# Path: thrifty/toads_data.py
# class DetectionResult(object):
#     def __init__(self, timestamp, block, soa, carrier_info, corr_info,
#                  rxid=None, txid=None):
#     def serialize(self):
#     def deserialize(cls, string, with_rxid=False, with_txid=False):
# def _load_toads(stream, with_rxid=True, with_txid=True):
# def load_toad(stream):
# def load_toads(stream):
# def toads_array(detections, with_ids=True):
# 
# Path: thrifty/settings.py
# def parse_kvconfig(config_file):
#     """A simple key:value config file parser."""
#     settings = {}
#     for line_no, line in enumerate(config_file):
#         if CONFIG_COMMENT_CHAR in line:
#             line, _ = line.split(CONFIG_COMMENT_CHAR, 1)
#         if len(line.strip()) == 0:
#             continue
#         if CONFIG_DELIMITER not in line:
#             raise ConfigSyntaxError(line_no + 1, 'No delimiter found')
#         key, value = line.split(CONFIG_DELIMITER, 1)
#         settings[key.strip()] = value.strip()
#     return settings


import argparse
import glob
import itertools
import numpy as np
from collections import defaultdict
from thrifty import toads_data
from thrifty.settings import parse_kvconfig
    # TODO: only filter if SOA is within code_len
    mask_unidentified = (cur['txid'] == -1)  # FIXME: magic number
    mask_prev = ((cur['block'] == prev['block'] + 1) &
                 (cur['energy'] < prev['energy']))
    mask_next = ((cur['block'] == next_['block'] - 1) &
                 (cur['energy'] < next_['energy']))
    mask = ~(mask_prev | mask_next | mask_unidentified)

    reverse_idx = np.argsort(idx)

    return mask[reverse_idx]


def filter_duplicates(detections):
    """Return detections with duplicates and unidentified detections removed,
    sorted by timestamp."""
    mask = identify_duplicates(detections)
    filtered = list(itertools.compress(detections, mask))
    filtered.sort(key=lambda x: x.timestamp)
    return filtered


def load_toad_files(toad_globs):
    filenames = []
    for toad_glob in toad_globs:
        filenames.extend(glob.glob(toad_glob))

    detections = []
    for filename in filenames:
        with open(filename, 'r') as file_:

# Path: thrifty/toads_data.py
# class DetectionResult(object):
#     def __init__(self, timestamp, block, soa, carrier_info, corr_info,
#                  rxid=None, txid=None):
#     def serialize(self):
#     def deserialize(cls, string, with_rxid=False, with_txid=False):
# def _load_toads(stream, with_rxid=True, with_txid=True):
# def load_toad(stream):
# def load_toads(stream):
# def toads_array(detections, with_ids=True):
# 
# Path: thrifty/settings.py
# def parse_kvconfig(config_file):
#     """A simple key:value config file parser."""
#     settings = {}
#     for line_no, line in enumerate(config_file):
#         if CONFIG_COMMENT_CHAR in line:
#             line, _ = line.split(CONFIG_COMMENT_CHAR, 1)
#         if len(line.strip()) == 0:
#             continue
#         if CONFIG_DELIMITER not in line:
#             raise ConfigSyntaxError(line_no + 1, 'No delimiter found')
#         key, value = line.split(CONFIG_DELIMITER, 1)
#         settings[key.strip()] = value.strip()
#     return settings


# Path: thrifty/identify.py
import argparse
import glob
import itertools
import numpy as np
from collections import defaultdict
from thrifty import toads_data
from thrifty.settings import parse_kvconfig

    # TODO: only filter if SOA is within code_len
    mask_unidentified = (cur['txid'] == -1)  # FIXME: magic number
    mask_prev = ((cur['block'] == prev['block'] + 1) &
                 (cur['energy'] < prev['energy']))
    mask_next = ((cur['block'] == next_['block'] - 1) &
                 (cur['energy'] < next_['energy']))
    mask = ~(mask_prev | mask_next | mask_unidentified)

    reverse_idx = np.argsort(idx)

    return mask[reverse_idx]


def filter_duplicates(detections):
    """Return detections with duplicates and unidentified detections removed,
    sorted by timestamp."""
    mask = identify_duplicates(detections)
    filtered = list(itertools.compress(detections, mask))
    filtered.sort(key=lambda x: x.timestamp)
    return filtered


def load_toad_files(toad_globs):
    filenames = []
    for toad_glob in toad_globs:
        filenames.extend(glob.glob(toad_glob))

    detections = []
    for filename in filenames:
        with open(filename, 'r') as file_:

            detections.extend(toads_data.load_toad(file_))