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Make FMT functional more flexible w.r.t. the shape of the weight functions #31

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prehner merged 3 commits into from
Jun 10, 2022
Merged

Make FMT functional more flexible w.r.t. the shape of the weight functions #31

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0fe5201
Make FMT functional more flexible
prehner Jun 6, 2022
2cd5d83
change return type to enum
prehner Jun 10, 2022
dce23d9
update changelog
prehner Jun 10, 2022
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Make FMT functional more flexible
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@prehner
prehner committed Jun 6, 2022
commit 0fe5201ebcf3dc6c2dab6bee12be4c0e05d297dc
2 changes: 1 addition & 1 deletion Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
name = "feos-dft"
version = "0.2.0"
authors = ["Philipp Rehner <prehner@ethz.ch>"]
edition = "2018"
edition = "2021"
license = "MIT OR Apache-2.0"
description = "Generic classical DFT implementations for the `feos` project."
homepage = "https://github.com/feos-org"
Expand Down
41 changes: 24 additions & 17 deletions src/fundamental_measure_theory.rs
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Expand Up @@ -19,6 +19,11 @@ pub trait FMTProperties {
fn component_index(&self) -> Array1<usize>;
fn chain_length(&self) -> Array1<f64>;
fn hs_diameter<N: DualNum<f64>>(&self, temperature: N) -> Array1<N>;

fn geometry_coefficients<N: DualNum<f64>>(&self, _temperature: N) -> [Array1<N>; 4] {
let m = self.chain_length().mapv(|m| N::from(m));
[m.clone(), m.clone(), m.clone(), m]
}
}

/// Different versions of fundamental measure theory
Expand Down Expand Up @@ -60,8 +65,8 @@ impl<P> FMTContribution<P> {
impl<P: FMTProperties, N: DualNum<f64>> FunctionalContributionDual<N> for FMTContribution<P> {
fn weight_functions(&self, temperature: N) -> WeightFunctionInfo<N> {
let r = self.properties.hs_diameter(temperature) * 0.5;
let m = self.properties.chain_length();
match (self.version, m.len()) {
let [c0, c1, c2, c3] = self.properties.geometry_coefficients(temperature);
match (self.version, r.len()) {
(FMTVersion::WhiteBear | FMTVersion::AntiSymWhiteBear, 1) => {
WeightFunctionInfo::new(self.properties.component_index(), false).extend(
vec![
Expand All @@ -70,8 +75,9 @@ impl<P: FMTProperties, N: DualNum<f64>> FunctionalContributionDual<N> for FMTCon
WeightFunctionShape::DeltaVec,
]
.into_iter()
.map(|s| WeightFunction {
prefactor: self.properties.chain_length().mapv(|m| m.into()),
.zip([c2, c3.clone(), c3])
.map(|(s, c)| WeightFunction {
prefactor: c,
kernel_radius: r.clone(),
shape: s,
})
Expand All @@ -83,54 +89,54 @@ impl<P: FMTProperties, N: DualNum<f64>> FunctionalContributionDual<N> for FMTCon
WeightFunctionInfo::new(self.properties.component_index(), false)
.add(
WeightFunction {
prefactor: Zip::from(&m)
prefactor: Zip::from(&c0)
.and(&r)
.map_collect(|&m, &r| r.powi(-2) * m / (4.0 * PI)),
.map_collect(|&c, &r| r.powi(-2) * c / (4.0 * PI)),
kernel_radius: r.clone(),
shape: WeightFunctionShape::Delta,
},
true,
)
.add(
WeightFunction {
prefactor: Zip::from(&m)
prefactor: Zip::from(&c1)
.and(&r)
.map_collect(|&m, &r| r.recip() * m / (4.0 * PI)),
.map_collect(|&c, &r| r.recip() * c / (4.0 * PI)),
kernel_radius: r.clone(),
shape: WeightFunctionShape::Delta,
},
true,
)
.add(
WeightFunction {
prefactor: m.mapv(|m| m.into()),
prefactor: c2,
kernel_radius: r.clone(),
shape: WeightFunctionShape::Delta,
},
true,
)
.add(
WeightFunction {
prefactor: m.mapv(|m| m.into()),
prefactor: c3.clone(),
kernel_radius: r.clone(),
shape: WeightFunctionShape::Theta,
},
true,
)
.add(
WeightFunction {
prefactor: Zip::from(&m)
prefactor: Zip::from(&c3)
.and(&r)
.map_collect(|&m, &r| r.recip() * m / (4.0 * PI)),
.map_collect(|&c, &r| r.recip() * c / (4.0 * PI)),
kernel_radius: r.clone(),
shape: WeightFunctionShape::DeltaVec,
},
true,
)
.add(
WeightFunction {
prefactor: m.mapv(|m| m.into()),
kernel_radius: r.clone(),
prefactor: c3,
kernel_radius: r,
shape: WeightFunctionShape::DeltaVec,
},
true,
Expand All @@ -145,8 +151,9 @@ impl<P: FMTProperties, N: DualNum<f64>> FunctionalContributionDual<N> for FMTCon
WeightFunctionShape::Theta,
]
.into_iter()
.map(|s| WeightFunction {
prefactor: self.properties.chain_length().mapv(|m| m.into()),
.zip(self.properties.geometry_coefficients(temperature))
.map(|(s, c)| WeightFunction {
prefactor: c,
kernel_radius: r.clone(),
shape: s,
})
Expand All @@ -165,7 +172,7 @@ impl<P: FMTProperties, N: DualNum<f64>> FunctionalContributionDual<N> for FMTCon
let pure_component_weighted_densities = matches!(
self.version,
FMTVersion::WhiteBear | FMTVersion::AntiSymWhiteBear
) && self.properties.chain_length().len() == 1;
) && self.properties.component_index().len() == 1;

// scalar weighted densities
let (n2, n3) = if pure_component_weighted_densities {
Expand Down