change banner text and adjust v and t default settings

src/app.py

@@ -11,13 +11,25 @@ import utils
 
 # Function to create input select widgets
 def create_param_selectors(model_name: str, model_num: int = 1):
-    
+
     d_config = model_config[model_name]
     params = d_config["params"]
     param_bounds_low = d_config["param_bounds"][0]
     param_bounds_high = d_config["param_bounds"][1]
     param_defaults = d_config["default_params"]
 
+    # fix some specific parameters to
+    # custom defaults for better / more interesting 
+    # default visuals
+
+    if "v" in params:
+        v_index = params.index("v")
+        param_defaults[v_index] = 0.5
+
+    if "t" in params:
+        t_index = params.index("t")
+        param_defaults[t_index] = 0.2
+
     d_param_slider = {}
     for i, (name, low, high, default) in enumerate(
         zip(
@@ -56,23 +68,23 @@ def create_styling_selectors(model_num: int = 1):
     Returns:
         dict: Dictionary containing all styling parameters with their user-selected values
     """
-    
+
     # Color options for different plot elements
     color_options = ["blue", "red", "green", "orange", "purple", "black", "gray", "brown"]
-    
+
     # Legend location options (matplotlib standard locations)
     legend_locations = ["upper right", "upper left", "lower left", "lower right", 
                         "center", "upper center", "lower center", "center left", "center right"]
-    
+
     # Marker type options for trajectories
     marker_options = { "Diamond": "D", "Square": "s", "Line": 0, "Circle": "o", "Star": "*",  "Triangle": "^",
                      "Plus": "+", "X": "x"}
-    
+
     styling_config = {}
-    
+
     # Create an expander for styling options to keep the interface clean
     with st.expander(f"🎨 Styling", expanded=False):
-        
+
         # Color Settings Section
         st.markdown("**Colors**")
         styling_config["data_color"] = st.selectbox(
@@ -81,14 +93,14 @@ def create_styling_selectors(model_num: int = 1):
             index=color_options.index("blue" if model_num == 1 else "red"),
             key=f"data_color_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         styling_config["posterior_uncertainty_color"] = st.selectbox(
             "Model Color", 
             color_options,
             index=color_options.index("black"),
             key=f"model_color_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         # Line Width Settings Section
         st.markdown("**Lines**")
         styling_config["linewidth_histogram"] = st.slider(
@@ -99,7 +111,7 @@ def create_styling_selectors(model_num: int = 1):
             step=0.1,
             key=f"hist_lw_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         styling_config["linewidth_model"] = st.slider(
             "Model Line Width",
             min_value=0.1,
@@ -108,7 +120,7 @@ def create_styling_selectors(model_num: int = 1):
             step=0.1,
             key=f"model_lw_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         # Histogram Settings Section
         st.markdown("**Histograms**")
         styling_config["bin_size"] = st.slider(
@@ -119,7 +131,7 @@ def create_styling_selectors(model_num: int = 1):
             step=0.01,
             key=f"bin_size_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         styling_config["alpha"] = st.slider(
             "alpha",
             min_value=0.0,
@@ -128,7 +140,7 @@ def create_styling_selectors(model_num: int = 1):
             step=0.05,
             key=f"alpha_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         # Model Components Section - Toggle which parts of the model to show
         st.markdown("**Model Components**")
         styling_config["add_data_model_keep_boundary"] = st.checkbox(
@@ -141,7 +153,7 @@ def create_styling_selectors(model_num: int = 1):
             value=True,
             key=f"show_slope_{model_num}_{st.session_state['styling_version']}"
         )
-        
+
         styling_config["add_data_model_keep_ndt"] = st.checkbox(
             "Show Non-Decision Time", 
             value=True,
@@ -419,8 +431,7 @@ st.markdown("""
 <div style='background-color: #f0f2f6; padding: 15px; border-radius: 10px; margin: 20px 0; border-left: 5px solid #1f77b4;'>
     <p style='margin: 0; font-size: 16px;'>
         <strong>📊 Fit to your own data</strong><br>
-        This dashboard provides interactive visualization of Sequential Sampling Models. 
-        To fit these models to your own data, checkout the <a href='https://github.com/lnccbrown/HSSM' target='_blank' style='color: #1f77b4; text-decoration: none;'><strong>HSSM</strong></a> toolbox.
+        This dashboard provides interactive visualization of several Sequential Sampling Models available for fitting to data in the <a href='https://github.com/lnccbrown/HSSM' target='_blank' style='color: #1f77b4; text-decoration: none;'><strong>HSSM</strong></a> toolbox.
     </p>
 </div>
 """, unsafe_allow_html=True)