fix: load bu number of clusters

src/services/vameApi/app/services/project_service.py

@@ -120,66 +120,79 @@ def load_project(project_path: Path):
             symlink.symlink_to(project_path)
 
     states_path = Path(project_path) / "states" / "states.json"
-
     states = json.load(open(states_path)) if os.path.exists(states_path) else None
-
     config = yaml.safe_load(open(config_path, "r")) if config_path.exists() else None
 
+    # Extract parameters from the config
+    parametrizations = config["parametrizations"]  # e.g., ["hmm", "kmeans"]
+    n_cluster = config["n_cluster"]  # e.g., 28
+
+    # Create the visualization dictionary dynamically
+    visualization = {
+        param: get_visualization_images(project_path, f"{param}-{n_cluster}")
+        for param in parametrizations
+    }
+
     images = dict(
         evaluation=get_evaluation_images(project_path),
-        visualization=dict(
-            hmm=get_visualization_images(project_path, 'hmm-15'),
-            kmeans=get_visualization_images(project_path, 'kmeans-15')
-        )
+        visualization=visualization
     )
 
-    videos = dict(
-        motif=dict(
-            hmm=get_motif_videos(project_path, 'hmm-15'),
-            kmeans=get_motif_videos(project_path, 'kmeans-15')
-        ),
-        community=dict(
-            hmm=get_community_videos(project_path, 'hmm-15'),
-            kmeans=get_community_videos(project_path, 'kmeans-15')
-        )
-    )
+    # Create the videos dictionary dynamically
+    videos = {
+        category: {
+            param: get_motif_videos(project_path, f"{param}-{n_cluster}")
+            for param in parametrizations
+        }
+        for category in ['motif', 'community']
+    }
 
     has_latent_vector_files = False
     if config:
-        has_latent_vector_files = all(map(lambda video: (get_video_results_path(video, project_path) / f"latent_vector_{video}.npy").exists(), config["video_sets"]))
+        has_latent_vector_files = all(
+            map(lambda video: (get_video_results_path(video, project_path) / f"latent_vector_{video}.npy").exists(), config["video_sets"])
+        )
 
     has_communities = (project_path / 'cohort_community_label.npy').exists()
 
     original_videos_location = project_path / 'videos'
     original_csvs_location = original_videos_location / 'pose_estimation'
 
     # Get all files in the original data directory
-    original_videos = list(map(lambda file: str(file), get_files(original_videos_location)))
-    original_csvs = list(map(lambda file: str(file), get_files(original_csvs_location)))
-
-    motif_videos_created_hmm=all(map(lambda videos: len(videos) > 0, videos["motif"]["hmm"].values()))
-    motif_videos_created_kmeans=all(map(lambda videos: len(videos) > 0, videos["motif"]["kmeans"].values()))
-
-    community_videos_created_hmm = all(map(lambda videos: len(videos) > 0, videos["community"]["kmeans"].values()))
-    community_videos_created_kmeans = all(map(lambda videos: len(videos) > 0, videos["community"]["hmm"].values()))
-
-    umaps_created_hmm = any(map(lambda videos: len(videos) > 0, images["visualization"]["hmm"].values()))
-
-    umaps_created_kmeans = any(map(lambda videos: len(videos) > 0, images["visualization"]["kmeans"].values()))
+    original_videos = list(map(str, get_files(original_videos_location)))
+    original_csvs = list(map(str, get_files(original_csvs_location)))
+
+    # Check if motif videos were created for each parametrization
+    motif_videos_created = {
+        param: all(map(lambda videos: len(videos) > 0, videos["motif"][param].values()))
+        for param in parametrizations
+    }
+
+    # Check if community videos were created for each parametrization
+    community_videos_created = {
+        param: all(map(lambda videos: len(videos) > 0, videos["community"][param].values()))
+        for param in parametrizations
+    }
+
+    # Check if UMAPs were created for each parametrization
+    umaps_created = {
+        param: any(map(lambda videos: len(videos) > 0, images["visualization"][param].values()))
+        for param in parametrizations
+    }
 
     pose_ref_index_description, ref_index_len = get_pose_ref_index_description(original_csvs[0])
 
     # Provide project workflow status
     workflow = dict(
-        organized = (project_path / 'data' / 'train').exists(),
+        organized=(project_path / 'data' / 'train').exists(),
         pose_ref_index_description=pose_ref_index_description,
         ref_index_len=ref_index_len,
-        modeled = len(images["evaluation"]) > 0,
-        segmented = has_latent_vector_files,
-        motif_videos_created=(lambda: motif_videos_created_hmm or motif_videos_created_kmeans)(),
+        modeled=len(images["evaluation"]) > 0,
+        segmented=has_latent_vector_files,
+        motif_videos_created=any(motif_videos_created.values()),
         communities_created=has_communities,
-        community_videos_created = (lambda: community_videos_created_hmm or community_videos_created_kmeans)(),
-        umaps_created = (lambda: umaps_created_hmm or umaps_created_kmeans)(),
+        community_videos_created=any(community_videos_created.values()),
+        umaps_created=any(umaps_created.values()),
     )
 
     return dict(
@@ -193,4 +206,4 @@ def load_project(project_path: Path):
         csvs=original_csvs,
         workflow=workflow,
         states=states
-    )
+    )