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Documentation for 8a6f2052e2
This commit is contained in:
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@@ -317,14 +317,14 @@ Here is the call graph for this function:</div>
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<div class="line"><a id="l00379" name="l00379"></a><span class="lineno"> 379</span> }</div>
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<div class="line"><a id="l00380" name="l00380"></a><span class="lineno"> 380</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
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<div class="line"><a id="l00381" name="l00381"></a><span class="lineno"> 381</span> W[i] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector<std::valarray<double></a>>(num_out);</div>
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<div class="line"><a id="l00382" name="l00382"></a><span class="lineno"> 382</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
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<div class="line"><a id="l00383" name="l00383"></a><span class="lineno"> 383</span> W[i][k] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00382" name="l00382"></a><span class="lineno"> 382</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a> < num_out; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>++) {</div>
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<div class="line"><a id="l00383" name="l00383"></a><span class="lineno"> 383</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00384" name="l00384"></a><span class="lineno"> 384</span><span class="preprocessor">#ifdef _OPENMP</span></div>
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<div class="line"><a id="l00385" name="l00385"></a><span class="lineno"> 385</span><span class="preprocessor">#pragma omp for</span></div>
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<div class="line"><a id="l00386" name="l00386"></a><span class="lineno"> 386</span><span class="preprocessor">#endif</span></div>
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<div class="line"><a id="l00387" name="l00387"></a><span class="lineno"> 387</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
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<div class="line"><a id="l00388" name="l00388"></a><span class="lineno"> 388</span> <span class="comment">// preallocate with random initial weights</span></div>
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<div class="line"><a id="l00389" name="l00389"></a><span class="lineno"> 389</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00389" name="l00389"></a><span class="lineno"> 389</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00390" name="l00390"></a><span class="lineno"> 390</span> }</div>
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<div class="line"><a id="l00391" name="l00391"></a><span class="lineno"> 391</span> }</div>
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<div class="line"><a id="l00392" name="l00392"></a><span class="lineno"> 392</span> }</div>
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@@ -341,6 +341,7 @@ Here is the call graph for this function:</div>
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<div class="ttc" id="agroup__machine__learning_html_gaf5ce14f026d6d231bef29161bac2b485"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a></div><div class="ttdeci">double _random(double a, double b)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:53</div></div>
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<div class="ttc" id="akohonen__som__topology_8cpp_html_a48efb079040c7aaa3a4917a0e486cba9"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a48efb079040c7aaa3a4917a0e486cba9">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector< std::valarray< double > > *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:330</div></div>
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<div class="ttc" id="amax_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a></div><div class="ttdeci">T max(T... args)</div></div>
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<div class="ttc" id="amidpoint__integral__method_8cpp_html_ae9f66040f8e0ba73c1c741261c22a52a"><div class="ttname"><a href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">numerical_methods::midpoint_rule::k</a></div><div class="ttdeci">double k(double x)</div><div class="ttdoc">A function k(x) that will be used to test the method.</div><div class="ttdef"><b>Definition:</b> midpoint_integral_method.cpp:103</div></div>
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<div class="ttc" id="anamespacemachine__learning_html_aa72a53c88203fde278f1fe6c3afe5b07"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#aa72a53c88203fde278f1fe6c3afe5b07">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector< std::vector< std::valarray< double > > > &W)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:142</div></div>
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<div class="ttc" id="anamespacemachine__learning_html_ac43d294e21a0c4fa33c53757df054576"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ac43d294e21a0c4fa33c53757df054576">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector< std::valarray< double > > &X, std::vector< std::vector< std::valarray< double > > > *W, double alpha_min)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:269</div></div>
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<div class="ttc" id="avalarray_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a></div></div>
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@@ -386,14 +387,14 @@ Here is the call graph for this function:</div>
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<div class="line"><a id="l00461" name="l00461"></a><span class="lineno"> 461</span> }</div>
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<div class="line"><a id="l00462" name="l00462"></a><span class="lineno"> 462</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
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<div class="line"><a id="l00463" name="l00463"></a><span class="lineno"> 463</span> W[i] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector<std::valarray<double></a>>(num_out);</div>
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<div class="line"><a id="l00464" name="l00464"></a><span class="lineno"> 464</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
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<div class="line"><a id="l00465" name="l00465"></a><span class="lineno"> 465</span> W[i][k] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00464" name="l00464"></a><span class="lineno"> 464</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a> < num_out; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>++) {</div>
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<div class="line"><a id="l00465" name="l00465"></a><span class="lineno"> 465</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00466" name="l00466"></a><span class="lineno"> 466</span><span class="preprocessor">#ifdef _OPENMP</span></div>
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<div class="line"><a id="l00467" name="l00467"></a><span class="lineno"> 467</span><span class="preprocessor">#pragma omp for</span></div>
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<div class="line"><a id="l00468" name="l00468"></a><span class="lineno"> 468</span><span class="preprocessor">#endif</span></div>
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<div class="line"><a id="l00469" name="l00469"></a><span class="lineno"> 469</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
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<div class="line"><a id="l00470" name="l00470"></a><span class="lineno"> 470</span> <span class="comment">// preallocate with random initial weights</span></div>
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<div class="line"><a id="l00471" name="l00471"></a><span class="lineno"> 471</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00471" name="l00471"></a><span class="lineno"> 471</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00472" name="l00472"></a><span class="lineno"> 472</span> }</div>
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<div class="line"><a id="l00473" name="l00473"></a><span class="lineno"> 473</span> }</div>
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<div class="line"><a id="l00474" name="l00474"></a><span class="lineno"> 474</span> }</div>
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@@ -447,14 +448,14 @@ Here is the call graph for this function:</div>
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<div class="line"><a id="l00547" name="l00547"></a><span class="lineno"> 547</span> }</div>
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<div class="line"><a id="l00548" name="l00548"></a><span class="lineno"> 548</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
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<div class="line"><a id="l00549" name="l00549"></a><span class="lineno"> 549</span> W[i] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector<std::valarray<double></a>>(num_out);</div>
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<div class="line"><a id="l00550" name="l00550"></a><span class="lineno"> 550</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
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<div class="line"><a id="l00551" name="l00551"></a><span class="lineno"> 551</span> W[i][k] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00550" name="l00550"></a><span class="lineno"> 550</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a> < num_out; <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>++) {</div>
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<div class="line"><a id="l00551" name="l00551"></a><span class="lineno"> 551</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>] = <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray<double></a>(features);</div>
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<div class="line"><a id="l00552" name="l00552"></a><span class="lineno"> 552</span><span class="preprocessor">#ifdef _OPENMP</span></div>
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<div class="line"><a id="l00553" name="l00553"></a><span class="lineno"> 553</span><span class="preprocessor">#pragma omp for</span></div>
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<div class="line"><a id="l00554" name="l00554"></a><span class="lineno"> 554</span><span class="preprocessor">#endif</span></div>
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<div class="line"><a id="l00555" name="l00555"></a><span class="lineno"> 555</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
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<div class="line"><a id="l00556" name="l00556"></a><span class="lineno"> 556</span> <span class="comment">// preallocate with random initial weights</span></div>
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<div class="line"><a id="l00557" name="l00557"></a><span class="lineno"> 557</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00557" name="l00557"></a><span class="lineno"> 557</span> W[i][<a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ae9f66040f8e0ba73c1c741261c22a52a">k</a>][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
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<div class="line"><a id="l00558" name="l00558"></a><span class="lineno"> 558</span> }</div>
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<div class="line"><a id="l00559" name="l00559"></a><span class="lineno"> 559</span> }</div>
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<div class="line"><a id="l00560" name="l00560"></a><span class="lineno"> 560</span> }</div>
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@@ -446,13 +446,14 @@ Here is the call graph for this function:</div>
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<div class="line"><a id="l00291" name="l00291"></a><span class="lineno"> 291</span> <a class="code hl_classRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector<std::valarray<double></a>> current_pass = X;</div>
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<div class="line"><a id="l00292" name="l00292"></a><span class="lineno"> 292</span> details.<a class="code hl_functionRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/emplace_back.html">emplace_back</a>(X);</div>
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<div class="line"><a id="l00293" name="l00293"></a><span class="lineno"> 293</span> <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span> &l : <a class="code hl_namespace" href="../../d5/d2c/namespacelayers.html">layers</a>) {</div>
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<div class="line"><a id="l00294" name="l00294"></a><span class="lineno"> 294</span> current_pass = <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#a5342906d42b80fc6b6b3ad17bf00fcb9">multiply</a>(current_pass, l.kernel);</div>
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<div class="line"><a id="l00295" name="l00295"></a><span class="lineno"> 295</span> current_pass = <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ad0bdc88e5f1be47c46c0f0c8ebf754bb">apply_function</a>(current_pass, l.activation_function);</div>
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<div class="line"><a id="l00294" name="l00294"></a><span class="lineno"> 294</span> current_pass = <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#a5342906d42b80fc6b6b3ad17bf00fcb9">multiply</a>(current_pass, <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ad53616fb4fa6880ae876bcba53365c51">l</a>.kernel);</div>
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<div class="line"><a id="l00295" name="l00295"></a><span class="lineno"> 295</span> current_pass = <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ad0bdc88e5f1be47c46c0f0c8ebf754bb">apply_function</a>(current_pass, <a class="code hl_function" href="../../df/d11/midpoint__integral__method_8cpp.html#ad53616fb4fa6880ae876bcba53365c51">l</a>.activation_function);</div>
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<div class="line"><a id="l00296" name="l00296"></a><span class="lineno"> 296</span> details.<a class="code hl_functionRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/emplace_back.html">emplace_back</a>(current_pass);</div>
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<div class="line"><a id="l00297" name="l00297"></a><span class="lineno"> 297</span> }</div>
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<div class="line"><a id="l00298" name="l00298"></a><span class="lineno"> 298</span> <span class="keywordflow">return</span> details;</div>
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<div class="line"><a id="l00299" name="l00299"></a><span class="lineno"> 299</span> }</div>
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<div class="ttc" id="aemplace_back_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/emplace_back.html">std::vector::emplace_back</a></div><div class="ttdeci">T emplace_back(T... args)</div></div>
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<div class="ttc" id="amidpoint__integral__method_8cpp_html_ad53616fb4fa6880ae876bcba53365c51"><div class="ttname"><a href="../../df/d11/midpoint__integral__method_8cpp.html#ad53616fb4fa6880ae876bcba53365c51">numerical_methods::midpoint_rule::l</a></div><div class="ttdeci">double l(double x)</div><div class="ttdoc">A function l(x) that will be used to test the method.</div><div class="ttdef"><b>Definition:</b> midpoint_integral_method.cpp:109</div></div>
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<div class="ttc" id="anamespacemachine__learning_html_a5342906d42b80fc6b6b3ad17bf00fcb9"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a5342906d42b80fc6b6b3ad17bf00fcb9">machine_learning::multiply</a></div><div class="ttdeci">std::vector< std::valarray< T > > multiply(const std::vector< std::valarray< T > > &A, const std::vector< std::valarray< T > > &B)</div><div class="ttdef"><b>Definition:</b> vector_ops.hpp:460</div></div>
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<div class="ttc" id="anamespacemachine__learning_html_ad0bdc88e5f1be47c46c0f0c8ebf754bb"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ad0bdc88e5f1be47c46c0f0c8ebf754bb">machine_learning::apply_function</a></div><div class="ttdeci">std::vector< std::valarray< T > > apply_function(const std::vector< std::valarray< T > > &A, T(*func)(const T &))</div><div class="ttdef"><b>Definition:</b> vector_ops.hpp:329</div></div>
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<div class="ttc" id="avector_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a></div></div>
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