{

// Initialize the Python runtime.

Py_Initialize();

// Initialize NumPy

np::initialize();

// Create an ndarray from a simple tuple

p::object tu = p::make_tuple('a','b','c') ;

np::ndarray example_tuple = np::array (tu) ;

// and from a list

p::list l ;

np::ndarray example_list = np::array (l) ;

// Optionally, you can also specify a dtype

np::dtype dt = np::dtype::get_builtin<int>();

np::ndarray example_list1 = np::array (l,dt);

// You can also create an array by supplying data.First,create an integer array

int data[] = {1,2,3,4} ;

// Create a shape, and strides, needed by the function

p::tuple shape = p::make_tuple(4) ;

p::tuple stride = p::make_tuple(4) ;

// The function also needs an owner, to keep track of the data array passed. Passing none is dangerous

p::object own ;

// The from_data function takes the data array, datatype,shape,stride and owner as arguments

// and returns an ndarray

np::ndarray data_ex = np::from_data(data,dt,shape,stride,own);

// Print the ndarray we created

std::cout << "Single dimensional array ::" << std::endl << p::extract < char const * > (p::str(data_ex)) << std::endl ;

// Now lets make an 3x2 ndarray from a multi-dimensional array using non-unit strides

// First lets create a 3x4 array of 8-bit integers

uint8_t mul_data[][4] = {{1,2,3,4},{5,6,7,8},{1,3,5,7}};

// Now let's create an array of 3x2 elements, picking the first and third elements from each row

// For that, the shape will be 3x2

shape = p::make_tuple(3,2) ;

// The strides will be 4x2 i.e. 4 bytes to go to the next desired row, and 2 bytes to go to the next desired column

stride = p::make_tuple(4,2) ;

// Get the numpy dtype for the built-in 8-bit integer data type

np::dtype dt1 = np::dtype::get_builtin<uint8_t>();

// First lets create and print out the ndarray as is

np::ndarray mul_data_ex = np::from_data(mul_data,dt1, p::make_tuple(3,4),p::make_tuple(4,1),p::object());

std::cout << "Original multi dimensional array :: " << std::endl << p::extract < char const * > (p::str(mul_data_ex)) << std::endl ;

// Now create the new ndarray using the shape and strides

mul_data_ex = np::from_data(mul_data,dt1, shape,stride,p::object());

// Print out the array we created using non-unit strides

std::cout << "Selective multidimensional array :: "<<std::endl << p::extract < char const * > (p::str(mul_data_ex)) << std::endl ;