beter clusters and qol

apps/cluster_map/ui_components.py

@@ -7,7 +7,8 @@ import numpy as np
 from config import (
     APP_TITLE, APP_ICON, APP_LAYOUT, METHOD_EXPLANATIONS,
     CLUSTERING_METHODS_REQUIRING_N_CLUSTERS, COMPUTATIONALLY_INTENSIVE_METHODS,
-    LARGE_DATASET_WARNING_THRESHOLD, MAX_DISPLAYED_AUTHORS
+    LARGE_DATASET_WARNING_THRESHOLD, MAX_DISPLAYED_AUTHORS,
+    DEFAULT_DIMENSION_REDUCTION_METHOD, DEFAULT_CLUSTERING_METHOD
 )
 
 
@@ -38,17 +39,23 @@ def create_method_controls():
     )
     
     # Dimension reduction method
+    method_options = ["PCA", "t-SNE", "UMAP", "Spectral Embedding", "Force-Directed"]
+    default_index = method_options.index(DEFAULT_DIMENSION_REDUCTION_METHOD) if DEFAULT_DIMENSION_REDUCTION_METHOD in method_options else 0
     method = st.sidebar.selectbox(
         "Dimension Reduction Method",
-        ["PCA", "t-SNE", "UMAP", "Spectral Embedding", "Force-Directed"],
+        method_options,
+        index=default_index,
         help="PCA is fastest, UMAP balances speed and quality, t-SNE and Spectral are slower but may reveal better structures. Force-Directed creates natural spacing."
     )
     
     # Clustering method
+    clustering_options = ["None", "HDBSCAN", "Spectral Clustering", "Gaussian Mixture", 
+                         "Agglomerative (Ward)", "Agglomerative (Complete)", "OPTICS"]
+    clustering_default_index = clustering_options.index(DEFAULT_CLUSTERING_METHOD) if DEFAULT_CLUSTERING_METHOD in clustering_options else 0
     clustering_method = st.sidebar.selectbox(
         "Clustering Method",
-        ["None", "HDBSCAN", "Spectral Clustering", "Gaussian Mixture", 
-         "Agglomerative (Ward)", "Agglomerative (Complete)", "OPTICS"],
+        clustering_options,
+        index=clustering_default_index,
         help="Apply clustering to identify groups. HDBSCAN and OPTICS can find variable density clusters."
     )
     
@@ -57,9 +64,25 @@ def create_method_controls():
 
 def create_clustering_controls(clustering_method):
     """Create controls for clustering parameters"""
-    n_clusters = 5
+    # Always show the clusters slider, but indicate when it's used
     if clustering_method in CLUSTERING_METHODS_REQUIRING_N_CLUSTERS:
-        n_clusters = st.sidebar.slider("Number of Clusters", 2, 15, 5)
+        help_text = "Number of clusters to create. This setting affects the clustering algorithm."
+        disabled = False
+    elif clustering_method == "None":
+        help_text = "Clustering is disabled. This setting has no effect."
+        disabled = True
+    else:
+        help_text = f"{clustering_method} automatically determines the number of clusters. This setting has no effect."
+        disabled = True
+    
+    n_clusters = st.sidebar.slider(
+        "Number of Clusters", 
+        min_value=2, 
+        max_value=20, 
+        value=5,
+        disabled=disabled,
+        help=help_text
+    )
     
     return n_clusters