[FEAT] Possibility to choose between running the optimization with manually entered values or by adding a pre-existing scenario (JSON) -> in this case, the values are automatically populated in all other input tabs

data/cost_sliders.json

@@ -67,7 +67,7 @@
       "max": 1296342.17
     }
   },
-  "Coastal revegetation (mangrove, seaweeds\u2026)": {
+  "Coastal revegetation (mangrove, seaweeds)": {
     "Non-arable land (ha/tCO2)": {
       "min": 0.0078,
       "median": 0.12056618,

tabs/tab1_inputs.py

@@ -14,7 +14,6 @@ def render_tab():
     for r in resource_order:
         if r not in st.session_state.resource_caps:
             st.session_state.resource_caps[r] = 0.0
-
     st.header("Resource inputs")
 
     st.info("""
@@ -28,6 +27,7 @@ def render_tab():
     # Reset button
     st.markdown("### Controls")
     col_reset, _ = st.columns([1, 5])
+
     with col_reset:
         if st.button("🔄 Reset All", type="secondary"):
             for r in st.session_state.resource_caps:
@@ -35,6 +35,51 @@ def render_tab():
             st.success("All resource values reset to 0.")
             st.rerun()
 
+    # Dowload template
+    st.markdown("**Import resource values**")
+    col_template, col_upload = st.columns([1, 1])
+    with col_template:
+        st.markdown("Use the template below to fill in your resource availability values and import them directly into the tool.")
+        with open("data/resource_template.xlsx", "rb") as f:
+            st.download_button(
+                label="📥 Download Excel Template",
+                data=f,
+                file_name="resource_template.xlsx",
+                use_container_width= True,
+                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+            )
+    with col_upload:
+        uploaded_file = st.file_uploader("Upload your Excel file", type="xlsx")
+        if uploaded_file is not None:
+            try:
+                df = pd.read_excel(uploaded_file)
+                required_cols = {"Resource", "Available Amount"}
+                if not required_cols.issubset(df.columns):
+                    raise ValueError(f"Missing columns: {required_cols - set(df.columns)}")
+                for _, row in df.iterrows():
+                    r = row["Resource"]
+                    val = row["Available Amount"]
+                    if r not in st.session_state.resource_caps:
+                        continue
+                    if pd.isna(val):
+                        continue
+                    try:
+                        val = float(val)
+                    except (ValueError, TypeError):
+                        continue
+                    if val == 0:
+                        continue
+                    st.session_state.resource_caps[r] = val
+                st.success(f"Resource values imported successfully.", icon="✅")
+
+                for r, v in st.session_state.resource_caps.items():
+                    st.session_state[f"cap_{r}"] = v
+
+            except Exception as e:
+                st.error(f"Error importing resource values: {e}")
+            
+    col_reset, _ = st.columns([1, 5])
+
     # Inputs by resource group
     st.markdown("### Set available resources for one year")
     for group, rlist in resource_groups.items():

tabs/tab3_coefficients.py

@@ -10,7 +10,7 @@ def render_tab(cost_sliders):
     st.header("Resource efficiency coefficients")
 
     # === Initialization ===
-    if "costs" not in st.session_state:
+    if "costs" not in st.session_state or st.session_state.costs == {}:
         st.session_state.costs = {
             m: {
                 r: (0.0 if (m, r) in secondary_resources else cost_sliders[m][r]["median"])

tabs/tab4_optimization.py

@@ -11,6 +11,7 @@ import streamlit as st
 from config.config import method_order, resource_order, resource_units
 from optimization.optimization import run_optimization
 from utils.ui_helpers import format_results_summary
+from utils.data_utils import is_valid_scenario
 
 
 def render_tab():
@@ -22,59 +23,83 @@ def render_tab():
     Run the optimization tool, explore results, and save scenarios for comparison or export.
     """)
 
-    # Validate necessary inputs
-    if "constraints" not in st.session_state or "costs" not in st.session_state or "resource_caps" not in st.session_state:
-        st.error("Missing inputs. Please complete previous steps.")
-        return
-
+    # Initialize necessary session state variables if they don't exist
+    if "resource_caps" not in st.session_state:
+        st.session_state.resource_caps = {}
+    if "constraints" not in st.session_state:
+        st.session_state.constraints = {}
+    if "costs" not in st.session_state:
+        st.session_state.costs = {}
     if "scenarios" not in st.session_state:
         st.session_state.scenarios = {}
-
-    if sum(st.session_state.resource_caps.values()) <= 0:
-        st.warning("\u26a0\ufe0f All resources are currently set to 0. Please increase availability.")
-        return
-
+    
     # Run optimization
-    if st.button("Run Optimization"):
-        success, result = run_optimization(
-            resource_caps=st.session_state.resource_caps,
-            method_constraints=st.session_state.constraints,
-            method_costs=st.session_state.costs,
-        )
-
-        if success:
-            allocations = result["method_usage"]
-            total_removed = result["total_removed"]
-
-            if total_removed <= 0:
-                st.warning("\u274c Optimization removed 0 tCO₂. Relax constraints or increase resources.")
-                return
-
-            total_cost = sum(
-                allocations[m] * sum(st.session_state.costs[m].values())
-                for m in allocations
-            )
-
-            st.session_state.latest_result = {
-                "summary": {
-                    "total_co2_removed": total_removed,
-                    "total_cost": total_cost
-                },
-                "allocations": allocations,
-                "resource_caps": st.session_state.resource_caps.copy(),
-                "method_constraints": st.session_state.constraints,
-                "method_costs": st.session_state.costs,
-            }
-
-            st.success(f"\u2705 Optimization successful: {total_removed:,.0f} tCO₂ removed")
+    st.markdown("### Run optimization")
+    col_run, col_load = st.columns(2)
+
+    with col_run:
+        st.markdown("**From current input values**")
+        run_clicked = st.button("▶️ Run Optimization", use_container_width=False)
+
+    with col_load:
+        st.markdown("**From a saved JSON scenario**")
+        uploaded_scenario = st.file_uploader("Upload a saved JSON scenario", type="json", key="scenario_loader")
+        if uploaded_scenario is not None:
+            try:
+                data = json.load(uploaded_scenario)
+                if is_valid_scenario(data):
+                    if st.button("↩️ Reload this scenario into all tabs", use_container_width=True):
+                        st.session_state.resource_caps = data["resource_caps"].copy()
+                        st.session_state.constraints = data["method_constraints"].copy()
+                        st.session_state.costs = data["method_costs"].copy()
+                        keys_to_delete = [k for k in st.session_state if any(
+                            k.startswith(prefix) for prefix in ["slider_", "manual_", "toggle_"]
+                        )]
+                        for k in keys_to_delete:
+                            del st.session_state[k]
+                        st.session_state.latest_result = data
+                        st.success("Scenario loaded. All tabs have been updated.")
+                        st.rerun()
+                else:
+                    st.error("Invalid scenario format.")
+            except Exception as e:
+                st.error(f"Error loading scenario: {e}")
+
+    # Vérifications et exécution — uniquement si Run Optimization cliqué
+    if run_clicked:
+        if sum(st.session_state.resource_caps.values()) <= 0:
+            st.warning("⚠️ All resources are currently set to 0. Please increase availability or load a saved scenario.")
         else:
-            st.error("\u274c Optimization failed")
-            if "message" in result:
-                st.error(result["message"])
+            success, result = run_optimization(
+                resource_caps=st.session_state.resource_caps,
+                method_constraints=st.session_state.constraints,
+                method_costs=st.session_state.costs,
+            )
+            if success:
+                allocations = result["method_usage"]
+                total_removed = result["total_removed"]
+                if total_removed <= 0:
+                    st.warning("❌ Optimization removed 0 tCO₂. Relax constraints or increase resources.")
+                else:
+                    total_cost = sum(
+                        allocations[m] * sum(st.session_state.costs[m].values())
+                        for m in allocations
+                    )
+                    st.session_state.latest_result = {
+                        "summary": {"total_co2_removed": total_removed, "total_cost": total_cost},
+                        "allocations": allocations,
+                        "resource_caps": st.session_state.resource_caps.copy(),
+                        "method_constraints": st.session_state.constraints,
+                        "method_costs": st.session_state.costs,
+                    }
+                    st.success(f"✅ Optimization successful: {total_removed:,.0f} tCO₂ removed")
+            else:
+                st.error("❌ Optimization failed")
+                if "message" in result:
+                    st.error(result["message"])
 
     if "latest_result" not in st.session_state:
         return
-
     latest = st.session_state.latest_result
     allocations = latest["allocations"]
     resource_caps = latest["resource_caps"]

tabs/tab6_scenarios.py

@@ -4,17 +4,7 @@ import matplotlib.pyplot as plt
 import pandas as pd
 import seaborn as sns
 import streamlit as st
-
-
-def is_valid_scenario(scenario):
-    return (
-        isinstance(scenario, dict)
-        and "allocations" in scenario
-        and "resource_caps" in scenario
-        and "method_costs" in scenario
-        and "method_constraints" in scenario
-        and "summary" in scenario
-    )
+from utils.data_utils import is_valid_scenario
 
 def render_tab():
     st.header("Scenario Comparison")

utils/data_utils.py

@@ -1,5 +1,5 @@
 import json
-
+import pandas as pd
 import streamlit as st
 
 
@@ -19,14 +19,27 @@ def render_resource_input(name_clean, r, tooltip=None):
     else:
         st.markdown(f"**{name_clean}**")
 
-    if r not in st.session_state.resource_caps:
-        st.session_state.resource_caps[r] = 0.0
+    widget_key = f"cap_{r}"
+
+    if widget_key not in st.session_state:
+        st.session_state[widget_key] = st.session_state.resource_caps.get(r, 0.0)
 
     cap = st.number_input(
         label="label",
         label_visibility="collapsed",
         min_value=0.0,
         format="%.2f",
-        key=f"cap_{r}"
+        key=widget_key,
     )
+
     st.session_state.resource_caps[r] = cap
+
+def is_valid_scenario(scenario):
+    return (
+        isinstance(scenario, dict)
+        and "allocations" in scenario
+        and "resource_caps" in scenario
+        and "method_costs" in scenario
+        and "method_constraints" in scenario
+        and "summary" in scenario
+    )