def plume_center(d, t):
"""
Compute plume center of mass
:param d: open NetCDF4 dataset
:param t: number of timestep
"""
tr = d.variables['tr17_1'][t, :, :, :]
smoke_int = np.sum(tr, axis=0)
z = height8p(d, t)
h = np.sum(z * tr, axis=0)
h[smoke_int <= smoke_threshold_int] = 0
smoke_int[smoke_int <= smoke_threshold_int] = 1
return h / smoke_int
def plume_height(d, t):
"""
Compute plume height
:param d: open NetCDF4 dataset
:param t: number of timestep
"""
z = height8p(d, t)
tr = d.variables['tr17_1'][t, :, :, :]
h = np.zeros(tr.shape[1:])
for i in range(0, tr.shape[2]):
for j in range(0, tr.shape[1]):
for k in range(tr.shape[0] - 1, -1, -1):
if tr[k, j, i] > smoke_threshold:
h[j, i] = z[k, j, i]
break
return h
def smoke_at_height(varname,d,t,level):
s = interpolate2height(smoke_concentration(d,t),height8p(d,t),level)
print_stats(varname,s,'ug/m^3')
return s