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// SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
// SPDX-FileCopyrightText: Bradley M. Bell <bradbell@seanet.com>
// SPDX-FileContributor: 2003-22 Bradley M. Bell
// ----------------------------------------------------------------------------
/*
{xrst_begin for_sparse_jac.cpp}
Forward Mode Jacobian Sparsity: Example and Test
################################################
{xrst_literal
// BEGIN C++
// END C++
}
{xrst_end for_sparse_jac.cpp}
*/
// BEGIN C++
# include <set>
# include <cppad/cppad.hpp>
namespace { // -------------------------------------------------------------
// define the template function BoolCases<Vector>
template <class Vector> // vector class, elements of type bool
bool BoolCases(void)
{ bool ok = true;
using CppAD::AD;
// domain space vector
size_t n = 2;
CPPAD_TESTVECTOR(AD<double>) X(n);
X[0] = 0.;
X[1] = 1.;
// declare independent variables and start recording
CppAD::Independent(X);
// range space vector
size_t m = 3;
CPPAD_TESTVECTOR(AD<double>) Y(m);
Y[0] = X[0];
Y[1] = X[0] * X[1];
Y[2] = X[1];
// create f: X -> Y and stop tape recording
CppAD::ADFun<double> f(X, Y);
// sparsity pattern for the identity matrix
Vector r(n * n);
size_t i, j;
for(i = 0; i < n; i++)
{ for(j = 0; j < n; j++)
r[ i * n + j ] = (i == j);
}
// sparsity pattern for F'(x)
Vector s(m * n);
s = f.ForSparseJac(n, r);
// check values
ok &= (s[ 0 * n + 0 ] == true); // Y[0] does depend on X[0]
ok &= (s[ 0 * n + 1 ] == false); // Y[0] does not depend on X[1]
ok &= (s[ 1 * n + 0 ] == true); // Y[1] does depend on X[0]
ok &= (s[ 1 * n + 1 ] == true); // Y[1] does depend on X[1]
ok &= (s[ 2 * n + 0 ] == false); // Y[2] does not depend on X[0]
ok &= (s[ 2 * n + 1 ] == true); // Y[2] does depend on X[1]
// check that values are stored
ok &= (f.size_forward_bool() > 0);
ok &= (f.size_forward_set() == 0);
// sparsity pattern for F'(x)^T, note R is the identity, so R^T = R
bool transpose = true;
Vector st(n * m);
st = f.ForSparseJac(n, r, transpose);
// check values
ok &= (st[ 0 * m + 0 ] == true); // Y[0] does depend on X[0]
ok &= (st[ 1 * m + 0 ] == false); // Y[0] does not depend on X[1]
ok &= (st[ 0 * m + 1 ] == true); // Y[1] does depend on X[0]
ok &= (st[ 1 * m + 1 ] == true); // Y[1] does depend on X[1]
ok &= (st[ 0 * m + 2 ] == false); // Y[2] does not depend on X[0]
ok &= (st[ 1 * m + 2 ] == true); // Y[2] does depend on X[1]
// check that values are stored
ok &= (f.size_forward_bool() > 0);
ok &= (f.size_forward_set() == 0);
// free values from forward calculation
f.size_forward_bool(0);
ok &= (f.size_forward_bool() == 0);
return ok;
}
// define the template function SetCases<Vector>
template <class Vector> // vector class, elements of type std::set<size_t>
bool SetCases(void)
{ bool ok = true;
using CppAD::AD;
// domain space vector
size_t n = 2;
CPPAD_TESTVECTOR(AD<double>) X(n);
X[0] = 0.;
X[1] = 1.;
// declare independent variables and start recording
CppAD::Independent(X);
// range space vector
size_t m = 3;
CPPAD_TESTVECTOR(AD<double>) Y(m);
Y[0] = X[0];
Y[1] = X[0] * X[1];
Y[2] = X[1];
// create f: X -> Y and stop tape recording
CppAD::ADFun<double> f(X, Y);
// sparsity pattern for the identity matrix
Vector r(n);
size_t i;
for(i = 0; i < n; i++)
{ assert( r[i].empty() );
r[i].insert(i);
}
// sparsity pattern for F'(x)
Vector s(m);
s = f.ForSparseJac(n, r);
// an interator to a standard set
std::set<size_t>::iterator itr;
bool found;
// Y[0] does depend on X[0]
found = s[0].find(0) != s[0].end(); ok &= ( found == true );
// Y[0] does not depend on X[1]
found = s[0].find(1) != s[0].end(); ok &= ( found == false );
// Y[1] does depend on X[0]
found = s[1].find(0) != s[1].end(); ok &= ( found == true );
// Y[1] does depend on X[1]
found = s[1].find(1) != s[1].end(); ok &= ( found == true );
// Y[2] does not depend on X[0]
found = s[2].find(0) != s[2].end(); ok &= ( found == false );
// Y[2] does depend on X[1]
found = s[2].find(1) != s[2].end(); ok &= ( found == true );
// check that values are stored
ok &= (f.size_forward_set() > 0);
ok &= (f.size_forward_bool() == 0);
// sparsity pattern for F'(x)^T
bool transpose = true;
Vector st(n);
st = f.ForSparseJac(n, r, transpose);
// Y[0] does depend on X[0]
found = st[0].find(0) != st[0].end(); ok &= ( found == true );
// Y[0] does not depend on X[1]
found = st[1].find(0) != st[1].end(); ok &= ( found == false );
// Y[1] does depend on X[0]
found = st[0].find(1) != st[0].end(); ok &= ( found == true );
// Y[1] does depend on X[1]
found = st[1].find(1) != st[1].end(); ok &= ( found == true );
// Y[2] does not depend on X[0]
found = st[0].find(2) != st[0].end(); ok &= ( found == false );
// Y[2] does depend on X[1]
found = st[1].find(2) != st[1].end(); ok &= ( found == true );
// check that values are stored
ok &= (f.size_forward_set() > 0);
ok &= (f.size_forward_bool() == 0);
return ok;
}
} // End empty namespace
# include <vector>
# include <valarray>
bool ForSparseJac(void)
{ bool ok = true;
// Run with Vector equal to four different cases
// all of which are Simple Vectors with elements of type bool.
ok &= BoolCases< CppAD::vectorBool >();
ok &= BoolCases< CppAD::vector <bool> >();
ok &= BoolCases< std::vector <bool> >();
ok &= BoolCases< std::valarray <bool> >();
// Run with Vector equal to two different cases both of which are
// Simple Vectors with elements of type std::set<size_t>
typedef std::set<size_t> set;
ok &= SetCases< CppAD::vector <set> >();
// ok &= SetCases< std::vector <set> >();
// Do not use valarray because its element access in the const case
// returns a copy instead of a reference
// ok &= SetCases< std::valarray <set> >();
return ok;
}
// END C++
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