Xclim

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This is a significant jump in the release. Many modifications have been made and will be added to the documentation in the coming days. Among the many changes:

* New indices have been added with documentation and call examples.
* Run_length based operations have been optimized.
* Support for CF non-standard calendars.
* Automated/improved unit conversion and management via pint library.
* Added ensemble utilities for creation and analysis of muti-model climate ensembles.
* Added subsetting utilities for spatio-temporal subsets of xarray data objects.
* Added streamflow indicators.
* Refactoring of the code : separation of indices.py into a directory with sub-files (simple, threshold and multivariate); ensembles and subset utilities separated into distinct modules (pulled from utils.py).
* Indicators are now split into packages named by realms. import xclim.atmos to load indicators related to atmospheric variables.

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*This was a staging release and is functionally identical to 0.7-beta*.

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Major Changes:

* Support for resampling of data structured using non-standard CF-Time calendars.
* Added several ICCLIM and other indicators.
* Dropped support for Python 3.4.
* Now under Apache v2.0 license.
* Stable PyPI-based dependencies.
* Dask optimizations for better memory management.
* Introduced class-based indicator calculations with data integrity verification and CF-Compliant-like metadata writing functionality.

Class-based indicators are new methods that allow index calculation with error-checking and provide on-the-fly metadata checks for CF-Compliant (and CF-compliant-like) data that are passed to them. When written to NetCDF, outputs of these indicators will append appropriate metadata based on the indicator, threshold values, moving window length, and time period / resampling frequency examined.

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* File attributes checks.
* Added daily downsampler function.
* Better documentation on ICCLIM indices.

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* Added total precipitation indicator.

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* Fully PEP8 compliant and available under MIT License.