Prepare release 0.8.1 (#88)

* Fix argmin result display

* Update changelog

* Bump 0.8.1

* Update README, remove old history

CHANGELOG.md

@@ -4,6 +4,16 @@ Changes
 Version 0.9.0 - unreleased
 ==========================
 
+Version 0.8.1 - 28/03/2023
+==========================
+
+* `ego`:
+  * Make objective and constraints training in parallel (#86)
+  * Lock mopta execution to allow concurrent computations (#84)
+  * Fix and adjust infill criterion optimmization retries strategy (#87)
+* `moe`:
+  * Fix k-fold cross-validation (#85)  
+
 Version 0.8.0 - 10/03/2023
 ==========================
 

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "egobox"
-version = "0.8.0"
+version = "0.8.1"
 authors = ["Rémi Lafage <[email protected]>"]
 edition = "2018"
 description = "A toolbox for efficient global optimization"
@@ -25,10 +25,10 @@ persistent-ego = ["egobox-ego/persistent"]
 blas = ["ndarray/blas", "egobox-gp/blas", "egobox-moe/blas", "egobox-ego/blas"]
 
 [dependencies]
-egobox-doe = { version = "0.8.0", path="./doe" }
-egobox-gp = { version = "0.8.0", path="./gp" }
-egobox-moe = { version = "0.8.0", path="./moe", features=["persistent"] }
-egobox-ego = { version = "0.8.0", path="./ego", features=["persistent"] }
+egobox-doe = { version = "0.8.1", path="./doe" }
+egobox-gp = { version = "0.8.1", path="./gp" }
+egobox-moe = { version = "0.8.1", path="./moe", features=["persistent"] }
+egobox-ego = { version = "0.8.1", path="./ego", features=["persistent"] }
 
 linfa = { version = "0.6.1", default-features = false }
 

README.md

@@ -28,10 +28,10 @@ Depending on the sub-packages you want to use, you have to add following declara
 
 ```text
 [dependencies]
-egobox-doe = { version = "0.7.0" }
-egobox-gp  = { version = "0.7.0" }
-egobox-moe = { version = "0.7.0" }
-egobox-ego = { version = "0.7.0" }
+egobox-doe = { version = "0.8.0" }
+egobox-gp  = { version = "0.8.0" }
+egobox-moe = { version = "0.8.0" }
+egobox-ego = { version = "0.8.0" }
 ```
 
 ### Features
@@ -74,7 +74,7 @@ Otherwise, you can choose an external BLAS/LAPACK backend available through the
 Thus, for instance, to use `gp` with the Intel MKL BLAS/LAPACK backend, you could specify in your `Cargo.toml` the following features:
 ```text
 [dependencies]
-egobox-gp = { version = "0.7.0", features = ["blas", "linfa/intel-mkl-static"] }
+egobox-gp = { version = "0.8.0", features = ["blas", "linfa/intel-mkl-static"] }
 ```
 or you could run the `gp` example as follows:
 ``` bash
@@ -117,19 +117,3 @@ If you find this project useful for your research, you may cite it as follows:
 
 Additionally, you may consider adding a star to the repository. This positive feedback improves the visibility of the project.
 
-## History
-
-I started this library as a way to learn Rust and see if it can be used to implement algorithms like those in the SMT toolbox[^1]. As the first components (doe, gp) emerged, it appears I could translate Python code almost line by line in Rust (well... after a great deal of borrow-checker fight!) and thanks to [Rust ndarray library ecosystem](https://github.com/rust-ndarray). 
-
-This library relies also on the [linfa project](https://github.com/rust-ml/linfa) which aims at being the "scikit-learn-like ML library for Rust". Along the way I could contribute to `linfa` by porting gaussian mixture model (`linfa-clustering/gmm`) and partial least square family methods (`linfa-pls`) confirming the fact that Python algorithms translation in Rust could be pretty straightforward.
-
-While I did not benchmark exactly my Rust code against SMT Python one, from my debugging sessions, I noticed I did not get such a great speed up. Actually, algorithms like `doe` and `gp` relies extensively on linear algebra and Python famous libraries `numpy`/`scipy` which are strongly optimized by calling C or Fortran compiled code.
-
-My guess at this point was that interest could come from some Rust algorithms built upon these initial building blocks hence I started to implement mixture of experts algorithm (`moe`) and on top surrogate-based optimization EGO algorithm (`ego`) which gives its name to the library[^2][^3]. Aside from performance, such library can also take advantage from the others [Rust selling points](https://www.rust-lang.org/). 
-
-
-[^1]: M. A. Bouhlel and J. T. Hwang and N. Bartoli and R. Lafage and J. Morlier and J. R. R. A. Martins. A Python surrogate modeling framework with derivatives. Advances in Engineering Software, 2019.
-
-[^2]: Bartoli, Nathalie, et al. "Adaptive modeling strategy for constrained global optimization with application to aerodynamic wing design." Aerospace Science and technology 90 (2019): 85-102.
-
-[^3]: Dubreuil, Sylvain, et al. "Towards an efficient global multidisciplinary design optimization algorithm." Structural and Multidisciplinary Optimization 62.4 (2020): 1739-1765.

doe/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "egobox-doe"
-version = "0.8.0"
+version = "0.8.1"
 authors = ["Rémi Lafage <[email protected]>"]
 edition = "2018"
 description = "A library for design of experiments"

ego/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "egobox-ego"
-version = "0.8.0"
+version = "0.8.1"
 authors = ["Rémi Lafage <[email protected]>"]
 edition = "2018"
 description = "A library for efficient global optimization"
@@ -16,9 +16,9 @@ persistent = ["serde_json"]
 blas = ["ndarray-linalg", "linfa/ndarray-linalg", "linfa-pls/blas"]
 
 [dependencies]
-egobox-doe = { version = "0.8.0", path = "../doe", features = ["serializable"] }
-egobox-gp = { version = "0.8.0", path = "../gp", features = ["serializable"] }
-egobox-moe = { version = "0.8.0", path = "../moe", features = ["serializable"] }
+egobox-doe = { version = "0.8.1", path = "../doe", features = ["serializable"] }
+egobox-gp = { version = "0.8.1", path = "../gp", features = ["serializable"] }
+egobox-moe = { version = "0.8.1", path = "../moe", features = ["serializable"] }
 
 linfa = { version = "0.6.1", default-features = false }
 linfa-pls = { version = "0.6.1", default-features = false }

ego/src/egor.rs

@@ -93,7 +93,7 @@ use crate::mixint::*;
 use crate::types::*;
 
 use egobox_moe::{CorrelationSpec, MoeParams, RegressionSpec};
-use log::{debug, info};
+use log::info;
 use ndarray::{concatenate, Array2, ArrayBase, Axis, Data, Ix2};
 use ndarray_rand::rand::SeedableRng;
 use rand_xoshiro::Xoshiro256Plus;
@@ -301,7 +301,7 @@ impl<O: GroupFunc, SB: SurrogateBuilder> Egor<O, SB> {
         let xtypes = self.solver.xtypes.clone();
 
         let result = Executor::new(self.fobj.clone(), self.solver.clone()).run()?;
-        debug!("ARGMIN result = {}", result);
+        info!("{}", result);
         let (x_data, y_data) = result.state().clone().take_data().unwrap();
 
         let res = if no_discrete {

gp/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "egobox-gp"
-version = "0.8.0"
+version = "0.8.1"
 authors = ["Rémi Lafage <[email protected]>"]
 edition = "2018"
 description = "A library for gaussian process modeling"
@@ -16,7 +16,7 @@ serializable = ["serde", "linfa/serde"]
 blas = ["ndarray-linalg", "linfa/ndarray-linalg", "linfa-pls/blas"]
 
 [dependencies]
-egobox-doe = { version = "0.8.0", path="../doe" }
+egobox-doe = { version = "0.8.1", path="../doe" }
 
 linfa = { version = "0.6.1", default-features = false }
 linfa-pls = { version = "0.6.1", default-features = false }

moe/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "egobox-moe"
-version = "0.8.0"
+version = "0.8.1"
 authors = ["Rémi Lafage <[email protected]>"]
 edition = "2018"
 description = "A library for mixture of expert gaussian processes"
@@ -17,8 +17,8 @@ serializable = ["serde", "typetag", "linfa-clustering/serde", "egobox-gp/seriali
 blas = ["ndarray-linalg", "linfa/ndarray-linalg", "linfa-clustering/blas", "linfa-pls/blas"]
 
 [dependencies]
-egobox-doe = { version = "0.8.0", path = "../doe" }
-egobox-gp = { version = "0.8.0", path = "../gp" }
+egobox-doe = { version = "0.8.1", path = "../doe" }
+egobox-gp = { version = "0.8.1", path = "../gp" }
 
 linfa = { version = "0.6.1", default-features = false }
 linfa-clustering = { version = "0.6.1", default-features = false }

pyproject.toml

@@ -24,7 +24,7 @@ python-source="python"
 
 [tool.poetry]
 name = "egobox"
-version = "0.8.0"
+version = "0.8.1"
 description = "Python binding for egobox EGO optimizer written in Rust"
 authors = ["Rémi Lafage <[email protected]>"]