readme and test
This commit is contained in:
randogoth
parent
faaad93ef4
commit
517b7d55f1
5 changed files with 91 additions and 68 deletions
74
Cargo.lock
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74
Cargo.lock
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@ -31,17 +31,6 @@ version = "1.0.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
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[[package]]
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name = "getrandom"
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version = "0.2.12"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "190092ea657667030ac6a35e305e62fc4dd69fd98ac98631e5d3a2b1575a12b5"
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dependencies = [
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"cfg-if",
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"libc",
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"wasi",
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]
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[[package]]
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name = "heck"
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version = "0.4.1"
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@ -85,17 +74,6 @@ dependencies = [
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"scopeguard",
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]
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[[package]]
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name = "lyagushka"
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version = "0.1.0"
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dependencies = [
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"atty",
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"pyo3",
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"rand",
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"serde",
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"serde_json",
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]
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[[package]]
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name = "memoffset"
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version = "0.9.0"
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@ -134,12 +112,6 @@ dependencies = [
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"windows-targets",
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]
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[[package]]
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name = "ppv-lite86"
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version = "0.2.17"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "5b40af805b3121feab8a3c29f04d8ad262fa8e0561883e7653e024ae4479e6de"
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[[package]]
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name = "proc-macro2"
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version = "1.0.78"
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@ -149,6 +121,16 @@ dependencies = [
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"unicode-ident",
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]
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[[package]]
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name = "pyagushka"
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version = "0.1.0"
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dependencies = [
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"atty",
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"pyo3",
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"serde",
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"serde_json",
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]
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[[package]]
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name = "pyo3"
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version = "0.20.2"
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@ -219,36 +201,6 @@ dependencies = [
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"proc-macro2",
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]
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[[package]]
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name = "rand"
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version = "0.8.5"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "34af8d1a0e25924bc5b7c43c079c942339d8f0a8b57c39049bef581b46327404"
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dependencies = [
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"libc",
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"rand_chacha",
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"rand_core",
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]
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[[package]]
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name = "rand_chacha"
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version = "0.3.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "e6c10a63a0fa32252be49d21e7709d4d4baf8d231c2dbce1eaa8141b9b127d88"
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dependencies = [
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"ppv-lite86",
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"rand_core",
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]
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[[package]]
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name = "rand_core"
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version = "0.6.4"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "ec0be4795e2f6a28069bec0b5ff3e2ac9bafc99e6a9a7dc3547996c5c816922c"
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dependencies = [
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"getrandom",
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]
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[[package]]
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name = "redox_syscall"
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version = "0.4.1"
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@ -336,12 +288,6 @@ version = "0.2.3"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "c7de7d73e1754487cb58364ee906a499937a0dfabd86bcb980fa99ec8c8fa2ce"
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[[package]]
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name = "wasi"
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version = "0.11.0+wasi-snapshot-preview1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
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[[package]]
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name = "winapi"
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version = "0.3.9"
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@ -1,15 +1,18 @@
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[package]
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name = "lyagushka"
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name = "pyagushka"
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version = "0.1.0"
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edition = "2021"
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[lib]
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name = "lyagushka"
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name = "pyagushka"
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crate-type = ["cdylib"]
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[dependencies]
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atty = "0.2.14"
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pyo3 = "0.20.2"
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rand = "0.8.5"
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serde = { version = "1.0.196", features = ["derive"] }
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serde_json = "1.0.113"
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[features]
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extension-module = ["pyo3/extension-module"]
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default = ["extension-module"]
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61
readme.md
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61
readme.md
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@ -0,0 +1,61 @@
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# lyagushka
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(Russian лягушка: frog)
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Cluster and Gap Analysis Tool inspired by Fatum Project's 'Zhaba' algorithm (Russian 'жаба': toad) that finds attractor clusters in lists of integers.
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This Rust command-line tool analyzes a dataset of integers to identify clusters of closely grouped points and significant gaps between these clusters. It calculates z-scores for each cluster or gap to measure their statistical significance relative to the dataset's mean distance. The analysis results, including clusters, gaps, and their z-scores, are output as a JSON string.
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## Features
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- **Cluster Identification**: Identifies groups of points that are closely spaced together based on a customizable threshold.
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- **Gap Detection**: Detects significant gaps between clusters, providing insights into the dataset's distribution.
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- **Z-Score Calculation**: Calculates z-scores for both clusters and gaps, offering a statistical measure of their deviation from the mean distance.
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- **Flexible Input**: Accepts input data either from a file specified as a command-line argument or piped directly into stdin.
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- **JSON Output**: Outputs the analysis results in a readable JSON format, making it easy to interpret or use in further processing.
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## Usage
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### From a File
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To analyze a dataset from a file, provide the filename as an argument along with two additional parameters: the factor for adjusting clustering and gap detection thresholds, and the minimum cluster size.
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```sh
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cargo run -- filename.txt 0.5 2
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```
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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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echo "1\n2\n10\n20" | cargo run -- 0.5 2
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```
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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 used to fine-tune the sensitivity of cluster and gap detection. Lower values result in tighter clusters and wider gaps, while higher values do the opposite.
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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 clusters and gaps, 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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"span_length": 1.0,
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"num_elements": 2,
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"centroid": 1.5,
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"z_score": -1.23
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},
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{
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"span_length": 8.0,
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"num_elements": 0,
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"centroid": 6.0,
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"z_score": 2.45
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}
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]
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```
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@ -167,7 +167,7 @@ fn lyagushka(_py: Python, int_list: &PyList, factor: f32, min_cluster_size: usiz
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#[pymodule]
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fn lyagushka_module(_py: Python, m: &PyModule) -> PyResult<()> {
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fn pyagushka(_py: Python, m: &PyModule) -> PyResult<()> {
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m.add_function(wrap_pyfunction!(lyagushka, m)?)?;
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Ok(())
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}
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13
test.py
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13
test.py
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from pyagushka import lyagushka
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from randonautentropy import rndo
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import json
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random_data = []
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with open('random_values.txt', 'r') as file:
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for line in file:
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random_data.append(int(line.strip()))
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anomalies = json.loads(lyagushka(random_data, 1.0, 5))
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print(anomalies)
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