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Ruben Martinez-Cantin  committed 2aa7668

Bug in Python interface. Matlab linking issues doc moved to install.

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  • Parent commits 2400278
  • Tags v0.6

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Files changed (4)

File doxygen/install.dox

 are. If the install path is the default, you can execute the
 exportlocalpath.sh script before calling MATLAB.
 
-On MacOS there are known issues both in Matlab and Octave about the compiler linking with
+\subsubsection notematlab Issues on libstdc++ linking:
+
+<ul>
+<li> Matlab for *nix OS may ship outdated libraries for gcc (e.g.: 4.3 in
+2011b). You might get errors like this one:
+\verbatim
+/usr/lib/x86_64-linux-gnu/gcc/x86_64-linux-gnu/4.5.2/cc1: /usr/local/MATLAB/R2010b/sys/os/glnxa64/libstdc++.so.6: version `GLIBCXX_3.4.14' not found (required by /usr/lib/libppl_c.so.2)
+\endverbatim
+
+The solution is to change the symbolic links
+in /matlabroot/sys/os/glnx86 for \em libgcc_s.so.1
+and \em libstdc++.so.6 to point to the system libraries, which
+typically can be found in /lib or /usr/lib.
+
+
+<li> On MacOS there are known issues both in Matlab and Octave about the compiler linking with
 the worng std++ library for different reasons. See:
-\li http://www.mathworks.com/matlabcentral/newsreader/view_thread/291752
-\li https://mailman.cae.wisc.edu/pipermail/octave-maintainers/2012-January/026341.html
+<ul> 
+<li> http://www.mathworks.com/matlabcentral/newsreader/view_thread/291752
+<li> https://mailman.cae.wisc.edu/pipermail/octave-maintainers/2012-January/026341.html
+</ul>
+</ul>
 
 <HR>
 

File doxygen/reference.dox

 [x_out, y_out] = bayesopt(@my_function, n_dimensions, parameters, lower_bound, upper_bound)
 \endcode
 
-\subsubsection notematlab Note on gcc versions:
-
-Matlab for *nix OS may ship outdated libraries for gcc (e.g.: 4.3 in
-2011b). You might get errors like this one:
-\verbatim
-/usr/lib/x86_64-linux-gnu/gcc/x86_64-linux-gnu/4.5.2/cc1: /usr/local/MATLAB/R2010b/sys/os/glnxa64/libstdc++.so.6: version `GLIBCXX_3.4.14' not found (required by /usr/lib/libppl_c.so.2)
-\endverbatim
-
-The solution is to change the symbolic links
-in /matlabroot/sys/os/glnx86 for \em libgcc_s.so.1
-and \em libstdc++.so.6 to point to the system libraries, which
-typically can be found in /lib or /usr/lib.
 
 */

File python/bayesopt.cpp

-/* Generated by Cython 0.19 on Mon Mar 24 16:08:19 2014 */
+/* Generated by Cython 0.19 on Tue Mar 25 19:34:10 2014 */
 
 #define PY_SSIZE_T_CLEAN
 #ifndef CYTHON_USE_PYLONG_INTERNALS
 static char __pyx_k_8[] = "unknown dtype code in numpy.pxd (%d)";
 static char __pyx_k_9[] = "Format string allocated too short, see comment in numpy.pxd";
 static char __pyx_k_12[] = "Format string allocated too short.";
-static char __pyx_k_16[] = "/home/rmcantin/code/bayesopt-devel/python/bayesopt.pyx";
+static char __pyx_k_16[] = "/home/rmcantin/code/bayesopt/python/bayesopt.pyx";
 static char __pyx_k__B[] = "B";
 static char __pyx_k__H[] = "H";
 static char __pyx_k__I[] = "I";
  * 
  *     score = dparams.get('sc_type', None)             # <<<<<<<<<<<<<<
  *     if score is not None:
- *         params.sc_type = str2score(learning)
+ *         params.sc_type = str2score(score)
  */
   if (unlikely(((PyObject *)__pyx_v_dparams) == Py_None)) {
     PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "get");
  * 
  *     score = dparams.get('sc_type', None)
  *     if score is not None:             # <<<<<<<<<<<<<<
- *         params.sc_type = str2score(learning)
+ *         params.sc_type = str2score(score)
  * 
  */
   __pyx_t_7 = (__pyx_v_score != Py_None);
     /* "bayesopt.pyx":129
  *     score = dparams.get('sc_type', None)
  *     if score is not None:
- *         params.sc_type = str2score(learning)             # <<<<<<<<<<<<<<
- * 
- * 
- */
-    __pyx_t_4 = __Pyx_PyObject_AsString(__pyx_v_learning); if (unlikely((!__pyx_t_4) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 129; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ *         params.sc_type = str2score(score)             # <<<<<<<<<<<<<<
+ * 
+ * 
+ */
+    __pyx_t_4 = __Pyx_PyObject_AsString(__pyx_v_score); if (unlikely((!__pyx_t_4) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 129; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     __pyx_v_params.sc_type = str2score(__pyx_t_4);
     goto __pyx_L4;
   }

File python/bayesopt.pyx

 
     score = dparams.get('sc_type', None)
     if score is not None:
-        params.sc_type = str2score(learning)
+        params.sc_type = str2score(score)
 
         
     params.epsilon = dparams.get('epsilon',params.epsilon)