opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
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use crate::domains::{AtomDomain, LazyFrameDomain, Margin, SeriesDomain};
use crate::error::*;
use polars::prelude::*;

pub fn get_test_data() -> Fallible<(LazyFrameDomain, LazyFrame)> {
    let lf_domain = LazyFrameDomain::new(vec![
        SeriesDomain::new("chunk_2_bool", AtomDomain::<bool>::default()),
        SeriesDomain::new("cycle_5_alpha", AtomDomain::<String>::default()),
        SeriesDomain::new("const_1f64", AtomDomain::<f64>::new_non_nan()),
        SeriesDomain::new("chunk_(..10u32)", AtomDomain::<u32>::default()),
        SeriesDomain::new("cycle_(..100i32)", AtomDomain::<i32>::default()),
    ])?
    .with_margin(
        Margin::select()
            .with_invariant_lengths()
            .with_max_length(1000),
    )?
    .with_margin(
        Margin::by(["chunk_2_bool"])
            .with_invariant_lengths()
            .with_max_length(500)
            .with_max_groups(2),
    )?
    .with_margin(
        Margin::by(["chunk_2_bool", "cycle_5_alpha"])
            .with_invariant_keys()
            .with_max_length(200),
    )?
    .with_margin(
        Margin::by(["cycle_(..100i32)"])
            .with_invariant_keys()
            .with_max_length(100),
    )?;

    let lf = df!(
        "chunk_2_bool" => [[false; 500], [true; 500]].concat(),
        "cycle_5_alpha" => ["A", "B", "C", "D", "E"].repeat(200),
        "const_1f64" => [1.0; 1000],
        "chunk_(..10u32)" => (0..10u32).flat_map(|i| [i; 100].into_iter()).collect::<Vec<_>>(),
        "cycle_(..100i32)" => (0..100i32).cycle().take(1000).collect::<Vec<_>>()
    )?
    .lazy();

    Ok((lf_domain, lf))
}