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Remove auto argument from pm.Deterministic docstring #6592

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merged 4 commits into from
Mar 14, 2023
Merged

Remove auto argument from pm.Deterministic docstring #6592

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b5fa488
Remove auto argument from Deterministic
shreyas3156 Mar 11, 2023
dfa2599
Add missing arguments in the deterministic docstring as per numpydoc …
shreyas3156 Mar 12, 2023
605e2e7
Add missing arguments in the Potential docstring
shreyas3156 Mar 12, 2023
3298083
Add spaces around colons
michaelosthege Mar 12, 2023
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36 changes: 22 additions & 14 deletions pymc/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1967,6 +1967,25 @@ def Deterministic(name, var, model=None, dims=None):
they don't add randomness to the model. They are generally used to record
an intermediary result.

Parameters
----------
name : str
Name of the deterministic variable to be registered in the model.
var : tensor_like
Expression for the calculation of the variable.
model : Model, optional
The model object to which the Deterministic variable is added.
If ``None`` is provided, the current model in the context stack is used.
dims : str or tuple of str, optional
Dimension names for the variable.

Returns
-------
var : tensor_like
The registered, named variable wrapped in Deterministic.

Examples
--------
Indeed, PyMC allows for arbitrary combinations of random variables, for
example in the case of a logistic regression

Expand Down Expand Up @@ -2007,19 +2026,6 @@ def Deterministic(name, var, model=None, dims=None):
of times during a NUTS step, the Deterministic quantities are just
computeed once at the end of the step, with the final values of the other
random variables.

Parameters
----------
name: str
var: PyTensor variables
auto: bool
Add automatically created deterministics (e.g., when imputing missing values)
to a separate model.auto_deterministics list for filtering during sampling.


Returns
-------
var: var, with name attribute
"""
model = modelcontext(model)
var = var.copy(model.name_for(name))
Expand Down Expand Up @@ -2059,7 +2065,9 @@ def Potential(name, var, model=None, dims=None):
Expression to be added to the model joint logp.
model : Model, optional
The model object to which the potential function is added.
If ``None`` is provided, the current model is used.
If ``None`` is provided, the current model in the context stack is used.
dims : str or tuple of str, optional
Dimension names for the variable.

Returns
-------
Expand Down