Add raw song buffer constructor

Use set for paths-to-update comparison

.github/workflows/rust.yml

@@ -10,7 +10,7 @@ env:
   CARGO_TERM_COLOR: always
 
 jobs:
-  build:
+  build-test-lint-linux:
 
     runs-on: ubuntu-latest
 
@@ -20,17 +20,61 @@ jobs:
         submodules: recursive
     - uses: actions-rs/toolchain@v1
       with:
-        toolchain: nightly-2021-04-01
+        toolchain: nightly-2022-02-16
         override: false
     - name: Packages
-      run: sudo apt-get install build-essential yasm libavutil-dev libavcodec-dev libavformat-dev libavfilter-dev libavfilter-dev libavdevice-dev libswresample-dev libfftw3-dev ffmpeg
+      run: sudo apt-get update && sudo apt-get install build-essential yasm libavutil-dev libavcodec-dev libavformat-dev libavfilter-dev libavfilter-dev libavdevice-dev libswresample-dev libfftw3-dev ffmpeg
+    - name: Check format
+      run: cargo fmt -- --check
     - name: Build
       run: cargo build --verbose
     - name: Run tests
       run: cargo test --verbose
+    - name: Run library tests
+      run: cargo test --verbose --features=library
     - name: Run example tests
       run: cargo test --verbose --examples
     - name: Build benches
-      run: cargo +nightly-2021-04-01 bench --verbose --features=bench --no-run
+      run: cargo +nightly-2022-02-16 bench --verbose --features=bench --no-run
     - name: Build examples
-      run: cargo build --examples --verbose
+      run: cargo build --examples --verbose --features=serde,library
+    - name: Lint
+      run: cargo clippy --examples --features=serde,library -- -D warnings
+
+  build-test-lint-windows:
+    name: Windows - build, test and lint
+    runs-on: windows-latest
+    strategy:
+      matrix:
+        include:
+          - ffmpeg_version: latest
+            ffmpeg_download_url: https://www.gyan.dev/ffmpeg/builds/ffmpeg-release-full-shared.7z
+      fail-fast: false
+    env:
+      FFMPEG_DOWNLOAD_URL: ${{ matrix.ffmpeg_download_url }}
+    steps:
+      - uses: actions/checkout@v2
+      - name: Install dependencies
+        run: |
+          $VCINSTALLDIR = $(& "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe" -latest -property installationPath)
+          Add-Content $env:GITHUB_ENV "LIBCLANG_PATH=${VCINSTALLDIR}\VC\Tools\LLVM\x64\bin`n"
+          Invoke-WebRequest "${env:FFMPEG_DOWNLOAD_URL}" -OutFile ffmpeg-release-full-shared.7z
+          7z x ffmpeg-release-full-shared.7z
+          mkdir ffmpeg
+          mv ffmpeg-*/* ffmpeg/
+          Add-Content $env:GITHUB_ENV "FFMPEG_DIR=${pwd}\ffmpeg`n"
+          Add-Content $env:GITHUB_PATH "${pwd}\ffmpeg\bin`n"
+      - name: Set up Rust
+        uses: actions-rs/toolchain@v1
+        with:
+          toolchain: stable
+          override: true
+          components: rustfmt, clippy
+      - name: Build
+        run: cargo build --examples
+      - name: Test
+        run: cargo test --examples --features=serde
+      - name: Lint
+        run: cargo clippy --examples --features=serde -- -D warnings
+      - name: Check format
+        run: cargo fmt -- --check

CHANGELOG.md

@@ -1,3 +1,107 @@
-Change Log
+#Changelog
 
-All user visible changes to this project will be documented in this file. This project adheres to Semantic Versioning, as described for Rust libraries in RFC #1105
+## bliss 0.6.5
+* Fix library update performance issues.
+* Pretty-print JSON in the config file.
+
+## bliss 0.6.4
+* Fix a bug in the customizable CPU number option in `library`.
+
+## bliss 0.6.3
+* Add customizable CPU number in the `library` module.
+
+## bliss 0.6.2
+* Add a `library` module, that greatly helps when making player plug-ins.
+
+## bliss 0.6.1
+* Fix a decoding bug while decoding certain WAV files.
+
+## bliss 0.6.0
+* Change String to PathBuf in `analyze_paths`.
+* Add `analyze_paths_with_cores`.
+
+## bliss 0.5.2
+* Fix a bug with some broken MP3 files.
+* Bump ffmpeg to 5.1.0.
+
+## bliss 0.5.0
+* Add support for CUE files.
+* Add `album_artist` and `duration` to `Song`.
+* Fix a bug in `estimate_tuning` that led to empty chroma errors.
+* Remove the unusued Library trait, and extract a few useful functions from
+  there (`analyze_paths`, `closest_to_album_group`).
+* Rename `distance` module to `playlist`.
+* Remove all traces of the "analyse" word vs "analyze" to make the codebase
+  more coherent.
+* Rename `Song::new` to `Song::from_path`.
+
+## bliss 0.4.6
+* Bump ffmpeg crate version to allow for cross-compilation.
+
+## bliss 0.4.5
+* Bump ffmpeg crate version.
+* Add an "ffmpeg-static" option.
+
+## bliss 0.4.4
+* Make features' version public.
+
+## bliss 0.4.3
+* Add features' version on each Song instance.
+
+## bliss 0.4.2
+* Add a binary example to easily make playlists.
+
+## bliss 0.4.1
+* Add a function to make album playlists.
+
+## bliss 0.4.0
+* Make the song-to-song custom sorting method faster.
+* Rename `to_vec` and `to_arr1` to `as_vec` and `as_arr1` .
+* Add a playlist_dedup function. 
+
+## bliss 0.3.5
+* Add custom sorting methods for playlist-making.
+
+## bliss 0.3.4
+* Bump ffmpeg's version to avoid building ffmpeg when building bliss.
+
+## bliss 0.3.3
+* Add a streaming analysis function, to help libraries displaying progress.
+
+## bliss 0.3.2
+* Fixed a rare ffmpeg multithreading bug.
+
+## bliss 0.3.1
+* Show error message when song storage fails in the Library trait.
+* Added a `distance` module containing euclidean and cosine distance.
+* Added various custom_distance functions to avoid being limited to the
+  euclidean distance only.
+
+## bliss 0.3.0
+* Changed `Song.path` from `String` to `PathBuf`.
+* Made `Song` metadata (artist, album, etc) `Option`s.
+* Added a `BlissResult` error type.
+
+## bliss 0.2.6
+* Fixed an allocation bug in Song::decode that potentially caused segfaults.
+
+## bliss 0.2.5
+* Updates to docs
+
+## bliss 0.2.4
+* Make `Analysis::to_vec()` public.
+
+## bliss 0.2.3
+
+* Made `NUMBER_FEATURES` public.
+
+## bliss 0.2.1
+
+* Made `Analysis::new` public.
+* Made `Analysis` serializable.
+
+## bliss 0.2.0
+
+* Added an `Analysis` struct to `Song`, as well as an `AnalysisIndex` to
+  index it easily.
+* Changed some logging parameters for the Library trait.

Cargo.toml

@@ -1,27 +1,32 @@
 [package]
-name = "bliss-audio"
-version = "0.1.3"
-authors = ["Polochon-street <polochonstreet@gmx.fr>"]
+name = "bliss-audio-symphonia"
+version = "0.6.5"
+authors = ["Polochon-street <polochonstreet@gmx.fr>", "NGnius (Graham) <ngniusness@gmail.com>"]
 edition = "2018"
 license = "GPL-3.0-only"
 description = "A song analysis library for making playlists"
 homepage = "https://lelele.io/bliss.html"
-repository = "https://github.com/Polochon-street/bliss-rs"
-keywords = ["audio", "analysis", "MIR", "playlist"]
+repository = "https://github.com/NGnius/bliss-rs"
+keywords = ["audio", "analysis", "MIR", "playlist", "similarity"]
 readme = "README.md"
 
 [package.metadata.docs.rs]
-features = ["bliss-audio-aubio-rs/rustdoc"]
+features = ["bliss-audio-aubio-rs/rustdoc", "library"]
 no-default-features = true
 
 [features]
-# Building ffmpeg until either
-# https://github.com/zmwangx/rust-ffmpeg/pull/60
-# or https://github.com/zmwangx/rust-ffmpeg/pull/62 is in
-default = ["bliss-audio-aubio-rs/static", "build-ffmpeg"]
-build-ffmpeg = ["ffmpeg-next/build"]
-bench = []
+default = ["bliss-audio-aubio-rs/static"]
+# Build ffmpeg instead of using the host's.
+# Use if you want to build python bindings with maturin.
 python-bindings = ["bliss-audio-aubio-rs/fftw3"]
+# Enable the benchmarks with `cargo +nightly bench --features=bench`
+bench = []
+library = [
+    "serde", "dep:rusqlite", "dep:dirs", "dep:tempdir",
+    "dep:anyhow", "dep:serde_ini", "dep:serde_json",
+    "dep:indicatif",
+]
+serde = ["dep:serde"]
 
 [dependencies]
 ripemd160 = "0.9.0"
@@ -34,11 +39,45 @@ lazy_static = "1.4.0"
 rayon = "1.5.0"
 crossbeam = "0.8.0"
 noisy_float = "0.2.0"
-ffmpeg-next = "4.3.8"
+symphonia = { version = "0.5", features = ["mp3", "aac", "alac"]}
+rubato = { version = "0.12" }
 log = "0.4.14"
 env_logger = "0.8.3"
 thiserror = "1.0.24"
 # Until https://github.com/aubio/aubio/issues/336 is somehow solved
 # Hopefully we'll be able to use the official aubio-rs at some point.
 bliss-audio-aubio-rs = "0.2.0"
+strum = "0.21"
+strum_macros = "0.21"
+rcue = "0.1.1"
+
+# Deps for the library feature
 serde = { version = "1.0", optional = true, features = ["derive"] }
+serde_json = { version = "1.0.59", optional = true }
+serde_ini = { version = "0.2.0", optional = true }
+tempdir = { version = "0.3.7", optional = true }
+rusqlite = { version = "0.27.0", optional = true }
+dirs = { version = "4.0.0", optional = true }
+anyhow = { version = "1.0.58", optional = true }
+indicatif = { version = "0.17.0", optional = true }
+
+[dev-dependencies]
+mime_guess = "2.0.3"
+glob = "0.3.0"
+anyhow = "1.0.45"
+clap = "2.33.3"
+pretty_assertions = "1.2.1"
+serde_json = "1.0.59"
+
+[[example]]
+name = "library"
+required-features = ["library"]
+
+[[example]]
+name = "library_extra_info"
+required-features = ["library"]
+
+
+[[example]]
+name = "playlist"
+required-features = ["serde"]

README.md

@@ -1,14 +1,17 @@
+A modified version of the bliss-audio to remove ffmpeg and replace it with Rust's symphonia library.
+
 [![crate](https://img.shields.io/crates/v/bliss-audio.svg)](https://crates.io/crates/bliss-audio)
 [![build](https://github.com/Polochon-street/bliss-rs/workflows/Rust/badge.svg)](https://github.com/Polochon-street/bliss-rs/actions)
-[![doc](https://docs.rs/bliss-rs/badge.svg)](https://docs.rs/bliss-audio/)
+[![doc](https://docs.rs/bliss-audio/badge.svg)](https://docs.rs/bliss-audio/)
 
-# bliss music analyser - Rust version
+# bliss music analyzer - Rust version
 bliss-rs is the Rust improvement of [bliss](https://github.com/Polochon-street/bliss), a
 library used to make playlists by analyzing songs, and computing distance between them.
 
 Like bliss, it eases the creation of « intelligent » playlists and/or continuous
 play, à la Spotify/Grooveshark Radio, as well as easing creating plug-ins for
-existing audio players.
+existing audio players. For instance, you can use it to make calm playlists
+to help you sleeping, fast playlists to get you started during the day, etc.
 
 For now (and if you're looking for an easy-to use smooth play experience),
 [blissify](https://crates.io/crates/blissify) implements bliss for
@@ -21,53 +24,56 @@ used by C-bliss, since it uses
 different, more accurate values, based on
 [actual literature](https://lelele.io/thesis.pdf). It is also faster.
 
-Note 2: The `bliss-rs` crate is outdated. You should use `bliss-audio`
-(this crate) instead.
-
 ## Examples
-For simple analysis / distance computing, a look at `examples/distance.rs` and
-`examples/analyse.rs`.
+For simple analysis / distance computing, take a look at `examples/distance.rs` and
+`examples/analyze.rs`.
 
-Ready to use examples:
+If you simply want to try out making playlists from a folder containing songs,
+[this example](https://github.com/Polochon-street/bliss-rs/blob/master/examples/playlist.rs)
+contains all you need. Usage:
+
+        cargo run --features=serde --release --example=playlist /path/to/folder /path/to/first/song
+
+Don't forget the `--release` flag!
+
+By default, it outputs the playlist to stdout, but you can use `-o <path>`
+to output it to a specific path.
+
+To avoid having to analyze the entire folder
+several times, it also stores the analysis in `/tmp/analysis.json`. You can customize
+this behavior by using `-a <path>` to store this file in a specific place.
+
+Ready to use code examples:
 
 ### Compute the distance between two songs
 ```
-use bliss_audio::Song;
+use bliss_audio::{BlissError, Song};
 
-fn main() {
-        let song1 = Song::new("/path/to/song1");
-        let song2 = Song::new("/path/to/song2");
+fn main() -> Result<(), BlissError> {
+    let song1 = Song::from_path("/path/to/song1")?;
+    let song2 = Song::from_path("/path/to/song2")?;
         
-        println!("Distance between song1 and song2 is {}", song1.distance(song2));
+    println!("Distance between song1 and song2 is {}", song1.distance(&song2));
+    Ok(())
 }
 ```
 
 ### Make a playlist from a song
 ```
-use bliss_rs::{BlissError, Song};
-use ndarray::{arr1, Array};
+use bliss_audio::{BlissError, Song};
 use noisy_float::prelude::n32;
 
 fn main() -> Result<(), BlissError> {
     let paths = vec!["/path/to/song1", "/path/to/song2", "/path/to/song3"];
     let mut songs: Vec<Song> = paths
         .iter()
-        .map(|path| Song::new(path))
+        .map(|path| Song::from_path(path))
         .collect::<Result<Vec<Song>, BlissError>>()?;
 
     // Assuming there is a first song
-    let analysis_first_song = arr1(&songs[0].analysis);
+    let first_song = songs.first().unwrap().to_owned();
 
-    // Identity matrix used to compute the distance.
-    // Note that it can be changed to alter feature ponderation, which
-    // may yield to better playlists (subjectively).
-    let m = Array::eye(analysis_first_song.len());
-
-    songs.sort_by_cached_key(|song| {
-        n32((arr1(&song.analysis) - &analysis_first_song)
-            .dot(&m)
-            .dot(&(arr1(&song.analysis) - &analysis_first_song)))
-    });
+    songs.sort_by_cached_key(|song| n32(first_song.distance(&song)));
     println!(
         "Playlist is: {:?}",
         songs
@@ -83,16 +89,42 @@ fn main() -> Result<(), BlissError> {
 
 Instead of reinventing ways to fetch a user library, play songs, etc,
 and embed that into bliss, it is easier to look at the
-[Library](https://github.com/Polochon-street/bliss-rs/blob/master/src/library.rs#L12)
-trait.
-
-By implementing a few functions to get songs from a media library, and store
-the resulting analysis, you get access to functions to analyze an entire
-library (with multithreading), and to make playlists easily.
+[library](https://docs.rs/bliss-audio/latest/bliss_audio/library/index.html) module.
+It implements common analysis functions, and allows analyzed songs to be put
+in a sqlite database seamlessly.
 
 See [blissify](https://crates.io/crates/blissify) for a reference
 implementation.
 
+## Cross-compilation
+
+To cross-compile bliss-rs from linux to x86_64 windows, install the
+`x86_64-pc-windows-gnu` target via:
+
+        rustup target add x86_64-pc-windows-gnu
+
+Make sure you have `x86_64-w64-mingw32-gcc` installed on your computer.
+
+Then run:
+
+        cargo build --target x86_64-pc-windows-gnu --release
+
+Will produce a `.rlib` library file. If you want to generate a shared `.dll`
+library, add:
+
+        [lib]
+        crate-type = ["cdylib"]
+
+to `Cargo.toml` before compiling, and if you want to generate a `.lib` static
+library, add:
+
+        [lib]
+        crate-type = ["staticlib"]
+
+You can of course test the examples yourself by compiling them as .exe:
+
+        cargo build --target x86_64-pc-windows-gnu --release --examples
+
 ## Acknowledgements
 
 * This library relies heavily on [aubio](https://aubio.org/)'s

data/empty.cue

@@ -0,0 +1,29 @@
+REM GENRE Random
+REM DATE 2022
+PERFORMER "Polochon_street"
+TITLE "Album for CUE test"
+FILE "empty.wav" WAVE
+  TRACK 01 AUDIO
+    TITLE "Renaissance"
+    PERFORMER "David TMX"
+    INDEX 01 0:00:00
+  TRACK 02 AUDIO
+    TITLE "Piano"
+    PERFORMER "Polochon_street"
+    INDEX 01 0:11:05
+  TRACK 03 AUDIO
+    TITLE "Tone"
+    PERFORMER "Polochon_street"
+    INDEX 01 0:16:69
+
+FILE "not-existing.wav" WAVE
+  TRACK 01 AUDIO
+    TITLE "Nope"
+    PERFORMER "Charlie"
+    INDEX 01 0:00:00
+  TRACK 02 AUDIO
+    TITLE "Nope"
+    PERFORMER "Charlie"
+    INDEX 01 0:10:00
+
+

data/testcue.cue

@@ -0,0 +1,29 @@
+REM GENRE Random
+REM DATE 2022
+PERFORMER "Polochon_street"
+TITLE "Album for CUE test"
+FILE "testcue.flac" WAVE
+  TRACK 01 AUDIO
+    TITLE "Renaissance"
+    PERFORMER "David TMX"
+    INDEX 01 0:00:00
+  TRACK 02 AUDIO
+    TITLE "Piano"
+    PERFORMER "Polochon_street"
+    INDEX 01 0:11:05
+  TRACK 03 AUDIO
+    TITLE "Tone"
+    PERFORMER "Polochon_street"
+    INDEX 01 0:16:69
+
+FILE "not-existing.wav" WAVE
+  TRACK 01 AUDIO
+    TITLE "Nope"
+    PERFORMER "Charlie"
+    INDEX 01 0:00:00
+  TRACK 02 AUDIO
+    TITLE "Nope"
+    PERFORMER "Charlie"
+    INDEX 01 0:10:00
+
+

examples/analyze.rs

@@ -1,16 +1,16 @@
-use bliss_audio::Song;
+use bliss_audio_symphonia::Song;
 use std::env;
 
 /**
  * Simple utility to print the result of an Analysis.
  *
- * Takes a list of files to analyse an the result of the corresponding Analysis.
+ * Takes a list of files to analyze an the result of the corresponding Analysis.
  */
 fn main() {
     let args: Vec<String> = env::args().skip(1).collect();
     for path in &args {
-        match Song::new(&path) {
-            Ok(song) => println!("{}: {:?}", path, song.analysis,),
+        match Song::from_path(&path) {
+            Ok(song) => println!("{}: {:?}", path, song.analysis),
             Err(e) => println!("{}: {}", path, e),
         }
     }

examples/distance.rs

@@ -1,10 +1,10 @@
-use bliss_audio::Song;
+use bliss_audio_symphonia::Song;
 use std::env;
 
 /**
  * Simple utility to print distance between two songs according to bliss.
  *
- * Takes two file paths, and analyse the corresponding songs, printing
+ * Takes two file paths, and analyze the corresponding songs, printing
  * the distance between the two files according to bliss.
  */
 fn main() -> Result<(), String> {
@@ -13,11 +13,11 @@ fn main() -> Result<(), String> {
     let first_path = paths.next().ok_or("Help: ./distance <song1> <song2>")?;
     let second_path = paths.next().ok_or("Help: ./distance <song1> <song2>")?;
 
-    let song1 = Song::new(&first_path).map_err(|x| x.to_string())?;
-    let song2 = Song::new(&second_path).map_err(|x| x.to_string())?;
+    let song1 = Song::from_path(&first_path).map_err(|x| x.to_string())?;
+    let song2 = Song::from_path(&second_path).map_err(|x| x.to_string())?;
 
     println!(
-        "d({}, {}) = {}",
+        "d({:?}, {:?}) = {}",
         song1.path,
         song2.path,
         song1.distance(&song2)

examples/library.rs

@@ -0,0 +1,204 @@
+/// Basic example of how one would combine bliss with an "audio player",
+/// through [Library].
+///
+/// For simplicity's sake, this example recursively gets songs from a folder
+/// to emulate an audio player library, without handling CUE files.
+use anyhow::Result;
+use bliss_audio::library::{AppConfigTrait, BaseConfig, Library};
+use clap::{App, Arg, SubCommand};
+use glob::glob;
+use serde::{Deserialize, Serialize};
+use std::fs;
+use std::num::NonZeroUsize;
+use std::path::{Path, PathBuf};
+
+#[derive(Serialize, Deserialize, Clone, Debug)]
+// A config structure, that will be serialized as a
+// JSON file upon Library creation.
+pub struct Config {
+    #[serde(flatten)]
+    // The base configuration, containing both the config file
+    // path, as well as the database path.
+    pub base_config: BaseConfig,
+    // An extra field, to store the music library path. Any number
+    // of arbitrary fields (even Serializable structures) can
+    // of course be added.
+    pub music_library_path: PathBuf,
+}
+
+impl Config {
+    pub fn new(
+        music_library_path: PathBuf,
+        config_path: Option<PathBuf>,
+        database_path: Option<PathBuf>,
+        number_cores: Option<NonZeroUsize>,
+    ) -> Result<Self> {
+        let base_config = BaseConfig::new(config_path, database_path, number_cores)?;
+        Ok(Self {
+            base_config,
+            music_library_path,
+        })
+    }
+}
+
+// The AppConfigTrait must know how to access the base config.
+impl AppConfigTrait for Config {
+    fn base_config(&self) -> &BaseConfig {
+        &self.base_config
+    }
+
+    fn base_config_mut(&mut self) -> &mut BaseConfig {
+        &mut self.base_config
+    }
+}
+
+// A trait allowing to implement methods for the Library,
+// useful if you don't need to store extra information in fields.
+// Otherwise, doing
+// ```
+// struct CustomLibrary {
+//    library: Library<Config>,
+//    extra_field: ...,
+// }
+// ```
+// and implementing functions for that struct would be the way to go.
+// That's what the [reference](https://github.com/Polochon-street/blissify-rs)
+// implementation does.
+trait CustomLibrary {
+    fn song_paths(&self) -> Result<Vec<String>>;
+}
+
+impl CustomLibrary for Library<Config> {
+    /// Get all songs in the player library
+    fn song_paths(&self) -> Result<Vec<String>> {
+        let music_path = &self.config.music_library_path;
+        let pattern = Path::new(&music_path).join("**").join("*");
+
+        Ok(glob(&pattern.to_string_lossy())?
+            .map(|e| fs::canonicalize(e.unwrap()).unwrap())
+            .filter(|e| match mime_guess::from_path(e).first() {
+                Some(m) => m.type_() == "audio",
+                None => false,
+            })
+            .map(|x| x.to_string_lossy().to_string())
+            .collect::<Vec<String>>())
+    }
+}
+
+// A simple example of what a CLI-app would look.
+//
+// Note that `Library::new` is used only on init, and subsequent
+// commands use `Library::from_path`.
+fn main() -> Result<()> {
+    let matches = App::new("library-example")
+        .version(env!("CARGO_PKG_VERSION"))
+        .author("Polochon_street")
+        .about("Example binary implementing bliss for an audio player.")
+        .subcommand(
+            SubCommand::with_name("init")
+                .about(
+                    "Initialize a Library, both storing the config and analyzing folders
+                containing songs.",
+                )
+                .arg(
+                    Arg::with_name("FOLDER")
+                        .help("A folder containing the music library to analyze.")
+                        .required(true),
+                )
+                .arg(
+                    Arg::with_name("database-path")
+                        .short("d")
+                        .long("database-path")
+                        .help(
+                            "Optional path where to store the database file containing
+                 the songs' analysis. Defaults to XDG_DATA_HOME/bliss-rs/bliss.db.",
+                        )
+                        .takes_value(true),
+                )
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to store the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                ),
+        )
+        .subcommand(
+            SubCommand::with_name("update")
+                .about(
+                    "Update a Library's songs, trying to analyze failed songs,
+                    as well as songs not in the library.",
+                )
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to load the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                ),
+        )
+        .subcommand(
+            SubCommand::with_name("playlist")
+                .about(
+                    "Make a playlist, starting with the song at SONG_PATH, returning
+                       the songs' paths.",
+                )
+                .arg(Arg::with_name("SONG_PATH").takes_value(true))
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to load the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                )
+                .arg(
+                    Arg::with_name("playlist-length")
+                        .short("l")
+                        .long("playlist-length")
+                        .help("Optional playlist length. Defaults to 20.")
+                        .takes_value(true),
+                ),
+        )
+        .get_matches();
+    if let Some(sub_m) = matches.subcommand_matches("init") {
+        let folder = PathBuf::from(sub_m.value_of("FOLDER").unwrap());
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let database_path = sub_m.value_of("database-path").map(PathBuf::from);
+
+        let config = Config::new(folder, config_path, database_path, None)?;
+        let mut library = Library::new(config)?;
+
+        library.analyze_paths(library.song_paths()?, true)?;
+    } else if let Some(sub_m) = matches.subcommand_matches("update") {
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let mut library: Library<Config> = Library::from_config_path(config_path)?;
+        library.update_library(library.song_paths()?, true)?;
+    } else if let Some(sub_m) = matches.subcommand_matches("playlist") {
+        let song_path = sub_m.value_of("SONG_PATH").unwrap();
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let playlist_length = sub_m
+            .value_of("playlist-length")
+            .unwrap_or("20")
+            .parse::<usize>()?;
+        let library: Library<Config> = Library::from_config_path(config_path)?;
+        let songs = library.playlist_from::<()>(song_path, playlist_length)?;
+        let song_paths = songs
+            .into_iter()
+            .map(|s| s.bliss_song.path.to_string_lossy().to_string())
+            .collect::<Vec<String>>();
+        for song in song_paths {
+            println!("{:?}", song);
+        }
+    }
+
+    Ok(())
+}

examples/library_extra_info.rs

@@ -0,0 +1,227 @@
+/// Basic example of how one would combine bliss with an "audio player",
+/// through [Library], showing how to put extra info in the database for
+/// each song.
+///
+/// For simplicity's sake, this example recursively gets songs from a folder
+/// to emulate an audio player library, without handling CUE files.
+use anyhow::Result;
+use bliss_audio::library::{AppConfigTrait, BaseConfig, Library};
+use clap::{App, Arg, SubCommand};
+use glob::glob;
+use serde::{Deserialize, Serialize};
+use std::fs;
+use std::num::NonZeroUsize;
+use std::path::{Path, PathBuf};
+
+#[derive(Serialize, Deserialize, Clone, Debug)]
+/// A config structure, that will be serialized as a
+/// JSON file upon Library creation.
+pub struct Config {
+    #[serde(flatten)]
+    /// The base configuration, containing both the config file
+    /// path, as well as the database path.
+    pub base_config: BaseConfig,
+    /// An extra field, to store the music library path. Any number
+    /// of arbitrary fields (even Serializable structures) can
+    /// of course be added.
+    pub music_library_path: PathBuf,
+}
+
+impl Config {
+    pub fn new(
+        music_library_path: PathBuf,
+        config_path: Option<PathBuf>,
+        database_path: Option<PathBuf>,
+        number_cores: Option<NonZeroUsize>,
+    ) -> Result<Self> {
+        let base_config = BaseConfig::new(config_path, database_path, number_cores)?;
+        Ok(Self {
+            base_config,
+            music_library_path,
+        })
+    }
+}
+
+// The AppConfigTrait must know how to access the base config.
+impl AppConfigTrait for Config {
+    fn base_config(&self) -> &BaseConfig {
+        &self.base_config
+    }
+
+    fn base_config_mut(&mut self) -> &mut BaseConfig {
+        &mut self.base_config
+    }
+}
+
+// A trait allowing to implement methods for the Library,
+// useful if you don't need to store extra information in fields.
+// Otherwise, doing
+// ```
+// struct CustomLibrary {
+//    library: Library<Config>,
+//    extra_field: ...,
+// }
+// ```
+// and implementing functions for that struct would be the way to go.
+// That's what the [reference](https://github.com/Polochon-street/blissify-rs)
+// implementation does.
+trait CustomLibrary {
+    fn song_paths_info(&self) -> Result<Vec<(String, ExtraInfo)>>;
+}
+
+impl CustomLibrary for Library<Config> {
+    /// Get all songs in the player library, along with the extra info
+    /// one would want to store along with each song.
+    fn song_paths_info(&self) -> Result<Vec<(String, ExtraInfo)>> {
+        let music_path = &self.config.music_library_path;
+        let pattern = Path::new(&music_path).join("**").join("*");
+
+        Ok(glob(&pattern.to_string_lossy())?
+            .map(|e| fs::canonicalize(e.unwrap()).unwrap())
+            .filter_map(|e| {
+                mime_guess::from_path(&e).first().map(|m| {
+                    (
+                        e.to_string_lossy().to_string(),
+                        ExtraInfo {
+                            extension: e.extension().map(|e| e.to_string_lossy().to_string()),
+                            file_name: e.file_name().map(|e| e.to_string_lossy().to_string()),
+                            mime_type: format!("{}/{}", m.type_(), m.subtype()),
+                        },
+                    )
+                })
+            })
+            .collect::<Vec<(String, ExtraInfo)>>())
+    }
+}
+
+#[derive(Deserialize, Serialize, Debug, PartialEq, Clone, Default)]
+// An (somewhat simple) example of what extra metadata one would put, along
+// with song analysis data.
+struct ExtraInfo {
+    extension: Option<String>,
+    file_name: Option<String>,
+    mime_type: String,
+}
+
+// A simple example of what a CLI-app would look.
+//
+// Note that `Library::new` is used only on init, and subsequent
+// commands use `Library::from_path`.
+fn main() -> Result<()> {
+    let matches = App::new("library-example")
+        .version(env!("CARGO_PKG_VERSION"))
+        .author("Polochon_street")
+        .about("Example binary implementing bliss for an audio player.")
+        .subcommand(
+            SubCommand::with_name("init")
+                .about(
+                    "Initialize a Library, both storing the config and analyzing folders
+                containing songs.",
+                )
+                .arg(
+                    Arg::with_name("FOLDER")
+                        .help("A folder containing the music library to analyze.")
+                        .required(true),
+                )
+                .arg(
+                    Arg::with_name("database-path")
+                        .short("d")
+                        .long("database-path")
+                        .help(
+                            "Optional path where to store the database file containing
+                 the songs' analysis. Defaults to XDG_DATA_HOME/bliss-rs/bliss.db.",
+                        )
+                        .takes_value(true),
+                )
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to store the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                ),
+        )
+        .subcommand(
+            SubCommand::with_name("update")
+                .about(
+                    "Update a Library's songs, trying to analyze failed songs,
+                    as well as songs not in the library.",
+                )
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to load the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                ),
+        )
+        .subcommand(
+            SubCommand::with_name("playlist")
+                .about(
+                    "Make a playlist, starting with the song at SONG_PATH, returning
+                       the songs' paths.",
+                )
+                .arg(Arg::with_name("SONG_PATH").takes_value(true))
+                .arg(
+                    Arg::with_name("config-path")
+                        .short("c")
+                        .long("config-path")
+                        .help(
+                            "Optional path where to load the config file containing
+                 the library setup. Defaults to XDG_DATA_HOME/bliss-rs/config.json.",
+                        )
+                        .takes_value(true),
+                )
+                .arg(
+                    Arg::with_name("playlist-length")
+                        .short("l")
+                        .long("playlist-length")
+                        .help("Optional playlist length. Defaults to 20.")
+                        .takes_value(true),
+                ),
+        )
+        .get_matches();
+    if let Some(sub_m) = matches.subcommand_matches("init") {
+        let folder = PathBuf::from(sub_m.value_of("FOLDER").unwrap());
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let database_path = sub_m.value_of("database-path").map(PathBuf::from);
+
+        let config = Config::new(folder, config_path, database_path, None)?;
+        let mut library = Library::new(config)?;
+
+        library.analyze_paths_extra_info(library.song_paths_info()?, true)?;
+    } else if let Some(sub_m) = matches.subcommand_matches("update") {
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let mut library: Library<Config> = Library::from_config_path(config_path)?;
+        library.update_library_extra_info(library.song_paths_info()?, true)?;
+    } else if let Some(sub_m) = matches.subcommand_matches("playlist") {
+        let song_path = sub_m.value_of("SONG_PATH").unwrap();
+        let config_path = sub_m.value_of("config-path").map(PathBuf::from);
+        let playlist_length = sub_m
+            .value_of("playlist-length")
+            .unwrap_or("20")
+            .parse::<usize>()?;
+        let library: Library<Config> = Library::from_config_path(config_path)?;
+        let songs = library.playlist_from::<ExtraInfo>(song_path, playlist_length)?;
+        let playlist = songs
+            .into_iter()
+            .map(|s| {
+                (
+                    s.bliss_song.path.to_string_lossy().to_string(),
+                    s.extra_info.mime_type,
+                )
+            })
+            .collect::<Vec<(String, String)>>();
+        for (path, mime_type) in playlist {
+            println!("{} <{}>", path, mime_type,);
+        }
+    }
+
+    Ok(())
+}

examples/playlist.rs

@@ -0,0 +1,95 @@
+use anyhow::Result;
+use bliss_audio_symphonia::playlist::{closest_to_first_song, dedup_playlist, euclidean_distance};
+use bliss_audio_symphonia::{analyze_paths, Song};
+use clap::{App, Arg};
+use glob::glob;
+use std::env;
+use std::fs;
+use std::io::BufReader;
+use std::path::{Path, PathBuf};
+
+/* Analyzes a folder recursively, and make a playlist out of the file
+ * provided by the user. */
+// How to use: ./playlist [-o file.m3u] [-a analysis.json] <folder> <file to start the playlist from>
+fn main() -> Result<()> {
+    let matches = App::new("playlist")
+        .version(env!("CARGO_PKG_VERSION"))
+        .author("Polochon_street")
+        .about("Analyze a folder and make a playlist from a target song")
+        .arg(Arg::with_name("output-playlist").short("o").long("output-playlist")
+            .value_name("PLAYLIST.M3U")
+            .help("Outputs the playlist to a file.")
+            .takes_value(true))
+        .arg(Arg::with_name("analysis-file").short("a").long("analysis-file")
+            .value_name("ANALYSIS.JSON")
+            .help("Use the songs that have been analyzed in <analysis-file>, and appends newly analyzed songs to it. Defaults to /tmp/analysis.json.")
+            .takes_value(true))
+        .arg(Arg::with_name("FOLDER").help("Folders containing some songs.").required(true))
+        .arg(Arg::with_name("FIRST-SONG").help("Song to start from (can be outside of FOLDER).").required(true))
+        .get_matches();
+
+    let folder = matches.value_of("FOLDER").unwrap();
+    let file = fs::canonicalize(matches.value_of("FIRST-SONG").unwrap())?;
+    let pattern = Path::new(folder).join("**").join("*");
+
+    let mut songs: Vec<Song> = Vec::new();
+    let analysis_path = matches
+        .value_of("analysis-file")
+        .unwrap_or("/tmp/analysis.json");
+    let analysis_file = fs::File::open(analysis_path);
+    if let Ok(f) = analysis_file {
+        let reader = BufReader::new(f);
+        songs = serde_json::from_reader(reader)?;
+    }
+
+    let analyzed_paths = songs
+        .iter()
+        .map(|s| s.path.to_owned())
+        .collect::<Vec<PathBuf>>();
+
+    let paths = glob(&pattern.to_string_lossy())?
+        .map(|e| fs::canonicalize(e.unwrap()).unwrap())
+        .filter(|e| match mime_guess::from_path(e).first() {
+            Some(m) => m.type_() == "audio",
+            None => false,
+        })
+        .map(|x| x.to_string_lossy().to_string())
+        .collect::<Vec<String>>();
+
+    let song_iterator = analyze_paths(
+        paths
+            .iter()
+            .filter(|p| !analyzed_paths.contains(&PathBuf::from(p)))
+            .map(|p| p.to_owned())
+            .collect::<Vec<String>>(),
+    );
+    let first_song = Song::from_path(file)?;
+    let mut analyzed_songs = vec![first_song.to_owned()];
+    for (path, result) in song_iterator {
+        match result {
+            Ok(song) => analyzed_songs.push(song),
+            Err(e) => println!("error analyzing {}: {}", path.display(), e),
+        };
+    }
+    analyzed_songs.extend_from_slice(&songs);
+    let serialized = serde_json::to_string(&analyzed_songs).unwrap();
+    let mut songs_to_chose_from: Vec<_> = analyzed_songs
+        .into_iter()
+        .filter(|x| x == &first_song || paths.contains(&x.path.to_string_lossy().to_string()))
+        .collect();
+    closest_to_first_song(&first_song, &mut songs_to_chose_from, euclidean_distance);
+    dedup_playlist(&mut songs_to_chose_from, None);
+
+    fs::write(analysis_path, serialized)?;
+    let playlist = songs_to_chose_from
+        .iter()
+        .map(|s| s.path.to_string_lossy().to_string())
+        .collect::<Vec<String>>()
+        .join("\n");
+    if let Some(m) = matches.value_of("output-playlist") {
+        fs::write(m, playlist)?;
+    } else {
+        println!("{}", playlist);
+    }
+    Ok(())
+}

src/chroma.rs

@@ -7,7 +7,7 @@ extern crate noisy_float;
 
 use crate::utils::stft;
 use crate::utils::{hz_to_octs_inplace, Normalize};
-use crate::BlissError;
+use crate::{BlissError, BlissResult};
 use ndarray::{arr1, arr2, concatenate, s, Array, Array1, Array2, Axis, Zip};
 use ndarray_stats::interpolate::Midpoint;
 use ndarray_stats::QuantileExt;
@@ -51,7 +51,7 @@ impl ChromaDesc {
      * Passing a full song here once instead of streaming smaller parts of the
      * song will greatly improve accuracy.
      */
-    pub fn do_(&mut self, signal: &[f32]) -> Result<(), BlissError> {
+    pub fn do_(&mut self, signal: &[f32]) -> BlissResult<()> {
         let mut stft = stft(signal, ChromaDesc::WINDOW_SIZE, 2205);
         let tuning = estimate_tuning(
             self.sample_rate as u32,
@@ -155,7 +155,7 @@ fn chroma_filter(
     n_fft: usize,
     n_chroma: u32,
     tuning: f64,
-) -> Result<Array2<f64>, BlissError> {
+) -> BlissResult<Array2<f64>> {
     let ctroct = 5.0;
     let octwidth = 2.;
     let n_chroma_float = f64::from(n_chroma);
@@ -180,7 +180,7 @@ fn chroma_filter(
         }),
     );
 
-    let mut d: Array2<f64> = Array::zeros((n_chroma as usize, (&freq_bins).len()));
+    let mut d: Array2<f64> = Array::zeros((n_chroma as usize, (freq_bins).len()));
     for (idx, mut row) in d.rows_mut().into_iter().enumerate() {
         row.fill(idx as f64);
     }
@@ -207,13 +207,13 @@ fn chroma_filter(
     wts *= &freq_bins;
 
     // np.roll(), np bro
-    let mut uninit: Vec<f64> = Vec::with_capacity((&wts).len());
+    let mut uninit: Vec<f64> = vec![0.; (wts).len()];
     unsafe {
         uninit.set_len(wts.len());
     }
     let mut b = Array::from(uninit)
         .into_shape(wts.dim())
-        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?;
+        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?;
     b.slice_mut(s![-3.., ..]).assign(&wts.slice(s![..3, ..]));
     b.slice_mut(s![..-3, ..]).assign(&wts.slice(s![3.., ..]));
 
@@ -226,7 +226,7 @@ fn pip_track(
     sample_rate: u32,
     spectrum: &Array2<f64>,
     n_fft: usize,
-) -> Result<(Vec<f64>, Vec<f64>), BlissError> {
+) -> BlissResult<(Vec<f64>, Vec<f64>)> {
     let sample_rate_float = f64::from(sample_rate);
     let fmin = 150.0_f64;
     let fmax = 4000.0_f64.min(sample_rate_float / 2.0);
@@ -291,7 +291,7 @@ fn pitch_tuning(
     frequencies: &mut Array1<f64>,
     resolution: f64,
     bins_per_octave: u32,
-) -> Result<f64, BlissError> {
+) -> BlissResult<f64> {
     if frequencies.is_empty() {
         return Ok(0.0);
     }
@@ -308,7 +308,7 @@ fn pitch_tuning(
     }
     let max_index = counts
         .argmax()
-        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?;
+        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?;
 
     // Return the bin with the most reoccuring frequency.
     Ok((-50. + (100. * resolution * max_index as f64)) / 100.)
@@ -320,8 +320,8 @@ fn estimate_tuning(
     n_fft: usize,
     resolution: f64,
     bins_per_octave: u32,
-) -> Result<f64, BlissError> {
-    let (pitch, mag) = pip_track(sample_rate, &spectrum, n_fft)?;
+) -> BlissResult<f64> {
+    let (pitch, mag) = pip_track(sample_rate, spectrum, n_fft)?;
 
     let (filtered_pitch, filtered_mag): (Vec<N64>, Vec<N64>) = pitch
         .iter()
@@ -330,11 +330,14 @@ fn estimate_tuning(
         .map(|(x, y)| (n64(*x), n64(*y)))
         .unzip();
 
+    if pitch.is_empty() {
+        return Ok(0.);
+    }
+
     let threshold: N64 = Array::from(filtered_mag.to_vec())
         .quantile_axis_mut(Axis(0), n64(0.5), &Midpoint)
-        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e.to_string())))?
+        .map_err(|e| BlissError::AnalysisError(format!("in chroma: {}", e)))?
         .into_scalar();
-
     let mut pitch = filtered_pitch
         .iter()
         .zip(&filtered_mag)
@@ -372,6 +375,7 @@ mod test {
     use ndarray::{arr1, arr2, Array2};
     use ndarray_npy::ReadNpyExt;
     use std::fs::File;
+    use std::path::Path;
 
     #[test]
     fn test_chroma_interval_features() {
@@ -437,7 +441,7 @@ mod test {
 
     #[test]
     fn test_chroma_desc() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut chroma_desc = ChromaDesc::new(SAMPLE_RATE, 12);
         chroma_desc.do_(&song.sample_array).unwrap();
         let expected_values = vec![
@@ -459,7 +463,7 @@ mod test {
 
     #[test]
     fn test_chroma_stft_decode() {
-        let signal = Song::decode("data/s16_mono_22_5kHz.flac")
+        let signal = Song::decode(Path::new("data/s16_mono_22_5kHz.flac"))
             .unwrap()
             .sample_array;
         let mut stft = stft(&signal, 8192, 2205);
@@ -485,9 +489,14 @@ mod test {
         assert!(0.000001 > (-0.09999999999999998 - tuning).abs());
     }
 
+    #[test]
+    fn test_chroma_estimate_tuning_empty_fix() {
+        assert!(0. == estimate_tuning(22050, &Array2::zeros((8192, 1)), 8192, 0.01, 12).unwrap());
+    }
+
     #[test]
     fn test_estimate_tuning_decode() {
-        let signal = Song::decode("data/s16_mono_22_5kHz.flac")
+        let signal = Song::decode(Path::new("data/s16_mono_22_5kHz.flac"))
             .unwrap()
             .sample_array;
         let stft = stft(&signal, 8192, 2205);
@@ -555,6 +564,7 @@ mod bench {
     use ndarray::{arr2, Array1, Array2};
     use ndarray_npy::ReadNpyExt;
     use std::fs::File;
+    use std::path::Path;
     use test::Bencher;
 
     #[bench]
@@ -603,7 +613,7 @@ mod bench {
 
     #[bench]
     fn bench_chroma_desc(b: &mut Bencher) {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut chroma_desc = ChromaDesc::new(SAMPLE_RATE, 12);
         let signal = song.sample_array;
         b.iter(|| {
@@ -614,7 +624,7 @@ mod bench {
 
     #[bench]
     fn bench_chroma_stft(b: &mut Bencher) {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut chroma_desc = ChromaDesc::new(SAMPLE_RATE, 12);
         let signal = song.sample_array;
         b.iter(|| {
@@ -625,7 +635,7 @@ mod bench {
 
     #[bench]
     fn bench_chroma_stft_decode(b: &mut Bencher) {
-        let signal = Song::decode("data/s16_mono_22_5kHz.flac")
+        let signal = Song::decode(Path::new("data/s16_mono_22_5kHz.flac"))
             .unwrap()
             .sample_array;
         let mut stft = stft(&signal, 8192, 2205);

src/cue.rs

@@ -0,0 +1,338 @@
+//! CUE-handling module.
+//!
+//! Using [BlissCue::songs_from_path] is most likely what you want.
+
+use crate::{Analysis, BlissError, BlissResult, Song, FEATURES_VERSION, SAMPLE_RATE};
+use rcue::cue::{Cue, Track};
+use rcue::parser::parse_from_file;
+use std::path::{Path, PathBuf};
+use std::time::Duration;
+
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Default, Debug, PartialEq, Eq, Clone)]
+/// A struct populated when the corresponding [Song] has been extracted from an
+/// audio file split with the help of a CUE sheet.
+pub struct CueInfo {
+    /// The path of the original CUE sheet, e.g. `/path/to/album_name.cue`.
+    pub cue_path: PathBuf,
+    /// The path of the audio file the song was extracted from, e.g.
+    /// `/path/to/album_name.wav`. Used because one CUE sheet can refer to
+    /// several audio files.
+    pub audio_file_path: PathBuf,
+}
+
+/// A struct to handle CUEs with bliss.
+/// Use either [analyze_paths](crate::analyze_paths) with CUE files or
+/// [songs_from_path](BlissCue::songs_from_path) to return a list of [Song]s
+/// from CUE files.
+pub struct BlissCue {
+    cue: Cue,
+    cue_path: PathBuf,
+}
+
+#[allow(missing_docs)]
+#[derive(Default, Debug, PartialEq, Clone)]
+struct BlissCueFile {
+    sample_array: Vec<f32>,
+    album: Option<String>,
+    artist: Option<String>,
+    genre: Option<String>,
+    tracks: Vec<Track>,
+    cue_path: PathBuf,
+    audio_file_path: PathBuf,
+}
+
+impl BlissCue {
+    /// Analyze songs from a CUE file, extracting individual [Song] objects
+    /// for each individual song.
+    ///
+    /// Each returned [Song] has a populated [cue_info](Song::cue_info) object, that can be
+    /// be used to retrieve which CUE sheet was used to extract it, as well
+    /// as the corresponding audio file.
+    pub fn songs_from_path<P: AsRef<Path>>(path: P) -> BlissResult<Vec<BlissResult<Song>>> {
+        let cue = BlissCue::from_path(&path)?;
+        let cue_files = cue.files();
+        let mut songs = Vec::new();
+        for cue_file in cue_files.into_iter() {
+            match cue_file {
+                Ok(f) => {
+                    if !f.sample_array.is_empty() {
+                        songs.extend_from_slice(&f.get_songs());
+                    } else {
+                        songs.push(Err(BlissError::DecodingError(
+                            "empty audio file associated to CUE sheet".into(),
+                        )));
+                    }
+                }
+                Err(e) => songs.push(Err(e)),
+            }
+        }
+        Ok(songs)
+    }
+
+    // Extract a BlissCue from a given path.
+    fn from_path<P: AsRef<Path>>(path: P) -> BlissResult<Self> {
+        let cue = parse_from_file(&path.as_ref().to_string_lossy(), false).map_err(|e| {
+            BlissError::DecodingError(format!(
+                "when opening CUE file '{:?}': {:?}",
+                path.as_ref(),
+                e
+            ))
+        })?;
+        Ok(BlissCue {
+            cue,
+            cue_path: path.as_ref().to_owned(),
+        })
+    }
+
+    // List all BlissCueFile from a BlissCue.
+    fn files(&self) -> Vec<BlissResult<BlissCueFile>> {
+        let mut cue_files = Vec::new();
+        for cue_file in self.cue.files.iter() {
+            let audio_file_path = match &self.cue_path.parent() {
+                Some(parent) => parent.join(Path::new(&cue_file.file)),
+                None => PathBuf::from(cue_file.file.to_owned()),
+            };
+            let genre = self
+                .cue
+                .comments
+                .iter()
+                .find(|(c, _)| c == "GENRE")
+                .map(|(_, v)| v.to_owned());
+            let raw_song = Song::decode(Path::new(&audio_file_path));
+            if let Ok(song) = raw_song {
+                let bliss_cue_file = BlissCueFile {
+                    sample_array: song.sample_array,
+                    genre,
+                    artist: self.cue.performer.to_owned(),
+                    album: self.cue.title.to_owned(),
+                    tracks: cue_file.tracks.to_owned(),
+                    audio_file_path,
+                    cue_path: self.cue_path.to_owned(),
+                };
+                cue_files.push(Ok(bliss_cue_file))
+            } else {
+                cue_files.push(Err(raw_song.unwrap_err()));
+            }
+        }
+        cue_files
+    }
+}
+
+impl BlissCueFile {
+    fn create_song(
+        &self,
+        analysis: BlissResult<Analysis>,
+        current_track: &Track,
+        duration: Duration,
+        index: usize,
+    ) -> BlissResult<Song> {
+        if let Ok(a) = analysis {
+            let song = Song {
+                path: PathBuf::from(format!(
+                    "{}/CUE_TRACK{:03}",
+                    self.cue_path.to_string_lossy(),
+                    index,
+                )),
+                album: self.album.to_owned(),
+                artist: current_track.performer.to_owned(),
+                album_artist: self.artist.to_owned(),
+                analysis: a,
+                duration,
+                genre: self.genre.to_owned(),
+                title: current_track.title.to_owned(),
+                track_number: Some(current_track.no.to_owned()),
+                features_version: FEATURES_VERSION,
+                cue_info: Some(CueInfo {
+                    cue_path: self.cue_path.to_owned(),
+                    audio_file_path: self.audio_file_path.to_owned(),
+                }),
+            };
+            Ok(song)
+        } else {
+            Err(analysis.unwrap_err())
+        }
+    }
+
+    // Get all songs from a BlissCueFile, using Song::analyze, each song being
+    // located using the sample_array and the timestamp delimiter.
+    fn get_songs(&self) -> Vec<BlissResult<Song>> {
+        let mut songs = Vec::new();
+        for (index, tuple) in (self.tracks[..]).windows(2).enumerate() {
+            let (current_track, next_track) = (tuple[0].to_owned(), tuple[1].to_owned());
+            if let Some((_, start_current)) = current_track.indices.get(0) {
+                if let Some((_, end_current)) = next_track.indices.get(0) {
+                    let start_current = (start_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
+                    let end_current = (end_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
+                    let duration = Duration::from_secs_f32(
+                        (end_current - start_current) as f32 / SAMPLE_RATE as f32,
+                    );
+                    let analysis = Song::analyze(&self.sample_array[start_current..end_current]);
+
+                    let song = self.create_song(analysis, &current_track, duration, index + 1);
+                    songs.push(song);
+                }
+            }
+        }
+        // Take care of the last track, since the windows iterator doesn't.
+        if let Some(last_track) = self.tracks.last() {
+            if let Some((_, start_current)) = last_track.indices.get(0) {
+                let start_current = (start_current.as_secs_f32() * SAMPLE_RATE as f32) as usize;
+                let duration = Duration::from_secs_f32(
+                    (self.sample_array.len() - start_current) as f32 / SAMPLE_RATE as f32,
+                );
+                let analysis = Song::analyze(&self.sample_array[start_current..]);
+                let song = self.create_song(analysis, last_track, duration, self.tracks.len());
+                songs.push(song);
+            }
+        }
+        songs
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use pretty_assertions::assert_eq;
+
+    #[test]
+    fn test_empty_cue() {
+        let songs = BlissCue::songs_from_path("data/empty.cue").unwrap();
+        let error = songs[0].to_owned().unwrap_err();
+        assert_eq!(
+            error,
+            BlissError::DecodingError("while opening format: DecodeError(\"wav: chunk length exceeds parent (list) chunk length\").".to_string())
+        );
+    }
+
+    #[test]
+    fn test_cue_analysis() {
+        let songs = BlissCue::songs_from_path("data/testcue.cue").unwrap();
+        let expected = vec![
+            Ok(Song {
+                path: Path::new("data/testcue.cue/CUE_TRACK001").to_path_buf(),
+                analysis: Analysis {
+                    internal_analysis: [
+                        0.38463724,
+                        -0.85219246,
+                        -0.761946,
+                        -0.8904667,
+                        -0.63892543,
+                        -0.73945934,
+                        -0.8004017,
+                        -0.8237293,
+                        0.33865356,
+                        0.32481194,
+                        -0.35692245,
+                        -0.6355889,
+                        -0.29584837,
+                        0.06431806,
+                        0.21875131,
+                        -0.58104205,
+                        -0.9466792,
+                        -0.94811195,
+                        -0.9820919,
+                        -0.9596871,
+                    ],
+                },
+                album: Some(String::from("Album for CUE test")),
+                artist: Some(String::from("David TMX")),
+                title: Some(String::from("Renaissance")),
+                genre: Some(String::from("Random")),
+                track_number: Some(String::from("01")),
+                features_version: FEATURES_VERSION,
+                album_artist: Some(String::from("Polochon_street")),
+                duration: Duration::from_secs_f32(11.066666603),
+                cue_info: Some(CueInfo {
+                    cue_path: PathBuf::from("data/testcue.cue"),
+                    audio_file_path: PathBuf::from("data/testcue.flac"),
+                }),
+                ..Default::default()
+            }),
+            Ok(Song {
+                path: Path::new("data/testcue.cue/CUE_TRACK002").to_path_buf(),
+                analysis: Analysis {
+                    internal_analysis: [
+                        0.18622077,
+                        -0.5989029,
+                        -0.5554645,
+                        -0.6343865,
+                        -0.24163479,
+                        -0.25766593,
+                        -0.40616858,
+                        -0.23334873,
+                        0.76875293,
+                        0.7785741,
+                        -0.5075115,
+                        -0.5272629,
+                        -0.56706166,
+                        -0.568486,
+                        -0.5639081,
+                        -0.5706943,
+                        -0.96501005,
+                        -0.96501285,
+                        -0.9649896,
+                        -0.96498996,
+                    ],
+                },
+                features_version: FEATURES_VERSION,
+                album: Some(String::from("Album for CUE test")),
+                artist: Some(String::from("Polochon_street")),
+                title: Some(String::from("Piano")),
+                genre: Some(String::from("Random")),
+                track_number: Some(String::from("02")),
+                album_artist: Some(String::from("Polochon_street")),
+                duration: Duration::from_secs_f64(5.853333473),
+                cue_info: Some(CueInfo {
+                    cue_path: PathBuf::from("data/testcue.cue"),
+                    audio_file_path: PathBuf::from("data/testcue.flac"),
+                }),
+                ..Default::default()
+            }),
+            Ok(Song {
+                path: Path::new("data/testcue.cue/CUE_TRACK003").to_path_buf(),
+                analysis: Analysis {
+                    internal_analysis: [
+                        0.0024261475,
+                        0.9874661,
+                        0.97330654,
+                        -0.9724426,
+                        0.99678576,
+                        -0.9961549,
+                        -0.9840142,
+                        -0.9269961,
+                        0.7498772,
+                        0.22429907,
+                        -0.8355152,
+                        -0.9977258,
+                        -0.9977849,
+                        -0.997785,
+                        -0.99778515,
+                        -0.997785,
+                        -0.99999976,
+                        -0.99999976,
+                        -0.99999976,
+                        -0.99999976,
+                    ],
+                },
+                album: Some(String::from("Album for CUE test")),
+                artist: Some(String::from("Polochon_street")),
+                title: Some(String::from("Tone")),
+                genre: Some(String::from("Random")),
+                track_number: Some(String::from("03")),
+                features_version: FEATURES_VERSION,
+                album_artist: Some(String::from("Polochon_street")),
+                duration: Duration::from_secs_f32(5.586666584),
+                cue_info: Some(CueInfo {
+                    cue_path: PathBuf::from("data/testcue.cue"),
+                    audio_file_path: PathBuf::from("data/testcue.flac"),
+                }),
+                ..Default::default()
+            }),
+            Err(BlissError::DecodingError(String::from(
+                "while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
+            ))),
+        ];
+        assert_eq!(expected, songs);
+    }
+}

src/lib.rs

@@ -1,28 +1,76 @@
+//! # bliss audio library
+//!
 //! bliss is a library for making "smart" audio playlists.
 //!
-//! The core of the library is the `Song` object, which relates to a
+//! The core of the library is the [Song] object, which relates to a
 //! specific analyzed song and contains its path, title, analysis, and
 //! other metadata fields (album, genre...).
-//! Analyzing a song is as simple as running `Song::new("/path/to/song")`.
+//! Analyzing a song is as simple as running `Song::from_path("/path/to/song")`.
 //!
-//! The [analysis](Song::analysis) field of each song is an array of f32, which makes the
-//! comparison between songs easy, by just using euclidean distance (see
-//! [distance](Song::distance) for instance).
+//! The [analysis](Song::analysis) field of each song is an array of f32, which
+//! makes the comparison between songs easy, by just using e.g. euclidean
+//! distance (see [distance](Song::distance) for instance).
 //!
 //! Once several songs have been analyzed, making a playlist from one Song
 //! is as easy as computing distances between that song and the rest, and ordering
 //! the songs by distance, ascending.
 //!
-//! It is also convenient to make plug-ins for existing audio players.
-//! It should be as easy as implementing the necessary traits for [Library].
-//! A reference implementation for the MPD player is available
-//! [here](https://github.com/Polochon-street/blissify-rs)
+//! If you want to implement a bliss plugin for an already existing audio
+//! player, the [Library] struct is a collection of goodies that should prove
+//! useful (it contains utilities to store analyzed songs in a self-contained
+//! database file, to make playlists directly from the database, etc).
+//! [blissify](https://github.com/Polochon-street/blissify-rs/) for both
+//! an example of how the [Library] struct works, and a real-life demo of bliss
+//! implemented for [MPD](https://www.musicpd.org/).
+//!
+//! # Examples
+//!
+//! ### Analyze & compute the distance between two songs
+//! ```no_run
+//! use bliss_audio::{BlissResult, Song};
+//!
+//! fn main() -> BlissResult<()> {
+//!     let song1 = Song::from_path("/path/to/song1")?;
+//!     let song2 = Song::from_path("/path/to/song2")?;
+//!
+//!     println!("Distance between song1 and song2 is {}", song1.distance(&song2));
+//!     Ok(())
+//! }
+//! ```
+//!
+//! ### Make a playlist from a song, discarding failed songs
+//! ```no_run
+//! use bliss_audio::{
+//!     analyze_paths,
+//!     playlist::{closest_to_first_song, euclidean_distance},
+//!     BlissResult, Song,
+//! };
+//!
+//! fn main() -> BlissResult<()> {
+//!     let paths = vec!["/path/to/song1", "/path/to/song2", "/path/to/song3"];
+//!     let mut songs: Vec<Song> = analyze_paths(&paths).filter_map(|(_, s)| s.ok()).collect();
+//!
+//!     // Assuming there is a first song
+//!     let first_song = songs.first().unwrap().to_owned();
+//!
+//!     closest_to_first_song(&first_song, &mut songs, euclidean_distance);
+//!
+//!     println!("Playlist is:");
+//!     for song in songs {
+//!         println!("{}", song.path.display());
+//!     }
+//!     Ok(())
+//! }
+//! ```
 #![cfg_attr(feature = "bench", feature(test))]
 #![warn(missing_docs)]
-#![warn(missing_doc_code_examples)]
+#![warn(rustdoc::missing_doc_code_examples)]
 mod chroma;
-mod library;
+pub mod cue;
+#[cfg(feature = "library")]
+pub mod library;
 mod misc;
+pub mod playlist;
 mod song;
 mod temporal;
 mod timbral;
@@ -33,68 +81,182 @@ extern crate num_cpus;
 #[cfg(feature = "serde")]
 #[macro_use]
 extern crate serde;
+use crate::cue::BlissCue;
+use log::info;
+use std::num::NonZeroUsize;
+use std::path::{Path, PathBuf};
+use std::sync::mpsc;
+use std::thread;
 use thiserror::Error;
 
-pub use song::Song;
-pub use library::Library;
+pub use song::{Analysis, AnalysisIndex, Song, NUMBER_FEATURES};
 
-const CHANNELS: u16 = 1;
+//const CHANNELS: u16 = 1;
 const SAMPLE_RATE: u32 = 22050;
+/// Stores the current version of bliss-rs' features.
+/// It is bumped every time one or more feature is added, updated or removed,
+/// so plug-ins can rescan libraries when there is a major change.
+pub const FEATURES_VERSION: u16 = 1;
 
-#[derive(Error, Debug, PartialEq)]
+#[derive(Error, Clone, Debug, PartialEq, Eq)]
 /// Umbrella type for bliss error types
 pub enum BlissError {
     #[error("error happened while decoding file – {0}")]
-    /// An error happened while decoding an (audio) file
+    /// An error happened while decoding an (audio) file.
     DecodingError(String),
     #[error("error happened while analyzing file – {0}")]
-    /// An error happened during the analysis of the samples by bliss
+    /// An error happened during the analysis of the song's samples by bliss.
     AnalysisError(String),
     #[error("error happened with the music library provider - {0}")]
     /// An error happened with the music library provider.
-    /// Useful to report errors when you implement the [Library] trait.
+    /// Useful to report errors when you implement bliss for an audio player.
     ProviderError(String),
 }
 
-/// Simple function to bulk analyze a set of songs represented by their
-/// absolute paths.
+/// bliss error type
+pub type BlissResult<T> = Result<T, BlissError>;
+
+/// Analyze songs in `paths`, and return the analyzed [Song] objects through an
+/// [mpsc::IntoIter].
 ///
-/// When making an extension for an audio player, prefer
-/// implementing the `Library` trait.
-#[doc(hidden)]
-pub fn bulk_analyse(paths: Vec<String>) -> Vec<Result<Song, BlissError>> {
-    let mut songs = Vec::with_capacity(paths.len());
-    let num_cpus = num_cpus::get();
-
-    crossbeam::scope(|s| {
-        let mut handles = Vec::with_capacity(paths.len() / num_cpus);
-        let mut chunk_number = paths.len() / num_cpus;
-        if chunk_number == 0 {
-            chunk_number = paths.len();
-        }
-        for chunk in paths.chunks(chunk_number) {
-            handles.push(s.spawn(move |_| {
-                let mut result = Vec::with_capacity(chunk.len());
-                for path in chunk {
-                    let song = Song::new(&path);
-                    result.push(song);
-                }
-                result
-            }));
+/// Returns an iterator, whose items are a tuple made of
+/// the song path (to display to the user in case the analysis failed),
+/// and a Result<Song>.
+///
+/// # Note
+///
+/// This function also works with CUE files - it finds the audio files
+/// mentionned in the CUE sheet, and then runs the analysis on each song
+/// defined by it, returning a proper [Song] object for each one of them.
+///
+/// Make sure that you don't submit both the audio file along with the CUE
+/// sheet if your library uses them, otherwise the audio file will be
+/// analyzed as one, single, long song. For instance, with a CUE sheet named
+/// `cue-file.cue` with the corresponding audio files `album-1.wav` and
+/// `album-2.wav` defined in the CUE sheet, you would just pass `cue-file.cue`
+/// to `analyze_paths`, and it will return [Song]s from both files, with
+/// more information about which file it is extracted from in the
+/// [cue info field](Song::cue_info).
+///
+/// # Example:
+/// ```no_run
+/// use bliss_audio::{analyze_paths, BlissResult};
+///
+/// fn main() -> BlissResult<()> {
+///     let paths = vec![String::from("/path/to/song1"), String::from("/path/to/song2")];
+///     for (path, result) in analyze_paths(&paths) {
+///         match result {
+///             Ok(song) => println!("Do something with analyzed song {} with title {:?}", song.path.display(), song.title),
+///             Err(e) => println!("Song at {} could not be analyzed. Failed with: {}", path.display(), e),
+///         }
+///     }
+///     Ok(())
+/// }
+/// ```
+pub fn analyze_paths<P: Into<PathBuf>, F: IntoIterator<Item = P>>(
+    paths: F,
+) -> mpsc::IntoIter<(PathBuf, BlissResult<Song>)> {
+    let cores = NonZeroUsize::new(num_cpus::get()).unwrap();
+    analyze_paths_with_cores(paths, cores)
 }
 
-        for handle in handles {
-            songs.extend(handle.join().unwrap());
+/// Analyze songs in `paths`, and return the analyzed [Song] objects through an
+/// [mpsc::IntoIter]. `number_cores` sets the number of cores the analysis
+/// will use, capped by your system's capacity. Most of the time, you want to
+/// use the simpler `analyze_paths` functions, which autodetects the number
+/// of cores in your system.
+///
+/// Return an iterator, whose items are a tuple made of
+/// the song path (to display to the user in case the analysis failed),
+/// and a Result<Song>.
+///
+/// # Note
+///
+/// This function also works with CUE files - it finds the audio files
+/// mentionned in the CUE sheet, and then runs the analysis on each song
+/// defined by it, returning a proper [Song] object for each one of them.
+///
+/// Make sure that you don't submit both the audio file along with the CUE
+/// sheet if your library uses them, otherwise the audio file will be
+/// analyzed as one, single, long song. For instance, with a CUE sheet named
+/// `cue-file.cue` with the corresponding audio files `album-1.wav` and
+/// `album-2.wav` defined in the CUE sheet, you would just pass `cue-file.cue`
+/// to `analyze_paths`, and it will return [Song]s from both files, with
+/// more information about which file it is extracted from in the
+/// [cue info field](Song::cue_info).
+///
+/// # Example:
+/// ```no_run
+/// use bliss_audio::{analyze_paths, BlissResult};
+///
+/// fn main() -> BlissResult<()> {
+///     let paths = vec![String::from("/path/to/song1"), String::from("/path/to/song2")];
+///     for (path, result) in analyze_paths(&paths) {
+///         match result {
+///             Ok(song) => println!("Do something with analyzed song {} with title {:?}", song.path.display(), song.title),
+///             Err(e) => println!("Song at {} could not be analyzed. Failed with: {}", path.display(), e),
+///         }
+///     }
+///     Ok(())
+/// }
+/// ```
+pub fn analyze_paths_with_cores<P: Into<PathBuf>, F: IntoIterator<Item = P>>(
+    paths: F,
+    number_cores: NonZeroUsize,
+) -> mpsc::IntoIter<(PathBuf, BlissResult<Song>)> {
+    let mut cores = NonZeroUsize::new(num_cpus::get()).unwrap();
+    if cores > number_cores {
+        cores = number_cores;
+    }
+    let paths: Vec<PathBuf> = paths.into_iter().map(|p| p.into()).collect();
+    #[allow(clippy::type_complexity)]
+    let (tx, rx): (
+        mpsc::Sender<(PathBuf, BlissResult<Song>)>,
+        mpsc::Receiver<(PathBuf, BlissResult<Song>)>,
+    ) = mpsc::channel();
+    if paths.is_empty() {
+        return rx.into_iter();
+    }
+    let mut handles = Vec::new();
+    let mut chunk_length = paths.len() / cores;
+    if chunk_length == 0 {
+        chunk_length = paths.len();
+    }
+    for chunk in paths.chunks(chunk_length) {
+        let tx_thread = tx.clone();
+        let owned_chunk = chunk.to_owned();
+        let child = thread::spawn(move || {
+            for path in owned_chunk {
+                info!("Analyzing file '{:?}'", path);
+                if let Some(extension) = Path::new(&path).extension() {
+                    let extension = extension.to_string_lossy().to_lowercase();
+                    if extension == "cue" {
+                        match BlissCue::songs_from_path(&path) {
+                            Ok(songs) => {
+                                for song in songs {
+                                    tx_thread.send((path.to_owned(), song)).unwrap();
+                                }
+                            }
+                            Err(e) => tx_thread.send((path.to_owned(), Err(e))).unwrap(),
+                        };
+                        continue;
+                    }
+                }
+                let song = Song::from_path(&path);
+                tx_thread.send((path.to_owned(), song)).unwrap();
+            }
+        });
+        handles.push(child);
     }
-    })
-    .unwrap();
 
-    songs
+    rx.into_iter()
 }
 
 #[cfg(test)]
 mod tests {
     use super::*;
+    #[cfg(test)]
+    use pretty_assertions::assert_eq;
 
     #[test]
     fn test_send_song() {
@@ -109,48 +271,59 @@ mod tests {
     }
 
     #[test]
-    fn test_bulk_analyse() {
-        let results = bulk_analyse(vec![
-            String::from("data/s16_mono_22_5kHz.flac"),
-            String::from("data/s16_mono_22_5kHz.flac"),
-            String::from("nonexistent"),
-            String::from("data/s16_stereo_22_5kHz.flac"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-            String::from("nonexistent"),
-        ]);
-        let mut errored_songs: Vec<String> = results
-            .iter()
-            .filter_map(|x| x.as_ref().err().map(|x| x.to_string()))
-            .collect();
-        errored_songs.sort_by(|a, b| a.cmp(b));
+    fn test_analyze_paths() {
+        let paths = vec![
+            "./data/s16_mono_22_5kHz.flac",
+            "./data/testcue.cue",
+            "./data/white_noise.flac",
+            "definitely-not-existing.foo",
+            "not-existing.foo",
+        ];
+        let mut results = analyze_paths(&paths)
+            .map(|x| match &x.1 {
+                Ok(s) => (true, s.path.to_owned(), None),
+                Err(e) => (false, x.0.to_owned(), Some(e.to_string())),
+            })
+            .collect::<Vec<_>>();
+        results.sort();
+        let expected_results = vec![
+            (
+                false,
+                PathBuf::from("./data/testcue.cue"),
+                Some(String::from(
+                    "error happened while decoding file – while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
+                )),
+            ),
+            (
+                false,
+                PathBuf::from("definitely-not-existing.foo"),
+                Some(String::from(
+                    "error happened while decoding file – while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
+                )),
+            ),
+            (
+                false,
+                PathBuf::from("not-existing.foo"),
+                Some(String::from(
+                    "error happened while decoding file – while opening song: Os { code: 2, kind: NotFound, message: \"No such file or directory\" }.",
+                )),
+            ),
+            (true, PathBuf::from("./data/s16_mono_22_5kHz.flac"), None),
+            (true, PathBuf::from("./data/testcue.cue/CUE_TRACK001"), None),
+            (true, PathBuf::from("./data/testcue.cue/CUE_TRACK002"), None),
+            (true, PathBuf::from("./data/testcue.cue/CUE_TRACK003"), None),
+            (true, PathBuf::from("./data/white_noise.flac"), None),
+        ];
 
-        let mut analysed_songs: Vec<String> = results
-            .iter()
-            .filter_map(|x| x.as_ref().ok().map(|x| x.path.to_string()))
-            .collect();
-        analysed_songs.sort_by(|a, b| a.cmp(b));
+        assert_eq!(results, expected_results);
 
-        assert_eq!(
-            vec![
-                String::from(
-                    "error happened while decoding file – while opening format: ffmpeg::Error(2: No such file or directory)."
-                );
-                8
-            ],
-            errored_songs
-        );
-        assert_eq!(
-            vec![
-                String::from("data/s16_mono_22_5kHz.flac"),
-                String::from("data/s16_mono_22_5kHz.flac"),
-                String::from("data/s16_stereo_22_5kHz.flac"),
-            ],
-            analysed_songs,
-        );
+        let mut results = analyze_paths_with_cores(&paths, NonZeroUsize::new(1).unwrap())
+            .map(|x| match &x.1 {
+                Ok(s) => (true, s.path.to_owned(), None),
+                Err(e) => (false, x.0.to_owned(), Some(e.to_string())),
+            })
+            .collect::<Vec<_>>();
+        results.sort();
+        assert_eq!(results, expected_results);
     }
 }

src/misc.rs

@@ -64,10 +64,11 @@ impl Normalize for LoudnessDesc {
 mod tests {
     use super::*;
     use crate::Song;
+    use std::path::Path;
 
     #[test]
     fn test_loudness() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut loudness_desc = LoudnessDesc::default();
         for chunk in song.sample_array.chunks_exact(LoudnessDesc::WINDOW_SIZE) {
             loudness_desc.do_(&chunk);

src/playlist.rs

@@ -0,0 +1,984 @@
+//! Module containing various functions to build playlists, as well as various
+//! distance metrics.
+//!
+//! All of the distance functions are intended to be used with the
+//! [custom_distance](Song::custom_distance) method, or with
+//!
+//! They will yield different styles of playlists, so don't hesitate to
+//! experiment with them if the default (euclidean distance for now) doesn't
+//! suit you.
+// TODO on the `by_key` functions: maybe Fn(&T) -> &Song is enough? Compared
+// to -> Song
+use crate::{BlissError, BlissResult, Song, NUMBER_FEATURES};
+use ndarray::{Array, Array1, Array2, Axis};
+use ndarray_stats::QuantileExt;
+use noisy_float::prelude::*;
+use std::collections::HashMap;
+
+/// Convenience trait for user-defined distance metrics.
+pub trait DistanceMetric: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
+impl<F> DistanceMetric for F where F: Fn(&Array1<f32>, &Array1<f32>) -> f32 {}
+
+/// Return the [euclidean
+/// distance](https://en.wikipedia.org/wiki/Euclidean_distance#Higher_dimensions)
+/// between two vectors.
+pub fn euclidean_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
+    // Could be any square symmetric positive semi-definite matrix;
+    // just no metric learning has been done yet.
+    // See https://lelele.io/thesis.pdf chapter 4.
+    let m = Array::eye(NUMBER_FEATURES);
+
+    (a - b).dot(&m).dot(&(a - b)).sqrt()
+}
+
+/// Return the [cosine
+/// distance](https://en.wikipedia.org/wiki/Cosine_similarity#Angular_distance_and_similarity)
+/// between two vectors.
+pub fn cosine_distance(a: &Array1<f32>, b: &Array1<f32>) -> f32 {
+    let similarity = a.dot(b) / (a.dot(a).sqrt() * b.dot(b).sqrt());
+    1. - similarity
+}
+
+/// Sort `songs` in place by putting songs close to `first_song` first
+/// using the `distance` metric.
+pub fn closest_to_first_song(
+    first_song: &Song,
+    #[allow(clippy::ptr_arg)] songs: &mut Vec<Song>,
+    distance: impl DistanceMetric,
+) {
+    songs.sort_by_cached_key(|song| n32(first_song.custom_distance(song, &distance)));
+}
+
+/// Sort `songs` in place by putting songs close to `first_song` first
+/// using the `distance` metric.
+///
+/// Sort songs with a key extraction function, useful for when you have a
+/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
+pub fn closest_to_first_song_by_key<F, T>(
+    first_song: &T,
+    #[allow(clippy::ptr_arg)] songs: &mut Vec<T>,
+    distance: impl DistanceMetric,
+    key_fn: F,
+) where
+    F: Fn(&T) -> Song,
+{
+    let first_song = key_fn(first_song);
+    songs.sort_by_cached_key(|song| n32(first_song.custom_distance(&key_fn(song), &distance)));
+}
+
+/// Sort `songs` in place using the `distance` metric and ordering by
+/// the smallest distance between each song.
+///
+/// If the generated playlist is `[song1, song2, song3, song4]`, it means
+/// song2 is closest to song1, song3 is closest to song2, and song4 is closest
+/// to song3.
+///
+/// Note that this has a tendency to go from one style to the other very fast,
+/// and it can be slow on big libraries.
+pub fn song_to_song(first_song: &Song, songs: &mut Vec<Song>, distance: impl DistanceMetric) {
+    let mut new_songs = Vec::with_capacity(songs.len());
+    let mut song = first_song.to_owned();
+
+    while !songs.is_empty() {
+        let distances: Array1<f32> =
+            Array::from_shape_fn(songs.len(), |i| song.custom_distance(&songs[i], &distance));
+        let idx = distances.argmin().unwrap();
+        song = songs[idx].to_owned();
+        new_songs.push(song.to_owned());
+        songs.retain(|s| s != &song);
+    }
+    *songs = new_songs;
+}
+
+/// Sort `songs` in place using the `distance` metric and ordering by
+/// the smallest distance between each song.
+///
+/// If the generated playlist is `[song1, song2, song3, song4]`, it means
+/// song2 is closest to song1, song3 is closest to song2, and song4 is closest
+/// to song3.
+///
+/// Note that this has a tendency to go from one style to the other very fast,
+/// and it can be slow on big libraries.
+///
+/// Sort songs with a key extraction function, useful for when you have a
+/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
+// TODO: maybe Clone is not needed?
+pub fn song_to_song_by_key<F, T: std::cmp::PartialEq + Clone>(
+    first_song: &T,
+    songs: &mut Vec<T>,
+    distance: impl DistanceMetric,
+    key_fn: F,
+) where
+    F: Fn(&T) -> Song,
+{
+    let mut new_songs: Vec<T> = Vec::with_capacity(songs.len());
+    let mut bliss_song = key_fn(&first_song.to_owned());
+
+    while !songs.is_empty() {
+        let distances: Array1<f32> = Array::from_shape_fn(songs.len(), |i| {
+            bliss_song.custom_distance(&key_fn(&songs[i]), &distance)
+        });
+        let idx = distances.argmin().unwrap();
+        let song = songs[idx].to_owned();
+        bliss_song = key_fn(&songs[idx]).to_owned();
+        new_songs.push(song.to_owned());
+        songs.retain(|s| s != &song);
+    }
+    *songs = new_songs;
+}
+
+/// Remove duplicate songs from a playlist, in place.
+///
+/// Two songs are considered duplicates if they either have the same,
+/// non-empty title and artist name, or if they are close enough in terms
+/// of distance.
+///
+/// # Arguments
+///
+/// * `songs`: The playlist to remove duplicates from.
+/// * `distance_threshold`: The distance threshold under which two songs are
+///   considered identical. If `None`, a default value of 0.05 will be used.
+pub fn dedup_playlist(songs: &mut Vec<Song>, distance_threshold: Option<f32>) {
+    dedup_playlist_custom_distance(songs, distance_threshold, euclidean_distance);
+}
+
+/// Remove duplicate songs from a playlist, in place.
+///
+/// Two songs are considered duplicates if they either have the same,
+/// non-empty title and artist name, or if they are close enough in terms
+/// of distance.
+///
+/// Dedup songs with a key extraction function, useful for when you have a
+/// structure like `CustomSong { bliss_song: Song, something_else: bool }` you
+/// want to deduplicate.
+///
+/// # Arguments
+///
+/// * `songs`: The playlist to remove duplicates from.
+/// * `distance_threshold`: The distance threshold under which two songs are
+///   considered identical. If `None`, a default value of 0.05 will be used.
+/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
+pub fn dedup_playlist_by_key<T, F>(songs: &mut Vec<T>, distance_threshold: Option<f32>, key_fn: F)
+where
+    F: Fn(&T) -> Song,
+{
+    dedup_playlist_custom_distance_by_key(songs, distance_threshold, euclidean_distance, key_fn);
+}
+
+/// Remove duplicate songs from a playlist, in place, using a custom distance
+/// metric.
+///
+/// Two songs are considered duplicates if they either have the same,
+/// non-empty title and artist name, or if they are close enough in terms
+/// of distance.
+///
+/// # Arguments
+///
+/// * `songs`: The playlist to remove duplicates from.
+/// * `distance_threshold`: The distance threshold under which two songs are
+///   considered identical. If `None`, a default value of 0.05 will be used.
+/// * `distance`: A custom distance metric.
+pub fn dedup_playlist_custom_distance(
+    songs: &mut Vec<Song>,
+    distance_threshold: Option<f32>,
+    distance: impl DistanceMetric,
+) {
+    songs.dedup_by(|s1, s2| {
+        n32(s1.custom_distance(s2, &distance)) < distance_threshold.unwrap_or(0.05)
+            || (s1.title.is_some()
+                && s2.title.is_some()
+                && s1.artist.is_some()
+                && s2.artist.is_some()
+                && s1.title == s2.title
+                && s1.artist == s2.artist)
+    });
+}
+
+/// Remove duplicate songs from a playlist, in place, using a custom distance
+/// metric.
+///
+/// Two songs are considered duplicates if they either have the same,
+/// non-empty title and artist name, or if they are close enough in terms
+/// of distance.
+///
+/// Dedup songs with a key extraction function, useful for when you have a
+/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
+/// you want to deduplicate.
+///
+/// # Arguments
+///
+/// * `songs`: The playlist to remove duplicates from.
+/// * `distance_threshold`: The distance threshold under which two songs are
+///   considered identical. If `None`, a default value of 0.05 will be used.
+/// * `distance`: A custom distance metric.
+/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
+pub fn dedup_playlist_custom_distance_by_key<F, T>(
+    songs: &mut Vec<T>,
+    distance_threshold: Option<f32>,
+    distance: impl DistanceMetric,
+    key_fn: F,
+) where
+    F: Fn(&T) -> Song,
+{
+    songs.dedup_by(|s1, s2| {
+        let s1 = key_fn(s1);
+        let s2 = key_fn(s2);
+        n32(s1.custom_distance(&s2, &distance)) < distance_threshold.unwrap_or(0.05)
+            || (s1.title.is_some()
+                && s2.title.is_some()
+                && s1.artist.is_some()
+                && s2.artist.is_some()
+                && s1.title == s2.title
+                && s1.artist == s2.artist)
+    });
+}
+
+/// Return a list of albums in a `pool` of songs that are similar to
+/// songs in `group`, discarding songs that don't belong to an album.
+/// It basically makes an "album" playlist from the `pool` of songs.
+///
+/// `group` should be ordered by track number.
+///
+/// Songs from `group` would usually just be songs from an album, but not
+/// necessarily - they are discarded from `pool` no matter what.
+///
+/// # Arguments
+///
+/// * `group` - A small group of songs, e.g. an album.
+/// * `pool` - A pool of songs to find similar songs in, e.g. a user's song
+/// library.
+///
+/// # Returns
+///
+/// A vector of songs, including `group` at the beginning, that you
+/// most likely want to plug in your audio player by using something like
+/// `ret.map(|song| song.path.to_owned()).collect::<Vec<String>>()`.
+pub fn closest_album_to_group(group: Vec<Song>, pool: Vec<Song>) -> BlissResult<Vec<Song>> {
+    let mut albums_analysis: HashMap<&str, Array2<f32>> = HashMap::new();
+    let mut albums = Vec::new();
+
+    // Remove songs from the group from the pool.
+    let pool = pool
+        .into_iter()
+        .filter(|s| !group.contains(s))
+        .collect::<Vec<_>>();
+    for song in &pool {
+        if let Some(album) = &song.album {
+            if let Some(analysis) = albums_analysis.get_mut(album as &str) {
+                analysis
+                    .push_row(song.analysis.as_arr1().view())
+                    .map_err(|e| {
+                        BlissError::ProviderError(format!("while computing distances: {}", e))
+                    })?;
+            } else {
+                let mut array = Array::zeros((1, song.analysis.as_arr1().len()));
+                array.assign(&song.analysis.as_arr1());
+                albums_analysis.insert(album, array);
+            }
+        }
+    }
+    let mut group_analysis = Array::zeros((group.len(), NUMBER_FEATURES));
+    for (song, mut column) in group.iter().zip(group_analysis.axis_iter_mut(Axis(0))) {
+        column.assign(&song.analysis.as_arr1());
+    }
+    let first_analysis = group_analysis
+        .mean_axis(Axis(0))
+        .ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
+    for (album, analysis) in albums_analysis.iter() {
+        let mean_analysis = analysis
+            .mean_axis(Axis(0))
+            .ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
+        let album = album.to_owned();
+        albums.push((album, mean_analysis.to_owned()));
+    }
+
+    albums.sort_by_key(|(_, analysis)| n32(euclidean_distance(&first_analysis, analysis)));
+    let mut playlist = group;
+    for (album, _) in albums {
+        let mut al = pool
+            .iter()
+            .filter(|s| s.album.is_some() && s.album.as_ref().unwrap() == &album.to_string())
+            .map(|s| s.to_owned())
+            .collect::<Vec<Song>>();
+        al.sort_by(|s1, s2| {
+            let track_number1 = s1
+                .track_number
+                .to_owned()
+                .unwrap_or_else(|| String::from(""));
+            let track_number2 = s2
+                .track_number
+                .to_owned()
+                .unwrap_or_else(|| String::from(""));
+            if let Ok(x) = track_number1.parse::<i32>() {
+                if let Ok(y) = track_number2.parse::<i32>() {
+                    return x.cmp(&y);
+                }
+            }
+            s1.track_number.cmp(&s2.track_number)
+        });
+        playlist.extend_from_slice(&al);
+    }
+    Ok(playlist)
+}
+
+/// Return a list of albums in a `pool` of songs that are similar to
+/// songs in `group`, discarding songs that don't belong to an album.
+/// It basically makes an "album" playlist from the `pool` of songs.
+///
+/// `group` should be ordered by track number.
+///
+/// Songs from `group` would usually just be songs from an album, but not
+/// necessarily - they are discarded from `pool` no matter what.
+///
+/// Order songs with a key extraction function, useful for when you have a
+/// structure like `CustomSong { bliss_song: Song, something_else: bool }`
+/// you want to order.
+///
+/// # Arguments
+///
+/// * `group` - A small group of songs, e.g. an album.
+/// * `pool` - A pool of songs to find similar songs in, e.g. a user's song
+/// library.
+/// * `key_fn`: A function used to retrieve the bliss [Song] from `T`.
+///
+/// # Returns
+///
+/// A vector of T, including `group` at the beginning, that you
+/// most likely want to plug in your audio player by using something like
+/// `ret.map(|song| song.path.to_owned()).collect::<Vec<String>>()`.
+// TODO: maybe Clone is not needed?
+pub fn closest_album_to_group_by_key<T: PartialEq + Clone, F>(
+    group: Vec<T>,
+    pool: Vec<T>,
+    key_fn: F,
+) -> BlissResult<Vec<T>>
+where
+    F: Fn(&T) -> Song,
+{
+    let mut albums_analysis: HashMap<String, Array2<f32>> = HashMap::new();
+    let mut albums = Vec::new();
+
+    // Remove songs from the group from the pool.
+    let pool = pool
+        .into_iter()
+        .filter(|s| !group.contains(s))
+        .collect::<Vec<_>>();
+    for song in &pool {
+        let song = key_fn(song);
+        if let Some(album) = song.album {
+            if let Some(analysis) = albums_analysis.get_mut(&album as &str) {
+                analysis
+                    .push_row(song.analysis.as_arr1().view())
+                    .map_err(|e| {
+                        BlissError::ProviderError(format!("while computing distances: {}", e))
+                    })?;
+            } else {
+                let mut array = Array::zeros((1, song.analysis.as_arr1().len()));
+                array.assign(&song.analysis.as_arr1());
+                albums_analysis.insert(album.to_owned(), array);
+            }
+        }
+    }
+    let mut group_analysis = Array::zeros((group.len(), NUMBER_FEATURES));
+    for (song, mut column) in group.iter().zip(group_analysis.axis_iter_mut(Axis(0))) {
+        let song = key_fn(song);
+        column.assign(&song.analysis.as_arr1());
+    }
+    let first_analysis = group_analysis
+        .mean_axis(Axis(0))
+        .ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
+    for (album, analysis) in albums_analysis.iter() {
+        let mean_analysis = analysis
+            .mean_axis(Axis(0))
+            .ok_or_else(|| BlissError::ProviderError(String::from("Mean of empty slice")))?;
+        let album = album.to_owned();
+        albums.push((album, mean_analysis.to_owned()));
+    }
+
+    albums.sort_by_key(|(_, analysis)| n32(euclidean_distance(&first_analysis, analysis)));
+    let mut playlist = group;
+    for (album, _) in albums {
+        let mut al = pool
+            .iter()
+            .filter(|s| {
+                let s = key_fn(s);
+                s.album.is_some() && s.album.as_ref().unwrap() == &album.to_string()
+            })
+            .map(|s| s.to_owned())
+            .collect::<Vec<T>>();
+        al.sort_by(|s1, s2| {
+            let s1 = key_fn(s1);
+            let s2 = key_fn(s2);
+            let track_number1 = s1
+                .track_number
+                .to_owned()
+                .unwrap_or_else(|| String::from(""));
+            let track_number2 = s2
+                .track_number
+                .to_owned()
+                .unwrap_or_else(|| String::from(""));
+            if let Ok(x) = track_number1.parse::<i32>() {
+                if let Ok(y) = track_number2.parse::<i32>() {
+                    return x.cmp(&y);
+                }
+            }
+            s1.track_number.cmp(&s2.track_number)
+        });
+        playlist.extend_from_slice(&al);
+    }
+    Ok(playlist)
+}
+
+#[cfg(test)]
+mod test {
+    use super::*;
+    use crate::Analysis;
+    use ndarray::arr1;
+    use std::path::Path;
+
+    #[derive(Debug, Clone, PartialEq)]
+    struct CustomSong {
+        something: bool,
+        bliss_song: Song,
+    }
+
+    #[test]
+    fn test_dedup_playlist_custom_distance() {
+        let first_song = Song {
+            path: Path::new("path-to-first").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let first_song_dupe = Song {
+            path: Path::new("path-to-dupe").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+
+        let second_song = Song {
+            path: Path::new("path-to-second").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
+            ]),
+            title: Some(String::from("dupe-title")),
+            artist: Some(String::from("dupe-artist")),
+            ..Default::default()
+        };
+        let third_song = Song {
+            path: Path::new("path-to-third").to_path_buf(),
+            title: Some(String::from("dupe-title")),
+            artist: Some(String::from("dupe-artist")),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let fourth_song = Song {
+            path: Path::new("path-to-fourth").to_path_buf(),
+            artist: Some(String::from("no-dupe-artist")),
+            title: Some(String::from("dupe-title")),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let fifth_song = Song {
+            path: Path::new("path-to-fourth").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0.001, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_custom_distance(&mut playlist, None, euclidean_distance);
+        assert_eq!(
+            playlist,
+            vec![
+                first_song.to_owned(),
+                second_song.to_owned(),
+                fourth_song.to_owned(),
+            ],
+        );
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_custom_distance(&mut playlist, Some(20.), cosine_distance);
+        assert_eq!(playlist, vec![first_song.to_owned()]);
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist(&mut playlist, Some(20.));
+        assert_eq!(playlist, vec![first_song.to_owned()]);
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist(&mut playlist, None);
+        assert_eq!(
+            playlist,
+            vec![
+                first_song.to_owned(),
+                second_song.to_owned(),
+                fourth_song.to_owned(),
+            ]
+        );
+
+        let first_song = CustomSong {
+            bliss_song: first_song,
+            something: true,
+        };
+        let second_song = CustomSong {
+            bliss_song: second_song,
+            something: true,
+        };
+        let first_song_dupe = CustomSong {
+            bliss_song: first_song_dupe,
+            something: true,
+        };
+        let third_song = CustomSong {
+            bliss_song: third_song,
+            something: true,
+        };
+        let fourth_song = CustomSong {
+            bliss_song: fourth_song,
+            something: true,
+        };
+
+        let fifth_song = CustomSong {
+            bliss_song: fifth_song,
+            something: true,
+        };
+
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_custom_distance_by_key(&mut playlist, None, euclidean_distance, |s| {
+            s.bliss_song.to_owned()
+        });
+        assert_eq!(
+            playlist,
+            vec![
+                first_song.to_owned(),
+                second_song.to_owned(),
+                fourth_song.to_owned(),
+            ],
+        );
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_custom_distance_by_key(&mut playlist, Some(20.), cosine_distance, |s| {
+            s.bliss_song.to_owned()
+        });
+        assert_eq!(playlist, vec![first_song.to_owned()]);
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_by_key(&mut playlist, Some(20.), |s| s.bliss_song.to_owned());
+        assert_eq!(playlist, vec![first_song.to_owned()]);
+        let mut playlist = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        dedup_playlist_by_key(&mut playlist, None, |s| s.bliss_song.to_owned());
+        assert_eq!(
+            playlist,
+            vec![
+                first_song.to_owned(),
+                second_song.to_owned(),
+                fourth_song.to_owned(),
+            ]
+        );
+    }
+
+    #[test]
+    fn test_song_to_song() {
+        let first_song = Song {
+            path: Path::new("path-to-first").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let first_song_dupe = Song {
+            path: Path::new("path-to-dupe").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+
+        let second_song = Song {
+            path: Path::new("path-to-second").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let third_song = Song {
+            path: Path::new("path-to-third").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let fourth_song = Song {
+            path: Path::new("path-to-fourth").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let mut songs = vec![
+            first_song.to_owned(),
+            third_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            fourth_song.to_owned(),
+        ];
+        song_to_song(&first_song, &mut songs, euclidean_distance);
+        assert_eq!(
+            songs,
+            vec![
+                first_song.to_owned(),
+                first_song_dupe.to_owned(),
+                second_song.to_owned(),
+                third_song.to_owned(),
+                fourth_song.to_owned(),
+            ],
+        );
+
+        let first_song = CustomSong {
+            bliss_song: first_song,
+            something: true,
+        };
+        let second_song = CustomSong {
+            bliss_song: second_song,
+            something: true,
+        };
+        let first_song_dupe = CustomSong {
+            bliss_song: first_song_dupe,
+            something: true,
+        };
+        let third_song = CustomSong {
+            bliss_song: third_song,
+            something: true,
+        };
+        let fourth_song = CustomSong {
+            bliss_song: fourth_song,
+            something: true,
+        };
+
+        let mut songs: Vec<CustomSong> = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            second_song.to_owned(),
+        ];
+
+        song_to_song_by_key(&first_song, &mut songs, euclidean_distance, |s| {
+            s.bliss_song.to_owned()
+        });
+
+        assert_eq!(
+            songs,
+            vec![
+                first_song,
+                first_song_dupe,
+                second_song,
+                third_song,
+                fourth_song,
+            ],
+        );
+    }
+
+    #[test]
+    fn test_sort_closest_to_first_song() {
+        let first_song = Song {
+            path: Path::new("path-to-first").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let first_song_dupe = Song {
+            path: Path::new("path-to-dupe").to_path_buf(),
+            analysis: Analysis::new([
+                1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+
+        let second_song = Song {
+            path: Path::new("path-to-second").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 1.9, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let third_song = Song {
+            path: Path::new("path-to-third").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.5, 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let fourth_song = Song {
+            path: Path::new("path-to-fourth").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+        let fifth_song = Song {
+            path: Path::new("path-to-fifth").to_path_buf(),
+            analysis: Analysis::new([
+                2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 0., 1., 1., 1.,
+            ]),
+            ..Default::default()
+        };
+
+        let mut songs = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        closest_to_first_song(&first_song, &mut songs, euclidean_distance);
+
+        let first_song = CustomSong {
+            bliss_song: first_song,
+            something: true,
+        };
+        let second_song = CustomSong {
+            bliss_song: second_song,
+            something: true,
+        };
+        let first_song_dupe = CustomSong {
+            bliss_song: first_song_dupe,
+            something: true,
+        };
+        let third_song = CustomSong {
+            bliss_song: third_song,
+            something: true,
+        };
+        let fourth_song = CustomSong {
+            bliss_song: fourth_song,
+            something: true,
+        };
+
+        let fifth_song = CustomSong {
+            bliss_song: fifth_song,
+            something: true,
+        };
+
+        let mut songs: Vec<CustomSong> = vec![
+            first_song.to_owned(),
+            first_song_dupe.to_owned(),
+            second_song.to_owned(),
+            third_song.to_owned(),
+            fourth_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+
+        closest_to_first_song_by_key(&first_song, &mut songs, euclidean_distance, |s| {
+            s.bliss_song.to_owned()
+        });
+
+        assert_eq!(
+            songs,
+            vec![
+                first_song,
+                first_song_dupe,
+                second_song,
+                fourth_song,
+                fifth_song,
+                third_song
+            ],
+        );
+    }
+
+    #[test]
+    fn test_euclidean_distance() {
+        let a = arr1(&[
+            1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
+        ]);
+        let b = arr1(&[
+            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
+        ]);
+        assert_eq!(euclidean_distance(&a, &b), 4.242640687119285);
+
+        let a = arr1(&[0.5; 20]);
+        let b = arr1(&[0.5; 20]);
+        assert_eq!(euclidean_distance(&a, &b), 0.);
+        assert_eq!(euclidean_distance(&a, &b), 0.);
+    }
+
+    #[test]
+    fn test_cosine_distance() {
+        let a = arr1(&[
+            1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
+        ]);
+        let b = arr1(&[
+            0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,
+        ]);
+        assert_eq!(cosine_distance(&a, &b), 0.7705842661294382);
+
+        let a = arr1(&[0.5; 20]);
+        let b = arr1(&[0.5; 20]);
+        assert_eq!(cosine_distance(&a, &b), 0.);
+        assert_eq!(cosine_distance(&a, &b), 0.);
+    }
+
+    #[test]
+    fn test_closest_to_group() {
+        let first_song = Song {
+            path: Path::new("path-to-first").to_path_buf(),
+            analysis: Analysis::new([0.; 20]),
+            album: Some(String::from("Album")),
+            artist: Some(String::from("Artist")),
+            track_number: Some(String::from("01")),
+            ..Default::default()
+        };
+
+        let second_song = Song {
+            path: Path::new("path-to-second").to_path_buf(),
+            analysis: Analysis::new([0.1; 20]),
+            album: Some(String::from("Another Album")),
+            artist: Some(String::from("Artist")),
+            track_number: Some(String::from("10")),
+            ..Default::default()
+        };
+
+        let third_song = Song {
+            path: Path::new("path-to-third").to_path_buf(),
+            analysis: Analysis::new([10.; 20]),
+            album: Some(String::from("Album")),
+            artist: Some(String::from("Another Artist")),
+            track_number: Some(String::from("02")),
+            ..Default::default()
+        };
+
+        let fourth_song = Song {
+            path: Path::new("path-to-fourth").to_path_buf(),
+            analysis: Analysis::new([20.; 20]),
+            album: Some(String::from("Another Album")),
+            artist: Some(String::from("Another Artist")),
+            track_number: Some(String::from("01")),
+            ..Default::default()
+        };
+        let fifth_song = Song {
+            path: Path::new("path-to-fifth").to_path_buf(),
+            analysis: Analysis::new([40.; 20]),
+            artist: Some(String::from("Third Artist")),
+            album: None,
+            ..Default::default()
+        };
+
+        let pool = vec![
+            first_song.to_owned(),
+            fourth_song.to_owned(),
+            third_song.to_owned(),
+            second_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        let group = vec![first_song.to_owned(), third_song.to_owned()];
+        assert_eq!(
+            vec![
+                first_song.to_owned(),
+                third_song.to_owned(),
+                fourth_song.to_owned(),
+                second_song.to_owned()
+            ],
+            closest_album_to_group(group, pool.to_owned()).unwrap(),
+        );
+
+        let first_song = CustomSong {
+            bliss_song: first_song,
+            something: true,
+        };
+        let second_song = CustomSong {
+            bliss_song: second_song,
+            something: true,
+        };
+        let third_song = CustomSong {
+            bliss_song: third_song,
+            something: true,
+        };
+        let fourth_song = CustomSong {
+            bliss_song: fourth_song,
+            something: true,
+        };
+
+        let fifth_song = CustomSong {
+            bliss_song: fifth_song,
+            something: true,
+        };
+
+        let pool = vec![
+            first_song.to_owned(),
+            fourth_song.to_owned(),
+            third_song.to_owned(),
+            second_song.to_owned(),
+            fifth_song.to_owned(),
+        ];
+        let group = vec![first_song.to_owned(), third_song.to_owned()];
+        assert_eq!(
+            vec![
+                first_song.to_owned(),
+                third_song.to_owned(),
+                fourth_song.to_owned(),
+                second_song.to_owned()
+            ],
+            closest_album_to_group_by_key(group, pool.to_owned(), |s| s.bliss_song.to_owned())
+                .unwrap(),
+        );
+    }
+}

src/temporal.rs

@@ -4,7 +4,7 @@
 //! of a given Song.
 
 use crate::utils::Normalize;
-use crate::BlissError;
+use crate::{BlissError, BlissResult};
 use bliss_audio_aubio_rs::{OnsetMode, Tempo};
 use log::warn;
 use ndarray::arr1;
@@ -19,7 +19,7 @@ use noisy_float::prelude::*;
  * It indicates the (subjective) "speed" of a music piece. The higher the BPM,
  * the "quicker" the song will feel.
  *
- * It uses `WPhase`, a phase-deviation onset detection function to perform
+ * It uses `SpecFlux`, a phase-deviation onset detection function to perform
  * onset detection; it proved to be the best for finding out the BPM of a panel
  * of songs I had, but it could very well be replaced by something better in the
  * future.
@@ -39,7 +39,7 @@ impl BPMDesc {
     pub const WINDOW_SIZE: usize = 512;
     pub const HOP_SIZE: usize = BPMDesc::WINDOW_SIZE / 2;
 
-    pub fn new(sample_rate: u32) -> Result<Self, BlissError> {
+    pub fn new(sample_rate: u32) -> BlissResult<Self> {
         Ok(BPMDesc {
             aubio_obj: Tempo::new(
                 OnsetMode::SpecFlux,
@@ -48,21 +48,15 @@ impl BPMDesc {
                 sample_rate,
             )
             .map_err(|e| {
-                BlissError::AnalysisError(format!(
-                    "error while loading aubio tempo object: {}",
-                    e.to_string()
-                ))
+                BlissError::AnalysisError(format!("error while loading aubio tempo object: {}", e))
             })?,
             bpms: Vec::new(),
         })
     }
 
-    pub fn do_(&mut self, chunk: &[f32]) -> Result<(), BlissError> {
+    pub fn do_(&mut self, chunk: &[f32]) -> BlissResult<()> {
         let result = self.aubio_obj.do_result(chunk).map_err(|e| {
-            BlissError::AnalysisError(format!(
-                "aubio error while computing tempo {}",
-                e.to_string()
-            ))
+            BlissError::AnalysisError(format!("aubio error while computing tempo {}", e))
         })?;
 
         if result > 0. {
@@ -101,10 +95,11 @@ impl Normalize for BPMDesc {
 mod tests {
     use super::*;
     use crate::{Song, SAMPLE_RATE};
+    use std::path::Path;
 
     #[test]
     fn test_tempo_real() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut tempo_desc = BPMDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(BPMDesc::HOP_SIZE) {
             tempo_desc.do_(&chunk).unwrap();

src/timbral.rs

@@ -9,7 +9,7 @@ use bliss_audio_aubio_rs::{bin_to_freq, PVoc, SpecDesc, SpecShape};
 use ndarray::{arr1, Axis};
 
 use super::utils::{geometric_mean, mean, number_crossings, Normalize};
-use crate::{BlissError, SAMPLE_RATE};
+use crate::{BlissError, BlissResult, SAMPLE_RATE};
 
 /**
  * General object holding all the spectral descriptor.
@@ -120,27 +120,27 @@ impl SpectralDesc {
         ]
     }
 
-    pub fn new(sample_rate: u32) -> Result<Self, BlissError> {
+    pub fn new(sample_rate: u32) -> BlissResult<Self> {
         Ok(SpectralDesc {
             centroid_aubio_desc: SpecDesc::new(SpecShape::Centroid, SpectralDesc::WINDOW_SIZE)
                 .map_err(|e| {
                     BlissError::AnalysisError(format!(
                         "error while loading aubio centroid object: {}",
-                        e.to_string()
+                        e
                     ))
                 })?,
             rolloff_aubio_desc: SpecDesc::new(SpecShape::Rolloff, SpectralDesc::WINDOW_SIZE)
                 .map_err(|e| {
                     BlissError::AnalysisError(format!(
                         "error while loading aubio rolloff object: {}",
-                        e.to_string()
+                        e
                     ))
                 })?,
             phase_vocoder: PVoc::new(SpectralDesc::WINDOW_SIZE, SpectralDesc::HOP_SIZE).map_err(
                 |e| {
                     BlissError::AnalysisError(format!(
                         "error while loading aubio pvoc object: {}",
-                        e.to_string()
+                        e
                     ))
                 },
             )?,
@@ -158,15 +158,12 @@ impl SpectralDesc {
      * `get_centroid`, `get_flatness` and `get_rolloff` to get the respective
      * descriptors' values.
      */
-    pub fn do_(&mut self, chunk: &[f32]) -> Result<(), BlissError> {
+    pub fn do_(&mut self, chunk: &[f32]) -> BlissResult<()> {
         let mut fftgrain: Vec<f32> = vec![0.0; SpectralDesc::WINDOW_SIZE];
         self.phase_vocoder
             .do_(chunk, fftgrain.as_mut_slice())
             .map_err(|e| {
-                BlissError::AnalysisError(format!(
-                    "error while processing aubio pv object: {}",
-                    e.to_string()
-                ))
+                BlissError::AnalysisError(format!("error while processing aubio pv object: {}", e))
             })?;
 
         let bin = self
@@ -175,7 +172,7 @@ impl SpectralDesc {
             .map_err(|e| {
                 BlissError::AnalysisError(format!(
                     "error while processing aubio centroid object: {}",
-                    e.to_string()
+                    e
                 ))
             })?;
 
@@ -204,12 +201,12 @@ impl SpectralDesc {
         self.values_rolloff.push(freq);
 
         let cvec: CVec = fftgrain.as_slice().into();
-        let geo_mean = geometric_mean(&cvec.norm());
+        let geo_mean = geometric_mean(cvec.norm());
         if geo_mean == 0.0 {
             self.values_flatness.push(0.0);
             return Ok(());
         }
-        let flatness = geo_mean / mean(&cvec.norm());
+        let flatness = geo_mean / mean(cvec.norm());
         self.values_flatness.push(flatness);
         Ok(())
     }
@@ -266,6 +263,7 @@ impl Normalize for ZeroCrossingRateDesc {
 mod tests {
     use super::*;
     use crate::Song;
+    use std::path::Path;
 
     #[test]
     fn test_zcr_boundaries() {
@@ -287,7 +285,7 @@ mod tests {
 
     #[test]
     fn test_zcr() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut zcr_desc = ZeroCrossingRateDesc::default();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             zcr_desc.do_(&chunk);
@@ -309,7 +307,7 @@ mod tests {
             assert!(0.0000001 > (expected - actual).abs());
         }
 
-        let song = Song::decode("data/white_noise.flac").unwrap();
+        let song = Song::decode(Path::new("data/white_noise.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(22050).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
@@ -326,7 +324,7 @@ mod tests {
 
     #[test]
     fn test_spectral_flatness() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
@@ -356,7 +354,7 @@ mod tests {
             assert!(0.0000001 > (expected - actual).abs());
         }
 
-        let song = Song::decode("data/tone_11080Hz.flac").unwrap();
+        let song = Song::decode(Path::new("data/tone_11080Hz.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
@@ -372,7 +370,7 @@ mod tests {
 
     #[test]
     fn test_spectral_roll_off() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
@@ -390,7 +388,7 @@ mod tests {
 
     #[test]
     fn test_spectral_centroid() {
-        let song = Song::decode("data/s16_mono_22_5kHz.flac").unwrap();
+        let song = Song::decode(Path::new("data/s16_mono_22_5kHz.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
@@ -419,7 +417,7 @@ mod tests {
         {
             assert!(0.0000001 > (expected - actual).abs());
         }
-        let song = Song::decode("data/tone_11080Hz.flac").unwrap();
+        let song = Song::decode(Path::new("data/tone_11080Hz.flac")).unwrap();
         let mut spectral_desc = SpectralDesc::new(SAMPLE_RATE).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();

src/utils.rs

@@ -3,7 +3,6 @@ use ndarray::{arr1, s, Array, Array1, Array2};
 use rustfft::num_complex::Complex;
 use rustfft::num_traits::Zero;
 use rustfft::FftPlanner;
-extern crate ffmpeg_next as ffmpeg;
 use log::warn;
 use std::f32::consts::PI;
 
@@ -29,7 +28,7 @@ pub(crate) fn stft(signal: &[f32], window_length: usize, hop_length: usize) -> A
         (signal.len() as f32 / hop_length as f32).ceil() as usize,
         window_length / 2 + 1,
     ));
-    let signal = reflect_pad(&signal, window_length / 2);
+    let signal = reflect_pad(signal, window_length / 2);
 
     // Periodic, so window_size + 1
     let mut hann_window = Array::zeros(window_length + 1);
@@ -45,7 +44,7 @@ pub(crate) fn stft(signal: &[f32], window_length: usize, hop_length: usize) -> A
         .step_by(hop_length)
         .zip(stft.rows_mut())
     {
-        let mut signal = (arr1(&window) * &hann_window).mapv(|x| Complex::new(x, 0.));
+        let mut signal = (arr1(window) * &hann_window).mapv(|x| Complex::new(x, 0.));
         match signal.as_slice_mut() {
             Some(s) => fft.process(s),
             None => {
@@ -101,8 +100,7 @@ pub(crate) fn geometric_mean(input: &[f32]) -> f32 {
     let mut exponents: i32 = 0;
     let mut mantissas: f64 = 1.;
     for ch in input.chunks_exact(8) {
-        let mut m;
-        m = (ch[0] as f64 * ch[1] as f64) * (ch[2] as f64 * ch[3] as f64);
+        let mut m = (ch[0] as f64 * ch[1] as f64) * (ch[2] as f64 * ch[3] as f64);
         m *= 3.273390607896142e150; // 2^500 : avoid underflows and denormals
         m *= (ch[4] as f64 * ch[5] as f64) * (ch[6] as f64 * ch[7] as f64);
         if m == 0. {
@@ -172,6 +170,7 @@ mod tests {
     use ndarray::{arr1, Array};
     use ndarray_npy::ReadNpyExt;
     use std::fs::File;
+    use std::path::Path;
 
     #[test]
     fn test_convolve() {
@@ -497,7 +496,7 @@ mod tests {
         let file = File::open("data/librosa-stft.npy").unwrap();
         let expected_stft = Array2::<f32>::read_npy(file).unwrap().mapv(|x| x as f64);
 
-        let song = Song::decode("data/piano.flac").unwrap();
+        let song = Song::decode(Path::new("data/piano.flac")).unwrap();
 
         let stft = stft(&song.sample_array, 2048, 512);
 
@@ -524,6 +523,7 @@ mod bench {
     use super::*;
     use crate::Song;
     use ndarray::Array;
+    use std::path::Path;
     use test::Bencher;
 
     #[bench]
@@ -538,7 +538,9 @@ mod bench {
 
     #[bench]
     fn bench_compute_stft(b: &mut Bencher) {
-        let signal = Song::decode("data/piano.flac").unwrap().sample_array;
+        let signal = Song::decode(Path::new("data/piano.flac"))
+            .unwrap()
+            .sample_array;
 
         b.iter(|| {
             stft(&signal, 2048, 512);