File size: 4,136 Bytes
b9d0cf5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | from typing import List, Optional, cast
import pandas as pd
import solara
data_global_cell_id = []
data_la_cell_name = []
data_wcdma_service_area_number = []
data_wcdma_service_area_name = []
class dfs:
gsm_core_infos = solara.reactive(cast(Optional[pd.DataFrame], None))
wcdma_core_infos = solara.reactive(cast(Optional[pd.DataFrame], None))
def parse_content(all_files):
data_global_cell_id = []
data_la_cell_name = []
data_wcdma_service_area_number = []
data_wcdma_service_area_name = []
for file in all_files:
all_data_global_cell_id = []
all_data_la_cell_name = []
all_data_wcdma_service_area_number = []
all_data_wcdma_service_area_name = []
content = file.decode("utf-8").splitlines()
for line in content:
if "Global cell ID" in line:
data_global_cell_id.append([line.split("=")[1].strip()])
elif "LA cell name" in line:
data_la_cell_name.append([line.split("=")[1].strip()])
elif "3G service area number" in line:
data_wcdma_service_area_number.append([line.split("=")[1].strip()])
elif "3G service area name" in line:
data_wcdma_service_area_name.append([line.split("=")[1].strip()])
# Append the extracted data for the current file to the overall lists
all_data_global_cell_id.extend(data_global_cell_id)
all_data_la_cell_name.extend(data_la_cell_name)
all_data_wcdma_service_area_number.extend(data_wcdma_service_area_number)
all_data_wcdma_service_area_name.extend(data_wcdma_service_area_name)
# Create a DataFrame from the extracted data
df_global_cell_id = pd.DataFrame(
all_data_global_cell_id, columns=["Global cell ID"]
)
df_la_cell_name = pd.DataFrame(all_data_la_cell_name, columns=["LA cell name"])
df_wcdma_service_area_number = pd.DataFrame(
all_data_wcdma_service_area_number, columns=["3G service area number"]
)
df_wcdma_service_area_name = pd.DataFrame(
all_data_wcdma_service_area_name, columns=["3G service area name"]
)
# add index column df_global_cell_id and df_la_cell_name and dfa_wcdma_service_area_numbera and df_wcdma_service_area_name
df_global_cell_id.insert(0, "index", range(0, len(df_global_cell_id)))
df_la_cell_name.insert(0, "index", range(0, len(df_la_cell_name)))
df_wcdma_service_area_number.insert(
0, "index", range(0, len(df_wcdma_service_area_number))
)
df_wcdma_service_area_name.insert(
0, "index", range(0, len(df_wcdma_service_area_name))
)
# Merge global_cell_id and la_cell_name on index
df_la_cell_name = df_la_cell_name.merge(df_global_cell_id, on="index")
# merge wcdma_service_area_number and wcdma_service_area_name on index
df_wcdma_service_area_name = df_wcdma_service_area_name.merge(
df_wcdma_service_area_number, on="index"
)
df_la_cell_name["LAC_ID"] = df_la_cell_name["Global cell ID"].str[5:]
df_wcdma_service_area_name["LAC_ID"] = df_wcdma_service_area_name[
"3G service area number"
].str[5:]
df_la_cell_name["LAC"] = df_la_cell_name["LAC_ID"].str[:4]
df_la_cell_name["Cell ID"] = df_la_cell_name["LAC_ID"].str[4:]
df_wcdma_service_area_name["LAC"] = df_wcdma_service_area_name["LAC_ID"].str[:4]
df_wcdma_service_area_name["Cell ID"] = df_wcdma_service_area_name["LAC_ID"].str[4:]
# convert LAC to from HEXadecimal to DECimal
df_la_cell_name["LAC_DECIMAL"] = df_la_cell_name["LAC"].apply(lambda x: int(x, 16))
df_la_cell_name["Cell_ID_DECIMAL"] = df_la_cell_name["Cell ID"].apply(
lambda x: int(x, 16)
)
df_wcdma_service_area_name["LAC_DECIMAL"] = df_wcdma_service_area_name["LAC"].apply(
lambda x: int(x, 16)
)
df_wcdma_service_area_name["Cell_ID_DECIMAL"] = df_wcdma_service_area_name[
"Cell ID"
].apply(lambda x: int(x, 16))
df_la_cell_name = df_la_cell_name.reset_index(drop=True)
dfs.gsm_core_infos.value = df_la_cell_name
dfs.wcdma_core_infos.value = df_wcdma_service_area_name
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