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Censor & Truncate Docstrings #7590

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Censor & Truncate Docstrings #7590

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03764d0
int and array-like typing
RyanAugust Nov 26, 2024
685dcd0
example with partial censor
RyanAugust Nov 26, 2024
eb31d65
int typing for Truncated
RyanAugust Nov 26, 2024
578808b
Truncated partial example
RyanAugust Nov 26, 2024
f070e88
example breakout for partial censor + trunc strategies
RyanAugust Nov 26, 2024
50948b4
strip whitespace
RyanAugust Nov 26, 2024
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13 changes: 11 additions & 2 deletions pymc/distributions/censored.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,9 +84,9 @@ class Censored(Distribution):

.. warning:: dist will be cloned, rendering it independent of the one passed as input.

lower : float or None
lower : float, int, array-like or None
Lower (left) censoring point. If `None` the distribution will not be left censored
upper : float or None
upper : float, int, array-like or None
Upper (right) censoring point. If `None`, the distribution will not be right censored.

Warnings
Expand All @@ -101,11 +101,20 @@ class Censored(Distribution):

Examples
--------
Censoring with upper & lower points set to +/-1
.. code-block:: python

with pm.Model():
normal_dist = pm.Normal.dist(mu=0.0, sigma=1.0)
censored_normal = pm.Censored("censored_normal", normal_dist, lower=-1, upper=1)

Partial censoring of normal distributions achienved by passing +/-inf censor points.
Examples of 4 censor conditions: uncensored (-inf, inf), upper censored (-inf, 1),
Comment on lines +111 to +112
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First emphasize that censoring bounds can change across dimensions of the variable, and then enumerate the examples. If they don't change, one can use None as upper or lower, not only +/-np.inf

lower censored (-1, inf), and both censored (-1, 1)
.. code-block:: python
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I think you need to leave a blank line between the description and the code example for it to render correctly: https://pymcio--7590.org.readthedocs.build/projects/docs/en/7590/api/distributions/censored.html

Before: https://www.pymc.io/projects/docs/en/stable/api/distributions/censored.html

with pm.Model():
normal_dist = pm.Normal.dist(mu=0.0, sigma=1.0)
partially_censored_normals = pm.Censored("partially_censored_normals", normal_dist, lower=[-np.inf, -np.inf, -1, -1], upper=[np.inf, 1, np.inf, 1], shape=(4,))
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@ricardoV94 ricardoV94 Nov 27, 2024 •
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make it multiple line so it renders nicely in the docs: https://pymcio--7590.org.readthedocs.build/projects/docs/en/7590/api/distributions/censored.html

The name is probably too long

"""

rv_type = CensoredRV
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12 changes: 10 additions & 2 deletions pymc/distributions/truncated.py
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Expand Up @@ -266,9 +266,9 @@ class Truncated(Distribution):

.. warning:: dist will be cloned, rendering it independent of the one passed as input.

lower: tensor_like of float or None
lower: tensor_like of float, int, or None
Lower (left) truncation point. If `None` the distribution will not be left truncated.
upper: tensor_like of float or None
upper: tensor_like of float, int, or None
Upper (right) truncation point. If `None`, the distribution will not be right truncated.
max_n_steps: int, defaults 10_000
Maximum number of resamples that are attempted when performing rejection sampling.
Expand All @@ -285,12 +285,20 @@ class Truncated(Distribution):

Examples
--------
Truncation with upper & lower points set to +/-1
.. code-block:: python

with pm.Model():
normal_dist = pm.Normal.dist(mu=0.0, sigma=1.0)
truncated_normal = pm.Truncated("truncated_normal", normal_dist, lower=-1, upper=1)

Partial truncatin of normal distributions achieved by passing +/-inf truncation points.
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Suggested change
Partial truncatin of normal distributions achieved by passing +/-inf truncation points.
Partial truncation of normal distributions achieved by passing +/-inf truncation points.

Examples of 4 truncation conditions: untruncated (-inf, inf), upper truncated (-inf, 1),
lower truncated (-1, inf), and both truncated (-1, 1)
.. code-block:: python
with pm.Model():
normal_dist = pm.Normal.dist(mu=0.0, sigma=1.0)
partially_truncated_normal = pm.Truncated("partially_truncated_normal", normal_dist, lower=[-np.inf, -np.inf, -1, -1], upper=[np.inf, 1, np.inf, 1], shape=(4,))
"""

rv_type = TruncatedRV
Expand Down