Struct linfa::dataset::Pr [−][src]
pub struct Pr(pub f32);
Probability types
This helper struct exists to distinguish probabilities from floating points. For example SVM selects regression or classification training, based on the target type, and could not distinguish them without a new-type definition.
Implementations
Methods from Deref<Target = f32>
pub const RADIX: u32
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pub const MANTISSA_DIGITS: u32
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pub const DIGITS: u32
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pub const EPSILON: f32
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pub const MIN: f32
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pub const MIN_POSITIVE: f32
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pub const MAX: f32
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pub const MIN_EXP: i32
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pub const MAX_EXP: i32
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pub const MIN_10_EXP: i32
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pub const MAX_10_EXP: i32
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pub const NAN: f32
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pub const INFINITY: f32
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pub const NEG_INFINITY: f32
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pub fn as_ne_bytes(&self) -> &[u8; 4]
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num_as_ne_bytes
)Return the memory representation of this floating point number as a byte array in native byte order.
to_ne_bytes
should be preferred over this whenever possible.
Examples
#![feature(num_as_ne_bytes)] let num = 12.5f32; let bytes = num.as_ne_bytes(); assert_eq!( bytes, if cfg!(target_endian = "big") { &[0x41, 0x48, 0x00, 0x00] } else { &[0x00, 0x00, 0x48, 0x41] } );
pub fn total_cmp(&self, other: &f32) -> Ordering
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total_cmp
)Returns an ordering between self and other values. Unlike the standard partial comparison between floating point numbers, this comparison always produces an ordering in accordance to the totalOrder predicate as defined in IEEE 754 (2008 revision) floating point standard. The values are ordered in following order:
- Negative quiet NaN
- Negative signaling NaN
- Negative infinity
- Negative numbers
- Negative subnormal numbers
- Negative zero
- Positive zero
- Positive subnormal numbers
- Positive numbers
- Positive infinity
- Positive signaling NaN
- Positive quiet NaN
Note that this function does not always agree with the PartialOrd
and PartialEq
implementations of f32
. In particular, they regard
negative and positive zero as equal, while total_cmp
doesn’t.
Example
#![feature(total_cmp)] struct GoodBoy { name: String, weight: f32, } let mut bois = vec![ GoodBoy { name: "Pucci".to_owned(), weight: 0.1 }, GoodBoy { name: "Woofer".to_owned(), weight: 99.0 }, GoodBoy { name: "Yapper".to_owned(), weight: 10.0 }, GoodBoy { name: "Chonk".to_owned(), weight: f32::INFINITY }, GoodBoy { name: "Abs. Unit".to_owned(), weight: f32::NAN }, GoodBoy { name: "Floaty".to_owned(), weight: -5.0 }, ]; bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));
Trait Implementations
impl PartialOrd<Pr> for Pr
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impl PartialOrd<Pr> for Pr
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