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Only copy datetime64 data if it is using non-nanosecond precision. #125

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Only copy datetime64 data if it is using non-nanosecond precision. #125

wants to merge 17 commits into from

Commits on May 16, 2014

  1. convert array of netCDF4.datetime objects to numpy.datetime64 array t… 

    …o support virtual_variable indexing, pydata#121
    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  2. restrict the conversion of netCDF4.datetime objects to numpy.datetime… 

    …64 object to valid years (1677<time<2262)
    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  3. Handle arbitrary shape time arrays in nctime_to_nptime. Also added th… 

    …e ability to fallback to netCDF4.datetime objects since this solution does not fix the problem for all calendars in all situations.
    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  4. initial implementation of support for NetCDF groups

    @alimanfoo
    alimanfoo authored and Alex Kleeman committed May 16, 2014
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  5. cleanup fallback code a bit

    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  6. use IOError; safer recursion; don't worry about group cycles

    @alimanfoo
    alimanfoo authored and Alex Kleeman committed May 16, 2014
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  7. Require only numpy 1.7 for the benefit of readthedocs 

    ReadTheDocs comes with pre-built packages for the basic scientific python
stack, but some of these packages are old (e.g., numpy is 1.7.1). The only way
to upgrade packages on readthedocs is to use a virtual environment and a
requirements.txt.

Unfortunately, this means we can't upgrade both numpy and pandas
simultaneously, because pandas may get built first and link against the wrong
version of numpy. We inadvertantly stumbled upon a work around to build the
"latest" docs by first installing numpy in the (cached) virtual environment,
and then later (in another commit), adding pandas to the requirements.txt
file.

However, this is a real hack and makes it impossible to maintain different
versions of the docs, such as for tagged releases. Accordingly, this commit
relaxes the numpy version requirement so we can use a version that readthedocs
already has installed. (We actually don't really need a newer version of numpy
for any current functionality in xray, although it's nice to have for support
for missing value functions like nanmean.)
    @shoyer
    shoyer authored and Alex Kleeman committed May 16, 2014
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  8. simplify group access to avoid recursion; test missing group error

    @alimanfoo
    alimanfoo authored and Alex Kleeman committed May 16, 2014
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  9. Add further testing for single element time ordinals. 

    Expanded warnings for when non numpy.datetime64 arrays are returned.
Use context manager for warnings in test_conventions.py.
    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  10. filter warnings from earlier tests

    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  11. correct filter message for warnings

    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  12. add test to catch fallback warnings, insure returning a numpy array d… 

    …uring fallback of single element
    Joe Hamman authored and Alex Kleeman committed May 16, 2014
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  13. fix python 3 build; right way to test exception is raised

    @alimanfoo
    alimanfoo authored and Alex Kleeman committed May 16, 2014
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  14. Only copy datetime64 data if it is using non-nanosecond precision.

    Alex Kleeman committed May 16, 2014
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  15. Convert datetime objects to datetime64 upon variable creation in 

    an attempt to standardize time handling.

NOTE: virtual variable slicing is now broken, so do not submit.
    Alex Kleeman committed May 16, 2014
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  16. Added utils.safe_timestamp() which avoids issues when datetime[ns] 

    variables get cast to integers.
    Alex Kleeman committed May 16, 2014
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  17. Updated test_variable to deal with python 3 unicode types

    Alex Kleeman committed May 16, 2014
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