[opengm] 108/386: improved python learning

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to branch debian/master
in repository opengm.

commit 8cd242d531e9c67a2b5254de25b342c618451b3d
Author: DerThorsten <thorsten.beier at iwr.uni-heidelberg.de>
Date:   Wed Dec 17 17:27:32 2014 +0100

    improved python learning
---
 fubar/example1.py                                  |  1 -
 src/interfaces/python/opengm/learning/__init__.py  | 34 ++++++++++++++++++----
 .../python/opengm/learning/pyGridSearchLearner.cxx | 16 ++++++++++
 3 files changed, 45 insertions(+), 6 deletions(-)

diff --git a/fubar/example1.py b/fubar/example1.py
index 6c4aeb6..038399b 100644
--- a/fubar/example1.py
+++ b/fubar/example1.py
@@ -6,4 +6,3 @@ import opengm.learning
 datasetA = opengm.learning.createDataset(loss='hamming')
 datasetB = opengm.learning.createDataset(loss='generalized-hamming')
 
-print datasetA, datasetB
diff --git a/src/interfaces/python/opengm/learning/__init__.py b/src/interfaces/python/opengm/learning/__init__.py
index 384f0a3..b71b5b4 100644
--- a/src/interfaces/python/opengm/learning/__init__.py
+++ b/src/interfaces/python/opengm/learning/__init__.py
@@ -1,10 +1,9 @@
 from _learning import *
+import numpy
+import struct
 
-
-
-
-
-
+DatasetWithHammingLoss.lossType = 'hamming'
+DatasetWithGeneralizedHammingLoss.lossType = 'generalized-hamming'
 
 
 def createDataset(loss='hamming', numInstances=0):
@@ -19,3 +18,28 @@ def createDataset(loss='hamming', numInstances=0):
     else:
         raise RuntimeError("loss must be 'hamming' /'h' or 'generalized-hamming'/'gh' ")   
 
+
+
+
+def gridSearchLearner(dataset, lowerBounds, upperBounds, nTestPoints):
+
+    if dataset.__class__.lossType == 'hamming':
+        learnerCls = GridSearch_HammingLoss
+        leanerParamCls = GridSearch_HammingLossParameter
+    elif dataset.__class__.lossType == 'generalized-hamming':
+        learnerCls = GridSearch_GeneralizedHammingLoss
+        leanerParamCls = GridSearch_GeneralizedHammingLossParameter
+
+    nr = numpy.require 
+
+    sizeT_type = 'uint64'
+
+    if struct.calcsize("P") * 8 == 32:
+        sizeT_type = 'uint32'
+
+    param = leanerParamCls(nr(lowerBounds,dtype='float64'), nr(lowerBounds,dtype='float64'), 
+                           nr(lowerBounds,dtype=sizeT_type))
+
+    learner = learnerCls(dataset, param)
+
+    return learner
diff --git a/src/interfaces/python/opengm/learning/pyGridSearchLearner.cxx b/src/interfaces/python/opengm/learning/pyGridSearchLearner.cxx
index e8f9cfb..74946f1 100644
--- a/src/interfaces/python/opengm/learning/pyGridSearchLearner.cxx
+++ b/src/interfaces/python/opengm/learning/pyGridSearchLearner.cxx
@@ -14,6 +14,21 @@ namespace ol = opengm::learning;
 
 namespace opengm{
 
+
+    template<class PARAM>
+    PARAM * pyGridSearchParamConstructor(
+        op::NumpyView<double> lowerBound,
+        op::NumpyView<double> upperBound,
+        op::NumpyView<size_t> nTestPoints
+    ){
+        PARAM * p  = new PARAM();
+        p->parameterUpperbound_.assign(lowerBound.begin(), lowerBound.end());
+        p->parameterLowerbound_.assign(upperBound.begin(), upperBound.end());
+        p->testingPoints_.assign(nTestPoints.begin(), nTestPoints.end());
+        return p;
+    }
+
+
     template<class LEARNER>
     void pyLearnDummy(LEARNER & learner){
 
@@ -35,6 +50,7 @@ namespace opengm{
 
 
         bp::class_<PyLearnerParam>(paramClsName.c_str(), bp::init<>())
+            .def("__init__", make_constructor(&pyGridSearchParamConstructor<PyLearnerParam> ,boost::python::default_call_policies()))
         ;
 
         bp::class_<PyLearner>( clsName.c_str(), bp::init<DatasetType &, const PyLearnerParam &>() )

-- 
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