view release on metacpan or  search on metacpan

lib/Audio/NoiseGen.pm  view on Meta::CPAN

  split
  sequence
  note
  rest
  segment
  formula
  hardlimit
  amp
  oneshot
  lowpass
  highpass

lib/Audio/NoiseGen.pm  view on Meta::CPAN

    $last_sample = $cur_gen->();
    return $last_sample || 0;
  }
}

=head2 formula( formula => sub { $_*(42&$_>>10) } )

Plays a formula. Takes 'formula', 'bits', and 'sample_rate'. 'bits' defaults to 8, 'sample_rate' defaults to 8000.

Formula uses C<< $_ >> instead of 't', but is otherwise similar to what is described at L<http://countercomplex.blogspot.com/2011/10/algorithmic-symphonies-from-one-line-of.html>.

=cut

sub formula {
  my %params = generalize(
    bits        => 8,
    sample_rate => 8000,
    @_
  );
  my $formula = $params{formula};
  my $formula_increment = $params{sample_rate}->() / $sample_rate;
  my $max = 2 ** $params{bits}->();
  my $t = 0;
  return sub {
    $t += $formula_increment;
    local $_ = int $t;
    return (((
      $formula->(int $t)
    ) % $max - ($max/2))/($max/2))
  }
}

 # Return RC low-pass filter output samples, given input samples,

lib/Audio/NoiseGen.pm  view on Meta::CPAN

  my $gen = shift;
  if(!ref $gen) {
    print STDERR "segement '$gen'\n";
    $gen = segment($gen);
  # } elsif(ref $gen eq 'CODE') {
    # $gen = formula($gen);
  }
  my $self = {
    gen => $gen,
  };
  bless $self, $class;

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mpg123/mpg123.c  view on Meta::CPAN

	    if(param.verbose)
		print_stat(rd,fr,frameNum,xfermem_get_usedspace(buffermem),&ai); 

	    if (!param.quiet) {
		/* 
		 * This formula seems to work at least for
		 * MPEG 1.0/2.0 layer 3 streams.
		 */
		int secs = get_songlen(rd,fr,frameNum);
		fprintf(stderr,"\n[%d:%02d] Decoding of %s finished.\n", secs / 60,
			secs % 60, filename);

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lib/Authen/PluggableCaptcha/Tutorial.pm  view on Meta::CPAN

For example:

  key= md5( $site_secret , $time , $page_name , $session_id ) + ':' + $session
  key= 'xxxxxxxxxxxxxxxxxx:10000001'

If we know the site_secret under that formula, we always have every components of the item at our disposal -- and can validate the key for integrity

The default KeyManager class uses a site_secret to create the key.

=head3 Also, from the example in the Tutorial, it isn't quite clear if you first have to generate a new CAPTCHA, just to get its key, and then use that key to construct an existing CAPTCHA to create the JPEG. This isn't the case, is it? I could call ...

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ramblings/remark.js  view on Meta::CPAN

require=function(e,t,n){function i(n,s){if(!t[n]){if(!e[n]){var o=typeof require=="function"&&require;if(!s&&o)return o(n,!0);if(r)return r(n,!0);throw new Error("Cannot find module '"+n+"'")}var u=t[n]={exports:{}};e[n][0].call(u.exports,function(t)...
this.QUOTE_STRING_MODE={className:"string",begin:'"',end:'"',illegal:"\\n",contains:[this.BACKSLASH_ESCAPE]};this.PHRASAL_WORDS_MODE={begin:/\b(a|an|the|are|I|I'm|isn't|don't|doesn't|won't|but|just|should|pretty|simply|enough|gonna|going|wtf|so|such)...
SUBST.contains=EXPRESSIONS;return{aliases:["coffee","cson","iced"],keywords:KEYWORDS,contains:EXPRESSIONS.concat([{className:"comment",begin:"###",end:"###"},hljs.HASH_COMMENT_MODE,{className:"function",begin:"("+JS_IDENT_RE+"\\s*=\\s*)?(\\(.*\\))?\\...
}()},{}],8:[function(require,module,exports){exports.addClass=function(element,className){element.className=exports.getClasses(element).concat([className]).join(" ")};exports.removeClass=function(element,className){element.className=exports.getClasse...
events.on("slideChanged",updateHash);navigateByHash()}function navigateByHash(){var slideNoOrName=(dom.getLocationHash()||"").substr(1);events.emit("gotoSlide",slideNoOrName)}function updateHash(slideNoOrName){dom.setLocationHash("#"+slideNoOrName)}}...

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zlib/adler32.c  view on Meta::CPAN

{
    unsigned long sum1;
    unsigned long sum2;
    unsigned rem;

    /* the derivation of this formula is left as an exercise for the reader */
    rem = (unsigned)(len2 % BASE);
    sum1 = adler1 & 0xffff;
    sum2 = rem * sum1;
    MOD(sum2);
    sum1 += (adler2 & 0xffff) + BASE - 1;

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lib/BalanceOfPower/Role/Shopper.pm  view on Meta::CPAN

    my $self = shift;
    my $y = shift;
    my $type = shift;
    my $nation = shift;

    #Price formula is MaxPrice - (( MaxPrice - MinPrice) / MaxValue) * Value
    #MaxPrice and MinPrice are constant

    my $min_price = PRICE_RANGES->{$type}->[0];
    my $max_price = PRICE_RANGES->{$type}->[1];

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lib/Baseball/Sabermetrics.pm  view on Meta::CPAN

  $league->define(
      rc => 'ab * obp',
      babip => '(h_allowed - hr_allowed) / (p_pa - h_allowed - p_so - p_bb - hr_allowed',
      # what started with '$' will be reserved.
      # Players have team and league predefined, and team has league.
      formula1 => 'hr / $_->team->hr';
      formula2 => 'hr / $_->league->hr';
      complex => sub {
	    print "You can write a sub directly\n";
	    $_->slg - $_->ba;
      },
      ...
  );

  # Some formulas can be applied to players, teams, and league, depend on what
  # columns are used in the formula.  For example, ab and obp are defined for
  # players, teams, and league, so that rc is available for all of them.

  # top 5 obp of teams
  $_->print qw/ team name ba obp slg isop / for $league->top('teams', 5, 'obp');

lib/Baseball/Sabermetrics.pm  view on Meta::CPAN

  $league->{Yankees}->report_pitchers qw/ name ip p_so p_bb whip go_ab /;
  $league->{Yankees}->report_batters  qw/ name ba obp slg isop /;

  $league->report_teams qw/ name win lose era obp /;

  # show all available formula
  print join ' ', $league->formula_list;

=head1 Data Structure

Baseball::Sabermetrics is aimed for providing a base class of your interested teams (a league, for example).  You'll need to provide a data retriever to pull data out.  The following example shows how you have to fill data into this structure.

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share/SpamAssassin/easy_ham/00271.b67b5b37ce874d5ccea3391922f14506  view on Meta::CPAN

to another. This is why, under international 
contracts, it is necessary to specify to which 
laws one is referring (French law, American &c.).

The authors only found three public licences 
which were correctly formulated on this point: 
QPL, IBM Public Licence and the Mozilla Public
Licence).

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lib/BigIP/iControl.pm  view on Meta::CPAN

=head3 get_pool_statistics_stringified ($pool)

	my %stats = $ic->get_pool_statistics_stringified($pool);
	print "Pool $pool bytes in: $stats{stat}{STATISTIC_SERVER_SIDE_BYTES_OUT}";

Returns a hash containing all pool statistics for the specified pool in a delicious, easily digestable and improved formula.

=cut

sub get_pool_statistics_stringified {
	my ($self, $pool)= @_;

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lib/Bio/DB/BigBed.pm  view on Meta::CPAN

In addition, the bin objects add the following convenience methods:

 $bin->count()    Same as $bin->score->{validCount}
 $bin->minVal()   Same as $bin->score->{minVal}
 $bin->maxVal()   Same as $bin->score->{maxVal}
 $bin->mean()     The mean of values in the bin (from the formula above)
 $bin->variance() The variance of values in the bin (ditto)
 $bin->stdev()    The standard deviation of values in the bin (ditto)

From these values one can determine the mean, variance and standard
deviation across one or more genomic intervals. The formulas are as
follows:

 sub mean {
    my ($sumData,$validCount) = @_;
    return $sumData/$validCount;

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lib/Bio/CUA/CUB/Calculator.pm  view on Meta::CPAN

{
	my ($self, $seq) = @_;
	$self->_xai($seq, 'CAI');
}

# the real calculator of tAI or CAI as both have the same formula
sub _xai
{
	my ($self, $seq, $type) = @_;

	my $name;

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lib/Bio/Cellucidate.pm  view on Meta::CPAN

A Model has one or many simulation runs and a simulation run belongs to
a model.

=item L<Bio::Cellucidate::OdeResult>

Represents the set of ODE formulas generated when running a simulation in ODE-mode.
The results can be used directly in MATLAB.

=item L<Bio::Cellucidate::Plot>

A plot contains a single time series and a number of data series representing the

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lib/Bio/GeneDesign.pm  view on Meta::CPAN

arguments; they are 50mm (.05) and 100 pm (.0000001) respectively.

You can pass either a string variable, a Bio::Seq object, or a Bio::SeqFeatureI
object to be analyzed with the -sequence flag.

There are four different formulae to choose from. If you wish to use the nearest
neighbor method, use the -nearest_neighbor flag. Otherwise the appropriate
formula will be determined by the length of your -sequence argument.

For sequences under 14 base pairs:
  Tm = (4 * #GC) + (2 * #AT).

For sequences between 14 and 50 base pairs:

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lib/Bio/Graphics/Panel.pm  view on Meta::CPAN

responsible for allocating sufficient -pad_left or -pad_right room for
the labels to appear.  The necessary width is the number of characters
in the longest key times the font width (gdMediumBoldFont by default)
plus 3 pixels of internal padding.  The simplest way to calculate this
is to iterate over the possible track labels, find the largest one,
and then to compute its width using the formula:

  $width = gdMediumBoldFont->width * length($longest_key) +3;

In order to obtain scalable vector graphics (SVG) output, you should
pass new() the -image_class=E<gt>'GD::SVG' parameter. This will cause

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scripts/Data/psi-mi.obo  view on Meta::CPAN

subset: Drugable
is_a: MI:0300 ! alias type

[Term]
id: MI:2008
name: chemical formula
def: "Chemical formula describing atomic or elemental composition" [PMID:14755292]
subset: Drugable
is_a: MI:2086 ! physicochemical attribute name

[Term]
id: MI:2009

scripts/Data/psi-mi.obo  view on Meta::CPAN

is_a: MI:0353 ! cross-reference type

[Term]
id: MI:2025
name: molecular weight
def: "Molecular weight in g/mol, determined from molecular formula or sequence." [PMID:14755292]
subset: Drugable
is_a: MI:0640 ! parameter type

[Term]
id: MI:2026

scripts/Data/psi-mi.obo  view on Meta::CPAN

is_a: MI:2054 ! bioactive entity reference

[Term]
id: MI:2155
name: average molecular weight
def: "Molecular weight in g/mol, determined from molecular formula or sequence." [PMID:14755292]
subset: Drugable
synonym: "avrg mol weight" EXACT PSI-MI-short []
is_a: MI:2025 ! molecular weight

[Term]
id: MI:2156
name: monoisotopic molecular weight
def: "Molecular weight in g/mol, determined from molecular formula or sequence." [PMID:14755292]
subset: Drugable
synonym: "monoisotopic mol wgt" EXACT PSI-MI-short []
is_a: MI:2025 ! molecular weight

[Term]

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lib/Bio/KBase/CDMI/CDMI_APIImpl.pm  view on Meta::CPAN

=item Description

Since we accumulate data relating to the co-occurrence (i.e., chromosomal
clustering) of genes in prokaryotic genomes,  we can note which pairs of genes tend to co-occur.
From this data, one can compute the protein families that tend to co-occur (i.e., tend to
cluster on the chromosome).  This allows one to formulate conjectures for unclustered pairs, based
on clustered pairs from the same protein_families.

=back

=cut

lib/Bio/KBase/CDMI/CDMI_APIImpl.pm  view on Meta::CPAN

=item Description

A substem is composed of two components: a set of roles that are gathered to be annotated
simultaneously and a spreadsheet depicting the proteins within each genome that implement
the roles.  The set of roles may correspond to a pathway, a complex, an inventory (say, "transporters")
or whatever other principle an annotator used to formulate the subsystem.

The subsystem spreadsheet is a list of "rows", each representing the subsytem in a specific genome.
Each row includes a variant code (indicating what version of the molecular machine exists in the
genome) and cells.  Each cell is a 2-tuple:

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t/cd_hit.t  view on Meta::CPAN

https://github.com/weizhongli/cdhit
If you --force installation, I will eventually try to install CD-HIT with brew:
https://brew.sh/
EOT
}
# TODO: fix this as CD-HIT formula currently fails on OS X Mojave
#       This can be done with a --build-from-source option of brew

# expected members for
my $exp_clstr_file = file('test', 'cdHit.out.groups');
open my $in, '<', $exp_clstr_file;

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lib/Bio/Phylo/EvolutionaryModels.pm  view on Meta::CPAN

    #Loop for sampling each tree
    while ( scalar @sample < $options{sample_size} ) {
        my @nodes;

       #Compute the random tree age from the inverse CDF (different formulas for
       #birth rate == death rate and otherwise)
        my $tree_age;

        #The uniform random variable
        my $r = rand;

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CHANGELOG.md  view on Meta::CPAN

## [v3.6.9](https://github.com/sanger-pathogens/Roary/tree/v3.6.9) (2016-09-22)
[Full Changelog](https://github.com/sanger-pathogens/Roary/compare/v3.6.8...v3.6.9)

**Implemented enhancements:**

- I have published a Roary homebrew formula [\#208](https://github.com/sanger-pathogens/Roary/issues/208)
- Getting Roary into Homebrew [\#152](https://github.com/sanger-pathogens/Roary/issues/152)

**Closed issues:**

- roary\_plots.py missing  [\#277](https://github.com/sanger-pathogens/Roary/issues/277)

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lib/Bio/Tools/CodonOptTable.pm  view on Meta::CPAN

    return 1;
}

#    Function : Calculate the RSCU(Relative Synonymous Codons Uses).
#    Note     : The formula is used in the following references.
#	 http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=3547335

sub _calculate_rscu {
    my $self = shift;

lib/Bio/Tools/CodonOptTable.pm  view on Meta::CPAN

    }
    return ( \@myCodons, \%rscu_max_table );
}

#    Function : Calculate the RAC (Relative Adaptiveness of a Codon).
#    Note     : The formula is used in the following references.
#	 http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=3547335

sub _calculate_rac {
    my ( $self, $codons, $max_rscu ) = @_;
    my ( $rac, @myCodons );

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DNAGen.pm  view on Meta::CPAN

Default is 'undef', which means gc-ratio is not related to sequence selection.

=head2 set_mt

Setting for the melting temperature. For now, Wallace formula is adopted for calculation.

You can give it a specific value, like

    $gen->set_mt(30);

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lib/Bio/Tools/ProteinogenicAA.pm  view on Meta::CPAN

		$info[7] eq 'X' ? $aa->is_hydrophobic(1) : $aa->is_hydrophobic(0);
		$info[8] eq 'X' ? $aa->is_polar(1) : $aa->is_polar(0);
		$aa->pH($info[9]);
		$aa->van_der_waals_volume($info[10]);
		$aa->codons($info[11]);
		$aa->formula($info[12]);
		$aa->monoisotopic_mass($info[13]);
		$aa->avg_mass($info[14]);
		
		push(@list, $aa);

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lib/Bio/ViennaNGS/Expression.pm  view on Meta::CPAN

  my ($self,$sample,$rl) = @_;
  my ($TPM,$T,$totalTPM) = (0)x3;
  my ($i,$meanTPM);

  # iterate through $self->data[$i] twice:
  # 1. for computing T (denominator in TPM formula)
  foreach $i (keys %{${$self->data}[$sample]}){
    my $count  = ${${$self->data}[$sample]}{$i}{count};
    my $length =  ${${$self->data}[$sample]}{$i}{length};
    #print "count: $count\nlength: $length\n";
    $T += $count * $rl / $length;

lib/Bio/ViennaNGS/Expression.pm  view on Meta::CPAN

  my ($self,$sample,$rl) = @_;
  my ($R,$T,$length,$count,$totalRPKM) = (0)x5;
  my ($i,$meanRPKM);

  # iterate through $self->data[$i] twice:
  # 1. compute T (denominator in TPM formula) and total number of reads
  foreach $i (keys %{${$self->data}[$sample]}){
    $count  = ${${$self->data}[$sample]}{$i}{count};
    $length =  ${${$self->data}[$sample]}{$i}{length};
    #print "count: $count\nlength: $length\n";
    $T += $count * $rl / $length;

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README  view on Meta::CPAN

     - round-tripping fuzzy locations (they will be stored according
	  to their Bio::Location::CoordinatePolicyI interpretation)
     - Bio::Annotation::DBLink::optional_id

To understand the layout of the API and how you can interact with the
adaptors to formulate your own queries, here is what you should know
and read (i.e., read the PODs of all interfaces and modules named
below).

1) Bio::DB::BioDB acts as a factory of database adaptors, where a
database adaptor encapsulates an entire database, not a specific

README  view on Meta::CPAN

4) A persistence adaptor will implement Bio::DB::PersistenceAdaptorI. 
Apart from actually implementing all the persistence methods for 
persistent objects, a persistence adaptor allows you to locate 
objects in the database by key and by query. You can
find_by_primary_key(), find_by_unique_key(), find_by_association(), 
and find_by_query(). The latter allows you to formulate object queries 
as Bio::DB::Query::BioQuery objects and retrieve the matching objects.

5) The guiding principle for the redesign of the adaptors was to
separate business logic from schema logic. While business logic is
largely driven by the object model (hence, by the bioperl object

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lib/Bio/Tools/Run/StandAloneBlast.pm  view on Meta::CPAN

Blastpgp (including Psiblast)

  -j  is the maximum number of rounds (default 1; i.e., regular BLAST)
  -h  is the e-value threshold for including sequences in the
	    score matrix model (default 0.001)
  -c  is the "constant" used in the pseudocount formula specified in the paper (default 10)
  -B  Multiple alignment file for PSI-BLAST "jump start mode"  Optional
  -Q  Output File for PSI-BLAST Matrix in ASCII [File Out]  Optional

rpsblast

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Bio/SeqFeature/Primer.pm  view on Meta::CPAN

         : -oligo : set the oligo concentration on which to base the
                    calculation (default=0.00000025 molar).
 Notes   : Calculation of Tm as per Allawi et. al Biochemistry 1997
           36:10581-10594. Also see documentation at
           http://www.idtdna.com/Scitools/Scitools.aspx as they use this
           formula and have a couple nice help pages. These Tm values will be
           about are about 0.5-3 degrees off from those of the idtdna web tool.
           I don't know why.

           This was suggested by Barry Moore (thanks!). See the discussion on
           the bioperl-l with the subject "Bio::SeqFeature::Primer Calculating

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Vector.pod  view on Meta::CPAN

and stores the result in "C<$set3>".

This can be written as "C<$set3 = ($set1 u $set2) \ ($set1 n $set2)>" in set
theory (the union of the two sets less their intersection).

When sets are implemented as bit vectors then the above formula is
equivalent to the exclusive-or between corresponding bits of the two
bit vectors (hence the name of this method).

Note that this method is also much more efficient than evaluating the
above formula explicitly since it uses a built-in machine language
instruction internally.

In-place calculation is also possible, i.e., "C<$set3>" may be identical
with "C<$set1>" or "C<$set2>" or both.

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src/boost/config/auto_link.hpp  view on Meta::CPAN

Algorithm:
~~~~~~~~~~

Libraries for Borland and Microsoft compilers are automatically
selected here, the name of the lib is selected according to the following
formula:

BOOST_LIB_PREFIX
   + BOOST_LIB_NAME
   + "_"
   + BOOST_LIB_TOOLSET

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include/boost/config/auto_link.hpp  view on Meta::CPAN

Algorithm:
~~~~~~~~~~

Libraries for Borland and Microsoft compilers are automatically
selected here, the name of the lib is selected according to the following
formula:

BOOST_LIB_PREFIX
   + BOOST_LIB_NAME
   + "_"
   + BOOST_LIB_TOOLSET