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Incorporate observations from EPP lecture (#416)
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janosg committed Dec 13, 2022
1 parent 60e05f9 commit d3cbbab
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Showing 8 changed files with 296 additions and 9 deletions.
6 changes: 3 additions & 3 deletions .pre-commit-config.yaml
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Expand Up @@ -45,7 +45,7 @@ repos:
types: [python]

- repo: https://github.com/asottile/pyupgrade
rev: v3.2.3
rev: v3.3.1
hooks:
- id: pyupgrade
args: [--py38-plus]
Expand All @@ -58,7 +58,7 @@ repos:
exclude: docs/source/how_to_guides/optimization/how_to_specify_constraints.md

- repo: https://github.com/psf/black
rev: "22.10.0"
rev: "22.12.0"
hooks:
- id: black
language_version: python3.9
Expand Down Expand Up @@ -87,6 +87,6 @@ repos:
additional_dependencies: [isort==5.6.4]

- repo: https://github.com/mgedmin/check-manifest
rev: "0.48"
rev: "0.49"
hooks:
- id: check-manifest
2 changes: 1 addition & 1 deletion docs/source/algorithms.md
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Expand Up @@ -3686,7 +3686,7 @@ using an NLOPT algorithm. To install nlopt run `conda install nlopt`.
estimagic supports the following [SimOpt](https://github.com/simopt-admin/simopt)
algorithms. Please add the [appropriate
citations](https://github.com/simopt-admin/simopt) in addition to estimagic when using a
SimOpt algorithm. To install simopt run `pip install simoptlib`.
SimOpt algorithm. To install simopt run `pip install simoptlib==1.0.1`.

```{eval-rst}
.. dropdown:: simopt_adam
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Expand Up @@ -687,7 +687,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.5 ('base')",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -701,7 +701,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
"version": "3.9.13"
},
"vscode": {
"interpreter": {
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1 change: 1 addition & 0 deletions docs/source/how_to_guides/optimization/index.md
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Expand Up @@ -15,6 +15,7 @@ how_to_handle_errors_during_optimization.ipynb
how_to_scale_optimization_problems
how_to_do_multistart_optimizations.ipynb
how_to_benchmark_optimization_algorithms.ipynb
how_to_visualize_histories.ipynb
how_to_visualize_an_optimization_problem.ipynb
how_to_pick_an_optimizer.ipynb
```
3 changes: 2 additions & 1 deletion setup.cfg
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Expand Up @@ -50,12 +50,13 @@ install_requires =
numpy>=1.17
pandas>=1.0
bokeh>=1.3
scipy
scipy>=1.7
fuzzywuzzy
sqlalchemy>=1.3
plotly
dill
pybaum
numba


[options.packages.find]
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3 changes: 3 additions & 0 deletions src/estimagic/optimization/scipy_optimizers.py
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Expand Up @@ -143,6 +143,8 @@ def scipy_slsqp(
def scipy_neldermead(
criterion,
x,
lower_bounds,
upper_bounds,
*,
stopping_max_iterations=STOPPING_MAX_ITERATIONS,
stopping_max_criterion_evaluations=STOPPING_MAX_CRITERION_EVALUATIONS,
Expand All @@ -168,6 +170,7 @@ def scipy_neldermead(
res = scipy.optimize.minimize(
fun=criterion,
x0=x,
bounds=_get_scipy_bounds(lower_bounds, upper_bounds),
method="Nelder-Mead",
options=options,
)
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