我需要具体确定哪种降水类型进入此字符串，具体请参见第225行
雪，颗粒，冷冻或混合。有时候，我通过为每个循环构建一个空数组并对其求和来克服这个问题，现在我遇到的问题是什么是“混合降水”，什么不是我来到需要将其扩展为一个数组的地方，而不是我使用np.sum函数（请参阅第298行）将其扩展为一个数组的12个不同的数组。问题是我很难区分是降水与雪，颗粒和冰冻是混合降水，还是由于降水的组合而没有（n）。
1 TAF CYYZ 142340Z 1500/1606 10010KT 6SM -SN BR BKN040 OVC090
2 TEMPO 1500/1504 4SM -PLSN BR BKN020 OVC040
3 PROB30 1500/1503 VRB20G30KT 2SM +TSRA BR BKN015 OVC030CB
4 FM150400 18012KT P6SM BKN050
5 TEMPO 1504/1507 3SM -SHRA BR BKN015 OVC030
6 BECMG 1504/1506 22015KT
7 FM150700 23015G25KT P6SM BKN040
8 TEMPO 1510/1512 BKN020 BKN040
9 FM151200 23015G25KT P6SM OVC015
10 BECMG 1514/1516 23018G30KT
11 FM152000 24018G30KT 5SM -RA BR OVC012
12 FM160200 27015G25KT P6SM BKN020 BKN040'
我想知道我是否可以使用A，B，C，D，E代替数字 AAAA，巴巴
第264行的compare_function是我需要帮助的一个
例如
n 1
snow 10
pellets 100
freezing 1000
mix 10000
n 1
n + n 2
n + n + n 3
n + n + n + n 4
s 10
s+s 20
s+s+s 30
s+s+s+s 40
s+s+n+n 22
s+n 11
s+n+n 12
s+s+n 21
s+s+s+n 31
s+s+n+n 22
p 100
p+p 200
p+p+p 300
p+p+p+p 400
p+p+p+n 301
p+p+n+n 202
p+n+n+n 103
f 1000
f+f 2000
f+f+f 3000
f+f+f+f 4000
f+f+f+n 3001
f+f+n+n 2002
f+n+n+n 1003
m 10000
m+m 20000
m+m+m 30000
m+m+m+m 40000
p+f+s+n 1111
P+f+n+n 1102
p+f 1100
p+f+n 1101
s+p 110
s+f 1010
s+m 10010
f+p+p 1200
f+s+s 1020
p+f+s 1110
我认为这可能是一种方法，但我仍然可能缺少一些组合
winter_type={'s': 10|20|30|40|22|11|12|21|31|22,
'p': 100|200|300|400|301|202|103,
'f': 1000|2000|3000|4000|3001|2002|1003,
'm': 10000|20000|30000|40000|1111|1102|1100|1101|110|1010|10010|1200|1020|1110
'n' : 1|2|3|4}
这里是应该使用pyTAF从字符串中提取降水的时间
['2019-03-15 00:00', '2019-03-15 01:00', '2019-03-15 02:00', '2019-03-15 03:00', '2019-03-15 04:00', '2019-03-15 05:00', '2019-03-15 06:00', '2019-03-15 07:00', '2019-03-15 08:00', '2019-03-15 09:00', '2019-03-15 10:00', '2019-03-15 11:00', '2019-03-15 12:00', '2019-03-15 13:00', '2019-03-15 14:00', '2019-03-15 15:00', '2019-03-15 16:00', '2019-03-15 17:00', '2019-03-15 18:00', '2019-03-15 19:00', '2019-03-15 20:00', '2019-03-15 21:00', '2019-03-15 22:00', '2019-03-15 23:00', '2019-03-16 00:00', '2019-03-16 01:00', '2019-03-16 02:00', '2019-03-16 03:00', '2019-03-16 04:00', '2019-03-16 05:00']
这是结果时间
['2019-03-15 00:00', '2019-03-15 00:00', '2019-03-15 00:00', '2019-03-15 04:00', '2019-03-15 04:00', '2019-03-15 04:00', '2019-03-15 07:00', '2019-03-15 10:00', '2019-03-15 12:00', '2019-03-15 14:00', '2019-03-15 20:00', '2019-03-16 02:00'] ['2019-03-15 04:00', '2019-03-15 04:00', '2019-03-15 03:00', '2019-03-15 07:00', '2019-03-15 07:00', '2019-03-15 06:00', '2019-03-15 12:00', '2019-03-15 12:00', '2019-03-15 20:00', '2019-03-15 16:00', '2019-03-16 02:00', '2019-03-16 06:00']
['m', 'm', 'm', 'm', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n', 'n']
这是原始代码
# Import Libraries
import pytaf
import re
from datetime import datetime, timedelta
from dateutil import parser
import numpy as np
"""WARNING DO NOT PUT TAF IN FOR KBFM WILL NOT WORK"""
#values = "TAF AMD KORD 150028Z 1500/1606 24024G38KT P6SM VCSH OVC025 TEMPO 1500/1503 4SM -RA FM150300 24016G28KT P6SM VCSH OVC018 FM150600 24014G21KT P6SM VCSH BKN008 OVC012 FM151200 28015G24KT P6SM VCSH OVC020 TEMPO 1514/1517 4SM -RASN FM151800 29017G28KT P6SM BKN035 TEMPO 1519/1520 4SM -RASN "
values ='TAF CYYZ 142340Z 1500/1606 10010KT 6SM -SN BR BKN040 OVC090 TEMPO 1500/1504 4SM -PLSN BR BKN020 OVC040 PROB30 1500/1503 VRB20G30KT 2SM +TSRA BR BKN015 OVC030CB FM150400 18012KT P6SM BKN050 TEMPO 1504/1507 3SM -SHRA BR BKN015 OVC030 BECMG 1504/1506 22015KT FM150700 23015G25KT P6SM BKN040 TEMPO 1510/1512 BKN020 BKN040 FM151200 23015G25KT P6SM OVC015 BECMG 1514/1516 23018G30KT FM152000 24018G30KT 5SM -RA BR OVC012 FM160200 27015G25KT P6SM BKN020 BKN040'
def extractor_function(values):
#read values i.e. taf into the pytaf program
def read_taf_function(values):
taf = pytaf.TAF(values)
return(taf)
taf=read_taf_function(values)
# initailzing vars for time year and month (for leap years and tafs the have XX00/XX24 where XX is the the same day)
leap_year = 2020, 2024, 2028
month = [1,2,3,4,5,6,7,8,8,9,10,12]
dd = [31,28,31,30,31,30,31,31,30,31,30,31]
#
#utc time
#current_utc_time=datetime.utcnow()
#print(current_utc_time)
# header functiom
def header_time_information_function(taf):
index_time_stamp = []
yyyy = 2019
mm = 3
dd = 15
begintime = []
endtime = []
res2=[]
res3=[]
"""
Function built to extract time from pytaf using any Terminal Aerodrome Forecast
Extracts - The Issuance Time, Start Time, End Time
"""
taf_header = taf._taf_header
# if statement to know if leap year or not
if mm==1 or mm==3 or mm==5 or mm==7 or mm==8 or mm==10 or mm==12:
if dd==31 and int(taf_header["valid_till_hours"])==24:
dd=1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<31 and int(taf_header["valid_till_hours"])==24:
dd=dd+1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<31 and not int(taf_header["valid_till_hours"])==24:
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, int(taf_header["valid_till_date"]), int(taf_header["valid_till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
elif mm==4 or mm==6 or mm==9 or mm==11:
if dd==30 and int(taf_header["valid_till_hours"])==24:
dd=1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<30 and int(taf_header["valid_till_hours"])==24:
dd=dd+1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<30 and not int(taf_header["valid_till_hours"])==24:
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, int(taf_header["valid_till_date"]), int(taf_header["valid_till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
elif mm==2:
if yyyy==2020 or yyyy==2024:
if dd==29 and int(taf_header["valid_till_hours"])==24:
dd=1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<29 and int(taf_header["valid_till_hours"])==24:
dd=dd+1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<29 and not int(taf_header["valid_till_hours"])==24:
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, int(taf_header["valid_till_date"]), int(taf_header["valid_till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
else:
if dd==28 and int(taf_header["valid_till_hours"])==24:
dd=1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<28 and int(taf_header["valid_till_hours"])==24:
dd=dd+1
hh=int(taf_header["valid_till_hours"])==00
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, dd, hh, 00).strftime('%Y-%m-%d %H:%M')
elif dd<28 and not int(taf_header["valid_till_hours"])==24:
res2 = datetime(yyyy, mm, int(taf_header['valid_from_date']), int(taf_header['valid_from_hours']), 00).strftime('%Y-%m-%d %H:%M')
res3 = datetime(yyyy, mm, int(taf_header["valid_till_date"]), int(taf_header["valid_till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
begintime = res2
endtime = res3
return(begintime,endtime)
def timex_function(taf):
index_time_stamp = []
index_time_stamp.append(1)
yyyy = 2019
mm = 3
dd = 15
dumby=header_time_information_function(taf)
insertfromtime = []
begintime=list()
begintime.append(dumby[0])
endtime=list()
endtime.append(dumby[1])
# initilzing vars
regex = r"PROB\d{0,2}"
weather_groups=taf._weather_groups
#for val in weather_groups:
# print(val)
"""For Loop with assoicated if and if else to Pull Each Time (DD/HH:MM) in Each From Tempo Prob Becming Line in the Terminal Aerodrome Forecast"""
for i in range(1,len(weather_groups)):
# initilzing vars
res1=[]
res2=[]
fmtype=[]
#print(str(weather_groups[i]["header"]))
fmtype = str(weather_groups[i]["header"]["type"])
if fmtype == "FM":
res1 = datetime(yyyy, mm, int(weather_groups[i]["header"]["from_date"]), int(weather_groups[i]["header"]["from_hours"]), int( weather_groups[i]["header"]["from_minutes"])).strftime('%Y-%m-%d %H:%M')
begintime.append(res1)
endtime.append('-9999')
insertfromtime.append(res1)
index_time_stamp.append(1)
elif fmtype == "TEMPO":
res1 = datetime(yyyy, mm, int(weather_groups[i]["header"]["from_date"]), int(weather_groups[i]["header"]["from_hours"]),00).strftime('%Y-%m-%d %H:%M')
res2 = datetime(yyyy, mm, int(weather_groups[i]["header"]["till_date"]), int(weather_groups[i]["header"]["till_hours"]),00).strftime('%Y-%m-%d %H:%M')
begintime.append(res1)
endtime.append(res2)
index_time_stamp.append(2)
elif re.search(regex,fmtype):
res1 = datetime(yyyy, mm, int(weather_groups[i]["header"]["from_date"]), int(weather_groups[i]["header"]["from_hours"]), 00).strftime('%Y-%m-%d %H:%M')
res2 = datetime(yyyy, mm, int(weather_groups[i]["header"]["till_date"]), int(weather_groups[i]["header"]["till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
begintime.append(res1)
endtime.append(res2)
index_time_stamp.append(2)
elif fmtype =="BECMG":
res1 = datetime(yyyy, mm, int(weather_groups[i]["header"]["from_date"]), int(weather_groups[i]["header"]["from_hours"]), 00).strftime('%Y-%m-%d %H:%M')
res2 = datetime(yyyy, mm, int(weather_groups[i]["header"]["till_date"]), int(weather_groups[i]["header"]["till_hours"]), 00).strftime('%Y-%m-%d %H:%M')
begintime.append(res1)
endtime.append(res2)
index_time_stamp.append(2)
fmtype=[]
if index_time_stamp[len(index_time_stamp)-1]==1:
firstendtime =insertfromtime[0]
insertfromtime = insertfromtime[1:len(insertfromtime)]
endtime_shorten = endtime[0:len(endtime)-1]
reference00 = [i for i in range(len(endtime_shorten))]
val3 = 0
for val1,val2 in zip(endtime_shorten,reference00):
#print(val1)
if val1=='-9999':
print(val3)
endtime_shorten[val2]=insertfromtime[val3]
val3 = val3 + 1
endtime = list(endtime_shorten) + [endtime[len(endtime)-1]]
endtime = [firstendtime] + list(endtime[1:len(endtime)-1]) + [endtime[0]]
elif index_time_stamp[len(index_time_stamp)-1]==2:
firstendtime =insertfromtime[0]
insertfromtime = list(insertfromtime[1:len(insertfromtime)]) + [endtime[0]]
print(insertfromtime)
endtime = endtime[1:len(endtime)]
reference00 = [i for i in range(len(endtime))]
val3 = 0
for val1,val2 in zip(endtime,reference00):
print(val1,val2,endtime[val2])
if val1=='-9999':
endtime[val2]=insertfromtime[val3]
val3 = val3 + 1
endtime = [firstendtime] + list(endtime[0:len(endtime)])
print(begintime,endtime)
return(begintime,endtime)
def precip_extraction_function():
"""
Function built for extracting precip group
"""
# initilzing vars
precip_tf = []
precip_type = []
precip_groups = taf._raw_weather_groups
precip = {
'snow': r'\sSN\s|\s-SN\s|\s+SN\s',
'pellets': r'\sPL\s|\s-PL\s|\s+PL\s|\sIC\s|\s-IC\s|\s+IC\s',
'freezing': r'\sFZRA\s|\s-FZRA\s|\s+FZRA\s|\sFZDZ\s|\s-FZDZ\s|\s+FZDZ\s',
'mix': r'RAPL|PLRA|SNPL|PLSN|SNFZDZ|SNFZRA|RASN|SNRA|DZSN|SNDZ'}
for g in precip_groups:
precip_tf.append(' '.join([k for k, v in precip.items() if re.search(v, g)]))
for values in precip_tf:
if values == 'snow':
precip_type.append(100)
elif values == 'pellets':
precip_type.append(200)
elif values == 'freezing':
precip_type.append(300)
elif values == 'mix':
precip_type.append(400)
elif values == '':
precip_type.append(-999)
return(precip_type)
print(precip_extraction_function())
def datetime_range(start, end, delta):
current = start
while current < end:
yield current
current += delta
def time_range_function():
results=header_time_information_function(taf)
startime=datetime.strptime(results[0],"%Y-%m-%d %H:%M")
endtime=datetime.strptime(results[1], '%Y-%m-%d %H:%M')
reference_time = [dt.strftime('%Y-%m-%d %H:%M') for dt in datetime_range(startime, endtime, timedelta(hours=1))]
return(reference_time)
def comparing_function():
# winter precip is [number of line, number of reference time]
number_of_lines=precip_extraction_function()
reference_time = time_range_function()
reference_time_index = [i for i in range(len(reference_time))]
winter_precip = np.zeros((len(number_of_lines), len(reference_time)))
times=timex_function(taf)
gotime=times[0]
nogotime=times[1]
precip_tf = precip_extraction_function()
line_reference_index = [i for i in range(len(precip_tf))]
# for loop to loop thru the TAF lines
for values01,values02,values03,values04 in zip(gotime,nogotime,precip_tf,line_reference_index):
startime=datetime.strptime(values01,'%Y-%m-%d %H:%M')
endtime=datetime.strptime(values02, '%Y-%m-%d %H:%M')
# for loop to loop thru the reference time
for values05,values06 in zip(reference_time,reference_time_index):
currenttime=datetime.strptime(values05, '%Y-%m-%d %H:%M')
if parser.parse(str(startime))<=parser.parse(str(currenttime))<parser.parse(str(endtime)):
if values03==-999:
winter_precip[values04,values06] = 1
elif values03==100:
winter_precip[values04,values06] = 10
elif values03==200:
winter_precip[values04,values06] = 100
elif values03==300:
winter_precip[values04,values06] = 1000
elif values03==400:
winter_precip[values04,values06]= 10000
print(winter_precip)
winter_totals = np.sum(winter_precip,axis=0)
print(winter_totals)
winter_weather = list()
for values in winter_totals:
if values==10 and values==13:
winter_weather.append('s')
elif values>=100 and values<1000:
winter_weather.append('p')
elif values>=1000 and values<10000:
winter_weather.append('f')
elif values>=10000:
winter_weather.append('m')
elif values<10:
winter_weather.append('n')
print(len(winter_weather))
return(winter_weather)
def icao_station_info_function():
station_id = taf._taf_header['icao_code']
return(station_id)
return(comparing_function(),time_range_function(),icao_station_info_function())
return(timex_function(taf))
print(extractor_function(values))