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feat: implementar estatísticas

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Shino
2025-11-09 18:32:47 -01:00
parent 5eed5fbe7a
commit a490bc7756
10 changed files with 110 additions and 683 deletions
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2
utils/crud.py
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@@ -21,6 +21,8 @@ def read_ids(df):
ids = _get_uniques(df)
_show_events(ids)
def get_unique_events_table(df):
return df.drop_duplicates(subset="ID", keep="first")
def read_header(df, event_id):
# Informações do header do evento

1
utils/parser.py
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@@ -1,6 +1,5 @@
# pyright: basic
import io
import warnings
from collections import defaultdict
from datetime import datetime

96
utils/stats.py Normal file
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@@ -0,0 +1,96 @@
# pyright: basic
import os
import pandas as pd
import numpy as np
STAT_MENU = """=== Earthquakes ===
== Estatísticas ==
[1] Média
[2] Variância
[3] Desvio padrão
[4] Máximo
[5] Mínimo
[Q] Voltar ao menu principal
"""
def stat_menu(df: pd.DataFrame):
inStats = True
while inStats:
os.system("cls")
print(STAT_MENU)
usrIn = input("Opção: ").lower()
match usrIn:
case "1":
pass
case "2":
pass
case "3":
pass
case "4":
pass
case "5":
pass
case "q":
inStats = False
pass
case _:
pass
def average(df: pd.DataFrame, filter_by):
values = df[filter_by].to_numpy()
if filter_by == "Magnitudes":
values = _unpack_mags(values)
return np.average(values)
def variance(df, filter_by):
values = df[filter_by].to_numpy()
if filter_by == "Magnitudes":
values = _unpack_mags(values)
return np.var(values)
def std_dev(df, filter_by):
values = df[filter_by].to_numpy()
if filter_by == "Magnitudes":
values = _unpack_mags(values)
return np.std(values)
def max(df, filter_by):
values = df[filter_by].to_numpy()
if filter_by == "Magnitudes":
values = _unpack_mags(values)
return np.max(values)
def min(df, filter_by):
values = df[filter_by].to_numpy()
if filter_by == "Magnitudes":
values = _unpack_mags(values)
return np.min(values)
def _unpack_mags(arr: np.ndarray):
newVals = np.empty(0)
for v in arr:
for m in v:
newVals = np.append(newVals, np.float32(m["Magnitude"]))
return newVals

31
utils/test_data.txt
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@@ -1,31 +0,0 @@
1996 6 7 1325 29.2 L 59.846 5.130 12.0F TES 12 .60 1.9LTES 2.2CTES 2.0LNAO1
GAP=177 2.78 4.5 12.80.000 0.2239E+02 0.6258E+03 -0.2817E+03E
1996 6 7 1325 30.5 L 59.763 5.396 29.2 NAO 2 1.0 2.0LNAO1
8.3 41.0 74.7 1 F
1996-06-07-1324-51S.TEST__009 6
ACTION:SPL 14-12-11 12:04 OP:jh STATUS: ID:19960607132529 L I
STAT COM NTLO IPHASE W HHMM SS.SSS PAR1 PAR2 AGA OPE AIN RES W DIS CAZ7
EGD HHZ NS IP 4 1325 35.950 C BER jh 120.0-1.131047.70 6
EGD HHZ NS END 1325 35.950 111.0 BER jh 0.0 47.70 6
EGD HHZ NS AMP 1325 35.950 11.1 33.3 BER jh 47.70 6
EGD HHN NS ES 1325 42.030 BER jh 70.0-.8901047.70 6
BER BHZ NS00 IP 1325 38.120 C kkk AUT -.9801061.00 11
BER BHZ NS00 END 1325 38.120 55.0 BER jh 4.8 61.00 11
BER BHN NS00 ES 1325 45.440 BER jh 70.0-.9901061.00 11
BER BHZ NS00 IAML A1325 46.710 31.7 0.20 BER jh 0.4 61.00 11
KMY BHZ NS10 IP 1325 40.260 C PPP Ajh 70.0 .3301070.90 175
KMY BHZ NS10 END 1325 40.260 62.0 BER jh 70.90 175
KMY BHN NS10 ES 1325 48.740 BER jh 70.0.3001070.90 175
KMY BHZ NS10 IAML 1325 48.920 83.6 0.20 BER jh 70.90 175
ASK SHZ NS EP 2 1325 39.590 D -1.031071.10 3
ASK SHZ NS END 1325 39.590 68.0 71.10 3
ASK SHZ NS ES 1325 48.070 -1.021071.10 3
ASK SHZ NS AMP 1325 48.070 333.3 2.20 71.10 3
ASK SHZ NS IAML 1325 50.900 111.0 0.30 71.10 3
NRA0 S Z Pn A1326 19.090 50.0-.05010368.0 72
NRA0 S Z END 1326 19.090 333.0 368.0 72
NRA0 S Z BAZ-P 1326 19.090 256.9 6.9 0. 368.0 72
NRA0 S Z Pg 1326 27.940 -.64010368.0 72
NRA0 S Z BAZ 1326 27.940 253.0 7.3 -3. 368.0 72
NRA0 S Z Lg 1327 10.540 -.89010368.0 72
NRA0 S Z BAZ 1327 10.540 266.6 4.1 9. 368.0 72

50
utils/tests.py
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@@ -1,50 +0,0 @@
import pytest
import parser
def test_type_1():
test_data =[" 1996 6 7 1325 29.2 L 59.846 5.130 12.0F TES 12 .60 1.9LTES 2.2CTES 2.0LNAO1",
" 1996 6 7 1325 30.5 L 59.763 5.396 29.2 NAO 2 1.0 2.0LNAO1"]
expected = {"DateTime": "1996-06-07T13:25:29.200000", "Distance Indicator": "L", "Event ID": " ", 'Lat': 59.846, 'Long': 5.13,'Depth': 12.0, 'Agency': 'TES', 'Magnitudes': [{'M': ' 1.9', 'T': 'L'},{'M': ' 2.2', 'T': 'C'},{'M': ' 2.0', 'T': 'L'},{'M': ' 2.0', 'T': 'L'}]}
_ret = parser.parse_type_1(test_data)
for (k,v) in _ret.items():
assert _ret[k] == expected[k]
def test_type_3():
test_data = [" OP: CVUA-RM/RC 3",
" STATUS: OK SENTIDO 3",
" SENTIDO: II/III -Pico: S. Caetano 3",
" PUB: NAO 3",
" WEB: SIM 3",
" OBS: Por ordem do CT nao foi emitido novo comunicado 3",
" OBS: Sismo sobreposto 3",
" REGIAO: Pico,VZ14,SZ06,FE95 405 3"]
_ret = parser.parse_type_3(test_data)
assert len(_ret["Comments"]) == 8
def test_type_6():
test_data = [" 1996-06-03-2002-18S.TEST__012 6",
" 1996-06-03-1917-52S.TEST__002 6"]
expected = {"Wave": ["1996-06-03-2002-18S.TEST__012", "1996-06-03-1917-52S.TEST__002"]}
_ret = parser.parse_type_6(test_data)
for (k,v) in _ret.items():
assert _ret[k] == expected[k]
def test_type_i():
test_data = [" ACTION:SPL 08-10-02 10:19 OP:jh STATUS: ID:19960603195540 I"]
expected = {"Action": "SPL", "Action Extra": {"Date": '2008-10-02T10:19:00', "OP": "jh", "Status": "", "ID":19960603195540}}
_ret = parser.parse_type_i(test_data)
for (k,v) in _ret.items():
assert _ret[k] == expected[k]
def test_type_e():
test_data =[" GAP=348 2.88 999.9 999.9999.9 -0.1404E+08 -0.3810E+08 0.1205E+09E"]
expected = {"Gap": 348, "Origin": 2.88, "Error_lat": 999.9, "Error_long": 999.9, "Error_depth": 999.9, "Cov_xy": -14040000.0, "Cov_xz": -38100000.0, "Cov_yz": 120500000.0}
_ret = parser.parse_type_e(test_data)
for (k,v) in _ret.items():
assert _ret[k] == expected[k]

0
utils/vis.py
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