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Update io pystan #1585

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merged 5 commits into from
Mar 4, 2021
Merged

Update io pystan #1585

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ef3b4c2
update io_pystan.py to follow schema convention
madhucharan Feb 26, 2021
f6fc67c
refactor io_pystan.py
madhucharan Feb 26, 2021
6f17a04
update CHANGELOG.md
madhucharan Feb 26, 2021
a8dc57d
remove lp from rename dict and refactor the function
madhucharan Feb 28, 2021
b97585a
Merge branch 'main' into update_io_pystanpy
ahartikainen Mar 4, 2021
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
* Integrate `index_origin` with all the library ([1201](https://github.com/arviz-devs/arviz/pull/1201))
* Fix pareto k threshold typo in reloo function ([1580](https://github.com/arviz-devs/arviz/pull/1580))
* Preserve shape from Stan code in `from_cmdstanpy` ([1579](https://github.com/arviz-devs/arviz/pull/1579))
* Updated `from_pystan` converters to follow schema convention ([1585](https://github.com/arviz-devs/arviz/pull/1585)
* Used generator instead of list wherever possible ([1588](https://github.com/arviz-devs/arviz/pull/1588))
* Correctly use chain index when constructing PyMC3 `DefaultTrace` in `from_pymc3` ([1590](https://github.com/arviz-devs/arviz/pull/1590))

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25 changes: 20 additions & 5 deletions arviz/data/io_pystan.py
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Expand Up @@ -627,6 +627,14 @@ def get_sample_stats(fit, warmup=False):
"""Extract sample stats from PyStan fit."""
dtypes = {"divergent__": bool, "n_leapfrog__": np.int64, "treedepth__": np.int64}

rename_dict = {
"divergent": "diverging",
"n_leapfrog": "n_steps",
"treedepth": "tree_depth",
"stepsize": "step_size",
"accept_stat": "acceptance_rate",
}

ndraws_warmup = fit.sim["warmup2"]
if max(ndraws_warmup) == 0:
warmup = False
Expand All @@ -653,17 +661,16 @@ def get_sample_stats(fit, warmup=False):
dtype = dtypes.get(key)
values = values.astype(dtype)
name = re.sub("__$", "", key)
name = "diverging" if name == "divergent" else name
name = rename_dict.get(name, name)
data[name] = values

data_warmup = OrderedDict()
if warmup:
for key, values in extraction_warmup.items():
values = np.stack(values, axis=0)
dtype = dtypes.get(key)
values = values.astype(dtype)
values = values.astype(dtypes.get(key))
name = re.sub("__$", "", key)
name = "diverging" if name == "divergent" else name
name = rename_dict.get(name, name)
data_warmup[name] = values

return data, data_warmup
Expand Down Expand Up @@ -773,6 +780,14 @@ def get_sample_stats_stan3(fit, variables=None, ignore=None):
"""Extract sample stats from PyStan3 fit."""
dtypes = {"divergent__": bool, "n_leapfrog__": np.int64, "treedepth__": np.int64}

rename_dict = {
"divergent": "diverging",
"n_leapfrog": "n_steps",
"treedepth": "tree_depth",
"stepsize": "step_size",
"accept_stat": "acceptance_rate",
}

if isinstance(variables, str):
variables = [variables]
if isinstance(ignore, str):
Expand All @@ -789,7 +804,7 @@ def get_sample_stats_stan3(fit, variables=None, ignore=None):
dtype = dtypes.get(key)
values = values.astype(dtype)
name = re.sub("__$", "", key)
name = "diverging" if name == "divergent" else name
name = rename_dict.get(name, name)
data[name] = values

return data
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