view release on metacpan or  search on metacpan

ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

 view release on metacpan or  search on metacpan

ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

#
# pack_input_xs(data_sv, out_sv, n_pts, n_feats, miss_mode, fill_sv)
#     Walks the Perl arrayref-of-arrayrefs and writes a packed double buffer
#     into out_sv.  Replaces the dominant per-call Perl map-pack loop.
#     miss_mode selects how an undef cell is packed: 0 => 0.0, 1 => the
#     per-feature fill from fill_sv (impute), 2 => NaN (nan strategy).
#
# score_all_xs(nodes_av, idx_av, val_av, x_sv, sm_sv,
#              n_pts, n_feats, n_trees, use_openmp)
#     Sums path lengths for all n_pts query points across all n_trees trees
#     in one call.  Outer loop over points is OpenMP-parallel when the

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

 *
 * miss_mode selects what an undef cell (or missing row) becomes:
 *   0 => 0.0          (the 'die'/'zero' missing strategies)
 *   1 => fill[k]      (the 'impute' strategy; fill_sv is a packed
 *                      double buffer of n_feats per-feature fill values)
 *   2 => NaN          (the 'nan' strategy; the C scorer's `<` / `<=`
 *                      comparisons are both false for NaN, so a point
 *                      missing the split feature falls to the right
 *                      child -- matching how fit() routes it)
 * fill_sv is only dereferenced when miss_mode == 1. */
void pack_input_xs(SV* data_sv, SV* out_sv, int n_pts, int n_feats,
                   int miss_mode, SV* fill_sv){

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

 * _build_tree produces (leaf/axis/oblique -- see the file-top
 * comment), so every downstream consumer (_pack_tree, to_json,
 * from_json, the pure-Perl scorer) is unchanged.
 *
 * x_sv: packed row-major double buffer, n_pts rows of n_feats each
 *       (from pack_input_xs -- NaN marks a missing cell under the
 *       'nan' missing-strategy).
 * mode_flag: 0 => axis-parallel splits, 1 => oblique (extended).
 * ext_level: extension_level_used (ignored when mode_flag == 0).
 * out_rv: pre-existing arrayref; filled with n_trees tree roots.
 * ------------------------------------------------------------------ */

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

        lo[f] = HUGE_VAL;
        hi[f] = -HUGE_VAL;
    }
    for (int i = 0; i < size; i++) {
        const double* row = x + (size_t)idxs[i] * (size_t)nf;
        /* No isnan() guard needed: NaN < x and NaN > x are always false
         * under IEEE 754, so a NaN cell (the 'nan' missing strategy)
         * already leaves lo/hi untouched without an explicit check --
         * one less branch, and it's what lets this loop vectorize
         * cleanly as a plain elementwise min/max scan. */
        #ifdef _OPENMP
        #pragma omp simd

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

        hi[f] = -HUGE_VAL;
    }
    for (int i = 0; i < size; i++) {
        const double* row = x + (size_t)idxs[i] * (size_t)nf;
        /* See the matching comment in _build_node_c: no isnan() guard
         * needed, since NaN < x / NaN > x are always false already --
         * that's what lets this vectorize as a plain min/max scan.
         * omp simd here is thread-safe to call from inside the caller's
         * omp parallel region: it's a per-thread vectorization hint,
         * not a team construct, so it doesn't nest into anything. */
        #ifdef _OPENMP

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

		$split = _to_double( rand() * $split );
		$split = _to_double( $lo->[$attr] + $split );
	}

	# A point missing the split feature (nan mode only) routes to the right
	# child -- the same side NaN reaches in the C scorer, where (NaN < split)
	# is false.  Under die/zero/impute every cell is defined, so the
	# "defined($v)" guard is dead weight there and skipped entirely.
	my ( @left, @right );
	if ($nan) {
		for my $row (@$X) {

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

			$b = _to_double( $b + _to_double( $c * $p ) );
		}
	} ## end for my $f (@idx)

	# A point missing any feature on the hyperplane (nan mode only) routes
	# to the right child: in the C scorer the dot product becomes NaN and
	# (NaN <= b) is false, so this keeps fit and score consistent.  Under
	# die/zero/impute every cell is defined, so the per-feature "defined"
	# check and early-exit are dead weight there and skipped entirely.
	my ( @left, @right );
	if ($nan) {
		for my $row (@$X) {

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

# The type tag is also used as a loop sentinel: 0 (_NODE_LEAF) is falsy.
# No $self argument -- the node type encodes everything needed.
#-------------------------------------------------------------------------------
# The optional $nan flag selects the nan-strategy routing: a point missing
# the split feature goes to the right child (matching the C scorer, where
# the NaN comparison is false).  Without it, undef is coerced to 0 -- the
# behaviour the die/zero/impute strategies rely on (their data is dense by
# the time it reaches here, so the "// 0" is normally a no-op).
#
# Args:
#   $x :: one sample, an arrayref of feature values.  undef cells are

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

#   $data :: either an arrayref of feature-value arrayrefs (returned
#            unchanged, not copied) or a PackedData instance (unpacked into
#            fresh rows).
#
# Returns: an arrayref of feature-value arrayrefs.  Rows unpacked from
# PackedData hold plain doubles, so a NaN packed for a missing cell comes
# back as NaN rather than undef.  Croaks on anything else.
#
# Example:
#   my $rows = $self->_to_arrayref($data);
#   _path_length( $rows->[0], $tree, 0, 0 );
sub _to_arrayref {

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

#   zero   -- undef counts as the value 0, at fit and score time.
#   impute -- undef is replaced by a learned per-feature mean/median; the
#             fill vector is stored on the model and reused at score time.
#   nan    -- ranges are built over present values only and a point missing
#             the split feature is routed to the right child, consistently
#             at fit (Perl) and score (C packs NaN; `<`/`<=` send it right).
# ---------------------------------------------------------------------------

# Returns the training data to actually build trees on, after applying the
# missing-value strategy.
#

lib/Algorithm/Classifier/IsolationForest.pm  view on Meta::CPAN

	];
} ## end sub _densify

# (miss_mode, fill_packed) pair for pack_input_xs, per the active strategy.
# die/zero -> 0 (undef becomes 0.0); impute -> 1 (undef becomes fill[k]);
# nan -> 2 (undef becomes NaN, which the C scorer routes right).
#
# Args: none beyond the model itself.
#
# Returns: the two-element list ($miss_mode, $fill_packed) -- the mode flag
# above, and a 'd*' string of the per-feature fills under impute or the

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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html/jquery.couponcode.js  view on Meta::CPAN

    var self    = $.extend({}, $.fn.couponCode.defaults, options);
    self.focus  = null;
    self.inputs = [];
    self.flags  = [];
    self.parts  = parseInt(self.parts, 10);
    if(isNaN(self.parts) || self.parts < 1 || self.parts > 6) {
        alert("CouponCode 'parts' must be in range 1-6");
        return;
    }

    var start_val = $(base_entry).val();

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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XS.xs  view on Meta::CPAN

#else
/* compare left and right SVs. Returns:
 * -1: <
 *  0: ==
 *  1: >
 *  2: left or right was a NaN
 */
I32
my_Perl_do_ncmp(pTHX_ SV* const left, SV * const right)
{
    PERL_ARGS_ASSERT_DO_NCMP;
    /* Fortunately it seems NaN isn't IOK */
    if (SvIV_please_nomg(right) && SvIV_please_nomg(left)) {
            if (!SvIsUV(left)) {
                const IV leftiv = SvIVX(left);
                if (!SvIsUV(right)) {
                    /* ## IV <=> IV ## */

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else

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ppport.h  view on Meta::CPAN

      s++; if (s == send || (*s != 'Y' && *s != 'y')) return 0;
      s++;
    }
    sawinf = 1;
  } else if (*s == 'N' || *s == 'n') {
    /* XXX TODO: There are signaling NaNs and quiet NaNs. */
    s++; if (s == send || (*s != 'A' && *s != 'a')) return 0;
    s++; if (s == send || (*s != 'N' && *s != 'n')) return 0;
    s++;
    sawnan = 1;
  } else