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chore: [pre-commit.ci] pre-commit autoupdate (#2343)
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* Update pre-commit hooks:
   - github.com/astral-sh/ruff-pre-commit: v0.0.287 → v0.0.292
   - github.com/psf/black-pre-commit-mirror: 23.7.0 → 23.9.1
   - github.com/codespell-project/codespell: v2.2.5 → v2.2.6
* Apply typo fixes from codespell.
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pre-commit-ci[bot] authored Oct 3, 2023
1 parent 976eec1 commit 6ebf9a3
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Showing 8 changed files with 15 additions and 15 deletions.
8 changes: 4 additions & 4 deletions .pre-commit-config.yaml
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Expand Up @@ -27,13 +27,13 @@ repos:
exclude: ^validation/|\.dtd$|\.xml$

- repo: https://github.com/astral-sh/ruff-pre-commit
rev: "v0.0.287"
rev: "v0.0.292"
hooks:
- id: ruff
args: ["--fix", "--show-fixes"]

- repo: https://github.com/psf/black-pre-commit-mirror
rev: 23.7.0
rev: 23.9.1
hooks:
- id: black-jupyter

Expand Down Expand Up @@ -62,11 +62,11 @@ repos:
rev: 1.7.0
hooks:
- id: nbqa-ruff
additional_dependencies: [ruff==0.0.287]
additional_dependencies: [ruff==0.0.292]
args: ["--extend-ignore=F821,F401,F841,F811"]

- repo: https://github.com/codespell-project/codespell
rev: v2.2.5
rev: v2.2.6
hooks:
- id: codespell
files: ^.*\.(py|md|rst)$
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2 changes: 1 addition & 1 deletion docs/faq.rst
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Expand Up @@ -141,7 +141,7 @@ How did ``pyhf`` get started?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In 2017 Lukas Heinrich was discussing with colleauge Holger Schulz how it would be convenient
to share and produce statistical results from LHC experiements if they were able to be
to share and produce statistical results from LHC experiments if they were able to be
created with tools that didn't require the large ``C++`` dependencies and tooling expertise as
:math:`\HiFa{}`.
Around the same time that Lukas began thinking on these ideas, Matthew Feickert was working on
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2 changes: 1 addition & 1 deletion docs/governance/ROADMAP.rst
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Expand Up @@ -7,7 +7,7 @@ This is the pyhf 2019 into 2020 Roadmap (Issue
Overview and Goals
------------------

We will follow loosely Seibert’s `Heirarchy of
We will follow loosely Seibert’s `Hierarchy of
Needs <https://twitter.com/FRoscheck/status/1159158552298229763>`__

|Seibert Hierarchy of Needs SciPy 2019| (`Stan
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2 changes: 1 addition & 1 deletion src/pyhf/contrib/viz/brazil.py
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Expand Up @@ -112,7 +112,7 @@ def plot_brazil_band(test_pois, cls_obs, cls_exp, test_size, ax, **kwargs):
ax (:obj:`matplotlib.axes.Axes`): The matplotlib axis object to plot on.
Returns:
:obj:`tuple`: The :obj:`matplotlib.aritst` objects drawn.
:obj:`tuple`: The :obj:`matplotlib.artist` objects drawn.
"""
line_color = kwargs.pop("color", "black")
(cls_obs_line,) = ax.plot(
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4 changes: 2 additions & 2 deletions src/pyhf/tensor/jax_backend.py
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Expand Up @@ -89,8 +89,8 @@ def clip(self, tensor_in, min_value, max_value):
Args:
tensor_in (:obj:`tensor`): The input tensor object
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be cliped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be cliped to
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be clipped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be clipped to
Returns:
JAX ndarray: A clipped `tensor`
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4 changes: 2 additions & 2 deletions src/pyhf/tensor/numpy_backend.py
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Expand Up @@ -98,8 +98,8 @@ def clip(
Args:
tensor_in (:obj:`tensor`): The input tensor object
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be cliped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be cliped to
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be clipped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be clipped to
Returns:
NumPy ndarray: A clipped `tensor`
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4 changes: 2 additions & 2 deletions src/pyhf/tensor/pytorch_backend.py
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Expand Up @@ -49,8 +49,8 @@ def clip(self, tensor_in, min_value, max_value):
Args:
tensor_in (:obj:`tensor`): The input tensor object
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be cliped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be cliped to
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be clipped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be clipped to
Returns:
PyTorch tensor: A clipped `tensor`
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4 changes: 2 additions & 2 deletions src/pyhf/tensor/tensorflow_backend.py
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Expand Up @@ -46,8 +46,8 @@ def clip(self, tensor_in, min_value, max_value):
Args:
tensor_in (:obj:`tensor`): The input tensor object
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be cliped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be cliped to
min_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The minimum value to be clipped to
max_value (:obj:`scalar` or :obj:`tensor` or :obj:`None`): The maximum value to be clipped to
Returns:
TensorFlow Tensor: A clipped `tensor`
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