Fix xr_linregress problem with dask

.travis.yml

@@ -7,10 +7,12 @@ notifications:
 matrix:
   fast_finish: true
   include:
-  - env: CONDA_ENV=py27
-  - env: CONDA_ENV=py35
-  - env: CONDA_ENV=py36
   - env: CONDA_ENV=py36
+  - env: CONDA_ENV=py37
+  - env: CONDA_ENV=py37-upstream_master
+  - env: CONDA_ENV=py38
+  allow_failures:
+  - env: CONDA_ENV=py38
 
 before_install:
   - wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
@@ -22,7 +24,7 @@ before_install:
 
 install:
   - conda env create --file ci/environment-$CONDA_ENV.yml
-  - source activate test_env
+  - source activate test_env_xarrayutils
   - conda list
   - pip install --no-deps -e .
 

ci/environment-py36.yml

@@ -1,21 +1,22 @@
-name: test_env
+name: test_env_xarrayutils
 channels:
   - conda-forge
 dependencies:
   - python=3.6
   - xarray
-  - dask
+  - dask < 2  #remove this once upstream problem
+              # (https://github.com/pydata/xarray/issues/3574) is fixed
   - numpy
-  - pytest
   - future
   - scipy
-  - flake8
+  - black
   - astropy
   - matplotlib
   # Necesary additions for the plotting tools (might have to make thos optional)
   - gsw
   - cartopy
   - xgcm
+  - pip
   - pip:
     - codecov
     - pytest-cov

ci/environment-py37-upstream_master.yml

@@ -0,0 +1,23 @@
+name: test_env_xarrayutils
+channels:
+  - conda-forge
+dependencies:
+  - python=3.7
+  - dask < 2 #remove this once upstream problem
+             # (https://github.com/pydata/xarray/issues/3574) is fixed
+  - numpy
+  - pytest
+  - future
+  - scipy
+  - black
+  - astropy
+  - matplotlib
+  # Necesary additions for the plotting tools (might have to make thos optional)
+  - gsw
+  - cartopy
+  - pip
+  - pip:
+    - git+https://github.com/pydata/xarray.git
+    - git+https://github.com/xgcm/xgcm.git
+    - codecov
+    - pytest-cov

ci/environment-py37.yml

@@ -1,21 +1,23 @@
-name: test_env
+name: test_env_xarrayutils
 channels:
   - conda-forge
 dependencies:
   - python=3.7
-  - xarray
-  - dask
+  - xarray < 0.14
+  - dask < 2 #remove this once upstream problem
+             # (https://github.com/pydata/xarray/issues/3574) is fixed
   - numpy
   - pytest
   - future
   - scipy
-  - flake8
+  - black
   - astropy
   - matplotlib
   # Necesary additions for the plotting tools (might have to make thos optional)
   - gsw
   - cartopy
   - xgcm
+  - pip
   - pip:
     - codecov
     - pytest-cov

ci/environment-py27.yml → ci/environment-py38.yml

@@ -1,21 +1,23 @@
-name: test_env
+name: test_env_xarrayutils
 channels:
   - conda-forge
 dependencies:
-  - python=2.7
+  - python=3.8
   - xarray
-  - dask
+  - dask < 2 #remove this once upstream problem
+             # (https://github.com/pydata/xarray/issues/3574) is fixed
   - numpy
   - pytest
   - future
   - scipy
-  - flake8
+  - black
   - astropy
   - matplotlib
   # Necesary additions for the plotting tools (might have to make thos optional)
   - gsw
   - cartopy
   - xgcm
+  - pip
   - pip:
     - codecov
     - pytest-cov

docs/Untitled.ipynb

@@ -0,0 +1,178 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Using xarrayutils to build a xgcm compatible grid for observational products\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# Still gotta figure out how to do the download clean...store on figshare as unzipped file?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import xgcm\n",
+    "from xarrayutils.build_grids import grid_aggregate,rebuild_grid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "path = '/Users/juliusbusecke/Work/CODE/PYTHON/xarrayutils/notebooks/MIMOC_ML_v2'\n",
+    "ds = xr.open_mfdataset(path+'/MIMOC_ML_v2.2_CT_SA_MLP_month*',concat_dim='month')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "ds_new = xr.Dataset(data_vars=ds.drop(['LONGITUDE','LATITUDE']).data_vars,coords={'LONG':ds.LONGITUDE.mean('month'),'LAT':ds.LATITUDE.mean('month'),'month':ds.month})\n",
+    "ds_new.LAT.attrs = {'axis':'X',\n",
+    "                    'standard_name': 'x_grid_index',\n",
+    "                    'long_name': 'x-dimension of the grid'}\n",
+    "\n",
+    "ds_new.LONG.attrs = {'axis':'Y',\n",
+    "                    'standard_name': 'y_grid_index',\n",
+    "                    'long_name': 'y-dimension of the grid'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# grid = xgcm.Grid(ds_new)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'XC'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-5-18be2f814549>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mbins\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'LONG'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'LAT'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mgrid_coarse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgrid_aggregate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds_new\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbins\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m/Users/juliusbusecke/Work/CODE/PYTHON/xarrayutils/xarrayutils/build_grids.py\u001b[0m in \u001b[0;36mgrid_aggregate\u001b[0;34m(grid, bins)\u001b[0m\n\u001b[1;32m     73\u001b[0m     \u001b[0mtemp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mff\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'XC'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'YC'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 75\u001b[0;31m         temp[ff] = xr.DataArray(da.from_array(grid[ff].data,chunks=grid[ff].shape),\n\u001b[0m\u001b[1;32m     76\u001b[0m                                 coords=grid[ff].coords,dims=grid[ff].dims)\n\u001b[1;32m     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/Users/juliusbusecke/anaconda/lib/python2.7/site-packages/xarray/core/dataset.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    697\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhashable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 698\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct_dataarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    699\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    700\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_copy_listed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/Users/juliusbusecke/anaconda/lib/python2.7/site-packages/xarray/core/dataset.pyc\u001b[0m in \u001b[0;36m_construct_dataarray\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m    640\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    641\u001b[0m             _, name, variable = _get_virtual_variable(\n\u001b[0;32m--> 642\u001b[0;31m                 self._variables, name, self._level_coords, self.dims)\n\u001b[0m\u001b[1;32m    643\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    644\u001b[0m         \u001b[0mcoords\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mOrderedDict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/Users/juliusbusecke/anaconda/lib/python2.7/site-packages/xarray/core/dataset.pyc\u001b[0m in \u001b[0;36m_get_virtual_variable\u001b[0;34m(variables, key, level_vars, dim_sizes)\u001b[0m\n\u001b[1;32m     69\u001b[0m         \u001b[0mref_var\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdim_var\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_index_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_level_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mref_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m         \u001b[0mref_var\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvariables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mref_name\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mvar_name\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'XC'"
+     ]
+    }
+   ],
+   "source": [
+    "bins = [('LONG',10),('LAT',10)]\n",
+    "grid_coarse = grid_aggregate(ds_new,bins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "out = rebuild_grid(ds_new)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "ds_new"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "grid = xgcm.Grid(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "interp_test = grid.diff(ds.ABSOLUTE_SALINITY_MIXED_LAYER,'X')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}