73 lines
No EOL
2.4 KiB
Markdown
73 lines
No EOL
2.4 KiB
Markdown
# lyagushka
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(Russian лягушка [lʲɪˈɡuʂkə]: frog)
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Lyagushka is a Rust command-line tool inspired by Fatum Project's ['Zhaba' algorithm](https://gist.github.com/randogoth/ab5ab9e8665303be176f16241e7b26b5) (Russian 'жаба': toad) and expands upon it for more versatility.
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It is an algorithm that analyzes a one-dimensional dataset of integers to identify clusters of closely grouped "attractor" points and significant "void" gaps between these clusters. It calculates z-scores for each cluster or gap to measure their statistical significance relative to the dataset's mean density and distance between points. The analysis results, including attractors, voids, and their z-scores, are output as a JSON string.
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## Building
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With a Rust and Cargo environment set up, simply run:
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```sh
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$ cargo build --release
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```
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## Usage
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### Parameters
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* `filename.txt` (optional): A file containing a newline-separated list of integers to analyze. If not provided, the program expects input from stdin.
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* `factor`: A floating-point value by which the mean density/span is multiplied to make up a threshold for attractor and void detection.
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* `min_cluster_size`: An integer specifying the minimum number of contiguous points required to be considered a cluster.
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### Output
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The tool outputs a JSON string that includes details about the identified attractors and voids, along with their respective z-scores. Here's an example of the JSON output format:
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```json
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[
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//...
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{
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"elements": [ 722, 722, 722, 725, 725, 726, 726, 726],
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"start": 722,
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"end": 726,
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"span_length": 4,
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"num_elements": 8,
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"centroid": 724.0,
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"z_score": 1.19528
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},
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{
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"elements": [],
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"start": 732,
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"end": 740,
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"span_length": 8,
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"num_elements": 0,
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"centroid": 736.0,
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"z_score": -1.13359
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},
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//...
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]
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```
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### From a File
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To analyze a dataset from a file, provide the filename as an argument, followed by the factor and minimum cluster size parameters
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```sh
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lyagushka random_values.txt 1.5 6
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```
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(= '*Attractor clusters need to have at least 6 numbers with 1.5 times the mean density, void gaps need to be at leat 1.5 times the mean gap size wide*')
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### From Stdin
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Alternatively, you can pipe a list of integers into the tool, followed by the factor and minimum cluster size.
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```sh
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cat random_values.txt | lyagushka 0.5 2
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```
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## Python Module
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If you need lyagushka in a Python environment, check out the 'Python' branch of this repository |