def sunhis2initial(hisfile, icfile):
"""
Main function
"""
print '#####\nCreating initial condition file (%s) from history file (%s)...' % (
icfile, hisfile)
# Load the history file
sunhis = Spatial(hisfile, tstep=-1, klayer=[-99])
# Load the initial condition object
timeic = datetime.strftime(sunhis.time[-1], '%Y%m%d.%H%M%S')
sunic = InitialCond(hisfile, timeic)
# Load the last time step into each variable
sunic.h = sunhis.loadData(variable='eta').reshape((1, sunic.h.shape))
sunic.T = sunhis.loadData(variable='temp').reshape((1, ) + sunic.T.shape)
sunic.S = sunhis.loadData(variable='salt').reshape((1, ) + sunic.S.shape)
sunic.uc = sunhis.loadData(variable='uc').reshape((1, ) + sunic.uc.shape)
sunic.vc = sunhis.loadData(variable='vc').reshape((1, ) + sunic.vc.shape)
print sunic.h.shape
print sunic.T.shape
# Load the age
if sunhis.hasVar('agec'):
sunic.agec = sunhis.loadData(variable='agec').reshape((1, ) +
sunic.agec.shape)
sunic.agealpha = sunhis.loadData(
variable='agealpha').reshape((1, ) + sunic.agealpha.shape)
# Write to the output file
sunic.writeNC(icfile)
def _dumpic(self):
"""
Dump initial condition plots
For each variable (uc,vc,T,S,eta):
- surface plot
- seabed plot
"""
varnames = ['uc', 'vc', 'temp', 'salt', 'eta']
sun = Spatial(self.suntanspath + '/' + self.icfile, klayer=[0])
# Plot the surface variables
for vv in varnames:
h = plt.figure()
sun.variable = vv
sun.loadData()
sun.clim = [sun.data.min(), sun.data.max()]
sun.plot()
outfile = '%s/IC_%s_surface.png' % (self.plotdir, vv)
sun.savefig(outfile)
del h
# Plot the seabed variables
sun.klayer = [-1]
for vv in varnames:
h = plt.figure()
sun.variable = vv
sun.loadData()
sun.clim = [sun.data.min(), sun.data.max()]
sun.plot()
outfile = '%s/IC_%s_seabed.png' % (self.plotdir, vv)
sun.savefig(outfile)
del h
def suntans2untrim(ncfile, outfile, tstart, tend, grdfile=None):
"""
Converts a suntans averages netcdf file into untrim format
for use in particle tracking
"""
####
# Step 1: Load the suntans data object
####
sun = Spatial(ncfile, klayer=[-99])
# Calculate some other variables
sun.de = sun.get_edgevar(sun.dv, method='min')
sun.mark[sun.mark == 5] = 0
sun.mark[sun.mark == 3] = 2
sun.facemark = np.zeros((sun.Nc, ), dtype=np.int)
# Update the grad variable from the ascii grid file if supplied
if not grdfile == None:
print('Updating grid with ascii values...')
grd = Grid(grdfile)
sun.grad = grd.grad[:, ::-1]
###
# Step 2: Write the grid variables to a netcdf file
###
nc = Dataset(outfile, 'w', format='NETCDF4_CLASSIC')
# Global variable
nc.Description = 'UnTRIM history file converted from SUNTANS output'
# Write the dimensions
for dd in list(untrim_griddims.keys()):
if dd == 'time':
nc.createDimension(untrim_griddims[dd], 0)
elif dd == 'numsides':
nc.createDimension(untrim_griddims[dd], sun.maxfaces)
else:
nc.createDimension(untrim_griddims[dd], sun[dd])
for dd in other_dims:
nc.createDimension(dd, other_dims[dd])
###
# Step 3: Initialize all of the grid variables
###
def create_nc_var(name, dimensions, attdict,data=None, \
dtype='f8',zlib=False,complevel=0,fill_value=999999.0):
tmp=nc.createVariable(name, dtype, dimensions,\
zlib=zlib,complevel=complevel,fill_value=fill_value)
for aa in list(attdict.keys()):
tmp.setncattr(aa, attdict[aa])
if not data == None:
nc.variables[name][:] = data
# Make sure the masked cells have a value of -1
mask = sun['cells'].mask.copy()
sun['cells'][mask] = FILLVALUE
sun['face'][mask] = FILLVALUE
for vv in list(untrim_gridvars.keys()):
vname = untrim_gridvars[vv]
print('Writing grid variable %s (%s)...' % (vname, vv))
if vv == 'time':
continue
# add dz_min attribute to z_r variable
if vv == 'z_r':
ugrid[vname]['attributes'].update({'dz_min': 1e-5})
#sun[vv][:]=sun[vv][::-1]
sun[vv][:] = sun['z_w'][0:-1][::-1]
# Reverse the order of grad(???)
if vv == 'grad':
sun[vv][:] = sun[vv][:, ::-1]
## Fix one-based indexing
#if vv in ['cells','edges','grad']:
# mask = sun[vv][:]==-1
# tmp = sun[vv][:]+1
# tmp[mask]=-1
# #sun[vv][:]=sun[vv][:]+1
# create_nc_var(vname,ugrid[vname]['dimensions'],ugrid[vname]['attributes'],\
# data=tmp,dtype=ugrid[vname]['dtype'])
create_nc_var(vname,ugrid[vname]['dimensions'],ugrid[vname]['attributes'],\
data=sun[vv],dtype=ugrid[vname]['dtype'])
# Initialize the two time variables
vname = untrim_gridvars['time']
create_nc_var(vname,ugrid[vname]['dimensions'],ugrid[vname]['attributes'],\
dtype=ugrid[vname]['dtype'])
vname = 'Mesh2_data_time_string'
create_nc_var(vname,ugrid[vname]['dimensions'],ugrid[vname]['attributes'],\
dtype=ugrid[vname]['dtype'])
###
# Step 4: Initialize all of the time-varying variables (but don't write)
###
for vname in varnames:
print('Creating variable %s...' % (vname))
create_nc_var(vname,ugrid[vname]['dimensions'],ugrid[vname]['attributes'],\
dtype=ugrid[vname]['dtype'],zlib=True,complevel=1,fill_value=999999.)
###
# Step 5: Loop through all of the time steps and write the variables
###
tsteps = sun.getTstep(tstart, tend)
tdays = othertime.DaysSince(sun.time, basetime=datetime(1899, 12, 31))
for ii, tt in enumerate(tsteps):
# Convert the time to the untrim formats
timestr = datetime.strftime(sun.time[tt], '%Y-%m-%d %H:%M:%S')
print('Writing data at time %s (%d of %d)...' %
(timestr, tt, tsteps[-1]))
#Write the time variables
nc.variables['Mesh2_data_time'][ii] = tdays[ii]
nc.variables['Mesh2_data_time_string'][:, ii] = timestr
# Load each variable or calculate it and convert it to the untrim format
sun.tstep = [tt]
###
# Compute a few terms first
eta = sun.loadData(variable='eta')
U = sun.loadData(variable='U_F')
dzz = sun.getdzz(eta)
dzf = sun.getdzf(eta)
vname = 'Mesh2_sea_surface_elevation'
#print '\tVariable: %s...'%vname
nc.variables[vname][:, ii] = eta
vname = 'Mesh2_salinity_3d'
#print '\tVariable: %s...'%vname
tmp3d = sun.loadData(variable='salt')
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
vname = 'Mesh2_vertical_diffusivity_3d'
#print '\tVariable: %s...'%vname
tmp3d = sun.loadData(variable='nu_v')
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
vname = 'h_flow_avg'
#print '\tVariable: %s...'%vname
nc.variables[vname][:, :, ii] = U.swapaxes(0, 1)[:, ::-1]
vname = 'v_flow_avg'
#print '\tVariable: %s...'%vname
tmp3d = sun.loadData(variable='w') * sun.Ac # m^3/s
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
# Need to calculate a few terms for the other variables
vname = 'Mesh2_edge_wet_area'
#print '\tVariable: %s...'%vname
#dzf = sun.loadData(variable='dzf')
tmp3d = dzf * sun.df
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
vname = 'Mesh2_face_water_volume'
#print '\tVariable: %s...'%vname
#dzz = sun.loadData(variable='dzz')
tmp3d = dzz * sun.Ac
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
vname = 'Mesh2_face_wet_area'
#print '\tVariable: %s...'%vname
tmp3d = np.repeat(sun.Ac[np.newaxis, ...], sun.Nkmax, axis=0)
nc.variables[vname][:, :, ii] = tmp3d.swapaxes(0, 1)[:, ::-1]
# UnTRIM references from bottom to top i.e.
# k = 0 @ bed ; k = Nkmax-1 @ top
vname = 'Mesh2_edge_bottom_layer'
#print '\tVariable: %s...'%vname
#tmp2d = sun.Nkmax-sun.Nke # zero based
tmp2d = sun.Nkmax - sun.Nke + 1 # one based
nc.variables[vname][:, ii] = tmp2d
vname = 'Mesh2_edge_top_layer'
#print '\tVariable: %s...'%vname
etop = sun.loadData(variable='etop')
#tmp2d = sun.Nkmax-etop-1 # zero based
tmp2d = sun.Nkmax - etop # one based
nc.variables[vname][:, ii] = tmp2d
vname = 'Mesh2_face_bottom_layer'
#print '\tVariable: %s...'%vname
#tmp2d = sun.Nkmax-sun.Nk + 1 # zero based
tmp2d = sun.Nkmax - sun.Nk # one based
nc.variables[vname][:, ii] = tmp2d
vname = 'Mesh2_face_top_layer'
#print '\tVariable: %s...'%vname
ctop = sun.loadData(variable='ctop')
#tmp2d = sun.Nkmax-ctop-1 # zero based
tmp2d = sun.Nkmax - ctop # one based
nc.variables[vname][:, ii] = tmp2d
print(72 * '#')
print('\t Finished SUNTANS->UnTRIM conversion')
print(72 * '#')
# close the file
nc.close()
"""
Generates a series of animations
"""
from sunpy import Spatial
import numpy as np
import matplotlib.pyplot as plt
runname='SFBay3D'
ncfile = '%s/%s_0*.nc'%('data',runname)
k = 1 # depth layer
plt.figure()
sun = Spatial(ncfile,klayer=[k],variable='salt')
sun.tstep=np.arange(0,len(sun.time))
sun.loadData()
sun.clim = [28.0,32.0]
sun.animate(vector_overlay=False)
sun.saveanim('plots/%s_salt.mov'%runname)
sun.clim=None
plt.figure()
sun = Spatial(ncfile,klayer=[k],variable='uc')
sun.tstep=np.arange(0,len(sun.time))
sun.loadData()
sun.animate(vector_overlay=False)
sun.saveanim('plots/%s_uc.mov'%runname)
sun.clim=None
plt.figure()
sun = Spatial(ncfile,klayer=[k],variable='eta')
"""
Generates a series of animations from the suntans output
"""
from sunpy import Spatial
import numpy as np
import matplotlib.pyplot as plt
ncfile = 'rundata/Estuary_SUNTANS_00*nc'
plt.figure()
sun = Spatial(ncfile,klayer=[1],variable='salt')
sun.tstep=np.arange(0,len(sun.time))
sun.loadData()
sun.animate(vector_overlay=False)
sun.saveanim('plots/salt.mov')
plt.figure()
sun = Spatial(ncfile,klayer=[1],variable='temp')
sun.tstep=np.arange(0,len(sun.time))
sun.loadData()
sun.animate(vector_overlay=False)
sun.saveanim('plots/temp.mov')
plt.figure()
sun = Spatial(ncfile,variable='tau_y')
sun.tstep=np.arange(0,len(sun.time))
sun.loadData()
sun.animate(vector_overlay=False)
sun.saveanim('plots/tau_y.mov')
import numpy as np import matplotlib.pyplot as plt from datetime import timedelta from scipy.integrate import cumtrapz import pdb ### # Inputs ncfile = 'data/Heatflux_AVG.0' #cellindex=range(0,9) cellindex=[4] t0 = 0 ### sun = Spatial(ncfile,klayer=[-99]) sun.tstep = range(t0,sun.Nt) time = sun.time[sun.tstep] # Constants dt = sun.globalatts['dt']*sun.globalatts['ntaverage'] RHO0 = 1000.0 Cp = 4186.0 fac = (RHO0*Cp) area = sun.Ac[cellindex] sumarea = np.sum(area) depth = sun.dv[cellindex] volume = area*depth # Cell volume
