From e3d7fc8e8e8a096b443a1dd9351c2cb5fecf9b24 Mon Sep 17 00:00:00 2001
From: pfrank <philipp@mpa-garching.mpg.de>
Date: Wed, 6 Nov 2019 10:33:12 +0100
Subject: [PATCH] new slope handling
---
nifty5/library/correlated_fields.py | 53 +++++++++++++++--------------
1 file changed, 27 insertions(+), 26 deletions(-)
diff --git a/nifty5/library/correlated_fields.py b/nifty5/library/correlated_fields.py
index 027f7d4ad..c32caba0f 100644
--- a/nifty5/library/correlated_fields.py
+++ b/nifty5/library/correlated_fields.py
@@ -50,36 +50,37 @@ def _normal(mean, sig, key):
sig*ducktape(DomainTuple.scalar_domain(), None, key))
-class _SlopeOperator(Operator):
- def __init__(self, smooth, loglogavgslope):
- self._domain = MultiDomain.union(
- [smooth.domain, loglogavgslope.domain])
- self._target = smooth.target
- from ..operators.simple_linear_operators import PartialExtractor
- self._smooth = smooth @ PartialExtractor(self._domain, smooth.domain)
- self._llas = loglogavgslope @ PartialExtractor(self._domain,
- loglogavgslope.domain)
- logkl = _log_k_lengths(self._target[0])
- assert logkl.shape[0] == self._target[0].shape[0] - 1
- logkl = np.insert(logkl, 0, 0)
-
- self._t = VdotOperator(from_global_data(self._target, logkl)).adjoint
- self._T = float(logkl[-1] - logkl[1])
- ind = (smooth.target.shape[0] - 1,)
- self._extr_op = ValueInserter(smooth.target, ind).adjoint
+class _SlopeRemover(EndomorphicOperator):
+ def __init__(self,domain,logkl):
+ self._domain = makeDomain(domain)
+ self._sc = logkl / float(logkl[-1])
- def apply(self, x):
- self._check_input(x)
- smooth = self._smooth(x)
- res0 = self._llas(x)
- res1 = self._extr_op(smooth)/self._T
- return self._t(res0 - res1) + smooth
+ self._capability = self.TIMES | self.ADJOINT_TIMES
+ def apply(self,x,mode):
+ self._check_input(x,mode)
+ x = x.to_global_data()
+ if mode == self.TIMES:
+ res = x - x[-1] * self._sc
+ else:
+ res = np.empty(x.shape)
+ res += x
+ res[-1] -= (x*self._sc).sum()
+ return from_global_data(self._tgt(mode),res)
+
+def _make_slope_Operator(smooth,loglogavgslope):
+ tg = smooth.target
+ logkl = _log_k_lengths(tg[0])
+ assert logkl.shape[0] == tg[0].shape[0] - 1
+ logkl -= logkl[0]
+ logkl = np.insert(logkl, 0, 0)
+ noslope = _SlopeRemover(tg,logkl) @ smooth
+ _t = VdotOperator(from_global_data(tg, logkl)).adjoint
+ return noslope + _t @ loglogavgslope
def _log_k_lengths(pspace):
return np.log(pspace.k_lengths[1:])
-
class _TwoLogIntegrations(LinearOperator):
def __init__(self, target):
self._target = makeDomain(target)
@@ -184,8 +185,8 @@ class CorrelatedFieldMaker:
scale = sigmasq*(Adder(shift) @ scale).sqrt()
smooth = twolog @ (scale*ducktape(scale.target, None, key))
- smoothslope = _SlopeOperator(smooth, loglogavgslope)
-
+ smoothslope = _make_slope_Operator(smooth,loglogavgslope)
+
# move to tests
assert_allclose(
smooth(from_random('normal', smooth.domain)).val[0:2], 0)
--
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