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Posted to commits@arrow.apache.org by uw...@apache.org on 2018/05/18 07:47:15 UTC
[14/51] [partial] arrow-site git commit: Update API docs
http://git-wip-us.apache.org/repos/asf/arrow-site/blob/c77df435/docs/cpp/numpy-internal_8h_source.html
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<div class="title">numpy-internal.h</div> </div>
</div><!--header-->
<div class="contents">
-<a href="numpy-internal_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">// Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// or more contributor license agreements. See the NOTICE file</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// distributed with this work for additional information</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">// regarding copyright ownership. The ASF licenses this file</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment">// to you under the Apache License, Version 2.0 (the</span></div><div class="line"><a name="l00006"></a><spa
n class="lineno"> 6</span> <span class="comment">// "License"); you may not use this file except in compliance</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment">// with the License. You may obtain a copy of the License at</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment">//</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// http://www.apache.org/licenses/LICENSE-2.0</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment">//</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment">// Unless required by applicable law or agreed to in writing,</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment">// software distri
buted under the License is distributed on an</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment">// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment">// KIND, either express or implied. See the License for the</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment">// specific language governing permissions and limitations</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">// under the License.</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment">// Internal utilities for dealing with NumPy</span></div><div class="line"><a name="l00019"></a><s
pan class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#ifndef ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#define ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include "<a class="code" href="numpy__interop_8h.html">arrow/python/numpy_interop.h</a>"</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="platform_8h.html">arrow/python/platform.h</a>"</span></div><div class="line"><a name="l00026"></a><span class="l
ineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <cstdint></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace </span><a class="code" href="namespacearrow.html">arrow</a> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span>py {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00035"></a><sp
an class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html"> 35</a></span> <span class="keyword">class </span><a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html">Ndarray1DIndexer</a> {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00037"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e"> 37</a></span>  <span class="keyword">typedef</span> int64_t <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a>;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a17a7c880dd72b47f5ba74d9ba255ff89"> 39</a></span>  <a class="code
" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a17a7c880dd72b47f5ba74d9ba255ff89">Ndarray1DIndexer</a>() : arr_(nullptr), data_(nullptr) {}</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#ad35c314063aa4e67a8df2b0a3714b57d"> 41</a></span>  <span class="keyword">explicit</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#ad35c314063aa4e67a8df2b0a3714b57d">Ndarray1DIndexer</a>(PyArrayObject* arr) : <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html">Ndarray1DIndexer</a>() { <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315">Init</a>(arr); }</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="classarrow
_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315"> 43</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315">Init</a>(PyArrayObject* arr) {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  arr_ = arr;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="logging_8h.html#ae89df3243bbb8341130c7b3f44145ea0">DCHECK_EQ</a>(1, PyArray_NDIM(arr)) << <span class="stringliteral">"Only works with 1-dimensional arrays"</span>;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  Py_INCREF(arr);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  data_ = <span class="keyword">reinterpret_cast<</span>T*<span class="keyword">></span>(PyArray_DATA(arr));</div><div class="line"><a name="l00048">
</a><span class="lineno"> 48</span>  stride_ = PyArray_STRIDES(arr)[0] / <span class="keyword">sizeof</span>(T);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a4c24bc66a76b98150fcceea2063ba641"> 51</a></span>  <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a4c24bc66a76b98150fcceea2063ba641">~Ndarray1DIndexer</a>() { Py_XDECREF(arr_); }</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10efabad98d436019f1a04"> 53</a></span>  int64_t <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10e
fabad98d436019f1a04">size</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> PyArray_SIZE(arr_); }</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb"> 55</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">data</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> data_; }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7"> 57</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7">begin</a>
()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">data</a>(); }</div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a56d28a2d587932ff078b079c77a7f8ff"> 58</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a56d28a2d587932ff078b079c77a7f8ff">end</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7">begin</a>() + <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10efabad98d436019f1a04">size</a>() * stride_; }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="class
arrow_1_1py_1_1_ndarray1_d_indexer.html#a7163a1a2a2e4ce2ac7eeda40c08f4cfb"> 60</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a7163a1a2a2e4ce2ac7eeda40c08f4cfb">is_strided</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> stride_ == 1; }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a8ba63684282273881e5b4b3cb844e183"> 62</a></span>  T& <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a8ba63684282273881e5b4b3cb844e183">operator[]</a>(<a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a> index) { <span class="keywordflow">return</span> data_[index * stride_]; }</div><div class="line"><a name="l00063"></a><span class="l
ineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a9835daa2afea41b64ca76393aa98b93e"> 63</a></span>  T& <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a9835daa2afea41b64ca76393aa98b93e">operator[]</a>(<a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a> index)<span class="keyword"> const </span>{ <span class="keywordflow">return</span> data_[index * stride_]; }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  PyArrayObject* arr_;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  T* data_;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  int64_t stride_;</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> };</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment">// Handling of Numpy Types by their static numbers</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment">// (the NPY_TYPES enum and related defines)</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keyword">static</span> <span class="keyword">inline</span> std::string GetNumPyTypeName(<span class="keywordtype">int</span> npy_type) {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="preprocessor">#define TYPE_CASE(TYPE, NAME) \</span></div><div class="line"><a name="l00076"></a><sp
an class="lineno"> 76</span> <span class="preprocessor"> case NPY_##TYPE: \</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="preprocessor"> return NAME;</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">switch</span> (npy_type) {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(BOOL, <span class="stringliteral">"bool"</span>)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT8, "<a class="code" href="namespacearrow.html#a9c09bf26bc03f0fb0c84a0277215dd67">int8</a>")</div><div cla
ss="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT16, "<a class="code" href="namespacearrow.html#a034c5c703e15039fe76af412d349734d">int16</a>")</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT32, "<a class="code" href="namespacearrow.html#a86f6bfe394347f77befa2143297ad541">int32</a>")</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT64, "<a class="code" href="namespacearrow.html#a733b16be653069b8d926529662e34e79">int64</a>")</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="preprocessor">#if !NPY_INT32_IS_INT</span></div><d
iv class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT, <span class="stringliteral">"intc"</span>)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(LONGLONG, <span class="stringliteral">"longlong"</span>)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="numpy-internal_
8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT8, <span class="stringliteral">"uint8"</span>)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT16, "<a class="code" href="namespacearrow.html#a9f1e44bc2ab9b465b6e7b601eb48f0a0">uint16</a>")</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT32, "<a class="code" href="namespacearrow.html#ae80e510cfb2931ac18c73cba0be6d894">uint32</a>")</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT64, "<a class="code" href="namespacearrow.html#ae548d03275f4afaa97a269774ce6930c">uint64</a>")</div><div
class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="preprocessor">#if !NPY_INT32_IS_INT</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT, <span class="stringliteral">"uintc"</span>)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(ULONGLONG, <span class="stringliteral">"ulonglong"</span>)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="preprocesso
r">#endif</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT16, <span class="stringliteral">"float16"</span>)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT32, "<a class="code" href="namespacearrow.html#a48fca9d26feda61c8255ec3c44a2078c">float32</a>")</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT64, "<a class="code" href="namespacearrow.html#ab6f514320a9b037ab161fa97db73b970">float64</a>")</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184
f6d3977bcad8220">TYPE_CASE</a>(DATETIME, "datetime64")</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(OBJECT, "<span class="keywordtype">object</span>")</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(VOID, "<span class="keywordtype">void</span>")</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  default:</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  break;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  }</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span
class="preprocessor">#undef TYPE_CASE</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  std::stringstream ss;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  ss << <span class="stringliteral">"unrecognized type ("</span> << npy_type << <span class="stringliteral">") in GetNumPyTypeName"</span>;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> ss.str();</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06"> 117</a></span> <span class="preprocessor">#define TYPE_VISIT_INLINE(TYPE) \</span></div><div class="line"><a name="l00118"></a><
span class="lineno"> 118</span> <span class="preprocessor"> case NPY_##TYPE: \</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="preprocessor"> return visitor->template Visit<NPY_##TYPE>(arr);</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="keyword">template</span> <<span class="keyword">typename</span> VISITOR></div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="namespacearrow_1_1py.html#a52c0b9dd7f438cb97fb897f1e6bf04b1"> 122</a></span> <span class="keyword">inline</span> <a class="code" href="classarrow_1_1_status.html">Status</a> <a class="code" href="namespacearrow_1_1py.html#a52c0b9dd7f438cb97fb897f1e6bf04b1">VisitNumpyArrayInline</a>(PyArrayObject* arr, VISITOR* visitor) {</div><div class="line"><a name="l0012
3"></a><span class="lineno"> 123</span>  <span class="keywordflow">switch</span> (PyArray_TYPE(arr)) {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(BOOL);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT8);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT8);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT16);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code
" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT16);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT32);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT32);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT64);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT64);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="preprocessor">
#if !NPY_INT32_IS_INT</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(LONGLONG);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href=
"numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(ULONGLONG);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT16);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT32);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT64);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLIN
E</a>(DATETIME);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(OBJECT);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::stringstream ss;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  ss << <span class="stringliteral">"NumPy type not implemented: "</span> << GetNumPyTypeName(PyArray_TYPE(arr));</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1_status.html#ab33edfeaca5f374e024ab0b72019a25a">Status::NotImplemented</a>(ss.str());</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> }</div><div class="line"><a name="l0015
1"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="preprocessor">#undef TYPE_VISIT_INLINE</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> } <span class="comment">// namespace py</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> } <span class="comment">// namespace arrow</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="preprocessor">#endif // ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a07dca18024c2f204e46da889fcca76fb"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">ar
row::py::Ndarray1DIndexer::data</a></div><div class="ttdeci">T * data() const</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:55</div></div>
+<a href="numpy-internal_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">// Licensed to the Apache Software Foundation (ASF) under one</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// or more contributor license agreements. See the NOTICE file</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// distributed with this work for additional information</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">// regarding copyright ownership. The ASF licenses this file</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment">// to you under the Apache License, Version 2.0 (the</span></div><div class="line"><a name="l00006"></a><spa
n class="lineno"> 6</span> <span class="comment">// "License"); you may not use this file except in compliance</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment">// with the License. You may obtain a copy of the License at</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment">//</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// http://www.apache.org/licenses/LICENSE-2.0</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment">//</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment">// Unless required by applicable law or agreed to in writing,</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment">// software distri
buted under the License is distributed on an</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment">// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment">// KIND, either express or implied. See the License for the</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment">// specific language governing permissions and limitations</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">// under the License.</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment">// Internal utilities for dealing with NumPy</span></div><div class="line"><a name="l00019"></a><s
pan class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#ifndef ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#define ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include "<a class="code" href="numpy__interop_8h.html">arrow/python/numpy_interop.h</a>"</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="platform_8h.html">arrow/python/platform.h</a>"</span></div><div class="line"><a name="l00026"></a><span class="l
ineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <cstdint></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace </span><a class="code" href="namespacearrow.html">arrow</a> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span>py {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00035"></a><sp
an class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html"> 35</a></span> <span class="keyword">class </span><a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html">Ndarray1DIndexer</a> {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00037"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e"> 37</a></span>  <span class="keyword">typedef</span> int64_t <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a>;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a17a7c880dd72b47f5ba74d9ba255ff89"> 39</a></span>  <a class="code
" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a17a7c880dd72b47f5ba74d9ba255ff89">Ndarray1DIndexer</a>() : arr_(nullptr), data_(nullptr) {}</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#ad35c314063aa4e67a8df2b0a3714b57d"> 41</a></span>  <span class="keyword">explicit</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#ad35c314063aa4e67a8df2b0a3714b57d">Ndarray1DIndexer</a>(PyArrayObject* arr) : <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html">Ndarray1DIndexer</a>() { <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315">Init</a>(arr); }</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="classarrow
_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315"> 43</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315">Init</a>(PyArrayObject* arr) {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  arr_ = arr;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="logging_8h.html#ae89df3243bbb8341130c7b3f44145ea0">DCHECK_EQ</a>(1, PyArray_NDIM(arr)) << <span class="stringliteral">"Only works with 1-dimensional arrays"</span>;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  Py_INCREF(arr);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  data_ = <span class="keyword">reinterpret_cast<</span>T*<span class="keyword">></span>(PyArray_DATA(arr));</div><div class="line"><a name="l00048">
</a><span class="lineno"> 48</span>  stride_ = PyArray_STRIDES(arr)[0] / <span class="keyword">sizeof</span>(T);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a4c24bc66a76b98150fcceea2063ba641"> 51</a></span>  <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a4c24bc66a76b98150fcceea2063ba641">~Ndarray1DIndexer</a>() { Py_XDECREF(arr_); }</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10efabad98d436019f1a04"> 53</a></span>  int64_t <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10e
fabad98d436019f1a04">size</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> PyArray_SIZE(arr_); }</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb"> 55</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">data</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> data_; }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7"> 57</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7">begin</a>
()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">data</a>(); }</div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a56d28a2d587932ff078b079c77a7f8ff"> 58</a></span>  T* <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a56d28a2d587932ff078b079c77a7f8ff">end</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a55c3de74319953a6c3649526c38ebfc7">begin</a>() + <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a65a7dd1e9e10efabad98d436019f1a04">size</a>() * stride_; }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="class
arrow_1_1py_1_1_ndarray1_d_indexer.html#a7163a1a2a2e4ce2ac7eeda40c08f4cfb"> 60</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a7163a1a2a2e4ce2ac7eeda40c08f4cfb">is_strided</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> stride_ != 1; }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a8ba63684282273881e5b4b3cb844e183"> 62</a></span>  T& <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a8ba63684282273881e5b4b3cb844e183">operator[]</a>(<a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a> index) { <span class="keywordflow">return</span> data_[index * stride_]; }</div><div class="line"><a name="l00063"></a><span class="l
ineno"><a class="line" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a9835daa2afea41b64ca76393aa98b93e"> 63</a></span>  T& <a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a9835daa2afea41b64ca76393aa98b93e">operator[]</a>(<a class="code" href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">size_type</a> index)<span class="keyword"> const </span>{ <span class="keywordflow">return</span> data_[index * stride_]; }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  PyArrayObject* arr_;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  T* data_;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  int64_t stride_;</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> };</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment">// Handling of Numpy Types by their static numbers</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment">// (the NPY_TYPES enum and related defines)</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keyword">static</span> <span class="keyword">inline</span> std::string GetNumPyTypeName(<span class="keywordtype">int</span> npy_type) {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="preprocessor">#define TYPE_CASE(TYPE, NAME) \</span></div><div class="line"><a name="l00076"></a><sp
an class="lineno"> 76</span> <span class="preprocessor"> case NPY_##TYPE: \</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="preprocessor"> return NAME;</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">switch</span> (npy_type) {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(BOOL, <span class="stringliteral">"bool"</span>)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT8, "<a class="code" href="namespacearrow.html#a9c09bf26bc03f0fb0c84a0277215dd67">int8</a>")</div><div cla
ss="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT16, "<a class="code" href="namespacearrow.html#a034c5c703e15039fe76af412d349734d">int16</a>")</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT32, "<a class="code" href="namespacearrow.html#a86f6bfe394347f77befa2143297ad541">int32</a>")</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT64, "<a class="code" href="namespacearrow.html#a733b16be653069b8d926529662e34e79">int64</a>")</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="preprocessor">#if !NPY_INT32_IS_INT</span></div><d
iv class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(INT, <span class="stringliteral">"intc"</span>)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(LONGLONG, <span class="stringliteral">"longlong"</span>)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="numpy-internal_
8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT8, <span class="stringliteral">"uint8"</span>)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT16, "<a class="code" href="namespacearrow.html#a9f1e44bc2ab9b465b6e7b601eb48f0a0">uint16</a>")</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT32, "<a class="code" href="namespacearrow.html#ae80e510cfb2931ac18c73cba0be6d894">uint32</a>")</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT64, "<a class="code" href="namespacearrow.html#ae548d03275f4afaa97a269774ce6930c">uint64</a>")</div><div
class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="preprocessor">#if !NPY_INT32_IS_INT</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(UINT, <span class="stringliteral">"uintc"</span>)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(ULONGLONG, <span class="stringliteral">"ulonglong"</span>)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="preprocesso
r">#endif</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT16, <span class="stringliteral">"float16"</span>)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT32, "<a class="code" href="namespacearrow.html#a48fca9d26feda61c8255ec3c44a2078c">float32</a>")</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(FLOAT64, "<a class="code" href="namespacearrow.html#ab6f514320a9b037ab161fa97db73b970">float64</a>")</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184
f6d3977bcad8220">TYPE_CASE</a>(DATETIME, "datetime64")</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(OBJECT, "<span class="keywordtype">object</span>")</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a>(VOID, "<span class="keywordtype">void</span>")</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  default:</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  break;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  }</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span
class="preprocessor">#undef TYPE_CASE</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  std::stringstream ss;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  ss << <span class="stringliteral">"unrecognized type ("</span> << npy_type << <span class="stringliteral">") in GetNumPyTypeName"</span>;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> ss.str();</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06"> 117</a></span> <span class="preprocessor">#define TYPE_VISIT_INLINE(TYPE) \</span></div><div class="line"><a name="l00118"></a><
span class="lineno"> 118</span> <span class="preprocessor"> case NPY_##TYPE: \</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="preprocessor"> return visitor->template Visit<NPY_##TYPE>(arr);</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="keyword">template</span> <<span class="keyword">typename</span> VISITOR></div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="namespacearrow_1_1py.html#a52c0b9dd7f438cb97fb897f1e6bf04b1"> 122</a></span> <span class="keyword">inline</span> <a class="code" href="classarrow_1_1_status.html">Status</a> <a class="code" href="namespacearrow_1_1py.html#a52c0b9dd7f438cb97fb897f1e6bf04b1">VisitNumpyArrayInline</a>(PyArrayObject* arr, VISITOR* visitor) {</div><div class="line"><a name="l0012
3"></a><span class="lineno"> 123</span>  <span class="keywordflow">switch</span> (PyArray_TYPE(arr)) {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(BOOL);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT8);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT8);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT16);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code
" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT16);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT32);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT32);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT64);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT64);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="preprocessor">
#if !NPY_INT32_IS_INT</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(INT);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(UINT);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="preprocessor">#if !NPY_INT64_IS_LONG_LONG</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(LONGLONG);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href=
"numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(ULONGLONG);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT16);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT32);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(FLOAT64);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLIN
E</a>(DATETIME);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a>(OBJECT);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::stringstream ss;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  ss << <span class="stringliteral">"NumPy type not implemented: "</span> << GetNumPyTypeName(PyArray_TYPE(arr));</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">return</span> <a class="code" href="classarrow_1_1_status.html#ab33edfeaca5f374e024ab0b72019a25a">Status::NotImplemented</a>(ss.str());</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> }</div><div class="line"><a name="l0015
1"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="preprocessor">#undef TYPE_VISIT_INLINE</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> } <span class="comment">// namespace py</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> } <span class="comment">// namespace arrow</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="preprocessor">#endif // ARROW_PYTHON_NUMPY_INTERNAL_H</span></div><div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a07dca18024c2f204e46da889fcca76fb"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a07dca18024c2f204e46da889fcca76fb">ar
row::py::Ndarray1DIndexer::data</a></div><div class="ttdeci">T * data() const</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:55</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a4c24bc66a76b98150fcceea2063ba641"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a4c24bc66a76b98150fcceea2063ba641">arrow::py::Ndarray1DIndexer::~Ndarray1DIndexer</a></div><div class="ttdeci">~Ndarray1DIndexer()</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:51</div></div>
<div class="ttc" id="namespacearrow_html_a034c5c703e15039fe76af412d349734d"><div class="ttname"><a href="namespacearrow.html#a034c5c703e15039fe76af412d349734d">arrow::int16</a></div><div class="ttdeci">std::shared_ptr< DataType > int16()</div></div>
<div class="ttc" id="namespacearrow_html_a9f1e44bc2ab9b465b6e7b601eb48f0a0"><div class="ttname"><a href="namespacearrow.html#a9f1e44bc2ab9b465b6e7b601eb48f0a0">arrow::uint16</a></div><div class="ttdeci">std::shared_ptr< DataType > uint16()</div></div>
@@ -78,7 +78,7 @@ $(function() {
<div class="ttc" id="platform_8h_html"><div class="ttname"><a href="platform_8h.html">platform.h</a></div></div>
<div class="ttc" id="namespacearrow_html_ae80e510cfb2931ac18c73cba0be6d894"><div class="ttname"><a href="namespacearrow.html#ae80e510cfb2931ac18c73cba0be6d894">arrow::uint32</a></div><div class="ttdeci">std::shared_ptr< DataType > uint32()</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_aabdf59a87c8a78ecec53aab4ec603315"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#aabdf59a87c8a78ecec53aab4ec603315">arrow::py::Ndarray1DIndexer::Init</a></div><div class="ttdeci">void Init(PyArrayObject *arr)</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:43</div></div>
-<div class="ttc" id="classarrow_1_1_status_html"><div class="ttname"><a href="classarrow_1_1_status.html">arrow::Status</a></div><div class="ttdef"><b>Definition:</b> status.h:106</div></div>
+<div class="ttc" id="classarrow_1_1_status_html"><div class="ttname"><a href="classarrow_1_1_status.html">arrow::Status</a></div><div class="ttdef"><b>Definition:</b> status.h:93</div></div>
<div class="ttc" id="namespacearrow_html_ae548d03275f4afaa97a269774ce6930c"><div class="ttname"><a href="namespacearrow.html#ae548d03275f4afaa97a269774ce6930c">arrow::uint64</a></div><div class="ttdeci">std::shared_ptr< DataType > uint64()</div></div>
<div class="ttc" id="numpy-internal_8h_html_a6d9f06383c97b89a49f0f0d715c17c06"><div class="ttname"><a href="numpy-internal_8h.html#a6d9f06383c97b89a49f0f0d715c17c06">TYPE_VISIT_INLINE</a></div><div class="ttdeci">#define TYPE_VISIT_INLINE(TYPE)</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:117</div></div>
<div class="ttc" id="namespacearrow_html_a9c09bf26bc03f0fb0c84a0277215dd67"><div class="ttname"><a href="namespacearrow.html#a9c09bf26bc03f0fb0c84a0277215dd67">arrow::int8</a></div><div class="ttdeci">std::shared_ptr< DataType > int8()</div></div>
@@ -91,14 +91,14 @@ $(function() {
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a7163a1a2a2e4ce2ac7eeda40c08f4cfb"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a7163a1a2a2e4ce2ac7eeda40c08f4cfb">arrow::py::Ndarray1DIndexer::is_strided</a></div><div class="ttdeci">bool is_strided() const</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:60</div></div>
<div class="ttc" id="numpy-internal_8h_html_a0ab91150fb3672184f6d3977bcad8220"><div class="ttname"><a href="numpy-internal_8h.html#a0ab91150fb3672184f6d3977bcad8220">TYPE_CASE</a></div><div class="ttdeci">#define TYPE_CASE(TYPE, NAME)</div></div>
<div class="ttc" id="namespacearrow_html"><div class="ttname"><a href="namespacearrow.html">arrow</a></div><div class="ttdoc">Top-level namespace for Apache Arrow C++ API. </div><div class="ttdef"><b>Definition:</b> adapter.h:32</div></div>
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+<div class="ttc" id="logging_8h_html_ae89df3243bbb8341130c7b3f44145ea0"><div class="ttname"><a href="logging_8h.html#ae89df3243bbb8341130c7b3f44145ea0">DCHECK_EQ</a></div><div class="ttdeci">#define DCHECK_EQ(val1, val2)</div><div class="ttdef"><b>Definition:</b> logging.h:95</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_ad35c314063aa4e67a8df2b0a3714b57d"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#ad35c314063aa4e67a8df2b0a3714b57d">arrow::py::Ndarray1DIndexer::Ndarray1DIndexer</a></div><div class="ttdeci">Ndarray1DIndexer(PyArrayObject *arr)</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:41</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a56d28a2d587932ff078b079c77a7f8ff"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a56d28a2d587932ff078b079c77a7f8ff">arrow::py::Ndarray1DIndexer::end</a></div><div class="ttdeci">T * end() const</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:58</div></div>
<div class="ttc" id="namespacearrow_html_ab6f514320a9b037ab161fa97db73b970"><div class="ttname"><a href="namespacearrow.html#ab6f514320a9b037ab161fa97db73b970">arrow::float64</a></div><div class="ttdeci">std::shared_ptr< DataType > float64()</div></div>
<div class="ttc" id="numpy__interop_8h_html"><div class="ttname"><a href="numpy__interop_8h.html">numpy_interop.h</a></div></div>
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<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a9835daa2afea41b64ca76393aa98b93e"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a9835daa2afea41b64ca76393aa98b93e">arrow::py::Ndarray1DIndexer::operator[]</a></div><div class="ttdeci">T & operator[](size_type index) const</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:63</div></div>
-<div class="ttc" id="classarrow_1_1_status_html_ab33edfeaca5f374e024ab0b72019a25a"><div class="ttname"><a href="classarrow_1_1_status.html#ab33edfeaca5f374e024ab0b72019a25a">arrow::Status::NotImplemented</a></div><div class="ttdeci">static Status NotImplemented(const std::string &msg)</div><div class="ttdef"><b>Definition:</b> status.h:138</div></div>
+<div class="ttc" id="classarrow_1_1_status_html_ab33edfeaca5f374e024ab0b72019a25a"><div class="ttname"><a href="classarrow_1_1_status.html#ab33edfeaca5f374e024ab0b72019a25a">arrow::Status::NotImplemented</a></div><div class="ttdeci">static Status NotImplemented(const std::string &msg)</div><div class="ttdef"><b>Definition:</b> status.h:125</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html_a1292bfad93b4aa33d53af65828842a0e"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html#a1292bfad93b4aa33d53af65828842a0e">arrow::py::Ndarray1DIndexer::size_type</a></div><div class="ttdeci">int64_t size_type</div><div class="ttdef"><b>Definition:</b> numpy-internal.h:37</div></div>
<div class="ttc" id="classarrow_1_1py_1_1_ndarray1_d_indexer_html"><div class="ttname"><a href="classarrow_1_1py_1_1_ndarray1_d_indexer.html">arrow::py::Ndarray1DIndexer</a></div><div class="ttdoc">Indexing convenience for interacting with strided 1-dim ndarray objects. </div><div class="ttdef"><b>Definition:</b> numpy-internal.h:35</div></div>
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http://git-wip-us.apache.org/repos/asf/arrow-site/blob/c77df435/docs/cpp/numpy__convert_8h_source.html
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@@ -75,7 +75,7 @@ $(function() {
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<div class="ttc" id="platform_8h_html"><div class="ttname"><a href="platform_8h.html">platform.h</a></div></div>
<div class="ttc" id="namespacearrow_1_1py_html_acf548283df305290d6797233eb10ea8f"><div class="ttname"><a href="namespacearrow_1_1py.html#acf548283df305290d6797233eb10ea8f">arrow::py::NdarrayToTensor</a></div><div class="ttdeci">Status NdarrayToTensor(MemoryPool *pool, PyObject *ao, std::shared_ptr< Tensor > *out)</div></div>
-<div class="ttc" id="classarrow_1_1_status_html"><div class="ttname"><a href="classarrow_1_1_status.html">arrow::Status</a></div><div class="ttdef"><b>Definition:</b> status.h:106</div></div>
+<div class="ttc" id="classarrow_1_1_status_html"><div class="ttname"><a href="classarrow_1_1_status.html">arrow::Status</a></div><div class="ttdef"><b>Definition:</b> status.h:93</div></div>
<div class="ttc" id="namespacearrow_1_1py_html_a2dc076087e72fcc661e948407e631d44"><div class="ttname"><a href="namespacearrow_1_1py.html#a2dc076087e72fcc661e948407e631d44">arrow::py::cast_npy_type_compat</a></div><div class="ttdeci">int cast_npy_type_compat(int type_num)</div></div>
<div class="ttc" id="namespacearrow_1_1py_html_a1d8a85306c0b562037827048b2db437e"><div class="ttname"><a href="namespacearrow_1_1py.html#a1d8a85306c0b562037827048b2db437e">arrow::py::is_contiguous</a></div><div class="ttdeci">bool is_contiguous(PyObject *array)</div></div>
<div class="ttc" id="visibility_8h_html"><div class="ttname"><a href="visibility_8h.html">visibility.h</a></div></div>
@@ -85,7 +85,7 @@ $(function() {
<div class="ttc" id="namespacearrow_1_1py_html_a9d0ba3df1922f37090d3de6db967aa72"><div class="ttname"><a href="namespacearrow_1_1py.html#a9d0ba3df1922f37090d3de6db967aa72">arrow::py::NumPyDtypeToArrow</a></div><div class="ttdeci">Status NumPyDtypeToArrow(PyObject *dtype, std::shared_ptr< DataType > *out)</div></div>
<div class="ttc" id="classarrow_1_1_memory_pool_html"><div class="ttname"><a href="classarrow_1_1_memory_pool.html">arrow::MemoryPool</a></div><div class="ttdoc">Base class for memory allocation. </div><div class="ttdef"><b>Definition:</b> memory_pool.h:34</div></div>
<div class="ttc" id="classarrow_1_1_buffer_html"><div class="ttname"><a href="classarrow_1_1_buffer.html">arrow::Buffer</a></div><div class="ttdoc">Object containing a pointer to a piece of contiguous memory with a particular size. </div><div class="ttdef"><b>Definition:</b> buffer.h:48</div></div>
-<div class="ttc" id="classarrow_1_1_data_type_html"><div class="ttname"><a href="classarrow_1_1_data_type.html">arrow::DataType</a></div><div class="ttdef"><b>Definition:</b> type.h:136</div></div>
+<div class="ttc" id="classarrow_1_1_data_type_html"><div class="ttname"><a href="classarrow_1_1_data_type.html">arrow::DataType</a></div><div class="ttdef"><b>Definition:</b> type.h:137</div></div>
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http://git-wip-us.apache.org/repos/asf/arrow-site/blob/c77df435/docs/cpp/pages.html
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@@ -73,6 +73,7 @@ $(function() {
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