Changelog

1.3.1

General Updates

  • Added tox to serve as the unit testing infrastructure, and changed which unit tests were run (see the github actions to see what exactly is running)

  • Added tests to check future versions of numpy and astropy

  • Added back in the remote data unit tests

xarray_to_cdf

  • Added an ISTP check to determine is attribute and variable names are compliant

cdfwrite

  • Clearer error message surrounding data type conversions to CDF data types

1.3.0

General Updates

  • Added .devcontainer to support development of cdflib on github

  • Renamed the master branch to “main”

  • Added netcdf4 to the test dependencies

  • unit tests no longer test to_unixtime and from_unixtime conversions. The loss in the decimal place that occurs from floating point arithmetic causes too many issues. It may be deprecated functionality in the future.

xarray_to_cdf

  • In general, numpy types now have a 1-to-1 correspondence with CDF data types in xarray_to_cdf and cdf_to_xarray. See the documentation for more details

  • Added an ISTP check in xarray_to_cdf to verify that epochs are monotonically increasing

  • Added an ISTP check in xarray_to_cdf to determine if we need a LABL_PTR_1 or LABLAXIS

  • Added ability to manually set the CDF data type of a variable in xarray_to_cdf

  • Added checks in xarray_to_cdf to ensure all CDF_EPOCH16 variables can be cast to a complex128 data type

  • Added automatic conversion of python datetime objects to CDF time variables in xarray_to_cdf, deprecating the from_datetime and datetime_to_cdftt2000 flags

  • Added automatic conversion of numpy datetime64 arrays to CDF time variables in xarray_to_cdf, deprecating the datetime64_to_cdftt2000

  • Automatically populates the FILLVAL attribute with the appropriate ISTP compliant fillvals

  • Ignores variables attributes named “TIME_ATTRS” and “CDF_DATA_TYPE” from being written to the CDF. While these are used to modify the function’s behavior, they will no longer show up in the CDF file.

  • NaNs and NaTs will automatically be converted to the appropriate FILLVAL. To keep NaNs in the cdf file, use “nan_to_fillval=False”

cdf_to_xarray

  • To help avoid some “lossy” conversion from CDF files, cdf_to_xarray will append 2 attributes to the variables in the object created. CDF_DATA_TYPE will hold the type of CDF data the variable was if it was not obvious. TIME_ATTRS contains a list of attributes that represeted time. These attributes enable better conversion of the xarray object back to a CDF file. These attributes are also automatically ignored when writing to the CDF file.

  • fillval_to_nan will now automatically convert CDF time variables to datetime64(‘NaT’)

epochs

  • to_datetime will now give nano-second precision

  • to_datetime will return all FILLVAL, PAD VALUES, and NaNs to datetime64(‘NaT’)

  • compute(_epoch/_epoch16/_tt2000) returns 0000-01-01T00:00:00.000 for PAD VALUES, keeping with CDF standards

1.2.6

  • Fixed a bug in cdf_to_xarray that couldn’t find dimensions for a variable if there was only one record

1.2.5

  • Fixed bugs in the xarray conversion code that occured when handling numpy arrays with a length but a dimension of 0.

1.2.4

  • Added in more logging/error statements to behavior in xarray_to_cdf

1.2.3

  • xarray_to_cdf now automatically converts FILLVAL attributes to the same type of the primary variable

1.2.2

  • xarray_to_cdf now automatically converts VALIDMIN/VALIDMAX attributes to the same type of the primary variable

1.2.1

  • xarray_to_cdf now supports xarrays with datetime64 arrays

1.2.0

  • Attribute data with a single value is now returned as a Python scalar instead of a numpy array.

  • Added missing changelog entries for 1.1.1 and 1.1.2.

1.1.2

  • Fixed a minor bug when writing CDF files.

1.1.1

  • Added terminate_on_warning and auto_fix_depends options to ~cdflib.xarray.xarray_to_cdf.xarray_to_cdf. See the docstring for more info.

1.1.0

  • If the deflate library is installed it is now used to decompress data, which can lead to around 2x speedups over the native gzip Python library.

  • Fixed reading attributes with multiple entries when using cdflib.cdfread.CDF.globalattsget.

1.0.5

1.0.4

  • Fixed issue where multi-dimensional variables were dropped when converting to xarray.

  • Replaced all print and warning statements with a logger, cdflib.logging.logger.

1.0.3

  • The variable parameter to cdflib.cdfread.CDF.varattsget is no longer optional. Not specifying it raised an error anyway in previous versions of cdflib.

  • Fixed an error loading CDF files without a pad value set.

1.0.2

To make the xarray functionality easier to discover and import, a new cdflib.xarray namespace has been added. This means the recommended way to import the xarray functionality is now from cdflib.xarray import cdf_to_xarray, xarray_to_cdf

1.0.1

To keep astropy and xarray as optional dependencies, cdfastropy, cdf_to_xarray, and xarray_to_cdf are no longer available under cdflib. Instead import them from cdflib.xarray_to_cdf.xarray_to_cdf, cdflib.cdf_to_xarray.cdf_to_xarray, or cdflib.epochs_astropy.CDFAstropy.

1.0.0

Version 1.0.0 is a new major version for cdflib, and contains a number of breaking changes. These have been made to improve consistency across the package, and make it easier to maintain and build on the package going forward in the future.

Although we have tried our best to not introduce new bugs and list all changes below, some things may have slipped through the cracks. If you have any issues, please do not hesitate to open them at https://github.com/MAVENSDC/cdflib/issues.

Python support

cdflib is now only tested on Python 3.8, 3.9, 3.10, and 3.11. It may work for older versions of Python, but this is not guarenteed. If you need to use cdflib on an older version of Python, please open an issue to discuss whether the cdflib maintainers can support this.

Returning arrays

All to_np keyword arguments have been removed throughout the library, and the code now behaves as if to_np=True throughout. This change has been made to reduce code omplexity and make maintaining the code easier. If you need outputs as lists, call .tolist() on the output array.

to_np=True was the deafult in cdfread, so if you weren’t specifying it behaviour will not change there. to_np=False was the default in epochs, so if you weren’t specifying it there beahviour will change.

Changes to CDF method returns

Most of the methods that return data from the CDF reader class have had their return types changed from dictionaries to dataclasses. This allows the return type to be more clearly documented (see Dataclasses), for internal checks to be made to make sure data types are consistent, and a nicer representation when the return values are printed.

Where previously an item would have been accessed as dict["value"], items in the dataclasses can be accessed using dataclass.value.

The methods that have been updated are:

Other breaking changes

  • The CDF factory class (cdflib.CDF) has been removed, and cdflib.CDF is now the reader class. This change has been made to prevent potential confusion when the user makes a mistake in specifying the file to open, and cdflib would silently create a writer class instead. If you want to create a CDF writer class, explicitly import cdflib.cdfwrite.CDF instead.

  • cdflib.cdfread.CDF.varget no longer takes an inq argument. Instead use the new method cdflib.cdfread.CDF.vdr_info to get the VDR info.

  • getVersion() methods have been removed throughout the package. Instead the CDF version can be read from class attributes.

  • Removed cdflib.cdfepochs.CDFepoch.getLeapSecondLastUpdated. Directly inspect CDFepoch.LTS instead to get the last date at which a leapsecond was added.

  • The expand keyword argument to cdflib.cdfread.CDF.varget has been removed. Use CDF.varinq to get variable information instead.

  • The expand keyword argument to CDF.globalattsget and CDF.varattsget has been removed. Use cdflib.cdfread.CDF.attinq to get attribute information instead.

  • Removed CDF.print_attrs

  • The version, release, and increement attributes of CDF have been removed.

  • Removed the record_range_only argument to cdflib.cdfread.CDF.varget.

  • Removed CDF.epochrange. Use cdflib.cdfread.CDF.varinq instead to get the data ranges.

New features

  • Type hints have been added across the majority of the package.

Bugfixes

  • "Majority" is now correctly read from the CDF spec if present.