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< a href = "#define-members" > Macros< / a > |
< a href = "#func-members" > Functions< / a > < / div >
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< div class = "headertitle" > < div class = "title" > Kohonen SOM trace/chain algorithm< div class = "ingroups" > < a class = "el" href = "../../d9/d66/group__machine__learning.html" > Machine learning algorithms< / a > < / div > < / div > < / div >
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< div class = "contents" >
< div class = "dynheader" >
Collaboration diagram for Kohonen SOM trace/chain algorithm:< / div >
< div class = "dyncontent" >
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< div class = "center" > < iframe scrolling = "no" frameborder = "0" src = "../../d0/dcb/group__kohonen__1d.svg" width = "418" height = "51" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe >
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< / div >
< / div >
< table class = "memberdecls" >
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< tr class = "heading" > < td colspan = "2" > < h2 class = "groupheader" > < a id = "define-members" name = "define-members" > < / a >
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Macros< / h2 > < / td > < / tr >
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< tr class = "memitem:gaffe776513b24d84b39af8ab0930fef7f" > < td class = "memItemLeft" align = "right" valign = "top" > < a id = "gaffe776513b24d84b39af8ab0930fef7f" name = "gaffe776513b24d84b39af8ab0930fef7f" > < / a >
#define  < / td > < td class = "memItemRight" valign = "bottom" > < b > max< / b > (a, b)      (((a) > (b)) ? (a) : (b))< / td > < / tr >
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< tr class = "memdesc:gaffe776513b24d84b39af8ab0930fef7f" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > shorthand for maximum value < br / > < / td > < / tr >
< tr class = "separator:gaffe776513b24d84b39af8ab0930fef7f" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:gac6afabdc09a49a433ee19d8a9486056d" > < td class = "memItemLeft" align = "right" valign = "top" > < a id = "gac6afabdc09a49a433ee19d8a9486056d" name = "gac6afabdc09a49a433ee19d8a9486056d" > < / a >
#define  < / td > < td class = "memItemRight" valign = "bottom" > < b > min< / b > (a, b)      (((a) < (b)) ? (a) : (b))< / td > < / tr >
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< tr class = "memdesc:gac6afabdc09a49a433ee19d8a9486056d" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > shorthand for minimum value < br / > < / td > < / tr >
< tr class = "separator:gac6afabdc09a49a433ee19d8a9486056d" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< / table > < table class = "memberdecls" >
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< tr class = "heading" > < td colspan = "2" > < h2 class = "groupheader" > < a id = "func-members" name = "func-members" > < / a >
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Functions< / h2 > < / td > < / tr >
< tr class = "memitem:gaf5ce14f026d6d231bef29161bac2b485" > < td class = "memItemLeft" align = "right" valign = "top" > double  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d0/dcb/group__kohonen__1d.html#gaf5ce14f026d6d231bef29161bac2b485" > _random< / a > (double a, double b)< / td > < / tr >
< tr class = "memdesc:gaf5ce14f026d6d231bef29161bac2b485" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Helper function to generate a random number in a given interval. < a href = "../../d0/dcb/group__kohonen__1d.html#gaf5ce14f026d6d231bef29161bac2b485" > More...< / a > < br / > < / td > < / tr >
< tr class = "separator:gaf5ce14f026d6d231bef29161bac2b485" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:ga7b84b14e60f47812b581d1f93057c85a" > < td class = "memItemLeft" align = "right" valign = "top" > int  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d0/dcb/group__kohonen__1d.html#ga7b84b14e60f47812b581d1f93057c85a" > save_nd_data< / a > (const char *fname, double **X, int num_points, int num_features)< / td > < / tr >
< tr class = "memdesc:ga7b84b14e60f47812b581d1f93057c85a" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Save a given n-dimensional data martix to file. < a href = "../../d0/dcb/group__kohonen__1d.html#ga7b84b14e60f47812b581d1f93057c85a" > More...< / a > < br / > < / td > < / tr >
< tr class = "separator:ga7b84b14e60f47812b581d1f93057c85a" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:ga4a57a413a3cef286a7da6d4666575586" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d0/dcb/group__kohonen__1d.html#ga4a57a413a3cef286a7da6d4666575586" > kohonen_get_min_1d< / a > (double const *X, int N, double *val, int *idx)< / td > < / tr >
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< tr class = "memdesc:ga4a57a413a3cef286a7da6d4666575586" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Get minimum value and index of the value in a vector. < a href = "../../d0/dcb/group__kohonen__1d.html#ga4a57a413a3cef286a7da6d4666575586" > More...< / a > < br / > < / td > < / tr >
< tr class = "separator:ga4a57a413a3cef286a7da6d4666575586" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:gae334493a0917a24736fe5ba82aa6f81f" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d0/dcb/group__kohonen__1d.html#gae334493a0917a24736fe5ba82aa6f81f" > kohonen_update_weights< / a > (double const *x, double *const *W, double *D, int num_out, int num_features, double alpha, int R)< / td > < / tr >
< tr class = "memdesc:gae334493a0917a24736fe5ba82aa6f81f" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Update weights of the SOM using Kohonen algorithm. < a href = "../../d0/dcb/group__kohonen__1d.html#gae334493a0917a24736fe5ba82aa6f81f" > More...< / a > < br / > < / td > < / tr >
< tr class = "separator:gae334493a0917a24736fe5ba82aa6f81f" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:gaeaeffbff2be4d5d15b0d4f10f846abde" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d0/dcb/group__kohonen__1d.html#gaeaeffbff2be4d5d15b0d4f10f846abde" > kohonen_som_tracer< / a > (double **X, double *const *W, int num_samples, int num_features, int num_out, double alpha_min)< / td > < / tr >
< tr class = "memdesc:gaeaeffbff2be4d5d15b0d4f10f846abde" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Apply incremental algorithm with updating neighborhood and learning rates on all samples in the given datset. < a href = "../../d0/dcb/group__kohonen__1d.html#gaeaeffbff2be4d5d15b0d4f10f846abde" > More...< / a > < br / > < / td > < / tr >
< tr class = "separator:gaeaeffbff2be4d5d15b0d4f10f846abde" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< / table >
< a name = "details" id = "details" > < / a > < h2 class = "groupheader" > Detailed Description< / h2 >
< h2 class = "groupheader" > Function Documentation< / h2 >
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< a id = "gaf5ce14f026d6d231bef29161bac2b485" name = "gaf5ce14f026d6d231bef29161bac2b485" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#gaf5ce14f026d6d231bef29161bac2b485" > ◆ < / a > < / span > _random()< / h2 >
< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > double _random < / td >
< td > (< / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > a< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > b< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Helper function to generate a random number in a given interval. < / p >
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< p > < br / >
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Steps:< / p > < ol type = "1" >
< li > < code > r1 = rand() % 100< / code > gets a random number between 0 and 99< / li >
< li > < code > r2 = r1 / 100< / code > converts random number to be between 0 and 0.99< / li >
< li > scale and offset the random number to given range of \([a,b)\) < p class = "formulaDsp" >
\[ y = (b - a) \times \frac{\text{(random number between 0 and RAND_MAX)} \; \text{mod}\; 100}{100} + a \]
< / p >
< / li >
< / ol >
< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramname" > a< / td > < td > lower limit < / td > < / tr >
< tr > < td class = "paramname" > b< / td > < td > upper limit < / td > < / tr >
< / table >
< / dd >
< / dl >
< dl class = "section return" > < dt > Returns< / dt > < dd > random number in the range \([a,b)\) < / dd > < / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 55< / span > {< / div >
< div class = "line" > < span class = "lineno" > 56< / span > < span class = "keywordtype" > int< / span > r = rand() % 100;< / div >
< div class = "line" > < span class = "lineno" > 57< / span > < span class = "keywordflow" > return< / span > ((b - a) * r / 100.f) + a;< / div >
< div class = "line" > < span class = "lineno" > 58< / span > }< / div >
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< a id = "ga4a57a413a3cef286a7da6d4666575586" name = "ga4a57a413a3cef286a7da6d4666575586" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#ga4a57a413a3cef286a7da6d4666575586" > ◆ < / a > < / span > kohonen_get_min_1d()< / h2 >
< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void kohonen_get_min_1d < / td >
< td > (< / td >
< td class = "paramtype" > double const *  < / td >
< td class = "paramname" > < em > X< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > N< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double *  < / td >
< td class = "paramname" > < em > val< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int *  < / td >
< td class = "paramname" > < em > idx< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Get minimum value and index of the value in a vector. < / p >
< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > X< / td > < td > vector to search < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > N< / td > < td > number of points in the vector < / td > < / tr >
< tr > < td class = "paramdir" > [out]< / td > < td class = "paramname" > val< / td > < td > minimum value found < / td > < / tr >
< tr > < td class = "paramdir" > [out]< / td > < td class = "paramname" > idx< / td > < td > index where minimum value was found < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 105< / span > {< / div >
< div class = "line" > < span class = "lineno" > 106< / span > val[0] = INFINITY; < span class = "comment" > // initial min value< / span > < / div >
< div class = "line" > < span class = "lineno" > 107< / span > < / div >
< div class = "line" > < span class = "lineno" > 108< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++) < span class = "comment" > // check each value< / span > < / div >
< div class = "line" > < span class = "lineno" > 109< / span > {< / div >
< div class = "line" > < span class = "lineno" > 110< / span > < span class = "keywordflow" > if< / span > (X[i] < val[0]) < span class = "comment" > // if a lower value is found< / span > < / div >
< div class = "line" > < span class = "lineno" > 111< / span > { < span class = "comment" > // save the value and its index< / span > < / div >
< div class = "line" > < span class = "lineno" > 112< / span > idx[0] = i;< / div >
< div class = "line" > < span class = "lineno" > 113< / span > val[0] = X[i];< / div >
< div class = "line" > < span class = "lineno" > 114< / span > }< / div >
< div class = "line" > < span class = "lineno" > 115< / span > }< / div >
< div class = "line" > < span class = "lineno" > 116< / span > }< / div >
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< a id = "gaeaeffbff2be4d5d15b0d4f10f846abde" name = "gaeaeffbff2be4d5d15b0d4f10f846abde" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#gaeaeffbff2be4d5d15b0d4f10f846abde" > ◆ < / a > < / span > kohonen_som_tracer()< / h2 >
< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void kohonen_som_tracer < / td >
< td > (< / td >
< td class = "paramtype" > double **  < / td >
< td class = "paramname" > < em > X< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double *const *  < / td >
< td class = "paramname" > < em > W< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_samples< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_features< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_out< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > alpha_min< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Apply incremental algorithm with updating neighborhood and learning rates on all samples in the given datset. < / p >
< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > X< / td > < td > data set < / td > < / tr >
< tr > < td class = "paramdir" > [in,out]< / td > < td class = "paramname" > W< / td > < td > weights matrix < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_samples< / td > < td > number of output points < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_features< / td > < td > number of features per input sample < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_out< / td > < td > number of output points < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > alpha_min< / td > < td > terminal value of alpha < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 181< / span > {< / div >
< div class = "line" > < span class = "lineno" > 182< / span > < span class = "keywordtype" > int< / span > R = num_out > > 2, iter = 0;< / div >
< div class = "line" > < span class = "lineno" > 183< / span > < span class = "keywordtype" > double< / span > alpha = 1.f;< / div >
< div class = "line" > < span class = "lineno" > 184< / span > < span class = "keywordtype" > double< / span > *D = (< span class = "keywordtype" > double< / span > *)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (num_out * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > ));< / div >
< div class = "line" > < span class = "lineno" > 185< / span > < / div >
< div class = "line" > < span class = "lineno" > 186< / span > < span class = "comment" > // Loop alpha from 1 to alpha_min< / span > < / div >
< div class = "line" > < span class = "lineno" > 187< / span > < span class = "keywordflow" > for< / span > (; alpha > alpha_min; alpha -= 0.01, iter++)< / div >
< div class = "line" > < span class = "lineno" > 188< / span > {< / div >
< div class = "line" > < span class = "lineno" > 189< / span > < span class = "comment" > // Loop for each sample pattern in the data set< / span > < / div >
< div class = "line" > < span class = "lineno" > 190< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > sample = 0; sample < num_samples; sample++)< / div >
< div class = "line" > < span class = "lineno" > 191< / span > {< / div >
< div class = "line" > < span class = "lineno" > 192< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > double< / span > *x = X[sample];< / div >
< div class = "line" > < span class = "lineno" > 193< / span > < span class = "comment" > // update weights for the current input pattern sample< / span > < / div >
< div class = "line" > < span class = "lineno" > 194< / span > < a class = "code hl_function" href = "../../d0/dcb/group__kohonen__1d.html#gae334493a0917a24736fe5ba82aa6f81f" > kohonen_update_weights< / a > (x, W, D, num_out, num_features, alpha, R);< / div >
< div class = "line" > < span class = "lineno" > 195< / span > }< / div >
< div class = "line" > < span class = "lineno" > 196< / span > < / div >
< div class = "line" > < span class = "lineno" > 197< / span > < span class = "comment" > // every 10th iteration, reduce the neighborhood range< / span > < / div >
< div class = "line" > < span class = "lineno" > 198< / span > < span class = "keywordflow" > if< / span > (iter % 10 == 0 & & R > 1)< / div >
< div class = "line" > < span class = "lineno" > 199< / span > R--;< / div >
< div class = "line" > < span class = "lineno" > 200< / span > }< / div >
< div class = "line" > < span class = "lineno" > 201< / span > < / div >
< div class = "line" > < span class = "lineno" > 202< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (D);< / div >
< div class = "line" > < span class = "lineno" > 203< / span > }< / div >
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< div class = "ttc" id = "agroup__kohonen__1d_html_gae334493a0917a24736fe5ba82aa6f81f" > < div class = "ttname" > < a href = "../../d0/dcb/group__kohonen__1d.html#gae334493a0917a24736fe5ba82aa6f81f" > kohonen_update_weights< / a > < / div > < div class = "ttdeci" > void kohonen_update_weights(double const *x, double *const *W, double *D, int num_out, int num_features, double alpha, int R)< / div > < div class = "ttdoc" > Update weights of the SOM using Kohonen algorithm.< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_trace.c:129< / div > < / div >
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< div class = "ttc" id = "amalloc__dbg_8h_html_a725f50ecaf1959d96de79b36b4788fee" > < div class = "ttname" > < a href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > < / div > < div class = "ttdeci" > #define malloc(bytes)< / div > < div class = "ttdoc" > This macro replace the standard malloc function with malloc_dbg.< / div > < div class = "ttdef" > < b > Definition:< / b > malloc_dbg.h:18< / div > < / div >
< div class = "ttc" id = "amalloc__dbg_8h_html_a9cc854374299a1dd933bf62029761768" > < div class = "ttname" > < a href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > < / div > < div class = "ttdeci" > #define free(ptr)< / div > < div class = "ttdoc" > This macro replace the standard free function with free_dbg.< / div > < div class = "ttdef" > < b > Definition:< / b > malloc_dbg.h:26< / div > < / div >
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< / div > <!-- fragment --> < div class = "dynheader" >
Here is the call graph for this function:< / div >
< div class = "dyncontent" >
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< div class = "center" > < iframe scrolling = "no" frameborder = "0" src = "../../d0/dcb/group__kohonen__1d_gaeaeffbff2be4d5d15b0d4f10f846abde_cgraph.svg" width = "564" height = "38" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe >
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< / div >
< / div >
< / div >
< / div >
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< a id = "gae334493a0917a24736fe5ba82aa6f81f" name = "gae334493a0917a24736fe5ba82aa6f81f" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#gae334493a0917a24736fe5ba82aa6f81f" > ◆ < / a > < / span > kohonen_update_weights()< / h2 >
< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void kohonen_update_weights < / td >
< td > (< / td >
< td class = "paramtype" > double const *  < / td >
< td class = "paramname" > < em > x< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double *const *  < / td >
< td class = "paramname" > < em > W< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double *  < / td >
< td class = "paramname" > < em > D< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_out< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_features< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > alpha< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > R< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Update weights of the SOM using Kohonen algorithm. < / p >
< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > x< / td > < td > data point < / td > < / tr >
< tr > < td class = "paramdir" > [in,out]< / td > < td class = "paramname" > W< / td > < td > weights matrix < / td > < / tr >
< tr > < td class = "paramdir" > [in,out]< / td > < td class = "paramname" > D< / td > < td > temporary vector to store distances < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_out< / td > < td > number of output points < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_features< / td > < td > number of features per input sample < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > alpha< / td > < td > learning rate \(0< \alpha\le1\) < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > R< / td > < td > neighborhood range < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 131< / span > {< / div >
< div class = "line" > < span class = "lineno" > 132< / span > < span class = "keywordtype" > int< / span > j, k;< / div >
< div class = "line" > < span class = "lineno" > 133< / span > < / div >
< div class = "line" > < span class = "lineno" > 134< / span > < span class = "preprocessor" > #ifdef _OPENMP< / span > < / div >
< div class = "line" > < span class = "lineno" > 135< / span > < span class = "preprocessor" > #pragma omp for< / span > < / div >
< div class = "line" > < span class = "lineno" > 136< / span > < span class = "preprocessor" > #endif< / span > < / div >
< div class = "line" > < span class = "lineno" > 137< / span > < span class = "comment" > // step 1: for each output point< / span > < / div >
< div class = "line" > < span class = "lineno" > 138< / span > < span class = "keywordflow" > for< / span > (j = 0; j < num_out; j++)< / div >
< div class = "line" > < span class = "lineno" > 139< / span > {< / div >
< div class = "line" > < span class = "lineno" > 140< / span > D[j] = 0.f;< / div >
< div class = "line" > < span class = "lineno" > 141< / span > < span class = "comment" > // compute Euclidian distance of each output< / span > < / div >
< div class = "line" > < span class = "lineno" > 142< / span > < span class = "comment" > // point from the current sample< / span > < / div >
< div class = "line" > < span class = "lineno" > 143< / span > < span class = "keywordflow" > for< / span > (k = 0; k < num_features; k++)< / div >
< div class = "line" > < span class = "lineno" > 144< / span > D[j] += (W[j][k] - x[k]) * (W[j][k] - x[k]);< / div >
< div class = "line" > < span class = "lineno" > 145< / span > }< / div >
< div class = "line" > < span class = "lineno" > 146< / span > < / div >
< div class = "line" > < span class = "lineno" > 147< / span > < span class = "comment" > // step 2: get closest node i.e., node with smallest Euclidian distance to< / span > < / div >
< div class = "line" > < span class = "lineno" > 148< / span > < span class = "comment" > // the current pattern< / span > < / div >
< div class = "line" > < span class = "lineno" > 149< / span > < span class = "keywordtype" > int< / span > d_min_idx;< / div >
< div class = "line" > < span class = "lineno" > 150< / span > < span class = "keywordtype" > double< / span > d_min;< / div >
< div class = "line" > < span class = "lineno" > 151< / span > < a class = "code hl_function" href = "../../d0/dcb/group__kohonen__1d.html#ga4a57a413a3cef286a7da6d4666575586" > kohonen_get_min_1d< / a > (D, num_out, & d_min, & d_min_idx);< / div >
< div class = "line" > < span class = "lineno" > 152< / span > < / div >
< div class = "line" > < span class = "lineno" > 153< / span > < span class = "comment" > // step 3a: get the neighborhood range< / span > < / div >
< div class = "line" > < span class = "lineno" > 154< / span > < span class = "keywordtype" > int< / span > from_node = < a class = "code hl_define" href = "../../d0/dcb/group__kohonen__1d.html#gaffe776513b24d84b39af8ab0930fef7f" > max< / a > (0, d_min_idx - R);< / div >
< div class = "line" > < span class = "lineno" > 155< / span > < span class = "keywordtype" > int< / span > to_node = < a class = "code hl_define" href = "../../d0/dcb/group__kohonen__1d.html#gac6afabdc09a49a433ee19d8a9486056d" > min< / a > (num_out, d_min_idx + R + 1);< / div >
< div class = "line" > < span class = "lineno" > 156< / span > < / div >
< div class = "line" > < span class = "lineno" > 157< / span > < span class = "comment" > // step 3b: update the weights of nodes in the< / span > < / div >
< div class = "line" > < span class = "lineno" > 158< / span > < span class = "comment" > // neighborhood< / span > < / div >
< div class = "line" > < span class = "lineno" > 159< / span > < span class = "preprocessor" > #ifdef _OPENMP< / span > < / div >
< div class = "line" > < span class = "lineno" > 160< / span > < span class = "preprocessor" > #pragma omp for< / span > < / div >
< div class = "line" > < span class = "lineno" > 161< / span > < span class = "preprocessor" > #endif< / span > < / div >
< div class = "line" > < span class = "lineno" > 162< / span > < span class = "keywordflow" > for< / span > (j = from_node; j < to_node; j++)< / div >
< div class = "line" > < span class = "lineno" > 163< / span > < span class = "keywordflow" > for< / span > (k = 0; k < num_features; k++)< / div >
< div class = "line" > < span class = "lineno" > 164< / span > < span class = "comment" > // update weights of nodes in the neighborhood< / span > < / div >
< div class = "line" > < span class = "lineno" > 165< / span > W[j][k] += alpha * (x[k] - W[j][k]);< / div >
< div class = "line" > < span class = "lineno" > 166< / span > }< / div >
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< div class = "ttc" id = "agroup__kohonen__1d_html_ga4a57a413a3cef286a7da6d4666575586" > < div class = "ttname" > < a href = "../../d0/dcb/group__kohonen__1d.html#ga4a57a413a3cef286a7da6d4666575586" > kohonen_get_min_1d< / a > < / div > < div class = "ttdeci" > void kohonen_get_min_1d(double const *X, int N, double *val, int *idx)< / div > < div class = "ttdoc" > Get minimum value and index of the value in a vector.< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_trace.c:104< / div > < / div >
< div class = "ttc" id = "agroup__kohonen__1d_html_gac6afabdc09a49a433ee19d8a9486056d" > < div class = "ttname" > < a href = "../../d0/dcb/group__kohonen__1d.html#gac6afabdc09a49a433ee19d8a9486056d" > min< / a > < / div > < div class = "ttdeci" > #define min(a, b)< / div > < div class = "ttdoc" > shorthand for minimum value< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_trace.c:36< / div > < / div >
< div class = "ttc" id = "agroup__kohonen__1d_html_gaffe776513b24d84b39af8ab0930fef7f" > < div class = "ttname" > < a href = "../../d0/dcb/group__kohonen__1d.html#gaffe776513b24d84b39af8ab0930fef7f" > max< / a > < / div > < div class = "ttdeci" > #define max(a, b)< / div > < div class = "ttdoc" > shorthand for maximum value< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_trace.c:32< / div > < / div >
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< / div > <!-- fragment --> < div class = "dynheader" >
Here is the call graph for this function:< / div >
< div class = "dyncontent" >
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< div class = "center" > < iframe scrolling = "no" frameborder = "0" src = "../../d0/dcb/group__kohonen__1d_gae334493a0917a24736fe5ba82aa6f81f_cgraph.svg" width = "374" height = "38" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe >
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< / div >
< / div >
< / div >
< / div >
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< a id = "ga7b84b14e60f47812b581d1f93057c85a" name = "ga7b84b14e60f47812b581d1f93057c85a" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#ga7b84b14e60f47812b581d1f93057c85a" > ◆ < / a > < / span > save_nd_data()< / h2 >
< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > int save_nd_data < / td >
< td > (< / td >
< td class = "paramtype" > const char *  < / td >
< td class = "paramname" > < em > fname< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double **  < / td >
< td class = "paramname" > < em > X< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_points< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > num_features< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Save a given n-dimensional data martix to file. < / p >
< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > fname< / td > < td > filename to save in (gets overwriten without confirmation) < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > X< / td > < td > matrix to save < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_points< / td > < td > rows in the matrix = number of points < / td > < / tr >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > num_features< / td > < td > columns in the matrix = dimensions of points < / td > < / tr >
< / table >
< / dd >
< / dl >
< dl class = "section return" > < dt > Returns< / dt > < dd > 0 if all ok < / dd >
< dd >
-1 if file creation failed < / dd > < / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 72< / span > {< / div >
< div class = "line" > < span class = "lineno" > 73< / span > FILE *fp = fopen(fname, < span class = "stringliteral" > " wt" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 74< / span > < span class = "keywordflow" > if< / span > (!fp) < span class = "comment" > // error with fopen< / span > < / div >
< div class = "line" > < span class = "lineno" > 75< / span > {< / div >
< div class = "line" > < span class = "lineno" > 76< / span > < span class = "keywordtype" > char< / span > msg[120];< / div >
< div class = "line" > < span class = "lineno" > 77< / span > sprintf(msg, < span class = "stringliteral" > " File error (%s): " < / span > , fname);< / div >
< div class = "line" > < span class = "lineno" > 78< / span > perror(msg);< / div >
< div class = "line" > < span class = "lineno" > 79< / span > < span class = "keywordflow" > return< / span > -1;< / div >
< div class = "line" > < span class = "lineno" > 80< / span > }< / div >
< div class = "line" > < span class = "lineno" > 81< / span > < / div >
< div class = "line" > < span class = "lineno" > 82< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < num_points; i++) < span class = "comment" > // for each point in the array< / span > < / div >
< div class = "line" > < span class = "lineno" > 83< / span > {< / div >
< div class = "line" > < span class = "lineno" > 84< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > j = 0; j < num_features; j++) < span class = "comment" > // for each feature in the array< / span > < / div >
< div class = "line" > < span class = "lineno" > 85< / span > {< / div >
< div class = "line" > < span class = "lineno" > 86< / span > fprintf(fp, < span class = "stringliteral" > " %.4g" < / span > , X[i][j]); < span class = "comment" > // print the feature value< / span > < / div >
< div class = "line" > < span class = "lineno" > 87< / span > < span class = "keywordflow" > if< / span > (j < num_features - 1) < span class = "comment" > // if not the last feature< / span > < / div >
< div class = "line" > < span class = "lineno" > 88< / span > fprintf(fp, < span class = "stringliteral" > " ," < / span > ); < span class = "comment" > // suffix comma< / span > < / div >
< div class = "line" > < span class = "lineno" > 89< / span > }< / div >
< div class = "line" > < span class = "lineno" > 90< / span > < span class = "keywordflow" > if< / span > (i < num_points - 1) < span class = "comment" > // if not the last row< / span > < / div >
< div class = "line" > < span class = "lineno" > 91< / span > fprintf(fp, < span class = "stringliteral" > " \n" < / span > ); < span class = "comment" > // start a new line< / span > < / div >
< div class = "line" > < span class = "lineno" > 92< / span > }< / div >
< div class = "line" > < span class = "lineno" > 93< / span > fclose(fp);< / div >
< div class = "line" > < span class = "lineno" > 94< / span > < span class = "keywordflow" > return< / span > 0;< / div >
< div class = "line" > < span class = "lineno" > 95< / span > }< / div >
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< / div > <!-- fragment -->
< / div >
< / div >
< / div > <!-- contents -->
< / div > <!-- doc - content -->
<!-- start footer part -->
< div id = "nav-path" class = "navpath" > <!-- id is needed for treeview function! -->
< ul >
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< li class = "footer" > Generated by < a href = "https://www.doxygen.org/index.html" > < img class = "footer" src = "../../doxygen.svg" width = "104" height = "31" alt = "doxygen" / > < / a > 1.9.3 < / li >
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< / ul >
< / div >
< / body >
< / html >
