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Richard Torenvliet
eos
Commits
ca8aa7d7
Commit
ca8aa7d7
authored
Oct 04, 2016
by
Patrik Huber
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Added conversion for 3x4 matrices
Careful about GLM's notation! A 3x4 matrix is a mat4x3!
parent
fbcfa576
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utils/pybind11_glm.hpp
utils/pybind11_glm.hpp
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utils/pybind11_glm.hpp
View file @
ca8aa7d7
...
@@ -29,6 +29,9 @@ NAMESPACE_BEGIN(detail)
...
@@ -29,6 +29,9 @@ NAMESPACE_BEGIN(detail)
*
*
* All converters for matrices assume col-major storage of glm, the default.
* All converters for matrices assume col-major storage of glm, the default.
* Things will likely break if non-default storage order is used.
* 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
>
template
<
typename
T
,
glm
::
precision
P
>
...
@@ -175,6 +178,60 @@ protected:
...
@@ -175,6 +178,60 @@ protected:
static
PYBIND11_DESCR
elements
()
{
return
_
(
std
::
to_string
(
num_elements
).
c_str
());
}
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
>
template
<
typename
T
,
glm
::
precision
P
>
struct
type_caster
<
glm
::
tmat4x4
<
T
,
P
>>
struct
type_caster
<
glm
::
tmat4x4
<
T
,
P
>>
{
{
...
...
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