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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"
    ]
   },
   {

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"
    ]
   },
   {

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"
    ]
   },
   {

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)"
    ]
   },

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)"
    ]
   },

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"
    ]
   },
   {

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"
    ]
   },

docs/source/how_to/how_to_bounds.ipynb

@@ -32,6 +32,7 @@
    "outputs": [],
    "source": [
     "import numpy as np\n",
+    "\n",
     "import optimagic as om"
    ]
   },

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",

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",

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\")"
    ]
   },

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"
    ]
   },

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",

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"
    ]
   },

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"
    ]
   },

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"
    ]
   },
   {

docs/source/tutorials/optimization_overview.ipynb

@@ -16,8 +16,9 @@
    "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"
    ]
   },
   {

src/estimagic/__init__.py

@@ -1,6 +1,17 @@
 import warnings
 from dataclasses import dataclass
 
+from estimagic import utilities
+from estimagic.bootstrap import BootstrapResult, bootstrap
+from estimagic.estimate_ml import LikelihoodResult, estimate_ml
+from estimagic.estimate_msm import MomentsResult, estimate_msm
+from estimagic.estimation_table import (
+    estimation_table,
+    render_html,
+    render_latex,
+)
+from estimagic.lollipop_plot import lollipop_plot
+from estimagic.msm_weighting import get_moments_cov
 from optimagic import OptimizeLogReader as _OptimizeLogReader
 from optimagic import OptimizeResult as _OptimizeResult
 from optimagic import __version__
@@ -22,18 +33,6 @@
 from optimagic import traceback_report as _traceback_report
 from optimagic.decorators import deprecated
 
-from estimagic import utilities
-from estimagic.bootstrap import BootstrapResult, bootstrap
-from estimagic.estimate_ml import LikelihoodResult, estimate_ml
-from estimagic.estimate_msm import MomentsResult, estimate_msm
-from estimagic.estimation_table import (
-    estimation_table,
-    render_html,
-    render_latex,
-)
-from estimagic.lollipop_plot import lollipop_plot
-from estimagic.msm_weighting import get_moments_cov
-
 MSG = (
     "estimagic.{name} has been deprecated in version 0.5.0. Use optimagic.{name} "
     "instead. This function will be removed in version 0.6.0."

src/estimagic/bootstrap.py

@@ -5,16 +5,16 @@
 
 import numpy as np
 import pandas as pd
-from optimagic.batch_evaluators import joblib_batch_evaluator
-from optimagic.parameters.block_trees import matrix_to_block_tree
-from optimagic.parameters.tree_registry import get_registry
-from optimagic.utilities import get_rng
 from pybaum import leaf_names, tree_flatten, tree_just_flatten, tree_unflatten
 
 from estimagic.bootstrap_ci import calculate_ci
 from estimagic.bootstrap_helpers import check_inputs
 from estimagic.bootstrap_outcomes import get_bootstrap_outcomes
 from estimagic.shared_covs import calculate_estimation_summary
+from optimagic.batch_evaluators import joblib_batch_evaluator
+from optimagic.parameters.block_trees import matrix_to_block_tree
+from optimagic.parameters.tree_registry import get_registry
+from optimagic.utilities import get_rng
 
 
 def bootstrap(

src/estimagic/bootstrap_outcomes.py

@@ -1,7 +1,6 @@
-from optimagic.batch_evaluators import process_batch_evaluator
-
 from estimagic.bootstrap_helpers import check_inputs
 from estimagic.bootstrap_samples import get_bootstrap_indices
+from optimagic.batch_evaluators import process_batch_evaluator
 
 
 def get_bootstrap_outcomes(

src/estimagic/estimate_ml.py

@@ -5,6 +5,26 @@
 
 import numpy as np
 import pandas as pd
+
+from estimagic.ml_covs import (
+    cov_cluster_robust,
+    cov_hessian,
+    cov_jacobian,
+    cov_robust,
+    cov_strata_robust,
+)
+from estimagic.shared_covs import (
+    FreeParams,
+    calculate_ci,
+    calculate_estimation_summary,
+    calculate_free_estimates,
+    calculate_p_values,
+    calculate_summary_data_estimation,
+    get_derivative_case,
+    transform_covariance,
+    transform_free_cov_to_cov,
+    transform_free_values_to_params_tree,
+)
 from optimagic import deprecations, mark
 from optimagic.deprecations import (
     replace_and_warn_about_deprecated_bounds,
@@ -32,26 +52,6 @@
 from optimagic.typing import AggregationLevel
 from optimagic.utilities import get_rng, to_pickle
 
-from estimagic.ml_covs import (
-    cov_cluster_robust,
-    cov_hessian,
-    cov_jacobian,
-    cov_robust,
-    cov_strata_robust,
-)
-from estimagic.shared_covs import (
-    FreeParams,
-    calculate_ci,
-    calculate_estimation_summary,
-    calculate_free_estimates,
-    calculate_p_values,
-    calculate_summary_data_estimation,
-    get_derivative_case,
-    transform_covariance,
-    transform_free_cov_to_cov,
-    transform_free_values_to_params_tree,
-)
-
 
 def estimate_ml(
     loglike,

src/estimagic/estimate_msm.py

@@ -9,29 +9,6 @@
 
 import numpy as np
 import pandas as pd
-from optimagic import deprecations, mark
-from optimagic.deprecations import (
-    replace_and_warn_about_deprecated_bounds,
-)
-from optimagic.differentiation.derivatives import first_derivative
-from optimagic.differentiation.numdiff_options import (
-    NumdiffPurpose,
-    get_default_numdiff_options,
-    pre_process_numdiff_options,
-)
-from optimagic.exceptions import InvalidFunctionError
-from optimagic.optimization.fun_value import LeastSquaresFunctionValue
-from optimagic.optimization.optimize import minimize
-from optimagic.optimization.optimize_result import OptimizeResult
-from optimagic.parameters.block_trees import block_tree_to_matrix, matrix_to_block_tree
-from optimagic.parameters.bounds import Bounds, pre_process_bounds
-from optimagic.parameters.conversion import Converter, get_converter
-from optimagic.parameters.space_conversion import InternalParams
-from optimagic.parameters.tree_registry import get_registry
-from optimagic.shared.check_option_dicts import (
-    check_optimization_options,
-)
-from optimagic.utilities import get_rng, to_pickle
 from pybaum import leaf_names, tree_just_flatten
 
 from estimagic.msm_covs import cov_optimal, cov_robust
@@ -56,6 +33,29 @@
     transform_free_cov_to_cov,
     transform_free_values_to_params_tree,
 )
+from optimagic import deprecations, mark
+from optimagic.deprecations import (
+    replace_and_warn_about_deprecated_bounds,
+)
+from optimagic.differentiation.derivatives import first_derivative
+from optimagic.differentiation.numdiff_options import (
+    NumdiffPurpose,
+    get_default_numdiff_options,
+    pre_process_numdiff_options,
+)
+from optimagic.exceptions import InvalidFunctionError
+from optimagic.optimization.fun_value import LeastSquaresFunctionValue
+from optimagic.optimization.optimize import minimize
+from optimagic.optimization.optimize_result import OptimizeResult
+from optimagic.parameters.block_trees import block_tree_to_matrix, matrix_to_block_tree
+from optimagic.parameters.bounds import Bounds, pre_process_bounds
+from optimagic.parameters.conversion import Converter, get_converter
+from optimagic.parameters.space_conversion import InternalParams
+from optimagic.parameters.tree_registry import get_registry
+from optimagic.shared.check_option_dicts import (
+    check_optimization_options,
+)
+from optimagic.utilities import get_rng, to_pickle
 
 
 def estimate_msm(

src/estimagic/estimation_table.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 import pandas as pd
+
 from optimagic.shared.compat import pd_df_map
 
 suppress_performance_warnings = np.testing.suppress_warnings()
@@ -1473,8 +1474,7 @@ def _get_digits_after_decimal(df):
             )
         except KeyError:
             trail_length = 0
-        if trail_length > max_trail:
-            max_trail = trail_length
+        max_trail = max(trail_length, max_trail)
     return max_trail
 
 

src/estimagic/examples/logit.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import pandas as pd
+
 from optimagic import mark