def schism(tmpdir, kwargs):
grid = pgrid.grid(type='tri2d',
grid_file=(DATA_DIR / 'hgrid.gr3').as_posix())
#update dem
xp = grid.Dataset.SCHISM_hgrid_node_x.values
yp = grid.Dataset.SCHISM_hgrid_node_y.values
kwargs.update({'grid_x': xp, 'grid_y': yp})
#get dem
df = pdem.dem(**kwargs)
grid.Dataset['depth'].loc[:] = -df.Dataset.ival.values
filename_ = str(tmpdir.join('hgrid_.gr3'))
#output to grid file
grid.to_file(filename_)
#read again new grid
grid_ = pgrid.grid(type='tri2d', grid_file=filename_)
#compare
return grid.Dataset.equals(grid_.Dataset)
def test_answer(tmpdir):
rpath = str(tmpdir) + '/'
df = pg.grid(type='tri2d', grid_file=GRID_FILE)
df.to_file(rpath + 'test.gr3')
dh = pg.grid(type='tri2d', grid_file=rpath + 'test.gr3')
assert df.Dataset.equals(dh.Dataset)
def create(self, **kwargs):
if not kwargs: kwargs = self.__dict__.copy()
# Grid
self.grid = pgrid.grid(type='r2d', **kwargs)
# set lat/lon from file
if hasattr(self, 'grid_file'):
kwargs.update({'lon_min': self.grid.Dataset.x.values.min()})
kwargs.update({'lon_max': self.grid.Dataset.x.values.max()})
kwargs.update({'lat_min': self.grid.Dataset.y.values.min()})
kwargs.update({'lat_max': self.grid.Dataset.y.values.max()})
nj, ni = self.grid.Dataset.lons.shape
self.nj, self.ni = nj, ni
kwargs.update({'ni': ni, 'nj': nj})
# get bathymetry
self.bath(**kwargs)
# get boundaries
self.bc()
#get meteo
if self.atm: self.force(**kwargs)
#get tide
if self.tide: self.tidebc()
self.config(**kwargs)
def read_folder(self, rfolder, **kwargs):
gfile = glob.glob(rfolder + '/*.grd') # Grid
dfile = glob.glob(rfolder + '/*.dep') # bathymetry
u = glob.glob(rfolder + '/*.amu') # meteo
v = glob.glob(rfolder + '/*.amv')
p = glob.glob(rfolder + '/*.amp')
#config
self.mdf = pd.read_csv(d[0], sep='=')
self.mdf = self.mdf.set_index(self.mdf.columns[0]) # set index
#grid
self.grid = pgrid.grid('r2d', grid_file=gfile[0])
#bath
self.dem.Dataset = d3d.from_dep(dfile[0])
#meteo
mf = []
mf.append(d3d.from_force(u[0], 'u10'))
mf.append(d3d.from_force(v[0], 'v10'))
mf.append(d3d.from_force(p[0], 'msl'))
self.meteo.Dataset = xr.merge(mf)
#---------------------------------------------------------------------
logger.exception('folder incomplete. Abort\n')
sys.exit(1)
def test_answer(tmpdir, window, coast):
df = pg.grid(type='tri2d',
geometry=window,
coastlines=coast,
rpath=str(tmpdir) + '/')
check = np.isnan(df.Dataset.depth.values).sum() == 0
assert check == True
def func(tmpdir, name):
filename = DATA_DIR / name
#read grid file
grid = pgrid.grid(type='tri2d', grid_file=filename)
filename_ = str(tmpdir.join('hgrid_.gr3'))
#output to grid file
grid.to_file(filename_)
#read again new grid
grid_ = pgrid.grid(type='tri2d', grid_file=filename_)
#cleanup
os.remove(filename_)
#compare
return grid.Dataset.equals(grid_.Dataset)
def test_schism_grid(tmpdir, dic):
grid = pg.grid(type = 'tri2d',geometry=dic, coastlines=natural_earth, rpath = str(tmpdir)+'/')
xg = grid.Dataset.SCHISM_hgrid_node_x.values
yg = grid.Dataset.SCHISM_hgrid_node_y.values
df = pdem.dem(**dic, grid_x=xg, grid_y=yg, dem_source=DEM_SOURCE) #get dem
df.adjust(natural_earth)
assert np.isnan(df.Dataset.fval.values).sum() == 0
def test_d3d_grid(tmpdir, dic):
grid = pg.grid(type = 'r2d', geometry=dic, resolution=.1, rpath = str(tmpdir)+'/')
gr = grid.Dataset
xp,yp=gr.lons, gr.lats
#get dem
df = pdem.dem(**dic, grid_x=xp, grid_y=yp, dem_source=DEM_SOURCE)
df.adjust(natural_earth)
assert np.isnan(df.Dataset.fval.values).sum() == 0
def set(self, **kwargs):
if isinstance(self.model, str):
self.model = pyPoseidon.read_model(self.model)
for attr, value in self.model.__dict__.items():
if not hasattr(self, attr): setattr(self, attr, value)
execute = get_value(self, kwargs, 'execute', False)
pwd = os.getcwd()
files = [
'bctides.in', 'launchSchism.sh', '/sflux/sflux_inputs.txt',
'/outputs/flux.out'
]
files_sym = [
'hgrid.gr3', 'hgrid.ll', 'manning.gr3', 'vgrid.in', 'drag.gr3',
'rough.gr3', 'station.in', 'windrot_geo2proj.gr3'
]
station_files = [
'/outputs/staout_1', '/outputs/staout_2', '/outputs/staout_3',
'/outputs/staout_4', '/outputs/staout_5', '/outputs/staout_6',
'/outputs/staout_7', '/outputs/staout_8', '/outputs/staout_9'
]
self.origin = self.model.rpath
self.date0 = self.model.date
if not os.path.exists(self.origin):
sys.stdout.write('Initial folder not present {}\n'.format(
self.origin))
sys.exit(1)
ppath = self.ppath
# create the folder/run path
rpath = self.cpath
if not os.path.exists(rpath):
os.makedirs(rpath)
copy2(ppath + self.tag + '_model.json', rpath) #copy the info file
# load model
with open(rpath + self.tag + '_model.json', 'rb') as f:
info = pd.read_json(f, lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
args = set(kwargs.keys()).intersection(
info.keys()) # modify dic with kwargs
for attr in list(args):
info[attr] = kwargs[attr]
info['config_file'] = ppath + 'param.nml'
#update the properties
info['start_date'] = self.date
info['time_frame'] = self.time_frame
info['end_date'] = self.date + pd.to_timedelta(self.time_frame)
info['meteo_source'] = self.meteo
info['rpath'] = rpath
# info['grid_file'] = ppath + '/hgrid.gr3'
# for attr, value in self.items():
# setattr(info, attr, value)
m = pmodel(**info)
# Grid
m.grid = pgrid.grid(type='tri2d', **info)
# get lat/lon from file
if hasattr(self, 'grid_file'):
info.update(
{'lon_min': m.grid.Dataset.SCHISM_hgrid_node_x.values.min()})
info.update(
{'lon_max': m.grid.Dataset.SCHISM_hgrid_node_x.values.max()})
info.update(
{'lat_min': m.grid.Dataset.SCHISM_hgrid_node_y.values.min()})
info.update(
{'lat_max': m.grid.Dataset.SCHISM_hgrid_node_y.values.max()})
# copy/link necessary files
logger.debug('copy necessary files')
for filename in files:
ipath = glob.glob(ppath + filename)
if ipath:
try:
copy2(ppath + filename, rpath + filename)
except:
dir_name, file_name = os.path.split(filename)
if not os.path.exists(rpath + dir_name):
os.makedirs(rpath + dir_name)
copy2(ppath + filename, rpath + filename)
logger.debug('.. done')
#copy the station files
logger.debug('copy station files')
for filename in station_files:
ipath = glob.glob(ppath + filename)
if ipath:
try:
copy2(ppath + filename, rpath + filename)
except:
dir_name, file_name = os.path.split(filename)
if not os.path.exists(rpath + dir_name):
os.makedirs(rpath + dir_name)
copy2(ppath + filename, rpath + filename)
logger.debug('.. done')
#symlink the station files
#logger.debug('symlink station files')
#for filename in station_files:
# ipath = glob.glob(self.path+self.folders[0] + filename)
# if ipath:
# if not os.path.exists(rpath + '/outputs/'):
# os.makedirs(rpath + '/outputs/')
# try:
# os.symlink(ipath[0],rpath + filename)
# except OSError as e:
# if e.errno == errno.EEXIST:
# logger.warning('Restart link present\n')
# logger.warning('overwriting\n')
# os.remove(rpath + filename)
# os.symlink(ipath[0],rpath + filename)
#logger.debug('.. done')
#symlink the big files
logger.debug('symlink model files')
for filename in files_sym:
ipath = glob.glob(self.origin + filename)
if ipath:
try:
os.symlink(ipath[0], rpath + filename)
except OSError as e:
if e.errno == errno.EEXIST:
logger.warning('Restart link present\n')
logger.warning('overwriting\n')
os.remove(rpath + filename)
os.symlink(ipath[0], rpath + filename)
logger.debug('.. done')
# create restart file
logger.debug('create restart file')
#check for combine hotstart
hotout = int((self.date - self.date0).total_seconds() /
info['params']['core']['dt'])
logger.debug('hotout_it = {}'.format(hotout))
resfile = glob.glob(ppath +
'/outputs/hotstart_it={}.nc'.format(hotout))
if not resfile:
# load model model from ppath
with open(ppath + self.tag + '_model.json', 'rb') as f:
ph = pd.read_json(f, lines=True).T
ph[ph.isnull().values] = None
ph = ph.to_dict()[0]
p = pmodel(**ph)
p.hotstart(it=hotout)
# link restart file
inresfile = '/outputs/hotstart_it={}.nc'.format(hotout)
outresfile = '/hotstart.nc'
logger.info('set restart\n')
try:
os.symlink(ppath + inresfile, rpath + outresfile)
except OSError as e:
if e.errno == errno.EEXIST:
logger.warning('Restart link present\n')
logger.warning('overwriting\n')
os.remove(rpath + outresfile)
os.symlink(ppath + inresfile, rpath + outresfile)
else:
raise e
#get new meteo
logger.info('process meteo\n')
flag = get_value(self, kwargs, 'update', [])
check = [
os.path.exists(rpath + 'sflux/' + f)
for f in ['sflux_air_1.0001.nc']
]
if (np.any(check) == False) or ('meteo' in flag):
m.force(**info)
if hasattr(self, 'meteo_split_by'):
times, datasets = zip(*m.meteo.Dataset.groupby(
'time.{}'.format(self.meteo_split_by)))
mpaths = [
'sflux/sflux_air_1.{:04d}.nc'.format(t + 1)
for t in np.arange(len(times))
]
for das, mpath in list(zip(datasets, mpaths)):
m.to_force(das,
vars=['msl', 'u10', 'v10'],
rpath=rpath,
filename=mpath,
date=self.date0)
else:
m.to_force(m.meteo.Dataset,
vars=['msl', 'u10', 'v10'],
rpath=rpath,
date=self.date0)
else:
logger.warning('meteo files present\n')
# modify param file
rnday_new = (self.date - self.date0).total_seconds() / (
3600 * 24.) + pd.to_timedelta(
self.time_frame).total_seconds() / (3600 * 24.)
hotout_write = int(rnday_new * 24 * 3600 /
info['params']['core']['dt'])
info['parameters'].update({
'ihot': 2,
'rnday': rnday_new,
'start_hour': self.date0.hour,
'start_day': self.date0.day,
'start_month': self.date0.month,
'start_year': self.date0.year
})
m.config(output=True, **info)
m.config_file = rpath + 'param.nml'
os.chdir(rpath)
#subprocess.call(rpath+'run_flow2d3d.sh',shell=True)
m.save()
if execute: m.run()
#cleanup
# os.remove(rpath+'hotstart.nc')
# save compiled nc file
#out = data(**{'solver':m.solver,'rpath':rpath,'savenc':True})
logger.info('done for date :' +
datetime.datetime.strftime(self.date, '%Y%m%d.%H'))
os.chdir(pwd)