feat: Implementado formato JSON personalizado

utils/parser.py

@@ -159,6 +159,7 @@ def _parse_type_3(data: list[str]):
     for line in data:
         if line.startswith(" SENTIDO") or line.startswith(" REGIAO"):
             c, v = line[:-2].strip().split(": ", maxsplit=1)
+            v = v.split(",")[0]
             comments[c.capitalize()] = v
 
     return comments
@@ -173,8 +174,8 @@ def _parse_type_6(data: list[str]):
 
 def _parse_type_7(data: list[str]):
     aux = io.StringIO("\n".join(data))
-    dados = pd.read_fwf(aux, colspecs=[(1,5), (6,8),(10,15), (18,20), (20,22), (23,28), (34,38)])
-    dados.rename(columns={'STAT': "Estacao", 'SP': "Componente" , 'PHASW': "Tipo Onda", 'HR': "Hora", 'MM': "Min", 'SECON': "Seg", 'AMPL': "Amplitude"}, inplace=True)
+    dados = pd.read_fwf(aux, colspecs=[(1,5), (6,8),(10,15), (18,20), (20,22), (23,28), (34,38), (71,75)])
+    dados.rename(columns={'STAT': "Estacao", 'SP': "Componente" , 'PHASW': "Tipo Onda", 'HR': "Hora", 'MM': "Min", 'SECON': "Seg", 'AMPL': "Amplitude", " DIST": "Dist. Epi"}, inplace=True)
     return dados
 
 

utils/stats.py

@@ -1,6 +1,7 @@
 # pyright: basic
 
 import os
+import sys
 
 import pandas as pd
 import numpy as np
@@ -29,7 +30,7 @@ CHOICE = {"1": "Magnitudes", "2": "Distancia","3": "Prof"}
 
 
 def filter_submenu(type: str):
-    os.system("cls")
+    os.system("cls" if sys.platform == "windows" else "clear")
     print(f"{STAT_HEADER}\n  = {type} =  ")
     print(FILTER_CHOICES)
 
@@ -45,7 +46,7 @@ def filter_submenu(type: str):
 def stat_menu(df: pd.DataFrame):
     inStats = True
     while inStats:
-        os.system("cls")
+        os.system("cls" if sys.platform == "windows" else "clear")
         print(STAT_HEADER + "\n" + STAT_MENU)
         usrIn = input("Opção: ").lower()
 

utils/utils.py

@@ -0,0 +1,76 @@
+#! /usr/bin/env python
+# pyright: basic
+
+from datetime import time
+import json
+from math import modf
+from typing import Any
+
+from numpy import nan
+import pandas as pd
+
+
+def save_as_json(info: dict[str, Any]) -> bool:
+    with open("test.json", "w") as fp:
+        json.dump(info, fp)
+    
+    return True
+
+# TODO: passar os nomes das colunas, para não haver problemas no futuro, caso se altere os nomes da dataframe
+def create_dict_struct(df: pd.DataFrame, event_cols, station_cols) -> dict[str, Any]:
+    # get all events by their id
+    uniqueIds = df["ID"].unique()
+
+    allEvents = {}
+
+    for id in uniqueIds:
+        filteredDf = df.loc[df["ID"] == id]
+        first_row = filteredDf.head(1)
+        allEvents[int(id)] = create_event_info(first_row)
+        allEvents[int(id)].update(create_stations_info_1(filteredDf))
+
+    return allEvents
+
+
+def create_event_info(info: pd.DataFrame) -> dict[str, Any]:
+    return {"DataHora": info.iloc[0]["Data"], "Lat": float(info.iloc[0]["Lat"]), "Long": float(info.iloc[0]["Long"]),
+                "Profundidade": float(info.iloc[0]["Prof"]), "Tipo Evento": info.iloc[0]["Tipo Ev"],
+                "Magnitude": create_mag_info(info.iloc[0]["Magnitudes"]), "Regiao": info.iloc[0]["Regiao"],
+                "Sentido": info.iloc[0]["Sentido"]}
+
+
+def create_stations_info_1(info: pd.DataFrame) -> dict[str, Any]:
+    stationsDict = {}
+    for idx in range(len(info)):
+        aux = info.iloc[idx]
+
+        micro, sec = tuple(map(int, modf(aux["Seg"])))
+        hms = time(hour=aux["Hora"],minute=aux["Min"], second=sec, microsecond=micro).strftime("%H:%M:%S.%f")
+        station = {"Componente": aux["Componente"], "Hora": hms, "Distancia": float(aux["DIS"])}
+
+        if type(aux["Tipo Onda"]) != float:
+            station.update({"Tipo Onda": aux["Tipo Onda"]})
+            if aux["Tipo Onda"] == "IAML":
+                station.update({"Amplitude": float(aux["Amplitude"])})
+
+
+        if aux["Estacao"] not in stationsDict.keys():
+            stationsDict[aux["Estacao"]] = [station]
+        else:
+            stationsDict[aux["Estacao"]].append(station)
+    return {"Estacoes": stationsDict}
+
+
+def create_mag_info(magnitudes):
+    mags = {}
+    for value in magnitudes:
+        mags[value["Tipo"]] = value["Magnitude"]
+    return mags
+
+
+if __name__ == '__main__':
+    import parser
+
+    df = parser.parse("dados.txt")
+    a = create_dict_struct(df, None, None)
+    save_as_json(a)