Pushing the docs to dev/ for branch: main, commit aee7f594f5d82ba75bcb8d720066ce18c727d0d1

Author: sklearn-ci

Diff for: dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -153,7 +153,7 @@ def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gray):
 
 # %%
 batch_pca_estimator = decomposition.MiniBatchSparsePCA(
-    n_components=n_components, alpha=0.1, n_iter=100, batch_size=3, random_state=rng
+    n_components=n_components, alpha=0.1, max_iter=100, batch_size=3, random_state=rng
 )
 batch_pca_estimator.fit(faces_centered)
 plot_gallery(
@@ -171,7 +171,7 @@ def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gray):
 
 # %%
 batch_dict_estimator = decomposition.MiniBatchDictionaryLearning(
-    n_components=n_components, alpha=0.1, n_iter=50, batch_size=3, random_state=rng
+    n_components=n_components, alpha=0.1, max_iter=50, batch_size=3, random_state=rng
 )
 batch_dict_estimator.fit(faces_centered)
 plot_gallery("Dictionary learning", batch_dict_estimator.components_[:n_components])
@@ -272,7 +272,7 @@ def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gray):
 dict_pos_dict_estimator = decomposition.MiniBatchDictionaryLearning(
     n_components=n_components,
     alpha=0.1,
-    n_iter=50,
+    max_iter=50,
     batch_size=3,
     random_state=rng,
     positive_dict=True,
@@ -294,7 +294,7 @@ def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gray):
 dict_pos_code_estimator = decomposition.MiniBatchDictionaryLearning(
     n_components=n_components,
     alpha=0.1,
-    n_iter=50,
+    max_iter=50,
     batch_size=3,
     fit_algorithm="cd",
     random_state=rng,
@@ -318,7 +318,7 @@ def plot_gallery(title, images, n_col=n_col, n_row=n_row, cmap=plt.cm.gray):
 dict_pos_estimator = decomposition.MiniBatchDictionaryLearning(
     n_components=n_components,
     alpha=0.1,
-    n_iter=50,
+    max_iter=50,
     batch_size=3,
     fit_algorithm="cd",
     random_state=rng,

Diff for: dev/_downloads/4825fc8223d1af0f3b61080c3dea3a62/plot_faces_decomposition.py

@@ -148,7 +148,7 @@
       },
       "outputs": [],
       "source": [
-        "batch_pca_estimator = decomposition.MiniBatchSparsePCA(\n    n_components=n_components, alpha=0.1, n_iter=100, batch_size=3, random_state=rng\n)\nbatch_pca_estimator.fit(faces_centered)\nplot_gallery(\n    \"Sparse components - MiniBatchSparsePCA\",\n    batch_pca_estimator.components_[:n_components],\n)"
+        "batch_pca_estimator = decomposition.MiniBatchSparsePCA(\n    n_components=n_components, alpha=0.1, max_iter=100, batch_size=3, random_state=rng\n)\nbatch_pca_estimator.fit(faces_centered)\nplot_gallery(\n    \"Sparse components - MiniBatchSparsePCA\",\n    batch_pca_estimator.components_[:n_components],\n)"
       ]
     },
     {
@@ -166,7 +166,7 @@
       },
       "outputs": [],
       "source": [
-        "batch_dict_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components, alpha=0.1, n_iter=50, batch_size=3, random_state=rng\n)\nbatch_dict_estimator.fit(faces_centered)\nplot_gallery(\"Dictionary learning\", batch_dict_estimator.components_[:n_components])"
+        "batch_dict_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components, alpha=0.1, max_iter=50, batch_size=3, random_state=rng\n)\nbatch_dict_estimator.fit(faces_centered)\nplot_gallery(\"Dictionary learning\", batch_dict_estimator.components_[:n_components])"
       ]
     },
     {
@@ -252,7 +252,7 @@
       },
       "outputs": [],
       "source": [
-        "dict_pos_dict_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    n_iter=50,\n    batch_size=3,\n    random_state=rng,\n    positive_dict=True,\n)\ndict_pos_dict_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive dictionary\",\n    dict_pos_dict_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
+        "dict_pos_dict_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    max_iter=50,\n    batch_size=3,\n    random_state=rng,\n    positive_dict=True,\n)\ndict_pos_dict_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive dictionary\",\n    dict_pos_dict_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
       ]
     },
     {
@@ -270,7 +270,7 @@
       },
       "outputs": [],
       "source": [
-        "dict_pos_code_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    n_iter=50,\n    batch_size=3,\n    fit_algorithm=\"cd\",\n    random_state=rng,\n    positive_code=True,\n)\ndict_pos_code_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive code\",\n    dict_pos_code_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
+        "dict_pos_code_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    max_iter=50,\n    batch_size=3,\n    fit_algorithm=\"cd\",\n    random_state=rng,\n    positive_code=True,\n)\ndict_pos_code_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive code\",\n    dict_pos_code_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
       ]
     },
     {
@@ -288,7 +288,7 @@
       },
       "outputs": [],
       "source": [
-        "dict_pos_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    n_iter=50,\n    batch_size=3,\n    fit_algorithm=\"cd\",\n    random_state=rng,\n    positive_dict=True,\n    positive_code=True,\n)\ndict_pos_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive dictionary & code\",\n    dict_pos_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
+        "dict_pos_estimator = decomposition.MiniBatchDictionaryLearning(\n    n_components=n_components,\n    alpha=0.1,\n    max_iter=50,\n    batch_size=3,\n    fit_algorithm=\"cd\",\n    random_state=rng,\n    positive_dict=True,\n    positive_code=True,\n)\ndict_pos_estimator.fit(faces_centered)\nplot_gallery(\n    \"Dictionary learning - positive dictionary & code\",\n    dict_pos_estimator.components_[:n_components],\n    cmap=plt.cm.RdBu,\n)"
       ]
     }
   ],