- Release 1.2.0
- Previous versions of wrf-python promoted the strings used in xarray (e.g. name, attributes) to Unicode strings for Python 2.7. This caused problems when porting examples for PyNGL to use wrf-python in Python 3.x. All strings are now the native string type for the Python version being used. While this change should be transparent to most users, any users that worked with the xarray name or attribute values on Python 2.7 may run in to string related errors, so we’ve decided to bump the major version number.
- Release 1.1.3
- Fixed/Enhanced the cloud top temperature diagnostic.
- Optical depth was not being calculated correctly when cloud ice mixing ratio was not available.
- Fixed an indexing bug that caused crashes on Windows, but should have been crashing on all platforms.
- Users can now specify if they want cloud free regions to use fill values, rather than the default behavior of using the surface temperature.
- Users can now specify the optical depth required to trigger the cloud top temperature calculation. However, the default value of 1.0 should be sufficient for most users.
- Added ‘th’ alias for the theta product.
- Fixed a crash issue related to updraft helicity when a dictionary is used as the input.
- Dictionary inputs now work correctly with xy_to_ll and ll_to_xy.
- The cape_2d diagnostic can now work with a single column of data, just like cape_3d.
- Release 1.1.2
- Fix OpenMP directive issue with cloud top temperature.
- 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.
- Release 1.1.0
- Computational routines now support multiple cores using OpenMP. See Using OpenMP 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!).
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
wrf.getvar()to avoid naming conflicts with the raw computational routine names. Users should be using
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 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.
- Release 1.0.5
- Reduced the CI test file sizes by half.
- Release 1.0.4
- Fix warnings with CI tests which were caused by fill values being written as NaN to the NetCDF result file.
- Added the __eq__ operator to the WrfProj projection base class.
- Fixed array order issue when using the raw CAPE routine with 1D arrays.
- Relase 1.0.3
- Fixed an issue with the cartopy Mercator subclass where the xlimits were being calculated to the same value (or very close), causing blank plots.
- Release 1.0.2
- Fixed issue with the wspd_wdir product types when sequences of files are used.
- Release 1.0.1
- Fixed issue with initialization of PolarStereographic and LatLon map projection objects.
- Fixed issue where XTIME could be included in the coordinate list of a variable, but the actual XTIME variable could be missing. NCL allows this, so wrf-python should as well.
- Release 1.0.0.
- Fixed issue with not being able to set the thread-local coordinate cache to 0 to disable it. Also, the cache will now correctly resize itself when the size is reduced to less than its current setting.
- Fixed an issue with the ‘0000-00-00 00:00:00’ time used in geo_em files causing crashes due to the invalid time. The time is now set to numpy.datetime64(‘NaT’).
- Fixed issue with wrf.cape_3d not working correctly with a single column of data.
- Beta release 3.
- Improvements made for conda-forge integration testing.
- Fixed an incorrectly initialized variable issue with vinterp. This issue mainly impacts the unit tests for continuous integration testing with conda-forge, since the data set used for these tests is heavily cropped.
- Back-ported the inspect.BoundArguments.apply_defaults so that Python 3.4 works. Windows users that want to try out wrf-python with Python 3.4 can use the bladwig conda channel to get it.
- Beta release 2.
- xarray 0.9 no longer includes default index dimensions in the coordinate mappings. This was causing a crash in the routines that cause a reduction in dimension shape, mainly the interpolation routines. This has been fixed.
- Documentation updated to show the new output from xarray.
- Beta release 1.
- Added more packaging boilerplate.
- Note: Currently unable to build with Python 3.5 on Windows, due to issues with distutils, numpy distutils, and mingw compiler. Will attempt to find a workaround before the next release. Windows users should use Python 2.7 or Python 3.4 for now.
- Alpha release 3.
- Added docstrings.
- The mapping API has changed.
- The projection attributes are no longer arrays for moving domains.
- Utility functions have been added for extracting geobounds. It is now easier to get map projection objects from sliced variables.
- Utility functions have been added for getting cartopy, basemap, and pyngl objects.
- Users should no longer need to use xarray attributes directly
- Now uses CoordPair for cross sections so that lat/lon can be used instead of raw x,y grid coordinates.
- Renamed npvalues to to_np which is more intuitive.
- Fixed issue with generator expressions.
- Renamed some functions and arguments.
- Currently unable to build on Windows with Python 3.5+ using open source mingw compiler. The mingwpy project is working on resolving the incompatibilities between mingw and Visual Studio 2015 that was used to build Python 3.5+. Numpy 1.13 also has improved f2py support for Python 3.5+ on Windows, so this will be revisited when it is released.