[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ exclude: |
 repos:
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v6.0.0
     hooks:
       - id: check-added-large-files
       - id: check-case-conflict
@@ -42,7 +42,7 @@ repos:
           ['--no-error-on-unmatched-pattern', '--ignore-unknown']
 
   - repo: https://github.com/igorshubovych/markdownlint-cli
-    rev: v0.41.0
+    rev: v0.45.0
     hooks:
       - id: markdownlint
         args: ["--fix"]
@@ -59,26 +59,26 @@ repos:
         args: ["--ignore=E006,E011"]
 
   - repo: https://github.com/shellcheck-py/shellcheck-py
-    rev: v0.10.0.1
+    rev: v0.11.0.1
     hooks:
       - id: shellcheck
         args: ["-x"]  # Check external files
 
   - repo: https://github.com/Mateusz-Grzelinski/actionlint-py
-    rev: v1.7.1.15
+    rev: v1.7.7.24
     hooks:
       - id: actionlint
 
   - repo: https://github.com/adrienverge/yamllint.git
-    rev: v1.35.1
+    rev: v1.37.1
     hooks:
       - id: yamllint
         args:
           ["-d", "{rules: {line-length: {max: 120}},
           ignore-from-file: [.gitignore],}"]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.2
+    rev: v0.12.12
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix, --config=pyproject.toml]
@@ -94,7 +94,7 @@ repos:
           then /bin/mkdir .mypy_cache; fi; exit 0'
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.10.1"
+    rev: "v1.17.1"
     hooks:
       - id: mypy
         verbose: true

tests/test_powerPlant.py

@@ -52,17 +52,17 @@ def test_power_plants():
 
     loss_var = pp.financial_losses(damages=damage, energy_price=elec_price, r=r_var)
 
-    assert np.isclose(
-        loss_cst.mean(), loss_var.mean()
-    ), "Losses are not calculated properly"
+    assert np.isclose(loss_cst.mean(), loss_var.mean()), (
+        "Losses are not calculated properly"
+    )
 
     # Now the same pp in two different ways
 
     pp2 = PowerPlants(capacity=900913242.0091324, av_rate=1, name=name)
     loss_var2 = pp2.financial_losses(damages=damage, energy_price=elec_price, r=r_var)
 
-    assert np.isclose(
-        loss_var.mean(), loss_var2.mean()
-    ), "Losses are not calculated properly"
+    assert np.isclose(loss_var.mean(), loss_var2.mean()), (
+        "Losses are not calculated properly"
+    )
 
     print("FINISHED DCV TEST SUCCESSFULLY!!!")

tests/test_realstate.py

@@ -79,15 +79,15 @@ def test_asset():
     variance_loss = losses[0].var()
     expected_variance_loss = 724.0
     print(
-        f'Mean Financial Losses: {real_asset.financial_losses(["2030-02-09"], damage=discrete_rand_var)[0].mean()}'
+        f"Mean Financial Losses: {real_asset.financial_losses(['2030-02-09'], damage=discrete_rand_var)[0].mean()}"
     )
     print(
-        f'Variance Financial Losses: {real_asset.financial_losses(["2030-02-09"], damage=discrete_rand_var)[0].var()}'
+        f"Variance Financial Losses: {real_asset.financial_losses(['2030-02-09'], damage=discrete_rand_var)[0].var()}"
     )
     assert np.allclose(mean_loss, expected_mean_loss), "Mean is not calculated properly"
-    assert np.allclose(
-        variance_loss, expected_variance_loss
-    ), "Variance is not calculated properly"
+    assert np.allclose(variance_loss, expected_variance_loss), (
+        "Variance is not calculated properly"
+    )
 
     intervals_osc = np.array(
         [
@@ -150,12 +150,12 @@ def test_asset():
         ]
     )
 
-    assert np.allclose(
-        discrete_rand_var_osc.intervals, expected_intervals
-    ), "Intervals are not calculated properly"
-    assert np.allclose(
-        discrete_rand_var_osc.probabilities, expected_probabilities
-    ), "Probabilities are not calculated properly"
+    assert np.allclose(discrete_rand_var_osc.intervals, expected_intervals), (
+        "Intervals are not calculated properly"
+    )
+    assert np.allclose(discrete_rand_var_osc.probabilities, expected_probabilities), (
+        "Probabilities are not calculated properly"
+    )
 
     # zero included
 
@@ -246,7 +246,7 @@ def test_asset():
             loan_amounts=loan_amounts,
         )
 
-    print(f" LTV mean value (first date, fist asset): {ltv[0,0].mean()}")
+    print(f" LTV mean value (first date, fist asset): {ltv[0, 0].mean()}")
     means = DiscreteRandomVariable.means_vectorized(ltv)
     print(f" LTV mean values: {means}")
 
@@ -257,7 +257,7 @@ def test_asset():
     assert np.allclose(means, expected_means), "LTV mean values calculation failed"
 
     # Variances
-    print(f" LTV variance (first date, fist asset): {ltv[0,0].var()}")
+    print(f" LTV variance (first date, fist asset): {ltv[0, 0].var()}")
     vars = DiscreteRandomVariable.vars_vectorized(ltv)
     print(f" LTV variances: {vars}")