Switch dashboard to Gradio and update dependencies

configs/params.yaml

@@ -7,15 +7,20 @@ species:
       year_3: 6   # %
       year_4: 5   # %
       year_5: 5   # %
-      subsequent: 1.5  # %
+      year_6: 5   # %
+      year_7: 5   # %
+      year_8: 5   # %
+      year_9: 5   # %
+      year_10: 5  # %
+      subsequent: 1.5  # % (years 11-30)
     chapman_richards:
       dbh:
         a: 11.07  # asymptotic maximum DBH (cm)
-        b: 0.25   # growth rate parameter (yr^-1)
+        b: 0.1237   # growth rate parameter (yr^-1)
         c: 2.1    # shape parameter
       height:
         a: 12.0   # asymptotic maximum height (m)
-        b: 0.25   # growth rate parameter (yr^-1)
+        b: 0.1237   # growth rate parameter (yr^-1)
         c: 2.1    # shape parameter
     allometry:
       equation: "Zanvo et al. 2023: Total = 1.938 × (DBH² H)^0.67628"
@@ -31,15 +36,20 @@ species:
       year_3: 6   # %
       year_4: 5   # %
       year_5: 5   # %
-      subsequent: 1.5  # %
+      year_6: 5   # %
+      year_7: 5   # %
+      year_8: 5   # %
+      year_9: 5   # %
+      year_10: 5  # %
+      subsequent: 1.5  # % (years 11-30)
     chapman_richards:
       dbh:
         a: 17.0   # asymptotic maximum DBH (cm)
-        b: 0.25   # growth rate parameter (yr^-1)
+        b: 0.1237  # growth rate parameter (yr^-1)
         c: 2.1    # shape parameter
       height:
         a: 8.8    # asymptotic maximum height (m)
-        b: 0.25   # growth rate parameter (yr^-1)
+        b: 0.1237  # growth rate parameter (yr^-1)
         c: 2.1    # shape parameter
     allometry:
       equation: "Zanvo et al. 2023: Total = 1.486 × (DBH² H)^0.55864"
@@ -51,7 +61,7 @@ project:
   duration_years: 30  # matches project_years
   planting_schedule:
     year_1: 2500  # ha
-    year_2: 2000  # ha
+    year_2: 2500  # ha
     year_3: 0  # ha
     year_4: 0  # ha
     year_5: 0  # ha
@@ -59,7 +69,7 @@ project:
 carbon:
   biomass_to_carbon: 0.47  # IPCC default
   carbon_to_co2: 3.67     # molecular weight ratio
-  buffer_percentage: 15    # risk buffer
+  buffer_percentage: 20    # risk buffer
   leakage_percentage: 0    # no leakage assumed
   baseline_emissions: 0    # tCO2/ha/year
 

dashboard/app.py

@@ -69,55 +69,82 @@ def create_plots_and_tables(
     # Format y-axis with comma separator
     ax1.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: format_number(x)))
     
-    # Milestone years plot
-    milestones = [5, 10, 15, 20, 25, 30]
-    milestone_data = results[results["year"].isin(milestones)]
-    
+    # Annual ERs plot (replacing milestone years plot)
     fig2 = plt.figure(figsize=(10, 6))
     ax2 = fig2.add_subplot(111)
-    width = 0.35
-    x = np.arange(len(milestones))
-    ax2.bar(x - width/2, milestone_data["gross_carbon"], width, label="Gross Carbon")
-    ax2.bar(x + width/2, milestone_data["net_carbon"], width, label="Net Carbon")
-    ax2.set_xticks(x)
-    ax2.set_xticklabels(milestones)
+    
+    # Calculate annual ERs (year-over-year change in net carbon)
+    annual_ers = results["net_carbon"].diff()
+    annual_ers.iloc[0] = results["net_carbon"].iloc[0]  # First year is total, not difference
+    
+    # Plot annual ERs as bars
+    ax2.bar(results["year"], annual_ers, color='#2ecc71', alpha=0.7)
     ax2.set_xlabel("Year")
-    ax2.set_ylabel("Carbon (tCO2)")
-    ax2.set_title("Carbon Sequestration at Milestone Years")
-    ax2.legend()
+    ax2.set_ylabel("Annual ERs (tCO2)")
+    ax2.set_title("Annual Emission Reductions")
+    
     # Format y-axis with comma separator
     ax2.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: format_number(x)))
+    
+    # Add grid for better readability
+    ax2.grid(True, axis='y', linestyle='--', alpha=0.7)
+    
+    # Ensure integer ticks for years
+    ax2.xaxis.set_major_locator(plt.MaxNLocator(integer=True))
 
     # New biomass per tree plot
     fig3 = plt.figure(figsize=(10, 6))
     ax3 = fig3.add_subplot(111)
     
-    # Load config to get planting densities
+    # Load config to get growth parameters
     config = load_config()
-    rhiz_density = config["species"][0]["planting_density"]  # Rhizophora density
-    avic_density = config["species"][1]["planting_density"]  # Avicennia density
+    rhiz_params = config["species"][0]["chapman_richards"]
+    avic_params = config["species"][1]["chapman_richards"]
     
-    # Extract biomass per tree data from species_results
-    years = species_results.index
+    # Get initial values
+    rhiz_init = config["species"][0]["initial_values"]
+    avic_init = config["species"][1]["initial_values"]
     
-    # Get species column names (first two columns after 'Year' should be the species)
-    species_cols = [col for col in species_results.columns if 'tCO2' in col]
-    if len(species_cols) >= 2:
-        rhiz_col = species_cols[0]  # First species column
-        avic_col = species_cols[1]  # Second species column
-        
-        # Calculate biomass per tree using actual planting densities
-        rhiz_biomass = species_results[rhiz_col].astype(float) / (results["area_year_1"].iloc[0] * rhiz_density)
-        avic_biomass = species_results[avic_col].astype(float) / (results["area_year_1"].iloc[0] * avic_density)
-        
-        ax3.plot(years, rhiz_biomass, 'o-', color='#1f77b4', label='Rhizophora spp. - Total Biomass')
-        ax3.plot(years, avic_biomass, 'o-', color='#ff7f0e', label='Avicennia germinans - Total Biomass')
-        
-        ax3.set_xlabel("Year since planting")
-        ax3.set_ylabel("Biomass (tonnes per tree)")
-        ax3.set_title("Total Biomass per Tree")
-        ax3.grid(True)
-        ax3.legend()
+    # Create time series
+    years = np.arange(len(species_results))
+    
+    # Calculate DBH and height for each species over time
+    def chapman_richards(t, params, initial):
+        a, b, c = params["a"], params["b"], params["c"]
+        return initial + (a - initial) * (1 - np.exp(-b * t)) ** c
+    
+    # Calculate growth for Rhizophora
+    rhiz_dbh = chapman_richards(years, rhiz_params["dbh"], rhiz_init["dbh"])
+    rhiz_height = chapman_richards(years, rhiz_params["height"], rhiz_init["height"])
+    
+    # Calculate growth for Avicennia
+    avic_dbh = chapman_richards(years, avic_params["dbh"], avic_init["dbh"])
+    avic_height = chapman_richards(years, avic_params["height"], avic_init["height"])
+    
+    # Calculate biomass using Zanvo equations (convert kg to tonnes)
+    rhiz_biomass = 1.938 * (rhiz_dbh**2 * rhiz_height)**0.67628 / 1000  # Convert kg to tonnes
+    avic_biomass = 1.486 * (avic_dbh**2 * avic_height)**0.55864 / 1000  # Convert kg to tonnes
+    
+    # Plot with proper formatting
+    ax3.plot(years, rhiz_biomass, 'o-', color='#1f77b4', label='Rhizophora spp. - Total Biomass')
+    ax3.plot(years, avic_biomass, 'o-', color='#ff7f0e', label='Avicennia germinans - Total Biomass')
+    
+    ax3.set_xlabel("Year since planting")
+    ax3.set_ylabel("Biomass (tonnes per tree)")
+    ax3.set_title("Total Biomass per Tree")
+    ax3.grid(True)
+    ax3.legend()
+    
+    # Set proper axis limits
+    ax3.set_xlim(0, len(years)-1)
+    ax3.set_ylim(bottom=0)  # Start y-axis at 0
+    
+    # Format y-axis with comma separator
+    ax3.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: format_number(x)))
+    
+    # Ensure the plot is drawn
+    fig3.tight_layout()
+    plt.draw()
 
     # Calculate total area from planting schedule
     total_area = sum(float(v) for k, v in results.iloc[-1].items() if k.startswith("area_year"))
@@ -155,13 +182,26 @@ Net Carbon per ha: {format_number(net_carbon_per_ha)} tCO2/ha
     for col in species_table.select_dtypes(include=[np.number]).columns:
         species_table[col] = species_table[col].apply(format_number)
     
+    # Create annual ERs table
+    annual_results = pd.DataFrame({
+        'Year': results['year'],
+        'Annual ERs (tCO2)': annual_ers,
+        'Cumulative ERs (tCO2)': results['net_carbon'],
+        'Area Planted (ha)': results[[col for col in results.columns if col.startswith('area_year_')]].sum(axis=1),
+        'Cumulative Area (ha)': results[[col for col in results.columns if col.startswith('area_year_')]].cumsum().sum(axis=1)
+    })
+    
+    # Format annual results table with comma separators
+    for col in annual_results.select_dtypes(include=[np.number]).columns:
+        annual_results[col] = annual_results[col].apply(format_number)
+    
     # Format scenario comparison table with comma separators
     scenario_table = scenario_results.copy()
     scenario_table.index.name = "Scenario"
     for col in scenario_table.select_dtypes(include=[np.number]).columns:
         scenario_table[col] = scenario_table[col].apply(format_number)
     
-    return fig1, fig2, fig3, summary, species_table, scenario_table
+    return fig1, fig2, fig3, summary, annual_results, scenario_table
 
 
 def update_model(
@@ -353,7 +393,7 @@ def main():
         # Outputs
         with gr.Row():
             plot1 = gr.Plot(label="Carbon Sequestration Over Time")
-            plot2 = gr.Plot(label="Milestone Years")
+            plot2 = gr.Plot(label="Annual Emission Reductions")
         
         with gr.Row():
             plot3 = gr.Plot(label="Total Biomass per Tree")
@@ -362,8 +402,8 @@ def main():
         
         with gr.Row():
             species_table = gr.Dataframe(
-                label="Per Species Carbon Change & Cumulative Hectares",
-                headers=["Year", "Rhizophora tCO2", "Avicennia tCO2", "Total tCO2", "Cumulative ha", "tCO2/ha"]
+                label="Annual Emission Reductions",
+                headers=["Year", "Annual ERs (tCO2)", "Cumulative ERs (tCO2)", "Area Planted (ha)", "Cumulative Area (ha)"]
             )
             scenario_table = gr.Dataframe(
                 label="Scenario Comparison",

src/er_model.py

@@ -76,28 +76,46 @@ class ERModel:
         self.species_results: Optional[pd.DataFrame] = None
         self.scenario_results: Optional[pd.DataFrame] = None
         
-    def calculate_surviving_trees(self, initial_trees: float, year: int, 
-                                mortality_rates: Dict[str, float]) -> float:
+    def calculate_cohort_surviving_trees(self, planting_year: int, current_year: int, initial_trees: float, mortality_rates: Dict[str, float]) -> float:
         """
-        Calculate surviving trees for a given year based on mortality rates.
-        
-        Args:
-            initial_trees: Initial number of trees planted
-            year: Years since planting (1-based)
-            mortality_rates: Dictionary of mortality rates by year
-            
-        Returns:
-            Number of surviving trees
+        Calculate surviving trees for a cohort planted in planting_year, in current_year.
+        Applies cumulative mortality for the cohort's age.
         """
+        age = current_year - planting_year + 1
+        if age < 1:
+            return 0
         surviving = initial_trees
-        
-        for y in range(1, year + 1):
-            rate = mortality_rates.get(f"year_{y}", 
-                                    mortality_rates["subsequent"]) / 100.0
+        for y in range(1, age + 1):
+            rate = mortality_rates.get(f"year_{y}", mortality_rates["subsequent"]) / 100.0
             surviving *= (1 - rate)
-            
         return surviving
-    
+
+    def calculate_total_surviving_trees(self, year: int) -> Dict[str, float]:
+        """
+        Calculate total surviving trees for each species in a given year, summing across all cohorts.
+        Returns a dict: {species_name: total_surviving_trees}
+        """
+        totals = {}
+        for species in self.species:
+            total = 0
+            for planting_year, area in self.project.planting_schedule.items():
+                py = int(planting_year.split("_")[1])
+                initial_trees = species.planting_density * area
+                total += self.calculate_cohort_surviving_trees(py, year, initial_trees, species.mortality_rates)
+            totals[species.name] = total
+        return totals
+
+    def calculate_cumulative_area(self, year: int) -> float:
+        """
+        Calculate cumulative area planted up to and including the given year.
+        """
+        total = 0
+        for planting_year, area in self.project.planting_schedule.items():
+            py = int(planting_year.split("_")[1])
+            if py <= year:
+                total += area
+        return total
+
     def chapman_richards_growth(self, age: float, params: Dict[str, float], initial_value: float) -> float:
         """
         Calculate growth using Chapman-Richards growth equation.
@@ -116,21 +134,19 @@ class ERModel:
     def calculate_carbon_for_species(self, species: Species, age: int, area: float) -> float:
         """
         Calculate carbon sequestration for a single species and age.
-        
         Args:
             species: Species parameters
             age: Age of trees in years
             area: Planted area in hectares
-            
         Returns:
             Carbon sequestration in tCO2
         """
-        # Calculate surviving trees
+        # Calculate surviving trees using cumulative mortality for the given age
         initial_trees = species.planting_density * area
-        surviving = self.calculate_surviving_trees(
-            initial_trees, age, species.mortality_rates
-        )
-        
+        surviving = initial_trees
+        for y in range(1, age + 1):
+            rate = species.mortality_rates.get(f"year_{y}", species.mortality_rates["subsequent"]) / 100.0
+            surviving *= (1 - rate)
         # Calculate DBH and height using Chapman-Richards
         dbh = self.chapman_richards_growth(
             age, 
@@ -142,17 +158,14 @@ class ERModel:
             species.chapman_richards["height"],
             species.initial_values["height"]
         )
-        
         # Calculate biomass using both DBH and height
         biomass = calculate_biomass(dbh, height, species.name, species.allometry)
-        
         # Convert to carbon
         carbon = calculate_carbon(
             biomass * surviving,
             self.carbon.biomass_to_carbon,
             self.carbon.carbon_to_co2
         )
-        
         return carbon
     
     def run_scenario(self, area: float, dbh_range: List[float], height_range: List[float], 
@@ -224,24 +237,43 @@ class ERModel:
             year_results = {"year": year}
             species_year_results = {"Year": year}
             total_carbon = 0
-            cumulative_area = 0
+            cumulative_area = self.calculate_cumulative_area(year)
             
             # Calculate for each planting cohort and species
-            for planting_year, area in self.project.planting_schedule.items():
-                py = int(planting_year.split("_")[1])
-                if py > year:
-                    continue
-                
-                cumulative_area += area
-                age = year - py + 1
-                
-                for species in self.species:
-                    carbon = self.calculate_carbon_for_species(species, age, area)
-                    total_carbon += carbon
-                    
-                    # Track per-species carbon
-                    species_key = f"{species.name} tCO2"
-                    species_year_results[species_key] = species_year_results.get(species_key, 0) + carbon
+            for species in self.species:
+                species_carbon = 0
+                for planting_year, area in self.project.planting_schedule.items():
+                    py = int(planting_year.split("_")[1])
+                    initial_trees = species.planting_density * area
+                    age = year - py + 1
+                    if age < 1:
+                        continue
+                    # Calculate surviving trees for this cohort
+                    surviving = self.calculate_cohort_surviving_trees(py, year, initial_trees, species.mortality_rates)
+                    # Calculate DBH and height using Chapman-Richards
+                    dbh = self.chapman_richards_growth(
+                        age, 
+                        species.chapman_richards["dbh"],
+                        species.initial_values["dbh"]
+                    )
+                    height = self.chapman_richards_growth(
+                        age,
+                        species.chapman_richards["height"],
+                        species.initial_values["height"]
+                    )
+                    # Calculate biomass using both DBH and height
+                    biomass = calculate_biomass(dbh, height, species.name, species.allometry)
+                    # Convert to carbon
+                    carbon = calculate_carbon(
+                        biomass * surviving,
+                        self.carbon.biomass_to_carbon,
+                        self.carbon.carbon_to_co2
+                    )
+                    species_carbon += carbon
+                total_carbon += species_carbon
+                # Track per-species carbon
+                species_key = f"{species.name} tCO2"
+                species_year_results[species_key] = species_carbon
             
             # Add total carbon and area metrics
             species_year_results["Total tCO2"] = total_carbon
@@ -257,7 +289,7 @@ class ERModel:
             year_results.update({
                 "gross_carbon": gross_carbon,
                 "net_carbon": net_carbon,
-                f"area_year_{year}": area if f"year_{year}" in self.project.planting_schedule else 0
+                "cumulative_area": cumulative_area
             })
             
             results.append(year_results)