4051-b2f1-de5348a8da66' 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>smn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dfb93743-d8cd-4ac6-bfd0-8ad24a816277' class='xr-index-data-in' type='checkbox'/><label for='index-dfb93743-d8cd-4ac6-bfd0-8ad24a816277' 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(Float64Index([           31.0125, 31.037499999999998, 31.062499999999996,\n",
       "              31.087499999999995, 31.112499999999994, 31.137499999999992,\n",
       "               31.16249999999999,  31.18749999999999, 31.212499999999988,\n",
       "              31.237499999999986,\n",
       "              ...\n",
       "               37.73749999999961,  37.76249999999962,  37.78749999999961,\n",
       "              37.812499999999616,  37.83749999999961,  37.86249999999961,\n",
       "              37.887499999999605,  37.91249999999961,   37.9374999999996,\n",
       "               37.96249999999961],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;smn_bin&#x27;, length=279))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>tmn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aa79406c-2351-409e-afbe-602f04a89b91' class='xr-index-data-in' type='checkbox'/><label for='index-aa79406c-2351-409e-afbe-602f04a89b91' 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(Float64Index([              -1.95, -1.8499999999999999, -1.7499999999999998,\n",
       "              -1.6499999999999997, -1.5499999999999996, -1.4499999999999995,\n",
       "              -1.3499999999999994, -1.2499999999999993, -1.1499999999999992,\n",
       "              -1.0499999999999992,\n",
       "              ...\n",
       "               30.950000000000028,   31.05000000000003,   31.15000000000003,\n",
       "               31.250000000000032,   31.35000000000003,  31.450000000000028,\n",
       "                31.55000000000003,   31.65000000000003,  31.750000000000032,\n",
       "                31.85000000000003],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;tmn_bin&#x27;, length=339))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55a52360-8deb-4e4e-875e-6e17639559ed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-55a52360-8deb-4e4e-875e-6e17639559ed' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'histogram_smn_tmn' (smn_bin: 279, tmn_bin: 339)>\n",
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) float64 31.01 31.04 31.06 31.09 ... 37.91 37.94 37.96\n",
       "  * tmn_bin  (tmn_bin) float64 -1.95 -1.85 -1.75 -1.65 ... 31.65 31.75 31.85"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hTSw_xhist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "79a41880-5edd-42b5-b48a-3cfa645cd7e2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/core/computation.py:760: RuntimeWarning: divide by zero encountered in log10\n",
      "  result_data = func(*input_data)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fb490700f10>"
      ]
     },
     "execution_count": 20,
     "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": [
    "np.log10(hTSw_xhist.T).plot(levels=31)#, vmin=11.5, vmax=16, cmap='brg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a0b6c142-ca70-4574-ae13-67f14e0bcda4",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hTSw_flox = flox_histogram(ds.smn, ds.tmn, bins=[sbins, tbins])#, weights=dVol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "90d888ee-619e-4fb1-9d3b-32367335668f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "  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",
       "}\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;histogram_smn_tmn&#x27; (smn_bin: 279, tmn_bin: 339)&gt;\n",
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) object (31.0, 31.025] ... (37.949999999999605, 37.9749...\n",
       "  * tmn_bin  (tmn_bin) object (-2.0, -1.9] ... (31.800000000000033, 31.900000...</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'>'histogram_smn_tmn'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>smn_bin</span>: 279</li><li><span class='xr-has-index'>tmn_bin</span>: 339</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-730fda77-5316-481d-84df-84baccfd12b2' class='xr-array-in' type='checkbox' checked><label for='section-730fda77-5316-481d-84df-84baccfd12b2' 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 0 0 3 2 0 0 0 0 0 1 2 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0</span></div><div class='xr-array-data'><pre>array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])</pre></div></div></li><li class='xr-section-item'><input id='section-720a57d4-116f-443f-9145-9d05f5735e68' class='xr-section-summary-in' type='checkbox'  checked><label for='section-720a57d4-116f-443f-9145-9d05f5735e68' 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'>smn_bin</span></div><div class='xr-var-dims'>(smn_bin)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(31.0, 31.025] ... (37.949999999...</div><input id='attrs-329aa83c-4949-4e15-b30c-dcee1d052113' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-329aa83c-4949-4e15-b30c-dcee1d052113' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efae44c6-9257-4c2f-a8fd-54e9b4443bb1' class='xr-var-data-in' type='checkbox'><label for='data-efae44c6-9257-4c2f-a8fd-54e9b4443bb1' title='Show/Hide data 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>statistical mean salinity [unitless] </dd></dl></div><div class='xr-var-data'><pre>array([Interval(31.0, 31.025, closed=&#x27;right&#x27;),\n",
       "       Interval(31.025, 31.049999999999997, closed=&#x27;right&#x27;),\n",
       "       Interval(31.049999999999997, 31.074999999999996, closed=&#x27;right&#x27;), ...,\n",
       "       Interval(37.89999999999961, 37.924999999999606, closed=&#x27;right&#x27;),\n",
       "       Interval(37.924999999999606, 37.949999999999605, closed=&#x27;right&#x27;),\n",
       "       Interval(37.949999999999605, 37.9749999999996, closed=&#x27;right&#x27;)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>tmn_bin</span></div><div class='xr-var-dims'>(tmn_bin)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(-2.0, -1.9] ... (31.80000000000...</div><input id='attrs-72ca93d1-3932-4cbd-8f09-049db41ef3d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72ca93d1-3932-4cbd-8f09-049db41ef3d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c2a9b9d-cc23-4b45-8fb4-70ea434035e8' class='xr-var-data-in' type='checkbox'><label for='data-7c2a9b9d-cc23-4b45-8fb4-70ea434035e8' title='Show/Hide data 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>statistical mean sea water temperature [degc] </dd></dl></div><div class='xr-var-data'><pre>array([Interval(-2.0, -1.9, closed=&#x27;right&#x27;),\n",
       "       Interval(-1.9, -1.7999999999999998, closed=&#x27;right&#x27;),\n",
       "       Interval(-1.7999999999999998, -1.6999999999999997, closed=&#x27;right&#x27;), ...,\n",
       "       Interval(31.60000000000003, 31.70000000000003, closed=&#x27;right&#x27;),\n",
       "       Interval(31.70000000000003, 31.800000000000033, closed=&#x27;right&#x27;),\n",
       "       Interval(31.800000000000033, 31.900000000000027, closed=&#x27;right&#x27;)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e6e3dd83-2cfc-4ea0-a0c5-8981a68fc461' class='xr-section-summary-in' type='checkbox'  ><label for='section-e6e3dd83-2cfc-4ea0-a0c5-8981a68fc461' 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>smn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b939d9fc-2f8a-4258-93fc-8d2feefb9988' class='xr-index-data-in' type='checkbox'/><label for='index-b939d9fc-2f8a-4258-93fc-8d2feefb9988' 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([                          (31.0, 31.025],\n",
       "                   (31.025, 31.049999999999997],\n",
       "       (31.049999999999997, 31.074999999999996],\n",
       "       (31.074999999999996, 31.099999999999994],\n",
       "       (31.099999999999994, 31.124999999999993],\n",
       "        (31.124999999999993, 31.14999999999999],\n",
       "         (31.14999999999999, 31.17499999999999],\n",
       "         (31.17499999999999, 31.19999999999999],\n",
       "        (31.19999999999999, 31.224999999999987],\n",
       "       (31.224999999999987, 31.249999999999986],\n",
       "       ...\n",
       "        (37.72499999999962, 37.749999999999616],\n",
       "       (37.749999999999616, 37.774999999999615],\n",
       "        (37.774999999999615, 37.79999999999961],\n",
       "         (37.79999999999961, 37.82499999999961],\n",
       "         (37.82499999999961, 37.84999999999961],\n",
       "         (37.84999999999961, 37.87499999999961],\n",
       "         (37.87499999999961, 37.89999999999961],\n",
       "        (37.89999999999961, 37.924999999999606],\n",
       "       (37.924999999999606, 37.949999999999605],\n",
       "         (37.949999999999605, 37.9749999999996]],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;smn_bin&#x27;, length=279))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>tmn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-287f6b63-cfa3-441e-8733-4f0a9d127b97' class='xr-index-data-in' type='checkbox'/><label for='index-287f6b63-cfa3-441e-8733-4f0a9d127b97' 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([                              (-2.0, -1.9],\n",
       "                      (-1.9, -1.7999999999999998],\n",
       "       (-1.7999999999999998, -1.6999999999999997],\n",
       "       (-1.6999999999999997, -1.5999999999999996],\n",
       "       (-1.5999999999999996, -1.4999999999999996],\n",
       "       (-1.4999999999999996, -1.3999999999999995],\n",
       "       (-1.3999999999999995, -1.2999999999999994],\n",
       "       (-1.2999999999999994, -1.1999999999999993],\n",
       "       (-1.1999999999999993, -1.0999999999999992],\n",
       "       (-1.0999999999999992, -0.9999999999999991],\n",
       "       ...\n",
       "          (30.900000000000027, 31.00000000000003],\n",
       "           (31.00000000000003, 31.10000000000003],\n",
       "           (31.10000000000003, 31.20000000000003],\n",
       "          (31.20000000000003, 31.300000000000033],\n",
       "         (31.300000000000033, 31.400000000000027],\n",
       "          (31.400000000000027, 31.50000000000003],\n",
       "           (31.50000000000003, 31.60000000000003],\n",
       "           (31.60000000000003, 31.70000000000003],\n",
       "          (31.70000000000003, 31.800000000000033],\n",
       "         (31.800000000000033, 31.900000000000027]],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;tmn_bin&#x27;, length=339))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ee76a733-ee56-4716-acbc-475ec020d405' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ee76a733-ee56-4716-acbc-475ec020d405' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'histogram_smn_tmn' (smn_bin: 279, tmn_bin: 339)>\n",
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       [0, 0, 1, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) object (31.0, 31.025] ... (37.949999999999605, 37.9749...\n",
       "  * tmn_bin  (tmn_bin) object (-2.0, -1.9] ... (31.800000000000033, 31.900000..."
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hTSw_flox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1e42f676-2af4-4857-93c4-601a0474d1f1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hTSw_xhist.variable.equals(hTSw_flox.variable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8bddba6d-a6d7-49e1-8cf9-0e0a6dc9d2b2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tom/miniconda3/envs/dev3.9/lib/python3.9/site-packages/xarray/core/computation.py:760: RuntimeWarning: divide by zero encountered in log10\n",
      "  result_data = func(*input_data)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fb4905e3400>"
      ]
     },
     "execution_count": 24,
     "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": [
    "np.log10(hTSw_flox.T).plot(levels=31)#, vmin=11.5, vmax=16, cmap='brg')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be5985df-0430-48dc-bac1-917f9b7dc005",
   "metadata": {},
   "source": [
    "### Volume census (weighted histogram)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "503ab056-1cab-4c91-b293-4ab7346dff26",
   "metadata": {},
   "source": [
    "Want to do a volume census, which requires grid points to be weighted by\n",
    "\n",
    "$$dV = dz * dx * dy$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "251d8c43-aae8-4bde-9381-6c63eff52cdc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create a dz variable\n",
    "dz = np.diff(ds.lev)\n",
    "dz = np.insert(dz, 0, dz[0])\n",
    "dz = xr.DataArray(dz, coords= {'lev':ds.lev}, dims='lev')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "44622f2b-5d45-480c-9dbb-17a6289ddfd7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# weight by volume of grid cell (resolution = 5degree, 1degree=110km)\n",
    "dVol = dz * (5*110e3) * (5*110e3*np.cos(ds.lat*np.pi/180))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0848ec6f-e00e-4dcf-bc87-9db5c158e37e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  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",
       "}\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 (lev: 102, lat: 36)&gt;\n",
       "array([[6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       ...,\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12]])\n",
       "Coordinates:\n",
       "  * lev      (lev) float64 0.0 5.0 10.0 15.0 ... 5.2e+03 5.3e+03 5.4e+03 5.5e+03\n",
       "  * lat      (lat) float64 -87.5 -82.5 -77.5 -72.5 -67.5 ... 72.5 77.5 82.5 87.5</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'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lev</span>: 102</li><li><span class='xr-has-index'>lat</span>: 36</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2a733d52-bbd8-4aa0-b601-35b17a9b1a4c' class='xr-array-in' type='checkbox' checked><label for='section-2a733d52-bbd8-4aa0-b601-35b17a9b1a4c' 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>6.597e+10 1.974e+11 3.274e+11 ... 6.547e+12 3.948e+12 1.319e+12</span></div><div class='xr-array-data'><pre>array([[6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       ...,\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12]])</pre></div></div></li><li class='xr-section-item'><input id='section-8f78e508-235b-4168-be1c-740bd48a3bed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f78e508-235b-4168-be1c-740bd48a3bed' 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'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 5.4e+03 5.5e+03</div><input id='attrs-041358e3-dc28-4aa5-a5d5-4d46672e02f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-041358e3-dc28-4aa5-a5d5-4d46672e02f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b05e599-fd41-4dbe-ae60-e9ed78157bcb' class='xr-var-data-in' type='checkbox'><label for='data-6b05e599-fd41-4dbe-ae60-e9ed78157bcb' title='Show/Hide data 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>grads_dim :</span></dt><dd>z</dd><dt><span>grads_mapping :</span></dt><dd>levels</dd><dt><span>units :</span></dt><dd>millibar</dd><dt><span>long_name :</span></dt><dd>altitude</dd><dt><span>minimum :</span></dt><dd>0.0</dd><dt><span>maximum :</span></dt><dd>5500.0</dd><dt><span>resolution :</span></dt><dd>54.455444</dd></dl></div><div class='xr-var-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-87.5 -82.5 -77.5 ... 82.5 87.5</div><input id='attrs-c5900123-ba4c-4660-a6cd-5fc701311938' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5900123-ba4c-4660-a6cd-5fc701311938' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b00d84b-2ff7-450e-8a23-5c5043f0abbb' class='xr-var-data-in' type='checkbox'><label for='data-7b00d84b-2ff7-450e-8a23-5c5043f0abbb' title='Show/Hide data 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>grads_dim :</span></dt><dd>y</dd><dt><span>grads_mapping :</span></dt><dd>linear</dd><dt><span>grads_size :</span></dt><dd>36</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>minimum :</span></dt><dd>-87.5</dd><dt><span>maximum :</span></dt><dd>87.5</dd><dt><span>resolution :</span></dt><dd>5.0</dd></dl></div><div class='xr-var-data'><pre>array([-87.5, -82.5, -77.5, -72.5, -67.5, -62.5, -57.5, -52.5, -47.5, -42.5,\n",
       "       -37.5, -32.5, -27.5, -22.5, -17.5, -12.5,  -7.5,  -2.5,   2.5,   7.5,\n",
       "        12.5,  17.5,  22.5,  27.5,  32.5,  37.5,  42.5,  47.5,  52.5,  57.5,\n",
       "        62.5,  67.5,  72.5,  77.5,  82.5,  87.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4822d4dc-e869-44a1-a513-0d75eb66e52a' class='xr-section-summary-in' type='checkbox'  ><label for='section-4822d4dc-e869-44a1-a513-0d75eb66e52a' 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>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0f735276-1bf9-4b1a-98b3-92ba351bf833' class='xr-index-data-in' type='checkbox'/><label for='index-0f735276-1bf9-4b1a-98b3-92ba351bf833' 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(Float64Index([   0.0,    5.0,   10.0,   15.0,   20.0,   25.0,   30.0,   35.0,\n",
       "                40.0,   45.0,\n",
       "              ...\n",
       "              4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0,\n",
       "              5400.0, 5500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;, length=102))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a1be4c1a-e7f5-4b91-85a4-b087656d1b05' class='xr-index-data-in' type='checkbox'/><label for='index-a1be4c1a-e7f5-4b91-85a4-b087656d1b05' 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(Float64Index([-87.5, -82.5, -77.5, -72.5, -67.5, -62.5, -57.5, -52.5, -47.5,\n",
       "              -42.5, -37.5, -32.5, -27.5, -22.5, -17.5, -12.5,  -7.5,  -2.5,\n",
       "                2.5,   7.5,  12.5,  17.5,  22.5,  27.5,  32.5,  37.5,  42.5,\n",
       "               47.5,  52.5,  57.5,  62.5,  67.5,  72.5,  77.5,  82.5,  87.5],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0d607182-4d3b-465b-b514-06f77cb58979' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0d607182-4d3b-465b-b514-06f77cb58979' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lev: 102, lat: 36)>\n",
       "array([[6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       [6.59743234e+10, 1.97420866e+11, 3.27364916e+11, ...,\n",
       "        3.27364916e+11, 1.97420866e+11, 6.59743234e+10],\n",
       "       ...,\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12],\n",
       "       [1.31948647e+12, 3.94841731e+12, 6.54729832e+12, ...,\n",
       "        6.54729832e+12, 3.94841731e+12, 1.31948647e+12]])\n",
       "Coordinates:\n",
       "  * lev      (lev) float64 0.0 5.0 10.0 15.0 ... 5.2e+03 5.3e+03 5.4e+03 5.5e+03\n",
       "  * lat      (lat) float64 -87.5 -82.5 -77.5 -72.5 -67.5 ... 72.5 77.5 82.5 87.5"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dVol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "48ee2599-6a2a-49ae-9e8c-5273c63241b9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hTSw_xhist = xhist_histogram(ds.smn, ds.tmn, bins=[sbins, tbins], weights=dVol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "98008a4f-c19c-4ad8-b3e1-a3f425a07e0b",
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   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;histogram_smn_tmn&#x27; (smn_bin: 279, tmn_bin: 339)&gt;\n",
       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 3.27364916e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 1.97420866e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       ...,\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) float64 31.01 31.04 31.06 31.09 ... 37.91 37.94 37.96\n",
       "  * tmn_bin  (tmn_bin) float64 -1.95 -1.85 -1.75 -1.65 ... 31.65 31.75 31.85</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'>'histogram_smn_tmn'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>smn_bin</span>: 279</li><li><span class='xr-has-index'>tmn_bin</span>: 339</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4e26a7cf-6664-456e-9c99-2164c0d2e029' class='xr-array-in' type='checkbox' checked><label for='section-4e26a7cf-6664-456e-9c99-2164c0d2e029' 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>0.0 0.0 0.0 1.979e+11 3.948e+11 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 3.27364916e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 1.97420866e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       ...,\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])</pre></div></div></li><li class='xr-section-item'><input id='section-1193d480-4267-44fa-9923-671a9325caf2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1193d480-4267-44fa-9923-671a9325caf2' 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'>smn_bin</span></div><div class='xr-var-dims'>(smn_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.01 31.04 31.06 ... 37.94 37.96</div><input id='attrs-6729567f-5e7a-4310-8280-f78661a72e1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6729567f-5e7a-4310-8280-f78661a72e1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f058f1d8-d617-48b0-b35f-13f9fb4ee400' class='xr-var-data-in' type='checkbox'><label for='data-f058f1d8-d617-48b0-b35f-13f9fb4ee400' title='Show/Hide data 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>statistical mean salinity [unitless] </dd></dl></div><div class='xr-var-data'><pre>array([31.0125, 31.0375, 31.0625, ..., 37.9125, 37.9375, 37.9625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>tmn_bin</span></div><div class='xr-var-dims'>(tmn_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.95 -1.85 -1.75 ... 31.75 31.85</div><input id='attrs-3f1eac18-ad3d-4c1a-8d7f-9495070a5ca3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f1eac18-ad3d-4c1a-8d7f-9495070a5ca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56cc7613-6185-487f-861a-4a8c67152c00' class='xr-var-data-in' type='checkbox'><label for='data-56cc7613-6185-487f-861a-4a8c67152c00' title='Show/Hide data 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>statistical mean sea water temperature [degc] </dd></dl></div><div class='xr-var-data'><pre>array([-1.95, -1.85, -1.75, ..., 31.65, 31.75, 31.85])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-224c6074-7699-41b0-98c4-f0d22f35660e' class='xr-section-summary-in' type='checkbox'  ><label for='section-224c6074-7699-41b0-98c4-f0d22f35660e' 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>smn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-007822e7-75b7-4d87-82b2-2d7929eb856d' class='xr-index-data-in' type='checkbox'/><label for='index-007822e7-75b7-4d87-82b2-2d7929eb856d' 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(Float64Index([           31.0125, 31.037499999999998, 31.062499999999996,\n",
       "              31.087499999999995, 31.112499999999994, 31.137499999999992,\n",
       "               31.16249999999999,  31.18749999999999, 31.212499999999988,\n",
       "              31.237499999999986,\n",
       "              ...\n",
       "               37.73749999999961,  37.76249999999962,  37.78749999999961,\n",
       "              37.812499999999616,  37.83749999999961,  37.86249999999961,\n",
       "              37.887499999999605,  37.91249999999961,   37.9374999999996,\n",
       "               37.96249999999961],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;smn_bin&#x27;, length=279))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>tmn_bin</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b0af6880-5ba0-4b36-8227-9ebdd3ed5b6b' class='xr-index-data-in' type='checkbox'/><label for='index-b0af6880-5ba0-4b36-8227-9ebdd3ed5b6b' 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(Float64Index([              -1.95, -1.8499999999999999, -1.7499999999999998,\n",
       "              -1.6499999999999997, -1.5499999999999996, -1.4499999999999995,\n",
       "              -1.3499999999999994, -1.2499999999999993, -1.1499999999999992,\n",
       "              -1.0499999999999992,\n",
       "              ...\n",
       "               30.950000000000028,   31.05000000000003,   31.15000000000003,\n",
       "               31.250000000000032,   31.35000000000003,  31.450000000000028,\n",
       "                31.55000000000003,   31.65000000000003,  31.750000000000032,\n",
       "                31.85000000000003],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;tmn_bin&#x27;, length=339))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80980685-573e-40c2-ab1d-ce037f6a732c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-80980685-573e-40c2-ab1d-ce037f6a732c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'histogram_smn_tmn' (smn_bin: 279, tmn_bin: 339)>\n",
       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 3.27364916e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 1.97420866e+11, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       ...,\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])\n",
       "Coordinates:\n",
       "  * smn_bin  (smn_bin) float64 31.01 31.04 31.06 31.09 ... 37.91 37.94 37.96\n",
       "  * tmn_bin  (tmn_bin) float64 -1.95 -1.85 -1.75 -1.65 ... 31.65 31.75 31.85"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hTSw_xhist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "afe89e35-ea9c-4dc5-855e-cdc40b9c25a5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fb490480c70>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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