Result:
found more than 407 distributions - search limited to the first 2001 files matching your query
( run in 1.262 )
Algorithm-CurveFit-Simple
view release on metacpan or search on metacpan
bin/curvefit view on Meta::CPAN
push @ydata, $2;
}
my ($max_dev, $avg_dev, $src) = fit(xdata => \@xdata, ydata => \@ydata, %OPT);
print STDERR "$max_dev\n$avg_dev\n" if (opt('v'));
print STDERR JSON::PP::encode_json(\%Algorithm::CurveFit::Simple::STATS_H)."\n" if (opt('d') || opt('debug') || opt('profile'));
print "$src\n";
return 0;
}
sub opt {
Algorithm-DecisionTree
view release on metacpan or search on metacpan
Examples/classify_test_data_in_a_file.pl view on Meta::CPAN
" 1st arg: name of the training datafile\n" .
" 2nd arg: name of the test data file\n" .
" 3rd arg: the name of the output file to which class labels will be written\n"
unless @ARGV == 3;
my $debug = 0;
### When the following variable is set to 1, only the most probable class for each
### data record is written out to the output file. This works only for the case
### when the output is sent to a `.txt' file. If the output is sent to a `.csv'
### file, you'll see all the class names and their probabilities for each data sample
Examples/classify_test_data_in_a_file.pl view on Meta::CPAN
}
$features_and_values_hash{$feature} = \@feature_values;
}
my %seen = ();
@all_class_names = grep {$_ if !$seen{$_}++} values %class_for_sample_hash;
print "\n All class names: @all_class_names\n" if $debug;
%numeric_features_valuerange_hash = ();
my %feature_values_how_many_uniques_hash = ();
%features_and_unique_values_hash = ();
foreach my $feature (keys %features_and_values_hash) {
my %seen1 = ();
Examples/classify_test_data_in_a_file.pl view on Meta::CPAN
my @minmaxvalues = minmax(\@unique_values_for_feature);
$numeric_features_valuerange_hash{$feature} = \@minmaxvalues;
}
$features_and_unique_values_hash{$feature} = \@unique_values_for_feature;
}
if ($debug) {
print "\nAll class names: @all_class_names\n";
print "\nEach sample data record:\n";
foreach my $sample (sort {sample_index($a) <=> sample_index($b)} keys %feature_values_for_samples_hash) {
print "$sample => @{$feature_values_for_samples_hash{$sample}}\n";
}
Algorithm-Dependency-Source-DBI
view release on metacpan or search on metacpan
- Updating to Module::Install 0.91
- Filter out links on BOTH source and destination
0.05 Wed 14 Nov 2007
- No functional changes
- Adding debugging messages to work out why the AUTOMATED_TESTING
tests were run when AUTOMATED_TESTING was NOT enabled at Makefile.PL
0.04 Tue 21 Aug 2007
- Added a missing dependency on Parse::CSV under AUTOMATED_TESTING
Algorithm-Diff-XS
view release on metacpan or search on metacpan
gen_constant_list|||
get_av|5.006000||p
get_context||5.006000|n
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_mstats|||
get_no_modify|||
get_num|||
incl_perldb|||
incline|||
incpush|||
ingroup|||
init_argv_symbols|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
rsignal_restore|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
runops_debug||5.005000|
runops_standard||5.005000|
rvpv_dup|||
rxres_free|||
rxres_restore|||
rxres_save|||
Algorithm-DimReduction
view release on metacpan or search on metacpan
inc/Spiffy.pm view on Meta::CPAN
no warnings;
my $self_package = shift;
# XXX Using parse_arguments here might cause confusion, because the
# subclass's boolean_arguments and paired_arguments can conflict, causing
# difficult debugging. Consider using something truly local.
my ($args, @export_list) = do {
local *boolean_arguments = sub {
qw(
-base -Base -mixin -selfless
-XXX -dumper -yaml
Algorithm-Evolve
view release on metacpan or search on metacpan
lib/Algorithm/Evolve.pm view on Meta::CPAN
my $rand_max = (1 << 31); ## close enough
###########################
sub debug {
print @_, "\n" if $DEBUG;
}
sub new {
my $pkg = shift;
Algorithm-ExpectationMaximization
view release on metacpan or search on metacpan
examples/canned_example1.pl view on Meta::CPAN
mask => $mask,
K => 3,
max_em_iterations => 300,
seeding => 'random',
terminal_output => 1,
debug => 0,
);
$clusterer->read_data_from_file();
# For visualizing the raw data:
Algorithm-FEC
view release on metacpan or search on metacpan
*/
#ifdef TEST
#define DEB(x)
#define DDB(x) x
#define DEBUG 0 /* minimal debugging */
#ifdef MSDOS
#include <time.h>
struct timeval {
unsigned long ticks;
return 0 ;
else
m++ ;
return 1 ;
}
#endif /* debug */
/*
* invert_mat() takes a matrix and produces its inverse
* k is the size of the matrix.
* (Gauss-Jordan, adapted from Numerical Recipes in C)
Algorithm-FloodControl
view release on metacpan or search on metacpan
t/02-cache-memcached.t view on Meta::CPAN
plan skip_all => '$ENV{ MEMCACHED_SERVER } is not set';
}
plan tests => 6;
require 't/tlib.pm';
$tlib::skip_concurrency = $tlib::skip_concurrency = 1;
tlib::test_backend( 'Cache::Memcached', { servers => [ $ENV{MEMCACHED_SERVER} ], debug => 0 })
Algorithm-Genetic-Diploid
view release on metacpan or search on metacpan
lib/Algorithm/Genetic/Diploid/Base.pm view on Meta::CPAN
=cut
sub new {
my $package = shift;
$logger->debug("instantiating new $package object");
my %self = @_;
$self{'id'} = $id++;
# experiment is provided as an argument
if ( $self{'experiment'} ) {
Algorithm-Heapify-XS
view release on metacpan or search on metacpan
debop||5.005000|
debprofdump||5.005000|
debprof|||
debstackptrs||5.007003|
debstack||5.007003|
debug_start_match|||
deb||5.007003|v
del_sv|||
delete_eval_scope|||
delimcpy||5.004000|n
deprecate_commaless_var_list|||
get_context||5.006000|n
get_cvn_flags|5.009005||p
get_cvs|5.011000||p
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_mstats|||
get_no_modify|||
get_num|||
incpush_use_sep|||
incpush|||
ingroup|||
init_argv_symbols|||
init_dbargs|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
run_user_filter|||
runops_debug||5.005000|
runops_standard||5.005000|
rv2cv_op_cv||5.013006|
rvpv_dup|||
rxres_free|||
rxres_restore|||
unreferenced_to_tmp_stack|||
unshare_hek_or_pvn|||
unshare_hek|||
unsharepvn||5.004000|
unwind_handler_stack|||
update_debugger_info|||
upg_version||5.009005|
usage|||
utf16_textfilter|||
utf16_to_utf8_reversed||5.006001|
utf16_to_utf8||5.006001|
Algorithm-IRCSRP2
view release on metacpan or search on metacpan
lib/Algorithm/IRCSRP2.pm view on Meta::CPAN
'isa' => 'Str',
'is' => 'rw',
'default' => 'unknown'
);
has 'debug_cb' => (
'isa' => 'CodeRef',
'is' => 'rw',
'default' => sub {
sub {
my @args = @_;
lib/Algorithm/IRCSRP2.pm view on Meta::CPAN
print(@args);
}
}
);
has '_orig_debug_cb' => (
'isa' => 'CodeRef',
'is' => 'rw',
'default' => sub {
sub {
}
lib/Algorithm/IRCSRP2.pm view on Meta::CPAN
# -------- methods --------
sub BUILD {
my ($self) = @_;
my $orig_cb = $self->debug_cb;
$self->_orig_debug_cb($orig_cb);
my $new_cb = sub {
my $str = join('', @_);
$str = (($self->am_i_dave) ? 'Dave: ' : 'Alice: ') . $self->nickname . ' ' . $str;
return $orig_cb->($str);
};
$self->debug_cb($new_cb);
return;
}
sub init {
lib/Algorithm/IRCSRP2.pm view on Meta::CPAN
if (length($new) != (32 + 32)) {
die('decrypt_message: length($new) != 32 + 32 ; length is ' . length($new));
}
$self->debug_cb->('decrypt_message: rekeying');
$self->session_key(substr($new, 0, 32));
$self->mac_key(substr($new, 32, 32));
$self->cipher(Crypt::OpenSSL::AES->new($self->session_key));
return;
}
$self->debug_cb->("decrypt_message: from $username ; msg $msg");
return $msg;
}
sub encrypt_message {
lib/Algorithm/IRCSRP2.pm view on Meta::CPAN
=item * B<am_i_dave> (ro, Bool) - Child class will set this.
=item * B<cbc_blocksize> (ro, Int) - CBC blocksize. Defaults to '16'.
=item * B<debug_cb> (rw, CodeRef) - Debug callback. Defaults to C<print()>
=item * B<error> (rw, Str) - If set, there was an error.
=item * B<nickname> (rw, Str) - Child class will set this. Defaults to 'unknown'.
Algorithm-KMeans
view release on metacpan or search on metacpan
examples/which_cluster_for_new_data.pl view on Meta::CPAN
K => 3,
cluster_seeding => 'random', # also try 'smart'
use_mahalanobis_metric => 1, # also try '0'
terminal_output => 1,
write_clusters_to_files => 1,
debug => 0,
);
$clusterer->read_data_from_file();
my ($clusters_hash, $cluster_centers_hash) = $clusterer->kmeans();
Algorithm-KNN-XS
view release on metacpan or search on metacpan
lib/Algorithm/KNN/XS.pm view on Meta::CPAN
=over 4
=item * $knn->Print( ... )
Prints the current tree. Normally useful for debugging.
my $output = $knn->Print(
points => 1,
);
Algorithm-LBFGS
view release on metacpan or search on metacpan
Algorithm-LBFGS.xs view on Meta::CPAN
#include "ppport.h"
#include "lbfgs.h"
/* Macros for debugging */
/* uncomment the line below to enable tracing and timing */
/* #define __ENABLE_TRACING__ */
#ifdef __ENABLE_TRACING__
Algorithm-Line-Lerp
view release on metacpan or search on metacpan
DEBUG_SBOX32_HASH|5.027001||Viu
DEBUG_SCOPE|5.008001||Viu
DEBUG_s_FLAG|5.007001||Viu
DEBUG_S_FLAG|5.017002||Viu
DEBUG_STACK_r|5.009005||Viu
debug_start_match|5.009004||Viu
DEBUG_STATE_r|5.009004||Viu
DEBUG_s_TEST|5.007001||Viu
DEBUG_S_TEST|5.017002||Viu
DEBUG_t|5.003007||Viu
DEBUG_T|5.007001||Viu
get_cv|5.006000|5.003007|p
get_cvn_flags|5.009005|5.003007|p
get_cvs|5.011000|5.003007|p
getcwd_sv|5.007002|5.007002|
get_db_sub|||iu
get_debug_opts|5.008001||Viu
get_deprecated_property_msg|5.031011||cVniu
getegid|5.005000||Viu
getenv|5.005000||Viu
getenv_len|5.006000||Viu
GETENV_LOCK|5.033005||Viu
ingroup|5.003007||Viu
INIT|5.003007||Viu
init_argv_symbols|5.007003||Viu
init_constants|5.017003||Viu
init_dbargs|||iu
init_debugger|5.005000||Viu
init_i18nl10n|5.006000||cVu
init_i18nl14n|5.006000||dcVu
initialize_invlist_guts|5.029002||Viu
init_ids|5.005000||Viu
init_interp|5.005000||Viu
magic_freemglob|5.033004||Viu
magic_freeovrld|5.007001||Viu
magic_freeutf8|5.033004||Viu
magic_get|5.003007||Viu
magic_getarylen|5.003007||Viu
magic_getdebugvar|5.021005||Viu
magic_getdefelem|5.004000||Viu
magic_getnkeys|5.004005||Viu
magic_getpack|5.003007||Viu
magic_getpos|5.003007||Viu
magic_getsig|5.003007||Viu
magic_set|5.003007||Viu
magic_set_all_env|5.004004||Viu
magic_setarylen|5.003007||Viu
magic_setcollxfrm|5.004000||Viu
magic_setdbline|5.003007||Viu
magic_setdebugvar|5.021005||Viu
magic_setdefelem|5.004000||Viu
magic_setenv|5.003007||Viu
magic_sethint|5.009004||Vi
magic_sethint_feature|5.031007||Viu
magic_setisa|5.003007||Viu
PERL_deBruijnMagic32|5.035003||Viu
PERL_deBruijnMagic64|5.035003||Viu
PERL_deBruijnShift32|5.035003||Viu
PERL_deBruijnShift64|5.035003||Viu
PERL_DEBUG|5.008001||Viu
Perl_debug_log|5.003007||Viu
PERL_DEBUG_PAD|5.007003||Viu
PERL_DEBUG_PAD_ZERO|5.007003||Viu
PERL_DECIMAL_VERSION|5.019008||Viu
PERL_DEFAULT_DO_EXEC3_IMPLEMENTATION|5.009003||Viu
perl_destruct|5.007003|5.007003|n
PERLIOBUF_DEFAULT_BUFSIZ|5.013007||Viu
PerlIO_canset_cnt|5.003007|5.003007|n
PerlIO_clearerr|5.007003|5.007003|
PerlIO_close|5.007003|5.007003|
PerlIO_context_layers|||u
PerlIO_debug|5.007001|5.007001|
PERLIO_DUP_CLONE|5.007003||Viu
PERLIO_DUP_FD|5.007003||Viu
PerlIO_eof|5.007003|5.007003|
PerlIO_error|5.007003|5.007003|
PerlIO_exportFILE|5.003007|5.003007|n
PERL_MAGIC_bm|5.007002|5.003007|p
PERL_MAGIC_checkcall|5.013006|5.013006|
PERL_MAGIC_collxfrm|5.007002|5.003007|p
PERL_MAGIC_dbfile|5.007002|5.003007|p
PERL_MAGIC_dbline|5.007002|5.003007|p
PERL_MAGIC_debugvar|5.021005|5.021005|
PERL_MAGIC_defelem|5.007002|5.003007|p
PERL_MAGIC_env|5.007002|5.003007|p
PERL_MAGIC_envelem|5.007002|5.003007|p
PERL_MAGIC_ext|5.007002|5.003007|p
PERL_MAGIC_fm|5.007002|5.003007|p
PL_DBsingle_iv|5.021005||Viu
PL_DBsub|5.005000||pV
PL_DBtrace|5.005000||pV
PL_DBtrace_iv|5.021005||Viu
PL_debstash|5.005000|5.003007|poVnu
PL_debug|5.005000||Viu
PL_debug_pad|5.007003||Viu
PL_defgv|5.004005|5.003007|p
PL_def_layerlist|5.007003||Viu
PL_defoutgv|5.005000||Viu
PL_defstash|5.005000||Viu
PL_delaymagic|5.005000||Viu
PL_maxsysfd|5.005000|5.005000|
PL_mbrlen_ps|5.031010||Viu
PL_mbrtowc_ps|5.031010||Viu
PL_Mem|5.006000||Viu
PL_mem_log|5.033005||Viu
PL_memory_debug_header|5.009004||Viu
PL_MemParse|5.006000||Viu
PL_MemShared|5.006000||Viu
PL_mess_sv|5.005000|5.004000|poVnu
PL_min_intro_pending|5.005000||Viu
PL_minus_a|5.005000||Viu
PL_vtbl_backref|5.015000||Viu
PL_vtbl_bm|5.015000||Viu
PL_vtbl_checkcall|5.017000||Viu
PL_vtbl_collxfrm|5.015000||Viu
PL_vtbl_dbline|5.015000||Viu
PL_vtbl_debugvar|5.021005||Viu
PL_vtbl_defelem|5.015000||Viu
PL_vtbl_env|5.015000||Viu
PL_vtbl_envelem|5.015000||Viu
PL_vtbl_fm|5.015000||Viu
PL_vtbl_hints|5.015000||Viu
reg_named_buff_nextkey|5.009005||cVu
reg_named_buff_scalar|5.009005||cVu
regnext|5.003007||cVu
reg_node|5.005000||Viu
regnode_guts|5.021005||Viu
regnode_guts_debug|||Viu
REGNODE_MAX|5.009004||Viu
REGNODE_SIMPLE|5.013002||Viu
REGNODE_VARIES|5.013002||Viu
reg_numbered_buff_fetch|5.009005||cViu
reg_numbered_buff_length|5.009005||cViu
RsPARA|5.003007||Viu
RsRECORD|5.005000||Viu
RsSIMPLE|5.003007||Viu
RsSNARF|5.003007||Viu
run_body|5.006000||Viu
runops_debug|5.005000||cVu
RUNOPS_DEFAULT|5.005000||Viu
runops_standard|5.005000||cVu
run_user_filter|5.009003||Viu
rv2cv_op_cv|5.013006|5.013006|
RV2CVOPCV_FLAG_MASK|5.021004||Viu
SETHOSTENT_R_PROTO|5.008000|5.008000|Vn
SETi|5.003007||Viu
setjmp|5.005000||Viu
setlinebuf|5.005000||Viu
setlocale|5.009000||Viu
setlocale_debug_string|5.027002||Vniu
SETLOCALE_LOCK|5.033005||Viu
SETLOCALE_R_PROTO|5.008000|5.008000|Vn
SETLOCALE_UNLOCK|5.033005||Viu
SET_MARK_OFFSET|5.006000||Viu
setmode|5.005000||Viu
unreferenced_to_tmp_stack|5.013002||Viu
unshare_hek|5.004000||Viu
unshare_hek_or_pvn|5.008000||Viu
unsharepvn|5.003007|5.003007|u
unwind_handler_stack|5.009003||Viu
update_debugger_info|5.009005||Viu
upg_version|5.009005|5.009005|
UPG_VERSION|5.019008||Viu
uproot_SV|||Viu
Uquad_t|5.006000|5.006000|Vn
U_S|5.003007||Viu
Algorithm-LineSegments
view release on metacpan or search on metacpan
0.03 March 2013
- Floating point number serialisation apparently differs among
platforms, making a test fail; attempt to address that.
0.02 March 2014
- Removed accidental debug print
0.01 March 2014
- Initial release
Algorithm-LinearManifoldDataClusterer
view release on metacpan or search on metacpan
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
_delta_normalized_error => undef,
_cluster_search_multiplier => $args{cluster_search_multiplier} || 1,
_visualize_each_iteration => $args{visualize_each_iteration} == 0 ? 0 : 1,
_show_hidden_in_3D_plots => $args{show_hidden_in_3D_plots} == 0 ? 0 : 1,
_make_png_for_each_iteration => $args{make_png_for_each_iteration} == 0 ? 0 : 1,
_debug => $args{debug} || 0,
_N => 0,
_KM => $args{K} * $args{cluster_search_multiplier},
_data_hash => {},
_data_tags => [],
_data_dimensions => 0,
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my @cluster_center = @{$self->add_point_coords($tag_set)};
@cluster_center = map {my $x = $_/$cluster_size; $x} @cluster_center;
# for covariance calculation:
my ($num_rows,$num_cols) = ($self->{_data_dimensions}, scalar(@$tag_set));
print "\nThe data will be stuffed into a matrix of $num_rows rows and $num_cols columns\n\n"
if $self->{_debug};
my $matrix = Math::GSL::Matrix->new($num_rows,$num_cols);
my $mean_vec = Math::GSL::Matrix->new($num_rows,1);
# All the record labels are stored in the array $self->{_data_tags}. The actual
# data for clustering is stored in a hash at $self->{_data_hash} whose keys are
# the record labels; the value associated with each key is the array holding the
# corresponding numerical multidimensional data.
$mean_vec->set_col(0, \@cluster_center);
if ($self->{_debug}) {
print "\nDisplaying the mean vector for the cluster:\n";
display_matrix( $mean_vec ) if $self->{_terminal_output};
}
foreach my $j (0..$num_cols-1) {
my $tag = $tag_set->[$j];
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
$matrix->set_col($j, \@diff_from_mean);
}
my $transposed = transpose( $matrix );
my $covariance = $matrix * $transposed;
$covariance *= 1.0 / $num_cols;
if ($self->{_debug}) {
print "\nDisplaying the Covariance Matrix for cluster:";
display_matrix( $covariance ) if $self->{_terminal_output};
}
return ($mean_vec, $covariance);
}
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my $covariance = shift;
my ($eigenvalues, $eigenvectors) = $covariance->eigenpair;
my $num_of_eigens = @$eigenvalues;
my $largest_eigen_index = 0;
my $smallest_eigen_index = 0;
print "Eigenvalue 0: $eigenvalues->[0]\n" if $self->{_debug};
foreach my $i (1..$num_of_eigens-1) {
$largest_eigen_index = $i if $eigenvalues->[$i] > $eigenvalues->[$largest_eigen_index];
$smallest_eigen_index = $i if $eigenvalues->[$i] < $eigenvalues->[$smallest_eigen_index];
print "Eigenvalue $i: $eigenvalues->[$i]\n" if $self->{_debug};
}
print "\nlargest eigen index: $largest_eigen_index\n" if $self->{_debug};
print "\nsmallest eigen index: $smallest_eigen_index\n\n" if $self->{_debug};
my @all_my_eigenvecs;
foreach my $i (0..$num_of_eigens-1) {
my @vec = $eigenvectors->[$i]->as_list;
my @eigenvec;
foreach my $ele (@vec) {
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
} else {
die "Eigendecomposition produced a complex eigenvector -- " .
"which should not happen for a covariance matrix!";
}
}
print "Eigenvector $i: @eigenvec\n" if $self->{_debug};
push @all_my_eigenvecs, \@eigenvec;
}
my @largest_eigen_vec = $eigenvectors->[$largest_eigen_index]->as_list;
print "\nLargest eigenvector: @largest_eigen_vec\n" if $self->{_debug};
my @sorted_eigenvec_indexes = sort {$eigenvalues->[$b] <=> $eigenvalues->[$a]} 0..@all_my_eigenvecs-1;
my @sorted_eigenvecs;
my @sorted_eigenvals;
foreach my $i (0..@sorted_eigenvec_indexes-1) {
$sorted_eigenvecs[$i] = $all_my_eigenvecs[$sorted_eigenvec_indexes[$i]];
$sorted_eigenvals[$i] = $eigenvalues->[$sorted_eigenvec_indexes[$i]];
}
if ($self->{_debug}) {
print "\nHere come sorted eigenvectors --- from the largest to the smallest:\n";
foreach my $i (0..@sorted_eigenvecs-1) {
print "eigenvec: @{$sorted_eigenvecs[$i]} eigenvalue: $sorted_eigenvals[$i]\n";
}
}
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my $KM = $self->{_KM};
my @initial_cluster_center_tags;
my $visualization_msg;
my @initial_cluster_center_indexes = $self->initialize_cluster_centers($KM, $self->{_N});
print "Randomly selected indexes for cluster center tags: @initial_cluster_center_indexes\n"
if $self->{_debug};
@initial_cluster_center_tags = map {$self->{_data_tags}->[$_]} @initial_cluster_center_indexes;
my @initial_cluster_center_coords = map {$self->{_data_hash}->{$_}} @initial_cluster_center_tags;
if ($self->{_debug}) {
foreach my $centroid (@initial_cluster_center_coords) {
print "Initial cluster center coords: @{$centroid}\n";
}
}
my $initial_clusters = $self->assign_data_to_clusters_initial(\@initial_cluster_center_coords);
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
$self->visualize_clusters_on_sphere($visualization_msg, $initial_clusters, "png")
if $self->{_make_png_for_each_iteration};
}
foreach my $cluster (@$initial_clusters) {
my ($mean, $covariance) = $self->estimate_mean_and_covariance($cluster);
display_mean_and_covariance($mean, $covariance) if $self->{_debug};
}
my @clusters = @$initial_clusters;
display_clusters(\@clusters) if $self->{_debug};
my $iteration_index = 0;
my $unimodal_correction_flag;
my $previous_min_value_for_unimodality_quotient;
while ($iteration_index < $self->{_max_iterations}) {
print "\n\n========================== STARTING ITERATION $iteration_index =====================\n\n"
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my @trailing_eigenvec_matrices_for_all_subspaces;
my @reference_vecs_for_all_subspaces;
foreach my $cluster (@clusters) {
next if @$cluster == 0;
my ($mean, $covariance) = $self->estimate_mean_and_covariance($cluster);
display_mean_and_covariance($mean, $covariance) if $self->{_debug};
print "--------------end of displaying mean and covariance\n\n" if $self->{_debug};
my ($eigenvecs, $eigenvals) = $self->eigen_analysis_of_covariance($covariance);
my @trailing_eigenvecs = @{$eigenvecs}[$self->{_P} .. $self->{_data_dimensions}-1];
my @trailing_eigenvals = @{$eigenvals}[$self->{_P} .. $self->{_data_dimensions}-1];
my $subspace_construction_error = reduce {abs($a) + abs($b)} @trailing_eigenvals;
push @subspace_construction_errors_this_iteration, $subspace_construction_error;
my $trailing_eigenvec_matrix = Math::GSL::Matrix->new($self->{_data_dimensions},
scalar(@trailing_eigenvecs));
foreach my $j (0..@trailing_eigenvecs-1) {
print "trailing eigenvec column: @{$trailing_eigenvecs[$j]}\n" if $self->{_debug};
$trailing_eigenvec_matrix->set_col($j, $trailing_eigenvecs[$j]);
}
push @trailing_eigenvec_matrices_for_all_subspaces,$trailing_eigenvec_matrix;
push @reference_vecs_for_all_subspaces, $mean;
}
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
push @{$best_subspace_based_partition_of_data{$index_for_closest_subspace}},
$data_tag;
}
print "empty-cluster jag: total reconstruction error in this iteration: \n" .
"$total_reconstruction_error_this_iteration\n"
if $self->{_debug};
foreach my $i (0..$self->{_KM}-1) {
$clusters[$i] = $best_subspace_based_partition_of_data{$i};
}
display_clusters(\@newclusters) if $self->{_terminal_output};
@clusters = grep {@$_ != 0} @newclusters;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my @new_final_clusters;
map { foreach my $ele (keys %{$self->{_data_tags_to_cluster_label_hash}}) {
push @{$new_final_clusters[$_]}, $ele
if $self->{_data_tags_to_cluster_label_hash}->{$ele} == $_ }
} 0..$self->{_K}-1;
if ($self->{_debug}) {
print "\ndisplaying the final clusters after accounting for unclustered data:\n";
display_clusters(\@new_final_clusters);
}
$self->{_final_clusters} = \@new_final_clusters;
@final_clusters = @new_final_clusters;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my $subspace_construction_error = reduce {abs($a) + abs($b)} @trailing_eigenvals;
push @subspace_construction_errors, $subspace_construction_error;
my $trailing_eigenvec_matrix = Math::GSL::Matrix->new($self->{_data_dimensions},
scalar(@trailing_eigenvecs));
foreach my $j (0..@trailing_eigenvecs-1) {
print "trailing eigenvec column: @{$trailing_eigenvecs[$j]}\n" if $self->{_debug};
$trailing_eigenvec_matrix->set_col($j, $trailing_eigenvecs[$j]);
}
push @trailing_eigenvec_matrices_for_all_subspaces,$trailing_eigenvec_matrix;
push @reference_vecs_for_all_subspaces, $mean;
}
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my $new_mean_dist_val = exp( -1.0 * $mean_dist_val / $dist_bet_means_based_normalizer );
$W_dist_between_means_based->set_elem($i,$j,$new_mean_dist_val);
}
}
$W = $W_reconstruction_error_based + $W_dist_between_means_based;
if ($self->{_debug}) {
print "\nDisplaying the similarity matrix W for the cluster graph:\n";
display_matrix($W) if $self->{_terminal_output};
}
my $add_all_columns = Math::GSL::Matrix->new($num_nodes,1);
foreach my $col (0..$num_nodes-1) {
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
}
my ($eigenvalues, $eigenvectors) = $A->eigenpair;
my $num_of_eigens = @$eigenvalues;
my $largest_eigen_index = 0;
my $smallest_eigen_index = 0;
if ($self->{_debug2}) {
print "Eigenvalue 0: $eigenvalues->[0]\n";
foreach my $i (1..$num_of_eigens-1) {
$largest_eigen_index = $i if $eigenvalues->[$i] > $eigenvalues->[$largest_eigen_index];
$smallest_eigen_index = $i if $eigenvalues->[$i] < $eigenvalues->[$smallest_eigen_index];
print "Eigenvalue $i: $eigenvalues->[$i]\n";
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
push @eigenvec, -1.0 * $mag;
} else {
die "Eigendecomposition produced a complex eigenvector!";
}
}
print "Eigenvector $i: @eigenvec\n" if $self->{_debug2};
push @all_my_eigenvecs, \@eigenvec;
}
if ($self->{_debug2}) {
my @largest_eigen_vec = $eigenvectors->[$largest_eigen_index]->as_list;
print "\nLargest eigenvector of A: @largest_eigen_vec\n";
}
my @sorted_eigenvec_indexes = sort {$eigenvalues->[$b] <=> $eigenvalues->[$a]} 0..@all_my_eigenvecs-1;
print "sorted eigenvec indexes for A: @sorted_eigenvec_indexes\n" if $self->{_debug2};
my @sorted_eigenvecs;
my @sorted_eigenvals;
foreach my $i (0..@sorted_eigenvec_indexes-1) {
$sorted_eigenvecs[$i] = $all_my_eigenvecs[$sorted_eigenvec_indexes[$i]];
$sorted_eigenvals[$i] = $eigenvalues->[$sorted_eigenvec_indexes[$i]];
}
if ($self->{_debug2}) {
print "\nHere come sorted eigenvectors for A --- from the largest to the smallest:\n";
foreach my $i (0..@sorted_eigenvecs-1) {
print "eigenvec: @{$sorted_eigenvecs[$i]} eigenvalue: $sorted_eigenvals[$i]\n";
}
}
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
foreach my $dimen (0..$self->{_data_dimensions}-1) {
push @coordinate_vec, $min_bounds[$dimen] + rand($ranges[$dimen]);
}
push @random_points, \@coordinate_vec;
}
if ($self->{_debug}) {
print "\nrandom points\n";
map {print "@$_\n"} @random_points;
}
my @mean = $mean->as_list;
unshift @random_points, \@mean;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
max_iterations
delta_reconstruction_error
visualize_each_iteration
show_hidden_in_3D_plots
make_png_for_each_iteration
debug
/;
my $found_match_flag;
foreach my $param (@params) {
foreach my $legal (@legal_params) {
$found_match_flag = 0;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
_total_number_of_samples_needed => $args{total_number_of_samples_needed}
|| croak("total_number_of_samples_needed required"),
_number_of_clusters_on_sphere => $args{number_of_clusters_on_sphere} || 3,
_cluster_width => $args{cluster_width} || 0.1,
_show_hidden_in_3D_plots => $args{show_hidden_in_3D_plots} || 1,
_debug => $args{debug} || 0,
}, $class;
}
sub _check_for_illegal_params3 {
my @params = @_;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
$cluster_covariance->[$j]->[$k] = 0.0 if $j != $k;
}
}
push @covariances, $cluster_covariance;
}
if ($self->{_debug}) {
foreach my $i (0..$K-1) {
print "\n\nCluster center: @{$cluster_centers[$i]}\n";
print "\nCovariance:\n";
foreach my $j (0..1) {
foreach my $k (0..1) {
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
my @data_dump;
foreach my $i (0..$K-1) {
my @m = @{shift @cluster_centers};
my @covar = @{shift @covariances};
my @new_data = Math::Random::random_multivariate_normal($N, @m, @covar);
if ($self->{_debug}) {
print "\nThe points for cluster $i:\n";
map { print "@$_ "; } @new_data;
print "\n\n";
}
my @wrapped_data;
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
}
$wrapped_d->[0] = $d->[0] unless defined $wrapped_d->[0];
$wrapped_d->[1] = $d->[1] unless defined $wrapped_d->[1];
push @wrapped_data, $wrapped_d;
}
if ($self->{_debug}) {
print "\nThe unwrapped points for cluster $i:\n";
map { print "@$_ "; } @wrapped_data;
print "\n\n";
}
my $label = $point_labels[$i];
my $j = 0;
@new_data = map {unshift @$_, $label."_".$j; $j++; $_} @wrapped_data;
push @data_dump, @new_data;
}
if ($self->{_debug}) {
print "\n\nThe labeled points for clusters:\n";
map { print "@$_\n"; } @data_dump;
}
fisher_yates_shuffle( \@data_dump );
open OUTPUT, ">$output_file";
my $total_num_of_points = $N * $K;
print "Total number of data points that will be written out to the file: $total_num_of_points\n"
if $self->{_debug};
foreach my $ele (@data_dump) {
my ($x,$y,$z);
my $label = $ele->[0];
my $azimuth = $ele->[1];
my $elevation = $ele->[2];
lib/Algorithm/LinearManifoldDataClusterer.pm view on Meta::CPAN
$z = sin($elevation);
my $csv_str = join ",", ($label,$x,$y,$z);
print OUTPUT "$csv_str\n";
}
print "\n\n";
print "Data written out to file $output_file\n" if $self->{_debug};
close OUTPUT;
}
# This version for the embedded class for data generation
sub visualize_data_on_sphere {
Algorithm-MasterMind
view release on metacpan or search on metacpan
lib/Algorithm/MasterMind/Evo.pm view on Meta::CPAN
$p->{'_partitions'} = scalar (keys %{$partitions->{$c}});
}
}
if ($generations_equal == MAX_GENERATIONS_RESET ) { #reset pop
# Print for debugging
my %population;
for my $p ( @$pop ) {
$population{$p->{'_str'}}++;
}
for my $s ( sort { $population{$b} <=> $population{$a} } keys %population ) {
Algorithm-MedianSelect-XS
view release on metacpan or search on metacpan
debop||5.005000|
debprofdump||5.005000|
debprof|||
debstackptrs||5.007003|
debstack||5.007003|
debug_start_match|||
deb||5.007003|v
del_sv|||
delete_eval_scope|||
delimcpy||5.004000|
deprecate_old|||
get_av|5.006000||p
get_context||5.006000|n
get_cvn_flags||5.009005|
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_mstats|||
get_no_modify|||
get_num|||
incline|||
incpush_if_exists|||
incpush|||
ingroup|||
init_argv_symbols|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
run_user_filter|||
runops_debug||5.005000|
runops_standard||5.005000|
rvpv_dup|||
rxres_free|||
rxres_restore|||
rxres_save|||
unpackstring||5.008001|
unshare_hek_or_pvn|||
unshare_hek|||
unsharepvn||5.004000|
unwind_handler_stack|||
update_debugger_info|||
upg_version||5.009005|
usage|||
utf16_to_utf8_reversed||5.006001|
utf16_to_utf8||5.006001|
utf8_distance||5.006000|
Algorithm-MinPerfHashTwoLevel
view release on metacpan or search on metacpan
lib/Algorithm/MinPerfHashTwoLevel.pm view on Meta::CPAN
if ($source_hash) {
$self->{source_hash}= $source_hash;
} else {
$source_hash= $self->{source_hash};
}
my $debug= $self->{debug} ||= 0;
# reuse the constructor seed.
$self->_seed($self->{constructor_seed});
# find the number of keys we have to deal with
lib/Algorithm/MinPerfHashTwoLevel.pm view on Meta::CPAN
$counter,
$max_tries,
0+keys(%$source_hash),
unpack("H*",$seed),
unpack("H*",$state),
if $debug;
my $bad_idx= compute_xs($self)
or return $self->{buckets};
push @failed_seeds, $seed;
lib/Algorithm/MinPerfHashTwoLevel.pm view on Meta::CPAN
=item new
Construct a new Algorithm::MinPerfHashTwoLevel object. Optional arguments
which may be provided are 'source_hash' which is a hash reference to use
as the source for the minimal perfect hash, 'seed' which is expected to be
a 16 byte string, and 'debug' which is expected to be 0 or 1, as well
as variant, which may be 5 (use version v0.14 for variants before 5).
The default is 5.
=item compute
Algorithm-Networksort
view release on metacpan or search on metacpan
- I really had an odd style for initializing variables from @_
back in 2003. Made it less odd.
- Small inefficiency with the column count in nw_text_graph() fixed.
1.21
Sun Sep 24 2012
- Added color debugging code in eg/svg.pl (it lists the
color settings in XML comments).
- Updated eg/text.pl to take command line options.
- Moved graph and text option handling to their own functions,
graph_segment() and text_segment(), for future non-messy coding.
Fri Sep 22 2012
- Modernized parts of the code -- $VERSION is now an 'our'
variable instead of a 'use VARS' variable, for example.
- Added 'create_license => 1' to the Build.PL list of attributes.
- Added 'dynamic_config => 0' to the Build.PL list of attributes.
- Added LICENSE to the MANIFEST file.
- Yanked an "$flag_internal" variable (and its debugging code)
in favor of Smart::Comments.
- Bumped the $VERSION value up a point.
1.20
Sun May 20 2012
- Really bad bug introduced in version 1.08 (text graph
Algorithm-PageRank-XS
view release on metacpan or search on metacpan
debop||5.005000|
debprofdump||5.005000|
debprof|||
debstackptrs||5.007003|
debstack||5.007003|
debug_start_match|||
deb||5.007003|v
del_sv|||
delete_eval_scope|||
delimcpy||5.004000|
deprecate_old|||
get_av|5.006000||p
get_context||5.006000|n
get_cvn_flags||5.009005|
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_mstats|||
get_no_modify|||
get_num|||
incline|||
incpush_if_exists|||
incpush|||
ingroup|||
init_argv_symbols|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
run_user_filter|||
runops_debug||5.005000|
runops_standard||5.005000|
rvpv_dup|||
rxres_free|||
rxres_restore|||
rxres_save|||
unpackstring||5.008001|
unshare_hek_or_pvn|||
unshare_hek|||
unsharepvn||5.004000|
unwind_handler_stack|||
update_debugger_info|||
upg_version||5.009005|
usage|||
utf16_to_utf8_reversed||5.006001|
utf16_to_utf8||5.006001|
utf8_distance||5.006000|
Algorithm-Pair-Best2
view release on metacpan or search on metacpan
lib/Algorithm/Pair/Best2.pm view on Meta::CPAN
join(', ', keys %args);
}
return bless($self, ref($proto) || $proto);
}
### my (%cache, %all, @head); # debug variables.
###
###
### sub dbg_hash {
### my ($self, $key, $val) = @_;
###
Algorithm-Permute
view release on metacpan or search on metacpan
_load_PL_utf8_foldclosures|||
_make_exactf_invlist|||
_new_invlist_C_array|||
_new_invlist|||
_pMY_CXT|5.007003||p
_setlocale_debug_string|||n
_setup_canned_invlist|||
_swash_inversion_hash|||
_swash_to_invlist|||
_to_fold_latin1|||
_to_uni_fold_flags||5.014000|
debop||5.005000|
debprofdump||5.005000|
debprof|||
debstackptrs||5.007003|
debstack||5.007003|
debug_start_match|||
deb||5.007003|v
defelem_target|||
del_sv|||
delete_eval_scope|||
delimcpy||5.004000|n
get_context||5.006000|n
get_cvn_flags|||
get_cvs|5.011000||p
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_invlist_iter_addr|||n
get_invlist_offset_addr|||n
get_invlist_previous_index_addr|||n
incpush|||
ingroup|||
init_argv_symbols|||
init_constants|||
init_dbargs|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
magic_dump||5.006000|
magic_existspack|||
magic_freearylen_p|||
magic_freeovrld|||
magic_getarylen|||
magic_getdebugvar|||
magic_getdefelem|||
magic_getnkeys|||
magic_getpack|||
magic_getpos|||
magic_getsig|||
magic_scalarpack|||
magic_set_all_env|||
magic_setarylen|||
magic_setcollxfrm|||
magic_setdbline|||
magic_setdebugvar|||
magic_setdefelem|||
magic_setenv|||
magic_sethint|||
magic_setisa|||
magic_setlvref|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
run_user_filter|||
runops_debug||5.005000|
runops_standard||5.005000|
rv2cv_op_cv||5.013006|
rvpv_dup|||
rxres_free|||
rxres_restore|||
unreferenced_to_tmp_stack|||
unshare_hek_or_pvn|||
unshare_hek|||
unsharepvn||5.003070|
unwind_handler_stack|||
update_debugger_info|||
upg_version||5.009005|
usage|||
utf16_textfilter|||
utf16_to_utf8_reversed||5.006001|
utf16_to_utf8||5.006001|
Algorithm-QuadTree-XS
view release on metacpan or search on metacpan
0.04 Thu Nov 10 2022
- greatly improve search performance
0.03 Sun Jun 5 2022
- fix mark underflow problem on debugging perls
0.02 Tue May 31 2022
- fix compilation on threaded perls
0.01 Mon May 30 2022
Algorithm-QuineMcCluskey
view release on metacpan or search on metacpan
Revision history for Algorithm-QuineMcCluskey
1.01
2019-12-03
- Debug changes only, does not affect the operation of the
non-debug code:
Smart comments had some obsolete variables that are now
changed. The chart() function, used by Smart comments, made
use of firstidx(), which was provided by a module that is no
longer included. Changed the code in chart() to use the any()
- Check to see if the terms (minterms, maxterms, or
dont-cares) are larger than 'width' in bit size.
It's possible I made that mistake myself recently.
- And although it's not an error, run the terms through
sort and uniq before converting to bitstrings. It
makes visual inspection of the debug output easier.
0.09
2016-6-27
- Found a case where don't-care terms with no covers
were nonetheless included with the prime implicants.
Fixed by changing a map{}-everything-will-work into
a loop.
2015-1-16
- New function tableformat() (current name, at least) to show
primes hash in the table form used in textbook Quine-McCluskey
descriptions. Should help users understand what's going on,
and help in debugging too.
- New module to contain tableforms() (and future functions),
named it Algorithm::QuineMcCluskey::Format.
- Do-while using is_LequivalentR() was supposed to be comparing
hash keys, but a 'keys' had been left off on one side.
Fixing that saves at least one loop.
changing one of the outer loops in purge_essentials,
and remel() becomes remels()).
2014-11-13
- The test with don't-care terms randomly fails two thirds
of the time. Separate it into its own file, and add
debugging statements.
2014-11-4
- Extended the object test to consider minterms, maxterms,
and columnstrings methods of creation.
- deAlias considered finished and merged into the master
Algorithm-RandomPointGenerator
view release on metacpan or search on metacpan
lib/Algorithm/RandomPointGenerator.pm view on Meta::CPAN
bless {
_hist_file => $args{input_histogram_file} || croak("histogram file required"),
_bbox_file => $args{bounding_box_file} || croak("bounding box file required"),
_N => $args{number_of_points} || 2000,
_how_many_to_discard => $args{how_many_to_discard} || 500,
_debug => $args{debug} || 0,
_proposal_density_width => $args{proposal_density_width} || 0.1,
_y_axis_pos_direction => $args{y_axis_pos_direction} || "down",
_output_hist_bins_along_x => $args{output_hist_bins_along_x} || 40,
_command_line_mode => $args{command_line_mode} || 0,
_x_delta => undef,
lib/Algorithm/RandomPointGenerator.pm view on Meta::CPAN
my $sample = shift;
my $histref = $self->{_normalized_input_hist};
my $bbsize = $self->{_bounding_box};
my $horiz_delta = $self->{_x_delta};
my $vert_delta = $self->{_y_delta};
print "horiz_delta: $horiz_delta vert_delta: $vert_delta\n" if $self->{_debug};
return 0 if $sample->[0] < $bbsize->[0][0] || $sample->[0] > $bbsize->[0][1] ||
$sample->[1] < $bbsize->[1][0] || $sample->[1] > $bbsize->[1][1];
print "horizontal extent: $bbsize->[0][0] $bbsize->[0][1]\n" if $self->{_debug};
print "vertical extent: $bbsize->[1][0] $bbsize->[1][1]\n" if $self->{_debug};
my $bin_horiz = int( ($sample->[0] - $bbsize->[0][0]) / $horiz_delta );
my $bin_vert = int( ($sample->[1] - $bbsize->[1][0]) / $vert_delta );
print "bin 2D index: horiz: $bin_horiz vert: $bin_vert for sample value @$sample\n"
if $self->{_debug};
my $prob00 = $histref->[$bin_vert][$bin_horiz] || 0;
return $prob00 if (($bin_horiz + 1) >= @{$histref->[0]}) || (($bin_vert + 1) >= @{$histref});
my $prob01 = $histref->[$bin_vert + 1][$bin_horiz] || 0;
my $prob10 = $histref->[$bin_vert][$bin_horiz+ 1] || 0;
my $prob11 = $histref->[$bin_vert + 1][$bin_horiz + 1] || 0;
print "The four probs: $prob00 $prob01 $prob10 $prob11\n" if $self->{_debug};
my $horiz_fractional = (($sample->[0] - $bbsize->[0][0]) / $horiz_delta) - $bin_horiz;
my $vert_fractional = (($sample->[1] - $bbsize->[1][0]) / $vert_delta) - $bin_vert;
print "horiz frac: $horiz_fractional vert frac: $vert_fractional\n" if $self->{_debug};
my $interpolated_prob = $prob00 * (1 - $horiz_fractional) * (1 - $vert_fractional) +
$prob10 * $horiz_fractional * (1 - $vert_fractional) +
$prob01 * (1 - $horiz_fractional) * $vert_fractional +
$prob11 * $horiz_fractional * $vert_fractional;
print "Interpolated prob: $interpolated_prob\n" if $self->{_debug};
return $interpolated_prob;
}
sub proposal_density {
my $self = shift;
lib/Algorithm/RandomPointGenerator.pm view on Meta::CPAN
how_many_to_discard
proposal_density_width
y_axis_pos_direction
output_hist_bins_along_x
command_line_mode
debug
/;
my $found_match_flag;
foreach my $param (@params) {
foreach my $legal (@legal_params) {
$found_match_flag = 0;
lib/Algorithm/RandomPointGenerator.pm view on Meta::CPAN
=item B<display_output_histogram_in_terminal_window():>
$generator->display_output_histogram_in_terminal_window();
Useful for debugging purposes, it displays in the terminal window a two dimensional
array of numbers that is the histogram of the random points generated by the module.
=back
=head1 THE C<examples> DIRECTORY
Algorithm-RectanglesContainingDot_XS
view release on metacpan or search on metacpan
gen_constant_list|||
get_av|5.006000||p
get_context||5.006000|n
get_cv|5.006000||p
get_db_sub|||
get_debug_opts|||
get_hash_seed|||
get_hv|5.006000||p
get_mstats|||
get_no_modify|||
get_num|||
incline|||
incpush_if_exists|||
incpush|||
ingroup|||
init_argv_symbols|||
init_debugger|||
init_global_struct|||
init_i18nl10n||5.006000|
init_i18nl14n||5.006000|
init_ids|||
init_interp|||
rsignal_save|||
rsignal_state||5.004000|
rsignal||5.004000|
run_body|||
run_user_filter|||
runops_debug||5.005000|
runops_standard||5.005000|
rvpv_dup|||
rxres_free|||
rxres_restore|||
rxres_save|||
Algorithm-SVM
view release on metacpan or search on metacpan
* operating system type and version
* exact text of error message or description of problem
* example model files/data being classified
If we don't have access to a system similar to yours, you may be asked
to insert some debugging lines and report back on the results.
The more help and information you can provide, the better.
5) SVM COPYRIGHT AND LICENCE
----------------------------
( run in 1.262 second using v1.01-cache-2.11-cpan-49f99fa48dc )