# Path: thrifty/tdoa_est.py
# SPEED_OF_LIGHT = 2.997e8
# MAX_TDOA = 30e3 / SPEED_OF_LIGHT
# TDOA_DTYPE = {'names': ('rx0', 'rx1', 'tdoa', 'snr', 'model_quality',
#                         'det0_idx', 'det1_idx'),
#               'formats': ('i4', 'i4', 'f8', 'f8', 'f8', 'i4', 'i4')}
# MATRIX_DTYPE = {'names': ('group_id', 'timestamp', 'tx') + TDOA_DTYPE['names'],
#                 'formats': ('i4', 'f8', 'i4') + TDOA_DTYPE['formats']}
# def make_detection_extractor(detections, matches):
#     def extract(rxid0, rxid1, timestamp_start, timestamp_stop):
# def estimate_model_quality(model, detection_pairs):
# def build_model_poly(detection_pairs, beacon_sdoa, nominal_sample_rate, deg=2):
#     def evaluate(det0, det1):
# def build_model_weighted_poly(detection_pairs, beacon_sdoa,
#                               nominal_sample_rate, deg=2):
#     def evaluate(det0, det1):
# def find_nearest_value(list_, value):
# def test_find_nearest_value():
# def build_model_nearest(detection_pairs, beacon_sdoa, nominal_sample_rate):
#     def evaluate(det0, det1):
# def build_model_linear(detection_pairs, beacon_sdoa, nominal_sample_rate):
#     def evaluate(det0, det1):
# def _dist(vector1, vector2):
# def estimate_tdoas(detections, matches, window_size,
#                    beacon_pos, rx_pos, sample_rate,
#                    model_builder=default_model, model_params=None):
#     def _beacon_tdoa(rxid0, rxid1, beaconid):
# def save_tdoa_groups(output, tdoa_groups):
# def load_tdoa_matrix(fname):
# def groups_to_matrix(groups):
# def load_tdoa_groups(fname):
# def load_pos_config(file_):
# def _main():


import numpy as np
import matplotlib.pyplot as plt
    import argparse
from thrifty import tdoa_est
    parser.add_argument('--rx1', type=int, default=1,
                        help="receiver ID of second receiver")
    parser.add_argument('--tx', type=int, default=0,
                        help="ID of mobile unit to analyze")
    parser.add_argument('--timestamp', type=_parse_range, default=None,
                        help="limit the analysis to TDOAs within a specific "
                             "range of timestamps")
    parser.add_argument('--detidx', type=_parse_range, default=None,
                        help="limit the analysis to TDOAs within a specific "
                             "range of detection IDs")
    args = parser.parse_args()

    if args.rx0 > args.rx1:
        args.rx0, args.rx1 = args.rx1, args.rx0

    tdoa_matrix = tdoa_est.load_tdoa_matrix(args.tdoa)
    selection = tdoa_matrix[(tdoa_matrix['rx0'] == args.rx0) &
                            (tdoa_matrix['rx1'] == args.rx1) &
                            (tdoa_matrix['tx'] == args.tx)]
    if args.timestamp is not None:
        start, stop = args.timestamp
        selection = selection[(selection['timestamp'] >= start) &
                              (selection['timestamp'] <= stop)]
    if args.detidx is not None:
        start, stop = args.detidx
        selection = selection[(selection['det0_idx'] >= start) &
                              (selection['det0_idx'] <= stop) &
                              (selection['det1_idx'] >= start) &
                              (selection['det1_idx'] <= stop)]


# Path: thrifty/tdoa_est.py
# SPEED_OF_LIGHT = 2.997e8
# MAX_TDOA = 30e3 / SPEED_OF_LIGHT
# TDOA_DTYPE = {'names': ('rx0', 'rx1', 'tdoa', 'snr', 'model_quality',
#                         'det0_idx', 'det1_idx'),
#               'formats': ('i4', 'i4', 'f8', 'f8', 'f8', 'i4', 'i4')}
# MATRIX_DTYPE = {'names': ('group_id', 'timestamp', 'tx') + TDOA_DTYPE['names'],
#                 'formats': ('i4', 'f8', 'i4') + TDOA_DTYPE['formats']}
# def make_detection_extractor(detections, matches):
#     def extract(rxid0, rxid1, timestamp_start, timestamp_stop):
# def estimate_model_quality(model, detection_pairs):
# def build_model_poly(detection_pairs, beacon_sdoa, nominal_sample_rate, deg=2):
#     def evaluate(det0, det1):
# def build_model_weighted_poly(detection_pairs, beacon_sdoa,
#                               nominal_sample_rate, deg=2):
#     def evaluate(det0, det1):
# def find_nearest_value(list_, value):
# def test_find_nearest_value():
# def build_model_nearest(detection_pairs, beacon_sdoa, nominal_sample_rate):
#     def evaluate(det0, det1):
# def build_model_linear(detection_pairs, beacon_sdoa, nominal_sample_rate):
#     def evaluate(det0, det1):
# def _dist(vector1, vector2):
# def estimate_tdoas(detections, matches, window_size,
#                    beacon_pos, rx_pos, sample_rate,
#                    model_builder=default_model, model_params=None):
#     def _beacon_tdoa(rxid0, rxid1, beaconid):
# def save_tdoa_groups(output, tdoa_groups):
# def load_tdoa_matrix(fname):
# def groups_to_matrix(groups):
# def load_tdoa_groups(fname):
# def load_pos_config(file_):
# def _main():


# Path: thrifty/tdoa_analysis.py
import numpy as np
import matplotlib.pyplot as plt
    import argparse
from thrifty import tdoa_est

    parser.add_argument('--rx1', type=int, default=1,
                        help="receiver ID of second receiver")
    parser.add_argument('--tx', type=int, default=0,
                        help="ID of mobile unit to analyze")
    parser.add_argument('--timestamp', type=_parse_range, default=None,
                        help="limit the analysis to TDOAs within a specific "
                             "range of timestamps")
    parser.add_argument('--detidx', type=_parse_range, default=None,
                        help="limit the analysis to TDOAs within a specific "
                             "range of detection IDs")
    args = parser.parse_args()

    if args.rx0 > args.rx1:
        args.rx0, args.rx1 = args.rx1, args.rx0

    tdoa_matrix = tdoa_est.load_tdoa_matrix(args.tdoa)
    selection = tdoa_matrix[(tdoa_matrix['rx0'] == args.rx0) &
                            (tdoa_matrix['rx1'] == args.rx1) &
                            (tdoa_matrix['tx'] == args.tx)]
    if args.timestamp is not None:
        start, stop = args.timestamp
        selection = selection[(selection['timestamp'] >= start) &
                              (selection['timestamp'] <= stop)]
    if args.detidx is not None:
        start, stop = args.detidx
        selection = selection[(selection['det0_idx'] >= start) &
                              (selection['det0_idx'] <= stop) &
                              (selection['det1_idx'] >= start) &
                              (selection['det1_idx'] <= stop)]


    tdoa_meter = selection['tdoa'] * tdoa_est.SPEED_OF_LIGHT