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2020-06-22 11:54:53 +00:00
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2
annotated.html
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@@ -141,7 +141,7 @@ $(document).ready(function(){initNavTree('annotated.html',''); initResizable();
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classes.html
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@@ -184,7 +184,7 @@ $(document).ready(function(){initNavTree('classes.html',''); initResizable(); })
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d0/d01/smallest__circle_8cpp.html
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@@ -563,7 +563,7 @@ Here is the call graph for this function:</div>
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<li class="navelem"><a class="el" href="../../dir_9510827d0b234b3cc54b29892f217477.html">others</a></li><li class="navelem"><a class="el" href="../../d0/d01/smallest__circle_8cpp.html">smallest_circle.cpp</a></li>
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d0/d08/realtime__stats_8cpp.html
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@@ -304,7 +304,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_296d53ceaeaa7e099814a6def439fe8a.html">math</a></li><li class="navelem"><a class="el" href="../../d0/d08/realtime__stats_8cpp.html">realtime_stats.cpp</a></li>
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d0/d0d/structmst-members.html
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@@ -105,7 +105,7 @@ $(document).ready(function(){initNavTree('d1/d77/structmst.html','../../'); init
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@@ -113,7 +113,7 @@ $(document).ready(function(){initNavTree('d5/d15/classcll.html','../../'); initR
<!-- start footer part -->
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d0/d78/classstatistics_1_1stats__computer1-members.html
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@@ -111,7 +111,7 @@ $(document).ready(function(){initNavTree('d7/d7c/classstatistics_1_1stats__compu
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d0/da2/number__of__positive__divisors_8cpp.html
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@@ -232,7 +232,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_296d53ceaeaa7e099814a6def439fe8a.html">math</a></li><li class="navelem"><a class="el" href="../../d0/da2/number__of__positive__divisors_8cpp.html">number_of_positive_divisors.cpp</a></li>
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d0/db6/non__recursive__merge__sort_8cpp.html
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@@ -144,7 +144,7 @@ int&#160;</td><td class="memItemRight" valign="bottom"><b>main</b> (int argc, ch
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_bb1b521853a9c46347182a9d10420771.html">sorting</a></li><li class="navelem"><a class="el" href="../../d0/db6/non__recursive__merge__sort_8cpp.html">non_recursive_merge_sort.cpp</a></li>
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@@ -107,7 +107,7 @@ $(document).ready(function(){initNavTree('d8/dc8/struct_point.html','../../'); i
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d0/dd2/class_queue___array.html
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@@ -139,7 +139,7 @@ int&#160;</td><td class="memItemRight" valign="bottom"><b>size</b></td></tr>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d0/dd2/class_queue___array.html">Queue_Array</a></li>
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d0/de2/gaussian__elimination_8cpp.html
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@@ -217,7 +217,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_9c6faab82c22511b50177aa2e38e2780.html">numerical_methods</a></li><li class="navelem"><a class="el" href="../../d0/de2/gaussian__elimination_8cpp.html">gaussian_elimination.cpp</a></li>
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d0/dff/structlinkedlist.html
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@@ -122,7 +122,7 @@ int&#160;</td><td class="memItemRight" valign="bottom"><b>data</b></td></tr>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d0/dff/structlinkedlist.html">linkedlist</a></li>
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d1/d07/class_solution-members.html
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@@ -110,7 +110,7 @@ $(document).ready(function(){initNavTree('dd/d4f/class_solution.html','../../');
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d1/d11/gcd__of__n__numbers_8cpp.html
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@@ -214,7 +214,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_296d53ceaeaa7e099814a6def439fe8a.html">math</a></li><li class="navelem"><a class="el" href="../../d1/d11/gcd__of__n__numbers_8cpp.html">gcd_of_n_numbers.cpp</a></li>
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d1/d1d/class_graph-members.html
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@@ -144,7 +144,7 @@ $(document).ready(function(){initNavTree('da/d9a/class_graph.html','../../'); in
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d1/d21/quick__sort_8cpp.html
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@@ -191,7 +191,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_bb1b521853a9c46347182a9d10420771.html">sorting</a></li><li class="navelem"><a class="el" href="../../d1/d21/quick__sort_8cpp.html">quick_sort.cpp</a></li>
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d1/d76/buzz__number_8cpp.html
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@@ -160,7 +160,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_9510827d0b234b3cc54b29892f217477.html">others</a></li><li class="navelem"><a class="el" href="../../d1/d76/buzz__number_8cpp.html">buzz_number.cpp</a></li>
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@@ -119,7 +119,7 @@ int&#160;</td><td class="memItemRight" valign="bottom"><b>near</b></td></tr>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
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d1/db3/structcompare.html
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@@ -113,7 +113,7 @@ bool&#160;</td><td class="memItemRight" valign="bottom"><b>operator()</b> (<a cl
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
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@@ -511,7 +511,7 @@ template&lt;class Type &gt; </div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d1/dc2/classstack.html">stack</a></li>
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@@ -118,7 +118,7 @@ $(document).ready(function(){initNavTree('d5/da1/structnode.html','../../'); ini
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d1/df3/hash__search_8cpp.html
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@@ -397,7 +397,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_19b2bf9199a15c634a08b1ede1dd896a.html">search</a></li><li class="navelem"><a class="el" href="../../d1/df3/hash__search_8cpp.html">hash_search.cpp</a></li>
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@@ -469,7 +469,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/d05/class_min_heap.html">MinHeap</a></li>
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@@ -292,7 +292,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_296d53ceaeaa7e099814a6def439fe8a.html">math</a></li><li class="navelem"><a class="el" href="../../d2/d0b/fast__power_8cpp.html">fast_power.cpp</a></li>
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@@ -200,7 +200,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_19b2bf9199a15c634a08b1ede1dd896a.html">search</a></li><li class="navelem"><a class="el" href="../../d2/d22/jump__search_8cpp.html">jump_search.cpp</a></li>
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@@ -120,7 +120,7 @@ int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../..
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/d2c/structtower.html">tower</a></li>
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@@ -508,7 +508,7 @@ template&lt;class Kind &gt; </div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/d36/structqueue.html">queue</a></li>
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@@ -625,7 +625,7 @@ template&lt;typename T &gt; </div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/d3b/namespaceqr__algorithm.html">qr_algorithm</a></li>
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@@ -256,7 +256,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_bb1b521853a9c46347182a9d10420771.html">sorting</a></li><li class="navelem"><a class="el" href="../../d2/d52/heap__sort_8cpp.html">heap_sort.cpp</a></li>
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@@ -135,7 +135,7 @@ Public Attributes</h2></td></tr>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/dc4/classstack__linked_list.html">stack_linkedList</a></li>
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@@ -115,7 +115,7 @@ Classes</h2></td></tr>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d2/dcf/namespacestatistics.html">statistics</a></li>
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@@ -405,7 +405,7 @@ Here is the call graph for this function:</div>
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../dir_9c6faab82c22511b50177aa2e38e2780.html">numerical_methods</a></li><li class="navelem"><a class="el" href="../../d3/d06/ode__semi__implicit__euler_8cpp.html">ode_semi_implicit_euler.cpp</a></li>
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<div class="ttc" id="aclock_t_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/clock_t.html">std::clock_t</a></div></div>
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<div class="ttc" id="apair_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/utility/pair.html">std::pair</a></div></div>
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<div class="ttc" id="amiller__rabin_8cpp_html_a798398d5bfd375a3c0ce68100842f6f5"><div class="ttname"><a href="../../d6/d42/miller__rabin_8cpp.html#a798398d5bfd375a3c0ce68100842f6f5">reverse_binary</a></div><div class="ttdeci">std::vector&lt; T &gt; reverse_binary(T num)</div><div class="ttdef"><b>Definition:</b> miller_rabin.cpp:19</div></div>
<div class="ttc" id="asqrt_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/sqrt.html">std::sqrt</a></div><div class="ttdeci">T sqrt(T... args)</div></div>
<div class="ttc" id="apower__for__huge__numbers_8cpp_html_ae249a2af508aa94266023ce8aa81426f"><div class="ttname"><a href="../../df/def/power__for__huge__numbers_8cpp.html#ae249a2af508aa94266023ce8aa81426f">power</a></div><div class="ttdeci">void power(int x, int n)</div><div class="ttdef"><b>Definition:</b> power_for_huge_numbers.cpp:56</div></div>
<div class="ttc" id="anamespaceqr__algorithm_html"><div class="ttname"><a href="../../d2/d3b/namespaceqr__algorithm.html">qr_algorithm</a></div><div class="ttdoc">Functions to compute QR decomposition of any rectangular matrix.</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_ab6171f4db68a5e50ae0f3500a63acd26"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#ab6171f4db68a5e50ae0f3500a63acd26">operator*</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; T &gt; &gt; operator*(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A, std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;B)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:71</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_ab6171f4db68a5e50ae0f3500a63acd26"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#ab6171f4db68a5e50ae0f3500a63acd26">operator*</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; T &gt; &gt; operator*(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A, std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;B)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:72</div></div>
<div class="ttc" id="aprime__numbers_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../de/d9b/prime__numbers_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> prime_numbers.cpp:26</div></div>
<div class="ttc" id="agroup__ode_html_gaa197c6b7085ac9ea71abc4c063e6f52f"><div class="ttname"><a href="../../d6/d60/group__ode.html#gaa197c6b7085ac9ea71abc4c063e6f52f">forward_euler_step</a></div><div class="ttdeci">void forward_euler_step(const double dx, const double &amp;x, std::valarray&lt; double &gt; *y, std::valarray&lt; double &gt; *dy)</div><div class="ttdoc">Compute next step approximation using the forward-Euler method.</div><div class="ttdef"><b>Definition:</b> ode_forward_euler.cpp:86</div></div>
<div class="ttc" id="amersenne_twister_engine_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/random/mersenne_twister_engine.html">std::mt19937</a></div></div>
@@ -360,7 +360,7 @@ $(document).ready(function(){initNavTree('d4/d68/qr__decompose_8h_source.html','
<div class="ttc" id="amodular__inverse__fermat__little__theorem_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d8/d53/modular__inverse__fermat__little__theorem_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> modular_inverse_fermat_little_theorem.cpp:84</div></div>
<div class="ttc" id="aclock_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/clock.html">std::clock</a></div><div class="ttdeci">T clock(T... args)</div></div>
<div class="ttc" id="adurand__kerner__roots_8cpp_html_ac38b9cfd2a39d856e0feba3b5d241ded"><div class="ttname"><a href="../../da/df2/durand__kerner__roots_8cpp.html#ac38b9cfd2a39d856e0feba3b5d241ded">durand_kerner_algo</a></div><div class="ttdeci">std::pair&lt; uint32_t, double &gt; durand_kerner_algo(const std::valarray&lt; double &gt; &amp;coeffs, std::valarray&lt; std::complex&lt; double &gt;&gt; *roots, bool write_log=false)</div><div class="ttdef"><b>Definition:</b> durand_kerner_roots.cpp:109</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a98eb5807f21b783c341cab402ced6732"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a98eb5807f21b783c341cab402ced6732">operator&lt;&lt;</a></div><div class="ttdeci">std::ostream &amp; operator&lt;&lt;(std::ostream &amp;out, std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;v)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:19</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a98eb5807f21b783c341cab402ced6732"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a98eb5807f21b783c341cab402ced6732">operator&lt;&lt;</a></div><div class="ttdeci">std::ostream &amp; operator&lt;&lt;(std::ostream &amp;out, std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;v)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:20</div></div>
<div class="ttc" id="aisnan_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/isnan.html">std::isnan</a></div><div class="ttdeci">T isnan(T... args)</div></div>
<div class="ttc" id="anamespacestatistics_html"><div class="ttname"><a href="../../d2/dcf/namespacestatistics.html">statistics</a></div><div class="ttdoc">Statistical algorithms.</div></div>
<div class="ttc" id="aode__forward__euler_8cpp_html_aa13517b8e5de1b75592052db7f7e237f"><div class="ttname"><a href="../../db/dd3/ode__forward__euler_8cpp.html#aa13517b8e5de1b75592052db7f7e237f">save_exact_solution</a></div><div class="ttdeci">void save_exact_solution(const double &amp;X0, const double &amp;X_MAX, const double &amp;step_size, const std::valarray&lt; double &gt; &amp;Y0)</div><div class="ttdef"><b>Definition:</b> ode_forward_euler.cpp:152</div></div>
@@ -384,10 +384,10 @@ $(document).ready(function(){initNavTree('d4/d68/qr__decompose_8h_source.html','
<div class="ttc" id="adurand__kerner__roots_8cpp_html_a51637ff89e55ca749993d3e84b95d153"><div class="ttname"><a href="../../da/df2/durand__kerner__roots_8cpp.html#a51637ff89e55ca749993d3e84b95d153">poly_function</a></div><div class="ttdeci">std::complex&lt; double &gt; poly_function(const std::valarray&lt; double &gt; &amp;coeffs, std::complex&lt; double &gt; x)</div><div class="ttdef"><b>Definition:</b> durand_kerner_roots.cpp:53</div></div>
<div class="ttc" id="alu__decompose_8cpp_html_a3c04138a5bfe5d72780bb7e82a18e627"><div class="ttname"><a href="../../dd/d65/lu__decompose_8cpp.html#a3c04138a5bfe5d72780bb7e82a18e627">main</a></div><div class="ttdeci">int main(int argc, char **argv)</div><div class="ttdef"><b>Definition:</b> lu_decompose.cpp:91</div></div>
<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 class="ttdoc">STL class.</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:357</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:358</div></div>
<div class="ttc" id="areal_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/complex/real.html">std::complex::real</a></div><div class="ttdeci">T real(T... args)</div></div>
<div class="ttc" id="adurand__kerner__roots_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../da/df2/durand__kerner__roots_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition:</b> durand_kerner_roots.cpp:207</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a4bcaaf41c66da4d3a471dacef133def7"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a4bcaaf41c66da4d3a471dacef133def7">predict_OLS_regressor</a></div><div class="ttdeci">std::vector&lt; float &gt; predict_OLS_regressor(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;X, std::vector&lt; float &gt; const &amp;beta)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:339</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a4bcaaf41c66da4d3a471dacef133def7"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a4bcaaf41c66da4d3a471dacef133def7">predict_OLS_regressor</a></div><div class="ttdeci">std::vector&lt; float &gt; predict_OLS_regressor(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;X, std::vector&lt; float &gt; const &amp;beta)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:340</div></div>
<div class="ttc" id="agaussian__elimination_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d0/de2/gaussian__elimination_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> gaussian_elimination.cpp:9</div></div>
<div class="ttc" id="aopen_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ofstream/open.html">std::ofstream::open</a></div><div class="ttdeci">T open(T... args)</div></div>
<div class="ttc" id="adurand__kerner__roots_8cpp_html_af270a96662132d0385cb6b4637c5a689"><div class="ttname"><a href="../../da/df2/durand__kerner__roots_8cpp.html#af270a96662132d0385cb6b4637c5a689">ACCURACY</a></div><div class="ttdeci">#define ACCURACY</div><div class="ttdef"><b>Definition:</b> durand_kerner_roots.cpp:45</div></div>
@@ -406,21 +406,22 @@ $(document).ready(function(){initNavTree('d4/d68/qr__decompose_8h_source.html','
<div class="ttc" id="asubstr_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/string/basic_string/substr.html">std::string::substr</a></div><div class="ttdeci">T substr(T... args)</div></div>
<div class="ttc" id="amiller__rabin_8cpp_html_a6f9c31c1047aa3191676d64571d4c506"><div class="ttname"><a href="../../d6/d42/miller__rabin_8cpp.html#a6f9c31c1047aa3191676d64571d4c506">miller_test</a></div><div class="ttdeci">bool miller_test(T d, T num)</div><div class="ttdef"><b>Definition:</b> miller_rabin.cpp:73</div></div>
<div class="ttc" id="aleast__common__multiple_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d4/d21/least__common__multiple_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> least_common_multiple.cpp:67</div></div>
<div class="ttc" id="anewton__raphson__method_8cpp_html_a002b2f4894492820fe708b1b7e7c5e70"><div class="ttname"><a href="../../de/dd3/newton__raphson__method_8cpp.html#a002b2f4894492820fe708b1b7e7c5e70">EPSILON</a></div><div class="ttdeci">#define EPSILON</div><div class="ttdoc">system accuracy limit</div><div class="ttdef"><b>Definition:</b> newton_raphson_method.cpp:20</div></div>
<div class="ttc" id="aode__forward__euler_8cpp_html_abaeae8f62a018d197f0187a1c80a90fe"><div class="ttname"><a href="../../db/dd3/ode__forward__euler_8cpp.html#abaeae8f62a018d197f0187a1c80a90fe">problem</a></div><div class="ttdeci">void problem(const double &amp;x, std::valarray&lt; double &gt; *y, std::valarray&lt; double &gt; *dy)</div><div class="ttdoc">Problem statement for a system with first-order differential equations. Updates the system differenti...</div><div class="ttdef"><b>Definition:</b> ode_forward_euler.cpp:54</div></div>
<div class="ttc" id="ahash__search_8cpp_html_a6e1a77282bc65ad359d753d25df23243"><div class="ttname"><a href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a></div><div class="ttdeci">int data[MAX]</div><div class="ttdoc">test data</div><div class="ttdef"><b>Definition:</b> hash_search.cpp:24</div></div>
<div class="ttc" id="asieve__of__eratosthenes_8cpp_html_a392fb874e547e582e9c66a08a1f23326"><div class="ttname"><a href="../../d8/ddf/sieve__of__eratosthenes_8cpp.html#a392fb874e547e582e9c66a08a1f23326">MAX</a></div><div class="ttdeci">#define MAX</div><div class="ttdef"><b>Definition:</b> sieve_of_eratosthenes.cpp:16</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a38ff1d954e9b7de93eb20e2dd101a045"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a38ff1d954e9b7de93eb20e2dd101a045">fit_OLS_regressor</a></div><div class="ttdeci">std::vector&lt; float &gt; fit_OLS_regressor(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;X, std::vector&lt; T &gt; const &amp;Y)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:309</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a31be3fe36e76b87d5616ff8e7918cd24"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a31be3fe36e76b87d5616ff8e7918cd24">operator-</a></div><div class="ttdeci">std::vector&lt; T &gt; operator-(std::vector&lt; T &gt; const &amp;A, std::vector&lt; T &gt; const &amp;B)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:174</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a38ff1d954e9b7de93eb20e2dd101a045"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a38ff1d954e9b7de93eb20e2dd101a045">fit_OLS_regressor</a></div><div class="ttdeci">std::vector&lt; float &gt; fit_OLS_regressor(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;X, std::vector&lt; T &gt; const &amp;Y)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:310</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a31be3fe36e76b87d5616ff8e7918cd24"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a31be3fe36e76b87d5616ff8e7918cd24">operator-</a></div><div class="ttdeci">std::vector&lt; T &gt; operator-(std::vector&lt; T &gt; const &amp;A, std::vector&lt; T &gt; const &amp;B)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:175</div></div>
<div class="ttc" id="amodular__inverse__fermat__little__theorem_8cpp_html_a4c6eefd1254eab3e8d34bf02c205e0f4"><div class="ttname"><a href="../../d8/d53/modular__inverse__fermat__little__theorem_8cpp.html#a4c6eefd1254eab3e8d34bf02c205e0f4">binExpo</a></div><div class="ttdeci">int64_t binExpo(int64_t a, int64_t b, int64_t m)</div><div class="ttdef"><b>Definition:</b> modular_inverse_fermat_little_theorem.cpp:52</div></div>
<div class="ttc" id="aendl_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a></div><div class="ttdeci">T endl(T... args)</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a98ab8f75d981088369b89b8be2182483"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a98ab8f75d981088369b89b8be2182483">get_inverse</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; float &gt; &gt; get_inverse(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:217</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a98ab8f75d981088369b89b8be2182483"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a98ab8f75d981088369b89b8be2182483">get_inverse</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; float &gt; &gt; get_inverse(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:218</div></div>
<div class="ttc" id="aclassstatistics_1_1stats__computer1_html_aa13bf7c38de112f71921a5525d71a2f2"><div class="ttname"><a href="../../d7/d7c/classstatistics_1_1stats__computer1.html#aa13bf7c38de112f71921a5525d71a2f2">statistics::stats_computer1::new_val</a></div><div class="ttdeci">void new_val(T x)</div><div class="ttdef"><b>Definition:</b> realtime_stats.cpp:32</div></div>
<div class="ttc" id="anamespaceqr__algorithm_html_a8ea313a1a1b5f9d0e3e332c29c6446ec"><div class="ttname"><a href="../../d2/d3b/namespaceqr__algorithm.html#a8ea313a1a1b5f9d0e3e332c29c6446ec">qr_algorithm::vector_dot</a></div><div class="ttdeci">double vector_dot(const std::valarray&lt; T &gt; &amp;a, const std::valarray&lt; T &gt; &amp;b)</div><div class="ttdef"><b>Definition:</b> qr_decompose.h:76</div></div>
<div class="ttc" id="aleft_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/manip/left.html">std::left</a></div><div class="ttdeci">T left(T... args)</div></div>
<div class="ttc" id="aode__midpoint__euler_8cpp_html_abaeae8f62a018d197f0187a1c80a90fe"><div class="ttname"><a href="../../d6/dd3/ode__midpoint__euler_8cpp.html#abaeae8f62a018d197f0187a1c80a90fe">problem</a></div><div class="ttdeci">void problem(const double &amp;x, std::valarray&lt; double &gt; *y, std::valarray&lt; double &gt; *dy)</div><div class="ttdoc">Problem statement for a system with first-order differential equations. Updates the system differenti...</div><div class="ttdef"><b>Definition:</b> ode_midpoint_euler.cpp:53</div></div>
<div class="ttc" id="aclassstatistics_1_1stats__computer2_html_ade6de704deea24fdc88077b3d9a0d534"><div class="ttname"><a href="../../d8/dab/classstatistics_1_1stats__computer2.html#ade6de704deea24fdc88077b3d9a0d534">statistics::stats_computer2::new_val</a></div><div class="ttdeci">void new_val(T x)</div><div class="ttdef"><b>Definition:</b> realtime_stats.cpp:77</div></div>
<div class="ttc" id="aclassstatistics_1_1stats__computer1_html_a27f0a03e2fd2254f1c81fe668226bd92"><div class="ttname"><a href="../../d7/d7c/classstatistics_1_1stats__computer1.html#a27f0a03e2fd2254f1c81fe668226bd92">statistics::stats_computer1::variance</a></div><div class="ttdeci">double variance() const</div><div class="ttdef"><b>Definition:</b> realtime_stats.cpp:45</div></div>
<div class="ttc" id="anewton__raphson__method_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../de/dd3/newton__raphson__method_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> newton_raphson_method.cpp:37</div></div>
<div class="ttc" id="anewton__raphson__method_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../de/dd3/newton__raphson__method_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> newton_raphson_method.cpp:44</div></div>
<div class="ttc" id="agroup__ode_html_ga36ff0710861ca39d957046c0b09b2985"><div class="ttname"><a href="../../d6/d60/group__ode.html#ga36ff0710861ca39d957046c0b09b2985">midpoint_euler</a></div><div class="ttdeci">double midpoint_euler(double dx, double x0, double x_max, std::valarray&lt; double &gt; *y, bool save_to_file=false)</div><div class="ttdoc">Compute approximation using the midpoint-Euler method in the given limits.</div><div class="ttdef"><b>Definition:</b> ode_midpoint_euler.cpp:107</div></div>
<div class="ttc" id="anumber__of__positive__divisors_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d0/da2/number__of__positive__divisors_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> number_of_positive_divisors.cpp:62</div></div>
<div class="ttc" id="abegin_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/begin.html">std::vector::cbegin</a></div><div class="ttdeci">T cbegin(T... args)</div></div>
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<div class="ttc" id="aexit_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a></div><div class="ttdeci">T exit(T... args)</div></div>
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<div class="ttc" id="apow_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/pow.html">std::pow</a></div><div class="ttdeci">T pow(T... args)</div></div>
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<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a889f9de199fa793497c864d8e493af05"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a889f9de199fa793497c864d8e493af05">get_transpose</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; T &gt; &gt; get_transpose(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:288</div></div>
<div class="ttc" id="aordinary__least__squares__regressor_8cpp_html_a889f9de199fa793497c864d8e493af05"><div class="ttname"><a href="../../dc/d38/ordinary__least__squares__regressor_8cpp.html#a889f9de199fa793497c864d8e493af05">get_transpose</a></div><div class="ttdeci">std::vector&lt; std::vector&lt; T &gt; &gt; get_transpose(std::vector&lt; std::vector&lt; T &gt;&gt; const &amp;A)</div><div class="ttdef"><b>Definition:</b> ordinary_least_squares_regressor.cpp:289</div></div>
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<div class="ttc" id="aclassgraph_html"><div class="ttname"><a href="../../dd/d9b/classgraph.html">graph</a></div><div class="ttdef"><b>Definition:</b> bfs.cpp:3</div></div>
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<div class="ttc" id="aclass_trie_html"><div class="ttname"><a href="../../dd/d2f/class_trie.html">Trie</a></div><div class="ttdef"><b>Definition:</b> trie_modern.cpp:16</div></div>
<div class="ttc" id="avector_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt; int &gt;</a></div></div>
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<div class="ttc" id="akohonen__som__topology_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:359</div></div>
<div class="ttc" id="asize_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/string/basic_string/size.html">std::string::size</a></div><div class="ttdeci">T size(T... args)</div></div>
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<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a74e3c6c037b67895014414c5d75465e5"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">machine_learning::adaline::fit</a></div><div class="ttdeci">double fit(const std::vector&lt; double &gt; &amp;x, const int &amp;y)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:112</div></div>
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<div class="ttc" id="astack_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/stack.html">std::stack</a></div><div class="ttdoc">STL class.</div></div>
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<div class="ttc" id="aiterator_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/iterator/iterator.html">std::iterator</a></div></div>
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<div class="ttc" id="aemplace_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/queue/emplace.html">std::queue::emplace</a></div><div class="ttdeci">T emplace(T... args)</div></div>
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<div class="ttc" id="anamespacemachine__learning_html"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html">machine_learning</a></div><div class="ttdoc">Machine learning algorithms.</div></div>
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<div class="ttc" id="anamespacemachine__learning_html_ac4010fe3a52a74e8b5b1aaadfe38b46f"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ac4010fe3a52a74e8b5b1aaadfe38b46f">machine_learning::update_weights</a></div><div class="ttdeci">double update_weights(const std::valarray&lt; double &gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, std::vector&lt; std::valarray&lt; double &gt;&gt; *D, double alpha, int R)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:193</div></div>
<div class="ttc" id="aqueue_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/queue.html">std::queue</a></div><div class="ttdoc">STL class.</div></div>
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<div class="ttc" id="aclass_solution_html"><div class="ttname"><a href="../../dd/d4f/class_solution.html">Solution</a></div><div class="ttdef"><b>Definition:</b> bridge_finding_with_tarjan_algorithm.cpp:13</div></div>
<div class="ttc" id="agroup__machine__learning_html_gab53c14440b2b2dd3172c66afc5c2f63f"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gab53c14440b2b2dd3172c66afc5c2f63f">get_min_2d</a></div><div class="ttdeci">void get_min_2d(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, double *val, int *x_idx, int *y_idx)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:97</div></div>
<div class="ttc" id="agroup__machine__learning_html_gab53c14440b2b2dd3172c66afc5c2f63f"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gab53c14440b2b2dd3172c66afc5c2f63f">get_min_2d</a></div><div class="ttdeci">void get_min_2d(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, double *val, int *x_idx, int *y_idx)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:99</div></div>
<div class="ttc" id="afront_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/queue/front.html">std::queue::front</a></div><div class="ttdeci">T front(T... args)</div></div>
<div class="ttc" id="asort_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/sort.html">std::sort</a></div><div class="ttdeci">T sort(T... args)</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ac8a9c2aaaa63b0f27ea176857e1e7d56"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">machine_learning::adaline::check_size_match</a></div><div class="ttdeci">bool check_size_match(const std::vector&lt; double &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:174</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ac8a9c2aaaa63b0f27ea176857e1e7d56"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">machine_learning::adaline::check_size_match</a></div><div class="ttdeci">bool check_size_match(const std::vector&lt; double &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:176</div></div>
<div class="ttc" id="asqrt_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/sqrt.html">std::sqrt</a></div><div class="ttdeci">T sqrt(T... args)</div></div>
<div class="ttc" id="astruct_entry_html"><div class="ttname"><a href="../../dd/d3b/struct_entry.html">Entry</a></div><div class="ttdef"><b>Definition:</b> double_hash_hash_table.cpp:28</div></div>
<div class="ttc" id="akohonen__som__trace_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../d9/d49/kohonen__som__trace_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition:</b> kohonen_som_trace.cpp:225</div></div>
@@ -484,7 +484,7 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="astructqueue_html"><div class="ttname"><a href="../../d2/d36/structqueue.html">queue</a></div><div class="ttdef"><b>Definition:</b> binary_search_tree.cpp:17</div></div>
<div class="ttc" id="aclass_cycle_check_html_ad9a270ffba3a68539b92272c702e3474"><div class="ttname"><a href="../../d3/dbb/class_cycle_check.html#ad9a270ffba3a68539b92272c702e3474">CycleCheck::isCyclicDFS</a></div><div class="ttdeci">static bool isCyclicDFS(Graph const &amp;graph)</div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:206</div></div>
<div class="ttc" id="aparanthesis__matching_8cpp_html_af93f4f37fc2ad9c37af4a715423b110c"><div class="ttname"><a href="../../dc/dc5/paranthesis__matching_8cpp.html#af93f4f37fc2ad9c37af4a715423b110c">top</a></div><div class="ttdeci">int top</div><div class="ttdoc">pointer to track stack index</div><div class="ttdef"><b>Definition:</b> paranthesis_matching.cpp:23</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6d0455dd5c30adda100e95f0423c786e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a></div><div class="ttdeci">void test3()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:521</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6d0455dd5c30adda100e95f0423c786e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a></div><div class="ttdeci">void test3()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:523</div></div>
<div class="ttc" id="aavltree_8cpp_html_a1ecfaaea49d452772dbb2b28133e36e0"><div class="ttname"><a href="../../d8/dee/avltree_8cpp.html#a1ecfaaea49d452772dbb2b28133e36e0">createNode</a></div><div class="ttdeci">node * createNode(int data)</div><div class="ttdef"><b>Definition:</b> avltree.cpp:21</div></div>
<div class="ttc" id="aclass_cycle_check_html"><div class="ttname"><a href="../../d3/dbb/class_cycle_check.html">CycleCheck</a></div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:153</div></div>
<div class="ttc" id="aclass_cycle_check_html_a2f4485c08b45e7a21a2e86f9c3f01d8b"><div class="ttname"><a href="../../d3/dbb/class_cycle_check.html#a2f4485c08b45e7a21a2e86f9c3f01d8b">CycleCheck::isCyclicDFSHelper</a></div><div class="ttdeci">static bool isCyclicDFSHelper(AdjList const &amp;adjList, std::vector&lt; nodeStates &gt; *state, unsigned int node)</div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:165</div></div>
@@ -495,7 +495,7 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="astruct_min_heap_node_html"><div class="ttname"><a href="../../d5/d29/struct_min_heap_node.html">MinHeapNode</a></div><div class="ttdef"><b>Definition:</b> huffman.cpp:7</div></div>
<div class="ttc" id="aline__segment__intersection_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d8/d6c/line__segment__intersection_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> line_segment_intersection.cpp:92</div></div>
<div class="ttc" id="aclasslarge__number_html_a622d84883180ff42f04955909adea5a9"><div class="ttname"><a href="../../db/d82/classlarge__number.html#a622d84883180ff42f04955909adea5a9">large_number::operator++</a></div><div class="ttdeci">large_number &amp; operator++()</div><div class="ttdef"><b>Definition:</b> large_number.h:175</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a52053d88ea1bcbbed9aca67ab4eeb499"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a52053d88ea1bcbbed9aca67ab4eeb499">test1</a></div><div class="ttdeci">void test1(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:202</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a52053d88ea1bcbbed9aca67ab4eeb499"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a52053d88ea1bcbbed9aca67ab4eeb499">test1</a></div><div class="ttdeci">void test1(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:204</div></div>
<div class="ttc" id="aavltree_8cpp_html_aa7cd8a68075fae1c33df41233c1bed6a"><div class="ttname"><a href="../../d8/dee/avltree_8cpp.html#aa7cd8a68075fae1c33df41233c1bed6a">insert</a></div><div class="ttdeci">node * insert(node *root, int item)</div><div class="ttdef"><b>Definition:</b> avltree.cpp:66</div></div>
<div class="ttc" id="afprintf_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/c/fprintf.html">std::printf</a></div><div class="ttdeci">T printf(T... args)</div></div>
<div class="ttc" id="aat_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/at.html">std::vector::at</a></div><div class="ttdeci">T at(T... args)</div></div>
@@ -505,7 +505,7 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="abasic_ofstream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ofstream.html">std::ofstream</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="astruct_segment_intersection_html_a3beb2ac1b35d67354f1dbaf9a971e655"><div class="ttname"><a href="../../d4/db4/struct_segment_intersection.html#a3beb2ac1b35d67354f1dbaf9a971e655">SegmentIntersection::direction</a></div><div class="ttdeci">int direction(Point first_point, Point second_point, Point third_point)</div><div class="ttdef"><b>Definition:</b> line_segment_intersection.cpp:63</div></div>
<div class="ttc" id="aclass_graph_html_ae8959064e179573cc48f8cee99115c07"><div class="ttname"><a href="../../da/d9a/class_graph.html#ae8959064e179573cc48f8cee99115c07">Graph::getAdjList</a></div><div class="ttdeci">std::remove_reference_t&lt; AdjList &gt; const &amp; getAdjList() const</div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:105</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a28160d17e492597a2f112e0d38551cda"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">machine_learning::adaline::eta</a></div><div class="ttdeci">const double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:185</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a28160d17e492597a2f112e0d38551cda"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">machine_learning::adaline::eta</a></div><div class="ttdeci">const double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:187</div></div>
<div class="ttc" id="amatrix__exponentiation_8cpp_html_afcf0d19607cd0edd8ae333d2b9c220c0"><div class="ttname"><a href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a></div><div class="ttdeci">ll k</div><div class="ttdef"><b>Definition:</b> matrix_exponentiation.cpp:48</div></div>
<div class="ttc" id="amin_element_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/min_element.html">std::min_element</a></div><div class="ttdeci">T min_element(T... args)</div></div>
<div class="ttc" id="aeulers__totient__function_8cpp_html_a35e4874a3e1d67eb708dc57944c8aea0"><div class="ttname"><a href="../../da/d23/eulers__totient__function_8cpp.html#a35e4874a3e1d67eb708dc57944c8aea0">phiFunction</a></div><div class="ttdeci">uint64_t phiFunction(uint64_t n)</div><div class="ttdef"><b>Definition:</b> eulers_totient_function.cpp:32</div></div>
@@ -521,16 +521,16 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="aperror_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/c/perror.html">std::perror</a></div><div class="ttdeci">T perror(T... args)</div></div>
<div class="ttc" id="amatrix__exponentiation_8cpp_html_ae1d1ec9482079231e898236e2b23c9ba"><div class="ttname"><a href="../../d7/d35/matrix__exponentiation_8cpp.html#ae1d1ec9482079231e898236e2b23c9ba">ll</a></div><div class="ttdeci">#define ll</div><div class="ttdef"><b>Definition:</b> matrix_exponentiation.cpp:33</div></div>
<div class="ttc" id="aerase_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/set/erase.html">std::set::erase</a></div><div class="ttdeci">T erase(T... args)</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">machine_learning::adaline::weights</a></div><div class="ttdeci">std::vector&lt; double &gt; weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:187</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">machine_learning::adaline::weights</a></div><div class="ttdeci">std::vector&lt; double &gt; weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:189</div></div>
<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 class="ttdoc">STL class.</div></div>
<div class="ttc" id="astruct_segment_intersection_html"><div class="ttname"><a href="../../d4/db4/struct_segment_intersection.html">SegmentIntersection</a></div><div class="ttdef"><b>Definition:</b> line_segment_intersection.cpp:22</div></div>
<div class="ttc" id="aruntime_error_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/error/runtime_error.html">std::runtime_error</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="aclasslarge__number_html_aeb22d2aae39d1b1e0bd39c7f47b333eb"><div class="ttname"><a href="../../db/d82/classlarge__number.html#aeb22d2aae39d1b1e0bd39c7f47b333eb">large_number::operator=</a></div><div class="ttdeci">large_number &amp; operator=(const large_number &amp;b)</div><div class="ttdef"><b>Definition:</b> large_number.h:229</div></div>
<div class="ttc" id="aextended__euclid__algorithm_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d9/d5d/extended__euclid__algorithm_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdoc">Main function.</div><div class="ttdef"><b>Definition:</b> extended_euclid_algorithm.cpp:87</div></div>
<div class="ttc" id="aopen_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ifstream/open.html">std::ifstream::open</a></div><div class="ttdeci">T open(T... args)</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_ab3081e021270ba21a9fd88646f6a6e26"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a></div><div class="ttdeci">void test_3d_classes1(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:397</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_ab3081e021270ba21a9fd88646f6a6e26"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a></div><div class="ttdeci">void test_3d_classes1(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:399</div></div>
<div class="ttc" id="afibonacci__fast_8cpp_html_a5712edca101204eca8accdb1e096707f"><div class="ttname"><a href="../../d4/d32/fibonacci__fast_8cpp.html#a5712edca101204eca8accdb1e096707f">fib</a></div><div class="ttdeci">uint64_t fib(uint64_t n)</div><div class="ttdef"><b>Definition:</b> fibonacci_fast.cpp:30</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0283886819c7c140a023582b7269e2d0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a></div><div class="ttdeci">void test2()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:437</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0283886819c7c140a023582b7269e2d0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a></div><div class="ttdeci">void test2()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:439</div></div>
<div class="ttc" id="astruct_segment_intersection_html_a008941b2272866c64cdaf959afa939bf"><div class="ttname"><a href="../../d4/db4/struct_segment_intersection.html#a008941b2272866c64cdaf959afa939bf">SegmentIntersection::on_segment</a></div><div class="ttdeci">bool on_segment(Point first_point, Point second_point, Point third_point)</div><div class="ttdef"><b>Definition:</b> line_segment_intersection.cpp:75</div></div>
<div class="ttc" id="aremove_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/remove.html">std::remove</a></div><div class="ttdeci">T remove(T... args)</div></div>
<div class="ttc" id="aclasslarge__number_html_af2b3ec9c35842d3a46ac7326f268af57"><div class="ttname"><a href="../../db/d82/classlarge__number.html#af2b3ec9c35842d3a46ac7326f268af57">large_number::_digits</a></div><div class="ttdeci">std::vector&lt; unsigned char &gt; _digits</div><div class="ttdef"><b>Definition:</b> large_number.h:285</div></div>
@@ -545,7 +545,7 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="apriority_queue_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/priority_queue.html">std::priority_queue</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="amatrix__exponentiation_8cpp_html_a9ecd98ce0064e2f7f97bb6a92f58ee72"><div class="ttname"><a href="../../d7/d35/matrix__exponentiation_8cpp.html#a9ecd98ce0064e2f7f97bb6a92f58ee72">a</a></div><div class="ttdeci">vector&lt; ll &gt; a</div><div class="ttdef"><b>Definition:</b> matrix_exponentiation.cpp:53</div></div>
<div class="ttc" id="arand_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a></div><div class="ttdeci">T rand(T... args)</div></div>
<div class="ttc" id="agroup__machine__learning_html_ga6c606bc85a3e9fd9d010f874ad760336"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a></div><div class="ttdeci">int save_2d_data(const char *fname, const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:60</div></div>
<div class="ttc" id="agroup__machine__learning_html_ga6c606bc85a3e9fd9d010f874ad760336"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a></div><div class="ttdeci">int save_2d_data(const char *fname, const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:62</div></div>
<div class="ttc" id="akohonen__som__trace_8cpp_html_a412b7afa156306b1f8788643c91a1c60"><div class="ttname"><a href="../../d9/d49/kohonen__som__trace_8cpp.html#a412b7afa156306b1f8788643c91a1c60">test_lamniscate</a></div><div class="ttdeci">void test_lamniscate(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_trace.cpp:267</div></div>
<div class="ttc" id="aswap_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/swap.html">std::swap</a></div><div class="ttdeci">T swap(T... args)</div></div>
<div class="ttc" id="atrie__modern_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../dc/d93/trie__modern_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> trie_modern.cpp:160</div></div>
@@ -560,10 +560,10 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="astructqueue_html_a26f48801df462ade003b50739196fa4c"><div class="ttname"><a href="../../d2/d36/structqueue.html#a26f48801df462ade003b50739196fa4c">queue::display</a></div><div class="ttdeci">void display()</div><div class="ttdef"><b>Definition:</b> queue.h:20</div></div>
<div class="ttc" id="aleft_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/manip/left.html">std::left</a></div><div class="ttdeci">T left(T... args)</div></div>
<div class="ttc" id="aclasslarge__number_html_a7ba872b9a3ce1f3da6c06c5409663cca"><div class="ttname"><a href="../../db/d82/classlarge__number.html#a7ba872b9a3ce1f3da6c06c5409663cca">large_number::operator==</a></div><div class="ttdeci">friend bool operator==(large_number const &amp;a, large_number const &amp;b)</div><div class="ttdef"><b>Definition:</b> large_number.h:155</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a1d821a24e1503d468c95d4acedca58b3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a1d821a24e1503d468c95d4acedca58b3">machine_learning::adaline::operator&lt;&lt;</a></div><div class="ttdeci">friend std::ostream &amp; operator&lt;&lt;(std::ostream &amp;out, const adaline &amp;ada)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:72</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a1d821a24e1503d468c95d4acedca58b3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a1d821a24e1503d468c95d4acedca58b3">machine_learning::adaline::operator&lt;&lt;</a></div><div class="ttdeci">friend std::ostream &amp; operator&lt;&lt;(std::ostream &amp;out, const adaline &amp;ada)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:74</div></div>
<div class="ttc" id="aexp_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/exp.html">std::exp</a></div><div class="ttdeci">T exp(T... args)</div></div>
<div class="ttc" id="abegin_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/iterator/begin.html">std::begin</a></div><div class="ttdeci">T begin(T... args)</div></div>
<div class="ttc" id="anamespacemachine__learning_html_a1d577f5d95b774ae97eb6838852d0df5"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; &amp;W)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:133</div></div>
<div class="ttc" id="anamespacemachine__learning_html_a1d577f5d95b774ae97eb6838852d0df5"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; &amp;W)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:135</div></div>
<div class="ttc" id="afactorial_8cpp_html_ae9945c15826a9c1b5c141db314b7f8b4"><div class="ttname"><a href="../../d9/d00/factorial_8cpp.html#ae9945c15826a9c1b5c141db314b7f8b4">factorial</a></div><div class="ttdeci">unsigned int factorial(unsigned int n)</div><div class="ttdef"><b>Definition:</b> factorial.cpp:8</div></div>
<div class="ttc" id="agreater_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/utility/functional/greater.html">std::greater</a></div></div>
<div class="ttc" id="anamespacestd_html"><div class="ttname"><a href="../../d8/dcc/namespacestd.html">std</a></div><div class="ttdoc">STL namespace.</div></div>
@@ -573,7 +573,7 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
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<div class="ttc" id="async_with_stdio_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/ios_base/sync_with_stdio.html">std::ios_base::sync_with_stdio</a></div><div class="ttdeci">T sync_with_stdio(T... args)</div></div>
<div class="ttc" id="aclassstack_html"><div class="ttname"><a href="../../d1/dc2/classstack.html">stack</a></div><div class="ttdef"><b>Definition:</b> stack.h:17</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a2256c10b16edba377b64a44b6c656908"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a></div><div class="ttdeci">double get_clock_diff(clock_t start_t, clock_t end_t)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:559</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a2256c10b16edba377b64a44b6c656908"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a></div><div class="ttdeci">double get_clock_diff(clock_t start_t, clock_t end_t)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:561</div></div>
<div class="ttc" id="agcd__of__n__numbers_8cpp_html_a25034543c20f271da04fb24ad2b2747a"><div class="ttname"><a href="../../d1/d11/gcd__of__n__numbers_8cpp.html#a25034543c20f271da04fb24ad2b2747a">gcd</a></div><div class="ttdeci">int gcd(int *a, int n)</div><div class="ttdef"><b>Definition:</b> gcd_of_n_numbers.cpp:15</div></div>
<div class="ttc" id="afast__power_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d2/d0b/fast__power_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> fast_power.cpp:68</div></div>
<div class="ttc" id="adouble__factorial_8cpp_html_a68ba20fed2ce427f6469c7689437829d"><div class="ttname"><a href="../../d7/d89/double__factorial_8cpp.html#a68ba20fed2ce427f6469c7689437829d">double_factorial_recursive</a></div><div class="ttdeci">uint64_t double_factorial_recursive(uint64_t n)</div><div class="ttdef"><b>Definition:</b> double_factorial.cpp:29</div></div>
@@ -601,31 +601,31 @@ $(document).ready(function(){initNavTree('d4/d86/large__number_8h_source.html','
<div class="ttc" id="aend_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/set/end.html">std::set::end</a></div><div class="ttdeci">T end(T... args)</div></div>
<div class="ttc" id="aparanthesis__matching_8cpp_html_aa37d24a036d239b3b528f13b9de880c7"><div class="ttname"><a href="../../dc/dc5/paranthesis__matching_8cpp.html#aa37d24a036d239b3b528f13b9de880c7">stack</a></div><div class="ttdeci">char stack[MAX]</div><div class="ttdef"><b>Definition:</b> paranthesis_matching.cpp:20</div></div>
<div class="ttc" id="aextended__euclid__algorithm_8cpp_html_a1792ac7c33aaf26b860ab55f5652ab25"><div class="ttname"><a href="../../d9/d5d/extended__euclid__algorithm_8cpp.html#a1792ac7c33aaf26b860ab55f5652ab25">extendedEuclid_1</a></div><div class="ttdeci">void extendedEuclid_1(T1 A, T1 B, T1 *GCD, T2 *x, T2 *y)</div><div class="ttdef"><b>Definition:</b> extended_euclid_algorithm.cpp:41</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_aa23d60262f917f35836ef4b1c1d9f7d3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">machine_learning::adaline::accuracy</a></div><div class="ttdeci">const double accuracy</div><div class="ttdoc">model fit convergence accuracy</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:186</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_aa23d60262f917f35836ef4b1c1d9f7d3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">machine_learning::adaline::accuracy</a></div><div class="ttdeci">const double accuracy</div><div class="ttdoc">model fit convergence accuracy</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:188</div></div>
<div class="ttc" id="agcd__iterative__euclidean_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d4/da0/gcd__iterative__euclidean_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition:</b> gcd_iterative_euclidean.cpp:47</div></div>
<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>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6b5e744876fd980a3451cbb385d4e755"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:318</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6b5e744876fd980a3451cbb385d4e755"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:320</div></div>
<div class="ttc" id="arange_error_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/error/range_error.html">std::range_error</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="astruct_point_html"><div class="ttname"><a href="../../d8/dc8/struct_point.html">Point</a></div><div class="ttdef"><b>Definition:</b> line_segment_intersection.cpp:12</div></div>
<div class="ttc" id="aclasslarge__number_html_a72ae1ef050c4c28c50952ecab22d4b94"><div class="ttname"><a href="../../db/d82/classlarge__number.html#a72ae1ef050c4c28c50952ecab22d4b94">large_number::operator!=</a></div><div class="ttdeci">friend bool operator!=(large_number const &amp;a, large_number const &amp;b)</div><div class="ttdef"><b>Definition:</b> large_number.h:168</div></div>
<div class="ttc" id="anamespacemachine__learning_html_adc731720947b4bc2ab047c141e7d0299"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, double alpha_min)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:259</div></div>
<div class="ttc" id="anamespacemachine__learning_html_adc731720947b4bc2ab047c141e7d0299"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, double alpha_min)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:261</div></div>
<div class="ttc" id="aparanthesis__matching_8cpp_html_aae41c72130114bf31204cde6873b6095"><div class="ttname"><a href="../../dc/dc5/paranthesis__matching_8cpp.html#aae41c72130114bf31204cde6873b6095">push</a></div><div class="ttdeci">void push(char ch)</div><div class="ttdoc">push byte to stack variable</div><div class="ttdef"><b>Definition:</b> paranthesis_matching.cpp:26</div></div>
<div class="ttc" id="aclass_trie_html_a95216ffc56cb9f8cede982cecb872af4"><div class="ttname"><a href="../../dd/d2f/class_trie.html#a95216ffc56cb9f8cede982cecb872af4">Trie::removeWordHelper</a></div><div class="ttdeci">std::shared_ptr&lt; TrieNode &gt; removeWordHelper(const std::string &amp;word, std::shared_ptr&lt; TrieNode &gt; curr, size_t index)</div><div class="ttdef"><b>Definition:</b> trie_modern.cpp:64</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0e7435446ed7c763f7de79a468add2e0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a></div><div class="ttdeci">void test_3d_classes2(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:477</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0e7435446ed7c763f7de79a468add2e0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a></div><div class="ttdeci">void test_3d_classes2(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:479</div></div>
<div class="ttc" id="aparanthesis__matching_8cpp_html_a6d25c7dfbfeb52c3cb9d1b56ab49b664"><div class="ttname"><a href="../../dc/dc5/paranthesis__matching_8cpp.html#a6d25c7dfbfeb52c3cb9d1b56ab49b664">pop</a></div><div class="ttdeci">char pop()</div><div class="ttdoc">pop a byte out of stack variable</div><div class="ttdef"><b>Definition:</b> paranthesis_matching.cpp:29</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a9f1c7cd34252a9ece5bbe7ba36799044"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a9f1c7cd34252a9ece5bbe7ba36799044">machine_learning::adaline::fit</a></div><div class="ttdeci">void fit(std::vector&lt; double &gt; const (&amp;X)[N], const int *y)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:134</div></div>
<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:48</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a9f1c7cd34252a9ece5bbe7ba36799044"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a9f1c7cd34252a9ece5bbe7ba36799044">machine_learning::adaline::fit</a></div><div class="ttdeci">void fit(std::vector&lt; double &gt; const (&amp;X)[N], const int *y)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:136</div></div>
<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:50</div></div>
<div class="ttc" id="aclass_graph_html_af765dda8f21280e1cecea19e129f1bc5"><div class="ttname"><a href="../../da/d9a/class_graph.html#af765dda8f21280e1cecea19e129f1bc5">Graph::addEdge</a></div><div class="ttdeci">void addEdge(Edge const &amp;edge)</div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:128</div></div>
<div class="ttc" id="afast__power_8cpp_html_a0d4e3f0099a6975b74a314a35bd0f94d"><div class="ttname"><a href="../../d2/d0b/fast__power_8cpp.html#a0d4e3f0099a6975b74a314a35bd0f94d">fast_power_linear</a></div><div class="ttdeci">double fast_power_linear(T a, T b)</div><div class="ttdef"><b>Definition:</b> fast_power.cpp:50</div></div>
<div class="ttc" id="abasic_istream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_istream.html">std::cin</a></div></div>
<div class="ttc" id="aclass_graph_html_ae30edce9b4e7c6347e67edc343f366d8"><div class="ttname"><a href="../../da/d9a/class_graph.html#ae30edce9b4e7c6347e67edc343f366d8">Graph::Graph</a></div><div class="ttdeci">Graph(unsigned int vertices, AdjList const &amp;adjList)</div><div class="ttdef"><b>Definition:</b> cycle_check_directed_graph.cpp:70</div></div>
<div class="ttc" id="aclasslarge__number_html_ac4fafa6289295419d48d444f0ae4b706"><div class="ttname"><a href="../../db/d82/classlarge__number.html#ac4fafa6289295419d48d444f0ae4b706">large_number::operator++</a></div><div class="ttdeci">large_number &amp; operator++(int)</div><div class="ttdef"><b>Definition:</b> large_number.h:183</div></div>
<div class="ttc" id="anamespacesorting_html_a50b66a1c652291b9a346ec7342967178"><div class="ttname"><a href="../../d5/d91/namespacesorting.html#a50b66a1c652291b9a346ec7342967178">sorting::quickSort</a></div><div class="ttdeci">void quickSort(int arr[], int low, int high)</div><div class="ttdef"><b>Definition:</b> quick_sort.cpp:63</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a379f7488a305f2571f2932b319931f82"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a379f7488a305f2571f2932b319931f82">test2</a></div><div class="ttdeci">void test2(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:236</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a379f7488a305f2571f2932b319931f82"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a379f7488a305f2571f2932b319931f82">test2</a></div><div class="ttdeci">void test2(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:238</div></div>
<div class="ttc" id="apartition_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/partition.html">std::partition</a></div><div class="ttdeci">T partition(T... args)</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a992bdf1fdb0b9d414bcf7981d2d87aa9"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a></div><div class="ttdeci">void test3(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:287</div></div>
<div class="ttc" id="aadaline__learning_8cpp_html_a992bdf1fdb0b9d414bcf7981d2d87aa9"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a></div><div class="ttdeci">void test3(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:289</div></div>
<div class="ttc" id="aunordered_map_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/unordered_map.html">std::unordered_map&lt; unsigned int, std::vector&lt; unsigned int &gt; &gt;</a></div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:42</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:44</div></div>
<div class="ttc" id="aeulers__totient__function_8cpp_html_a0ddf1224851353fc92bfbff6f499fa97"><div class="ttname"><a href="../../da/d23/eulers__totient__function_8cpp.html#a0ddf1224851353fc92bfbff6f499fa97">main</a></div><div class="ttdeci">int main(int argc, char *argv[])</div><div class="ttdoc">Main function.</div><div class="ttdef"><b>Definition:</b> eulers_totient_function.cpp:48</div></div>
<div class="ttc" id="aclasslarge__number_html_a70d23d67535e67030db570e56c00e16d"><div class="ttname"><a href="../../db/d82/classlarge__number.html#a70d23d67535e67030db570e56c00e16d">large_number::operator+</a></div><div class="ttdeci">friend large_number &amp; operator+(const large_number &amp;a, const T &amp;b)</div><div class="ttdef"><b>Definition:</b> large_number.h:220</div></div>
<div class="ttc" id="adata_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/data.html">std::vector::data</a></div><div class="ttdeci">T data(T... args)</div></div>
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<div class="ttc" id="aexit_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a></div><div class="ttdeci">T exit(T... args)</div></div>
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<div class="ttc" id="astructlist_html"><div class="ttname"><a href="../../d8/d10/structlist.html">list&lt; int &gt;</a></div></div>
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@@ -165,8 +165,8 @@ Functions</h2></td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p><a href="https://en.wikipedia.org/wiki/Self-organizing_map">Kohonen self organizing map</a> (topological map) </p>
<dl class="section author"><dt>Author</dt><dd><a href="https://github.com/kvedala">Krishna Vedala</a> This example implements a powerful unsupervised learning algorithm called as a self organizing map. The algorithm creates a connected network of weights that closely follows the given data points. This thus creates a topological map of the given data i.e., it maintains the relationship between varipus data points in a much higher dimesional space by creating an equivalent in a 2-dimensional space. <img src="https://raw.githubusercontent.com/TheAlgorithms/C-Plus-Plus/docs/images/machine_learning/2D_Kohonen_SOM.svg" alt="Trained topological maps for the test cases in the program" style="pointer-events: none;" class="inline"/> </dd></dl>
<dl class="section note"><dt>Note</dt><dd>This C++ version of the program is considerable slower than its <a href="https://github.com/kvedala/C/blob/master/machine_learning/kohonen_som_trace.c">C counterpart</a> </dd>
<dl class="section author"><dt>Author</dt><dd><a href="https://github.com/kvedala">Krishna Vedala</a></dd></dl>
<p>This example implements a powerful unsupervised learning algorithm called as a self organizing map. The algorithm creates a connected network of weights that closely follows the given data points. This thus creates a topological map of the given data i.e., it maintains the relationship between varipus data points in a much higher dimesional space by creating an equivalent in a 2-dimensional space. <img src="https://raw.githubusercontent.com/TheAlgorithms/C-Plus-Plus/docs/images/machine_learning/2D_Kohonen_SOM.svg" alt="Trained topological maps for the test cases in the program" style="pointer-events: none;" class="inline"/> </p><dl class="section note"><dt>Note</dt><dd>This C++ version of the program is considerable slower than its <a href="https://github.com/kvedala/C/blob/master/machine_learning/kohonen_som_trace.c">C counterpart</a> </dd>
<dd>
The compiled code is much slower when compiled with MS Visual C++ 2019 than with GCC on windows </dd></dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d9/d49/kohonen__som__trace_8cpp.html" title="Kohonen self organizing map (data tracing)">kohonen_som_trace.cpp</a> </dd></dl>
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</dd>
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<dl class="section return"><dt>Returns</dt><dd>time difference in seconds </dd></dl>
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<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>&#160; &lt;&lt; <span class="stringliteral">&quot; sec\n&quot;</span>;</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>&#160; </div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>&#160; start_clk = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/chrono/c/clock.html">std::clock</a>();</div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a>();</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>&#160; end_clk = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/chrono/c/clock.html">std::clock</a>();</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Test 3 completed in &quot;</span> &lt;&lt; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a>(start_clk, end_clk)</div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>&#160; &lt;&lt; <span class="stringliteral">&quot; sec\n&quot;</span>;</div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>&#160; </div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a></div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>&#160; &lt;&lt; <span class="stringliteral">&quot;(Note: Calculated times include: creating test sets, training &quot;</span></div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>&#160; <span class="stringliteral">&quot;model and writing files to disk.)\n\n&quot;</span>;</div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
@@ -297,36 +297,36 @@ Here is the call graph for this function:</div>
<li><code>w11.csv</code>: initial random map</li>
<li><code>w12.csv</code>: trained SOM map </li>
</ul>
<div class="fragment"><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; {</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <span class="keywordtype">int</span> j, N = 300;</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; <span class="keywordtype">int</span> features = 2;</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; }</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; }</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; }</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; </div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test1.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w11.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w12.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; {</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; <span class="keywordtype">int</span> j, N = 300;</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <span class="keywordtype">int</span> features = 2;</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; }</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; }</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; }</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160; </div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test1.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w11.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w12.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
@@ -355,36 +355,36 @@ Here is the call graph for this function:</div>
<li><code>w21.csv</code>: initial random map</li>
<li><code>w22.csv</code>: trained SOM map </li>
</ul>
<div class="fragment"><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>&#160; {</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>&#160; <span class="keywordtype">int</span> j, N = 300;</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160; <span class="keywordtype">int</span> features = 3;</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; }</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; }</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; }</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; </div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test2.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w21.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w22.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160; {</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160; <span class="keywordtype">int</span> j, N = 300;</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160; <span class="keywordtype">int</span> features = 3;</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; }</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; }</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; }</div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; </div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test2.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w21.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w22.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
@@ -413,36 +413,36 @@ Here is the call graph for this function:</div>
<li><code>w31.csv</code>: initial random map</li>
<li><code>w32.csv</code>: trained SOM map </li>
</ul>
<div class="fragment"><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>&#160; {</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>&#160; <span class="keywordtype">int</span> j, N = 500;</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>&#160; <span class="keywordtype">int</span> features = 3;</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>&#160; }</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>&#160; }</div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>&#160; }</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>&#160; </div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test3.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w31.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w32.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>&#160; {</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>&#160; <span class="keywordtype">int</span> j, N = 500;</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>&#160; <span class="keywordtype">int</span> features = 3;</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>&#160; <span class="keywordtype">int</span> num_out = 30;</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; X(N);</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::vector&lt;std::valarray&lt;double&gt;</a>&gt;&gt; W(num_out);</div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(num_out, N); i++) {</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>&#160; <span class="comment">// loop till max(N, num_out)</span></div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>&#160; <span class="keywordflow">if</span> (i &lt; N) <span class="comment">// only add new arrays if i &lt; N</span></div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>&#160; X[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>&#160; <span class="keywordflow">if</span> (i &lt; num_out) { <span class="comment">// only add new arrays if i &lt; num_out</span></div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>&#160; W[i] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt;(num_out);</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> = 0; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a> &lt; num_out; <a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>++) {</div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a>(features);</div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; features; j++)</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>&#160; <span class="comment">// preallocate with random initial weights</span></div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>&#160; W[i][<a class="code" href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a>][j] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>&#160; }</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>&#160; }</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>&#160; }</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>&#160; </div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>&#160; <a class="code" href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a>(&amp;X); <span class="comment">// create test data around circumference of a circle</span></div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a>(<span class="stringliteral">&quot;test3.csv&quot;</span>, X); <span class="comment">// save test data points</span></div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w31.csv&quot;</span>, W); <span class="comment">// save initial random weights</span></div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a>(X, &amp;W, 1e-4); <span class="comment">// train the SOM</span></div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a>(<span class="stringliteral">&quot;w32.csv&quot;</span>, W); <span class="comment">// save the resultant weights</span></div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
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<div class="dyncontent">
@@ -479,36 +479,36 @@ Here is the call graph for this function:</div>
</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; {</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][2] = {</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; {.5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; {.5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; {-.5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; {-.5, -.5} <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; };</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; </div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; </div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160;<span class="comment"> for (int j = 0; j &lt; 2; j++)</span></div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; }</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; {</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][2] = {</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; {.5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; {.5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; {-.5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; {-.5, -.5} <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; };</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; </div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; </div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; </div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160;<span class="comment"> for (int j = 0; j &lt; 2; j++)</span></div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; }</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;}</div>
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</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; {</div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][3] = {</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; {.5, .5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160; {.5, -.5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; {-.5, .5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; {-.5, -.5 - .5} <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; };</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; </div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; </div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; </div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160;<span class="comment"> for (int j = 0; j &lt; 3; j++)</span></div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160; }</div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; {</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][3] = {</div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; {.5, .5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; {.5, -.5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; {-.5, .5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; {-.5, -.5 - .5} <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>&#160; };</div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160; </div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160; </div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160; </div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>&#160;<span class="comment"> for (int j = 0; j &lt; 3; j++)</span></div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>&#160; }</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>&#160;}</div>
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</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160; {</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.2; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 8;</div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][3] = {</div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; {.5, .5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; {.5, .5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; {.5, -.5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; {.5, -.5, -.5}, <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160; {-.5, .5, .5}, <span class="comment">// centre of class 5</span></div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>&#160; {-.5, .5, -.5}, <span class="comment">// centre of class 6</span></div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>&#160; {-.5, -.5, .5}, <span class="comment">// centre of class 7</span></div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>&#160; {-.5, -.5, -.5} <span class="comment">// centre of class 8</span></div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>&#160; };</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>&#160; </div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>&#160; </div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>&#160; </div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>&#160;<span class="comment"> for (int j = 0; j &lt; 3; j++)</span></div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>&#160; }</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>&#160;}</div>
<div class="fragment"><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; {</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>-&gt;size();</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.2; <span class="comment">// radius of cluster</span></div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160; <span class="keywordtype">int</span> i;</div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 8;</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; <span class="keyword">const</span> <span class="keywordtype">double</span> centres[][3] = {</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; <span class="comment">// centres of each class cluster</span></div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; {.5, .5, .5}, <span class="comment">// centre of class 1</span></div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; {.5, .5, -.5}, <span class="comment">// centre of class 2</span></div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160; {.5, -.5, .5}, <span class="comment">// centre of class 3</span></div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>&#160; {.5, -.5, -.5}, <span class="comment">// centre of class 4</span></div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>&#160; {-.5, .5, .5}, <span class="comment">// centre of class 5</span></div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>&#160; {-.5, .5, -.5}, <span class="comment">// centre of class 6</span></div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>&#160; {-.5, -.5, .5}, <span class="comment">// centre of class 7</span></div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>&#160; {-.5, -.5, -.5} <span class="comment">// centre of class 8</span></div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>&#160; };</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>&#160; </div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>&#160; <span class="keywordflow">for</span> (i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>&#160; <span class="comment">// select a random class for the point</span></div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>&#160; <span class="keywordtype">int</span> cls = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % num_classes;</div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>&#160; </div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>&#160; <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>&#160; <a class="code" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>&#160; </div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>&#160; <span class="comment">/* The follosing can also be used</span></div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>&#160;<span class="comment"> for (int j = 0; j &lt; 3; j++)</span></div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>&#160;<span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>&#160; }</div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
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@@ -661,30 +661,30 @@ Here is the call graph for this function:</div>
<div class="ttc" id="asrand_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/random/srand.html">std::srand</a></div><div class="ttdeci">T srand(T... args)</div></div>
<div class="ttc" id="aclock_t_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/clock_t.html">std::clock_t</a></div></div>
<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 class="ttdoc">STL class.</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:357</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:359</div></div>
<div class="ttc" id="aclock_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/clock.html">std::clock</a></div><div class="ttdeci">T clock(T... args)</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6d0455dd5c30adda100e95f0423c786e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a></div><div class="ttdeci">void test3()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:521</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6d0455dd5c30adda100e95f0423c786e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a></div><div class="ttdeci">void test3()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:523</div></div>
<div class="ttc" id="abasic_ostream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a></div></div>
<div class="ttc" id="amatrix__exponentiation_8cpp_html_afcf0d19607cd0edd8ae333d2b9c220c0"><div class="ttname"><a href="../../d7/d35/matrix__exponentiation_8cpp.html#afcf0d19607cd0edd8ae333d2b9c220c0">k</a></div><div class="ttdeci">ll k</div><div class="ttdef"><b>Definition:</b> matrix_exponentiation.cpp:48</div></div>
<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 class="ttdoc">STL class.</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_ab3081e021270ba21a9fd88646f6a6e26"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a></div><div class="ttdeci">void test_3d_classes1(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:397</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0283886819c7c140a023582b7269e2d0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a></div><div class="ttdeci">void test2()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:437</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_ab3081e021270ba21a9fd88646f6a6e26"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ab3081e021270ba21a9fd88646f6a6e26">test_3d_classes1</a></div><div class="ttdeci">void test_3d_classes1(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:399</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0283886819c7c140a023582b7269e2d0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a></div><div class="ttdeci">void test2()</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:439</div></div>
<div class="ttc" id="arand_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a></div><div class="ttdeci">T rand(T... args)</div></div>
<div class="ttc" id="agroup__machine__learning_html_ga6c606bc85a3e9fd9d010f874ad760336"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a></div><div class="ttdeci">int save_2d_data(const char *fname, const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:60</div></div>
<div class="ttc" id="agroup__machine__learning_html_ga6c606bc85a3e9fd9d010f874ad760336"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga6c606bc85a3e9fd9d010f874ad760336">save_2d_data</a></div><div class="ttdeci">int save_2d_data(const char *fname, const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:62</div></div>
<div class="ttc" id="ahash__search_8cpp_html_a6e1a77282bc65ad359d753d25df23243"><div class="ttname"><a href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a></div><div class="ttdeci">int data[MAX]</div><div class="ttdoc">test data</div><div class="ttdef"><b>Definition:</b> hash_search.cpp:24</div></div>
<div class="ttc" id="anamespacemachine__learning_html_a1d577f5d95b774ae97eb6838852d0df5"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; &amp;W)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:133</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a2256c10b16edba377b64a44b6c656908"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a></div><div class="ttdeci">double get_clock_diff(clock_t start_t, clock_t end_t)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:559</div></div>
<div class="ttc" id="anamespacemachine__learning_html_a1d577f5d95b774ae97eb6838852d0df5"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; &amp;W)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:135</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a2256c10b16edba377b64a44b6c656908"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a></div><div class="ttdeci">double get_clock_diff(clock_t start_t, clock_t end_t)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:561</div></div>
<div class="ttc" id="atime_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/time.html">std::time</a></div><div class="ttdeci">T time(T... args)</div></div>
<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>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6b5e744876fd980a3451cbb385d4e755"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:318</div></div>
<div class="ttc" id="anamespacemachine__learning_html_adc731720947b4bc2ab047c141e7d0299"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, double alpha_min)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:259</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0e7435446ed7c763f7de79a468add2e0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a></div><div class="ttdeci">void test_3d_classes2(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:477</div></div>
<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:48</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6b5e744876fd980a3451cbb385d4e755"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6b5e744876fd980a3451cbb385d4e755">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:320</div></div>
<div class="ttc" id="anamespacemachine__learning_html_adc731720947b4bc2ab047c141e7d0299"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, double alpha_min)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:261</div></div>
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0e7435446ed7c763f7de79a468add2e0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0e7435446ed7c763f7de79a468add2e0">test_3d_classes2</a></div><div class="ttdeci">void test_3d_classes2(std::vector&lt; std::valarray&lt; double &gt;&gt; *data)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:479</div></div>
<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:50</div></div>
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@@ -148,7 +148,8 @@ Functions</h2></td></tr>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p><a href="https://en.wikipedia.org/wiki/ADALINE">Adaptive Linear Neuron (ADALINE)</a> implementation </p>
<dl class="section author"><dt>Author</dt><dd><a href="https://github.com/kvedala">Krishna Vedala</a></dd></dl>
<p><img src="https://upload.wikimedia.org/wikipedia/commons/b/be/Adaline_flow_chart.gif" alt="" width="200px" class="inline"/> <a href="https://commons.wikimedia.org/wiki/File:Adaline_flow_chart.gif">source</a> ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function </p><p class="formulaDsp">
<p><a href="https://commons.wikimedia.org/wiki/File:Adaline_flow_chart.gif"><img src="https://upload.wikimedia.org/wikipedia/commons/b/be/Adaline_flow_chart.gif" alt="Structure of an ADALINE network. Source: Wikipedia" style="width:200px; float:right;" class="inline"/></a></p>
<p>ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function </p><p class="formulaDsp">
\[ f\left(x_0,x_1,x_2,\ldots\right) = \sum_j x_jw_j+\theta \]
</p>
<p> where \(x_j\) are the input features of a sample, \(w_j\) are the coefficients of the linear function and \(\theta\) is a constant. If we know the \(w_j\), then for any given set of features, \(y\) can be computed. Computing the \(w_j\) is a supervised learning algorithm wherein a set of features and their corresponding outputs are given and weights are computed using stochastic gradient descent method. </p>
@@ -179,27 +180,27 @@ Functions</h2></td></tr>
</table>
</div><div class="memdoc">
<p>Main function </p>
<div class="fragment"><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; {</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/srand.html">std::srand</a>(<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/chrono/c/time.html">std::time</a>(<span class="keyword">nullptr</span>)); <span class="comment">// initialize random number generator</span></div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; </div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="keywordtype">double</span> eta = 0.1; <span class="comment">// default value of eta</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; <span class="keywordflow">if</span> (argc == 2) <span class="comment">// read eta value from commandline argument if present</span></div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; eta = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/byte/strtof.html">strtof</a>(argv[1], <span class="keyword">nullptr</span>);</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; </div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a52053d88ea1bcbbed9aca67ab4eeb499">test1</a>(eta);</div>
<div class="fragment"><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; {</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/srand.html">std::srand</a>(<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/chrono/c/time.html">std::time</a>(<span class="keyword">nullptr</span>)); <span class="comment">// initialize random number generator</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; </div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keywordtype">double</span> eta = 0.1; <span class="comment">// default value of eta</span></div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; <span class="keywordflow">if</span> (argc == 2) <span class="comment">// read eta value from commandline argument if present</span></div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; eta = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/string/byte/strtof.html">strtof</a>(argv[1], <span class="keyword">nullptr</span>);</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; </div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Press ENTER to continue...&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_istream.html">std::cin</a>.get();</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; </div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a379f7488a305f2571f2932b319931f82">test2</a>(eta);</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a52053d88ea1bcbbed9aca67ab4eeb499">test1</a>(eta);</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; </div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Press ENTER to continue...&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_istream.html">std::cin</a>.get();</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; </div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Press ENTER to continue...&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_istream.html">std::cin</a>.get();</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; </div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a>(eta);</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a379f7488a305f2571f2932b319931f82">test2</a>(eta);</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; </div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Press ENTER to continue...&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_istream.html">std::cin</a>.get();</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; </div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160;}</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; <a class="code" href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a>(eta);</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; </div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160;}</div>
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@@ -230,32 +231,32 @@ Here is the call graph for this function:</div>
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</dd>
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<div class="fragment"><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; {</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; </div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 10; <span class="comment">// number of sample points</span></div>
<div class="fragment"><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; {</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; </div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N] = {{0, 1}, {1, -2}, {2, 3}, {3, -1},</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; {4, 1}, {6, -5}, {-7, -3}, {-8, 5},</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; {-9, 2}, {-10, -15}};</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <span class="keywordtype">int</span> y[] = {1, -1, 1, -1, -1, -1, 1, 1, 1, -1}; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 1 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; </div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; ada.fit(X, y);</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; </div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({5, -3});</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(5,-3): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; assert(predict == -1);</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; predict = ada.predict({5, 8});</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(5,8): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; assert(predict == 1);</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160;}</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 10; <span class="comment">// number of sample points</span></div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; </div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N] = {{0, 1}, {1, -2}, {2, 3}, {3, -1},</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; {4, 1}, {6, -5}, {-7, -3}, {-8, 5},</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; {-9, 2}, {-10, -15}};</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <span class="keywordtype">int</span> y[] = {1, -1, 1, -1, -1, -1, 1, 1, 1, -1}; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 1 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; </div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; ada.fit(X, y);</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; </div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({5, -3});</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(5,-3): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; assert(predict == -1);</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; </div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; predict = ada.predict({5, 8});</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(5,8): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; assert(predict == 1);</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160;}</div>
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</dl>
<div class="fragment"><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; {</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; </div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 50; <span class="comment">// number of sample points</span></div>
<div class="fragment"><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; {</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N];</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="keywordtype">int</span> Y[N]; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; </div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="comment">// generate sample points in the interval</span></div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="keywordtype">int</span> range = 500; <span class="comment">// sample points full-range</span></div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; <span class="keywordtype">int</span> range2 = range &gt;&gt; 1; <span class="comment">// sample points half-range</span></div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; X[i] = {x0, x1};</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; Y[i] = (x0 + 3. * x1) &gt; -1 ? 1 : -1;</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; }</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; </div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 2 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; </div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; ada.fit(X, Y);</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; </div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <span class="keywordtype">int</span> N_test_cases = 5;</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N_test_cases; i++) {</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; </div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({x0, x1});</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 50; <span class="comment">// number of sample points</span></div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; </div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N];</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordtype">int</span> Y[N]; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; </div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="comment">// generate sample points in the interval</span></div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; <span class="keywordtype">int</span> range = 500; <span class="comment">// sample points full-range</span></div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="keywordtype">int</span> range2 = range &gt;&gt; 1; <span class="comment">// sample points half-range</span></div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; X[i] = {x0, x1};</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; Y[i] = (x0 + 3. * x1) &gt; -1 ? 1 : -1;</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; }</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; </div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 2 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; </div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; ada.fit(X, Y);</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; </div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <span class="keywordtype">int</span> N_test_cases = 5;</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N_test_cases; i++) {</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; </div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(&quot;</span> &lt;&lt; x0 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x1 &lt;&lt; <span class="stringliteral">&quot;): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({x0, x1});</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <span class="keywordtype">int</span> expected_val = (x0 + 3. * x1) &gt; -1 ? 1 : -1;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; assert(predict == expected_val);</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; }</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160;}</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(&quot;</span> &lt;&lt; x0 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x1 &lt;&lt; <span class="stringliteral">&quot;): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; </div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; <span class="keywordtype">int</span> expected_val = (x0 + 3. * x1) &gt; -1 ? 1 : -1;</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; assert(predict == expected_val);</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; }</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160;}</div>
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</table>
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<div class="fragment"><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; {</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(6, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; </div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 100; <span class="comment">// number of sample points</span></div>
<div class="fragment"><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; {</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(6, eta); <span class="comment">// 2 features</span></div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N];</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; <span class="keywordtype">int</span> Y[N]; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; </div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; <span class="comment">// generate sample points in the interval</span></div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <span class="keywordtype">int</span> range = 200; <span class="comment">// sample points full-range</span></div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; <span class="keywordtype">int</span> range2 = range &gt;&gt; 1; <span class="comment">// sample points half-range</span></div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="keywordtype">double</span> x2 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; X[i] = {x0, x1, x2, x0 * x0, x1 * x1, x2 * x2};</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; Y[i] = ((x0 * x0) + (x1 * x1) + (x2 * x2)) &lt;= 1.f ? 1 : -1;</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; }</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; </div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 3 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; </div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; ada.fit(X, Y);</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <span class="keywordtype">int</span> N_test_cases = 5;</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N_test_cases; i++) {</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <span class="keywordtype">double</span> x2 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({x0, x1, x2, x0 * x0, x1 * x1, x2 * x2});</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> N = 100; <span class="comment">// number of sample points</span></div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; </div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a> X[N];</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; <span class="keywordtype">int</span> Y[N]; <span class="comment">// corresponding y-values</span></div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <span class="comment">// generate sample points in the interval</span></div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="keywordtype">int</span> range = 200; <span class="comment">// sample points full-range</span></div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <span class="keywordtype">int</span> range2 = range &gt;&gt; 1; <span class="comment">// sample points half-range</span></div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; <span class="keywordtype">double</span> x2 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; X[i] = {x0, x1, x2, x0 * x0, x1 * x1, x2 * x2};</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; Y[i] = ((x0 * x0) + (x1 * x1) + (x2 * x2)) &lt;= 1.f ? 1 : -1;</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; }</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; </div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;------- Test 3 -------&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model before fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; </div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; ada.fit(X, Y);</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Model after fit: &quot;</span> &lt;&lt; ada &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; </div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <span class="keywordtype">int</span> N_test_cases = 5;</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N_test_cases; i++) {</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <span class="keywordtype">double</span> x0 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; <span class="keywordtype">double</span> x1 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; <span class="keywordtype">double</span> x2 = ((<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/random/rand.html">std::rand</a>() % range) - range2) / 100.f;</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; </div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(&quot;</span> &lt;&lt; x0 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x1 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x2</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; &lt;&lt; <span class="stringliteral">&quot;): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; </div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <span class="keywordtype">int</span> expected_val = ((x0 * x0) + (x1 * x1) + (x2 * x2)) &lt;= 1.f ? 1 : -1;</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; assert(predict == expected_val);</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; }</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160;}</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <span class="keywordtype">int</span> predict = ada.predict({x0, x1, x2, x0 * x0, x1 * x1, x2 * x2});</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; </div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Predict for x=(&quot;</span> &lt;&lt; x0 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x1 &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; x2</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; &lt;&lt; <span class="stringliteral">&quot;): &quot;</span> &lt;&lt; predict;</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; </div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <span class="keywordtype">int</span> expected_val = ((x0 * x0) + (x1 * x1) + (x2 * x2)) &lt;= 1.f ? 1 : -1;</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; assert(predict == expected_val);</div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot; ...passed&quot;</span> &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; }</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160;}</div>
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<div class="ttc" id="asrand_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/random/srand.html">std::srand</a></div><div class="ttdeci">T srand(T... args)</div></div>
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<div class="ttc" id="atime_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/chrono/c/time.html">std::time</a></div><div class="ttdeci">T time(T... args)</div></div>
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<div class="ttc" id="aadaline__learning_8cpp_html_a992bdf1fdb0b9d414bcf7981d2d87aa9"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a></div><div class="ttdeci">void test3(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:287</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:42</div></div>
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<div class="ttc" id="aadaline__learning_8cpp_html_a992bdf1fdb0b9d414bcf7981d2d87aa9"><div class="ttname"><a href="../../d5/db0/adaline__learning_8cpp.html#a992bdf1fdb0b9d414bcf7981d2d87aa9">test3</a></div><div class="ttdeci">void test3(double eta=0.01)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:289</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:44</div></div>
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<div class="fragment"><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; : <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a>(<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a>), <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>(<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>) {</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a> &lt;= 0) {</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> &lt;&lt; <span class="stringliteral">&quot;learning rate should be positive and nonzero&quot;</span></div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a>(EXIT_FAILURE);</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; }</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a> = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a>(</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; num_features +</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; 1); <span class="comment">// additional weight is for the constant bias term</span></div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="comment">// initialize with random weights in the range [-50, 49]</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i] = 1.<a class="code" href="../../d4/d32/fibonacci__fast_8cpp.html#a3ba232425d45f9e9c0b87a8cf7ab69d9">f</a>;</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// weights[i] = (static_cast&lt;double&gt;(std::rand() % 100) - 50);</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; }</div>
<div class="fragment"><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; : <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a>(<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a>), <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>(<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>) {</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a> &lt;= 0) {</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> &lt;&lt; <span class="stringliteral">&quot;learning rate should be positive and nonzero&quot;</span></div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a>(EXIT_FAILURE);</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; }</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a> = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;double&gt;</a>(</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; num_features +</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; 1); <span class="comment">// additional weight is for the constant bias term</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// initialize with random weights in the range [-50, 49]</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i] = 1.<a class="code" href="../../d4/d32/fibonacci__fast_8cpp.html#a3ba232425d45f9e9c0b87a8cf7ab69d9">f</a>;</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="comment">// weights[i] = (static_cast&lt;double&gt;(std::rand() % 100) - 50);</span></div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; }</div>
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@@ -252,16 +252,16 @@ Here is the call graph for this function:</div>
<dl class="section return"><dt>Returns</dt><dd><code>true</code> size matches </dd>
<dd>
<code>false</code> size does not match </dd></dl>
<div class="fragment"><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; {</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="keywordflow">if</span> (x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() != (<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() - 1)) {</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> &lt;&lt; __func__ &lt;&lt; <span class="stringliteral">&quot;: &quot;</span></div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; &lt;&lt; <span class="stringliteral">&quot;Number of features in x does not match the feature &quot;</span></div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <span class="stringliteral">&quot;dimension in model!&quot;</span></div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; }</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; }</div>
<div class="fragment"><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; {</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keywordflow">if</span> (x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() != (<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() - 1)) {</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a> &lt;&lt; __func__ &lt;&lt; <span class="stringliteral">&quot;: &quot;</span></div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; &lt;&lt; <span class="stringliteral">&quot;Number of features in x does not match the feature &quot;</span></div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="stringliteral">&quot;dimension in model!&quot;</span></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; }</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; }</div>
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</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>correction factor </dd></dl>
<div class="fragment"><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x))</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; </div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="comment">/* output of the model with current weights */</span></div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordtype">int</span> p = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">predict</a>(x);</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordtype">int</span> prediction_error = y - p; <span class="comment">// error in estimation</span></div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keywordtype">double</span> correction_factor = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a> * prediction_error;</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="comment">/* update each weight, the last weight is the bias term */</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) {</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i] += correction_factor * x[i];</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; }</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>()] += correction_factor; <span class="comment">// update bias</span></div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordflow">return</span> correction_factor;</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; }</div>
<div class="fragment"><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; {</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x))</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="comment">/* output of the model with current weights */</span></div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keywordtype">int</span> p = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">predict</a>(x);</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keywordtype">int</span> prediction_error = y - p; <span class="comment">// error in estimation</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keywordtype">double</span> correction_factor = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a> * prediction_error;</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; </div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="comment">/* update each weight, the last weight is the bias term */</span></div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) {</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i] += correction_factor * x[i];</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; }</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>()] += correction_factor; <span class="comment">// update bias</span></div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">return</span> correction_factor;</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; }</div>
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@@ -380,35 +380,35 @@ template&lt;int N&gt; </div>
</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; {</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <span class="keywordtype">double</span> avg_pred_error = 1.f;</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; </div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keywordtype">int</span> iter;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">for</span> (iter = 0; (iter &lt; MAX_ITER) &amp;&amp; (avg_pred_error &gt; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>);</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; iter++) {</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; avg_pred_error = 0.f;</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; </div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <span class="comment">// perform fit for each sample</span></div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordtype">double</span> err = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">fit</a>(X[i], y[i]);</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; avg_pred_error += std::abs(err);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; }</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; avg_pred_error /= N;</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; </div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="comment">// Print updates every 200th iteration</span></div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// if (iter % 100 == 0)</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;\tIter &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot;: Training weights: &quot;</span> &lt;&lt; *<span class="keyword">this</span></div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; &lt;&lt; <span class="stringliteral">&quot;\tAvg error: &quot;</span> &lt;&lt; avg_pred_error &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; }</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="keywordflow">if</span> (iter &lt; MAX_ITER)</div>
<div class="fragment"><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; {</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keywordtype">double</span> avg_pred_error = 1.f;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; </div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keywordtype">int</span> iter;</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordflow">for</span> (iter = 0; (iter &lt; MAX_ITER) &amp;&amp; (avg_pred_error &gt; <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; iter++) {</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; avg_pred_error = 0.f;</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; </div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="comment">// perform fit for each sample</span></div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; N; i++) {</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordtype">double</span> err = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">fit</a>(X[i], y[i]);</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; avg_pred_error += std::abs(err);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; avg_pred_error /= N;</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; </div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="comment">// Print updates every 200th iteration</span></div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="comment">// if (iter % 100 == 0)</span></div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;\tIter &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot;: Training weights: &quot;</span> &lt;&lt; *<span class="keyword">this</span></div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; &lt;&lt; <span class="stringliteral">&quot;\tAvg error: &quot;</span> &lt;&lt; avg_pred_error &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; }</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; </div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Converged after &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot; iterations.&quot;</span></div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Did not converge after &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot; iterations.&quot;</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; }</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordflow">if</span> (iter &lt; MAX_ITER)</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Converged after &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot; iterations.&quot;</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;Did not converge after &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot; iterations.&quot;</span></div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a>;</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div>
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@@ -453,20 +453,20 @@ template&lt;int N&gt; </div>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>model prediction output </dd></dl>
<div class="fragment"><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; {</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x))</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordtype">double</span> y = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/back.html">back</a>(); <span class="comment">// assign bias value</span></div>
<div class="fragment"><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; {</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x))</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="comment">// for (int i = 0; i &lt; x.size(); i++) y += x[i] * weights[i];</span></div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; y = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/inner_product.html">std::inner_product</a>(x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/begin.html">begin</a>(), x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/end.html">end</a>(), <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/begin.html">begin</a>(), y);</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordflow">if</span> (out != <span class="keyword">nullptr</span>) <span class="comment">// if out variable is provided</span></div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; *out = y;</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; </div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordflow">return</span> activation(y); <span class="comment">// quantizer: apply ADALINE threshold function</span></div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; }</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keywordtype">double</span> y = <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/back.html">back</a>(); <span class="comment">// assign bias value</span></div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="comment">// for (int i = 0; i &lt; x.size(); i++) y += x[i] * weights[i];</span></div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; y = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/inner_product.html">std::inner_product</a>(x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/begin.html">begin</a>(), x.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/end.html">end</a>(), <a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/begin.html">begin</a>(), y);</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; </div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordflow">if</span> (out != <span class="keyword">nullptr</span>) <span class="comment">// if out variable is provided</span></div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; *out = y;</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keywordflow">return</span> activation(y); <span class="comment">// quantizer: apply ADALINE threshold function</span></div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; }</div>
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@@ -511,16 +511,16 @@ Here is the call graph for this function:</div>
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<p>Operator to print the weights of the model </p>
<div class="fragment"><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; {</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;&lt;&quot;</span>;</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) {</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; out &lt;&lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i];</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">if</span> (i &lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() - 1)</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;, &quot;</span>;</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; }</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;&gt;&quot;</span>;</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordflow">return</span> out;</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; }</div>
<div class="fragment"><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; {</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;&lt;&quot;</span>;</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) {</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; out &lt;&lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i];</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span> (i &lt; ada.<a class="code" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() - 1)</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;, &quot;</span>;</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; }</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; out &lt;&lt; <span class="stringliteral">&quot;&gt;&quot;</span>;</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">return</span> out;</div>
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@@ -533,23 +533,23 @@ Here is the call graph for this function:</div>
<div class="ttc" id="afibonacci__fast_8cpp_html_a3ba232425d45f9e9c0b87a8cf7ab69d9"><div class="ttname"><a href="../../d4/d32/fibonacci__fast_8cpp.html#a3ba232425d45f9e9c0b87a8cf7ab69d9">f</a></div><div class="ttdeci">uint64_t f[MAX]</div><div class="ttdef"><b>Definition:</b> fibonacci_fast.cpp:27</div></div>
<div class="ttc" id="avector_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt; double &gt;</a></div></div>
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<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a74e3c6c037b67895014414c5d75465e5"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">machine_learning::adaline::fit</a></div><div class="ttdeci">double fit(const std::vector&lt; double &gt; &amp;x, const int &amp;y)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:112</div></div>
<div class="ttc" id="aback_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/back.html">std::vector::back</a></div><div class="ttdeci">T back(T... args)</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ab11242d9ad5b03a75911e29b04f78fd3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">machine_learning::adaline::predict</a></div><div class="ttdeci">int predict(const std::vector&lt; double &gt; &amp;x, double *out=nullptr)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:90</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ac8a9c2aaaa63b0f27ea176857e1e7d56"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">machine_learning::adaline::check_size_match</a></div><div class="ttdeci">bool check_size_match(const std::vector&lt; double &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:174</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ab11242d9ad5b03a75911e29b04f78fd3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">machine_learning::adaline::predict</a></div><div class="ttdeci">int predict(const std::vector&lt; double &gt; &amp;x, double *out=nullptr)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:92</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ac8a9c2aaaa63b0f27ea176857e1e7d56"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">machine_learning::adaline::check_size_match</a></div><div class="ttdeci">bool check_size_match(const std::vector&lt; double &gt; &amp;x)</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:176</div></div>
<div class="ttc" id="abasic_ostream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cerr</a></div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a28160d17e492597a2f112e0d38551cda"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">machine_learning::adaline::eta</a></div><div class="ttdeci">const double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:185</div></div>
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">machine_learning::adaline::weights</a></div><div class="ttdeci">std::vector&lt; double &gt; weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:187</div></div>
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<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">machine_learning::adaline::weights</a></div><div class="ttdeci">std::vector&lt; double &gt; weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:189</div></div>
<div class="ttc" id="aendl_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a></div><div class="ttdeci">T endl(T... args)</div></div>
<div class="ttc" id="abegin_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/begin.html">std::vector::begin</a></div><div class="ttdeci">T begin(T... args)</div></div>
<div class="ttc" id="aend_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/end.html">std::vector::end</a></div><div class="ttdeci">T end(T... args)</div></div>
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<div class="ttc" id="aclassmachine__learning_1_1adaline_html_aa23d60262f917f35836ef4b1c1d9f7d3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">machine_learning::adaline::accuracy</a></div><div class="ttdeci">const double accuracy</div><div class="ttdoc">model fit convergence accuracy</div><div class="ttdef"><b>Definition:</b> adaline_learning.cpp:188</div></div>
<div class="ttc" id="aexit_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/utility/program/exit.html">std::exit</a></div><div class="ttdeci">T exit(T... args)</div></div>
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d7/d6a/bisection__method_8cpp.html
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<div class="ttc" id="abasic_ostream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a></div></div>
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<div class="ttc" id="aendl_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/manip/endl.html">std::endl</a></div><div class="ttdeci">T endl(T... args)</div></div>
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@@ -268,7 +269,7 @@ template&lt;typename T &gt; </div>
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d8/d53/modular__inverse__fermat__little__theorem_8cpp.html
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@@ -271,7 +271,7 @@ Here is the call graph for this function:</div>
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@@ -174,7 +174,7 @@ Here is the call graph for this function:</div>
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