# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import pprint
import sys
# from collections import Mapping, OrderedDict
from collections import OrderedDict
from collections.abc import Mapping

import numpy as np
from tabulate import tabulate
from termcolor import colored


def print_csv_format(results):
    """
    Print main metrics in a format similar to Detectron2,
    so that they are easy to copypaste into a spreadsheet.
    Args:
        results (OrderedDict): {metric -> score}
    """
    # unordered results cannot be properly printed
    assert isinstance(results, OrderedDict) or not len(results), results
    logger = logging.getLogger(__name__)

    dataset_name = results.pop('dataset')
    metrics = ["Dataset"] + [k for k in results]
    csv_results = [(dataset_name, *list(results.values()))]

    # tabulate it
    table = tabulate(
        csv_results,
        tablefmt="pipe",
        floatfmt=".2f",
        headers=metrics,
        numalign="left",
    )

    logger.info("Evaluation results in csv format: \n" + colored(table, "cyan"))


def verify_results(cfg, results):
    """
    Args:
        results (OrderedDict[dict]): task_name -> {metric -> score}
    Returns:
        bool: whether the verification succeeds or not
    """
    expected_results = cfg.TEST.EXPECTED_RESULTS
    if not len(expected_results):
        return True

    ok = True
    for task, metric, expected, tolerance in expected_results:
        actual = results[task][metric]
        if not np.isfinite(actual):
            ok = False
        diff = abs(actual - expected)
        if diff > tolerance:
            ok = False

    logger = logging.getLogger(__name__)
    if not ok:
        logger.error("Result verification failed!")
        logger.error("Expected Results: " + str(expected_results))
        logger.error("Actual Results: " + pprint.pformat(results))

        sys.exit(1)
    else:
        logger.info("Results verification passed.")
    return ok


def flatten_results_dict(results):
    """
    Expand a hierarchical dict of scalars into a flat dict of scalars.
    If results[k1][k2][k3] = v, the returned dict will have the entry
    {"k1/k2/k3": v}.
    Args:
        results (dict):
    """
    r = {}
    for k, v in results.items():
        if isinstance(v, Mapping):
            v = flatten_results_dict(v)
            for kk, vv in v.items():
                r[k + "/" + kk] = vv
        else:
            r[k] = v
    return r