import pickle
from argparse import ArgumentParser
from dataclasses import dataclass
from math import isnan

import pandas as pd
from paperswithcode import PapersWithCodeClient
from paperswithcode.models import (
    EvaluationTableSyncRequest,
    MetricSyncRequest,
    ResultSyncRequest,
)


@dataclass
class Task:
    id: str
    name: str
    description: str
    area: str
    parent_task: str


_metrics = {"time": "training time (s)", "carbon_emission": "CO2 Emission (g)"}


def make_table(results_csv_list: list[str], metric: str):
    df_list = []
    for results_csv in results_csv_list:
        df = pd.read_csv(results_csv)
        columns = ["score"]
        if "time" in df.columns:
            columns.append("time")
        if "carbon_emission" in df.columns:
            columns.append("carbon_emission")
        df = (
            df.groupby(["dataset", "paradigm", "evaluation", "pipeline"])[columns]
            .mean()
            .reset_index()
        )
        df.score = df.score * 100
        columns = dict(**_metrics, score=metric)
        df.rename(columns=columns, inplace=True)
        df.paradigm = df.paradigm.replace(
            {"FilterBankMotorImagery": "MotorImagery", "LeftRightImagery": "MotorImagery"}
        )
        print(df.head())
        df_list.append(df)
    return pd.concat(df_list)


def upload_subtable(client, df, dataset, task, paper, evaluated_on):
    kwargs = {
        "task": task.id,
        "dataset": dataset.id,
        "description": task.description,
        "external_id": f"{dataset.id}-{task.id}",
        "mirror_url": "http://moabb.neurotechx.com/docs/benchmark_summary.html",
    }
    print(f"Uploading {kwargs=}")
    # client.evaluation_create(EvaluationTableCreateRequest(**kwargs))

    r = EvaluationTableSyncRequest(
        **kwargs,
        metrics=[
            MetricSyncRequest(name=metric, is_loss=metric in _metrics.values())
            for metric in df.columns
        ],
        results=[
            ResultSyncRequest(
                metrics={k: str(v) for k, v in row.to_dict().items() if not isnan(v)},
                paper=paper,
                methodology=pipeline,
                external_id=f"{dataset.id}-{task.id}-{pipeline}",
                evaluated_on=evaluated_on,
                # external_source_url="http://moabb.neurotechx.com/docs/benchmark_summary.html",
                # TODO: maybe update url with the exact row of the result
            )
            for pipeline, row in df.iterrows()
        ],
    )
    print(r)
    leaderboard_id = client.evaluation_synchronize(r)
    print(f"{leaderboard_id=}")
    return leaderboard_id


def upload_table(client, df, datasets, tasks, paper, evaluated_on, subsubtask):
    gp_cols = ["dataset", "paradigm", "evaluation"]
    df_gp = df.groupby(gp_cols)
    ids = []
    for (dataset_name, paradigm_name, evaluation_name), sub_df in df_gp:
        dataset = datasets[dataset_name]
        task_key = (paradigm_name, evaluation_name)
        if subsubtask is not None:
            task_key += (subsubtask,)
        task = tasks[task_key]
        id = upload_subtable(
            client,
            sub_df.set_index("pipeline").drop(
                columns=gp_cols
            ),  # + list(_metrics.values())),
            dataset,
            task,
            paper,
            evaluated_on,
        )
        ids.append(id)
    return ids


if __name__ == "__main__":
    parser = ArgumentParser()
    parser.add_argument("token", type=str, help="PapersWithCode API token")
    parser.add_argument(
        "metric",
        type=str,
        help="Metric used in the results CSV (see PapersWithCode metrics)",
    )
    parser.add_argument(
        "results_csv", type=str, help="CSV file with results to upload", nargs="+"
    )

    parser.add_argument(
        "-s",
        "--subsubtask",
        type=str,
        default=None,
        help="If relevant, the type of motor imagery task (see create_datasets_and_tasks.py)",
    )
    parser.add_argument(
        "-d",
        "--datasets",
        type=str,
        help="Pickle file created by create_datasets_and_tasks.py",
        default="paperswithcode_datasets_and_tasks.pickle",
    )
    parser.add_argument(
        "-o",
        "--output",
        type=str,
        help="Pickle output file",
        default="paperswithcode_results.pickle",
    )
    parser.add_argument("-p", "--paper", type=str, help="Paper URL", default="")
    parser.add_argument(
        "-e",
        "--evaluated_on",
        type=str,
        help="Results date YYYY-MM-DD",
        default="2024-04-09",
    )
    args = parser.parse_args()

    with open(args.datasets, "rb") as f:
        datasets = pickle.load(f)
    summary_table = make_table(args.results_csv, metric=args.metric)

    client = PapersWithCodeClient(token=args.token)

    upload_table(
        client,
        summary_table,
        datasets["datasets"],
        datasets["tasks"],
        args.paper,
        args.evaluated_on,
        args.subsubtask,
    )

# Commands used to upload the results of the benchmark paper:
# (generate a new API token, this one is expired)
# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_rf_Optuna.csv  -s="right hand vs. feet" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03
# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_lhrh_Optuna.csv  -s="left hand vs. right hand" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03
# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b Accuracy ../moabb_paper_plots/DATA/results_All_Optuna.csv  -s="all classes" -d paperswithcode_datasets_and_tasks2.pickle -o test_out.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03
# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b Accuracy ../moabb_paper_plots/DATA/results_SSVEP.csv ../moabb_paper_plots/DATA/results_SSVEP_DL.csv -d paperswithcode_datasets_and_tasks2.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03
# python scripts/paperswithcode/upload_results.py 5a4bd76b2b66908f0b8f28fb45dd41b918d3440b AUC-ROC ../moabb_paper_plots/DATA/results_P300.csv ../moabb_paper_plots/DATA/results_P300_DL.csv -d paperswithcode_datasets_and_tasks2.pickle -p "https://arxiv.org/abs/2404.15319v1" -e=2024-04-03