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This is to illustrate an issue with the Python xray package, where slicing with unsorted indices works on a loaded DataArray but not on an unloaded one. (Issue https://github.com/xray/xray/issues/623)
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xray_irregular_slice_before_load.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is to illustrate an issue with the Python [`xray`](https://github.com/xray/xray) package, where slicing with unsorted indices works on a `load`ed `DataArray` but not on an unloaded one."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import xray\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load some SST data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<xray.DataArray 'FilledSST' (lat: 50, lon: 8640)>\n",
"[432000 values with dtype=float64]\n",
"Coordinates:\n",
" time datetime64[ns] ...\n",
" * lat (lat) float32 89.9583 89.9167 89.875 89.8334 89.7917 89.7501 ...\n",
" * lon (lon) float32 -179.958 -179.917 -179.875 -179.833 -179.792 ...\n",
"Attributes:\n",
" standard_name: sea_surface_skin_temperature\n",
" long_name: Gap-Filled weekly SST time series for 1982-01-02 to 2012-12-28\n",
" units: Kelvin\n",
" grid_mapping: crs\n",
" valid_min: -180\n",
" valid_max: 4500\n",
" land_value: -1100\n",
" missing_pixel_value: -1100\n",
" source: The weekly sea surface temperature is derived from Pathfinder 5.2 SST.\n"
]
}
],
"source": [
"url = 'http://data.nodc.noaa.gov/thredds/dodsC/cortad/Version5/cortadv5_FilledSST.nc'\n",
"ds = xray.open_dataset(url)\n",
"sst = ds['FilledSST'].isel(time=0, lat=slice(0,50,1)) # thin slice to reduce size\n",
"print sst"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Define slice on longitude axis"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'lon': array([8620, 8621, 8622, 8623, 8624, 8625, 8626, 8627, 8628, 8629, 8630,\n",
" 8631, 8632, 8633, 8634, 8635, 8636, 8637, 8638, 8639, 0, 1,\n",
" 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,\n",
" 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,\n",
" 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n",
" 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,\n",
" 46, 47, 48, 49])}\n"
]
}
],
"source": [
"iselkw = dict(lon=np.mod(np.arange(-20,50,1), len(ds['lon'])))\n",
"print iselkw"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Slicing before loading throws an error:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "IndexError",
"evalue": "integer sequences in slices must be sorted and cannot have duplicates",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-4-0fa8e6b38584>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msst\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0miselkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/dataarray.pyc\u001b[0m in \u001b[0;36mload\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 461\u001b[0m \u001b[0mworking\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mmany\u001b[0m \u001b[0mfile\u001b[0m \u001b[0mobjects\u001b[0m \u001b[0mon\u001b[0m \u001b[0mdisk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 462\u001b[0m \"\"\"\n\u001b[1;32m--> 463\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_dataset\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 464\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/dataset.pyc\u001b[0m in \u001b[0;36mload\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 449\u001b[0m \"\"\"\n\u001b[0;32m 450\u001b[0m \u001b[1;31m# access .data to coerce everything to numpy or dask arrays\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 451\u001b[1;33m \u001b[0mall_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvariables\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 452\u001b[0m lazy_data = dict((k, v) for k, v in all_data.items()\n\u001b[0;32m 453\u001b[0m if isinstance(v, dask_array_type))\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/dataset.pyc\u001b[0m in \u001b[0;36m<genexpr>\u001b[1;34m((k, v))\u001b[0m\n\u001b[0;32m 449\u001b[0m \"\"\"\n\u001b[0;32m 450\u001b[0m \u001b[1;31m# access .data to coerce everything to numpy or dask arrays\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 451\u001b[1;33m \u001b[0mall_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvariables\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 452\u001b[0m lazy_data = dict((k, v) for k, v in all_data.items()\n\u001b[0;32m 453\u001b[0m if isinstance(v, dask_array_type))\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/variable.pyc\u001b[0m in \u001b[0;36mdata\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 220\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 223\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 224\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetter\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/variable.pyc\u001b[0m in \u001b[0;36mvalues\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 266\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mvalues\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 267\u001b[0m \u001b[1;34m\"\"\"The variable's data as a numpy.ndarray\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 268\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_as_array_or_item\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data_cached\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 269\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 270\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetter\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/variable.pyc\u001b[0m in \u001b[0;36m_data_cached\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_data_cached\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 233\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 234\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 235\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 236\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/numpy/core/numeric.pyc\u001b[0m in \u001b[0;36masarray\u001b[1;34m(a, dtype, order)\u001b[0m\n\u001b[0;32m 460\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 461\u001b[0m \"\"\"\n\u001b[1;32m--> 462\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 463\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 464\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0masanyarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/indexing.pyc\u001b[0m in \u001b[0;36m__array__\u001b[1;34m(self, dtype)\u001b[0m\n\u001b[0;32m 288\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__array__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 289\u001b[0m \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0morthogonally_indexable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 290\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 291\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 292\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/conventions.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 353\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 354\u001b[0m return mask_and_scale(self.array[key], self.fill_value,\n\u001b[1;32m--> 355\u001b[1;33m self.scale_factor, self.add_offset, self._dtype)\n\u001b[0m\u001b[0;32m 356\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 357\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__repr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/conventions.pyc\u001b[0m in \u001b[0;36mmask_and_scale\u001b[1;34m(array, fill_value, scale_factor, add_offset, dtype)\u001b[0m\n\u001b[0;32m 55\u001b[0m \"\"\"\n\u001b[0;32m 56\u001b[0m \u001b[1;31m# by default, cast to float to ensure NaN is meaningful\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 57\u001b[1;33m \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 58\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfill_value\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misnull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfill_value\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfill_value\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'size'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/core/indexing.pyc\u001b[0m in \u001b[0;36m__array__\u001b[1;34m(self, dtype)\u001b[0m\n\u001b[0;32m 288\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__array__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 289\u001b[0m \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0morthogonally_indexable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 290\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 291\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 292\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/backends/netCDF4_.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 43\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 44\u001b[0m \u001b[0mgetitem\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moperator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetitem\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 45\u001b[1;33m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetitem\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 46\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 47\u001b[0m \u001b[1;31m# work around for netCDF4-python's broken handling of 0-d\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/xray/backends/common.pyc\u001b[0m in \u001b[0;36mrobust_getitem\u001b[1;34m(array, key, catch, max_retries, initial_delay)\u001b[0m\n\u001b[0;32m 60\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_retries\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 61\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 62\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 63\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mcatch\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 64\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mmax_retries\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mnetCDF4/_netCDF4.pyx\u001b[0m in \u001b[0;36mnetCDF4._netCDF4.Variable.__getitem__ (netCDF4/_netCDF4.c:30994)\u001b[1;34m()\u001b[0m\n",
"\u001b[1;32m/climgeo/bluthgen/Software/anaconda/lib/python2.7/site-packages/netCDF4/utils.pyc\u001b[0m in \u001b[0;36m_StartCountStride\u001b[1;34m(elem, shape, dimensions, grp, datashape, put)\u001b[0m\n\u001b[0;32m 220\u001b[0m \u001b[1;31m# duplicate indices in the sequence)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[0mmsg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"integer sequences in slices must be sorted and cannot have duplicates\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 223\u001b[0m \u001b[1;31m# convert to boolean array.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 224\u001b[0m \u001b[1;31m# if unlim, let boolean array be longer than current dimension\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mIndexError\u001b[0m: integer sequences in slices must be sorted and cannot have duplicates"
]
}
],
"source": [
"sst.isel(**iselkw).load()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"But once loaded, the slicing with unsorted indices works fine:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"array([[ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" ..., \n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan],\n",
" [ nan, nan, nan, ..., nan, nan, nan]])"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sst.load().isel(**iselkw).values"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"ds.close()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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