This file is indexed.

/usr/share/pyshared/gamera/plugins/structural.py is in python-gamera 3.3.2-2.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
#
# Copyright (C) 2001-2005 Ichiro Fujinaga, Michael Droettboom,
#                          and Karl MacMillan
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#

"""The relational module contains plugins for computing the relationships
between glyphs."""

from gamera.plugin import * 

class bounding_box_grouping_function(PluginFunction):
    """
    Given two rectangles *a*, *b*, and a given *threshold* distance
    (in pixels), returns ``True`` if the two rectangles are closer
    than *threshold*.
    """
    self_type = None
    args = Args([Rect("a"), Rect("b"), Int("threshold")])
    return_type = Check("connected")

class shaped_grouping_function(PluginFunction):
    """
    Given two connected components *a*, *b*, and a given *threshold*
    distance (in pixels), returns ``True`` if any pixel in *a* are
    closer than *threshold* to any pixel in *b*.
    """
    self_type = None
    args = Args([ImageType(ONEBIT, "a"), ImageType(ONEBIT, "b"), Int("threshold")])
    return_type = Check("connected")

class polar_distance(PluginFunction):
    """
    Returns a tuple containing the normalized distance, polar
    direction, and non-normalized polar distance to another glyph
    (based on center of bounding boxes).
    """
    self_type = ImageType(ALL)
    return_type = FloatVector("polar")
    args = Args([ImageType(ALL, "other")])

class polar_match(PluginFunction):
    self_type = None
    return_type = Int("check")
    args = Args([Float('r1'), Float('q1'), Float('r2'), Float('q2')])

class least_squares_fit(PluginFunction):
    """
    Performs a least squares fit on a given list of points.

    The result is a tuple of the form (*m*, *b*, *q*) where *m* is the
    slope of the line, *b* is the *y*-offset, and *q* is the gamma fit
    of the line to the points.  (This assumes the same statistical
    significance for all points.
    
    See Numerical Recipes in C, section 15.2__ for more information.

    .. __: http://www.library.cornell.edu/nr/bookcpdf/c15-2.pdf
    """
    self_type = None
    return_type = Class("a_b_q")
    args = Args([PointVector("points")])

class least_squares_fit_xy(PluginFunction):
    """
    Identical to *least_squares_fit* for line angles below 45 degrees.
    For lines with a more vertical slope a least square fit of *x = my
    + b* is done instead.

    The result is a tuple of the form (*m*, *b*, *q*, *x_of_y*) where
    *m, b, q* are the same as in *least_squares_fit*, but the integer
    value *x_of_y* determines the actual meaning of the parameters *m*
    and *b*:

    When *x_of_y* is zero, *y = mx + b*. Otherwise *x = my + b*.
    """
    self_type = None
    return_type = Class("a_b_q_xofy")
    args = Args([PointVector("points")])
    author = "Christoph Dalitz"

class edit_distance(PluginFunction):
    """
    Computes the edit distance (also known as *Levenshtein distance*) between
    two strings.

    This counts the number of character substitutions, additions and deletions
    necessary to transform one string into another. This plugin is a 
    straightforward implementation of the classic algorithm by Wagner 
    and Fischer, which has runtime complexity *O(m*n)*, where *m* and *n* are
    the lengths of the two strings.

    See R.A. Wagner, M.J. Fischer: *The String-to-String Correction Problem.*
    Journal of the ACM 21, pp. 168-173, 1974.
    """
    self_type = None
    args = Args([String("s1"), String("s2")])
    return_type = Int("distance")
    author = "Christoph Dalitz"

class RelationalModule(PluginModule):
    cpp_headers = ["structural.hpp"]
    category = "Relational"
    functions = [polar_distance, polar_match,
                 bounding_box_grouping_function,
                 shaped_grouping_function,
                 least_squares_fit, least_squares_fit_xy,
                 edit_distance]
    author = "Michael Droettboom and Karl MacMillan"
    url = "http://gamera.sourceforge.net/"

module = RelationalModule()

bounding_box_grouping_function = bounding_box_grouping_function()
shaped_grouping_function = shaped_grouping_function()
least_squares_fit = least_squares_fit()
least_squares_fit_xy = least_squares_fit_xy()
edit_distance = edit_distance()