chronopt 0.2.0

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chronopt

chronos-optimum is a Rust-first toolkit for time-series inference and optimisation with ergonomic Python bindings. It couples high-performance solvers with a highly customisable builder API for identification and optimisation of differential systems.

Project goals

• Speed and numerical accuracy through a Rust core.
• Modular components with informative diagnostics.
• Batteries-included experience spanning optimisation, sampling, and plotting.

Core capabilities

• Gradient-free (Nelder-Mead, CMA-ES) and gradient-based (Adam) optimisers with configurable convergence criteria.
• Paralleled differential equation fitting via DiffSL with dense or sparse Diffsol backends.
• Customisable likelihood/cost metrics and Monte-Carlo sampling for posterior exploration.
• Flexible integration with state-of-the-art differential solvers, such as Diffrax, DifferentialEquations.jl
• Python builder APIs mirroring the Rust core plus generated type stubs for autocompletion.

Installation

Chronopt targets Python >= 3.11. Windows builds are currently marked experimental.

pip install chronopt

# Or with uv
uv pip install chronopt

# Optional extras
pip install "chronopt[plotting]"

Quickstart

ScalarProblem

import numpy as np
import chronopt as chron


def rosenbrock(x):
    value = (1 - x[0]) ** 2 + 100 * (x[1] - x[0] ** 2) ** 2
    return np.asarray([value], dtype=float)


builder = (
    chron.ScalarBuilder()
    .with_callable(rosenbrock)
    .with_parameter("x", 1.5)
    .with_parameter("y", -1.5)
)
problem = builder.build()
result = problem.optimize()

print(f"Optimal parameters: {result.x}")
print(f"Objective value: {result.fun:.3e}")
print(f"Success: {result.success}")

Differential solver workflow

import numpy as np
import chronopt as chron


# Example diffsol ODE (logistic growth)
dsl = """
in = [r, k]
r { 1 } k { 1 }
u_i { y = 0.1 }
F_i { (r * y) * (1 - (y / k)) }
"""

t = np.linspace(0.0, 5.0, 51)
observations = np.exp(-1.3 * t)
data = np.column_stack((t, observations))

builder = (
    chron.DiffsolBuilder()
    .with_diffsl(dsl)
    .with_data(data)
    .with_parameter("k", 1.0)
    .with_backend("dense")
)
problem = builder.build()

optimiser = chron.CMAES().with_max_iter(1000)
result = optimiser.run(problem, [0.5,0.5])

print(result.x)

Development setup

Clone the repository and create the Python environment:

uv sync

Build the Rust extension with Python bindings:

uv run maturin develop

Regenerate .pyi stubs after changing the bindings:

uv run cargo run -p chronopt-py --no-default-features --features stubgen --bin generate_stubs

Without uv, invoke the generator directly:

cargo run -p chronopt-py --no-default-features --features stubgen --bin generate_stubs

Pre-commit hooks

uv tool install pre-commit
pre-commit install
pre-commit run --all-files

Tests

uv run maturin develop && uv run pytest -v # Python tests
cargo test # Rust tests