def get_uv_at_depth(dirname, fname, dep_ind):
filesU = general_functions.get_files(dirname, fname, 'grid_U')
filesV = general_functions.get_files(dirname, fname, 'grid_V')
y, x = slice(1, -1, None), slice(1, -1, None)
with scDataset(filesU) as dsU, scDataset(filesV) as dsV:
vozocrtx0 = dsU.variables['vozocrtx'][:, dep_ind, y, x]
vomecrty0 = dsV.variables['vomecrty'][:, dep_ind, y, x]
sozotaux = dsU.variables['sozotaux'][:, 0, 0]
depthu = dsU.variables['depthu'][:]
depthv = dsV.variables['depthv'][:]
with nc.Dataset(os.path.join(dirname, '1_mesh_mask.nc'), 'r') as dsM:
umask0 = dsM.variables['umask'][0, dep_ind, y, x]
vmask0 = dsM.variables['vmask'][0, dep_ind, y, x]
e1u = dsM.variables['e1u'][0, y, x]
e1v = dsM.variables['e1v'][0, y, x]
e2u = dsM.variables['e2u'][0, y, x]
umask = np.tile(umask0, (len(sozotaux), 1, 1))
vmask = np.tile(vmask0, (len(sozotaux), 1, 1))
vozocrtx = np.ma.array(vozocrtx0, mask=1 - umask)
vomecrty = np.ma.array(vomecrty0, mask=1 - vmask)
return vozocrtx, vomecrty, umask[0, ...], vmask[
0, ...], e1u, e1v, e2u, depthu, depthv, sozotaux
def pcourantw(files,meshmask):
"""Given a list of W filenames and a mesh mask, returns an array with the unscaled Courant numbers.
:arg files: list of W filenames
:arg meshmask: mesh mask
:type meshmask: :py:class:`netCDF4.Dataset`
:returns: Numpy MaskedArray with unscaled Courant numbers.
:rtype: :py:class: `numpy.ma.core.MaskedArray`
"""
with nc_tools.scDataset(files) as f: #merging files
nt,nz,ny,nx = f.variables['vovecrtz'].shape
delta_z = meshmask['e3w_1d'][0,...]
delta_z = delta_z[:,np.newaxis,np.newaxis]
wmax = np.zeros((nz,ny,nx))
for n in range(nt):
wtmp = np.abs(f.variables['vovecrtz'][n,:,:,:])
wmax = np.maximum(wtmp,wmax) #taking maximum over time
wbdz = wmax / delta_z
wbdzmax = np.zeros((ny,nx))
for m in range(nz):
wbdztmp = wbdz[m,...]
wbdzmax = np.maximum(wbdztmp,wbdzmax) #taking maximum over depth
tmask = meshmask['tmask'][0,0,...]
return ma.masked_array(wbdzmax, mask = 1-tmask)
def pcourantv(files,meshmask):
"""Given a list of V filenames and a mesh mask, returns an array with the unscaled Courant numbers.
:arg files: list of V filenames
:arg meshmask: mesh mask
:type meshmask: :py:class:`netCDF4.Dataset`
:returns: Numpy MaskedArray with unscaled Courant numbers.
:rtype: :py:class: `numpy.ma.core.MaskedArray`
"""
delta_y = meshmask['e2v'][:]
with nc_tools.scDataset(files) as f: #merging files
nt,nz,ny,nx = f.variables['vomecrty'].shape
vmax = np.zeros((nz,ny,nx))
for n in range(nt):
vtmp = np.abs(f.variables['vomecrty'][n,:,:,:])
vmax = np.maximum(vtmp,vmax) #taking maximum over time
vbdymax = np.zeros((ny,nx))
for m in range(nz):
vbdytmp = vmax[m,...] / delta_y[0,...]
vbdymax = np.maximum(vbdytmp,vbdymax) #taking maximum over depth
vmask = meshmask['vmask'][0,0,...]
return ma.masked_array(vbdymax, mask = 1-vmask)
def pcourantu(files,meshmask):
"""Given a list of U filenames and a mesh mask, returns an array with the unscaled Courant numbers.
:arg files: list of U filenames
:arg meshmask: mesh mask
:type meshmask: :py:class:`netCDF4.Dataset`
:returns: Numpy MaskedArray with unscaled Courant numbers.
:rtype: :py:class: `numpy.ma.core.MaskedArray`
"""
delta_x = meshmask['e1u'][:]
with nc_tools.scDataset(files) as f: #merging files
nt,nz,ny,nx = f.variables['vozocrtx'].shape
umax = np.zeros((nz,ny,nx))
for n in range(nt):
utmp = np.abs(f.variables['vozocrtx'][n,:,:,:])
umax = np.maximum(utmp,umax) #taking maximum over time
ubdxmax = np.zeros((ny,nx))
for m in range(nz):
ubdxtmp = umax[m,...] / delta_x[0,...]
ubdxmax = np.maximum(ubdxtmp,ubdxmax) #taking maximum over depth
umask = meshmask['umask'][0,0,...]
return ma.masked_array(ubdxmax, mask = 1-umask)
def get_vars_for_box(dirname, fname, meshmaskname, x_start, x_end, y_start,
y_end, flag):
if flag == 'U':
gridname = 'grid_U'
velname = 'vozocrtx'
depthname = 'depthu'
maskname = 'umask'
e1name = 'e1u'
e2name = 'e2u'
elif flag == 'V':
gridname = 'grid_V'
velname = 'vomecrty'
depthname = 'depthv'
maskname = 'vmask'
e1name = 'e1v'
e2name = 'e2v'
elif flag == 'W':
gridname = 'grid_W'
velname = 'vovecrtz'
depthname = 'depthw'
maskname = 'tmask'
e1name = 'e1t'
e2name = 'e2t'
filesU = general_functions.get_files(dirname, fname, 'grid_U')
with scDataset(filesU) as dsU:
sozotaux = dsU.variables['sozotaux'][:, 0, 0]
x, y = slice(x_start, x_end, None), slice(y_start, y_end, None)
files = general_functions.get_files(dirname, fname, gridname)
with scDataset(files) as ds:
vel0 = ds.variables[velname][:, :, y, x]
depth = ds.variables[depthname][:]
with nc.Dataset(os.path.join(dirname, meshmaskname), 'r') as dsM:
mask0 = dsM.variables[maskname][0, :, y, x]
mask_all = dsM.variables[maskname][0, :, :, :]
e1 = dsM.variables[e1name][0, y, x]
e2 = dsM.variables[e2name][0, y, x]
mask = np.tile(mask0, (len(sozotaux), 1, 1, 1))
vel = np.ma.array(vel0, mask=1 - mask)
return vel, mask, mask_all, depth, e1, e2, sozotaux
def get_variables_fluxes(dirname, filepattern, ind_plane, vmask):
files = general_functions.get_files(dirname, filepattern, 'grid_V')
x, y = slice(1, -1, None), int(ind_plane)
with scDataset(files) as ds:
vomecrty0 = ds.variables['vomecrty'][:, :, y, x]
vmask0 = vmask[:, y, :]
vmask = np.tile(vmask0, (vomecrty0.shape[0], 1, 1))
vomecrty = np.ma.array(vomecrty0, mask=1 - vmask)
return vomecrty
def get_variables_fluxes(dirname, filepattern, surface_mask):
files = general_functions.get_files(dirname, filepattern, 'grid_W')
x, y = slice(1, -1, None), slice(1, -1, None)
with scDataset(files) as ds:
vovecrtz0 = ds.variables['vovecrtz'][:, :, y, x]
surface_mask_f = np.tile(surface_mask, (vovecrtz0.shape[0], 1, 1, 1))
vovecrtz = np.ma.array(vovecrtz0, mask=1 - surface_mask_f)
return vovecrtz
def get_vars_at_depth(dirname, fname, dep_ind):
filesU = general_functions.get_files(dirname, fname, 'grid_U')
filesV = general_functions.get_files(dirname, fname, 'grid_V')
filesW = general_functions.get_files(dirname, fname, 'grid_W')
filesT = general_functions.get_files(dirname, fname, 'grid_T')
print('files')
y, x = slice(1, -1, None), slice(1, -1, None)
with scDataset(filesU) as dsU, scDataset(filesV) as dsV, scDataset(
filesW) as dsW, scDataset(filesT) as dsT:
vozocrtx0 = dsU.variables['vozocrtx'][:, dep_ind, y, x]
print('U')
vomecrty0 = dsV.variables['vomecrty'][:, dep_ind, y, x]
print('V')
vovecrtz0 = dsW.variables['vovecrtz'][:, dep_ind, y, x]
print('W')
vosaline0 = dsT.variables['vosaline'][:, dep_ind, y, x]
vosaline0_orig = dsT.variables['vosaline'][0, dep_ind, y, x]
print('S')
sozotaux = dsU.variables['sozotaux'][:, 0, 0]
depthu = dsU.variables['depthu'][:]
with nc.Dataset(os.path.join(dirname, '1_mesh_mask.nc'), 'r') as dsM:
umask0 = dsM.variables['umask'][0, dep_ind, y, x]
vmask0 = dsM.variables['vmask'][0, dep_ind, y, x]
tmask0 = dsM.variables['tmask'][0, dep_ind, y, x]
umask = np.tile(umask0, (len(sozotaux), 1, 1))
vmask = np.tile(vmask0, (len(sozotaux), 1, 1))
tmask = np.tile(tmask0, (len(sozotaux), 1, 1))
tmask_orig = np.tile(tmask0, (1, 1, 1))
vozocrtx = np.ma.array(vozocrtx0, mask=1 - umask)
vomecrty = np.ma.array(vomecrty0, mask=1 - vmask)
vovecrtz = np.ma.array(vovecrtz0, mask=1 - tmask)
vosaline = np.ma.array(vosaline0, mask=1 - tmask)
vosaline_orig = np.ma.array(vosaline0_orig, mask=1 - tmask_orig)
return vozocrtx, vomecrty, vovecrtz, vosaline, vosaline_orig, umask, vmask, tmask, depthu, sozotaux
def get_uv_at_depth_day(dirname, fname, dep_ind, day):
''' day 1 = 0 to 24 hrs -- time_ind 24 hrs
day 2 = 24 to 48 hrs -- time_ind 48 hrs
day 3 = 48 to 72 hrs -- time_ind 72 hrs
enter the actual day you want (no day 0).
'''
filesU = general_functions.get_files(dirname, fname, 'grid_U')
filesV = general_functions.get_files(dirname, fname, 'grid_V')
y, x = slice(1, -1, None), slice(1, -1, None)
time_ind = day * 24
with scDataset(filesU) as dsU, scDataset(filesV) as dsV:
vozocrtx0 = dsU.variables['vozocrtx'][time_ind - 24:time_ind, dep_ind,
y, x]
vomecrty0 = dsV.variables['vomecrty'][time_ind - 24:time_ind, dep_ind,
y, x]
sozotaux = dsU.variables['sozotaux'][time_ind - 24:time_ind, 0, 0]
depthu = dsU.variables['depthu'][:]
depthv = dsV.variables['depthv'][:]
with nc.Dataset(os.path.join(dirname, '1_mesh_mask.nc'), 'r') as dsM:
umask0 = dsM.variables['umask'][0, dep_ind, y, x]
vmask0 = dsM.variables['vmask'][0, dep_ind, y, x]
e1u = dsM.variables['e1u'][0, y, x]
e2u = dsM.variables['e2u'][0, y, x]
umask = np.tile(umask0, (len(sozotaux), 1, 1))
vmask = np.tile(vmask0, (len(sozotaux), 1, 1))
vozocrtx = np.ma.array(vozocrtx0, mask=1 - umask)
vomecrty = np.ma.array(vomecrty0, mask=1 - vmask)
vozocrtx_avg = np.mean(vozocrtx, axis=0)
vomecrty_avg = np.mean(vomecrty, axis=0)
return vozocrtx, vomecrty, vozocrtx_avg, vomecrty_avg, umask[
0, ...], vmask[0, ...], e1u, e2u, depthu, depthv, sozotaux
def get_vars_salt(dirname, fname, meshmaskname, dep_ind_slice, time_s, time_f,
y_end):
if y_end == None:
y_end = -1
else:
y_end = y_end
y, x = slice(1, y_end, None), slice(1, -1, None)
filesT = general_functions.get_files(dirname, fname, 'grid_T')
filesU = general_functions.get_files(dirname, fname, 'grid_U')
with scDataset(filesT) as dsT, scDataset(filesU) as dsU:
deptht = dsT.variables['deptht'][:]
if dep_ind_slice == None:
vosaline0 = dsT.variables['vosaline'][time_s:time_f, :, y, x]
else:
vosaline0 = dsT.variables['vosaline'][time_s:time_f, dep_ind_slice,
y, x]
sozotaux = dsU.variables['sozotaux'][time_s:time_f, 0, 0]
with nc.Dataset(os.path.join(dirname, meshmaskname), 'r') as dsM:
if dep_ind_slice == None:
tmask0 = dsM.variables['tmask'][0, :, y, x]
else:
tmask0 = dsM.variables['tmask'][0, dep_ind_slice, y, x]
tmask = np.tile(tmask0, (len(sozotaux), 1, 1, 1))
vosaline = np.ma.array(vosaline0, mask=1 - tmask)
if dep_ind_slice == None:
tmask_return = tmask
else:
tmask_return = tmask[0, 0, ...]
return vosaline, sozotaux, deptht, tmask_return
def get_sal_cross_zon(dirname, fname, y_ind, time_ind, z_cut):
filesT = general_functions.get_files(dirname, fname, 'grid_T')
x = slice(1, -1, None)
with scDataset(filesT) as dsT:
vosaline0 = dsT.variables['vosaline'][time_ind, :z_cut, y_ind, x]
deptht_cz = dsT.variables['deptht'][:z_cut]
with nc.Dataset(os.path.join(dirname, '1_mesh_mask.nc'), 'r') as dsM:
tmask0 = dsM.variables['tmask'][0, :z_cut, y_ind, x]
tmask_cz = np.tile(tmask0, (1, 1, 1))
vosaline_cz = np.ma.array(vosaline0, mask=1 - tmask_cz)
return vosaline_cz, tmask_cz, deptht_cz
def get_sozotaux(dirname, fname):
filesU = general_functions.get_files(dirname, fname, 'grid_U')
with scDataset(filesU) as dsU:
sozotaux = dsU.variables['sozotaux'][:, 0, 0]
return sozotaux
x_end = 185
y_start = 157
y_end = 197
# ------------------------------------------------
dirname = '/ocean/imachuca/Canyons/results_mackenzie/extended_domain/'+kind+'_'+case+'/'
fname = '1_MCKNZ_1h_20170101_201701*'
meshmaskname = '1_mesh_mask.nc'
time_end = 6*24
filesW = general_functions.get_files(dirname, fname, 'grid_W')
y,x = slice(y_start, y_end,None), slice(x_start, x_end,None)
with scDataset(filesW) as dsW:
vovecrtz = dsW.variables['vovecrtz'][:time_end, dep_ind, y, x] * 1000
with nc.Dataset(os.path.join(dirname, meshmaskname), 'r') as dsM:
gdepw = dsM.variables['gdepw_1d'][0, dep_ind]
return vovecrtz, gdepw
# ---------------------------------------------------------------
def get_varbs_nitrate(kind, case, dep_ind):
dirname = '/ocean/imachuca/Canyons/results_mackenzie/extended_domain/'+kind+'_'+case+'/'
fname = '1_MCKNZ_1h_20170101_201701*'
meshmaskname = '1_mesh_mask.nc'
time_end = 6*24