From 7add755ae07a4812737c6084ff07673b597e2d1e Mon Sep 17 00:00:00 2001
From: Ankit Daftery <ankitdaf@gmail.com>
Date: Fri, 5 Aug 2011 09:06:19 +0000
Subject: [PATCH] Added tutorial for dtype

---
 libs/numpy/doc/Jamfile   |  2 +-
 libs/numpy/doc/dtype.rst | 34 ++++++++++++++++++++++++++++++++++
 2 files changed, 35 insertions(+), 1 deletion(-)
 create mode 100644 libs/numpy/doc/dtype.rst

diff --git a/libs/numpy/doc/Jamfile b/libs/numpy/doc/Jamfile
index f76da2c4..bf38ffb7 100644
--- a/libs/numpy/doc/Jamfile
+++ b/libs/numpy/doc/Jamfile
@@ -6,7 +6,7 @@ project user-config : requirements <docutils-cmd>rst2html ;
 import docutils ;
 
 import path ;
-sources = tutorial.rst ndarray.rst ;
+sources = tutorial.rst dtype.rst ndarray.rst ;
 bases = $(sources:S=) ;
   
 # This is a path relative to the html/ subdirectory where the
diff --git a/libs/numpy/doc/dtype.rst b/libs/numpy/doc/dtype.rst
new file mode 100644
index 00000000..8aa0994a
--- /dev/null
+++ b/libs/numpy/doc/dtype.rst
@@ -0,0 +1,34 @@
+How to use dtypes
+=================
+
+Here is a brief tutorial to show how to create ndarrays with built-in python data types, and extract the types and values of member variables
+
+Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module::
+
+	#include <boost/numpy.hpp>
+	#include <iostream>
+
+	namespace p = boost::python;
+	namespace np = boost::numpy;
+
+	int main(int argc, char **argv)
+	{
+	  Py_Initialize();
+	  np::initialize();
+
+Next, we create the shape and dtype. We use the get_builtin method to get the numpy dtype corresponding to the builtin C++ dtype 
+Here, we will create a 3x3 array passing a tuple with (3,3) for the size, and double as the data type ::
+
+	  p::tuple shape = p::make_tuple(3, 3);
+	  np::dtype dtype = np::dtype::get_builtin<double>();
+	  np::ndarray a = np::zeros(shape, dtype);
+
+Finally, we can print the array using the extract method in the python namespace. 
+Here, we first convert the variable into a string, and then extract it as a C++ character array from the python string using the <char const \* > template ::
+
+	std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
+
+We can also print the dtypes of the data members of the ndarray by using the get_dtype method for the ndarray ::
+
+	std::cout << "Datatype is:\n" << p::extract<char const *>(p::str(a.get_dtype())) << std::endl ;
+	}