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  61. <div class="section" id="how-to-access-data-using-raw-pointers">
  62. <h1>How to access data using raw pointers</h1>
  63. <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.
  64. The from_data method makes this possible.</p>
  65. <p>Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module:</p>
  66. <div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include</span> <span class="cpf">&lt;boost/python/numpy.hpp&gt;</span><span class="cp"></span>
  67. <span class="cp">#include</span> <span class="cpf">&lt;iostream&gt;</span><span class="cp"></span>
  68. <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>
  69. <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>
  70. <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>
  71. <span class="p">{</span>
  72. <span class="n">Py_Initialize</span><span class="p">();</span>
  73. <span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span>
  74. </pre></div>
  75. </div>
  76. <p>Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray:</p>
  77. <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>
  78. <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">&lt;</span><span class="kt">int</span><span class="o">&gt;</span><span class="p">(),</span>
  79. <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>
  80. <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>
  81. <span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
  82. </pre></div>
  83. </div>
  84. <p>Print the source C++ array, as well as the ndarray, to check if they are the same:</p>
  85. <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">&lt;&lt;</span> <span class="s">&quot;C++ array :&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
  86. <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">&lt;</span><span class="mi">4</span><span class="p">;</span><span class="n">j</span><span class="o">++</span><span class="p">)</span>
  87. <span class="p">{</span>
  88. <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o">&lt;&lt;</span> <span class="sc">&#39; &#39;</span><span class="p">;</span>
  89. <span class="p">}</span>
  90. <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
  91. <span class="o">&lt;&lt;</span> <span class="s">&quot;Python ndarray :&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o">&lt;</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*&gt;</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">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
  92. </pre></div>
  93. </div>
  94. <p>Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array:</p>
  95. <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>
  96. <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;Is the change reflected in the C++ array used to create the ndarray ? &quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
  97. <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">&lt;</span> <span class="mi">5</span><span class="p">;</span> <span class="n">j</span><span class="o">++</span><span class="p">)</span>
  98. <span class="p">{</span>
  99. <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o">&lt;&lt;</span> <span class="sc">&#39; &#39;</span><span class="p">;</span>
  100. <span class="p">}</span>
  101. </pre></div>
  102. </div>
  103. <p>Next, change an element of the source C++ array and see if it is reflected in the Python ndarray:</p>
  104. <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>
  105. <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
  106. <span class="o">&lt;&lt;</span> <span class="s">&quot;Is the change reflected in the Python ndarray ?&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
  107. <span class="o">&lt;&lt;</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o">&lt;</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*&gt;</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">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
  108. <span class="p">}</span>
  109. </pre></div>
  110. </div>
  111. <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>
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