Merge pull request #138 from scikit-learn-contrib/dev

Dev

.github/workflows/publish.yml

@@ -13,7 +13,7 @@ jobs:
     steps:
     - uses: actions/checkout@v4
     - name: Set up Python
-      uses: actions/setup-python@v3.12.0
+      uses: actions/setup-python@v4
       with:
         python-version: '3.10'
     - name: Install dependencies

HISTORY.rst

@@ -2,6 +2,12 @@
 History
 =======
 
+0.1.5 (2024-04-17)
+------------------
+
+* CICD now relies on Node.js 20
+* New tests for comparator.py and data.py
+
 0.1.4 (2024-04-15)
 ------------------
 

qolmat/imputations/em_sampler.py

@@ -71,7 +71,7 @@ def _conjugate_gradient(A: NDArray, X: NDArray, mask: NDArray) -> NDArray:
     return X_final
 
 
-def min_diff_Linf(list_params: List[NDArray], n_steps: int, order: int = 1) -> float:
+def max_diff_Linf(list_params: List[NDArray], n_steps: int, order: int = 1) -> float:
     """Computes the maximal L infinity norm between the `n_steps` last elements spaced by order.
     Used to compute the stop criterion.
 
@@ -762,8 +762,8 @@ def _check_convergence(self) -> bool:
         if n_iter < 3:
             return False
 
-        min_diff_means1 = min_diff_Linf(list_covs, n_steps=1)
-        min_diff_covs1 = min_diff_Linf(list_means, n_steps=1)
+        min_diff_means1 = max_diff_Linf(list_means, n_steps=1)
+        min_diff_covs1 = max_diff_Linf(list_covs, n_steps=1)
         min_diff_reached = min_diff_means1 < self.tolerance and min_diff_covs1 < self.tolerance
 
         if min_diff_reached:
@@ -772,16 +772,16 @@ def _check_convergence(self) -> bool:
         if n_iter < 7:
             return False
 
-        min_diff_means5 = min_diff_Linf(list_covs, n_steps=5)
-        min_diff_covs5 = min_diff_Linf(list_means, n_steps=5)
+        min_diff_means5 = max_diff_Linf(list_means, n_steps=5)
+        min_diff_covs5 = max_diff_Linf(list_covs, n_steps=5)
 
         min_diff_stable = (
             min_diff_means5 < self.stagnation_threshold
             and min_diff_covs5 < self.stagnation_threshold
         )
 
-        min_diff_loglik5_ord1 = min_diff_Linf(list_logliks, n_steps=5)
-        min_diff_loglik5_ord2 = min_diff_Linf(list_logliks, n_steps=5, order=2)
+        min_diff_loglik5_ord1 = max_diff_Linf(list_logliks, n_steps=5)
+        min_diff_loglik5_ord2 = max_diff_Linf(list_logliks, n_steps=5, order=2)
         max_loglik = (min_diff_loglik5_ord1 < self.stagnation_loglik) or (
             min_diff_loglik5_ord2 < self.stagnation_loglik
         )
@@ -1105,8 +1105,8 @@ def _check_convergence(self) -> bool:
         if n_iter < 3:
             return False
 
-        min_diff_B1 = min_diff_Linf(list_B, n_steps=1)
-        min_diff_S1 = min_diff_Linf(list_S, n_steps=1)
+        min_diff_B1 = max_diff_Linf(list_B, n_steps=1)
+        min_diff_S1 = max_diff_Linf(list_S, n_steps=1)
         min_diff_reached = min_diff_B1 < self.tolerance and min_diff_S1 < self.tolerance
 
         if min_diff_reached:
@@ -1115,14 +1115,14 @@ def _check_convergence(self) -> bool:
         if n_iter < 7:
             return False
 
-        min_diff_B5 = min_diff_Linf(list_B, n_steps=5)
-        min_diff_S5 = min_diff_Linf(list_S, n_steps=5)
+        min_diff_B5 = max_diff_Linf(list_B, n_steps=5)
+        min_diff_S5 = max_diff_Linf(list_S, n_steps=5)
         min_diff_stable = (
             min_diff_B5 < self.stagnation_threshold and min_diff_S5 < self.stagnation_threshold
         )
 
-        max_loglik5_ord1 = min_diff_Linf(list_logliks, n_steps=5, order=1)
-        max_loglik5_ord2 = min_diff_Linf(list_logliks, n_steps=5, order=2)
+        max_loglik5_ord1 = max_diff_Linf(list_logliks, n_steps=5, order=1)
+        max_loglik5_ord2 = max_diff_Linf(list_logliks, n_steps=5, order=2)
         max_loglik = (max_loglik5_ord1 < self.stagnation_loglik) or (
             max_loglik5_ord2 < self.stagnation_loglik
         )