#!/usr/bin/env python3

"""analyze-kconfig - Generate a model for KConfig selections

analyze-kconfig builds a model determining system attributes
(e.g. ROM or RAM usage) based on KConfig configuration variables.
Only boolean variables are supported at the moment.
"""

import argparse
import json
import kconfiglib
import logging
import os

from dfatool.loader import KConfigAttributes
from dfatool.model import KConfigModel


def main():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.RawDescriptionHelpFormatter, description=__doc__
    )
    parser.add_argument(
        "--export-tree",
        type=str,
        help="Export decision tree model to file",
        metavar="FILE",
    )
    parser.add_argument(
        "--config",
        type=str,
        help="Show model results for symbols in .config file",
        metavar="FILE",
    )
    parser.add_argument(
        "--attribute", choices=["rom", "ram"], default="rom", help="Model attribute"
    )
    parser.add_argument(
        "--max-stddev",
        type=float,
        help="Maximum acceptable model standard deviation for DecisionTree Leaves",
        default=10,
    )
    parser.add_argument(
        "--log-level",
        default=logging.INFO,
        type=lambda level: getattr(logging, level.upper()),
        help="Set log level",
    )
    parser.add_argument("kconfig_path", type=str, help="Path to Kconfig file")
    parser.add_argument(
        "model",
        type=str,
        help="Path to experiment results directory or model.json file",
    )

    args = parser.parse_args()

    if isinstance(args.log_level, int):
        logging.basicConfig(level=args.log_level)
    else:
        print(f"Invalid log level. Setting log level to INFO.", file=sys.stderr)

    if os.path.isdir(args.model):
        data = KConfigAttributes(args.kconfig_path, args.model)
        model = KConfigModel.from_benchmark(data, args.attribute)
        if args.max_stddev:
            model.max_stddev = args.max_stddev
        model.build_tree()

    else:
        with open(args.model, "r") as f:
            model = KConfigModel.from_json(json.load(f))

    if args.export_tree:
        with open(args.export_tree, "w") as f:
            json.dump(model.to_json(), f)

    if args.config:
        kconf = kconfiglib.Kconfig(args.kconfig_path)
        kconf.load_config(args.config)
        print(f"Model result for .config: {model.value_for_config(kconf)}")

        for symbol in model.symbols:
            kconf2 = kconfiglib.Kconfig(args.kconfig_path)
            kconf2.load_config(args.config)
            kconf_sym = kconf2.syms[symbol]
            if kconf_sym.tri_value == 0 and 2 in kconf_sym.assignable:
                kconf_sym.set_value(2)
            elif kconf_sym.tri_value == 2 and 0 in kconf_sym.assignable:
                kconf_sym.set_value(0)
            else:
                continue

            # specific to multipass:
            # Do not suggest changes which affect the application
            skip = False
            num_changes = 0
            changed_symbols = list()
            for i, csymbol in enumerate(model.symbols):
                if kconf.syms[csymbol].tri_value != kconf2.syms[csymbol].tri_value:
                    num_changes += 1
                    changed_symbols.append(csymbol)
                    if (
                        csymbol.startswith("app_")
                        and kconf.syms[csymbol].tri_value
                        != kconf2.syms[csymbol].tri_value
                    ):
                        skip = True
                        break
            if skip:
                continue

            try:
                model_diff = model.value_for_config(kconf2) - model.value_for_config(
                    kconf
                )
                if kconf_sym.choice:
                    print(
                        f"Setting {kconf_sym.choice.name} to {kconf_sym.name} changes {num_changes:2d} symbols, model change: {model_diff:+5.0f}"
                    )
                else:
                    print(
                        f"Setting {symbol} to {kconf_sym.str_value} changes {num_changes:2d} symbols, model change: {model_diff:+5.0f}"
                    )
            except TypeError:
                if kconf_sym.choice:
                    print(
                        f"Setting {kconf_sym.choice.name} to {kconf_sym.name} changes {num_changes:2d} symbols, model is undefined"
                    )
                else:
                    print(
                        f"Setting {symbol} to {kconf_sym.str_value} changes {num_changes:2d} symbols, model is undefined"
                    )
            for changed_symbol in changed_symbols:
                print(
                    f"    {changed_symbol:30s} -> {kconf2.syms[changed_symbol].str_value}"
                )


if __name__ == "__main__":
    main()