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Updating docstring of a class according to PEP 257 in a file #4449

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Merged
merged 9 commits into from
Jan 31, 2021
Merged

Updating docstring of a class according to PEP 257 in a file #4449

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4d4912d
one class docs updated
ashish-hacker Jan 29, 2021
3bad6fa
Updated with docs with PEP 257 in one class
ashish-hacker Jan 29, 2021
4e9a1de
Updated with docs with PEP 257 in one class
ashish-hacker Jan 29, 2021
7636524
updated
ashish-hacker Jan 30, 2021
24d6671
update
ashish-hacker Jan 30, 2021
55b17a9
Merge branch 'master' of https://github.com/ashish-hacker/pymc3
ashish-hacker Jan 30, 2021
0c450c1
Update
ashish-hacker Jan 30, 2021
f938eb7
update
ashish-hacker Jan 30, 2021
dbdeeaa
Update pymc3/step_methods/metropolis.py
twiecki Jan 31, 2021
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36 changes: 14 additions & 22 deletions pymc3/step_methods/metropolis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,28 +95,7 @@ def __call__(self, num_draws=None):


class Metropolis(ArrayStepShared):
"""
Metropolis-Hastings sampling step

Parameters
----------
vars: list
List of variables for sampler
S: standard deviation or covariance matrix
Some measure of variance to parameterize proposal distribution
proposal_dist: function
Function that returns zero-mean deviates when parameterized with
S (and n). Defaults to normal.
scaling: scalar or array
Initial scale factor for proposal. Defaults to 1.
tune: bool
Flag for tuning. Defaults to True.
tune_interval: int
The frequency of tuning. Defaults to 100 iterations.
model: PyMC Model
Optional model for sampling step. Defaults to None (taken from context).
mode: string or `Mode` instance.
compilation mode passed to Theano functions
"""Metropolis-Hastings sampling step
"""

name = "metropolis"
Expand Down Expand Up @@ -144,6 +123,19 @@ def __init__(
mode=None,
**kwargs
):
"""Metropolis-Hastings sampling step

Arguments:
vars -- List of variables for sampler (default None)
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This looks very different from all our other doc strings which follow the numpy style guide, can you make it adhere to that?

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Oh Sorry! My bad. I will fix it right away

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Done @twiecki : )

S -- Some measure of variance to parameterize proposal distribution (default None)
proposal_dist -- Function that returns zero-mean deviates when parameterized with
S (and n). Defaults to normal. (default None)
scaling -- Initial scale factor for proposal. (default 1.0)
tune -- Flag for tuning. (default True)
tune_interval -- The frequency of tuning. (default 100)
model -- Optional model for sampling step. Defaults to None (taken from context). (default None)
mode -- compilation mode passed to Theano functions. (default None)
"""

model = pm.modelcontext(model)

Expand Down