novo json

utils/parser.py

@@ -101,8 +101,7 @@ def _parse_preamble(hLines: list[str]):
             case "6":
                 aux[6].append(line)
             case "E":
-                pass
-                # aux["E"].append(line)
+                aux["E"].append(line)
             case "I":
                 aux["I"].append(line)
             case "F":
@@ -136,7 +135,7 @@ def _parse_type_1(data: list[str]):
     depth = float(aux[38:43])
     no_stat = int(aux[48:51])
 
-    hypo = {"Data": dt.isoformat(), "Distancia": dist_ind, "Tipo Ev": ev_type, "Lat": lat, "Long": long, "Prof": depth, "Estacoes": no_stat, "Magnitudes": list()}
+    hypo = {"Data": dt.isoformat(), "Distancia": dist_ind, "Tipo Evento": ev_type, "Latitude": lat, "Longitude": long, "Profundidade": depth, "Estacoes": no_stat, "Magnitudes": list()}
     for l in data:
         hypo["Magnitudes"] = hypo["Magnitudes"] + _parse_mag(l)
 
@@ -175,7 +174,7 @@ 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), (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)
+    dados.rename(columns={'STAT': "Estacao", 'SP': "Componente" , 'PHASW': "Tipo Onda", 'HR': "Hora", 'MM': "Min", 'SECON': "Seg", 'AMPL': "Amplitude", " DIST": "Distancia Epicentro"}, inplace=True)
     return dados
 
 

utils/utils.py

@@ -6,7 +6,6 @@ import json
 from math import modf
 from typing import Any
 
-from numpy import nan
 import pandas as pd
 
 
@@ -26,17 +25,24 @@ def create_dict_struct(df: pd.DataFrame, event_cols, station_cols) -> dict[str,
     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)] = create_event_info(first_row, event_cols)
         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_event_info(info: pd.DataFrame, cols) -> dict[str, Any]:
+    informacoes = dict()
+
+    for v in cols:
+        if v == "Magnitudes":
+            informacoes[v] = create_mag_info(info.iloc[0][v])
+        elif v in {"Latitude", "Longitude", "Profundidade", "Gap"}:
+            informacoes[v] = float(info.iloc[0][v])
+        else:
+            informacoes[v] = info.iloc[0][v]
+
+    return informacoes
 
 
 def create_stations_info_1(info: pd.DataFrame) -> dict[str, Any]: