#read in command line variables
if platform.system() == 'Linux':
base_dir = '/home/snegusse/modeling/brazos_river'
data_dir = '/home/snegusse/tmp'
tec_filename = 'tdff_curt.dat'
curtain_filename = 'brazos_centerline.shp'
curtain_file = os.path.join(base_dir, curtain_filename)
tec_file = os.path.join(data_dir, tec_filename)
param = 'tdff.63'
sfile = 19
nfile = 1
model = pyselfe.Dataset(os.path.join(data_dir, str(sfile) + '_' + param))
# Read in xy/node locations of profile line
cx, cy = read_curtain_shapefile(curtain_file)
#take every third point and remove points upstream of bz2
cx = cx[::-1]
cy = cy[::-1]
cx = cx[::3][-10:]
cy = cy[::3][-10:]
channel_orientation = calc_channel_orientation(cx, cy)
'river_boundary': np.array([.5, 1, 1, .5]),
'bz2': np.array([.5, 1., 1., 1., 1., .5]),
'straight_ds_bz3': np.array([.5, 1, 1, 1, 1, .5]),
'giww-u': np.array([.5, 1, 1, 1, 1, 1, .5]),
'giww-d': np.array([.5, 1, 1, 1, 1, 1, .5]),
'near_dow': np.array([.5, 1, 1, 1, 1, .5])
}
sites_sal_data = {}
sites_xvel_data = {}
sites_dp_data = {}
salt_flux = {}
flow_cfs = {}
mod_initial = (
pyselfe.Dataset(os.path.join(mod_dir, sal_init_file)),
pyselfe.Dataset(os.path.join(mod_dir, vel_init_file)),
)
[sal_t, tstep, eta, dp, sal_data] = \
mod_initial[0].read_time_series('salt.63', nfiles=nfiles,
datadir=mod_dir, sfile=sfile)
[vel_t, tstep, eta, dp, vel_data] = \
mod_initial[1].read_time_series('hvel.64',nfiles=nfiles,
datadir=mod_dir, sfile=sfile)
for profile in profile_nodes.keys():
flow_file = os.path.join(base_dir, mod_dir, profile + '_flow.csv')
hdf5_file = os.path.join(base_dir, mod_dir, profile + '.h5')
if os.path.exists(flow_file):
flow_data = pd.read_csv(flow_file,
sep=',',
sites_uvel_data = {}
sites_vvel_data = {}
sites_dp_data = {}
mod_t = {}
for i in mod_dirs.keys():
hdf5_file = os.path.join(base_dir, mod_dirs[i], i + '_' + \
'mod_data' + '.h5')
if os.path.exists(hdf5_file):
hdf5_storage = pd.io.pytables.HDFStore(hdf5_file, mode='r')
sites_sal_data[i] = hdf5_storage['salinity']
sites_uvel_data[i] = hdf5_storage['u_vel']
sites_vvel_data[i] = hdf5_storage['v_vel']
sites_dp_data[i] = hdf5_storage['depth']
else:
mod_initial[i] = (pyselfe.Dataset(os.path.join(mod_dirs[i],
sal_init_file)), pyselfe.Dataset(os.path.join(mod_dirs[i],
vel_init_file)),)
[sal_t, tstep, eta, dp, sal_data] = \
mod_initial[i][0].read_time_series('salt.63',
xy=brazos_sites.values,
nfiles=nfiles, datadir=mod_dirs[i],
sfile=sfile)
[vel_t, tstep, eta, dp, vel_data] = \
mod_initial[i][1].read_time_series('hvel.64',
xy=brazos_sites.values,
nfiles=nfiles, datadir=mod_dirs[i],
sfile=sfile)
sal_mod_datetimes = [mod_start_datetime + pd.datetools.Second(dt)
for dt in sal_t]
vel_mod_datetimes = [mod_start_datetime + pd.datetools.Second(dt)
for dt in vel_t]
if len(sys.argv)==1 or sys.argv[1]=='help' or sys.argv[1]=='-help' or sys.argv[1
]=='--help' :
location=runBash("which " + programname)
message = runBash("awk \'/^##/ {print $0}\' < " + location);
sys.exit(message)
#read in command line variables
datadir=sys.argv[1]
tecfile=sys.argv[2]
param=sys.argv[3]
nlevel=sys.argv[4]
nfile=int(sys.argv[5])
model = pyselfe.Dataset(datadir + '/1_'+param)
# level = nlevel - 1 because of zero indexing
try:
nlevel = int(nlevel)
[t,t_iter,eta,dp,data] = model.read_time_series(param,levels=nlevel-1,
nfiles=nfile,
sfile=1,
datadir=datadir)
except ValueError:
if nlevel == 'all':
[t,t_iter,eta,dp,data] = model.read_time_series(param,
nfiles=nfile,
sfile=1,
datadir=datadir)
data = data[:,:,1:,:].mean(axis=2)
mon_sites_file = '../field_data/corpus_station_list.csv'
selfe_data_dir = '/home/snegusse/modeling/corpus_christi_bay/laquinta_current_modeling/depth_sensitivty/47ft/windon/outputs/'
mon_sites = np.genfromtxt(mon_sites_file,
dtype=None,
names=True,
delimiter=',',
skip_header=1)
#convert from latlon to utm14
p = Proj(proj='utm', zone=14, ellps='WGS84')
xy = np.array(p(mon_sites['DDLon'], mon_sites['DDLat'])).transpose()
#initialize model data readers
selfe = pyselfe.Dataset(selfe_data_dir + '1_salt.63', nfiles=7)
for site, xy in zip(mon_sites, xy):
print 'processing site: ', site['Name']
pd = []
if 'tc0' in site['Name']:
data = np.genfromtxt('../field_data/' + site['Name'] + '.csv',
delimiter=',',
names='datetime,water_level,water_temperature',
dtype=[datetime, np.float, np.float],
missing_values='NA',
converters={'datetime': mk_tcoon_date})
d = {
'water_level': data['water_level'],
'water_temperature': data['water_temperature']
}