Commit ca8aa7d7 authored by Patrik Huber's avatar Patrik Huber

Added conversion for 3x4 matrices

Careful about GLM's notation! A 3x4 matrix is a mat4x3!
parent fbcfa576
......@@ -29,6 +29,9 @@ NAMESPACE_BEGIN(detail)
*
* All converters for matrices assume col-major storage of glm, the default.
* Things will likely break if non-default storage order is used.
*
* Note: GLM follows the GLSL matrix definition, so e.g. a glm::tmat4x3 has 4 cols
* and 3 rows, and is thus (in the standard mathematical notation) a 3x4 matrix.
*/
template<typename T, glm::precision P>
......@@ -175,6 +178,60 @@ protected:
static PYBIND11_DESCR elements() { return _(std::to_string(num_elements).c_str()); }
};
template<typename T, glm::precision P>
struct type_caster<glm::tmat4x3<T, P>>
{
using matrix_type = glm::tmat4x3<T, P>;
typedef typename T Scalar;
static constexpr std::size_t num_rows = 3;
static constexpr std::size_t num_cols = 4;
bool load(handle src, bool)
{
array_t<Scalar> buf(src, true);
if (!buf.check())
return false;
if (buf.ndim() == 2) // a 2-dimensional matrix
{
if (buf.shape(0) != num_rows || buf.shape(1) != num_cols) {
return false; // not a 3x4 matrix
}
if (buf.strides(0) / sizeof(Scalar) != num_cols || buf.strides(1) != sizeof(Scalar))
{
std::cout << "An array with non-standard strides is given. Please pass a contiguous array." << std::endl;
return false;
}
// What we get from Python is laid out in row-major memory order, while GLM's
// storage is col-major, thus, we create a mat3x4 and then transpose.
value = glm::transpose(glm::make_mat3x4(buf.mutable_data())); // make_mat*() copies the data (unnecessarily)
}
else { // buf.ndim() != 2
return false;
}
return true;
}
static handle cast(const matrix_type& src, return_value_policy /* policy */, handle /* parent */)
{
return array(
{ num_rows, num_cols }, // shape
{ sizeof(Scalar), sizeof(Scalar) * num_rows }, // strides - flip the row/col layout!
glm::value_ptr(src) // data
).release();
}
// Specifies the doc-string for the type in Python:
PYBIND11_TYPE_CASTER(matrix_type, _("numpy.ndarray[") + npy_format_descriptor<Scalar>::name() +
_("[") + rows() + _(", ") + cols() + _("]]"));
protected:
template <typename T = matrix_type>
static PYBIND11_DESCR rows() { return _(std::to_string(num_rows).c_str()); }
template <typename T = matrix_type>
static PYBIND11_DESCR cols() { return _(std::to_string(num_cols).c_str()); }
};
template<typename T, glm::precision P>
struct type_caster<glm::tmat4x4<T, P>>
{
......
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