def test_xarray_with_coords():
pytest.importorskip('dask')
SA_chunk = SA.chunk(chunks={'y': 1, 't': 1})
CT_chunk = CT.chunk(chunks={'y': 1, 't': 1})
lat_chunk = lat.chunk(chunks={'y': 1})
# Dimensions and cordinates match:
expected = gsw.sigma0(SA_vals, CT_vals)
xarray = gsw.sigma0(SA, CT)
chunked = gsw.sigma0(SA_chunk, CT_chunk)
assert_allclose(xarray, expected)
assert_allclose(chunked, expected)
# Broadcasting along dimension required (dimensions known)
expected = gsw.alpha(SA_vals, CT_vals, p_vals[np.newaxis, :, np.newaxis])
xarray = gsw.alpha(SA, CT, p)
chunked = gsw.alpha(SA_chunk, CT_chunk, p)
assert_allclose(xarray, expected)
assert_allclose(chunked, expected)
# Broadcasting along dimension required (dimensions unknown/exclusive)
expected = gsw.z_from_p(p_vals[:, np.newaxis], lat_vals[np.newaxis, :])
xarray = gsw.z_from_p(p, lat)
chunked = gsw.z_from_p(p, lat_chunk)
assert_allclose(xarray, expected)
assert_allclose(chunked, expected)
def interpolate(self):
self.ipres = range(int(min(self.pres)),int(max(self.pres)))
if len(self.pres)>4:
self.isals = np.interp(self.ipres,self.pres,self.sals)
self.itemps = np.interp(self.ipres,self.pres,self.temps)
if hasattr(self,"knownu"):
self.iknownu = np.interp(self.ipres,self.pres,self.knownu)
self.iknownv = np.interp(self.ipres,self.pres,self.knownv)
if hasattr(self,"knownpsi"):
self.iknownpsi = np.interp(self.ipres,self.pres,self.knownpsi)
if hasattr(self,"kapredi"):
self.ikapredi = np.interp(self.ipres,self.pres,self.kapredi)
self.idiffkr = np.interp(self.ipres,self.pres,self.diffkr)
self.ikapgm = np.interp(self.ipres,self.pres,self.kapgm)
#plt.plot(self.temps,self.pres)
#plt.plot(self.itemps,self.ipres)
#plt.show()
self.ialpha = gsw.alpha(self.isals,self.itemps,self.ipres)
self.ibeta = gsw.beta(self.isals,self.itemps,self.ipres)
self.idalphadtheta = gsw.cabbeling(self.isals,self.itemps,self.ipres)
self.idalphadp = gsw.thermobaric(self.isals,self.itemps,self.ipres)
###using gsw
self.n2 = gsw.Nsquared(self.isals,self.itemps,self.ipres,self.maplat)[0]
def calc_buoyancyflux(ds,xv,yv):
import gsw
# Calculate buoyancy flux
r0 = gsw.rho(ds.variables['vosaline'][0,0,yv,xv],ds.variables['votemper'][0,0,yv,xv],0)
alpha = gsw.alpha(ds.variables['vosaline'][0,0,yv,xv],ds.variables['votemper'][0,0,yv,xv],0)
beta = gsw.beta(ds.variables['vosaline'][0,0,yv,xv],ds.variables['votemper'][0,0,yv,xv],0)
D_T = -(alpha/gsw.cp0)*ds.variables['sohefldo'][0,yv,xv]
D_S = r0*beta*ds.variables['vosaline'][0,0,yv,xv]*ds.variables['sowaflup'][0,yv,xv]/1000
return D_T + D_S
def _main(args):
"""Run the command line program."""
temperature_cube, temperature_history = gio.combine_files(args.temperature_file, args.temperature_var, checks=True)
salinity_cube, salinity_history = gio.combine_files(args.salinity_file, 'sea_water_salinity', checks=True)
assert 'c' in str(temperature_cube.units).lower(), "Input temperature units must be in celsius"
# if not 'C' in str(bigthetao_cube.units):
# bigthetao_cube.data = bigthetao_cube.data - 273.15
# data_median = np.ma.median(bigthetao_cube.data)
# assert data_median < 100
# assert data_median > -10
# bigthetao_cube.units = 'C'
target_shape = temperature_cube.shape[1:]
depth = temperature_cube.coord('depth').points * -1
broadcast_depth = uconv.broadcast_array(depth, 0, target_shape)
broadcast_longitude = uconv.broadcast_array(temperature_cube.coord('longitude').points, [1, 2], target_shape)
broadcast_latitude = uconv.broadcast_array(temperature_cube.coord('latitude').points, [1, 2], target_shape)
pressure = gsw.p_from_z(broadcast_depth, broadcast_latitude)
absolute_salinity = gsw.SA_from_SP(salinity_cube.data, pressure, broadcast_longitude, broadcast_latitude)
if args.temperature_var == 'sea_water_conservative_temperature':
conservative_temperature = temperature_cube.data
elif args.temperature_var == 'sea_water_potential_temperature':
conservative_temperature = gsw.CT_from_pt(absolute_salinity, temperature_cube.data)
else:
raise ValueError('Invalid temperature variable')
if args.coefficient == 'alpha':
coefficient_data = gsw.alpha(absolute_salinity, conservative_temperature, pressure)
var_name = 'alpha'
standard_name = 'thermal_expansion_coefficient'
long_name = 'thermal expansion coefficient'
units = '1/K'
elif args.coefficient == 'beta':
coefficient_data = gsw.beta(absolute_salinity, conservative_temperature, pressure)
var_name = 'beta'
standard_name = 'saline_contraction_coefficient'
long_name = 'saline contraction coefficient'
units = 'kg/g'
else:
raise ValueError('Coefficient must be alpha or beta')
iris.std_names.STD_NAMES[standard_name] = {'canonical_units': units}
coefficient_cube = temperature_cube.copy()
coefficient_cube.data = coefficient_data
coefficient_cube.standard_name = standard_name
coefficient_cube.long_name = long_name
coefficient_cube.var_name = var_name
coefficient_cube.units = units
coefficient_cube.attributes['history'] = cmdprov.new_log(git_repo=repo_dir)
iris.save(coefficient_cube, args.outfile)
def get_alpha(self):
"""
Get alpha
Requires absolute salinity and conservative temperature to have been
calculated already
"""
if not hasattr(self, 'CT'): self.get_CT()
if not hasattr(self, 'SA'): self.get_SA()
self.alpha = gsw.alpha(self.SA, self.CT, self.pressure)
return self.alpha
def plot_RTS_profile(ax, z, R, T, S):
""" plot density (R) temperature (T) and salinity (S) profiles in common axis
with correctly scaled axis"""
col = plt.get_cmap("tab10")
# create axis tripplett
ax1 = [ax]
ax1.append(ax.twiny())
ax1.append(ax.twiny())
# right, left, top, bottom
ax1[2].spines['top'].set_position(('outward', 40))
i = -1
i += 1 # density
ax1[i].plot(R, z, color=col(i), Linewidth=1, Linestyle='-', Label=r'')
ax1[i].xaxis.label.set_color(color=col(i))
ax1[i].tick_params(axis='x', colors=col(i))
ax1[i].set_xlabel(r'$\langle\rho\rangle_t$ (kg/m$^3$)', fontsize=12)
i += 1 # temperature
ax1[i].plot(T, z, color=col(i), Linewidth=1, Linestyle='-', Label=r'')
ax1[i].xaxis.label.set_color(color=col(i))
ax1[i].tick_params(axis='x', colors=col(i))
ax1[i].set_xlabel(r'$\langle T \rangle_t$ ($^\circ$C)', fontsize=12)
i += 1 # salinity
ax1[i].plot(S, z, color=col(i), Linewidth=1, Linestyle='-', Label=r'')
ax1[i].xaxis.label.set_color(color=col(i))
ax1[i].tick_params(axis='x', colors=col(i))
ax1[i].set_xlabel(r'$\langle S \rangle_t$ (g/kg)', fontsize=12)
#---------------set correct lims-----------------
rho_lims = ax1[0].get_xlim()
T_lims = ax1[1].get_xlim()
S_lims = ax1[2].get_xlim()
import gsw # sea water tool box
Tcenter = np.mean(T_lims)
Scenter = np.mean(S_lims)
rho0 = 1015
alpha = -gsw.alpha(Scenter, Tcenter, 1)
T_lims = Tcenter + np.array([-1, 1
]) * np.diff(rho_lims) * .5 / alpha / rho0
beta = gsw.beta(Scenter, Tcenter, 1)
S_lims = Scenter + np.array([-1, 1]) * np.diff(rho_lims) * .5 / beta / rho0
ax1[1].set_xlim(T_lims)
ax1[2].set_xlim(S_lims)
def interpolate(self):
self.ipres = range(int(min(self.pres)), int(max(self.pres)))
if len(self.pres) > 4:
self.isals = np.interp(self.ipres, self.pres, self.sals)
self.itemps = np.interp(self.ipres, self.pres, self.temps)
self.igamma = np.interp(self.ipres, self.pres, self.gamma)
self.ialpha = gsw.alpha(self.isals, self.itemps, self.ipres)
self.ibeta = gsw.beta(self.isals, self.itemps, self.ipres)
self.idalphadtheta = gsw.cabbeling(self.isals, self.itemps,
self.ipres)
self.idalphadp = gsw.thermobaric(self.isals, self.itemps,
self.ipres)
###using gsw
self.n2 = gsw.Nsquared(self.isals, self.itemps, self.ipres,
self.lat)[0]
def turner(datadir, filename):
"""
compute turner angle for data contained in filename
"""
data = xr.open_dataset(os.path.join(datadir, filename))
T = data.ptemp.values
S = data.ab_sal.values
lon = data.lon.values[np.isreal(data.lon.values)][0]
lat = data.lat.values[np.isreal(data.lat.values)][0]
p = data.DEPTH.values
alpha = gsw.alpha(S, T, p)
beta = gsw.beta(S, T, p)
ta = turner_angle(np.gradient(T, -p), np.gradient(S, -p), alpha, beta)
colorcycle = [i['color'] for i in rcParams['axes.prop_cycle']]
c = np.array([colorcycle[0] for i in ta])
c[ta > 0] = colorcycle[1]
plt.scatter(p, ta, c=c, s=2)
return ([i for i in p], [i for i in ta])
def extractPointSurfaces(fname,fields={}):
if len(fields.keys())<1:
fields = {"lat":"lat","lon":"lon","pres":"P_gamma",\
"s":"NS_S","ct":"NS_CT","pv":"PV","psi":"accpo","dthetads":"dCTdS"}
ctddata = sio.loadmat(fname)
lats = np.asarray(ctddata[fields["lat"]])[0]
lons = np.asarray(ctddata[fields["lon"]])[0]
nspres = np.asarray(ctddata[fields["pres"]]).T
PV = np.asarray(ctddata[fields["pv"]]).T
NS_CT = np.asarray(ctddata[fields["ct"]]).T
dCTdS = np.asarray(ctddata[fields["dthetads"]]).T
NS_S = np.asarray(ctddata[fields["s"]]).T
ACCPO = np.asarray(ctddata[fields["psi"]]).T
ns = np.asarray(ctddata["P_gref"])
profiles = []
surfaces = {}
for j in Bar("surface").iter(range(len(ns))):
tempSurf = nstools.emptySurface()
tempSurf["data"]["psi"] = []
tempSurf["data"]["dthetads"] = []
tempSurf["data"]["dalphadp"] = []
tempSurf["data"]["dalphadtheta"] = []
for p in range(len(lats)):
if lats[p]>20 and lons[p]<0 or lons[p] > 170:
tempSurf["lats"].append(lats[p])
tempSurf["lons"].append(lons[p])
tempSurf["ids"].append(p)
tempSurf["data"]["pres"].append(nspres[p][j])
tempSurf["data"]["t"].append(NS_CT[p][j])
tempSurf["data"]["s"].append(NS_S[p][j])
tempSurf["data"]["psi"].append(ACCPO[p][j])
tempSurf["data"]["pv"].append(PV[p][j])
tempSurf["data"]["n^2"].append(np.nan)
tempSurf["data"]["dalphadp"].append(gsw.thermobaric(NS_S[p][j],NS_CT[p][j],nspres[p][j]))
tempSurf["data"]["dalphadtheta"].append(gsw.cabbeling(NS_S[p][j],NS_CT[p][j],nspres[p][j]))
tempSurf["data"]["alpha"].append(gsw.alpha(NS_S[p][j],NS_CT[p][j],nspres[p][j]))
tempSurf["data"]["beta"].append(gsw.beta(NS_S[p][j],NS_CT[p][j],nspres[p][j]))
tempSurf["data"]["dthetads"].append(dCTdS[p][j])
surfaces[ns[j][0]] = tempSurf
return surfaces
def derive(self,property):
"""
Derives seawater properties as salinity, buoyancy frequency squared etc.
Args:
ST:
N2:
"""
try:
gsw
except:
logger.warning('GSW toolbox missing, derive will not work, doing nothing')
return
if(property == 'ST'):
# Poor mans check if the variables exist
sensor_pair0 = False
sensor_pair1 = False
try:
tmp1 = self.data['cond0']
tmp1 = self.data['temp0']
tmp1 = self.data['p']
sensor_pair0 = True
except:
sensor_pair0 = False
try:
tmp1 = self.data['cond1']
tmp1 = self.data['temp1']
tmp1 = self.data['p']
sensor_pair1 = True
except:
sensor_pair1 = False
if(sensor_pair0):
logger.debug('Calculating PSU0/SA11/CT11/rho11')
SP = gsw.SP_from_C(self.data['cond0'],self.data['temp0'],self.data['p'])
self.derived['SP00'] = SP
SA = gsw.SA_from_SP(SP,self.data['p'],self.header['lon'],self.header['lat'])
self.derived['SA00'] = SA
CT = gsw.CT_from_t(SA,self.data['temp0'],self.data['p'])
self.derived['CT00'] = CT
rho = gsw.rho_CT_exact(SA,CT,self.data['p'])
self.derived['rho00'] = rho
if(sensor_pair1):
logger.debug('Calculating PSU1/SA11/CT11/rho11')
SP = gsw.SP_from_C(self.data['cond1'],self.data['temp1'],self.data['p'])
self.derived['SP11'] = SP
SA = gsw.SA_from_SP(SP,self.data['p'],self.header['lon'],self.header['lat'])
self.derived['SA11'] = SA
CT = gsw.CT_from_t(SA,self.data['temp1'],self.data['p'])
self.derived['CT11'] = CT
rho = gsw.rho_CT_exact(SA,CT,self.data['p'])
self.derived['rho11'] = rho
if(property == 'N2'):
# Poor mans check if the variables exist
sensor_pair0 = False
sensor_pair1 = False
try:
tmp1 = self.derived['SA00']
tmp1 = self.derived['CT00']
tmp1 = self.data['p']
sensor_pair0 = True
except:
logger.info('Did not find absolute salinities and temperature, do first a .derive("ST")')
sensor_pair0 = False
try:
tmp1 = self.derived['SA11']
tmp1 = self.derived['CT11']
tmp1 = self.data['p']
sensor_pair1 = True
except:
logger.info('Did not find absolute salinities and temperature, do first a .derive("ST")')
sensor_pair1 = False
if(sensor_pair0):
logger.debug('Calculating Nsquared00')
[N2,p_mid] = gsw.Nsquared(self.derived['SA00'],self.derived['CT00'],self.data['p'])
self.derived['Nsquared00'] = interp(self.data['p'],p_mid,N2)
if(sensor_pair1):
logger.debug('Calculating Nsquared11')
[N2,p_mid] = gsw.Nsquared(self.derived['SA11'],self.derived['CT11'],self.data['p'])
self.derived['Nsquared11'] = interp(self.data['p'],p_mid,N2)
if(property == 'alphabeta'):
# Poor mans check if the variables exist
sensor_pair0 = False
sensor_pair1 = False
try:
tmp1 = self.derived['SA00']
tmp1 = self.derived['CT00']
tmp1 = self.data['p']
sensor_pair0 = True
except:
logger.info('Did not find absolute salinities and temperature, do first a .derive("ST")')
sensor_pair0 = False
try:
tmp1 = self.derived['SA11']
tmp1 = self.derived['CT11']
tmp1 = self.data['p']
sensor_pair1 = True
except:
logger.info('Did not find absolute salinities and temperature, do first a .derive("ST")')
sensor_pair1 = False
if(sensor_pair0):
logger.debug('Calculating Nsquared00')
alpha = gsw.alpha(self.derived['SA00'],self.derived['CT00'],self.data['p'])
beta = gsw.beta(self.derived['SA00'],self.derived['CT00'],self.data['p'])
self.derived['alpha00'] = alpha
self.derived['beta00'] = beta
if(sensor_pair1):
logger.debug('Calculating Nsquared11')
alpha = gsw.alpha(self.derived['SA11'],self.derived['CT11'],self.data['p'])
beta = gsw.beta(self.derived['SA11'],self.derived['CT11'],self.data['p'])
self.derived['alpha11'] = alpha
self.derived['beta11'] = beta
def alphabeta(S, T, P):
SA = gsw.SA_from_SP(S, P, 6., 42.)
CT = gsw.CT_from_t(SA, T, P)
return gsw.alpha(SA, CT, P), gsw.beta(SA, CT, P)