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Drop nuts init method from pm.sample #3863

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Mar 31, 2020
Merged

Drop nuts init method from pm.sample #3863

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3b35141
Dropped nuts init method
AlexAndorra Mar 31, 2020
5fe3caa
Dropped nuts init method from tests
AlexAndorra Mar 31, 2020
43e6411
Refined doc string and added release note
AlexAndorra Mar 31, 2020
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1 change: 1 addition & 0 deletions RELEASE-NOTES.md
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Expand Up @@ -18,6 +18,7 @@
- Deprecated `sd` in version 3.7 has been replaced by `sigma` now raises `DepreciationWarning` on using `sd` in continuous, mixed and timeseries distributions. (see #3837 and #3688).
- In named models, `pm.Data` objects now get model-relative names (see [#3843](https://github.com/pymc-devs/pymc3/pull/3843)).
- `pm.sample` now takes 1000 draws and 1000 tuning samples by default, instead of 500 previously (see [#3855](https://github.com/pymc-devs/pymc3/pull/3855)).
- Dropped the outdated 'nuts' initialization method for `pm.sample` (see [#3863](https://github.com/pymc-devs/pymc3/pull/3863)).

## PyMC3 3.8 (November 29 2019)

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16 changes: 2 additions & 14 deletions pymc3/sampling.py
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Expand Up @@ -274,16 +274,14 @@ def sample(
* advi: Run ADVI to estimate posterior mean and diagonal mass matrix.
* advi_map: Initialize ADVI with MAP and use MAP as starting point.
* map: Use the MAP as starting point. This is discouraged.
* nuts: Run NUTS and estimate posterior mean and mass matrix from the trace.
* adapt_full: Adapt a dense mass matrix using the sample covariances
step: function or iterable of functions
A step function or collection of functions. If there are variables without step methods,
step methods for those variables will be assigned automatically. By default the NUTS step
method will be used, if appropriate to the model; this is a good default for beginning
users.
n_init: int
Number of iterations of initializer. Only works for 'nuts' and 'ADVI'.
If 'ADVI', number of iterations, if 'nuts', number of draws.
Number of iterations of initializer. Only works for 'ADVI' init methods.
start: dict, or array of dict
Starting point in parameter space (or partial point)
Defaults to ``trace.point(-1))`` if there is a trace provided and model.test_point if not
Expand Down Expand Up @@ -1865,14 +1863,11 @@ def init_nuts(
* advi: Run ADVI to estimate posterior mean and diagonal mass matrix.
* advi_map: Initialize ADVI with MAP and use MAP as starting point.
* map: Use the MAP as starting point. This is discouraged.
* nuts: Run NUTS and estimate posterior mean and mass matrix from
the trace.
* adapt_full: Adapt a dense mass matrix using the sample covariances
chains: int
Number of jobs to start.
n_init: int
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I think n_init is only used for advi now, right? COuld make that clear in the doc string.

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Done

Number of iterations of initializer
If 'ADVI', number of iterations, if 'nuts', number of draws.
Number of iterations of initializer. Only works for 'ADVI' init methods.
model: Model (optional if in ``with`` context)
progressbar: bool
Whether or not to display a progressbar for advi sampling.
Expand Down Expand Up @@ -2001,13 +1996,6 @@ def init_nuts(
cov = pm.find_hessian(point=start)
start = [start] * chains
potential = quadpotential.QuadPotentialFull(cov)
elif init == "nuts":
init_trace = pm.sample(
draws=n_init, step=pm.NUTS(), tune=n_init // 2, random_seed=random_seed
)
cov = np.atleast_1d(pm.trace_cov(init_trace))
start = list(np.random.choice(init_trace, chains))
potential = quadpotential.QuadPotentialFull(cov)
elif init == "adapt_full":
start = [model.test_point] * chains
mean = np.mean([model.dict_to_array(vals) for vals in start], axis=0)
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3 changes: 1 addition & 2 deletions pymc3/tests/test_sampling.py
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Expand Up @@ -87,7 +87,7 @@ def test_sample(self):

def test_sample_init(self):
with self.model:
for init in ("advi", "advi_map", "map", "nuts"):
for init in ("advi", "advi_map", "map"):
pm.sample(
init=init,
tune=0,
Expand Down Expand Up @@ -675,7 +675,6 @@ def test_sample_posterior_predictive_w(self):
"advi+adapt_diag_grad",
"map",
"advi_map",
"nuts",
],
)
def test_exec_nuts_init(method):
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