def get_field_test_ecl_info():
# important cell info: msg1 rep, msg3 rep, threshold, ecl
ddp = DeploymentDataProcessor('ls')
rootpath = 'F:/field_test_output_copy/decoded_pkl_1/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
print(len(flist))
df = pd.DataFrame(columns=[
'node_id', 'test_id', 'pack_id', 'ra_id', 'ecl', 'selected_by',
'threshold'
])
i = 0
for f in flist:
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id, ra_id = fn[2], fn[4], fn[5], 1
msg_list = ddp.load_pickle_file(f)
for m in msg_list:
if m[3] == 'LL1_LOG_ECL_INFO':
if i != 0 and (node_id, pack_id,
test_id) == (df.iloc[i - 1]['node_id'],
df.iloc[i - 1]['pack_id'],
df.iloc[i - 1]['test_id']):
ra_id += 1
ecl = m[7]['current_ecl']
ecl_by = m[7]['ecl_selected_by'].split('(')[0]
threshold = m[7]['threshold']
df.loc[i] = [
node_id, test_id, pack_id, ra_id, ecl, ecl_by, threshold
]
i += 1
df.to_csv('D:/temp/field_test_ecl.csv', index=False)
def get_msg3_rtx_field_test():
ddp = DeploymentDataProcessor('ls')
rootpath = 'F:/field_test_output_copy/decoded_pkl_1/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
print(len(flist))
df = pd.DataFrame(columns=[
'node_id', 'test_id', 'pack_id', 'msg1_tx', 'msg2_rx', 'msg4_rx'
])
i = 0
for f in flist:
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id = fn[2], fn[4], fn[5]
count_msg1 = 0
count_msg2 = 0
count_msg4 = 0
msg_list = ddp.load_pickle_file(f)
for m in msg_list:
if m[3] == 'LL1_RAR_UL_GRANT':
count_msg2 += 1
elif m[3] == 'LL1_NPRACH_START_TIME':
count_msg1 += 1
elif m[3] == 'LL1_RACH_CONTENTION_RESOLUTION_SUCCESS_IND':
count_msg4 += 1
df.loc[i] = [
node_id, test_id, pack_id, count_msg1, count_msg2, count_msg4
]
i += 1
df.to_csv('D:/temp/field_test_msg3.csv', index=False)
def stage_3(flag):
print('<Stage 3> Aggregate Extracted Info')
ddp = DeploymentDataProcessor(whoami)
if flag == 'ecl':
csv_dir = ddp.rse_csv_output_dir
elif flag == 'rar':
csv_dir = ddp.rar_csv_dir
elif flag == 'dci':
csv_dir = ddp.dci_csv_dir
elif flag == 'nrs':
csv_dir = ddp.rse_csv_output_dir
ddp.aggregate_extracted_info_to_csv(flag, csv_dir)
def get_msg3_rtx_1():
# rep = 8
# rep = 16
# dbg_log = 'D:/Nutstore/我的坚果云/Field Test/Amarisoft_SDR_Optimization/Msg3_Rep/DBG_Log/'
# get_pkl(dbg_log+'Msg3_Rep='+str(rep)+'/')
# rep = 32
# dbg_log = 'D:/Nutstore/我的坚果云/Field Test/Amarisoft_SDR_Optimization/Inactivetimer/DBG/Timer=20s/'
# get_pkl(dbg_log)
ddp = DeploymentDataProcessor('ls')
rootpath = 'D:/Nutstore/我的坚果云/Field Test/Deployment Experiment Output/decoded_pkl/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
df = pd.DataFrame(columns=[
'node_id', 'test_id', 'pack_id', 'msg3_rep', 'msg1_tx', 'msg2_rx',
'msg4_rx'
])
i = 0
for f in flist:
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id = fn[0], fn[2], fn[3]
count_msg1 = 0
count_msg2 = 0
count_msg4 = 0
msg_list = ddp.load_pickle_file(f)
for m in msg_list:
if m[3] == 'LL1_RAR_UL_GRANT':
count_msg2 += 1
elif m[3] == 'LL1_NPRACH_START_TIME':
count_msg1 += 1
elif m[3] == 'LL1_RACH_CONTENTION_RESOLUTION_SUCCESS_IND':
count_msg4 += 1
df.loc[i] = [
node_id, test_id, pack_id, rep, count_msg1, count_msg2, count_msg4
]
i += 1
df.to_csv('D:/temp/rep=16.csv', index=False)
def get_field_test_msg3_info():
# important cell info: msg1 rep, msg3 rep, threshold, ecl
ddp = DeploymentDataProcessor('ls')
rootpath = 'F:/field_test_output_copy/decoded_pkl_1/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
print(len(flist))
df = pd.DataFrame(columns=['node_id', 'test_id', 'pack_id', 'ra_id'] + [
'subcarrier_ind_nsc', 'pusch_start_subframe',
'modulation_coding_scheme_tbs', 'repetition_number',
'subcarrier_space', 'modulation_coding_scheme_imcs',
'modulation_coding_scheme_itbs', 'modulation_coding_scheme_qm',
'subcarrier_ind_isc', 'subcarrier_ind_len', 'resource_unit_number',
'result', 'expected_rapid'
])
i = 0
for f in flist:
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id, ra_id = fn[2], fn[4], fn[5], 1
msg_list = ddp.load_pickle_file(f)
for m in msg_list:
if m[3] == 'LL1_RAR_UL_GRANT':
if i != 0 and (node_id, pack_id,
test_id) == (df.iloc[i - 1]['node_id'],
df.iloc[i - 1]['pack_id'],
df.iloc[i - 1]['test_id']):
ra_id += 1
df.loc[i] = [node_id, test_id, pack_id, ra_id] + list(
m[7]['rar_pdu'].values()) + [
m[7]['result'], m[7]['expected_rapid']
]
i += 1
df.to_csv('D:/temp/field_test_msg3.csv', index=False)
def get_field_test_msg1_info():
# important cell info: msg1 rep, msg3 rep, threshold, ecl
ddp = DeploymentDataProcessor('ls')
rootpath = 'F:/field_test_output_copy/decoded_pkl_1/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
print(len(flist))
df = pd.DataFrame(columns=[
'node_id', 'test_id', 'pack_id', 'ra_id', 'hfn1', 'sfn1', 'sf1',
'hfn2', 'sfn2', 'sf2'
])
i = 0
for f in flist:
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id, ra_id = fn[2], fn[4], fn[5], 1
msg_list = ddp.load_pickle_file(f)
for m in msg_list:
if m[3] == 'LL1_NPRACH_START_TIME':
if i != 0 and (node_id, pack_id,
test_id) == (df.iloc[i - 1]['node_id'],
df.iloc[i - 1]['pack_id'],
df.iloc[i - 1]['test_id']):
ra_id += 1
hfn1, sfn1, sf1 = m[7]['hfn'], m[7]['sfn'], m[7]['sf']
elif m[3] == 'LL1_NPRACH_END_TIME':
hfn2, sfn2, sf2 = m[7]['hfn'], m[7]['sfn'], m[7]['sf']
df.loc[i] = [
node_id, test_id, pack_id, ra_id, hfn1, sfn1, sf1, hfn2,
sfn2, sf2
]
i += 1
df.to_csv('D:/temp/field_test_msg1.csv', index=False)
def get_ra_info():
ddp = DeploymentDataProcessor('ls')
rootpath = 'F:/field_test_output_copy/decoded_pkl_1/'
flist = []
for root, dirs, files in os.walk(rootpath):
if len(files) != 0:
for f in files:
flist.append(root + '/' + f)
print(len(flist))
df = pd.DataFrame(columns=['node_id', 'test_id', 'pack_id', 'ra_id'] + [
'ecl', 'selected_by', 'threshold', 'hfn1', 'sfn1', 'sf1', 'hfn2',
'sfn2', 'sf2', 'subcarrier_ind_nsc', 'pusch_start_subframe',
'modulation_coding_scheme_tbs', 'repetition_number',
'subcarrier_space', 'modulation_coding_scheme_imcs',
'modulation_coding_scheme_itbs', 'modulation_coding_scheme_qm',
'subcarrier_ind_isc', 'subcarrier_ind_len', 'resource_unit_number',
'result', 'expected_rapid'
])
i = 0
states = {
'START': 0,
'ECL': 1,
'MSG1_START': 2,
'MSG1_END': 3,
'RAR': 4,
'FINISHED': 5
}
ecl_list = 3 * [None]
msg1_start_list = 3 * [None]
msg1_end_list = 3 * [None]
rar_list = 13 * [None]
for j in range(0, len(flist)):
f = flist[j]
if j % 10 == 0:
print('DEBUG: ', j, ' / ', len(flist))
fn = f.split('/')[-1].split('.')[0].split('_')
node_id, test_id, pack_id, ra_id = fn[2], fn[4], fn[5], 1
msg_list = ddp.load_pickle_file(f)
st = states['START']
for m in msg_list:
if st == states['START']:
if m[3] == 'LL1_LOG_ECL_INFO':
ecl_list = [
m[7]['current_ecl'],
m[7]['ecl_selected_by'].split('(')[0],
m[7]['threshold']
]
st = states['ECL']
elif m[3] == 'LL1_NPRACH_START_TIME':
msg1_start_list = [m[7]['hfn'], m[7]['sfn'], m[7]['sf']]
st = states['MSG1_START']
elif m[3] == 'LL1_NPRACH_END_TIME':
msg1_end_list = [m[7]['hfn'], m[7]['sfn'], m[7]['sf']]
st = states['MSG1_END']
elif m[3] == 'LL1_RAR_UL_GRANT':
rar_list = list(m[7]['rar_pdu'].values()) + [
m[7]['result'], m[7]['expected_rapid']
]
st = states['RAR']
elif st == states['ECL']:
if m[3] == 'LL1_NPRACH_START_TIME':
msg1_start_list = [m[7]['hfn'], m[7]['sfn'], m[7]['sf']]
st = states['MSG1_START']
elif st == states['MSG1_START']:
if m[3] == 'LL1_NPRACH_END_TIME':
msg1_end_list = [m[7]['hfn'], m[7]['sfn'], m[7]['sf']]
st = states['MSG1_END']
elif st == states['MSG1_END']:
if m[3] == 'LL1_RAR_UL_GRANT':
rar_list = list(m[7]['rar_pdu'].values()) + [
m[7]['result'], m[7]['expected_rapid']
]
st = states['RAR']
elif st == states['RAR']:
if m[3] == 'LL1_LOG_ECL_INFO':
# last RA finished and start new RA
df.loc[i] = [
node_id, test_id, pack_id, ra_id
] + ecl_list + msg1_start_list + msg1_end_list + rar_list
i += 1
ecl_list = 3 * [None]
msg1_start_list = 3 * [None]
msg1_end_list = 3 * [None]
rar_list = 13 * [None]
ra_id += 1
ecl_list = [
m[7]['current_ecl'],
m[7]['ecl_selected_by'].split('(')[0],
m[7]['threshold']
]
st = states['ECL']
df.loc[i] = [node_id, test_id, pack_id, ra_id
] + ecl_list + msg1_start_list + msg1_end_list + rar_list
i += 1
ecl_list = 3 * [None]
msg1_start_list = 3 * [None]
msg1_end_list = 3 * [None]
rar_list = 13 * [None]
df.to_csv('D:/temp/field_test_ra_info.csv', index=False)
def stage_4(flag):
# merge the sum output data with meta csv
print('<Stage 4> Merge with meta data to post_ft_processing')
ddp = DeploymentDataProcessor(whoami)
if flag == 1:
ddp.merge_msg3_data_rep_with_meta()
def stage_2(cmd, one_file_name):
# Input from PKL, process and output the results.
print('<Stage 2> Message list => Extracted info')
ddp = DeploymentDataProcessor(whoami)
if cmd == 'print':
print(ddp.get_decoded_log_names())
if cmd == 'one':
ml = ddp.load_pickle_file(ddp.pkl_dir+one_file_name)
print(ml[0])
# ddp.extract_rsrp_snr_ecl(ddp.pkl_dir + one_file_name)
# ddp.get_rsrp_snr_ecl_list(ml)
if cmd == 'test':
ml = ddp.load_pickle_file(ddp.pkl_dir+one_file_name)
log_name = 'LL1_RAR_UL_GRANT'
log_name = 'LL1_PUSCH_CALC_TX_POWER'
log_name = 'LL1_LOG_ECL_INFO'
log_name = 'EMM_PSM_STATUS_IND'
ddp.take_out_specific_logs_from_msg_list(ml, log_name, 'visualize_seq_num/实验楼2F_消防栓/')
if cmd == 'ecl':
ddp.extract_rsrp_snr_ecl(ddp.pkl_dir+one_file_name)
if cmd == 'stat':
ddp.msg_list_stats(ddp.pkl_dir+one_file_name)
if cmd == 'dci':
ddp.extract_dci(ddp.pkl_dir + one_file_name)
if cmd == 'rar':
ddp.extract_msg3_repetition(ddp.pkl_dir + one_file_name)
if cmd == 'all':
'''
Note1: remember to change the function in pipeline_process_all()
Note2: select between the two file lists below. They are different.
'''
file_list = ddp.get_decoded_log_names()
# file_list = ddp.get_rse_csv_names()
# file_list = ddp.get_bler_report_csv_names()
ddp.pipeline_process_all(file_list)