Sonde Namespace Reference

ゾンデデータ取得・描画 More...

Functions
	ll2dist (lat1, lon1, lat2, lon2)

Variables
bool	savefig = True
str	dir_out = "./fig/"
bool	by_target_pos = True
float	lon0 = 139.7671248
float	lat0 = 35.6812362
bool	by_target_name = not by_target_pos
str	tname = "潮岬"
int	year = 2007
int	month = 7
int	day = 15
int	hour = 9
	jstdatetime = datetime.datetime(year,month,day,hour)
	utcdatetime = jstdatetime-datetime.timedelta(hours=9)
str	datatype0 = "hourly"
dict	varnamedic = {"気圧(hPa)":"PRES (hPa)", "ジオポテンシャル 高度(m)" : "Z (m)" , "気温(℃)":"TEMP (℃)", "相対湿度(%)":"RH (%)", "風速(m/s)":"WSPD (m/s)","風向(°)":"WDIR (°)"}
str	url = "https://www.data.jma.go.jp/obd/stats/etrn/upper/select/prefecture.php?year=&month=&day=&hour=&atm=&point="
	html = urllib.request.urlopen(url)
	soup = BeautifulSoup(html, 'html.parser')
	elements = soup.find_all('area')
list	station_etc_list = []
list	station_list = []
list	station_link_list = []
list	station_lat_list = [float(etc.split("javascript:viewPoint(")[1].split(",")[3][1:-1]) + float(etc.split("javascript:viewPoint(")[1].split(",")[4][1:-1])/60 for etc in station_etc_list]
list	station_lon_list = [float(etc.split("javascript:viewPoint(")[1].split(",")[5][1:-1]) + float(etc.split("javascript:viewPoint(")[1].split(",")[6][1:-1])/60 for etc in station_etc_list]
	lat = np.array(station_lat_list)
	lon = np.array(station_lon_list)
	dist = ll2dist(lat0,lon0,lat,lon)
	argmin_dist = np.argmin(dist)
	station_index = argmin_dist
list	station = station_list[station_index]
list	station_link = station_link_list[station_index]
list	lon_target = station_lon_list[station_index]
list	lat_target = station_lat_list[station_index]
str	datatype = datatype0 + "_usp.php?"
	fig
	ax
	figsize
	s
	table = pd.read_html(url)
	df = table[1]
	collist = df.columns
list	varlist = []
	var = df[col].values
list	pres = varlist[0]
list	z = varlist[1]
	time_target = jstdatetime.strftime("%Y-%m-%d %H hrs")
	marker
str	flabel = f"Sonde_{varnamedic[col].split(' ')[0]}_{time_target.replace(' ','_')}_lon{lon_target}_lat{lat_target}_{station}"

Detailed Description

ゾンデデータ取得・描画

指定した水平地点の近くのゾンデデータを取得し鉛直プロファイルを描画

Author

Tomoro Yanase, Team SCALE

Note

Function Documentation

ll2dist()

ll2dist	(		lat1,
			lon1,
			lat2,
			lon2 )

Variable Documentation

argmin_dist

argmin_dist = np.argmin(dist)

ax

ax

by_target_name

bool by_target_name = not by_target_pos

by_target_pos

bool by_target_pos = True

collist

collist = df.columns

datatype

str datatype = datatype0 + "_usp.php?"

datatype0

str datatype0 = "hourly"

day

int day = 15

df

df = table[1]

dir_out

str dir_out = "./fig/"

dist

dist = ll2dist(lat0,lon0,lat,lon)

elements

elements = soup.find_all('area')

fig

fig

figsize

figsize

flabel

str flabel = f"Sonde_{varnamedic[col].split(' ')[0]}_{time_target.replace(' ','_')}_lon{lon_target}_lat{lat_target}_{station}"

hour

int hour = 9

html

html = urllib.request.urlopen(url)

jstdatetime

jstdatetime = datetime.datetime(year,month,day,hour)

lat

lat = np.array(station_lat_list)

lat0

float lat0 = 35.6812362

lat_target

lat_target = station_lat_list[station_index]

lon

lon = np.array(station_lon_list)

lon0

float lon0 = 139.7671248

lon_target

lon_target = station_lon_list[station_index]

marker

marker

month

int month = 7

pres

list pres = varlist[0]

s

s

savefig

bool savefig = True

soup

soup = BeautifulSoup(html, 'html.parser')

station

list station = station_list[station_index]

station_etc_list

list station_etc_list = []

station_index

list station_index = argmin_dist

station_lat_list

list station_lat_list = [float(etc.split("javascript:viewPoint(")[1].split(",")[3][1:-1]) + float(etc.split("javascript:viewPoint(")[1].split(",")[4][1:-1])/60 for etc in station_etc_list]

station_link

list station_link = station_link_list[station_index]

station_link_list

list station_link_list = []

station_list

list station_list = []

station_lon_list

list station_lon_list = [float(etc.split("javascript:viewPoint(")[1].split(",")[5][1:-1]) + float(etc.split("javascript:viewPoint(")[1].split(",")[6][1:-1])/60 for etc in station_etc_list]

table

table = pd.read_html(url)

time_target

time_target = jstdatetime.strftime("%Y-%m-%d %H hrs")

tname

str tname = "潮岬"

url

str url = "https://www.data.jma.go.jp/obd/stats/etrn/upper/select/prefecture.php?year=&month=&day=&hour=&atm=&point="

utcdatetime

utcdatetime = jstdatetime-datetime.timedelta(hours=9)

var

var = df[col].values

varlist

list varlist = []

varnamedic

dict varnamedic = {"気圧(hPa)":"PRES (hPa)", "ジオポテンシャル 高度(m)" : "Z (m)" , "気温(℃)":"TEMP (℃)", "相対湿度(%)":"RH (%)", "風速(m/s)":"WSPD (m/s)","風向(°)":"WDIR (°)"}

year

int year = 2007

z

list z = varlist[1]