bjsmiley-surrealdb 1.0.1

A scalable, distributed, collaborative, document-graph database, for the realtime web
Documentation 
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use crate::err::Error;
use crate::fnc::util::math::vector::{
	Add, Angle, CrossProduct, Divide, DotProduct, Magnitude, Multiply, Normalize, Project, Subtract,
};
use crate::sql::{Number, Value};

pub fn add((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.add(&b)?.into())
}

pub fn angle((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.angle(&b)?.into())
}

pub fn divide((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.divide(&b)?.into())
}

pub fn cross((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.cross(&b)?.into())
}

pub fn dot((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.dot(&b)?.into())
}

pub fn magnitude((a,): (Vec<Number>,)) -> Result<Value, Error> {
	Ok(a.magnitude().into())
}

pub fn multiply((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.multiply(&b)?.into())
}

pub fn normalize((a,): (Vec<Number>,)) -> Result<Value, Error> {
	Ok(a.normalize().into())
}

pub fn project((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.project(&b)?.into())
}

pub fn subtract((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
	Ok(a.subtract(&b)?.into())
}

pub mod distance {

	use crate::err::Error;
	use crate::fnc::util::math::vector::{
		ChebyshevDistance, EuclideanDistance, HammingDistance, ManhattanDistance, MinkowskiDistance,
	};
	use crate::sql::{Number, Value};

	pub fn chebyshev((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.chebyshev_distance(&b)?.into())
	}

	pub fn euclidean((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.euclidean_distance(&b)?.into())
	}

	pub fn hamming((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.hamming_distance(&b)?.into())
	}

	pub fn mahalanobis((_, _): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Err(Error::FeatureNotYetImplemented {
			feature: "vector::distance::mahalanobis() function".to_string(),
		})
	}

	pub fn manhattan((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.manhattan_distance(&b)?.into())
	}

	pub fn minkowski((a, b, o): (Vec<Number>, Vec<Number>, Number)) -> Result<Value, Error> {
		Ok(a.minkowski_distance(&b, &o)?.into())
	}
}

pub mod similarity {

	use crate::err::Error;
	use crate::fnc::util::math::vector::{CosineSimilarity, JaccardSimilarity, PearsonSimilarity};
	use crate::sql::{Number, Value};

	pub fn cosine((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.cosine_similarity(&b)?.into())
	}

	pub fn jaccard((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.jaccard_similarity(&b)?.into())
	}

	pub fn pearson((a, b): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Ok(a.pearson_similarity(&b)?.into())
	}

	pub fn spearman((_, _): (Vec<Number>, Vec<Number>)) -> Result<Value, Error> {
		Err(Error::FeatureNotYetImplemented {
			feature: "vector::similarity::spearman() function".to_string(),
		})
	}
}