From b99e06c0d96060c0ca1e3f98cc5bed42ad694d88 Mon Sep 17 00:00:00 2001
From: Reimar Leike <reimar@mpa-garhcing.mpg.de>
Date: Wed, 17 Jun 2020 18:19:41 +0200
Subject: [PATCH] Adjusted fisher test to always make Fisher matrices reaL,
code for GaussianEnergy was reverted
---
nifty6/operators/energy_operators.py | 13 +---------
test/test_operators/test_fisher_metric.py | 31 ++++++++++++++++++++++-
2 files changed, 31 insertions(+), 13 deletions(-)
diff --git a/nifty6/operators/energy_operators.py b/nifty6/operators/energy_operators.py
index 21949965b..627c09eaa 100644
--- a/nifty6/operators/energy_operators.py
+++ b/nifty6/operators/energy_operators.py
@@ -244,18 +244,7 @@ class GaussianEnergy(EnergyOperator):
self._met = inverse_covariance
if sampling_dtype is not None:
self._met = SamplingDtypeSetter(self._met, sampling_dtype)
- if isinstance(sampling_dtype, dict):
- from .sandwich_operator import SandwichOperator
- scale = {k:np.sqrt(2.) if np.issubdtype(v, np.complexfloating)
- else 1. for k,v in sampling_dtype.items()}
- scale = _build_MultiScalingOperator(self._domain, scale)
- self._met = SandwichOperator.make(scale, self._met)
- else:
- if np.issubdtype(sampling_dtype, np.complexfloating):
- from .sandwich_operator import SandwichOperator
- scale = ScalingOperator(self._met.domain,np.sqrt(2))
- self._met = SandwichOperator.make(scale, self._met)
-
+
def _checkEquivalence(self, newdom):
newdom = makeDomain(newdom)
if self._domain is None:
diff --git a/test/test_operators/test_fisher_metric.py b/test/test_operators/test_fisher_metric.py
index 46edccca8..bacb89244 100644
--- a/test/test_operators/test_fisher_metric.py
+++ b/test/test_operators/test_fisher_metric.py
@@ -23,7 +23,6 @@ import nifty6 as ift
from ..common import list2fixture, setup_function, teardown_function
spaces = [ift.GLSpace(5),
- ift.MultiDomain.make({'': ift.RGSpace(5, distances=.789)}),
(ift.RGSpace(3, distances=.789), ift.UnstructuredDomain(2))]
pmp = pytest.mark.parametrize
field = list2fixture([ift.from_random(sp, 'normal') for sp in spaces] +
@@ -38,7 +37,34 @@ def _to_array(d):
assert isinstance(d, dict)
return np.concatenate(list(d.values()))
+def _complex2real(sp):
+ tup = tuple([d for d in sp])
+ rsp = ift.DomainTuple.make((ift.UnstructuredDomain(2),) + tup)
+ rl = ift.DomainTupleFieldInserter(rsp, 0, (0,))
+ im = ift.DomainTupleFieldInserter(rsp, 0, (1,))
+ x = ift.ScalingOperator(sp, 1)
+ return rl(x.real)+im(x.imag)
+
+def test_complex2real():
+ sp = ift.UnstructuredDomain(3)
+ op = _complex2real(ift.makeDomain(sp))
+ f = ift.from_random(op.domain, 'normal', dtype=np.complex128)
+ assert np.all((f == op.adjoint_times(op(f))).val)
+ assert op(f).dtype == np.float64
+ f = ift.from_random(op.target, 'normal')
+ assert np.all((f == op(op.adjoint_times(f))).val)
+
+def energy_tester_complex(pos, get_noisy_data, energy_initializer):
+ op = _complex2real(pos.domain)
+ npos = op(pos)
+ nget_noisy_data = lambda mean : get_noisy_data(op.adjoint_times(mean))
+ nenergy_initializer = lambda mean : energy_initializer(mean) @ op.adjoint
+ energy_tester(npos, nget_noisy_data, nenergy_initializer)
+
def energy_tester(pos, get_noisy_data, energy_initializer):
+ if np.issubdtype(pos.dtype, np.complexfloating):
+ energy_tester_complex(pos, get_noisy_data, energy_initializer)
+ return
domain = pos.domain
test_vec = ift.from_random(domain, 'normal')
results = []
@@ -48,6 +74,8 @@ def energy_tester(pos, get_noisy_data, energy_initializer):
energy = energy_initializer(data)
grad = energy(lin).jac.adjoint(ift.full(energy.target, 1.))
results.append(_to_array((grad*grad.s_vdot(test_vec)).val))
+ print(energy)
+ print(grad)
res = np.mean(np.array(results), axis=0)
std = np.std(np.array(results), axis=0)/np.sqrt(Nsamp)
energy = energy_initializer(data)
@@ -57,6 +85,7 @@ def energy_tester(pos, get_noisy_data, energy_initializer):
def test_GaussianEnergy(field):
dtype = field.dtype
+
icov = ift.from_random(field.domain, 'normal')**2
icov = ift.makeOp(icov)
get_noisy_data = lambda mean : mean + icov.draw_sample_with_dtype(
--
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