[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 exclude: (bin/run-figures)
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.1.0
+    rev: v4.2.0
     hooks:
     -   id: check-added-large-files
         args: ['--maxkb=10000'] # 100 is too small for graphs
@@ -13,21 +13,21 @@ repos:
     -   id: mixed-line-ending
     -   id: trailing-whitespace
 -   repo: https://github.com/asottile/blacken-docs
-    rev: v1.7.0
+    rev: v1.12.1
     hooks:
     -   id: blacken-docs
         files: '(\.md|\.rst)$'
         additional_dependencies: [black]
 -   repo: https://github.com/psf/black
-    rev: 20.8b0
+    rev: 22.3.0
     hooks:
     -   id: black
         args: ['--line-length=100']
         files: '(\.pyi?|wscript|ipynb)$'
         language_version: python3
         additional_dependencies: [black-nb]
--   repo: https://gitlab.com/pycqa/flake8
-    rev: 3.8.3
+-   repo: https://github.com/PyCQA/flake8
+    rev: 4.0.1
     hooks:
     -   id: flake8
         files: '(\.pyi?|wscript|ipynb)$'
@@ -41,13 +41,13 @@ repos:
         #     flake8-todo, flake8-unused-arguments, pep8-naming, pydocstyle, Pygments,
         # ]
 -   repo: https://github.com/asottile/reorder_python_imports
-    rev: v2.3.0
+    rev: v3.1.0
     hooks:
     -   id: reorder-python-imports
         files: '(\.pyi?|wscript)$'
         exclude: '.*conf(ig)*\.py'
 -   repo: https://github.com/asottile/add-trailing-comma
-    rev: v2.0.1
+    rev: v2.2.3
     hooks:
     -   id: add-trailing-comma
         args: [--py36-plus]

econsa/quantile_measures.py

@@ -250,16 +250,16 @@ def _dlr_conditional_samples(x):
     n_draws, n_params = x.shape
 
     # The dependence of m versus n_draws accroding to S. Kucherenko and S. Song(2017).
-    if n_draws == 2 ** 6:
-        m = 2 ** 3
-    elif n_draws in [2 ** 7, 2 ** 8, 2 ** 9]:
-        m = 2 ** 4
-    elif n_draws == 2 ** 10:
-        m = 2 ** 5
-    elif n_draws in [2 ** 11, 2 ** 12, 2 ** 13]:
-        m = 2 ** 6
-    elif n_draws in [2 ** 14, 2 ** 15]:
-        m = 2 ** 7
+    if n_draws == 2**6:
+        m = 2**3
+    elif n_draws in [2**7, 2**8, 2**9]:
+        m = 2**4
+    elif n_draws == 2**10:
+        m = 2**5
+    elif n_draws in [2**11, 2**12, 2**13]:
+        m = 2**6
+    elif n_draws in [2**14, 2**15]:
+        m = 2**7
     else:
         raise NotImplementedError
 

econsa/shapley.py

@@ -186,14 +186,14 @@ def get_shapley(
                 delta = estimated_cost - previous_cost
 
             shapley_effects[perms[j]] = shapley_effects[perms[j]] + delta
-            shapley_effects_squared[perms[j]] = shapley_effects_squared[perms[j]] + delta ** 2
+            shapley_effects_squared[perms[j]] = shapley_effects_squared[perms[j]] + delta**2
 
             previous_cost = estimated_cost
 
     shapley_effects = shapley_effects / n_perms / output_variance
-    shapley_effects_squared = shapley_effects_squared / n_perms / (output_variance ** 2)
+    shapley_effects_squared = shapley_effects_squared / n_perms / (output_variance**2)
     standard_errors = np.sqrt(
-        (shapley_effects_squared - shapley_effects ** 2) / n_perms,
+        (shapley_effects_squared - shapley_effects**2) / n_perms,
     )
 
     # confidence intervals

econsa/tests/test_quantile_measures.py

@@ -77,7 +77,7 @@ def test_1(test_1_fixture):
 
     for estimator, n_draws, decimal in zip(
         ["DLR", "DLR", "DLR", "DLR", "brute force"],
-        [2 ** 6, 2 ** 9, 2 ** 10, 2 ** 13, 3000],
+        [2**6, 2**9, 2**10, 2**13, 3000],
         [0, 1, 1, 2, 2],
     ):
         norm_q_2_solve = p_measures(
@@ -97,7 +97,7 @@ def test_wrong_value_criterion(test_1_fixture):
     # remove the last item in dictionary.
     test_1_fixture.popitem()
 
-    p_measures = partial(mc_quantile_measures, n_draws=2 ** 10, **test_1_fixture)
+    p_measures = partial(mc_quantile_measures, n_draws=2**10, **test_1_fixture)
 
     for estimator, scheme in zip(["double loop reordering", "DLR"], ["sobol", "halton"]):
         with pytest.raises(ValueError):
@@ -112,7 +112,7 @@ def test_not_implemented_criterion(test_1_fixture):
 
     p_measures = partial(mc_quantile_measures, estimator="DLR", **test_1_fixture)
 
-    for dist_type, n_draws in zip(["Gamma", "Normal"], [2 ** 10, 2 ** 5]):
+    for dist_type, n_draws in zip(["Gamma", "Normal"], [2**10, 2**5]):
         with pytest.raises(NotImplementedError):
             p_measures(dist_type=dist_type, n_draws=n_draws)
 
@@ -169,7 +169,7 @@ def simple_linear_function_modified(x):
 
     for estimator, n_draws in zip(
         ["DLR", "brute force"],
-        [2 ** 14, 3000],
+        [2**14, 3000],
     ):
         norm_q_2_solve = mc_quantile_measures(
             estimator=estimator,
@@ -242,7 +242,7 @@ def ishigami_transposed(x, a=7, b=0.1):
     # Here we test naive monte carlo estimates by specifying `sampling_scheme` to "random".
     for estimator, n_draws in zip(
         ["DLR", "brute force"],
-        [2 ** 14, 3000],
+        [2**14, 3000],
     ):
         norm_q_2_solve = mc_quantile_measures(
             estimator=estimator,

econsa/tests/test_shapley.py

@@ -43,9 +43,9 @@ def x_cond(n, subset_j, subsetj_conditional, xjc):
     cov = np.array([[1.0, 0, 0], [0, 1.0, 1.8], [0, 1.8, 4.0]])
     method = "exact"
     n_perms = None
-    n_output = 10 ** 4
-    n_outer = 10 ** 3
-    n_inner = 10 ** 2
+    n_output = 10**4
+    n_outer = 10**3
+    n_inner = 10**2
 
     col = ["X" + str(i) for i in np.arange(n_inputs) + 1]
     names = ["Shapley effects", "std. errors", "CI_min", "CI_max"]
@@ -107,7 +107,7 @@ def x_cond(n, subset_j, subsetj_conditional, xjc):
     cov = np.array([[1.0, 0, 0], [0, 1.0, 1.8], [0, 1.8, 4.0]])
     method = "random"
     n_perms = 30000
-    n_output = 10 ** 4
+    n_output = 10**4
     n_outer = 1
     n_inner = 3