Merge branch 'main' into docs

optimagic-dev · Sep 18, 2024 · 322d5df · 322d5df
2 parents 1bfcb89 + 42fd8a5
commit 322d5df
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -6,7 +6,7 @@ repos:
  - id: check-useless-excludes
  # - id: identity # Prints all files passed to pre-commits. Debugging.
  - repo: https://github.com/lyz-code/yamlfix
- rev: 1.16.0
+ rev: 1.17.0
  hooks:
  - id: yamlfix
  exclude: tests/optimagic/optimizers/_pounders/fixtures
@@ -68,7 +68,7 @@ repos:
  - --blank
  exclude: src/optimagic/optimization/algo_options.py
  - repo: https://github.com/astral-sh/ruff-pre-commit
- rev: v0.5.7
+ rev: v0.6.3
  hooks:
  # Run the linter.
  - id: ruff
@@ -119,7 +119,7 @@ repos:
  args:
  - --drop-empty-cells
  - repo: https://github.com/pre-commit/mirrors-mypy
- rev: v1.11.1
+ rev: v1.11.2
  hooks:
  - id: mypy
  files: src|tests

diff --git a/docs/source/estimagic/explanation/bootstrap_montecarlo_comparison.ipynb b/docs/source/estimagic/explanation/bootstrap_montecarlo_comparison.ipynb
@@ -42,13 +42,14 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "import estimagic as em\n",
  "import matplotlib.pyplot as plt\n",
  "import numpy as np\n",
  "import pandas as pd\n",
  "import scipy\n",
  "import statsmodels.api as sm\n",
- "from joblib import Parallel, delayed"
+ "from joblib import Parallel, delayed\n",
+ "\n",
+ "import estimagic as em"
  ]
  },
  {

diff --git a/docs/source/estimagic/tutorials/bootstrap_overview.ipynb b/docs/source/estimagic/tutorials/bootstrap_overview.ipynb
@@ -19,11 +19,12 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "import estimagic as em\n",
  "import numpy as np\n",
  "import pandas as pd\n",
  "import seaborn as sns\n",
- "import statsmodels.api as sm"
+ "import statsmodels.api as sm\n",
+ "\n",
+ "import estimagic as em"
  ]
  },
  {

diff --git a/docs/source/estimagic/tutorials/estimation_tables_overview.ipynb b/docs/source/estimagic/tutorials/estimation_tables_overview.ipynb
@@ -24,11 +24,12 @@
  "outputs": [],
  "source": [
  "# Make necessary imports\n",
- "import estimagic as em\n",
  "import pandas as pd\n",
  "import statsmodels.formula.api as sm\n",
- "from estimagic.config import EXAMPLE_DIR\n",
- "from IPython.core.display import HTML"
+ "from IPython.core.display import HTML\n",
+ "\n",
+ "import estimagic as em\n",
+ "from estimagic.config import EXAMPLE_DIR"
  ]
  },
  {

diff --git a/docs/source/estimagic/tutorials/likelihood_overview.ipynb b/docs/source/estimagic/tutorials/likelihood_overview.ipynb
@@ -34,11 +34,12 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "import estimagic as em\n",
  "import numpy as np\n",
  "import pandas as pd\n",
  "from scipy.stats import norm\n",
  "\n",
+ "import estimagic as em\n",
+ "\n",
  "rng = np.random.default_rng(seed=0)"
  ]
  },

diff --git a/docs/source/estimagic/tutorials/msm_overview.ipynb b/docs/source/estimagic/tutorials/msm_overview.ipynb
@@ -42,10 +42,11 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "import estimagic as em\n",
  "import numpy as np\n",
  "import pandas as pd\n",
  "\n",
+ "import estimagic as em\n",
+ "\n",
  "rng = np.random.default_rng(seed=0)"
  ]
  },

diff --git a/docs/source/explanation/why_optimization_is_hard.ipynb b/docs/source/explanation/why_optimization_is_hard.ipynb
@@ -28,8 +28,9 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
- "import optimagic as om\n",
- "import seaborn as sns"
+ "import seaborn as sns\n",
+ "\n",
+ "import optimagic as om"
  ]
  },
  {

diff --git a/docs/source/how_to/how_to_algorithm_selection.ipynb b/docs/source/how_to/how_to_algorithm_selection.ipynb
@@ -34,6 +34,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om"
  ]
  },

diff --git a/docs/source/how_to/how_to_bounds.ipynb b/docs/source/how_to/how_to_bounds.ipynb
@@ -32,6 +32,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om"
  ]
  },

diff --git a/docs/source/how_to/how_to_criterion_function.ipynb b/docs/source/how_to/how_to_criterion_function.ipynb
@@ -25,6 +25,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om\n",
  "\n",
  "\n",

diff --git a/docs/source/how_to/how_to_derivatives.ipynb b/docs/source/how_to/how_to_derivatives.ipynb
@@ -38,6 +38,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om\n",
  "\n",
  "\n",

diff --git a/docs/source/how_to/how_to_errors_during_optimization.ipynb b/docs/source/how_to/how_to_errors_during_optimization.ipynb
@@ -49,9 +49,10 @@
  "import warnings\n",
  "\n",
  "import numpy as np\n",
- "import optimagic as om\n",
  "from scipy.optimize import minimize as scipy_minimize\n",
  "\n",
+ "import optimagic as om\n",
+ "\n",
  "warnings.simplefilter(\"ignore\")"
  ]
  },

diff --git a/docs/source/how_to/how_to_logging.ipynb b/docs/source/how_to/how_to_logging.ipynb
@@ -30,6 +30,7 @@
  "from pathlib import Path\n",
  "\n",
  "import numpy as np\n",
+ "\n",
  "import optimagic as om"
  ]
  },

diff --git a/docs/source/how_to/how_to_multistart.ipynb b/docs/source/how_to/how_to_multistart.ipynb
@@ -36,6 +36,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om\n",
  "\n",
  "\n",

diff --git a/docs/source/how_to/how_to_slice_plot.ipynb b/docs/source/how_to/how_to_slice_plot.ipynb
@@ -31,6 +31,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om"
  ]
  },

diff --git a/docs/source/how_to/how_to_visualize_histories.ipynb b/docs/source/how_to/how_to_visualize_histories.ipynb
@@ -23,6 +23,7 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
+ "\n",
  "import optimagic as om"
  ]
  },

diff --git a/docs/source/tutorials/numdiff_overview.ipynb b/docs/source/tutorials/numdiff_overview.ipynb
@@ -17,8 +17,9 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
- "import optimagic as om\n",
- "import pandas as pd"
+ "import pandas as pd\n",
+ "\n",
+ "import optimagic as om"
  ]
  },
  {

diff --git a/docs/source/tutorials/optimization_overview.ipynb b/docs/source/tutorials/optimization_overview.ipynb
@@ -16,15 +16,18 @@
  "outputs": [],
  "source": [
  "import numpy as np\n",
- "import optimagic as om\n",
- "import pandas as pd"
+ "import pandas as pd\n",
+ "\n",
+ "import optimagic as om"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "## Basic usage of `minimize`"
+ "## Basic usage of `minimize`\n",
+ "\n",
+ "The basic usage of `optimagic.minimize` is very similar to `scipy.optimize.minimize`"
  ]
  },
  {
@@ -43,13 +46,13 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "res = om.minimize(\n",
+ "lbfgsb_res = om.minimize(\n",
  " fun=sphere,\n",
  " params=np.arange(5),\n",
  " algorithm=\"scipy_lbfgsb\",\n",
  ")\n",
  "\n",
- "res.params.round(5)"
+ "lbfgsb_res.params.round(5)"
  ]
  },
  {
@@ -58,7 +61,7 @@
  "source": [
  "## `params` do not have to be vectors\n",
  "\n",
- "In optimagic, params can by arbitrary [pytrees](https://jax.readthedocs.io/en/latest/pytrees.html). Examples are (nested) dictionaries of numbers, arrays and pandas objects. "
+ "In optimagic, params can by arbitrary [pytrees](https://jax.readthedocs.io/en/latest/pytrees.html). Examples are (nested) dictionaries of numbers, arrays and pandas objects. This is very useful if you have many parameters!"
  ]
  },
  {
@@ -77,20 +80,22 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "res = om.minimize(\n",
+ "nm_res = om.minimize(\n",
  " fun=dict_sphere,\n",
  " params={\"a\": 0, \"b\": 1, \"c\": pd.Series([2, 3, 4])},\n",
- " algorithm=\"scipy_powell\",\n",
+ " algorithm=\"scipy_neldermead\",\n",
  ")\n",
  "\n",
- "res.params"
+ "nm_res.params"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "## The result contains all you need to know"
+ "## You can compare optimizers\n",
+ "\n",
+ "In practice, it is super hard to pick the right optimizer for your problem. With optimagic, you can simply try a few and compare their results!"
  ]
  },
  {
@@ -99,29 +104,16 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "res = om.minimize(\n",
- " fun=dict_sphere,\n",
- " params={\"a\": 0, \"b\": 1, \"c\": pd.Series([2, 3, 4])},\n",
- " algorithm=\"scipy_neldermead\",\n",
- ")\n",
- "res"
+ "results = {\"lbfgsb\": lbfgsb_res, \"nelder_mead\": nm_res}\n",
+ "fig = om.criterion_plot(results, max_evaluations=300)\n",
+ "fig.show(renderer=\"png\")"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "## You can visualize the convergence"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "fig = om.criterion_plot(res, max_evaluations=300)\n",
- "fig.show(renderer=\"png\")"
+ "You can also zoom in on the history of specific parameters. This can be super helpful to diagnose problems in the optimization. "
  ]
  },
  {
@@ -131,7 +123,7 @@
  "outputs": [],
  "source": [
  "fig = om.params_plot(\n",
- " res,\n",
+ " nm_res,\n",
  " max_evaluations=300,\n",
  " # optionally select a subset of parameters to plot\n",
  " selector=lambda params: params[\"c\"],\n",
@@ -145,20 +137,23 @@
  "source": [
  "## There are many optimizers\n",
  "\n",
- "If you install some optional dependencies, you can choose from a large (and growing) set of optimization algorithms -- all with the same interface!\n",
+ "By default, optimagic comes with optimizers from scipy, including global optimizers \n",
+ "and least-squares optimizers. But we also have wrappers for algorithms from **NlOpt**, \n",
+ "**Pygmo**, as well as several optimizers from individual packages like **fides**, \n",
+ "**ipopt**, **pybobyqa** and **dfols**. \n",
  "\n",
- "For example, we wrap optimizers from `scipy.optimize`, `nlopt`, `cyipopt`, `pygmo`, `fides`, `tao` and others. \n",
+ "To use optimizers that are not from scipy, follow our [installation guide](../installation.md) for optional dependencies. To see which optimizers we have, check out the [full list](../algorithms.md).\n",
  "\n",
- "We also have some optimizers that are not part of other packages. Examples are a `parallel Nelder-Mead` algorithm, The `BHHH` algorithm and a `parallel Pounders` algorithm.\n",
- "\n",
- "See the full list [here](../how_to_guides/optimization/how_to_specify_algorithm_and_algo_options"
+ "If you are missing your favorite optimizer in the list, let us know with an [issue](https://github.com/optimagic-dev/optimagic/issues)"
  ]
  },
  {
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "## You can add bounds"
+ "## You can add bounds\n",
+ "\n",
+ "As any optimizer library, optimagic lets you specify bounds for the parameters."
  ]
  },
  {
@@ -183,7 +178,9 @@
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "## You can fix parameters "
+ "## You can fix parameters \n",
+ "\n",
+ "On top of bounds, you can also fix one or more parameters during the optimization. "
  ]
  },
  {

diff --git a/pyproject.toml b/pyproject.toml
@@ -40,8 +40,9 @@ classifiers = [
  "Operating System :: MacOS :: MacOS X",
  "Operating System :: Microsoft :: Windows",
  "Operating System :: POSIX",
- "Programming Language :: Python :: 3",
- "Programming Language :: Python :: 3 :: Only",
+ "Programming Language :: Python :: 3.10",
+ "Programming Language :: Python :: 3.11",
+ "Programming Language :: Python :: 3.12",
  "Topic :: Scientific/Engineering",
 ]
 authors = [