def get_gradient(self, fields_a, fields_f, frequencies, geom_list, f):
# sanitize the input
if (fields_a.ndim < 5) or (fields_f.ndim < 5):
raise ValueError(
"Fields arrays must have 5 dimensions (x,y,z,frequency,component)"
)
num_freqs = np.array(frequencies).size
grad = np.zeros((self.num_design_params * num_freqs, )) # preallocate
# compute the gradient
mp._get_gradient(grad, fields_a, fields_f, self.volume,
np.array(frequencies), geom_list, f)
return np.squeeze(
grad.reshape(self.num_design_params, num_freqs, order='F'))
def get_gradient(self,sim,fields_a,fields_f,frequencies):
for c in range(3):
fields_a[c] = fields_a[c].flatten(order='C')
fields_f[c] = fields_f[c].flatten(order='C')
fields_a = np.concatenate(fields_a)
fields_f = np.concatenate(fields_f)
num_freqs = np.array(frequencies).size
grad = np.zeros((num_freqs,self.num_design_params)) # preallocate
geom_list = sim.geometry
f = sim.fields
vol = sim._fit_volume_to_simulation(self.volume)
# compute the gradient
mp._get_gradient(grad,fields_a,fields_f,vol,np.array(frequencies),geom_list,f)
return np.squeeze(grad).T
def get_gradient(self, sim, fields_a, fields_f, frequencies,
finite_difference_step):
num_freqs = onp.array(frequencies).size
'''We have the option to linearly scale the gradients up front
using the scalegrad parameter (leftover from MPB API). Not
currently needed for any existing feature (but available for
future use)'''
scalegrad = 1
grad = onp.zeros((num_freqs, self.num_design_params)) # preallocate
vol = sim._fit_volume_to_simulation(self.volume)
# compute the gradient
mp._get_gradient(grad, scalegrad, fields_a[0].swigobj,
fields_a[1].swigobj, fields_a[2].swigobj,
fields_f[0].swigobj, fields_f[1].swigobj,
fields_f[2].swigobj, sim.gv, vol.swigobj,
onp.array(frequencies), sim.geps,
finite_difference_step)
return onp.squeeze(grad).T