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Added example for concat method #1037

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Feb 10, 2020
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Added example for concat method #1037

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Added example for concat method
percygautam Jan 29, 2020
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Changes to changelog
percygautam Jan 29, 2020
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Minor changes
percygautam Feb 1, 2020
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percygautam Feb 3, 2020
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Merge branch 'master' into docs_concat
percygautam Feb 10, 2020
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percygautam Feb 10, 2020
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added example of concat over chain/draw
percygautam Feb 10, 2020
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5 changes: 2 additions & 3 deletions CHANGELOG.md
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Expand Up @@ -23,11 +23,10 @@
### Documentation
* Updated `InferenceData` schema specification (`log_likelihood`,
`predictions` and `predictions_constant_data` groups)
* Clarify the usage of "plot_joint" (#1001)
* Added the API link of function to examples (#1013)
* Clarify the usage of "plot_joint" (#1001)
* Clarify the usage of `plot_joint` (#1001)
* Added the API link of function to examples (#1013)
* Updated PyStan_schema_example to include example of out-of-sample prediction (#1032)
* Added example for `concat` method (#1037)


## v0.6.1 (2019 Dec 28)
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40 changes: 40 additions & 0 deletions arviz/data/inference_data.py
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Expand Up @@ -252,6 +252,46 @@ def concat(*args, dim=None, copy=True, inplace=False, reset_dim=True):
InferenceData
A new InferenceData object by default.
When `inplace==True` merge args to first arg and return `None`

Examples
--------
Use ``concat`` method to concatenate InferenceData objects. This will concatenates over
unique groups by default. We first create an InferenceData object:
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.. ipython::

In [1]: import arviz as az
...: import numpy as np
...: import xarray as xr
...: dataset = xr.Dataset(
...: {
...: "a": (["chain", "draw", "a_dim"], np.random.normal(size=(4, 100, 3))),
...: "b": (["chain", "draw"], np.random.normal(size=(4, 100))),
...: },
...: coords={
...: "chain": (["chain"], np.arange(4)),
...: "draw": (["draw"], np.arange(100)),
...: "a_dim": (["a_dim"], ["x", "y", "z"]),
...: }
...: )
...: dataA = az.convert_to_inference_data(dataset)
...: dataA

We have created an ``InferenceData`` object with default group 'posterior'. Now we will
create another InferenceData object:
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.. ipython::

In [1]: dataB = az.convert_to_inference_data(dataset, group = "prior")
...: dataB

We have created another ``InferenceData`` object with group 'prior'. Now we will concatenate
these two ``InferenceData`` objects:

.. ipython::

In [1]: az.concat(dataA, dataB)
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"""
# pylint: disable=undefined-loop-variable, too-many-nested-blocks
if len(args) == 0:
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