update boost on linux

linx64/include/boost/python/numpy/config.hpp

@@ -62,7 +62,9 @@
 // Set the name of our library, this will get undef'ed by auto_link.hpp
 // once it's done with it:
 //
-#define BOOST_LIB_NAME boost_numpy
+#define _BOOST_PYTHON_CONCAT(N, M, m) N ## M ## m
+#define BOOST_PYTHON_CONCAT(N, M, m) _BOOST_PYTHON_CONCAT(N, M, m)
+#define BOOST_LIB_NAME BOOST_PYTHON_CONCAT(boost_numpy, PY_MAJOR_VERSION, PY_MINOR_VERSION)
 //
 // If we're importing code from a dll, then tell auto_link.hpp about it:
 //
@@ -75,4 +77,9 @@
 #include <boost/config/auto_link.hpp>
 #endif  // auto-linking disabled
 
+#undef BOOST_PYTHON_CONCAT
+#undef _BOOST_PYTHON_CONCAT
+
+#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
+
 #endif // CONFIG_NUMPY20170215_H_

linx64/include/boost/python/numpy/dtype.hpp

@@ -13,11 +13,10 @@
  */
 
 #include <boost/python.hpp>
-#include <boost/python/numpy/numpy_object_mgr_traits.hpp>
 #include <boost/python/numpy/config.hpp>
-
+#include <boost/python/numpy/numpy_object_mgr_traits.hpp>
 #include <boost/mpl/for_each.hpp>
-#include <boost/type_traits/add_pointer.hpp>
+#include <boost/python/detail/type_traits.hpp>
 
 namespace boost { namespace python { namespace numpy {
 
@@ -90,7 +89,7 @@ struct builtin_dtype<T,true> {
 };
 
 template <>
-struct builtin_dtype<bool,true> {
+struct BOOST_NUMPY_DECL builtin_dtype<bool,true> {
   static dtype get();
 };
 

linx64/include/boost/python/numpy/internal.hpp

@@ -15,6 +15,7 @@
  */
 
 #include <boost/python.hpp>
+#include <boost/python/numpy/config.hpp>
 #ifdef BOOST_PYTHON_NUMPY_INTERNAL
 #define NO_IMPORT_ARRAY
 #define NO_IMPORT_UFUNC

linx64/include/boost/python/numpy/ndarray.hpp

@@ -13,7 +13,7 @@
 
 #include <boost/python.hpp>
 #include <boost/utility/enable_if.hpp>
-#include <boost/type_traits/is_integral.hpp>
+#include <boost/python/detail/type_traits.hpp>
 #include <boost/python/numpy/numpy_object_mgr_traits.hpp>
 #include <boost/python/numpy/dtype.hpp>
 #include <boost/python/numpy/config.hpp>
@@ -86,11 +86,11 @@ public:
   /// @brief Copy the scalar (deep for all non-object fields).
   ndarray copy() const;
 
-  /// @brief Return the size of the nth dimension.
-  Py_intptr_t shape(int n) const { return get_shape()[n]; }
+  /// @brief Return the size of the nth dimension. raises IndexError if k not in [-get_nd() : get_nd()-1 ]
+  Py_intptr_t shape(int n) const;
 
-  /// @brief Return the stride of the nth dimension.
-  Py_intptr_t strides(int n) const { return get_strides()[n]; }
+  /// @brief Return the stride of the nth dimension. raises IndexError if k not in [-get_nd() : get_nd()-1]
+  Py_intptr_t strides(int n) const;
     
   /**
    *  @brief Return the array's raw data pointer.
@@ -176,7 +176,7 @@ ndarray from_data_impl(void * data,
 		       Container strides,
 		       object const & owner,
 		       bool writeable,
-		       typename boost::enable_if< boost::is_integral<typename Container::value_type> >::type * enabled = NULL)
+		       typename boost::enable_if< boost::python::detail::is_integral<typename Container::value_type> >::type * enabled = NULL)
 {
   std::vector<Py_intptr_t> shape_(shape.begin(),shape.end());
   std::vector<Py_intptr_t> strides_(strides.begin(), strides.end());

linx64/include/boost/python/numpy/ufunc.hpp

@@ -106,7 +106,7 @@ struct unary_ufunc
     dtype in_dtype = dtype::get_builtin<TArgument>();
     dtype out_dtype = dtype::get_builtin<TResult>();
     ndarray in_array = from_object(input, in_dtype, ndarray::ALIGNED);
-    ndarray out_array = (output != object()) ?
+    ndarray out_array = ! output.is_none() ?
       from_object(output, out_dtype, ndarray::ALIGNED | ndarray::WRITEABLE)
       : zeros(in_array.get_nd(), in_array.get_shape(), out_dtype);
     multi_iter iter = make_multi_iter(in_array, out_array);
@@ -171,7 +171,7 @@ struct binary_ufunc
     ndarray in1_array = from_object(input1, in1_dtype, ndarray::ALIGNED);
     ndarray in2_array = from_object(input2, in2_dtype, ndarray::ALIGNED);
     multi_iter iter = make_multi_iter(in1_array, in2_array);
-    ndarray out_array = (output != object())
+    ndarray out_array = !output.is_none()
       ? from_object(output, out_dtype, ndarray::ALIGNED | ndarray::WRITEABLE)
       : zeros(iter.get_nd(), iter.get_shape(), out_dtype);
     iter = make_multi_iter(in1_array, in2_array, out_array);