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value="Search" /> 49 <input type="hidden" name="check_keywords" value="yes" /> 50 <input type="hidden" name="area" value="default" /> 51 </form> 52 </div> 53 <script type="text/javascript">$('#searchbox').show(0);</script> 54 </td> 55 </tr> 56 </table> 57 </div> 58 <hr/> 59 <div class="content"> 60 <div class="navbar" style="text-align:right;"> 61 62 63 <a class="prev" title="Ufuncs" href="ufunc.html"><img src="../_static/prev.png" alt="prev"/></a> 64 <a class="up" title="Boost.Python NumPy extension Tutorial" href="index.html"><img src="../_static/up.png" alt="up"/></a> 65 <a class="next" title="Boost.Python NumPy extension Reference" href="../reference/index.html"><img src="../_static/next.png" alt="next"/></a> 66 67 </div> 68 69 <div class="section" id="how-to-access-data-using-raw-pointers"> 70<h1>How to access data using raw pointers</h1> 71<p>One of the advantages of the ndarray wrapper is that the same data can be used in both Python and C++ and changes can be made to reflect at both ends. 72The from_data method makes this possible.</p> 73<p>Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module:</p> 74<div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include</span> <span class="cpf"><boost/python/numpy.hpp></span><span class="cp"></span> 75<span class="cp">#include</span> <span class="cpf"><iostream></span><span class="cp"></span> 76 77<span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span> 78<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span> 79 80<span class="kt">int</span> <span class="nf">main</span><span class="p">(</span><span class="kt">int</span> <span class="n">argc</span><span class="p">,</span> <span class="kt">char</span> <span class="o">**</span><span class="n">argv</span><span class="p">)</span> 81<span class="p">{</span> 82 <span class="n">Py_Initialize</span><span class="p">();</span> 83 <span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span> 84</pre></div> 85</div> 86<p>Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray:</p> 87<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="n">arr</span><span class="p">[]</span> <span class="o">=</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">};</span> 88<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">py_array</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(),</span> 89 <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">5</span><span class="p">),</span> 90 <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="k">sizeof</span><span class="p">(</span><span class="kt">int</span><span class="p">)),</span> 91 <span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span> 92</pre></div> 93</div> 94<p>Print the source C++ array, as well as the ndarray, to check if they are the same:</p> 95<div class="highlight-c++"><div class="highlight"><pre><span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"C++ array :"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span> 96<span class="k">for</span> <span class="p">(</span><span class="kt">int</span> <span class="n">j</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="n">j</span><span class="o"><</span><span class="mi">4</span><span class="p">;</span><span class="n">j</span><span class="o">++</span><span class="p">)</span> 97<span class="p">{</span> 98 <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o"><<</span> <span class="sc">' '</span><span class="p">;</span> 99<span class="p">}</span> 100<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> 101 <span class="o"><<</span> <span class="s">"Python ndarray :"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">py_array</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span> 102</pre></div> 103</div> 104<p>Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array:</p> 105<div class="highlight-c++"><div class="highlight"><pre><span class="n">py_array</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="mi">5</span> <span class="p">;</span> 106<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Is the change reflected in the C++ array used to create the ndarray ? "</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span> 107<span class="k">for</span> <span class="p">(</span><span class="kt">int</span> <span class="n">j</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span> <span class="n">j</span> <span class="o"><</span> <span class="mi">5</span><span class="p">;</span> <span class="n">j</span><span class="o">++</span><span class="p">)</span> 108<span class="p">{</span> 109 <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o"><<</span> <span class="sc">' '</span><span class="p">;</span> 110<span class="p">}</span> 111</pre></div> 112</div> 113<p>Next, change an element of the source C++ array and see if it is reflected in the Python ndarray:</p> 114<div class="highlight-c++"><div class="highlight"><pre> <span class="n">arr</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="mi">8</span><span class="p">;</span> 115 <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> 116 <span class="o"><<</span> <span class="s">"Is the change reflected in the Python ndarray ?"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> 117 <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">py_array</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span> 118<span class="p">}</span> 119</pre></div> 120</div> 121<p>As we can see, the changes are reflected across the ends. This happens because the from_data method passes the C++ array by reference to create the ndarray, and thus uses the same locations for storing data.</p> 122</div> 123 124 125 <div class="navbar" style="text-align:right;"> 126 127 128 <a class="prev" title="Ufuncs" href="ufunc.html"><img src="../_static/prev.png" alt="prev"/></a> 129 <a class="up" title="Boost.Python NumPy extension Tutorial" href="index.html"><img src="../_static/up.png" alt="up"/></a> 130 <a class="next" title="Boost.Python NumPy extension Reference" href="../reference/index.html"><img src="../_static/next.png" alt="next"/></a> 131 132 </div> 133 </div> 134 </body> 135</html>
