def diagnostics(self, var, t):
""" should provide at least 'maxspeed' (for cfl determination) """
nh = self.nh
u = var.get('u')
v = var.get('v')
vort = var.get('vorticity')
buoy = var.get('buoyancy')
ke, maxu = fd.computekemaxu(self.msk, u, v, self.nh)
z, z2 = fd.computesumandnorm(self.msk, vort, self.nh)
b, b2 = fd.computesumandnorm(self.msk, buoy, self.nh)
# potential energy (minus sign because buoyancy is minus density)
pe = -self.gravity * fd.computesum(self.msk, buoy * self.yr, nh)
cst = self.mpitools.local_to_global([(maxu, 'max'), (ke, 'sum'),
(z, 'sum'), (z2, 'sum'),
(pe, 'sum'), (b, 'sum'),
(b2, 'sum')])
self.diags['maxspeed'] = cst[0]
self.diags['ke'] = cst[1] / self.area
self.diags['pe'] = cst[4] / self.area
self.diags['energy'] = (cst[1] + cst[4]) / self.area
self.diags['vorticity'] = cst[2] / self.area
self.diags['enstrophy'] = 0.5 * cst[3] / self.area
self.diags['buoyancy'] = cst[5] / self.area
self.diags['brms'] = np.sqrt(cst[6] / self.area -
(cst[5] / self.area)**2)
def diagnostics(self, var, t):
""" should provide at least 'maxspeed' (for cfl determination) """
nh = self.nh
u = var.get('u')
v = var.get('v')
vort = var.get('vorticity')
buoy = var.get('buoyancy')
V = var.get('V')
qE = var.get('qE')
qEneg = qE.copy()
qEneg[qE > 0] = 0.
ke, maxu = fd.computekemaxu(self.msk, u, v, self.nh)
z, z2 = fd.computesumandnorm(self.msk, vort, self.nh)
b, b2 = fd.computesumandnorm(self.msk, buoy, self.nh)
vm, v2 = fd.computesumandnorm(self.msk, V, self.nh)
q, q2 = fd.computesumandnorm(self.msk, qE, self.nh)
qn, qn2 = fd.computesumandnorm(self.msk, qEneg, self.nh)
# potential energy (minus sign because buoyancy is minus density)
pe = fd.computesum(self.msk, buoy * self.yr, nh)
pe = -self.gravity * pe
cst = self.mpitools.local_to_global([(maxu, 'max'), (ke, 'sum'),
(z, 'sum'), (z2, 'sum'),
(pe, 'sum'), (b, 'sum'),
(b2, 'sum'), (q, 'sum'),
(q2, 'sum'), (qn, 'sum'),
(qn2, 'sum'), (v2, 'sum')])
a = self.area
self.diags['maxspeed'] = cst[0]
self.diags['ke'] = (cst[1]) / a
self.diags['keV'] = (0.5 * cst[11]) / a
self.diags['pe'] = cst[4] / a
self.diags[
'energy'] = self.diags['ke'] + self.diags['pe'] + self.diags['keV']
self.diags['vorticity'] = cst[2] / a
self.diags['enstrophy'] = 0.5 * cst[3] / a
bm = cst[5] / a
self.diags['buoyancy'] = bm
self.diags['brms'] = sqrt(cst[6] / a - bm**2)
pvm = cst[7] / a
pvneg_mean = cst[9] / a
self.diags['pv_mean'] = pvm
self.diags['pv_std'] = sqrt(cst[8] / a - pvm**2)
self.diags['pvneg_mean'] = pvneg_mean
self.diags['pvneg_std'] = sqrt(cst[10] / a - pvneg_mean**2)
def diagnostics(self, var, t):
""" should provide at least 'maxspeed' (for cfl determination) """
self.timers.tic('diag')
u = var.get('u')
v = var.get('v')
trac = var.get('vorticity')
psi = var.get('psi')
source = self.var.get('source')
xr = self.xr
yr = self.yr
ke, maxu = fd.computekemaxu(self.msk, u, v, self.nh)
# ke = fd.computekewithpsi(self.msk, trac, psi, self.nh)
z, z2 = fd.computesumandnorm(self.msk, trac, self.nh)
px = fd.computedotprod(self.msk, trac, xr, self.nh)
py = fd.computedotprod(self.msk, trac, yr, self.nh)
angmom = fd.computesum(self.msk, psi, self.nh)
sce = fd.computedotprod(self.msk, trac, source, self.nh)
cst = self.mpitools.local_to_global([(maxu, 'max'), (ke, 'sum'),
(z, 'sum'), (z2, 'sum'),
(px, 'sum'), (py, 'sum'),
(angmom, 'sum'), (sce, 'sum')])
self.diags['maxspeed'] = cst[0]
self.diags['ke'] = cst[1] / self.area
self.diags['vorticity'] = cst[2] / self.area
self.diags['enstrophy'] = 0.5 * cst[3] / self.area
self.diags['px'] = cst[4] / self.area
self.diags['py'] = cst[5] / self.area
self.diags['angmom'] = cst[6] / self.area
self.diags['source'] = cst[7] / self.area
self.timers.toc('diag')