[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

.github/release.yml

@@ -15,4 +15,4 @@ changelog:
         - docs
     - title: Maintenance 🔧
       labels:
-        - "*"
+        - "*"

.github/workflows/coverage.yml

@@ -2,13 +2,13 @@ name: Workflow for Codecov conjugate
 
 on:
   push:
-    paths: 
+    paths:
       - "conjugate/**"
       - "pyproject.toml"
       - "tests/**"
 
   pull_request:
-    paths: 
+    paths:
       - "conjugate/**"
       - "pyproject.toml"
       - "tests/**"
@@ -24,7 +24,7 @@ jobs:
         with:
           python-version: '3.10'
       - name: Install dependencies
-        run: pip install . pytest pytest-cov pytest-mpl pypika 
+        run: pip install . pytest pytest-cov pytest-mpl pypika
       - name: Run tests and collect coverage
         run: pytest
       - name: Upload coverage to Codecov

.github/workflows/docs.yml

@@ -2,7 +2,7 @@ name: Docs
 on:
   push:
     branches:
-      - master 
+      - master
       - main
 permissions:
   contents: write
@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-        with: 
+        with:
           fetch-depth: 0
       - uses: actions/setup-python@v4
         with:

.github/workflows/sync-closing-labels.yml

@@ -13,7 +13,7 @@ jobs:
       uses: actions/checkout@v2
     - name: Sync labels with closing issues
       uses: wd60622/closing-labels@v0.0.3
-      with: 
+      with:
         exclude: "duplicate,help wanted,question"
       env:
         GH_TOKEN: ${{ github.token }}

.github/workflows/tests.yml

@@ -2,12 +2,12 @@ name: Tests
 
 on:
   push:
-    paths: 
+    paths:
       - "conjugate/**"
       - "pyproject.toml"
       - "tests/**"
   pull_request:
-    paths: 
+    paths:
       - "conjugate/**"
       - "pyproject.toml"
       - "tests/**"

CONTRIBUTING.md

@@ -1,26 +1,26 @@
 # Guidelines for Contributing
 
-Contributions are welcomed in all forms. These may be bugs, feature requests, documentation, or examples. Please feel free to: 
+Contributions are welcomed in all forms. These may be bugs, feature requests, documentation, or examples. Please feel free to:
 
 - Submit an issue
 - Open a pull request
 - Help with outstanding issues and pull requests
 
 ## Open an Issue
 
-If you find a bug or have a feature request, please [open an issue](https://github.com/wd60622/conjugate/issues/new) on GitHub. 
+If you find a bug or have a feature request, please [open an issue](https://github.com/wd60622/conjugate/issues/new) on GitHub.
 Please check that it is not one of the [open issues](https://github.com/wd60622/conjugate/issues).
 
 ## Local Development Steps
 
 ### Create a forked branch of the repo
 
-Do this once but keep it up to date 
+Do this once but keep it up to date
 
 1. [Fork wd60622/conjugate GitHub repo](https://github.com/wd60622/conjugate/fork)
 1. Clone forked repo and set upstream
 
-    ```bash 
+    ```bash
     git clone git@github.com:<your-username>/conjugate.git
     cd conjugate
     git remote add upstream git@github.com:wd60622/conjugate.git
@@ -36,15 +36,15 @@ In the root of the repo, run:
 poetry install
 ```
 
-And also install the [pre-commit](https://pre-commit.com/) hooks with: 
+And also install the [pre-commit](https://pre-commit.com/) hooks with:
 
-```bash 
-pre-commit install 
+```bash
+pre-commit install
 ```
 
 ## Pull Request Checklist
 
-Please check that your pull request meets the following criteria: 
+Please check that your pull request meets the following criteria:
 
 - Unit tests pass
 - pre-commit hooks pass
@@ -64,5 +64,4 @@ Tests will run on each pull request.
 
 Documentation will be updated with each merge to `main` branch.
 
-Package release to PyPI on every GitHub Release. 
-
+Package release to PyPI on every GitHub Release.

Makefile

@@ -2,7 +2,7 @@
 
 .DEFAULT_GOAL := help
 
-help: 
+help:
 	@awk 'BEGIN {FS = ":.*?## "} /^[a-zA-Z0-9_-]+:.*?## / {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}' $(MAKEFILE_LIST) | sort
 
 test-generate-baseline: ## Generate baseline images for tests
@@ -12,7 +12,7 @@ test: ## Run tests
 	poetry run pytest tests
 
 cov:  ## Run tests and generate coverage report
-	poetry run pytest tests 
+	poetry run pytest tests
 	coverage html
 	open htmlcov/index.html
 

README.md

@@ -1,8 +1,8 @@
 # Conjugate Models
 
 [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
-[![Tests](https://github.com/wd60622/conjugate/actions/workflows/tests.yml/badge.svg)](https://github.com/wd60622/conjugate/actions/workflows/tests.yml) 
-[![PyPI version](https://badge.fury.io/py/conjugate-models.svg)](https://badge.fury.io/py/conjugate-models) 
+[![Tests](https://github.com/wd60622/conjugate/actions/workflows/tests.yml/badge.svg)](https://github.com/wd60622/conjugate/actions/workflows/tests.yml)
+[![PyPI version](https://badge.fury.io/py/conjugate-models.svg)](https://badge.fury.io/py/conjugate-models)
 [![docs](https://github.com/wd60622/conjugate/actions/workflows/docs.yml/badge.svg)](https://wd60622.github.io/conjugate/)
 [![codecov](https://codecov.io/github/wd60622/conjugate/branch/main/graph/badge.svg)](https://app.codecov.io/github/wd60622/conjugate)
 
@@ -11,11 +11,11 @@ Bayesian conjugate models in Python
 
 ## Installation
 
-```bash 
+```bash
 pip install conjugate-models
 ```
 
-## Features 
+## Features
 
 - [Connection to Scipy Distributions](https://wd60622.github.io/conjugate/examples/scipy-connection) with `dist` attribute
 - [Built in Plotting](https://wd60622.github.io/conjugate/examples/plotting) with `plot_pdf`, `plot_pmf`, and `plot_cdf` methods
@@ -25,7 +25,7 @@ pip install conjugate-models
     - Out of box compatibility with `polars`, `pandas`, `numpy`, and more.
 - [Unsupported Distributions](https://wd60622.github.io/conjugate/examples/pymc-sampling) for sampling from unsupported distributions
 
-## Supported Models 
+## Supported Models
 
 Many likelihoods are supported including
 
@@ -41,7 +41,7 @@ Many likelihoods are supported including
 1. Pass data and prior into model from `models` modules
 1. Analytics with posterior and posterior predictive distributions
 
-```python 
+```python
 from conjugate.distributions import Beta, BetaBinomial
 from conjugate.models import binomial_beta, binomial_beta_predictive
 
@@ -54,7 +54,7 @@ prior = Beta(1, 1)
 prior_predictive: BetaBinomial = binomial_beta_predictive(n=N, distribution=prior)
 
 posterior: Beta = binomial_beta(n=N, x=x, prior=prior)
-posterior_predictive: BetaBinomial = binomial_beta_predictive(n=N, distribution=posterior) 
+posterior_predictive: BetaBinomial = binomial_beta_predictive(n=N, distribution=posterior)
 ```
 
 From here, do any analysis you'd like!

docs/distributions.md

@@ -1,6 +1,6 @@
 ---
-comments: true 
+comments: true
 ---
-# Distributions 
+# Distributions
 
 ::: conjugate.distributions

docs/examples/bayesian-update.md

@@ -1,10 +1,10 @@
 ---
-comments: true 
+comments: true
 ---
 
-Easy to use Bayesian inference incrementally by setting the posterior to the prior for the next set of data points. 
+Easy to use Bayesian inference incrementally by setting the posterior to the prior for the next set of data points.
 
-Abstractly, something like this: 
+Abstractly, something like this:
 
 ```python
 prior = ...
@@ -30,11 +30,11 @@ import matplotlib.pyplot as plt
 from conjugate.distributions import NormalInverseGamma
 from conjugate.models import normal
 
-def create_sampler(mu, sigma, rng): 
+def create_sampler(mu, sigma, rng):
     """Generate a sampler from a normal distribution with mean `mu` and standard deviation `sigma`."""
-    def sample(n: int): 
+    def sample(n: int):
         return rng.normal(loc=mu, scale=sigma, size=n)
-    
+
     return sample
 
 
@@ -45,9 +45,9 @@ sample = create_sampler(mu=mu, sigma=sigma, rng=rng)
 
 
 prior = NormalInverseGamma(
-    mu=0, 
-    alpha=1, beta=1, 
-    nu=1, 
+    mu=0,
+    alpha=1, beta=1,
+    nu=1,
 )
 
 cumsum = 0
@@ -57,9 +57,9 @@ for batch_size in batch_sizes:
     data = sample(n=batch_size)
 
     posterior = normal(
-        x_total=data.sum(), 
-        x2_total=(data ** 2).sum(), 
-        n=batch_size, 
+        x_total=data.sum(),
+        x2_total=(data ** 2).sum(),
+        n=batch_size,
         prior=prior
     )
 
@@ -69,14 +69,14 @@ for batch_size in batch_sizes:
     label = f"n={cumsum}"
     ax.scatter(variance_samples ** 0.5, beta_samples, alpha=0.25, label=label)
 
-    prior = posterior 
+    prior = posterior
 
 ax.scatter(sigma, mu, color="black", label="true")
 ax.set(
-    xlabel="$\sigma$", 
-    ylabel="$\mu$", 
-    xlim=(0, None), 
-    ylim=(0, None), 
+    xlabel="$\sigma$",
+    ylabel="$\mu$",
+    xlim=(0, None),
+    ylim=(0, None),
     title="Updated posterior samples of $\mu$ and $\sigma$"
 )
 ax.legend()
@@ -91,16 +91,16 @@ plt.show()
 With a Binomial model, we can assume as Beta prior
 
 
-```python 
+```python
 import numpy as np
 
 import matplotlib.pyplot as plt
 
 from conjugate.distributions import Beta
 from conjugate.models import binomial_beta
 
-def create_sampler(p, rng): 
-    def sampler(n: int): 
+def create_sampler(p, rng):
+    def sampler(n: int):
         return rng.binomial(n=n, p=p)
 
     return sampler
@@ -114,13 +114,13 @@ sample = create_sampler(p=p, rng=rng)
 ax = plt.gca()
 cumsum = 0
 batch_sizes = [5, 25, 50]
-for batch_size in batch_sizes: 
+for batch_size in batch_sizes:
     x = sample(n=batch_size)
 
     posterior = binomial_beta(
-        x=x, 
-        n=batch_size, 
-        prior=prior, 
+        x=x,
+        n=batch_size,
+        prior=prior,
     )
 
     cumsum += batch_size
@@ -132,14 +132,11 @@ for batch_size in batch_sizes:
 
 ax.axvline(p, label="true p", color="black", ymax=0.05)
 ax.set(
-    xlabel="p", 
-    ylim=(None, 10), 
+    xlabel="p",
+    ylim=(None, 10),
 )
 ax.legend()
 plt.show()
 ```
 
 ![Binomial Model](../images/bayesian-update-binomial.png)
-
-
-