RF: Uniformize extension handling.

Extensions are now named after the lib they are building, e.g.

SMLR build smlrc.so and is therefore named 'smlrc' not 'smlr' and
is now located in 'mvpa/clfs/libsmlrc'.

Makefile

@@ -44,11 +44,11 @@ build-stamp: 3rd
 	python setup.py build_ext
 	python setup.py build_py
 # to overcome the issue of not-installed svmc.so
-	for ext in svm smlr; do \
-		ln -sf ../../../build/lib.linux-$(ARCH)-$(PYVER)/mvpa/clfs/lib$$ext/$${ext}c.so \
-		mvpa/clfs/lib$$ext/; \
-		ln -sf ../../../build/lib.linux-$(ARCH)-$(PYVER)/mvpa/clfs/lib$$ext/$${ext}c.so \
-		mvpa/clfs/lib$$ext/$${ext}c.dylib; \
+	for ext in _svmc smlrc ridgetrain; do \
+		ln -sf ../../../build/lib.linux-$(ARCH)-$(PYVER)/mvpa/clfs/lib$${ext#_*}/$${ext}.so \
+		mvpa/clfs/lib$${ext#_*}/; \
+		ln -sf ../../../build/lib.linux-$(ARCH)-$(PYVER)/mvpa/clfs/lib$${ext#_*}/$${ext}.so \
+		mvpa/clfs/lib$${ext#_*}/$${ext}.dylib; \
 		done
 	touch $@
 

Makefile.win

@@ -29,10 +29,12 @@ installer: 3rd build
 
 
 configure-inplace-use:
-	copy build\\lib.win32-$(PYTHON_VERSION)\\mvpa\\clfs\\libsmlr\\smlrc.pyd \
-		mvpa\\clfs\\libsmlr
-	copy build\\lib.win32-$(PYTHON_VERSION)\\mvpa\\clfs\\libsvm\\svmc.pyd \
-		mvpa\\clfs\\libsvm
+	copy build\\lib.win32-$(PYTHON_VERSION)\\mvpa\\clfs\\libsmlrc\\smlrc.pyd \
+		mvpa\\clfs\\libsmlrc
+	copy build\\lib.win32-$(PYTHON_VERSION)\\mvpa\\clfs\\libsvmc\\_svmc.pyd \
+		mvpa\\clfs\\libsvmc
+	copy build\\lib.win32-$(PYTHON_VERSION)\\mvpa\\clfs\\libridgetrain\\ridgetrain.pyd \
+		mvpa\\clfs\\libridgetrain
 
 #
 # Cleaning

mvpa/base/externals.py

@@ -80,7 +80,7 @@ def __check_weave():
 
 
 # contains list of available (optional) external classifier extensions
-_KNOWN = {'libsvm':'import mvpa.clfs.libsvm._svm as __; x=__.convert2SVMNode',
+_KNOWN = {'libsvm':'import mvpa.clfs.libsvmc._svm as __; x=__.convert2SVMNode',
           'nifti':'from nifti import NiftiImage as __',
           'ctypes':'import ctypes as __',
           'shogun':'import shogun as __',

mvpa/clfs/libridgetrain/__init__.py

@@ -0,0 +1,21 @@
+#emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
+#ex: set sts=4 ts=4 sw=4 et:
+### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
+#
+#   See COPYING file distributed along with the PyMVPA package for the
+#   copyright and license terms.
+#
+### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
+"""Import helper for Fortran extension ridgetrain."""
+
+__docformat__ = 'restructuredtext'
+
+
+if __debug__:
+    from mvpa.base import debug
+    debug('INIT', 'mvpa.clfs.libridgetrain')
+
+from mvpa.clfs.libridgetrain.ridgetrain import ridgetrain
+
+if __debug__:
+    debug('INIT', 'mvpa.clfs.libridgetrain end')

mvpa/clfs/libsmlr/__init__.py → mvpa/clfs/libsmlrc/__init__.py

@@ -10,14 +10,14 @@
 
 if __debug__:
     from mvpa.base import debug
-    debug('INIT', 'mvpa.clfs.libsmlr')
+    debug('INIT', 'mvpa.clfs.libsmlrc')
 
 import numpy as N
 import ctypes as C
 import os
 import sys
 
-from mvpa.clfs.libsmlr.ctypes_helper import extend_args, c_darray
+from mvpa.clfs.libsmlrc.ctypes_helper import extend_args, c_darray
 
 # connect to library that's in this directory
 if sys.platform == 'win32':
@@ -54,5 +54,5 @@ def stepwise_regression(*args):
     return func(*arglist)
 
 if __debug__:
-    debug('INIT', 'mvpa.clfs.libsmlr end')
+    debug('INIT', 'mvpa.clfs.libsmlrc end')
 

mvpa/clfs/libsvm/__init__.py → mvpa/clfs/libsvmc/__init__.py

@@ -12,9 +12,9 @@
 
 if __debug__:
     from mvpa.base import debug
-    debug('INIT', 'mvpa.clfs.libsvm')
+    debug('INIT', 'mvpa.clfs.libsvmc')
 
-from mvpa.clfs.libsvm.svm import SVM
+from mvpa.clfs.libsvmc.svm import SVM
 
 if __debug__:
-    debug('INIT', 'mvpa.clfs.libsvm end')
+    debug('INIT', 'mvpa.clfs.libsvmc end')

mvpa/clfs/libsvm/_svm.py → mvpa/clfs/libsvmc/_svm.py

@@ -16,8 +16,8 @@
 
 import numpy as N
 
-from mvpa.clfs.libsvm import svmc
-from mvpa.clfs.libsvm.svmc import C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, \
+from mvpa.clfs.libsvmc import _svmc as svmc
+from mvpa.clfs.libsvmc._svmc import C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, \
                                   NU_SVR, LINEAR, POLY, RBF, SIGMOID, \
                                   PRECOMPUTED
 

mvpa/clfs/libsvm/svm.py → mvpa/clfs/libsvmc/svm.py

@@ -22,14 +22,14 @@
 from mvpa.clfs._svmbase import _SVM
 from mvpa.measures.base import Sensitivity
 
-import _svm as svm
+from mvpa.clfs.libsvmc import _svm as svm
 from sens import *
 
 if __debug__:
     from mvpa.base import debug
 
 # we better expose those since they are mentioned in docstrings
-from svmc import \
+from mvpa.clfs.libsvmc._svmc import \
      C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, \
      NU_SVR, LINEAR, POLY, RBF, SIGMOID, \
      PRECOMPUTED

mvpa/clfs/libsvm/svmc.i → mvpa/clfs/libsvmc/svmc.i

@@ -1,3 +1,4 @@
+//-*-c++-*-
 %module svmc
 %{
 #include "svm.h"

mvpa/clfs/ridge.py

@@ -15,8 +15,7 @@
 from scipy.linalg import lstsq
 
 from mvpa.clfs.base import Classifier
-
-import ridgetrain
+from mvpa.clfs.libridgetrain import ridgetrain
 
 class RidgeReg(Classifier):
     """Ridge regression `Classifier`.
@@ -76,7 +75,7 @@ def _train(self, data):
         """Train the classifier using `data` (`Dataset`).
         """
 
-        if self.implementation == "direct":
+        if self.__implementation == "direct":
             # create matrices to solve with additional penalty term
             # determine the lambda matrix
             if self.__lm is None:
@@ -102,7 +101,7 @@ def _train(self, data):
                 Lambda = self.__lm
             # We can directly run the training routine
             self.w = N.random.randn(data.nfeatures+1)
-            self.w = ridgetrain.ridgetrain(data.samples,\
+            self.w = ridgetrain(data.samples,\
                     data.labels, self.w, Lambda, self.__stopcrit)
         else:
             raise ValueError, "Unknown implementation '%s'" \

mvpa/clfs/smlr.py

@@ -23,7 +23,7 @@
 _DEFAULT_IMPLEMENTATION = "Python"
 if externals.exists('ctypes'):
     # Uber-fast C-version of the stepwise regression
-    from mvpa.clfs.libsmlr import stepwise_regression as _cStepwiseRegression
+    from mvpa.clfs.libsmlrc import stepwise_regression as _cStepwiseRegression
     _DEFAULT_IMPLEMENTATION = "C"
 else:
     _cStepwiseRegression = None

mvpa/clfs/svm.py

@@ -43,14 +43,14 @@
 
 if externals.exists('libsvm'):
     # By default for now we want simply to import all SVMs from libsvm
-    from mvpa.clfs import libsvm
-    _NuSVM = libsvm.SVM
+    from mvpa.clfs import libsvmc
+    _NuSVM = libsvmc.SVM
     if default_backend == 'libsvm' or SVM is None:
         if __debug__ and default_backend != 'libsvm' and SVM is None:
             debug('SVM',
                   'Default SVM backend %s was not found, so using libsvm'
                   % default_backend)
-        SVM = libsvm.SVM
+        SVM = libsvmc.SVM
     #from mvpa.clfs.libsvm.svm import *
 
 if SVM is None:

mvpa/clfs/warehouse.py

@@ -165,7 +165,7 @@ def items(self):
                             clfs['smlr'][0].descr) ]
 
 if externals.exists('libsvm'):
-    from mvpa.clfs import libsvm
+    from mvpa.clfs import libsvmc as libsvm
     clfs._known_tags.union_update(libsvm.SVM._KNOWN_IMPLEMENTATIONS.keys())
     clfs += [libsvm.SVM(descr="libsvm.LinSVM(C=def)", probability=1),
              libsvm.SVM(

setup.py

@@ -25,8 +25,8 @@
 
 # define the extension modules
 libsvmc_ext = Extension(
-    'mvpa.clfs.libsvm.svmc',
-    sources = [ 'mvpa/clfs/libsvm/svmc.i' ],
+    'mvpa.clfs.libsvmc._svmc',
+    sources = [ 'mvpa/clfs/libsvmc/svmc.i' ],
     include_dirs = [ '/usr/include/libsvm-2.0/libsvm', numpy_headers ],
     libraries    = [ 'svm' ],
     language     = 'c++',
@@ -36,8 +36,8 @@
                      '-I' + numpy_headers ] )
 
 smlrc_ext = Extension(
-    'mvpa.clfs.libsmlr.smlrc',
-    sources = [ 'mvpa/clfs/libsmlr/smlr.c' ],
+    'mvpa.clfs.libsmlrc.smlrc',
+    sources = [ 'mvpa/clfs/libsmlrc/smlr.c' ],
     libraries = ['m'],
     # extra_compile_args = ['-O0'],
     extra_link_args = extra_link_args,
@@ -79,8 +79,8 @@
                        'mvpa.mappers',
                        'mvpa.clfs',
                        'mvpa.clfs.sg',
-                       'mvpa.clfs.libsvm',
-                       'mvpa.clfs.libsmlr',
+                       'mvpa.clfs.libsvmc',
+                       'mvpa.clfs.libsmlrc',
                        'mvpa.algorithms',
                        'mvpa.measures',
                        'mvpa.featsel',

tests/test_svm.py

@@ -160,7 +160,7 @@ def testSillyness(self):
             self.failUnlessRaises(TypeError, SVM,  C=1.0, nu=2.3)
 
         if externals.exists('libsvm'):
-            self.failUnlessRaises(TypeError, libsvm.SVM,  C=1.0, nu=2.3)
+            self.failUnlessRaises(TypeError, libsvmc.SVM,  C=1.0, nu=2.3)
             self.failUnlessRaises(TypeError, LinearNuSVMC, C=2.3)
             self.failUnlessRaises(TypeError, LinearCSVMC, nu=2.3)