From 455b0dd97b4b8615f0e8cc003ce4d8add977b438 Mon Sep 17 00:00:00 2001
From: Martin Reinecke <martin@mpa-garching.mpg.de>
Date: Fri, 10 Aug 2018 15:15:14 +0200
Subject: [PATCH] cosmetics; start working on scipy minimizers and multifields
---
demos/getting_started_3.py | 2 ++
nifty5/minimization/scipy_minimizer.py | 35 +++++++++++++++++++++--
nifty5/operators/operator.py | 16 +++++------
test/test_minimization/test_minimizers.py | 5 +---
4 files changed, 42 insertions(+), 16 deletions(-)
diff --git a/demos/getting_started_3.py b/demos/getting_started_3.py
index b0e90e3a2..7b2c33888 100644
--- a/demos/getting_started_3.py
+++ b/demos/getting_started_3.py
@@ -76,6 +76,8 @@ if __name__ == '__main__':
ic_sampling = ift.GradientNormController(iteration_limit=100)
ic_newton = ift.GradientNormController(name='Newton', iteration_limit=100)
minimizer = ift.RelaxedNewton(ic_newton)
+ minimizer = ift.NewtonCG(1e-5, 10, True)
+ minimizer = ift.L_BFGS_B(1e-10, 1e-5, 100, 10, True)
# build model Hamiltonian
H = ift.Hamiltonian(likelihood, ic_sampling)
diff --git a/nifty5/minimization/scipy_minimizer.py b/nifty5/minimization/scipy_minimizer.py
index 057355b0d..0727b9b3c 100644
--- a/nifty5/minimization/scipy_minimizer.py
+++ b/nifty5/minimization/scipy_minimizer.py
@@ -18,24 +18,53 @@
from __future__ import absolute_import, division, print_function
+import numpy as np
from .. import dobj
from ..compat import *
from ..field import Field
+from ..multi_field import MultiField
+from ..domain_tuple import DomainTuple
from ..logger import logger
from .iteration_controller import IterationController
from .minimizer import Minimizer
+def _multiToArray(fld):
+ szall = 0
+ for val in fld.values():
+ if val.dtype != np.float64:
+ raise TypeError("need float64 fields")
+ szall += val.size
+ res = np.empty(szall, dtype=np.float64)
+ ofs = 0
+ for val in fld.values():
+ res[ofs:ofs+val.size] = val.local_data.reshape(-1)
+ ofs += val.size
+ return res
+
+
def _toArray(fld):
- return fld.to_global_data().reshape(-1)
+ if isinstance(fld, Field):
+ return fld.local_data.reshape(-1)
+ return _multiToArray(fld)
def _toArray_rw(fld):
- return fld.to_global_data_rw().reshape(-1)
+ if isinstance(fld, Field):
+ return fld.local_data.copy().reshape(-1)
+ return _multiToArray(fld)
def _toField(arr, dom):
- return Field.from_global_data(dom, arr.reshape(dom.shape).copy())
+ if isinstance(dom, DomainTuple):
+ return Field.from_local_data(dom, arr.reshape(dom.shape).copy())
+ ofs = 0
+ res = []
+ for d in dom.domains():
+ res.append(Field.from_local_data(
+ d, arr[ofs:ofs+d.size].copy().reshape(d.shape)))
+ ofs += d.size
+ return MultiField(dom, tuple(res))
class _MinHelper(object):
diff --git a/nifty5/operators/operator.py b/nifty5/operators/operator.py
index 04f91b1ec..11f979ac5 100644
--- a/nifty5/operators/operator.py
+++ b/nifty5/operators/operator.py
@@ -132,18 +132,16 @@ class _OpProd(Operator):
from ..linearization import Linearization
from ..sugar import makeOp
lin = isinstance(x, Linearization)
+ v = x._val if lin else x
+ v1 = v.extract(self._op1.domain)
+ v2 = v.extract(self._op2.domain)
if not lin:
- r1 = self._op1(x.extract(self._op1.domain))
- r2 = self._op2(x.extract(self._op2.domain))
- return r1*r2
- lin1 = self._op1(
- Linearization.make_var(x._val.extract(self._op1.domain)))
- lin2 = self._op2(
- Linearization.make_var(x._val.extract(self._op2.domain)))
+ return self._op1(v1) * self._op2(v2)
+ lin1 = self._op1(Linearization.make_var(v1))
+ lin2 = self._op2(Linearization.make_var(v2))
op = (makeOp(lin1._val)(lin2._jac))._myadd(
makeOp(lin2._val)(lin1._jac), False)
- jac = op(x.jac)
- return Linearization(lin1._val*lin2._val, jac)
+ return Linearization(lin1._val*lin2._val, op(x.jac))
class _OpSum(_CombinedOperator):
diff --git a/test/test_minimization/test_minimizers.py b/test/test_minimization/test_minimizers.py
index 35be855ca..e21051327 100644
--- a/test/test_minimization/test_minimizers.py
+++ b/test/test_minimization/test_minimizers.py
@@ -100,10 +100,7 @@ class Test_Minimizers(unittest.TestCase):
def __init__(self, loc):
self._loc = loc.to_global_data_rw()
self._capability = self.TIMES
-
- @property
- def domain(self):
- return space
+ self._domain = space
def apply(self, x, mode):
self._check_input(x, mode)
--
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