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python/external/boost/libs/numpy/doc/tutorial/simple.rst
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python/external/boost/libs/numpy/doc/tutorial/simple.rst
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A simple tutorial on Arrays
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===========================
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Let's start with a simple tutorial to create and modify arrays.
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Get the necessary headers for numpy components and set up necessary namespaces::
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#include <boost/numpy.hpp>
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#include <iostream>
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namespace p = boost::python;
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namespace np = boost::numpy;
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Initialise the Python runtime, and the numpy module. Failure to call these results in segmentation errors::
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int main(int argc, char **argv)
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{
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Py_Initialize();
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np::initialize();
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Zero filled n-dimensional arrays can be created using the shape and data-type of the array as a parameter. Here, the shape is 3x3 and the datatype is the built-in float type::
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p::tuple shape = p::make_tuple(3, 3);
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np::dtype dtype = np::dtype::get_builtin<float>();
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np::ndarray a = np::zeros(shape, dtype);
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You can also create an empty array like this ::
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np::ndarray b = np::empty(shape,dtype);
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Print the original and reshaped array. The array a which is a list is first converted to a string, and each value in the list is extracted using extract< >::
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std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
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// Reshape the array into a 1D array
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a = a.reshape(p::make_tuple(9));
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// Print it again.
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std::cout << "Reshaped array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
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}
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