This file is indexed.

/usr/include/ql/experimental/math/laplaceinterpolation.hpp is in libquantlib0-dev 1.9.1-1.

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
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */

/*
 Copyright (C) 2015 Peter Caspers

 This file is part of QuantLib, a free-software/open-source library
 for financial quantitative analysts and developers - http://quantlib.org/

 QuantLib is free software: you can redistribute it and/or modify it
 under the terms of the QuantLib license.  You should have received a
 copy of the license along with this program; if not, please email
 <quantlib-dev@lists.sf.net>. The license is also available online at
 <http://quantlib.org/license.shtml>.

 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 license for more details.
*/

/*! \file laplaceinterpolation.hpp
    \brief Laplace interpolation of missing values
*/

#ifndef quantlib_laplace_interpolation
#define quantlib_laplace_interpolation

#if !defined(QL_NO_UBLAS_SUPPORT)

#include <ql/math/matrixutilities/bicgstab.hpp>
#include <ql/math/matrixutilities/sparsematrix.hpp>

namespace QuantLib {

/*! reference: Numerical Recipes, 3rd edition, ch. 3.8
    two dimensional reconstruction of missing (i.e. null)
    values using laplace interpolation assuming an
    equidistant grid */

template <class M> void laplaceInterpolation(M &A, Real relTol = 1E-6) {

    struct f_A {
        const SparseMatrix &g;
        f_A(const SparseMatrix &g) : g(g) {}
        Disposable<Array> operator()(const Array &x) const {
            return prod(g, x);
        }
    };

    Size m = A.rows();
    Size n = A.columns();

    QL_REQUIRE(n > 1 && m > 1, "matrix (" << m << "," << n
                                          << ") must at least be 2x2");

    SparseMatrix g(m * n, m * n, 5 * m * n);
    Array rhs(m * n, 0.0), guess(m * n, 0.0);
    Real guessTmp = 0.0;
    Size i1, i2, i3, i4, j1, j2, j3, j4;
    bool inner;

    for (Size l = 0, i = 0; i < m; ++i) {
        for (Size j = 0; j < n; ++j) {

            inner = false;

            // top
            if (i == 0) {
                if (j == 0) {
                    i1 = 0;
                    j1 = 1;
                    i2 = 1;
                    j2 = 0;
                } else {
                    if (j == n - 1) {
                        i1 = 0;
                        j1 = n - 2;
                        i2 = 1;
                        j2 = n - 1;
                    } else {
                        i1 = i2 = 0;
                        j1 = j - 1;
                        j2 = j + 1;
                    }
                }
            }

            // bottom
            if (i == m - 1) {
                if (j == 0) {
                    i1 = m - 1;
                    j1 = 1;
                    i2 = m - 2;
                    j2 = 0;
                } else {
                    if (j == n - 1) {
                        i1 = m - 1;
                        j1 = n - 2;
                        i2 = m - 2;
                        j2 = n - 1;
                    } else {
                        i1 = i2 = m - 1;
                        j1 = j - 1;
                        j2 = j + 1;
                    }
                }
            }

            // left / right
            if (i > 0 && i < m - 1) {
                if (j == 0 || j == n - 1) {
                    j1 = j2 = j;
                    i1 = i - 1;
                    i2 = i + 1;
                } else {
                    inner = true;
                    i1 = i - 1;
                    i2 = i - 1;
                    i3 = i + 1;
                    i4 = i + 1;
                    j1 = j - 1;
                    j2 = j + 1;
                    j3 = j - 1;
                    j4 = j + 1;
                }
            }

            g(l, i * n + j) = 1.0;
            if (A[i][j] == Null<Real>()) {
                if (inner) {
                    g(l, i1 * n + j1) = -0.25;
                    g(l, i2 * n + j2) = -0.25;
                    g(l, i3 * n + j3) = -0.25;
                    g(l, i4 * n + j4) = -0.25;
                } else {
                    g(l, i1 * n + j1) = -0.5;
                    g(l, i2 * n + j2) = -0.5;
                }
                rhs[l] = 0.0;
                guess[l] = guessTmp;
            } else {
                rhs[l] = A[i][j];
                guess[l] = guessTmp = A[i][j];
            }
            ++l;
        }
    }

    // solve the equation (preconditioner is identiy)
    Array s = BiCGstab(f_A(g), 10 * m * n, relTol)
                  .solve(rhs, guess)
                  .x;

    // replace missing values by solution
    for (Size i = 0; i < m; ++i) {
        for (Size j = 0; j < n; ++j) {
            if (A[i][j] == Null<Real>()) {
                A[i][j] = s[i * n + j];
            }
        }
    }

    return;
};

} // namespace QuantLib

#endif // QL_NO_UBLAS_SUPPORT
#endif // include guard