CoFI (Common Framework for Inference)
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Introduction
CoFI (Common Framework for Inference) is an open source initiative for interfacing between generic inference algorithms and specific geoscience problems.
With a mission to bridge the gap between the domain expertise and the inference expertise, CoFI provides an interface across a wide range of inference algorithms from different sources, underpinned by a rich set of domain relevant examples.
Read the documentation, and let us know your feedback or any issues!
Installation
From PyPI:
$ pip install cofi
Or alternatively, from conda-forge:
$ conda install -c conda-forge cofi
Check CoFI documentation - installation page for details on dependencies and setting up with virtual environments.
Basic Usage
graph TD;
base_problem_details(inv_problem = BaseProblem#40;#41;\ninv_problem.set_objective#40;DEFINE ME#41;\ninv_problem.set_jacobian#40;DEFINE ME#41;\ninv_problem.set_initial_model#40;DEFINE ME#41;):::cls_code_block
inversion_options_details(inv_options = InversionOptions#40;#41;\ninv_options.set_tool#40;#34;scipy.linalg.lstsq#34;#41;):::cls_code_block
inversion_details(inv=Inversion#40;inv_problem, inv_options#41;\nresult = inv.run#40;#41;):::cls_code_block
subgraph base_problem ["Base Problem"]
base_problem_details
end
subgraph inversion_options ["Inversion Options"]
inversion_options_details
end
subgraph inversion ["Inversion"]
inversion_details
end
base_problem --> inversion;
inversion_options --> inversion;
classDef cls_base_problem fill: oldlace, stroke-width: 0, color: black;
classDef cls_inversion_options fill: oldlace, stroke-width: 0, color: black;
classDef cls_inversion fill: lavender, stroke-width: 0, color: black;
classDef cls_code_block fill: lightgrey, stroke-width: 0, text-align: left, color: black;
class base_problem cls_base_problem;
class inversion_options cls_inversion_options;
class inversion cls_inversion;
CoFI API has flexible ways of defining an inversion problem. For instance:
import cofi
inv_problem = cofi.BaseProblem()
inv_problem.set_objective(my_objective_func)
inv_problem.set_initial_model(my_starting_point)
Once a problem is defined, cofi can tell you what inference tools you can use based on what level of
information you've provided:
inv_problem.suggest_tools() # a tree will be printed
Run an inversion with these lines:
inv_options = cofi.InversionOptions()
inv_options.set_tool("torch.optim")
inv_options.set_params(options={"num_iterations": 50, "algorithm": "Adam"})
inv = cofi.Inversion(inv_problem, inv_options)
result = inv.run()
print(result.success)
print(result.model)
And now an inversion is completed! Check out our example gallery and tutorial pages for more real-world or advanced use cases.
Contributing
Interested in contributing? Please check out our contributor's guide.
Licence
This project is distributed under a 2-clause BSD licence. A copy of this licence is provided with distributions of the software.
4 maintainers
Metadata
4 maintainers
Release files for cofi 0.2.12
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| File | Size | Uploaded | |
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|---|---|---|---|---|
| cofi-0.2.12-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 160.9 kB
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