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Bill Ladwig
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Renamed the geobounds function since it was confusing the autosummary tool with Sphinx. Updated documentation.
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Lines changed: 765 additions & 238 deletions

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‎doc/source/_static/images/basemap_500.png‎

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‎doc/source/_static/images/basemap_front.png‎

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‎doc/source/_static/images/basemap_slp.png‎

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‎doc/source/_static/images/cartopy_500.png‎

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‎doc/source/_static/images/cartopy_cross.png‎

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‎doc/source/_static/images/cartopy_slp.png‎

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‎doc/source/_static/images/matthew.png‎

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‎doc/source/basic_usage.rst‎

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@@ -19,8 +19,8 @@ In the example below, sea level pressure is calculated and printed.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar
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@@ -78,8 +78,8 @@ NetCDF variables.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar
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@@ -141,8 +141,8 @@ The example below illustrates both.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar, disable_xarray
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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If you need to convert an :class:`xarray.DataArray` to a :class:`numpy.ndarray`,
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wrf-python provides the :meth:`wrf.npvalues` function for this purpose. Although
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wrf-python provides the :meth:`wrf.to_np` function for this purpose. Although
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an :class:`xarray.DataArary` object already contains the
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:attr:`xarray.DataArray.values` attribute to extract the Numpy array, there is a
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problem when working with compiled extensions. The behavior for xarray (and pandas)
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is to convert missing/fill values to NaN, which may cause crashes when working
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with compiled extensions. Also, some existing code may be designed to work with
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:class:`numpy.ma.MaskedArray`, and numpy arrays with NaN may not work with it.
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The :meth:`wrf.npvalues` function does the following:
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The :meth:`wrf.to_np` function does the following:
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#. If no missing/fill values are used, :meth:`wrf.npvalues` simply returns the
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#. If no missing/fill values are used, :meth:`wrf.to_np` simply returns the
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:attr:`xarray.DataArray.values` attribute.
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#. If missing/fill values are used, then :meth:`wrf.npvalues` replaces the NaN
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#. If missing/fill values are used, then :meth:`wrf.to_np` replaces the NaN
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values with the _FillValue found in the :attr:`xarray.DataArray.attrs`
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attribute (required) and a :class:`numpy.ma.MaskedArray` is returned.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar
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@@ -198,7 +198,7 @@ The :meth:`wrf.npvalues` function does the following:
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# Get the Sea Level Pressure
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cape_3d = getvar(ncfile, "cape_3d")
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cape_3d_ndarray = npvalues(cape_3d)
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cape_3d_ndarray = to_np(cape_3d)
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print(type(cape_3d_ndarray))
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@@ -229,12 +229,11 @@ function.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar, ALL_TIMES
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# Creating a simple test list with three timesteps
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wrflist = [Dataset("wrfout_d01_2016-10-07_00_00_00"),
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Dataset("wrfout_d01_2016-10-07_01_00_00"),
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar, ALL_TIMES
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from wrf import getvar, ALL_TIMES
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will be combined.
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.. code-block:: python
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar, ALL_TIMES
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from wrf import getvar, interplevel
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from netCDF4 import Dataset
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from wrf import getvar, vertcross, CoordPair
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from wrf import getvar, vertcross, CoordPair
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.. code-block:: python
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from __future__ import print_function
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from __future__ import (absolute_import, division, print_function, unicode_literals)
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from __future__ import print_function
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from wrf import getvar, interpline, CoordPair, xy_to_ll, ll_to_xy

‎doc/source/conf.py‎

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@@ -25,7 +25,7 @@ class Mock(MagicMock):
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def __getattr__(cls, name):
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MOCK_MODULES = ["numpy", "numpy.ma", "xarray",
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MOCK_MODULES = ["numpy", "numpy.ma", "xarray", "cartopy",
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"pandas", "matplotlib", "netCDF4", "mpl_toolkits.basemap",
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"wrf._wrffortran"]
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sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)

‎doc/source/new.rst‎

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v1.0a3
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-----------
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- Alpha release 3
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- Added docstrings
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- Now uses CoordPair for cross sections so that lat/lon can be used
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- Renamed some functions and or arguments
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- Alpha release 3.
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- Added docstrings.
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- The mapping API has changed.
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- The projection attributes are no longer arrays for moving domains.
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- Utility functions have been added for extracting geobounds. It is now
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easier to get map projection objects from sliced variables.
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- Utility functions have been added for getting cartopy, basemap, and pyngl
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objects.
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- Users should no longer need to use xarray attributes directly
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- Now uses CoordPair for cross sections so that lat/lon can be used instead of
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raw x,y grid coordinates.
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- Renamed npvalues to to_np which is more intuitive.
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- Fixed issue with generator expressions.
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- Renamed some functions and arguments.

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