DataDistribution

scirs2_core::parallel

Enum DataDistribution 

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pub enum DataDistribution {
    Uniform,
    Skewed {
        skewness: f64,
    },
    Gaussian {
        mean: f64,
        std_dev: f64,
    },
    PowerLaw {
        alpha: f64,
    },
    Bimodal {
        mean1: f64,
        mean2: f64,
        mix_ratio: f64,
    },
    Custom {
        name: String,
    },
}
Expand description

Data distribution types that affect partitioning strategy

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Uniform

Uniform distribution - data is evenly distributed

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Skewed

Skewed distribution - data is concentrated in certain regions

Fields

§skewness: f64

Skewness factor (0.0 = no skew, positive = right skew, negative = left skew)

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Gaussian

Gaussian/Normal distribution

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§mean: f64

Mean of the distribution

§std_dev: f64

Standard deviation

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PowerLaw

Power law distribution (e.g., Zipf distribution)

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§alpha: f64

Exponent parameter

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Bimodal

Bimodal distribution - two peaks

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§mean1: f64

First peak mean

§mean2: f64

Second peak mean

§mix_ratio: f64

Mixing ratio (0.0 to 1.0)

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Custom

Custom distribution defined by density function

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§name: String

Name or description of the distribution

Trait Implementations§

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impl Clone for DataDistribution

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fn clone(&self) -> DataDistribution

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for DataDistribution

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl PartialEq for DataDistribution

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fn eq(&self, other: &DataDistribution) -> bool

Tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl StructuralPartialEq for DataDistribution

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🔬This is a nightly-only experimental API. (clone_to_uninit)
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type Output = T

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fn saturating_as<Dst>(self) -> Dst
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Casts the value.
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Casts the value.
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