Fix download functionality with working CSV generation - Implement proper download functions that generate fresh CSV files - Use current parameter values to regenerate data for download - Create properly formatted CSV files with clean numeric data - Fix button click handlers to actually work - Update environment with correct Gradio version

README.md

@@ -25,11 +25,16 @@ This project implements a flexible, modular dashboard for mangrove carbon seques
 
 1. **Install dependencies:**
    ```bash
+   # Method 1: Using conda (recommended)
    conda env create -f environment.yml
    conda activate er-model
+   
+   # Method 2: Using pip in existing environment
+   pip install -r requirements.txt
    ```
 2. **Run the dashboard:**
    ```bash
+   conda activate er-model  # if using conda
    python dashboard/app.py
    ```
    The terminal will display a public share link.

dashboard/app.py

@@ -441,16 +441,20 @@ This dashboard visualizes these values annually over the project duration, provi
             with gr.Tabs():
                 with gr.Tab("Project Results (Annual)"):
                     results_box = gr.Dataframe(label="Project Results (Annual)")
-                    download_results_btn = gr.DownloadButton("📥 Download CSV", variant="secondary")
+                    download_results_file = gr.File(label="Download CSV", visible=False)
+                    download_results_btn = gr.Button("📥 Download CSV", variant="secondary")
                 with gr.Tab("Species Results (Annual)"):
                     species_box = gr.Dataframe(label="Species Results (Annual)")
-                    download_species_btn = gr.DownloadButton("📥 Download CSV", variant="secondary")
+                    download_species_file = gr.File(label="Download CSV", visible=False)
+                    download_species_btn = gr.Button("📥 Download CSV", variant="secondary")
                 with gr.Tab("Surviving Trees Table"):
                     survival_box = gr.Dataframe(label="Surviving Trees Table")
-                    download_survival_btn = gr.DownloadButton("📥 Download CSV", variant="secondary")
+                    download_survival_file = gr.File(label="Download CSV", visible=False)
+                    download_survival_btn = gr.Button("📥 Download CSV", variant="secondary")
                 with gr.Tab("Biomass Table"):
                     biomass_debug_table = gr.Dataframe(label="Biomass Table (inputs & outputs per year)")
-                    download_biomass_btn = gr.DownloadButton("📥 Download CSV", variant="secondary")
+                    download_biomass_file = gr.File(label="Download CSV", visible=False)
+                    download_biomass_btn = gr.Button("📥 Download CSV", variant="secondary")
             # --- End tabbed tables ---
             # Update the update_declining_increment callback to use these new inputs
             def update_declining_increment(y1, y2, y3, y4, y5,
@@ -491,12 +495,6 @@ This dashboard visualizes these values annually over the project duration, provi
                 survival_table = to_native(survival_table)
                 biomass_debug_df = to_native(biomass_debug_df)
                 
-                # Store raw data for downloads (before formatting)
-                update_declining_increment._last_results = results
-                update_declining_increment._last_species_results = species_results
-                update_declining_increment._last_survival_table = model.species_metrics.pivot(index="Year", columns="Species", values="Surviving Trees").reset_index()
-                update_declining_increment._last_biomass_table = model.species_metrics
-                
                 # --- Ensure all other values are native types ---
                 if hasattr(summary, 'item'):
                     summary = summary.item()
@@ -510,100 +508,170 @@ This dashboard visualizes these values annually over the project duration, provi
             )
 
             # Download functionality for tables
-            def download_results_csv():
-                if hasattr(update_declining_increment, '_last_results'):
-                    df = update_declining_increment._last_results.copy()
-                    # Remove formatting for CSV export
-                    for col in df.columns:
-                        if df[col].dtype == 'object':
+            def create_download_file(df, filename):
+                """Create a temporary CSV file for download"""
+                import tempfile
+                import os
+                
+                # Create a temporary file
+                temp_dir = tempfile.gettempdir()
+                filepath = os.path.join(temp_dir, filename)
+                
+                # Convert formatted strings back to numbers where possible
+                if df is not None and not df.empty:
+                    df_clean = df.copy()
+                    for col in df_clean.columns:
+                        if df_clean[col].dtype == 'object' and col.lower() != 'year':
                             try:
                                 # Try to convert formatted strings back to numbers
-                                df[col] = df[col].str.replace(',', '').astype(float)
+                                df_clean[col] = df_clean[col].astype(str).str.replace(',', '').astype(float)
                             except:
                                 pass  # Keep as string if conversion fails
                     
-                    temp_file = tempfile.NamedTemporaryFile(mode='w', suffix='.csv', delete=False)
-                    df.to_csv(temp_file.name, index=False)
-                    temp_file.close()
-                    return temp_file.name
+                    df_clean.to_csv(filepath, index=False)
+                    return filepath
                 return None
+            
+            def download_results_csv(y1, y2, y3, y4, y5, planting_density_A, planting_density_B, *mortality_inputs_and_soil_carbon):
+                """Generate and download project results CSV"""
+                try:
+                    # Recreate the results using current parameters
+                    *mortality_inputs, soil_carbon = mortality_inputs_and_soil_carbon
+                    config = update_planting_schedule(MODEL_CONFIGS["Declining Increment"], [y1, y2, y3, y4, y5])
+                    config['species'][0]['planting_density'] = planting_density_A
+                    config['species'][1]['planting_density'] = planting_density_B
+                    for i in [0, 1]:
+                        for yr_idx, yr in enumerate(range(1, 11)):
+                            config['species'][i]['mortality_rates'][f'year_{yr}'] = mortality_inputs[yr_idx]
+                        config['species'][i]['mortality_rates']['subsequent'] = mortality_inputs[10]
+                    config['carbon']['soil_carbon_per_ha_per_year'] = soil_carbon
+                    
+                    with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as tmp:
+                        yaml.dump(config, tmp)
+                        tmp_path = tmp.name
+                    model = ERModel(Path(tmp_path))
+                    results, _ = model.run()
+                    
+                    filepath = create_download_file(results, "project_results.csv")
+                    return gr.File(value=filepath, visible=True) if filepath else gr.File(visible=False)
+                except Exception as e:
+                    print(f"Error creating download: {e}")
+                    return gr.File(visible=False)
                 
-            def download_species_csv():
-                if hasattr(update_declining_increment, '_last_species_results'):
-                    df = update_declining_increment._last_species_results.copy()
-                    # Remove formatting for CSV export
-                    for col in df.columns:
-                        if df[col].dtype == 'object':
-                            try:
-                                # Try to convert formatted strings back to numbers
-                                df[col] = df[col].str.replace(',', '').astype(float)
-                            except:
-                                pass  # Keep as string if conversion fails
+            def download_species_csv(y1, y2, y3, y4, y5, planting_density_A, planting_density_B, *mortality_inputs_and_soil_carbon):
+                """Generate and download species results CSV"""
+                try:
+                    *mortality_inputs, soil_carbon = mortality_inputs_and_soil_carbon
+                    config = update_planting_schedule(MODEL_CONFIGS["Declining Increment"], [y1, y2, y3, y4, y5])
+                    config['species'][0]['planting_density'] = planting_density_A
+                    config['species'][1]['planting_density'] = planting_density_B
+                    for i in [0, 1]:
+                        for yr_idx, yr in enumerate(range(1, 11)):
+                            config['species'][i]['mortality_rates'][f'year_{yr}'] = mortality_inputs[yr_idx]
+                        config['species'][i]['mortality_rates']['subsequent'] = mortality_inputs[10]
+                    config['carbon']['soil_carbon_per_ha_per_year'] = soil_carbon
                     
-                    temp_file = tempfile.NamedTemporaryFile(mode='w', suffix='.csv', delete=False)
-                    df.to_csv(temp_file.name, index=False)
-                    temp_file.close()
-                    return temp_file.name
-                return None
+                    with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as tmp:
+                        yaml.dump(config, tmp)
+                        tmp_path = tmp.name
+                    model = ERModel(Path(tmp_path))
+                    _, species_results = model.run()
+                    
+                    filepath = create_download_file(species_results, "species_results.csv")
+                    return gr.File(value=filepath, visible=True) if filepath else gr.File(visible=False)
+                except Exception as e:
+                    print(f"Error creating download: {e}")
+                    return gr.File(visible=False)
                 
-            def download_survival_csv():
-                if hasattr(update_declining_increment, '_last_survival_table'):
-                    df = update_declining_increment._last_survival_table.copy()
-                    # Remove formatting for CSV export
-                    for col in df.columns:
-                        if df[col].dtype == 'object' and col != 'Year':
-                            try:
-                                # Try to convert formatted strings back to numbers
-                                df[col] = df[col].str.replace(',', '').astype(float)
-                            except:
-                                pass  # Keep as string if conversion fails
+            def download_survival_csv(y1, y2, y3, y4, y5, planting_density_A, planting_density_B, *mortality_inputs_and_soil_carbon):
+                """Generate and download survival table CSV"""
+                try:
+                    *mortality_inputs, soil_carbon = mortality_inputs_and_soil_carbon
+                    config = update_planting_schedule(MODEL_CONFIGS["Declining Increment"], [y1, y2, y3, y4, y5])
+                    config['species'][0]['planting_density'] = planting_density_A
+                    config['species'][1]['planting_density'] = planting_density_B
+                    for i in [0, 1]:
+                        for yr_idx, yr in enumerate(range(1, 11)):
+                            config['species'][i]['mortality_rates'][f'year_{yr}'] = mortality_inputs[yr_idx]
+                        config['species'][i]['mortality_rates']['subsequent'] = mortality_inputs[10]
+                    config['carbon']['soil_carbon_per_ha_per_year'] = soil_carbon
                     
-                    temp_file = tempfile.NamedTemporaryFile(mode='w', suffix='.csv', delete=False)
-                    df.to_csv(temp_file.name, index=False)
-                    temp_file.close()
-                    return temp_file.name
-                return None
+                    with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as tmp:
+                        yaml.dump(config, tmp)
+                        tmp_path = tmp.name
+                    model = ERModel(Path(tmp_path))
+                    model.run()
+                    survival_table = create_survival_table(model)
+                    
+                    # Convert survival table to raw numbers
+                    df_raw = model.species_metrics.copy()
+                    surv_raw = df_raw.pivot(index="Year", columns="Species", values="Surviving Trees")
+                    surv_raw.columns = [SPECIES_DISPLAY_NAMES.get(sp, sp) for sp in surv_raw.columns]
+                    surv_raw["Total Surviving Trees"] = surv_raw.sum(axis=1)
+                    surv_raw = surv_raw.reset_index()
+                    
+                    filepath = create_download_file(surv_raw, "surviving_trees.csv")
+                    return gr.File(value=filepath, visible=True) if filepath else gr.File(visible=False)
+                except Exception as e:
+                    print(f"Error creating download: {e}")
+                    return gr.File(visible=False)
                 
-            def download_biomass_csv():
-                if hasattr(update_declining_increment, '_last_biomass_table'):
-                    df = update_declining_increment._last_biomass_table.copy()
-                    # Remove formatting for CSV export - this table has complex column names
-                    for col in df.columns:
-                        if df[col].dtype == 'object':
-                            try:
-                                # Try to convert formatted strings back to numbers
-                                df[col] = df[col].str.replace(',', '').astype(float)
-                            except:
-                                pass  # Keep as string if conversion fails
+            def download_biomass_csv(y1, y2, y3, y4, y5, planting_density_A, planting_density_B, *mortality_inputs_and_soil_carbon):
+                """Generate and download biomass table CSV"""
+                try:
+                    *mortality_inputs, soil_carbon = mortality_inputs_and_soil_carbon
+                    config = update_planting_schedule(MODEL_CONFIGS["Declining Increment"], [y1, y2, y3, y4, y5])
+                    config['species'][0]['planting_density'] = planting_density_A
+                    config['species'][1]['planting_density'] = planting_density_B
+                    for i in [0, 1]:
+                        for yr_idx, yr in enumerate(range(1, 11)):
+                            config['species'][i]['mortality_rates'][f'year_{yr}'] = mortality_inputs[yr_idx]
+                        config['species'][i]['mortality_rates']['subsequent'] = mortality_inputs[10]
+                    config['carbon']['soil_carbon_per_ha_per_year'] = soil_carbon
                     
-                    temp_file = tempfile.NamedTemporaryFile(mode='w', suffix='.csv', delete=False)
-                    df.to_csv(temp_file.name, index=False)
-                    temp_file.close()
-                    return temp_file.name
-                return None
+                    with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as tmp:
+                        yaml.dump(config, tmp)
+                        tmp_path = tmp.name
+                    model = ERModel(Path(tmp_path))
+                    model.run()
+                    
+                    filepath = create_download_file(model.species_metrics, "biomass_table.csv")
+                    return gr.File(value=filepath, visible=True) if filepath else gr.File(visible=False)
+                except Exception as e:
+                    print(f"Error creating download: {e}")
+                    return gr.File(visible=False)
             
+            # Connect download buttons to functions
             download_results_btn.click(
                 download_results_csv,
-                inputs=[],
-                outputs=[]
+                inputs=[year_1, year_2, year_3, year_4, year_5,
+                        planting_density_A, planting_density_B,
+                        *mort_vars, mort_sub, soil_carbon],
+                outputs=[download_results_file]
             )
             
             download_species_btn.click(
                 download_species_csv,
-                inputs=[],
-                outputs=[]
+                inputs=[year_1, year_2, year_3, year_4, year_5,
+                        planting_density_A, planting_density_B,
+                        *mort_vars, mort_sub, soil_carbon],
+                outputs=[download_species_file]
             )
             
             download_survival_btn.click(
                 download_survival_csv,
-                inputs=[],
-                outputs=[]
+                inputs=[year_1, year_2, year_3, year_4, year_5,
+                        planting_density_A, planting_density_B,
+                        *mort_vars, mort_sub, soil_carbon],
+                outputs=[download_survival_file]
             )
             
             download_biomass_btn.click(
                 download_biomass_csv,
-                inputs=[],
-                outputs=[]
+                inputs=[year_1, year_2, year_3, year_4, year_5,
+                        planting_density_A, planting_density_B,
+                        *mort_vars, mort_sub, soil_carbon],
+                outputs=[download_biomass_file]
             )
             
             # Show initial results

environment.yml

@@ -0,0 +1,16 @@
+name: er-model
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.10
+  - pip
+  - pip:
+    - click>=8.1.7
+    - gradio>=4.0.0
+    - matplotlib>=3.8.2
+    - numpy>=1.26.3
+    - pandas>=2.2.0
+    - plotly>=5.0.0
+    - pyyaml>=6.0.1
+    - scipy>=1.12.0 

requirements.txt

@@ -1,5 +1,5 @@
 click>=8.1.7
-gradio>=3.41.2
+gradio>=4.0.0
 matplotlib>=3.8.2
 numpy>=1.26.3
 pandas>=2.2.0