First working version

master
Meliurwen 2 years ago
commit b870da3a16
Signed by: meliurwen
GPG Key ID: 818A8B35E9F1CE10
  1. 2
      .gitignore
  2. 4
      .gitmodules
  3. 8
      Cargo.toml
  4. 21
      LICENSE
  5. 1
      deps/reCTBN
  6. 7
      rust-toolchain.toml
  7. 39
      rustfmt.toml
  8. 72
      src/main.rs

2
.gitignore vendored

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/target
Cargo.lock

4
.gitmodules vendored

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[submodule "deps/reCTBN"]
path = deps/reCTBN
url = ../reCTBN.git
branch = dev

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[package]
name = "rectbn-benchmarks"
version = "0.1.0"
edition = "2021"
[dependencies]
reCTBN = { path = "deps/reCTBN/reCTBN", package = "reCTBN", version="0.1.0" }
json = "0.12.*"

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MIT License
Copyright (c) 2023 Meliurwen
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

1
deps/reCTBN vendored

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Subproject commit e638a627bb1efb675d4242eff0bb543715b55ddc

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# This file defines the Rust toolchain to use when a command is executed.
# See also https://rust-lang.github.io/rustup/overrides.html
[toolchain]
channel = "stable"
components = [ "clippy", "rustfmt" ]
profile = "minimal"

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# This file defines the Rust style for automatic reformatting.
# See also https://rust-lang.github.io/rustfmt
# NOTE: the unstable options will be uncommented when stabilized.
# Version of the formatting rules to use.
#version = "One"
# Number of spaces per tab.
tab_spaces = 4
max_width = 100
#comment_width = 80
# Prevent carriage returns, admitted only \n.
newline_style = "Unix"
# The "Default" setting has a heuristic which can split lines too aggresively.
#use_small_heuristics = "Max"
# How imports should be grouped into `use` statements.
#imports_granularity = "Module"
# How consecutive imports are grouped together.
#group_imports = "StdExternalCrate"
# Error if unable to get all lines within max_width, except for comments and
# string literals.
#error_on_line_overflow = true
# Error if unable to get comments or string literals within max_width, or they
# are left with trailing whitespaces.
#error_on_unformatted = true
# Files to ignore like third party code which is formatted upstream.
# Ignoring tests is a temporary measure due some issues regarding rank-3 tensors
ignore = [
"tests/"
]

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#![allow(non_snake_case)]
use std::collections::BTreeSet;
use reCTBN::parameter_learning::MLE;
use reCTBN::params::DiscreteStatesContinousTimeParams;
use reCTBN::params::Params::DiscreteStatesContinousTime;
use reCTBN::process::ctbn::CtbnNetwork;
use reCTBN::process::NetworkProcess;
use reCTBN::structure_learning::constraint_based_algorithm::CTPC;
use reCTBN::structure_learning::hypothesis_test::{ChiSquare, F};
use reCTBN::structure_learning::StructureLearningAlgorithm;
use reCTBN::tools::trajectory_generator;
use reCTBN::tools::Dataset;
use reCTBN::tools::RandomGraphGenerator;
use reCTBN::tools::RandomParametersGenerator;
use reCTBN::tools::UniformGraphGenerator;
use reCTBN::tools::UniformParametersGenerator;
fn uniform_parameters_generator_right_densities_ctmp() -> (CtbnNetwork, Dataset) {
let mut net = CtbnNetwork::new();
let nodes_cardinality = 20;
let domain_cardinality = 3;
for node in 0..nodes_cardinality {
// Create the domain for a discrete node
let mut domain = BTreeSet::new();
for dvalue in 0..domain_cardinality {
domain.insert(dvalue.to_string());
}
// Create the parameters for a discrete node using the domain
let param = DiscreteStatesContinousTimeParams::new(node.to_string(), domain);
//Create the node using the parameters
let node = DiscreteStatesContinousTime(param);
// Add the node to the network
net.add_node(node).unwrap();
}
// Initialize the Graph Generator using the one with an
// uniform distribution
let mut structure_generator = UniformGraphGenerator::new(1.0 / 3.0, Some(7641630759785120));
// Generate the graph directly on the network
structure_generator.generate_graph(&mut net);
// Initialize the parameters generator with uniform distributin
let mut cim_generator = UniformParametersGenerator::new(3.0..7.0, Some(7641630759785120));
// Generate CIMs with uniformly distributed parameters.
cim_generator.generate_parameters(&mut net);
let dataset = trajectory_generator(&net, 300, 200.0, Some(30230423));
return (net, dataset);
}
fn structure_learning_CTPC(net: CtbnNetwork, dataset: &Dataset) {
// Initialize the hypothesis tests to pass to the CTPC with their
// respective significance level `alpha`
let f = F::new(1e-6);
let chi_sq = ChiSquare::new(1e-4);
// Use the bayesian approach to learn the parameters
let parameter_learning = MLE {};
//Initialize CTPC
let ctpc = CTPC::new(parameter_learning, f, chi_sq);
// Learn the structure of the network from the generated trajectory
ctpc.fit_transform(net, dataset);
}
fn main() {
let (net, dataset) = uniform_parameters_generator_right_densities_ctmp();
structure_learning_CTPC(net, &dataset);
}
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