def load_scenarios(mydate,
scenario_ids=range(0, 21),
latBound=[-90, 90],
lonBound=[0, 360],
timeSteps=[0, 64]):
"""
Loads previously downloaded scenarios and returns the corresponding list of :class:`weatherTLKT.Weather` objects.
:param string mydate: 'yyyymmdd' date of the day starting the weather forecast in US format
:param scenario_ids: range covering the forecasts scenarios we want to download
:param list(float,float) latBound: [latmin, latmax], latitude boundaries of the domain on which the forecast is desired.
If smaller than domain of stored object, returns a cropped object.
Returns stored object otherwise
:param list(float,float) lonBound: [lonmin, lonmax], longitude boundaries of the domain on which the forecast is desired.
If smaller than domain of stored object, returns a cropped object.
Returns stored object otherwise
:param list(int,int) timeSteps: [min_t_index, max_t_index], time span of the desired forecast.
If smaller than domain of stored object, returns a cropped object.
Returns stored object otherwise
:return: List of of :class:`weatherTLKT.Weather`
:rtype: list()
"""
pathToSaveObj = []
weather_scen = []
for ii in scenario_ids:
if ii < 10:
s_id = '0' + str(ii)
else:
s_id = str(ii)
pathToSaveObj.append(('../data/' + mydate + '_' + s_id + '00z.obj'))
weather_scen.append(
Weather.load(pathToSaveObj[ii], latBound, lonBound, timeSteps))
print("Loaded : " + pathToSaveObj[-1])
return weather_scen
import copy
import pickle
import sys
sys.path.append("../solver")
#from MyTree import Tree
from worker import Tree
# %% We load the forecast files
#ATTENTION il faudra prendre le fichier de vent moyen à terme!!!
mydate = '20180108'
modelcycle = '0100z'
pathToSaveObj = '../data/' + mydate + '_gep_' + modelcycle + '.obj'
Wavg = Weather.load(pathToSaveObj)
Wavg=Wavg.crop(latBound=[40, 50], lonBound=[360 - 15, 360])
#mydate = '20170519'
#modelcycle = '00'
#pathToSaveObj = '../data/' + mydate + '_' + modelcycle + '.obj'
#Wavg = Weather.load(pathToSaveObj)
# %% We shift the times so that all times are in the correct bounds for interpolations
Tini = Wavg.time[0]
Wavg.time = Wavg.time - Tini
# %% We set up the parameters of the simulation
# times=np.arange(0,min([Wavg.time[-1],Wspr.time[-1]]),1*HOURS_TO_DAY)
# Tf=len(times)
lonBound = [-10 + 360, 360]
url = []
pathToSaveObj = []
urlold = 'http://nomads.ncep.noaa.gov:9090/dods/gfs_0p25/gfs20171014/gfs_0p25_00z'
for i in range(2):
url.append(website + 'gfs_' + resolution[i] + '/gfs' + mydate + '/gfs_' +
resolution[i] + '_' + modelcycle + 'z')
pathToSaveObj.append('../data/' + mydate + '_gfs_' + resolution[i] +
'.obj')
# launch in real python console
# Weather.download(url[0],pathToSaveObj[0],latBound=latBound,lonBound=lonBound,timeSteps=[0,81])
# Weather.download(url[1],pathToSaveObj[1],latBound=latBound,lonBound=lonBound,timeSteps=[0,81])
# %%
weather025 = Weather.load(pathToSaveObj[0])
weather1 = Weather.load(pathToSaveObj[1])
instant = 40
#weather025.plotMultipleQuiver(otherWeather = weather1)
time = weather025.time[instant]
weather1.Interpolators()
error = np.zeros((len(weather025.lat), len(weather025.lon)))
interp_u = np.zeros((len(weather025.lat), len(weather025.lon)))
interp_v = np.zeros((len(weather025.lat), len(weather025.lon)))
for i, lat in enumerate(weather025.lat):
for j, lon in enumerate(weather025.lon):
if lat >= min(weather1.lat) and lat <= max(
weather1.lat) and lon >= min(weather1.lon) and lon <= max(
weather1.lon):