#%% uses the latest version of aggregated inputs to create the dictionary of costs
import json
import sys

import pandas as pd

from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from utils.data_utils import strip_unit_suffix

def pop_by_name(d: dict, name: str):
    """Pop a key from dict by resource name, ignoring the unit suffix."""
    key = next((k for k in d if strip_unit_suffix(k) == name), None)
    if key:
        d.pop(key)

# Which base methods are replaced by derived variants.
# Methods listed here must have derived entries added in create_sliders_inputs().
REPLACED_BY_DERIVED = {"Bio-char", "Enhanced weathering"}

# Which derived methods follow each base method (in order).
DERIVED_FROM = {
    "Bio-char": [
        "Bio-char - Forest biomass",
        "Bio-char - Non-forest biomass",
        "Bio-char - Unspecified biomass",
    ],
    "Enhanced weathering": [
        "Enhanced weathering - Basalt mineral",
        "Enhanced weathering - Olivine mineral",
        "Enhanced weathering - Wollastonite mineral",
        "Enhanced weathering - Unspecified mineral",
    ],
    "BioCCS with combustion": ["BioCCS with combustion & growing biomass"],
    "BioCCS with anaerobic digestion/fermentation": [
        "BioCCS with anaerobic digestion/fermentation & growing biomass"
    ],
}


def build_method_groups(df, cost_sliders):
    """Build the method_groups dict from the CSV Method group column + derivation rules above.
    Group and method order follows first appearance in inputs_aggregated.csv."""
    base_methods_per_group = {}
    for _, row in df.drop_duplicates(subset=["Implementation"]).iterrows():
        m, g = row["Implementation"], row["Method group"]
        base_methods_per_group.setdefault(g, [])
        if m not in base_methods_per_group[g]:
            base_methods_per_group[g].append(m)

    method_groups = {}
    for g, base_list in base_methods_per_group.items():
        methods = []
        for base in base_list:
            if base not in REPLACED_BY_DERIVED:
                methods.append(base)
            for derived in DERIVED_FROM.get(base, []):
                if derived in cost_sliders:
                    methods.append(derived)
        if methods:
            method_groups[g] = methods
    return method_groups


def build_secondary_resources(df, cost_sliders):
    """Build the full set of (method, resource) secondary pairs from the CSV
    'Is secondary' column, then propagate to derived methods via DERIVED_FROM."""
    # Base pairs from CSV
    base_secondary = set()
    for _, row in df[df["Is secondary"] == True].iterrows():
        base_secondary.add((row["Implementation"], row["Resource"]))

    # Expand to derived methods: derived methods inherit secondary resources from their base
    full_secondary = set(base_secondary)
    for base, deriveds in DERIVED_FROM.items():
        base_resources_secondary = {r for (m, r) in base_secondary if m == base}
        for derived in deriveds:
            if derived in cost_sliders:
                for r in base_resources_secondary:
                    full_secondary.add((derived, r))

    return full_secondary


def create_sliders_inputs():
    df = pd.read_csv("data/inputs_aggregated.csv")

    cost_sliders = {}

    # Build cost_sliders from CSV: one entry per (method, resource) row.
    # Bio-char, Enhanced weathering and BioCCS variants are derived below.
    for _, row in df.iterrows():
        method = row["Implementation"]
        resource = row["Resource"] + " (" + row["Unit"] + ")"
        if row["min"] == row["max"] and row["Resource"] != "Geologic storage":
            row["min"] = row["min"] * .5
        entry = {
            "min": float(row["min"]),
            "median": float(row["median"]),
            "max": float(row["max"])
        }
        cost_sliders.setdefault(method, {})[resource] = entry

    # ── Derived methods ───────────────────────────────────────────────────────
    # Bio-char: split into 3 biomass-specific variants, remove generic base
    cost_sliders["Bio-char - Forest biomass"] = cost_sliders["Bio-char"].copy()
    pop_by_name(cost_sliders["Bio-char - Forest biomass"], "Non-forest biomass")
    pop_by_name(cost_sliders["Bio-char - Forest biomass"], "Unspecified biomass")
    cost_sliders["Bio-char - Non-forest biomass"] = cost_sliders["Bio-char"].copy()
    pop_by_name(cost_sliders["Bio-char - Non-forest biomass"], "Forest biomass")
    pop_by_name(cost_sliders["Bio-char - Non-forest biomass"], "Unspecified biomass")
    cost_sliders["Bio-char - Unspecified biomass"] = cost_sliders["Bio-char"].copy()
    pop_by_name(cost_sliders["Bio-char - Unspecified biomass"], "Forest biomass")
    pop_by_name(cost_sliders["Bio-char - Unspecified biomass"], "Non-forest biomass")
    del cost_sliders["Bio-char"]

    # Enhanced weathering: split into 4 mineral-specific variants, remove generic base
    cost_sliders["Enhanced weathering - Basalt mineral"] = cost_sliders["Enhanced weathering"].copy()
    pop_by_name(cost_sliders["Enhanced weathering - Basalt mineral"], "Olivine mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Basalt mineral"], "Wollastonite mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Basalt mineral"], "Unspecified mineral")
    cost_sliders["Enhanced weathering - Olivine mineral"] = cost_sliders["Enhanced weathering"].copy()
    pop_by_name(cost_sliders["Enhanced weathering - Olivine mineral"], "Basalt mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Olivine mineral"], "Wollastonite mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Olivine mineral"], "Unspecified mineral")
    cost_sliders["Enhanced weathering - Wollastonite mineral"] = cost_sliders["Enhanced weathering"].copy()
    pop_by_name(cost_sliders["Enhanced weathering - Wollastonite mineral"], "Basalt mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Wollastonite mineral"], "Olivine mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Wollastonite mineral"], "Unspecified mineral")
    cost_sliders["Enhanced weathering - Unspecified mineral"] = cost_sliders["Enhanced weathering"].copy()
    pop_by_name(cost_sliders["Enhanced weathering - Unspecified mineral"], "Basalt mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Unspecified mineral"], "Olivine mineral")
    pop_by_name(cost_sliders["Enhanced weathering - Unspecified mineral"], "Wollastonite mineral")
    del cost_sliders["Enhanced weathering"]

    # BioCCS: add growing-biomass variants alongside their base methods
    cost_sliders["BioCCS with combustion & growing biomass"] = cost_sliders["BioCCS with combustion"].copy()
    pop_by_name(cost_sliders["BioCCS with combustion"], "Arable land")
    pop_by_name(cost_sliders["BioCCS with combustion & growing biomass"], "Forest biomass")
    pop_by_name(cost_sliders["BioCCS with combustion & growing biomass"], "Unspecified biomass")

    cost_sliders["BioCCS with anaerobic digestion/fermentation & growing biomass"] = cost_sliders["BioCCS with anaerobic digestion/fermentation"].copy()
    pop_by_name(cost_sliders["BioCCS with anaerobic digestion/fermentation"], "Arable land")
    pop_by_name(cost_sliders["BioCCS with anaerobic digestion/fermentation & growing biomass"], "Non-forest biomass")
    pop_by_name(cost_sliders["BioCCS with anaerobic digestion/fermentation & growing biomass"], "Unspecified biomass")

    # ── Save outputs ──────────────────────────────────────────────────────────
    with open("data/cost_sliders.json", "w") as f:
        json.dump(cost_sliders, f, indent=2)
    print("Saved cost_sliders.json")

    method_groups = build_method_groups(df, cost_sliders)
    with open("data/method_groups.json", "w") as f:
        json.dump(method_groups, f, indent=2)
    print("Saved method_groups.json")

    secondary_resources = build_secondary_resources(df, cost_sliders)
    with open("data/secondary_resources.json", "w") as f:
        json.dump(sorted(secondary_resources), f, indent=2)
    print(f"Saved secondary_resources.json ({len(secondary_resources)} pairs)")

if __name__ == "__main__":
    create_sliders_inputs()
    print("Script executed successfully.")
# %%