[workspace]

name = "gimbal-python"

channels = ["conda-forge"]

platforms = ["linux-64", "win-64"]

[dependencies]

python = "3.11.*"

pip = "*"

pytorch = "*"

scikit-learn = "*"

matplotlib = "*"

jupyterlab = "*"

ipykernel = "*"

pymc = "*"

nutpie = "*"

arviz = "*"

preliz = "*"

ipywidgets = "*"

pytest = "*"

[tasks]

# Install package in editable mode

install-dev = "pip install -e ."

# Quick environment validation

check-setup = { cmd = "python -c 'import gimbal_pymc, pymc, nutpie; print(\"✓ Environment OK\")'" }

# Run the synthetic GIMBAL demo (legacy Torch implementation)

run-demo = "python -m examples.run_gimbal_demo"

# PyMC pipeline demos

demo-pymc = "python examples/demo_v0_2_0_pymc_pipeline.py"

demo-priors = "python examples/demo_v0_2_1_data_driven_priors.py"

# Launch JupyterLab for interactive notebooks

notebook = "jupyter lab"

# Dataset generation

generate-datasets = "python tests/pipeline/generate_dataset.py"

# Testing

test-pipeline = "pytest tests/pipeline/test_synthetic_data_generator.py -v"

test-unit = "pytest tests/unit/ -v"

test-stages = "pytest tests/test_stage1_collapsed_hmm.py tests/test_stage2_camera_model.py -v"

test-integration = "pytest tests/integration/ -v"

test-smoke = "pytest tests/smoke/ -v"

test-all = "pytest tests/ -v"

test-diagnostics = "pytest tests/diagnostics/ -v"

# Pipeline stages (for L00_minimal dataset)

pipeline-clean = "python tests/pipeline/stage_b_clean_2d.py tests/pipeline/datasets/L00_minimal tests/pipeline/fits/L00_minimal"

pipeline-triangulate = "python tests/pipeline/stage_c_triangulation.py tests/pipeline/datasets/L00_minimal tests/pipeline/fits/L00_minimal"

pipeline-full = "python tests/pipeline/fit_L00_toolchain.py"