Test and debug.

                          n_c * req_delay) / self.prrtSystemParameters.source_packet_interval)

    def get_k_lim(self, start, end):

        if end - start <= 1:

            return end

        if end < start:

            return start

        mid_point = math.ceil((end + start) / 2)

        p_r = np.around(self.residual_packet_erasure_rate(mid_point, self.n_max, self.prrtChannelParameters.loss_rate_fwd),

            8)  # Pr(k, n_max)

        p_r = np.around(self.residual_packet_erasure_rate(mid_point, self.n_max, self.prrtChannelParameters.loss_rate_fwd), 8)  # Pr(k, n_max)

        if p_r == self.prrtApplicationParameters.max_residual_loss_rate:

            return int(mid_point)

        elif p_r > self.prrtApplicationParameters.max_residual_loss_rate:

import pandas as pd

from multiprocessing import Pool

ds_basename = os.listdir("../../hecps/code/ML/data/")

# ds_basename = os.listdir("../../hecps/code/ML/data/")

# ds_basename = ["in_12_param_4_sz_zzatql"]

ds_rel_input_path = "../../hecps/code/ML/data/"

ds_rel_result_path = "documents/result/"

# ds_rel_input_path = "../../hecps/code/ML/data/"

# ds_rel_result_path = "documents/result/"

    #['documents/1','documents/2','documents/3','documents/4','documents/5','documents/6']

ds_basename = os.listdir("documents/debug/")

# ds_basename = ["in_12_param_4_sz_zzatql"]

ds_rel_input_path = "documents/debug/"

ds_rel_result_path = "documents/debug/"

def get_n_p_max(rtt_prop_fwd, pkt_length, data_rate_btl_fwd):

	return rtt_prop_fwd * data_rate_btl_fwd / pkt_length

def evaluate(searchAlgorithm, appParams, channelParams, systemParams):

    n_p_min = 1

    n_p_max = get_n_p_max(channelParams.rtt_prop_fwd, appParams.pkt_length, channelParams.data_rate_btl_fwd)

    n_p_max = np.round(get_n_p_max(channelParams.rtt_prop_fwd, appParams.pkt_length, channelParams.data_rate_btl_fwd), 0)

    if n_p_min <= n_p_max:

        start = time.time()

        search = hec_search.HECSearch(searchAlgorithm, n_p_min, n_p_max, appParams, channelParams, systemParams)

        for index, row in df_in_chunk.iterrows():

            appParams = prrt.PrrtApplicationParameters(row['app_max_latency'], row['app_max_residual_loss_rate'], row['app_data_rate'], row['app_pkt_length'])

            chnlParams = prrt.PrrtChannelParameters(row['ch_loss_rate'], 0, row['ch_rtt_prop_fwd'], 0, row['ch_data_rate_btl_fwd'], 0)

            sysParams = prrt.PrrtSystemParameters(row['sys_block_coding_dly'], row['sys_red_pkt_trans_dly'], row['sys_proc_dly'], row['sys_pkt_loss_detection_dly'], row['sys_src_pkt_interval'])

            for searchAlgorithm in ["GreedySearch", "FullSearch"]:

            sysParams = prrt.PrrtSystemParameters(row['sys_block_coding_dly'], np.round(row['sys_red_pkt_trans_dly'], 5), row['sys_proc_dly'], row['sys_pkt_loss_detection_dly'], row['sys_src_pkt_interval'])

            if index == 98:

                for searchAlgorithm in ["GreedySearch"]:

                    print(str(index))

                    search_result = evaluate(searchAlgorithm, appParams, chnlParams, sysParams)

                    if len(search_result) != 0:

        counter += 1

        #print("Chunk round: " + str(counter))

    save_result_to.to_csv(ds_rel_result_path + dataset_basename, sep=',', index = False)

    save_result_to.to_csv(ds_rel_result_path + dataset_basename.replace("in", "out", 1), sep=',', index = False)

#test_case("documents/5")

if __name__ == '__main__':

    pool = Pool(processes=8)

    pool.map(test_case, ds_basename, chunksize=1)

test_case(ds_basename[0])

# if __name__ == '__main__':

#     pool = Pool(processes=8)

#     pool.map(test_case, ds_basename, chunksize=1)