File size: 6,030 Bytes
9375c9a |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 |
// Copyright (C) 2013 Davis E. King ([email protected])
// License: Boost Software License See LICENSE.txt for the full license.
#include "opaque_types.h"
#include <dlib/python.h>
#include <dlib/matrix.h>
#include <dlib/string.h>
#include <pybind11/pybind11.h>
using namespace dlib;
namespace py = pybind11;
using std::string;
using std::ostringstream;
void matrix_set_size(matrix<double>& m, long nr, long nc)
{
m.set_size(nr,nc);
m = 0;
}
string matrix_double__repr__(matrix<double>& c)
{
ostringstream sout;
sout << "< dlib.matrix containing: \n";
sout << c;
return trim(sout.str()) + " >";
}
string matrix_double__str__(matrix<double>& c)
{
ostringstream sout;
sout << c;
return trim(sout.str());
}
std::shared_ptr<matrix<double> > make_matrix_from_size(long nr, long nc)
{
if (nr < 0 || nc < 0)
{
PyErr_SetString( PyExc_IndexError, "Input dimensions can't be negative."
);
throw py::error_already_set();
}
auto temp = std::make_shared<matrix<double>>(nr,nc);
*temp = 0;
return temp;
}
std::shared_ptr<matrix<double> > from_object(py::object obj)
{
py::tuple s = obj.attr("shape").cast<py::tuple>();
if (len(s) != 2)
{
PyErr_SetString( PyExc_IndexError, "Input must be a matrix or some kind of 2D array."
);
throw py::error_already_set();
}
const long nr = s[0].cast<long>();
const long nc = s[1].cast<long>();
auto temp = std::make_shared<matrix<double>>(nr,nc);
for ( long r = 0; r < nr; ++r)
{
for (long c = 0; c < nc; ++c)
{
(*temp)(r,c) = obj[py::make_tuple(r,c)].cast<double>();
}
}
return temp;
}
std::shared_ptr<matrix<double> > from_list(py::list l)
{
const long nr = py::len(l);
if (py::isinstance<py::list>(l[0]))
{
const long nc = py::len(l[0]);
// make sure all the other rows have the same length
for (long r = 1; r < nr; ++r)
pyassert(py::len(l[r]) == nc, "All rows of a matrix must have the same number of columns.");
auto temp = std::make_shared<matrix<double>>(nr,nc);
for ( long r = 0; r < nr; ++r)
{
for (long c = 0; c < nc; ++c)
{
(*temp)(r,c) = l[r].cast<py::list>()[c].cast<double>();
}
}
return temp;
}
else
{
// In this case we treat it like a column vector
auto temp = std::make_shared<matrix<double>>(nr,1);
for ( long r = 0; r < nr; ++r)
{
(*temp)(r) = l[r].cast<double>();
}
return temp;
}
}
long matrix_double__len__(matrix<double>& c)
{
return c.nr();
}
void matrix_double_serialize(const matrix<double>& m, const std::string& file)
{
serialize(file) << m;
}
void matrix_double_deserialize(matrix<double>& m, const std::string& file)
{
deserialize(file) >> m;
}
struct mat_row
{
mat_row() : data(0),size(0) {}
mat_row(double* data_, long size_) : data(data_),size(size_) {}
double* data;
long size;
};
void mat_row__setitem__(mat_row& c, long p, double val)
{
if (p < 0) {
p = c.size + p; // negative index
}
if (p > c.size-1) {
PyErr_SetString( PyExc_IndexError, "3 index out of range"
);
throw py::error_already_set();
}
c.data[p] = val;
}
string mat_row__str__(mat_row& c)
{
ostringstream sout;
sout << mat(c.data,1, c.size);
return sout.str();
}
string mat_row__repr__(mat_row& c)
{
ostringstream sout;
sout << "< matrix row: " << mat(c.data,1, c.size);
return trim(sout.str()) + " >";
}
long mat_row__len__(mat_row& m)
{
return m.size;
}
double mat_row__getitem__(mat_row& m, long r)
{
if (r < 0) {
r = m.size + r; // negative index
}
if (r > m.size-1 || r < 0) {
PyErr_SetString( PyExc_IndexError, "1 index out of range"
);
throw py::error_already_set();
}
return m.data[r];
}
mat_row matrix_double__getitem__(matrix<double>& m, long r)
{
if (r < 0) {
r = m.nr() + r; // negative index
}
if (r > m.nr()-1 || r < 0) {
PyErr_SetString( PyExc_IndexError, (string("2 index out of range, got ") + cast_to_string(r)).c_str()
);
throw py::error_already_set();
}
return mat_row(&m(r,0),m.nc());
}
py::tuple get_matrix_size(matrix<double>& m)
{
return py::make_tuple(m.nr(), m.nc());
}
void bind_matrix(py::module& m)
{
py::class_<mat_row>(m, "_row")
.def("__len__", &mat_row__len__)
.def("__repr__", &mat_row__repr__)
.def("__str__", &mat_row__str__)
.def("__setitem__", &mat_row__setitem__)
.def("__getitem__", &mat_row__getitem__);
py::class_<matrix<double>, std::shared_ptr<matrix<double>>>(m, "matrix",
"This object represents a dense 2D matrix of floating point numbers."
"Moreover, it binds directly to the C++ type dlib::matrix<double>.")
.def(py::init<>())
.def(py::init(&from_list))
.def(py::init(&from_object))
.def(py::init(&make_matrix_from_size))
.def("set_size", &matrix_set_size, py::arg("rows"), py::arg("cols"), "Set the size of the matrix to the given number of rows and columns.")
.def("__repr__", &matrix_double__repr__)
.def("__str__", &matrix_double__str__)
.def("nr", &matrix<double>::nr, "Return the number of rows in the matrix.")
.def("nc", &matrix<double>::nc, "Return the number of columns in the matrix.")
.def("serialize", &matrix_double_serialize, py::arg("file"), "Serialize the matrix to a file")
.def("deserialize", &matrix_double_deserialize, py::arg("file"), "Deserialize the matrix from a file")
.def("__len__", &matrix_double__len__)
.def("__getitem__", &matrix_double__getitem__, py::keep_alive<0,1>())
.def_property_readonly("shape", &get_matrix_size)
.def(py::pickle(&getstate<matrix<double>>, &setstate<matrix<double>>));
}
|