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Releases: pydata/xarray

v0.3.2

19 Feb 19:39
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This release focused on bug-fixes, speedups and resolving some niggling inconsistencies.

There are a few cases where the behavior of xray differs from the previous version. However, I expect that in almost all cases your code will continue to run unmodified.

xray now requires pandas v0.15.0 or later. This was necessary for supporting TimedeltaIndex without too many painful hacks.

Backwards incompatible changes:

  • Arrays of datetime.datetime objects are now automatically cast to datetime64[ns] arrays when stored in an xray object, using machinery borrowed from pandas:

    In [1]: from datetime import datetime
    
    In [2]: xray.Dataset({'t': [datetime(2000, 1, 1)]})
    Out[2]: 
    <xray.Dataset>
    Dimensions:  (t: 1)
    Coordinates:
      * t        (t) datetime64[ns] 2000-01-01
    Variables:
        *empty*
    
  • xray now has support (including serialization to netCDF) for pandas.TimedeltaIndex. datetime.timedelta objects are thus accordingly cast to timedelta64[ns] objects when appropriate.

  • Masked arrays are now properly coerced to use NaN as a sentinel value.

Enhancements:

  • Due to popular demand, we have added experimental attribute style access as a shortcut for dataset variables, coordinates and attributes:

    In [3]: ds = xray.Dataset({'tmin': ([], 25, {'units': 'celcius'})})
    
    In [4]: ds.tmin.units
    Out[4]: 'celcius'
    

    Tab-completion for these variables should work in editors such as IPython. However, setting variables or attributes in this fashion is not yet supported because there are some unresolved ambiguities.

  • You can now use a dictionary for indexing with labeled dimensions. This provides a safe way to do assignment with labeled dimensions:

    In [5]: array = xray.DataArray(np.zeros(5), dims=['x'])
    
    In [6]: array[dict(x=slice(3))] = 1
    
    In [7]: array
    Out[7]: 
    <xray.DataArray (x: 5)>
    array([ 1.,  1.,  1.,  0.,  0.])
    Coordinates:
      * x        (x) int64 0 1 2 3 4
    
  • Non-index coordinates can now be faithfully written to and restored from netCDF files. This is done according to CF conventions when possible by using the coordinates attribute on a data variable. When not possible, xray defines a global coordinates attribute.

  • Preliminary support for converting xray.DataArray objects to and from CDAT cdms2 variables.

  • We sped up any operation that involves creating a new Dataset or DataArray (e.g., indexing, aggregation, arithmetic) by a factor of 30 to 50%. The full speed up requires cyordereddict to be installed.

Bug fixes:

  • Fix for to_dataframe() with 0d string/object coordinates
  • Fix for to_netcdf with 0d string variable
  • Fix writing datetime64 arrays to netcdf if NaT is present
  • Fix align silently upcasts data arrays when NaNs are inserted

v0.3.1

23 Oct 06:31
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This is mostly a bug-fix release to make xray compatible with the latest release of pandas (v0.15).

We added several features to better support working with missing values and exporting xray objects to pandas. We also reorganized the internal API for serializing and deserializing datasets, but this change should be almost entirely transparent to users.

Other than breaking the experimental DataStore API, there should be no backwards incompatible changes.

New features:

  • Added count and dropna methods, copied from pandas, for working with missing values.
  • Added DataArray.to_pandas for
    converting a data array into the pandas object with the same dimensionality
    (1D to Series, 2D to DataFrame, etc.).
  • Support for reading gzipped netCDF3 files.
  • Reduced memory usage when writing netCDF files.
  • 'missing_value' is now supported as an alias for the '_FillValue' attribute
    on netCDF variables.
  • Trivial indexes, equivalent to range(n) where n is the length of the
    dimension, are no longer written to disk.

Bug fixes:

  • Compatibility fixes for pandas v0.15.
  • Fixes for display and indexing of NaT (not-a-time).
  • Fix slicing by label was an argument is a data array.
  • Test data is now shipped with the source distribution.
  • Ensure order does not matter when doing arithmetic with scalar data arrays.
  • Order of dimensions preserved with DataArray.to_dataframe.

v0.3

22 Sep 05:10
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New features:

  • Revamped coordinates: "coordinates" now refer to all arrays that are not
    used to index a dimension. Coordinates are intended to allow for keeping track
    of arrays of metadata that describe the grid on which the points in "variable"
    arrays lie. They are preserved (when unambiguous) even though mathematical
    operations.
  • Dataset math xray.Dataset objects now support all arithmetic
    operations directly. Dataset-array operations map across all dataset
    variables; dataset-dataset operations act on each pair of variables with the
    same name.
  • GroupBy math: This provides a convenient shortcut for normalizing by the
    average value of a group.
  • The dataset __repr__ method has been entirely overhauled; dataset
    objects now show their values when printed.
  • You can now index a dataset with a list of variables to return a new dataset:
    ds[['foo', 'bar']].

Backwards incompatible changes:

  • Dataset.__eq__ and Dataset.__ne__ are now element-wise operations
    instead of comparing all values to obtain a single boolean. Use the method
    Dataset.equals instead.

Deprecations:

  • Dataset.noncoords is deprecated: use Dataset.vars instead.
  • Dataset.select_vars deprecated: index a Dataset with a list of
    variable names instead.
  • DataArray.select_vars and DataArray.drop_vars deprecated: use
    DataArray.reset_coords instead.

v0.2

14 Aug 20:02
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This is major release that includes some new features and quite a few bug
fixes. Here are the highlights:

  • There is now a direct constructor for DataArray objects, which makes it
    possible to create a DataArray without using a Dataset. This is highlighted
    in the refreshed tutorial.
  • You can perform aggregation operations like mean directly on
    xray.Dataset objects, thanks to Joe Hamman. These aggregation
    methods also worked on grouped datasets.
  • xray now works on Python 2.6, thanks to Anna Kuznetsova.
  • A number of methods and attributes were given more sensible (usually shorter)
    names: labeled -> sel, indexed -> isel, select ->
    select_vars, unselect -> drop_vars, dimensions -> dims,
    coordinates -> coords, attributes -> attrs.
  • New Dataset.load_data and Dataset.close methods for datasets facilitate lower level of control of data loaded from disk.

v0.2.0alpha

01 Jul 23:08
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v0.2.0alpha Pre-release
Pre-release
Tag v0.2.0alpha for py 2.6 compat

v0.1.1

01 Jul 23:09
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xray 0.1.1 is a bug-fix release that includes changes that should be almost
entirely backwards compatible with v0.1:

  • Python 3 support (#53)
  • Required numpy version relaxed to 1.7 (#129)
  • Return numpy.datetime64 arrays for non-standard calendars (#126)
  • Support for opening datasets associated with NetCDF4 groups (#127)
  • Bug-fixes for concatenating datetime arrays (#134)

Special thanks to new contributors Thomas Kluyver, Joe Hamman and Alistair
Miles.

v0.1

01 Jul 23:09
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Initial release