Merge ecd06eb352a400bf63b55589a1090e760ec3a605 into 7d0978e5fba98538de20d0fdb9d66e6cbf80d3f7

This commit is contained in:
Palash Tyagi 2025-08-03 22:28:23 +00:00 committed by GitHub
commit c125e76183
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
14 changed files with 222 additions and 5 deletions

View File

@ -58,6 +58,10 @@
<h2>A lightweight dataframe & math toolkit for Rust</h2>
<hr style="border: 1px solid #d4d4d4; margin: 20px 0;">
<p>
📖 <a href="https://magnus167.github.io/rustframe/user-guide">User Guide</a>
<br><br>
📚 <a href="https://magnus167.github.io/rustframe/docs">Docs</a> |
📊 <a href="https://magnus167.github.io/rustframe/benchmark-report/">Benchmarks</a>

View File

@ -153,7 +153,6 @@ jobs:
echo "<meta http-equiv=\"refresh\" content=\"0; url=../docs/index.html\">" > target/doc/rustframe/index.html
mkdir output
cp tarpaulin-report.html target/doc/docs/
cp tarpaulin-report.json target/doc/docs/
cp tarpaulin-badge.json target/doc/docs/
@ -166,16 +165,30 @@ jobs:
# copy the benchmark report to the output directory
cp -r benchmark-report target/doc/
mkdir output
cp -r target/doc/* output/
- name: Build user guide
run: |
cargo binstall mdbook
bash ./docs/build.sh
- name: Copy user guide to output directory
run: |
mkdir output/user-guide
cp -r docs/book/* output/user-guide/
- name: Add index.html to output directory
run: |
cp .github/htmldocs/index.html target/doc/index.html
cp .github/rustframe_logo.png target/doc/rustframe_logo.png
cp .github/htmldocs/index.html output/index.html
cp .github/rustframe_logo.png output/rustframe_logo.png
- name: Upload Pages artifact
# if: github.event_name == 'push' || github.event_name == 'workflow_dispatch'
uses: actions/upload-pages-artifact@v3
with:
path: target/doc/
# path: target/doc/
path: output/
- name: Deploy to GitHub Pages
# if: github.event_name == 'push' || github.event_name == 'workflow_dispatch'

View File

@ -78,3 +78,8 @@ jobs:
uses: codecov/test-results-action@v1
with:
token: ${{ secrets.CODECOV_TOKEN }}
- name: Test build user guide
run: |
cargo binstall mdbook
bash ./docs/build.sh

2
.gitignore vendored
View File

@ -17,3 +17,5 @@ data/
tarpaulin-report.*
.github/htmldocs/rustframe_logo.png
docs/book/

View File

@ -198,3 +198,14 @@ To run the benchmarks, use:
```bash
cargo bench --features "bench"
```
## Building the user-guide
To build the user guide, use:
```bash
cargo binstall mdbook
bash docs/build.sh
```
This will generate the user guide in the `docs/book` directory.

7
docs/book.toml Normal file
View File

@ -0,0 +1,7 @@
[book]
title = "RustFrame User Guide"
author = ["RustFrame Contributors"]
description = "Guided journey through RustFrame capabilities."
[build]
build-dir = "book"

7
docs/build.sh Executable file
View File

@ -0,0 +1,7 @@
#!/usr/bin/env sh
# Build and test the RustFrame user guide using mdBook.
set -e
cd docs
bash gen.sh "$@"
cd ..

14
docs/gen.sh Normal file
View File

@ -0,0 +1,14 @@
#!/usr/bin/env sh
set -e
cargo clean
cargo build --manifest-path ../Cargo.toml
mdbook test -L ../target/debug/deps "$@"
mdbook build "$@"
cargo build
cargo build --release

7
docs/src/SUMMARY.md Normal file
View File

@ -0,0 +1,7 @@
# Summary
- [Introduction](./introduction.md)
- [Data Manipulation](./data-manipulation.md)
- [Compute Features](./compute.md)
- [Machine Learning](./machine-learning.md)
- [Utilities](./utilities.md)

31
docs/src/compute.md Normal file
View File

@ -0,0 +1,31 @@
# Compute Features
The `compute` module provides statistical routines like descriptive
statistics and correlation measures.
## Basic Statistics
```rust
# extern crate rustframe;
use rustframe::compute::stats::{mean, stddev};
use rustframe::matrix::Matrix;
let m = Matrix::from_vec(vec![1.0, 2.0, 3.0, 4.0], 2, 2);
let mean_val = mean(&m);
let std_val = stddev(&m);
```
## Correlation
```rust
# extern crate rustframe;
use rustframe::compute::stats::pearson;
use rustframe::matrix::Matrix;
let x = Matrix::from_vec(vec![1.0, 2.0, 3.0, 4.0], 2, 2);
let y = Matrix::from_vec(vec![2.0, 4.0, 6.0, 8.0], 2, 2);
let corr = pearson(&x, &y);
```
With the basics covered, explore predictive models in the
[machine learning](./machine-learning.md) chapter.

View File

@ -0,0 +1,43 @@
# Data Manipulation
RustFrame's `Frame` type couples tabular data with
column labels and a typed row index.
## Creating a Frame
```rust
# extern crate rustframe;
use rustframe::frame::{Frame, RowIndex};
use rustframe::matrix::Matrix;
let data = Matrix::from_cols(vec![vec![1.0, 2.0], vec![3.0, 4.0]]);
let frame = Frame::new(data, vec!["A", "B"], None);
assert_eq!(frame["A"], vec![1.0, 2.0]);
```
## Indexing Rows
```rust
# extern crate rustframe;
use rustframe::frame::{Frame, RowIndex};
use rustframe::matrix::Matrix;
let data = Matrix::from_cols(vec![vec![1.0, 2.0], vec![3.0, 4.0]]);
let index = RowIndex::Int(vec![10, 20]);
let frame = Frame::new(data, vec!["A", "B"], Some(index));
assert_eq!(frame.get_row(20)["B"], 4.0);
```
## Aggregations
```rust
# extern crate rustframe;
use rustframe::frame::Frame;
use rustframe::matrix::{Matrix, SeriesOps};
let frame = Frame::new(Matrix::from_cols(vec![vec![1.0, 2.0]]), vec!["A"], None);
assert_eq!(frame.sum_vertical(), vec![3.0]);
```
When you're ready to run analytics, continue to the
[compute features](./compute.md) chapter.

10
docs/src/introduction.md Normal file
View File

@ -0,0 +1,10 @@
# Introduction
Welcome to the **RustFrame User Guide**. This book provides a tour of
RustFrame's capabilities from basic data handling to advanced machine learning
workflows. Each chapter contains runnable snippets so you can follow along.
1. [Data manipulation](./data-manipulation.md) for loading and transforming data.
2. [Compute features](./compute.md) for statistics and analytics.
3. [Machine learning](./machine-learning.md) for predictive models.
4. [Utilities](./utilities.md) for supporting helpers and upcoming modules.

View File

@ -0,0 +1,39 @@
# Machine Learning
RustFrame ships with several algorithms:
- Linear and logistic regression
- K-means clustering
- Principal component analysis (PCA)
- Naive Bayes and dense neural networks
## Linear Regression
```rust
# extern crate rustframe;
use rustframe::compute::models::linreg::LinReg;
use rustframe::matrix::Matrix;
let x = Matrix::from_vec(vec![1.0, 2.0, 3.0, 4.0], 4, 1);
let y = Matrix::from_vec(vec![2.0, 3.0, 4.0, 5.0], 4, 1);
let mut model = LinReg::new(1);
model.fit(&x, &y, 0.01, 100);
let preds = model.predict(&x);
assert_eq!(preds.rows(), 4);
```
## K-means Walkthrough
```rust
# extern crate rustframe;
use rustframe::compute::models::k_means::KMeans;
use rustframe::matrix::Matrix;
let data = Matrix::from_vec(vec![1.0, 1.0, 5.0, 5.0], 2, 2);
let (model, _labels) = KMeans::fit(&data, 2, 10, 1e-4);
let new_point = Matrix::from_vec(vec![0.0, 0.0], 1, 2);
let cluster = model.predict(&new_point)[0];
```
For helper functions and upcoming modules, visit the
[utilities](./utilities.md) section.

24
docs/src/utilities.md Normal file
View File

@ -0,0 +1,24 @@
# Utilities
Utilities provide handy helpers around the core library. Existing tools
include:
- Date utilities for generating calendar sequences.
## Date Helpers
```rust
# extern crate rustframe;
use rustframe::utils::dateutils::{DatesList, DateFreq};
let list = DatesList::new("2024-01-01".into(), "2024-01-03".into(), DateFreq::Daily);
assert_eq!(list.count().unwrap(), 3);
```
Upcoming utilities will cover:
- Data import/export helpers
- Visualization adapters
- Streaming data interfaces
Contributions to these sections are welcome!