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residual_flow_flux.py
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residual_flow_flux.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Mar 28 14:22:31 2013
@author: SNegusse
"""
import os
import sys
sys.path.append('/home/snegusse/pyselfe/')
import numpy as np
import pandas as pd
import pyselfe
sfile = 1
nfiles = 2
mod_start_datetime = pd.datetime(2008,8,24,0,0)
no_dow_start_datetime = pd.datetime(2008,9,23,0,0)
density = 1020.
tidal_period = '1490min'
flux_calc_start_date = pd.datetime(2008,9,20,19)
flux_calc_end_date = pd.datetime(2008,9,25)
base_dir = '/home/snegusse/modeling/brazos_river/calibration_20080824'
mod_dirs = {'base_case': os.path.join(base_dir, 'base_case', 'outputs')}
#'fine': os.path.join(base_dir, 'grid_convergence', 'fine_grid_tvd',
# 'outputs')}
sal_init_file = str(sfile) + '_salt.63'
vel_init_file = str(sfile) + '_hvel.64'
mod_initial={}
sites_xy = pd.DataFrame(np.array([[246469.00 , 3226774.00, np.nan],
[ 251473.33, 3216482.68, np.nan],
[ 258762.88, 3213500.45, 62.],
[ 268056.17, 3204466.99, 103.],
[ 268006.08, 3204401.47, 103.],
[ 267495.05, 3198979.43, np.nan],
[ 276812.42, 3205896.17, np.nan] ,
[ 2730 , 3203521.88, np.nan]]),
index=['bz1','bz2','bz3','bz4','bz5',
'bz6u','icfr','frpt'],
columns=['x','y','orientation'])
brazos_sites = sites_xy.ix[['bz3','bz5'], ['x', 'y']]
sites_sal_data = {}
sites_uvel_data = {}
sites_vvel_data = {}
sites_dp_data = {}
mod_t = {}
for i in list(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]
sites_sal_data[i] = pd.Panel(sal_data[:,:,:,0],
major_axis=brazos_sites.index,
items=sal_mod_datetimes)
sites_uvel_data[i] = pd.Panel(vel_data[:,:,:,0],
major_axis=brazos_sites.index,
items=vel_mod_datetimes)
sites_vvel_data[i] = pd.Panel(vel_data[:,:,:,1],
major_axis=brazos_sites.index,
items=vel_mod_datetimes)
dp_dynamic = dp + eta
sites_dp_data[i] = pd.DataFrame(dp_dynamic, index=sal_mod_datetimes,
columns=brazos_sites.index.values)
hdf5_storage = pd.io.pytables.HDFStore(hdf5_file)
hdf5_storage['salinity'] = sites_sal_data[i]
hdf5_storage['u_vel'] = sites_uvel_data[i]
hdf5_storage['v_vel'] = sites_vvel_data[i]
hdf5_storage['depth'] = sites_dp_data[i]
hdf5_storage.close()
for site in brazos_sites.index:
site_sal_dict = {}
site_uvel_dict = {}
site_vvel_dict = {}
site_uprime_dict = {}
site_dp_dict = {}
site_salt_flux = {}
for sim in list(sites_sal_data.keys()):
site_sal_dict[sim] = sites_sal_data[sim].xs(site).T
site_uvel_dict[sim] = sites_uvel_data[sim].xs(site).T
site_vvel_dict[sim] = sites_vvel_data[sim].xs(site).T
site_uprime_dict[sim] = site_uvel_dict[sim] * \
np.cos(sites_xy.ix[site, 'orientation'] * np.pi / 180.) - \
site_vvel_dict[sim] * np.sin(sites_xy.ix[site, 'orientation'] * \
np.pi / 180.)
site_dp_dict[sim] = sites_dp_data[sim][site]
depth_avg_vel = site_uprime_dict[sim].mean(axis=1)
depth_avg_sal = site_sal_dict[sim].mean(axis=1)
site_flux_params = pd.DataFrame({'salinity': depth_avg_sal,
'velocity': depth_avg_vel,
'depth': site_dp_dict[sim]})
site_flux_params = site_flux_params[flux_calc_start_date:\
flux_calc_end_date]
tidal_avg_flux_param = site_flux_params.resample(tidal_period)
tidal_avg_flux_param = tidal_avg_flux_param[:-1]
site_salt_flux[sim] = tidal_avg_flux_param.prod(axis=1) * density