dtypes in UnitLogGauss
import numpy as np
import nifty5 as ift
space = ift.RGSpace(2)
f = ift.from_random('normal', space)
var_f = ift.Variable(f)
g = ift.from_random('normal', space, dtype=np.complex)
var_g = ift.Variable(g)
multi = ift.MultiField({'f': f, 'g': g})
var = ift.Variable(multi)
op = ift.ScalingOperator(1j, space)
op_multi = ift.ScalingOperator(1j, var.value.domain)
lh_f = ift.library.UnitLogGauss(op(var_f))
lh_g = ift.library.UnitLogGauss(op(var_g))
lh = ift.library.UnitLogGauss(op_multi(var))
print(lh_f.value)
print(lh_f.gradient)
print()
print(lh_g.value)
print(lh_g.gradient)
print()
print(lh.value)
print(lh.gradient['f'])
print(lh.gradient['g'])
Results in:
2.230929182659062
nifty5.Field instance
- domain = DomainTuple, len: 1
RGSpace(shape=(2,), distances=(0.5,), harmonic=False)
- val = array([-1.52732309+0.j, -1.45915817+0.j])
0.30445727594179295
nifty5.Field instance
- domain = DomainTuple, len: 1
RGSpace(shape=(2,), distances=(0.5,), harmonic=False)
- val = array([0.25117854+0.27192986j, 0.45978435-0.51036889j])
2.535386458600855
nifty5.Field instance
- domain = DomainTuple, len: 1
RGSpace(shape=(2,), distances=(0.5,), harmonic=False)
- val = array([-1.52732309+0.j, -1.45915817+0.j])
nifty5.Field instance
- domain = DomainTuple, len: 1
RGSpace(shape=(2,), distances=(0.5,), harmonic=False)
- val = array([0.25117854+0.27192986j, 0.45978435-0.51036889j])
I would expect that the gradient has the same dtype
as the input.