def __init__(self,**kwargs):
rpath = kwargs.get('rpath','./d3d/')
folders = kwargs.get('folders',None) #[os.path.join(os.path.abspath(loc),name) for name in os.listdir(loc) if os.path.isdir(os.path.join(loc,name))]
if folders :
self.folders = folders
else:
self.folders = [rpath]
#check if many tags present
ifiles = glob.glob(self.folders[0]+'/*_model.json')
if len(ifiles) > 1:
#---------------------------------------------------------------------
logger.warning('more than one configuration, specify tag argument \n')
#---------------------------------------------------------------------
tag = kwargs.get('tag', None)
if tag :
ifile = self.folders[0]+'/'+tag+'_model.json'
else:
ifile = ifiles[0]
#---------------------------------------------------------------------
logger.info('reading data based on {} \n'.format(ifile))
#---------------------------------------------------------------------
with open(ifile, 'rb') as f:
info = pd.read_json(f,lines=True).T
info[info.isnull().values] = None
self.info = info.to_dict()[0]
grid=r2d.read_file(self.folders[0]+'/'+self.info['tag']+'.grd')
deb=np.loadtxt(self.folders[0]+'/'+self.info['tag']+'.dep')
#create mask
d=deb[1:-1,1:-1]
self.w=d==-999.
b=deb[:-1,:-1]
b[b==-999.]=np.nan
self.dem = xr.Dataset({'bathymetry': (['latitude', 'longitude'], -b)},
coords={'longitude': ('longitude', grid.lons[0,:]),
'latitude': ('latitude', grid.lats[:,0])})
self.grid = grid
# READ DATA
nfiles = [folder +'/'+'trim-'+self.info['tag']+'.nc' for folder in self.folders]
ds = xr.open_mfdataset(nfiles, combine='by_coords',data_vars ='minimal')
self.Dataset=ds
#clean duplicates
self.Dataset = self.Dataset.sel(time=~self.Dataset.indexes['time'].duplicated())
dic = self.info.copy() # start with x's keys and values
dic.update(kwargs) # modifies z with y's keys and values & returns None
if 'sa_date' not in dic.keys():
dic.update({'sa_date':self.Dataset.time.values[0]})
if 'se_date' not in dic.keys():
dic.update({'se_date':self.Dataset.time.values[-1]})
self.obs = obs(**dic)
def __init__(self,**kwargs):
rpath = kwargs.get('rpath','./schism/')
folders = kwargs.get('folders',None) #[os.path.join(os.path.abspath(loc),name) for name in os.listdir(loc) if os.path.isdir(os.path.join(loc,name))]
if folders :
self.folders = folders
else:
self.folders = [rpath]
datai=[]
tag = kwargs.get('tag', 'schism')
misc = kwargs.get('misc', {})
for folder in self.folders:
logger.info('Combining output for folder {}\n'.format(folder))
xdat = glob.glob(folder + '/outputs/schout_[!0]*.nc')
xdat.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
if len(xdat) > 0:
datai.append(xdat) #append to list
else: #run merge output
with open(folder + '/' + tag +'_model.json', 'r') as f:
info = pd.read_json(f,lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
p = pm.model(**info)
p.misc = misc
p.results()
self.misc = p.misc
xdat = glob.glob(folder + '/outputs/schout_[!0]*.nc')
xdat.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
datai.append(xdat) #append to list
self.Dataset = xr.open_mfdataset(datai,combine='by_coords',data_vars='minimal')
with open(self.folders[-1] + '/' + tag +'_model.json', 'r') as f:
info = pd.read_json(f,lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
p = pm.model(**info)
logger.info('Retrieve station timeseries if any\n')
dstamp = kwargs.get('dstamp', info['date'])
try:
p.get_station_data(dstamp=dstamp)
self.time_series = p.time_series
except:
logger.info('no station data loaded')
dic={}
try:
with open(self.folders[0]+ '/' + tag +'_model.json', 'r') as f:
info = pd.read_json(f,lines=True).T
info[info.isnull().values] = None
self.info = info.to_dict()[0]
dic = self.info.copy() # start with x's keys and values
dic.update(kwargs) # modifies z with y's keys and values & returns None
except:
pass
if 'sa_date' not in dic.keys():
dic.update({'sa_date':self.Dataset.time.values[0]})
if 'se_date' not in dic.keys():
dic.update({'se_date':self.Dataset.time.values[-1]})
if 'lon_min' not in dic.keys():
dic.update({'lon_min':self.Dataset.SCHISM_hgrid_node_x.values.min()})
if 'lon_max' not in dic.keys():
dic.update({'lon_max':self.Dataset.SCHISM_hgrid_node_x.values.max()})
if 'lat_min' not in dic.keys():
dic.update({'lat_min':self.Dataset.SCHISM_hgrid_node_y.values.min()})
if 'lat_max' not in dic.keys():
dic.update({'lat_max':self.Dataset.SCHISM_hgrid_node_y.values.max()})
logger.info('Retrieve observations info\n')
self.obs = obs(**dic)
ret = kwargs.get('online',False)
if ret is True:
logger.info('collect observational data')
tgs = self.obs.locations.loc[self.obs.locations.Group=='TD UNESCO']
dic={}
for i in tgs.index:
# print(i, tgs.loc[i].Name.strip())
while True:
p = self.obs.iloc(i)
if p is not None:
if p.shape[0]>1:
p = p.dropna()
break
dic.update({tgs.loc[i].Name.strip():p})
tg = pd.concat(dic, axis=0, sort=True)
try:
tg = tg.drop('TimeUTC',axis=1)
except:
pass
tg.to_csv(self.folders[0]+ '/' + 'obs.csv')
self.obs.data = tg