Release 1.1.1
- Added script for building on Cheyenne with maxed out Intel settings, which
also required a patch for numpy.distutils.
- Fixed a few unicode characters hiding in a docstring that were causing
problems on Cheyenne, and also building the docs with Sphinx on Python 2.x.
- Fix issue with np.amax not working with xarray on Cheyenne, causing an error
with the mdbz product.
- Fix cape_2d private variable bug when running with multiple CPUs.
- Computational routines now support multiple cores using OpenMP. See
:ref:`using_omp` for details on how to use this new feature.
- The CAPE routines should be noticeably faster, even in the single threaded
case (thank you supreethms1809!).
- :meth:`wrf.getvar` now works correctly with non-gridded NetCDF variables
- The cloud fraction diagnostic has changed:
- Users can now select their own cloud threshold levels, and can choose
between a vertical coordinate defined as height (AGL), height (MSL), or
pressure.
- The default vertical coordinate type has been changed to be height (AGL).
This ensures that clouds appear over mountainous regions. If you need
the old behavior, set the *vert_type* argument to 'pressure'.
- Fixed a bug involving the cloud threshold search algorithm, where if the
surface was higher than the threshold for a cloud level, the algorithm
would use whatever was there before (uninitialized variable bug). This
caused some interesting visualization issues when plotted. Now, whenever
the surface is above a cloud level threshold, a fill value is used to
indicate that data is unavailable for that location.
- The cartopy object for LambertConformal should now work correctly in the
southern hemisphere.
- Fixed a bug with the PolarStereographic projection missing a geobounds
argument (thank you hanschen!).
- Renamed the modules containing the 'get_product' routines used
by :meth:`wrf.getvar` to avoid naming conflicts with the raw computational
routine names. Users should be using :meth:`wrf.getvar` instead of these
routines, but for those that imported the 'get_product' routines
directly, you will need to modify your code.
- Fixed a uniqueness issue with the internal coordinate cache that was causing
crashes when input data is changed to a different file in a jupyter notebook
cell.
- Added code to better support building wheels on Windows (thank you letmaik!)
- Improved support for scipy.io.netcdf objects.
- Added a new 'zstag' diagnostic that returns the height values for the
vertically staggered grid.
- A DOI is now available for wrf-python. Please cite wrf-python if you are
using it for your research. (See :ref:`citation`)
- Fixed issue with vertcross and interpline not working correctly when a
projection object is used. Users will now have to supply the lower left
latitude and longitude corner point.
- Beginning with numpy 1.14, wrf-python can be built using the MSVC
compiler with gfortran. WRF-Python can now be built for Python 3.5+ on
services like AppVeyor.
Since the size of OpenMP constants differs from system to system, there is now a fortran program that will print the KIND sizes, and the ompgen.F90 file is generated by python using a string template. This only needs to be performed if using OpenMP.
Version 1.1.0
- Release 1.1.0
- Computational routines now support multiple cores using OpenMP. See
:ref:`using_omp` for details on how to use this new feature.
- The CAPE routines should be noticeably faster, even in the single threaded
case (thank you supreethms1809!).
- :meth:`wrf.getvar` now works correctly with non-gridded NetCDF variables
- The cloud fraction diagnostic has changed:
- Users can now select their own cloud threshold levels, and can choose
between a vertical coordinate defined as height (AGL), height (MSL), or
pressure.
- The default vertical coordinate type has been changed to be height (AGL).
This ensures that clouds appear over mountainous regions. If you need
the old behavior, set the *vert_type* argument to 'pressure'.
- Fixed a bug involving the cloud threshold search algorithm, where if the
surface was higher than the threshold for a cloud level, the algorithm
would use whatever was there before (uninitialized variable bug). This
caused some interesting visualization issues when plotted. Now, whenever
the surface is above a cloud level threshold, a fill value is used to
indicate that data is unavailable for that location.
- The cartopy object for LambertConformal should now work correctly in the
southern hemisphere.
- Fixed a bug with the PolarStereographic projection missing a geobounds
argument (thank you hanschen!).
- Renamed the modules containing the 'get_product' routines used
by :meth:`wrf.getvar` to avoid naming conflicts with the raw computational
routine names. Users should be using :meth:`wrf.getvar` instead of these
routines, but for those that imported the 'get_product' routines
directly, you will need to modify your code.
- Fixed a uniqueness issue with the internal coordinate cache that was causing
crashes when input data is changed to a different file in a jupyter notebook
cell.
- Added code to better support building wheels on Windows (thank you letmaik!)
- Improved support for scipy.io.netcdf objects.
- Added a new 'zstag' diagnostic that returns the height values for the
vertically staggered grid.
- A DOI is now available for wrf-python. Please cite wrf-python if you are
using it for your research. (See :ref:`citation`)
- Fixed issue with vertcross and interpline not working correctly when a
projection object is used. Users will now have to supply the lower left
latitude and longitude corner point.
- Beginning with numpy 1.14, wrf-python can be built using the MSVC
compiler with gfortran. WRF-Python can now be built for Python 3.5+ on
services like AppVeyor.
Also added some helper functions to extract the lower left points from 2D lat/lon arrays and extract lat/lons from sequences of CoordPair objects.
Updated documentation and unit tests.
Bill Ladwig