def load_nei2fvcom(filename, sidelength=True):
"""
Loads a .nei file and returns the data as a dictionary that mimics the structure of fvcom output as closely as possible.
"""
# Load the neifile
data = load_neifile(filename)
# Use lcc projection get x,y data
data['x'], data['y'], data['proj'] = pjt.lcc(data['lon'], data['lat'])
# Get nv for grid
data = get_nv(data)
# ncdatasort to make typically structures
data = dt.ncdatasort(data)
# get the model sidelength
if sidelength:
data = get_sidelength(data)
return data
def load_nei2fvcom(filename,sidelength=True):
"""
Loads a .nei file and returns the data as a dictionary that mimics the structure of fvcom output as closely as possible.
"""
# Load the neifile
data=load_neifile(filename)
# Use lcc projection get x,y data
data['x'],data['y'],data['proj']=pjt.lcc(data['lon'],data['lat'])
# Get nv for grid
data=get_nv(data)
# ncdatasort to make typically structures
data=dt.ncdatasort(data)
# get the model sidelength
if sidelength:
data=get_sidelength(data)
return data
import os
np.set_printoptions(precision=8, suppress=True)
name = 'kitimat3_128'
grid = 'kitimat3'
dim = '2d'
directory = '/home/moflaher/Desktop/workspace_python/figures/timeseries/curl/' + grid + '_' + name + '_' + dim + '/'
if not os.path.exists(directory):
os.makedirs(directory)
if 1 == 1:
fileDir = '/media/moflaher/My Book/kitimat3_timetests/kitimat3_128_0/output/'
data = dt.loadnc(fileDir, None, '2D')
data = dt.ncdatasort(data)
#region, passage, passageP = regions('kitimat3') # nargout=3
#nidx, uvidx = get_indexs(nodell, uvnodell, region, trinodes) # nargout=2
if 1 == 1:
a, b = data['ua'].shape # nargout=2
curl = np.zeros((b, a))
z_vec = np.zeros((1, a)).T
ua_in = np.hstack([data['ua'], z_vec]).T
va_in = np.hstack([data['va'], z_vec]).T
for i in np.arange(0, len(data['uvnodell'])):
e1 = data['nbe'][i, 0]
e2 = data['nbe'][i, 1]
e3 = data['nbe'][i, 2]
dudy = np.dot(data['a2u'][i, 0], ua_in[i, :]) + np.dot(
np.set_printoptions(precision=8,suppress=True)
name = 'kitimat3_128'
grid = 'kitimat3'
dim = '2d'
directory='/home/moflaher/Desktop/workspace_python/figures/timeseries/curl/' + grid + '_' + name + '_' + dim + '/'
if not os.path.exists(directory):
os.makedirs(directory)
if 1 == 1:
fileDir='/media/moflaher/My Book/kitimat3_timetests/kitimat3_128_0/output/'
data = dt.loadnc(fileDir,None,'2D')
data = dt.ncdatasort(data)
#region, passage, passageP = regions('kitimat3') # nargout=3
#nidx, uvidx = get_indexs(nodell, uvnodell, region, trinodes) # nargout=2
if 1 == 1:
a, b = data['ua'].shape # nargout=2
curl = np.zeros((b, a))
z_vec = np.zeros((1,a)).T
ua_in = np.hstack([data['ua'],z_vec]).T
va_in = np.hstack([data['va'],z_vec]).T
for i in np.arange(0,len(data['uvnodell'])):
def cross_shore_transect_2d(grid, name, region, vec, npt):
data = dt.loadnc('runs/' + grid + '/' + name + '/output/',
singlename=grid + '_0001.nc')
print('done load')
data = dt.ncdatasort(data, trifinder=True)
print('done sort')
cages = gt.loadcage('runs/' + grid + '/' + name + '/input/' + grid +
'_cage.dat')
if np.shape(cages) != ():
tmparray = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2, 0]], 0],
data['nodell'][data['nv'][i, [0, 1, 2, 0]], 1]))
for i in cages
]
color = 'g'
lw = .2
ls = 'solid'
vectorstart = np.array(vec[0])
vectorend = np.array(vec[1])
vectorx = np.array([vectorstart[0], vectorend[0]])
vectory = np.array([vectorstart[1], vectorend[1]])
snv = (vectorend - vectorstart) / np.linalg.norm(vectorend - vectorstart)
xi = np.linspace(vectorstart[0], vectorend[0], npt)
yi = np.linspace(vectorstart[1], vectorend[1], npt)
us = data['ua'].shape
savepath = 'data/cross_shore_transect/'
if not os.path.exists(savepath): os.makedirs(savepath)
plotpath = 'figures/png/' + grid + '_2d/cross_shore_transect/'
if not os.path.exists(plotpath): os.makedirs(plotpath)
nidx = dt.get_nodes(data, region)
f = plt.figure()
ax = f.add_axes([.125, .1, .775, .8])
triax = ax.tripcolor(data['trigrid'],
data['h'],
vmin=data['h'][nidx].min(),
vmax=data['h'][nidx].max())
ax.plot(xi, yi, 'k', lw=3)
if np.shape(cages) != ():
lseg_t = LC(tmparray, linewidths=lw, linestyles=ls, color=color)
coast = ax.add_collection(lseg_t)
coast.set_zorder(30)
pt.prettyplot_ll(ax, setregion=region, cb=triax, cblabel=r'Depth (m)')
f.savefig(plotpath + name + '_' + ('%f' % vectorx[0]) + '_' +
('%f' % vectorx[1]) + '_' + ('%f' % vectory[0]) + '_' +
('%f' % vectory[1]) + '_' + ('%d' % len(xi)) +
'_line_location.png',
dpi=600)
plt.close(f)
fillarray_u = np.empty((us[0], npt))
fillarray_v = np.empty((us[0], npt))
fillalong = np.empty((us[0], npt))
fillcross = np.empty((us[0], npt))
dist = np.empty((npt, ))
h = np.empty((npt, ))
print('interp uvw on path')
for i in range(0, len(xi)):
print(i)
fillarray_u[:, i] = interpE_at_loc(data, 'ua', [xi[i], yi[i]])
fillarray_v[:, i] = interpE_at_loc(data, 'va', [xi[i], yi[i]])
h[i] = interpN_at_loc(data, 'h', [xi[i], yi[i]])
print('Calc along path current')
for i in range(0, len(xi)):
print(i)
inner = np.inner(
np.vstack([fillarray_u[:, i], fillarray_v[:, i]]).T, snv)
along = np.vstack([inner * snv[0], inner * snv[1]]).T
tmpa = np.multiply(np.sign(np.arctan2(along[:, 1], along[:, 0])),
np.linalg.norm(along, axis=1))
fillalong[:, i] = tmpa
cross = np.vstack([fillarray_u[:, i], fillarray_v[:, i]]).T - along
tmpc = np.multiply(np.sign(np.arctan2(cross[:, 1], cross[:, 0])),
np.linalg.norm(cross, axis=1))
fillcross[:, i] = tmpc
dist[i] = (sw.dist([vectorstart[1], yi[i]], [vectorstart[0], xi[i]],
'km'))[0] * 1000
if np.shape(cages) != ():
incage = np.zeros((len(xi), ))
host = data['trigrid'].get_trifinder().__call__(xi, yi)
incage[np.in1d(host, cages)] = 1
savedic = {}
savedic['u'] = fillarray_u
savedic['v'] = fillarray_v
savedic['along'] = fillalong
savedic['cross'] = fillcross
savedic['distance'] = dist
savedic['h'] = h
savedic['lon'] = xi
savedic['lat'] = yi
if np.shape(cages) != ():
savedic['incage'] = incage
np.save(
savepath + grid + '_' + name + '_' + ('%f' % vectorx[0]) + '_' +
('%f' % vectorx[1]) + '_' + ('%f' % vectory[0]) + '_' +
('%f' % vectory[1]) + '_' + ('%d' % len(xi)) + '_2d.npy', savedic)
sio.savemat(savepath + 'matfiles/' + grid + '_' + name + '_' +
('%f' % vectorx[0]) + '_' + ('%f' % vectorx[1]) + '_' +
('%f' % vectory[0]) + '_' + ('%f' % vectory[1]) + '_' +
('%d' % len(xi)) + '_2d.mat',
mdict=savedic)
def cross_shore_transect_2d(grid,name,region,vec,npt):
data = dt.loadnc('runs/'+grid+'/'+name+'/output/',singlename=grid + '_0001.nc')
print('done load')
data = dt.ncdatasort(data,trifinder=True)
print('done sort')
cages=gt.loadcage('runs/'+grid+'/' +name+ '/input/' +grid+ '_cage.dat')
if np.shape(cages)!=():
tmparray=[list(zip(data['nodell'][data['nv'][i,[0,1,2,0]],0],data['nodell'][data['nv'][i,[0,1,2,0]],1])) for i in cages ]
color='g'
lw=.2
ls='solid'
vectorstart=np.array(vec[0])
vectorend=np.array(vec[1])
vectorx=np.array([vectorstart[0],vectorend[0]])
vectory=np.array([vectorstart[1],vectorend[1]])
snv=(vectorend-vectorstart)/np.linalg.norm(vectorend-vectorstart)
xi=np.linspace(vectorstart[0],vectorend[0],npt)
yi=np.linspace(vectorstart[1],vectorend[1],npt)
us=data['ua'].shape
savepath='data/cross_shore_transect/'
if not os.path.exists(savepath): os.makedirs(savepath)
plotpath='figures/png/'+grid+'_2d/cross_shore_transect/'
if not os.path.exists(plotpath): os.makedirs(plotpath)
nidx=dt.get_nodes(data,region)
f=plt.figure()
ax=f.add_axes([.125,.1,.775,.8])
triax=ax.tripcolor(data['trigrid'],data['h'],vmin=data['h'][nidx].min(),vmax=data['h'][nidx].max())
ax.plot(xi,yi,'k',lw=3)
if np.shape(cages)!=():
lseg_t=LC(tmparray,linewidths = lw,linestyles=ls,color=color)
coast=ax.add_collection(lseg_t)
coast.set_zorder(30)
pt.prettyplot_ll(ax,setregion=region,cb=triax,cblabel=r'Depth (m)')
f.savefig(plotpath + name+'_'+('%f'%vectorx[0])+'_'+('%f'%vectorx[1])+'_'+('%f'%vectory[0])+'_'+('%f'%vectory[1])+'_'+('%d'%len(xi))+'_line_location.png',dpi=600)
plt.close(f)
fillarray_u=np.empty((us[0],npt))
fillarray_v=np.empty((us[0],npt))
fillalong=np.empty((us[0],npt))
fillcross=np.empty((us[0],npt))
dist=np.empty((npt,))
h=np.empty((npt,))
print('interp uvw on path')
for i in range(0,len(xi)):
print(i)
fillarray_u[:,i]=interpE_at_loc(data,'ua',[xi[i],yi[i]])
fillarray_v[:,i]=interpE_at_loc(data,'va',[xi[i],yi[i]])
h[i]=interpN_at_loc(data,'h',[xi[i],yi[i]])
print('Calc along path current')
for i in range(0,len(xi)):
print(i)
inner=np.inner(np.vstack([fillarray_u[:,i],fillarray_v[:,i]]).T,snv)
along=np.vstack([inner*snv[0],inner*snv[1]]).T
tmpa=np.multiply(np.sign(np.arctan2(along[:,1],along[:,0])),np.linalg.norm(along,axis=1))
fillalong[:,i]=tmpa
cross=np.vstack([fillarray_u[:,i],fillarray_v[:,i]]).T-along
tmpc=np.multiply(np.sign(np.arctan2(cross[:,1],cross[:,0])),np.linalg.norm(cross,axis=1))
fillcross[:,i]=tmpc
dist[i]=(sw.dist([vectorstart[1], yi[i]],[vectorstart[0], xi[i]],'km'))[0]*1000;
if np.shape(cages)!=():
incage=np.zeros((len(xi),))
host=data['trigrid'].get_trifinder().__call__(xi,yi)
incage[np.in1d(host,cages)]=1
savedic={}
savedic['u']=fillarray_u
savedic['v']=fillarray_v
savedic['along']=fillalong
savedic['cross']=fillcross
savedic['distance']=dist
savedic['h']=h
savedic['lon']=xi
savedic['lat']=yi
if np.shape(cages)!=():
savedic['incage']=incage
np.save(savepath+grid+'_'+name+'_'+('%f'%vectorx[0])+'_'+('%f'%vectorx[1])+'_'+('%f'%vectory[0])+'_'+('%f'%vectory[1])+'_'+('%d'%len(xi))+'_2d.npy',savedic)
sio.savemat(savepath+'matfiles/'+grid+'_'+name+'_'+('%f'%vectorx[0])+'_'+('%f'%vectorx[1])+'_'+('%f'%vectory[0])+'_'+('%f'%vectory[1])+'_'+('%d'%len(xi))+'_2d.mat',mdict=savedic)
