Merge pull request #194 from jorenham/feature/markdownlint

Use markdownlint

.editorconfig

@@ -12,5 +12,5 @@ trim_trailing_whitespace = true
 max_line_length = 79
 
 # 2 space indentation
-[{*.json,*.yaml,*.yml,}]
+[{*.json,*.jsonc,*.yaml,*.yml}]
 indent_size = 2

.gitignore

@@ -4,51 +4,20 @@ __pycache__/
 *$py.class
 
 # Distribution / packaging
-.Python
 build/
-develop-eggs/
 dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
 site/
-var/
-wheels/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
 
-# Unit test / coverage reports
-.coverage
-.coverage.*
-.cache
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
+# Cache
+.hypothesis
 .pytest_cache/
-cover/
 .ruff_cache/
-.pyright/
-
-# Jupyter Notebook
-.ipynb_checkpoints
 
 # Environments
 .env
 .venv/
-env/
 venv/
-ENV/
-env.bak/
-venv.bak/
 
-# IDE configuration
+# IntelliJ
 .idea/
-.vscode/
+.run/

.markdownlint.yaml

@@ -0,0 +1,13 @@
+default: true
+no-hard-tabs: true
+MD007:
+  indent: 4
+MD033:
+  allowed_elements:
+    - 'br'
+    - 'table'
+    - 'tr'
+    - 'th'
+    - 'td'
+    - 'img'
+MD041: false

.pre-commit-config.yaml

@@ -11,6 +11,7 @@ repos:
       - id: check-toml
       - id: check-vcs-permalinks
       - id: check-yaml
+        args: [--unsafe]
       - id: destroyed-symlinks
       - id: detect-private-key
       - id: fix-byte-order-marker
@@ -20,6 +21,12 @@ repos:
       - id: no-commit-to-branch
       - id: trailing-whitespace
         args: [--markdown-linebreak-ext=md]
+        exclude_types: [svg]
+
+  - repo: https://github.com/igorshubovych/markdownlint-cli
+    rev: v0.39.0
+    hooks:
+      - id: markdownlint
 
   - repo: https://github.com/python-poetry/poetry
     rev: 1.8.2

.vscode/extensions.json

@@ -0,0 +1,14 @@
+{
+  "recommendations": [
+    "charliermarsh.ruff",
+    "codezombiech.gitignore",
+    "davidanson.vscode-markdownlint",
+    "editorconfig.editorconfig",
+    "elagil.pre-commit-helper",
+    "ms-python.python",
+    "ms-python.vscode-pylance",
+    "serhioromano.vscode-gitflow",
+    "yzhang.markdown-all-in-one",
+    "zeshuaro.vscode-python-poetry"
+  ]
+}

README.md

@@ -1,35 +1,26 @@
 <!--overview-start-->
 
-<img src="https://jorenham.github.io/Lmo/img/lmo.svg" alt="jorenham/lmo" width="128" align="right">
-
 # Lmo - Trimmed L-moments and L-comoments
 
-[![license](https://img.shields.io/github/license/jorenham/lmo?style=flat-square)](https://github.com/jorenham/lmo/blob/master/LICENSE?)
-[![PyPI](https://img.shields.io/pypi/v/lmo?style=flat-square)](https://pypi.org/project/lmo/)
-[![PyPI - Downloads](https://img.shields.io/pypi/dm/Lmo?style=flat-square)](https://pypi.org/project/lmo/)
-[![versions](https://img.shields.io/pypi/pyversions/lmo?style=flat-square)](https://github.com/jorenham/lmo)
-![GitHub Workflow Status (with branch)](https://img.shields.io/github/actions/workflow/status/jorenham/lmo/CI.yml?branch=master&style=flat-square)
-![GitHub commit activity (branch)](https://img.shields.io/github/commit-activity/m/jorenham/Lmo?style=flat-square)
-[![Checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)
-
-
-
-~~~
-
-Is your tail too heavy?
-Can't find a moment?
-Are the swans black?
-The distribution pathological?
-
-... then look no further: Lmo's got you covered!
-
-Uniform or multi-dimensional, Lmo can summarize it all with one quick glance!
-
-~~~
-
-Unlike the legacy [moments](https://wikipedia.org/wiki/Moment_(mathematics)),
-[L-moments](https://wikipedia.org/wiki/L-moment) **uniquely describe** a
+![GitHub Workflow Status][IMG-GHA]
+![license][IMG-BSD]
+[![Lmo - PyPI][IMG-PYPI]](https://pypi.org/project/Lmo/)
+[![Lmo - Versions][IMG-VER]](https://github.com/jorenham/Lmo)
+[![Ruff][IMG-RUFF]](https://github.com/astral-sh/ruff)
+[![Pyright][IMG-PYRIGHT]](https://microsoft.github.io/pyright/)
+
+[IMG-GHA]: https://img.shields.io/github/actions/workflow/status/jorenham/Lmo/CI.yml?branch=master
+[IMG-BSD]: https://img.shields.io/github/license/jorenham/Lmo
+[IMG-PYPI]: https://img.shields.io/pypi/v/Lmo
+[IMG-VER]: https://img.shields.io/pypi/pyversions/Lmo
+[IMG-RUFF]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
+[IMG-PYRIGHT]: https://microsoft.github.io/pyright/img/pyright_badge.svg
+
+Unlike the legacy
+[product-moments](https://wikipedia.org/wiki/Moment_(mathematics)), the
+[*L-moments*](https://wikipedia.org/wiki/L-moment) **uniquely describe** a
 probability distribution, and are more robust and efficient.
+
 The "L" stands for Linear; it is a linear combination of order statistics.
 So Lmo is as fast as sorting your samples (in terms of time-complexity).
 
@@ -98,17 +89,24 @@ pip install lmo
 
 These are automatically installed by your package manager, alongside `lmo`.
 
-| Package | Minimum version |
-| --- | --- |
-| [Python](https://github.com/python/cpython) | `3.10` |
-| [NumPy](https://github.com/numpy/numpy) | `1.22` |
-| [SciPy](https://github.com/scipy/scipy) | `1.9` |
+| Package      | Minimum version     |
+| ------------ | ------------------- |
+| [Python][PY] | `3.10`              |
+| [NumPy][NP]  | See [NEP 29][NEP29] |
+| [SciPy][SP]  | `1.9`               |
+
+[PY]: https://github.com/python/cpython
+[NP]: https://github.com/numpy/numpy
+[SP]: https://github.com/scipy/scipy
+[NEP29]: https://numpy.org/neps/nep-0029-deprecation_policy.html#support-table
 
 ### Optional dependencies
 
-| Package | Minimum version | Notes
-| --- | --- | --- |
-| [Pandas](https://github.com/pandas-dev/pandas) | `1.4` | Lmo extends `pd.Series` and `pd.DataFrame` with convenient methods, e.g. `df.l_scale(trim=1)`. Install as `pip install lmo[pandas]` to ensure compatibility. |
+| Package      | Minimum version | Notes                        |
+| ------------ | --------------- | ---------------------------- |
+| [Pandas][PD] | `1.4`           | Installable as `lmo[pandas]` |
+
+[PD]: https://github.com/pandas-dev/pandas
 
 ## Foundational Literature
 

docs/distributions.md

@@ -1,3 +1,4 @@
+<!-- markdownlint-disable MD051 MD052 -->
 # L-moments of common probability distributions
 
 This page lists theoretical L-moments of popular probability distributions.
@@ -772,7 +773,6 @@ The [Gompertz distribution](https://wikipedia.org/wiki/Gompertz_distribution)
 [^GOMP] with shape parameter \( \alpha > 0 \) and \( x \ge 0 \), has the
 following CDF and PPF:
 
-
 \[
 \begin{align*}
     F(x) &= 1 - e^{\alpha (1 - e^x)} \\
@@ -800,7 +800,8 @@ The general trimmed L-moments of the Gompertz distribution are:
 
 ### GEV
 
-The [GEV](https://wikipedia.org/wiki/GEV_distribution) unifies the
+The [GEV](https://wikipedia.org/wiki/GEV_distribution) distribution [^GEV]
+unifies  the
 [Gumbel](https://wikipedia.org/wiki/Gumbel_distribution),
 [Fréchet](https://wikipedia.org/wiki/Fr%C3%A9chet_distribution),
 and [Weibull](https://wikipedia.org/wiki/Weibull_distribution) distributions.
@@ -1038,9 +1039,12 @@ The distribution functions for \( x > 0 \) are defined as:
 \end{align*}
 \]
 
-<img src="../gallery/burr12.svg" width="100%"
+<img
+    src="../gallery/burr12.svg"
+    width="100%"
     style="height: auto; aspect-ratio: 16/9;"
-    alt="Burr XII distribution PDF" />
+    alt="Burr XII distribution PDF"
+/>
 
 When \( \beta > 1 / \alpha \), the general \( r \)-th trimmed L-moment is:
 
@@ -1090,7 +1094,7 @@ shapes \( \gamma \equiv 1 / \alpha \) and \( \alpha' \equiv \beta \), location
 
 For [Kumaraswamy's distribution
 ](https://wikipedia.org/wiki/Kumaraswamy_distribution) [^KUM1] with parameters
-\( \alpha \in \mathbb{R}_{>0} \) and \( \beta \in \mathbb{R}_{>0} \),
+<!-- markdownlint-disable-line -->\( \alpha \in \mathbb{R}_{>0} \) and \( \beta \in \mathbb{R}_{>0} \),
 the general solution for the \( r \)th (untrimmed L-moment has been derived by
 M.C. Jones in 2009 [^KUM2]. Lmo has extended these results for the general
 trimmed L-moments.
@@ -1147,8 +1151,8 @@ There are several notable special cases of the Kumaraswamy distribution:
 ### Wakeby
 
 The [*Wakeby distribution*](https://wikipedia.org/wiki/Wakeby_distribution)
-[^WAK] is quantile-based -- the CDF and PDF are not analytically expressible for the
-general case.
+[^WAK] is quantile-based -- the CDF and PDF are not analytically expressible
+for the general case.
 Without loss of generality, Lmo uses a 3-parameter "standardized"
 paremetrization, with shape parameters \( \beta,\ \delta,\ \phi \).
 
@@ -1331,6 +1335,7 @@ r \tlmoment{s, t}{r}
 
 and the arbitrarily-trimmed L-location is
 
+<!-- markdownlint-disable -->
 \[
 \tlmoment{s, t}{1}
     = -(1 + \phi) \mathfrak{L}_{1}^{(s)}(\beta)
@@ -1351,6 +1356,7 @@ where
         & \text{otherwise.}
 \end{cases}
 \]
+<!-- markdownlint-enable -->
 
 These equations look scarier that they actually are. To see why, take a look
 at the first 4 L-moment, with 4 styles of trimming:
@@ -1549,6 +1555,7 @@ There are several notable special cases of the GLD:
     generating asymmetric random variables
 
 ## Constants and special functions
+<!-- markdownlint-disable MD051 MD052 -->
 
 An overview of the (non-obvious) mathematical notation of special functions
 and constants.
@@ -1808,7 +1815,6 @@ and constants.
     </tr>
 </table>
 
-
 *[STD]: Standard deviation
 *[MAD]: Median absolute deviation
 *[RV]: Random variable

docs/gallery/burr12.py

@@ -1,11 +1,11 @@
-# pyright: reportUnknownMemberType=false
+# pyright: reportUnknownMemberType=false, reportUnusedCallResult=false
 from pathlib import Path
 
 import numpy as np
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 
-from scipy.stats import burr12  # type: ignore
+from scipy.stats import burr12
 
 GALLERY_PATH = Path(__file__).resolve().parent
 TEX_LABEL_TEMPLATE = r'$\alpha = {},\ \beta = {}$'
@@ -55,4 +55,3 @@
         format='svg',
         bbox_inches='tight'
     )
-

docs/gallery/genlambda.py

@@ -1,4 +1,4 @@
-# pyright: reportUnknownMemberType=false
+# pyright: reportUnknownMemberType=false, reportUnusedCallResult=false
 from pathlib import Path
 
 import numpy as np
@@ -60,4 +60,3 @@
         format='svg',
         bbox_inches='tight'
     )
-

docs/gallery/kumaraswamy.py

@@ -1,4 +1,4 @@
-# pyright: reportUnknownMemberType=false
+# pyright: reportUnknownMemberType=false, reportUnusedCallResult=false
 from pathlib import Path
 
 import numpy as np
@@ -54,4 +54,3 @@
         format='svg',
         bbox_inches='tight'
     )
-

docs/gallery/wakeby.py

@@ -1,4 +1,4 @@
-# pyright: reportUnknownMemberType=false
+# pyright: reportUnknownMemberType=false, reportUnusedCallResult=false
 from pathlib import Path
 
 import numpy as np
@@ -54,4 +54,3 @@
         format='svg',
         bbox_inches='tight'
     )
-