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mapping.c
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Tue, Nov 12, 19:47
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66 KB
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text/x-c
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Thu, Nov 14, 19:47 (2 d)
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blob
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mapping.c
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#include <Python.h>
#include <math.h>
#include <numpy/arrayobject.h>
#include <omp.h>
#define kxmax1d 1024
#define kxmax2d 1024
#define kymax2d 1024
#define kxmax3d 64
#define kymax3d 64
#define kzmax3d 64
#define PI 3.14159265358979
/*********************************/
/* mkmap1d */
/*********************************/
static
PyObject
*
mapping_mkmap1d
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
;
int
ix
;
int
kx
;
npy_intp
ld
[
1
];
float
dseo
[
kxmax1d
];
float
x
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(i)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax1d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
1
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
1
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be one dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
dseo
[
ix
]
=
0.
;
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
if
(
ix
>=
0
&&
x
<
kx
)
dseo
[
ix
]
=
dseo
[
ix
]
+
gm
*
am
;
}
/* create the subimage */
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
]))
=
(
float
)
dseo
[
i
]
;
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap1dn */
/*********************************/
static
PyObject
*
mapping_mkmap1dn
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
;
int
ix
;
int
kx
;
npy_intp
ld
[
1
];
float
*
dseo
;
float
x
,
gm
,
am
;
size_t
bytes
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(i)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
1
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
1
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be one dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
dseo
[
ix
]
=
0.
;
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
if
(
ix
>=
0
&&
x
<
kx
)
dseo
[
ix
]
=
dseo
[
ix
]
+
gm
*
am
;
}
/* create the subimage */
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
]))
=
(
float
)
dseo
[
i
]
;
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap2d */
/*********************************/
static
PyObject
*
mapping_mkmap2d
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
;
int
ix
,
iy
;
int
kx
,
ky
;
npy_intp
ld
[
2
];
float
dseo
[
kxmax2d
][
kymax2d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
*
am
;
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap2dn */
/*********************************/
static
PyObject
*
mapping_mkmap2dn
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
;
int
ix
,
iy
;
int
kx
,
ky
;
npy_intp
ld
[
2
];
float
*
dseo
;
float
x
,
y
,
z
,
gm
,
am
;
size_t
bytes
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
ky
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
iy
+
ix
*
ky
]
=
0.
;
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
{
dseo
[
iy
+
ix
*
ky
]
=
dseo
[
iy
+
ix
*
ky
]
+
gm
*
am
;
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
j
+
i
*
ky
]
;
}
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap3d */
/*********************************/
static
PyObject
*
mapping_mkmap3d
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
,
k
;
int
ix
,
iy
,
iz
;
int
kx
,
ky
,
kz
;
npy_intp
ld
[
3
];
float
dseo
[
kxmax3d
][
kymax3d
][
kzmax3d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(iii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
,
&
kz
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax3d
||
ky
>
kymax3d
||
kz
>
kzmax3d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
ld
[
2
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
3
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
for
(
iz
=
0
;
iz
<
kz
;
iz
++
)
{
dseo
[
ix
][
iy
][
iz
]
=
0.
;
}
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
z
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
2
*
pos
->
strides
[
1
])
*
(
kz
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
iz
=
(
int
)(
z
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
if
(
iz
>=
0
&&
iz
<
kz
)
dseo
[
ix
][
iy
][
iz
]
=
dseo
[
ix
][
iy
][
iz
]
+
gm
*
am
;
}
/* create the subimage */
for
(
k
=
0
;
k
<
kz
;
k
++
)
{
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
])
+
(
k
)
*
(
mat
->
strides
[
2
]))
=
(
float
)
dseo
[
i
][
j
][
k
]
;
}
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap3dn */
/*********************************/
static
PyObject
*
mapping_mkmap3dn
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
,
k
;
int
ix
,
iy
,
iz
;
int
kx
,
ky
,
kz
;
npy_intp
ld
[
3
];
float
*
dseo
;
float
x
,
y
,
z
,
gm
,
am
;
size_t
bytes
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(iii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
,
&
kz
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
ky
*
kz
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
ld
[
2
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
3
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
for
(
iz
=
0
;
iz
<
kz
;
iz
++
)
{
dseo
[
ix
*
(
kz
*
ky
)
+
iy
*
(
kz
)
+
iz
]
=
0.
;
}
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
z
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
2
*
pos
->
strides
[
1
])
*
(
kz
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
iz
=
(
int
)(
z
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
if
(
iz
>=
0
&&
iz
<
kz
)
dseo
[
ix
*
(
kz
*
ky
)
+
iy
*
(
kz
)
+
iz
]
=
dseo
[
ix
*
(
kz
*
ky
)
+
iy
*
(
kz
)
+
iz
]
+
gm
*
am
;
}
/* create the subimage */
for
(
k
=
0
;
k
<
kz
;
k
++
)
{
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
])
+
(
k
)
*
(
mat
->
strides
[
2
]))
=
(
float
)
dseo
[
i
*
(
kz
*
ky
)
+
j
*
(
kz
)
+
k
]
;
}
}
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap1dw */
/*********************************/
static
PyObject
*
mapping_mkmap1dw
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
;
int
ix1
,
ix2
;
float
wx1
,
wx2
;
int
kx
;
npy_intp
ld
[
1
];
float
dseo
[
kxmax1d
];
float
x
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(i)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax1d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
1
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
1
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be one dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix1
=
0
;
ix1
<
kx
;
ix1
++
)
{
dseo
[
ix1
]
=
0.
;
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
]);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
if
(
x
>=
0
&&
x
<=
1
)
{
x
=
x
*
(
kx
-
1
);
ix1
=
(
int
)(
x
);
ix2
=
ix1
+
1
;
wx1
=
1
-
(
x
-
ix1
);
wx2
=
1
-
(
ix2
-
x
);
if
(
wx1
>
0
)
dseo
[
ix1
]
=
dseo
[
ix1
]
+
gm
*
am
*
wx1
;
if
(
wx2
>
0
)
dseo
[
ix2
]
=
dseo
[
ix2
]
+
gm
*
am
*
wx2
;
}
}
/* create the subimage */
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
]))
=
(
float
)
dseo
[
i
]
;
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap2dw */
/*********************************/
static
PyObject
*
mapping_mkmap2dw
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
;
int
ix1
,
ix2
,
iy1
,
iy2
;
float
wx1
,
wx2
,
wy1
,
wy2
;
int
kx
,
ky
;
npy_intp
ld
[
2
];
float
dseo
[
kxmax2d
][
kymax2d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix1
=
0
;
ix1
<
kx
;
ix1
++
)
{
for
(
iy1
=
0
;
iy1
<
ky
;
iy1
++
)
{
dseo
[
ix1
][
iy1
]
=
0.
;
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
]);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
]);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
if
((
x
>=
0
&&
x
<=
1
)
&&
(
y
>=
0
&&
y
<=
1
))
{
x
=
x
*
(
kx
-
1
);
ix1
=
(
int
)(
x
);
ix2
=
ix1
+
1
;
wx1
=
1
-
(
x
-
ix1
);
wx2
=
1
-
(
ix2
-
x
);
y
=
y
*
(
ky
-
1
);
iy1
=
(
int
)(
y
);
iy2
=
iy1
+
1
;
wy1
=
1
-
(
y
-
iy1
);
wy2
=
1
-
(
iy2
-
y
);
if
(
wx1
*
wy1
>
0
)
dseo
[
ix1
][
iy1
]
=
dseo
[
ix1
][
iy1
]
+
gm
*
am
*
wx1
*
wy1
;
if
(
wx2
*
wy1
>
0
)
dseo
[
ix2
][
iy1
]
=
dseo
[
ix2
][
iy1
]
+
gm
*
am
*
wx2
*
wy1
;
if
(
wx1
*
wy2
>
0
)
dseo
[
ix1
][
iy2
]
=
dseo
[
ix1
][
iy2
]
+
gm
*
am
*
wx1
*
wy2
;
if
(
wx2
*
wy2
>
0
)
dseo
[
ix2
][
iy2
]
=
dseo
[
ix2
][
iy2
]
+
gm
*
am
*
wx2
*
wy2
;
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap3dw */
/*********************************/
static
PyObject
*
mapping_mkmap3dw
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
,
k
;
int
ix1
,
ix2
,
iy1
,
iy2
,
iz1
,
iz2
;
float
wx1
,
wx2
,
wy1
,
wy2
,
wz1
,
wz2
;
int
kx
,
ky
,
kz
;
npy_intp
ld
[
3
];
float
dseo
[
kxmax3d
][
kymax3d
][
kzmax3d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(iii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
,
&
kz
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax3d
||
ky
>
kymax3d
||
kz
>
kzmax3d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
ld
[
2
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
3
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix1
=
0
;
ix1
<
kx
;
ix1
++
)
{
for
(
iy1
=
0
;
iy1
<
ky
;
iy1
++
)
{
for
(
iz1
=
0
;
iz1
<
kz
;
iz1
++
)
{
dseo
[
ix1
][
iy1
][
iz1
]
=
0.
;
}
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
]);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
]);
z
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
2
*
pos
->
strides
[
1
]);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
if
((
x
>=
0
&&
x
<=
1
)
&&
(
y
>=
0
&&
y
<=
1
)
&&
(
z
>=
0
&&
z
<=
1
))
{
x
=
x
*
(
kx
-
1
);
ix1
=
(
int
)(
x
);
ix2
=
ix1
+
1
;
wx1
=
1
-
(
x
-
ix1
);
wx2
=
1
-
(
ix2
-
x
);
y
=
y
*
(
ky
-
1
);
iy1
=
(
int
)(
y
);
iy2
=
iy1
+
1
;
wy1
=
1
-
(
y
-
iy1
);
wy2
=
1
-
(
iy2
-
y
);
z
=
z
*
(
kz
-
1
);
iz1
=
(
int
)(
z
);
iz2
=
iz1
+
1
;
wz1
=
1
-
(
z
-
iz1
);
wz2
=
1
-
(
iz2
-
z
);
if
(
wx1
*
wy1
*
wz1
>
0
)
dseo
[
ix1
][
iy1
][
iz1
]
=
dseo
[
ix1
][
iy1
][
iz1
]
+
gm
*
am
*
wx1
*
wy1
*
wz1
;
if
(
wx1
*
wy1
*
wz2
>
0
)
dseo
[
ix1
][
iy1
][
iz2
]
=
dseo
[
ix1
][
iy1
][
iz2
]
+
gm
*
am
*
wx1
*
wy1
*
wz2
;
if
(
wx1
*
wy2
*
wz1
>
0
)
dseo
[
ix1
][
iy2
][
iz1
]
=
dseo
[
ix1
][
iy2
][
iz1
]
+
gm
*
am
*
wx1
*
wy2
*
wz1
;
if
(
wx1
*
wy2
*
wz2
>
0
)
dseo
[
ix1
][
iy2
][
iz2
]
=
dseo
[
ix1
][
iy2
][
iz2
]
+
gm
*
am
*
wx1
*
wy2
*
wz2
;
if
(
wx2
*
wy1
*
wz1
>
0
)
dseo
[
ix2
][
iy1
][
iz1
]
=
dseo
[
ix2
][
iy1
][
iz1
]
+
gm
*
am
*
wx2
*
wy1
*
wz1
;
if
(
wx2
*
wy1
*
wz2
>
0
)
dseo
[
ix2
][
iy1
][
iz2
]
=
dseo
[
ix2
][
iy1
][
iz2
]
+
gm
*
am
*
wx2
*
wy1
*
wz2
;
if
(
wx2
*
wy2
*
wz1
>
0
)
dseo
[
ix2
][
iy2
][
iz1
]
=
dseo
[
ix2
][
iy2
][
iz1
]
+
gm
*
am
*
wx2
*
wy2
*
wz1
;
if
(
wx2
*
wy2
*
wz2
>
0
)
dseo
[
ix2
][
iy2
][
iz2
]
=
dseo
[
ix2
][
iy2
][
iz2
]
+
gm
*
am
*
wx2
*
wy2
*
wz2
;
}
}
/* create the subimage */
for
(
k
=
0
;
k
<
kz
;
k
++
)
{
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
])
+
(
k
)
*
(
mat
->
strides
[
2
]))
=
(
float
)
dseo
[
i
][
j
][
k
]
;
}
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap2dsph */
/*********************************/
static
PyObject
*
mapping_mkmap2dsph
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
rsp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
;
int
ix
,
iy
;
int
kx
,
ky
;
npy_intp
ld
[
2
];
float
dseo
[
kxmax2d
][
kymax2d
];
float
x
,
y
,
z
,
gm
,
am
,
sigma
,
sigma2
,
pisig
,
gaus
,
sum
;
int
xin
,
xfi
,
yin
,
yfi
,
ixx
,
iyy
;
int
dkx2
,
dky2
,
dkx
,
dky
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOOO(ii)"
,
&
pos
,
&
gmm
,
&
amp
,
&
rsp
,
&
kx
,
&
ky
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
}
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
sigma
=
*
(
float
*
)
(
rsp
->
data
+
i
*
(
rsp
->
strides
[
0
]));
/* the size of the subgrid */
dkx2
=
(
int
)(
3.
*
sigma
);
/* 3 sigma -> 98% volume */
dky2
=
(
int
)(
3.
*
sigma
);
dkx
=
2.
*
dkx2
+
1
;
dky
=
2.
*
dky2
+
1
;
if
(
dkx
==
1
&&
dky
==
1
){
/* the size is 1 */
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
*
am
;
}
else
{
ix
=
(
int
)
x
;
/* center of the sub grid */
iy
=
(
int
)
y
;
sigma2
=
sigma
*
sigma
;
pisig
=
1.
/
(
2.
*
PI
*
sigma2
);
sum
=
0
;
//printf("%f %d %d %d %d\n",sigma,dkx,dky,kx,ky);
/* bornes */
xin
=
ix
-
dkx2
;
yin
=
iy
-
dky2
;
xfi
=
ix
+
dkx2
+
1
;
yfi
=
iy
+
dky2
+
1
;
if
(
xin
<
0
){
xin
=
0
;}
if
(
yin
<
0
){
yin
=
0
;}
if
(
xfi
>
kx
-
1
){
xfi
=
kx
-
1
;}
if
(
yfi
>
ky
-
1
){
yfi
=
ky
-
1
;}
if
(
xfi
>
xin
&&
yfi
>
yin
)
{
/* loop over the grid */
for
(
ixx
=
xin
;
ixx
<
xfi
;
ixx
++
){
for
(
iyy
=
yin
;
iyy
<
yfi
;
iyy
++
){
gaus
=
pisig
*
exp
(
0.5
*
(
-
((
float
)(
ix
-
ixx
)
/
(
sigma
))
*
((
float
)(
ix
-
ixx
)
/
(
sigma
))
-
((
float
)(
iy
-
iyy
)
/
(
sigma
))
*
((
float
)(
iy
-
iyy
)
/
(
sigma
)))
);
sum
=
sum
+
gaus
;
dseo
[
ixx
][
iyy
]
=
dseo
[
ixx
][
iyy
]
+
gm
*
am
*
gaus
;
}
}
}
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap2dnsph */
/*********************************/
static
PyObject
*
mapping_mkmap2dnsph
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
rsp
=
NULL
;
PyArrayObject
*
mat
;
int
n
,
i
,
j
;
int
ix
,
iy
;
int
kx
,
ky
;
npy_intp
ld
[
2
];
float
*
dseo
;
size_t
bytes
;
float
x
,
y
,
z
,
gm
,
am
,
sigma
,
sigma2
,
pisig
,
gaus
,
sum
;
int
xin
,
xfi
,
yin
,
yfi
,
ixx
,
iyy
;
int
dkx2
,
dky2
,
dkx
,
dky
;
int
nth
;
omp_lock_t
*
lock
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOOO(ii)i"
,
&
pos
,
&
gmm
,
&
amp
,
&
rsp
,
&
kx
,
&
ky
,
&
nth
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
ky
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
ix
*
ky
+
iy
]
=
0.
;
}
}
/* set number of threads */
omp_set_num_threads
(
nth
);
if
(
!
(
lock
=
malloc
(
kx
*
ky
*
sizeof
(
omp_lock_t
))))
{
printf
(
"failed to allocate memory for lock'
\n
"
);
return
NULL
;
}
omp_init_lock
(
lock
);
#pragma omp parallel shared(dseo) private(i,x,y,gm,am,sigma,dkx2,dky2,dkx,dky,ix,iy,sigma2,pisig,sum,xin,yin,xfi,yfi,ixx,iyy,gaus)
{
/* full dseo : loop over all points in pos*/
//#pragma omp for schedule(dynamic,100) nowait
#pragma omp for schedule(dynamic,8) nowait
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
])
*
(
kx
);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
])
*
(
ky
);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
sigma
=
*
(
float
*
)
(
rsp
->
data
+
i
*
(
rsp
->
strides
[
0
]));
/* the size of the subgrid */
dkx2
=
(
int
)(
3.
*
sigma
);
/* 3 sigma -> 98% volume */
dky2
=
(
int
)(
3.
*
sigma
);
dkx
=
2.
*
dkx2
+
1
;
dky
=
2.
*
dky2
+
1
;
if
(
dkx
==
1
&&
dky
==
1
){
/* the size is 1 */
ix
=
(
int
)(
x
);
iy
=
(
int
)(
y
);
if
(
ix
>=
0
&&
ix
<
kx
)
if
(
iy
>=
0
&&
iy
<
ky
)
{
//#pragma omp critical
//omp_set_lock(lock);
dseo
[
ix
*
ky
+
iy
]
=
dseo
[
ix
*
ky
+
iy
]
+
gm
*
am
;
//omp_unset_lock(lock);
}
}
else
{
ix
=
(
int
)
x
;
/* center of the sub grid */
iy
=
(
int
)
y
;
sigma2
=
sigma
*
sigma
;
pisig
=
1.
/
(
2.
*
PI
*
sigma2
);
sum
=
0
;
//printf("%f %d %d %d %d\n",sigma,dkx,dky,kx,ky);
/* bornes */
xin
=
ix
-
dkx2
;
yin
=
iy
-
dky2
;
xfi
=
ix
+
dkx2
+
1
;
yfi
=
iy
+
dky2
+
1
;
if
(
xin
<
0
){
xin
=
0
;}
if
(
yin
<
0
){
yin
=
0
;}
if
(
xfi
>
kx
-
1
){
xfi
=
kx
-
1
;}
if
(
yfi
>
ky
-
1
){
yfi
=
ky
-
1
;}
if
(
xfi
>
xin
&&
yfi
>
yin
)
{
/* loop over the grid */
for
(
ixx
=
xin
;
ixx
<
xfi
;
ixx
++
){
for
(
iyy
=
yin
;
iyy
<
yfi
;
iyy
++
){
gaus
=
pisig
*
exp
(
0.5
*
(
-
((
float
)(
ix
-
ixx
)
/
(
sigma
))
*
((
float
)(
ix
-
ixx
)
/
(
sigma
))
-
((
float
)(
iy
-
iyy
)
/
(
sigma
))
*
((
float
)(
iy
-
iyy
)
/
(
sigma
)))
);
sum
=
sum
+
gaus
;
//#pragma omp critical
//omp_set_lock(lock);
dseo
[
ixx
*
ky
+
iyy
]
=
dseo
[
ixx
*
ky
+
iyy
]
+
gm
*
am
*
gaus
;
//omp_unset_lock(lock);
}
}
}
}
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
*
ky
+
j
]
;
}
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mapzero */
/*********************************/
static
PyObject
*
mapping_mapzero
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
float
xmx
,
ymx
,
xc
,
yc
,
zc
;
int
view
;
PyArrayObject
*
mat
;
int
kx
,
ky
;
int
kxx
,
kyy
;
int
kxx2
,
kyy2
;
int
n
,
i
,
j
;
int
ix
,
iy
,
xi
,
yi
,
zi
;
npy_intp
ld
[
2
];
float
ax
,
ay
,
bx
,
by
;
float
dseo
[
kxmax2d
][
kymax2d
];
float
mm
;
float
x
,
y
,
z
,
gm
;
if
(
!
PyArg_ParseTuple
(
args
,
"OO(ii)(ff)(fff)i"
,
&
pos
,
&
gmm
,
&
kx
,
&
ky
,
&
xmx
,
&
ymx
,
&
xc
,
&
yc
,
&
zc
,
&
view
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* set image dimension */
kxx
=
kx
;
kyy
=
ky
;
kxx2
=
kxx
/
2
;
kyy2
=
kyy
/
2
;
ax
=
kxx2
/
xmx
;
ay
=
kyy2
/
ymx
;
bx
=
kxx2
+
1.
;
by
=
kyy2
+
1.
;
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float0"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kxx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
kyy
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
}
}
/* choose the view */
if
(
view
==
1
){
/*xz*/
xi
=
0
;
yi
=
2
;
xc
=
xc
;
yc
=
zc
;
}
if
(
view
==
2
){
/*xy*/
xi
=
0
;
yi
=
1
;
xc
=
xc
;
yc
=
yc
;
}
if
(
view
==
3
){
/*yz*/
xi
=
1
;
yi
=
2
;
xc
=
yc
;
yc
=
zc
;
}
mm
=
0.
;
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
xi
*
pos
->
strides
[
1
])
-
xc
;
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
yi
*
pos
->
strides
[
1
])
-
yc
;
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
if
(
x
>
-
xmx
&&
x
<
xmx
)
{
if
(
y
>
-
ymx
&&
y
<
ymx
)
{
ix
=
(
int
)(
ax
*
x
+
bx
)
-
1
;
iy
=
(
int
)(
ay
*
y
+
by
)
-
1
;
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
;
/* add in cell */
mm
=
mm
+
gm
;
/* sum the weight */
}
}
}
/* normalisation */
/*
if(mm!=0.){
for (ix=0;ix<kxx;ix++) {
for (iy=0;iy<kyy;iy++) {
dseo[ix][iy]=dseo[ix][iy]/mm;
}
}
}
*/
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
ky
-
j
-
1
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mapzerosph */
/*********************************/
static
PyObject
*
mapping_mapzerosph
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
rsp
=
NULL
;
float
xmx
,
ymx
,
xc
,
yc
,
zc
,
frsp
;
int
view
;
PyArrayObject
*
mat
;
int
kx
,
ky
;
int
kxx
,
kyy
;
int
kxx2
,
kyy2
;
int
dkx2
,
dky2
,
dkx
,
dky
;
int
ikx
,
iky
;
int
n
,
i
,
j
;
int
ix
,
iy
,
xi
,
yi
,
ixx
,
iyy
;
int
xin
,
xfi
,
yin
,
yfi
;
npy_intp
ld
[
2
];
float
ax
,
ay
,
bx
,
by
;
float
dseo
[
kxmax2d
][
kymax2d
];
float
mm
;
float
x
,
y
,
z
,
gm
,
sigma
,
sigma2
,
pisig
,
gaus
,
ds
,
sum
;
int
*
pv
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)(ff)(fff)fi"
,
&
pos
,
&
gmm
,
&
rsp
,
&
kx
,
&
ky
,
&
xmx
,
&
ymx
,
&
xc
,
&
yc
,
&
zc
,
&
frsp
,
&
view
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* set image dimension */
kxx
=
kx
;
kyy
=
ky
;
kxx2
=
kxx
/
2
;
kyy2
=
kyy
/
2
;
ax
=
kxx2
/
xmx
;
ay
=
kyy2
/
ymx
;
bx
=
kxx2
+
1.
;
by
=
kyy2
+
1.
;
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float0"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kxx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
kyy
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
}
}
/* choose the view */
if
(
view
==
1
){
/*xz*/
xi
=
0
;
yi
=
2
;
xc
=
xc
;
yc
=
zc
;
}
if
(
view
==
2
){
/*xy*/
xi
=
0
;
yi
=
1
;
xc
=
xc
;
yc
=
yc
;
}
if
(
view
==
3
){
/*yz*/
xi
=
1
;
yi
=
2
;
xc
=
yc
;
yc
=
zc
;
}
mm
=
0
;
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
xi
*
pos
->
strides
[
1
])
-
xc
;
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
yi
*
pos
->
strides
[
1
])
-
yc
;
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
sigma
=
*
(
float
*
)
(
rsp
->
data
+
i
*
(
rsp
->
strides
[
0
]));
sigma
=
frsp
*
sigma
;
mm
=
mm
+
gm
;
/* define the subgrid */
/* the size of the subgrid */
dkx2
=
(
int
)(
ax
*
2.
*
sigma
);
/* 3 sigma -> 98% volume */
dky2
=
(
int
)(
ay
*
2.
*
sigma
);
dkx
=
2.
*
dkx2
+
1
;
dky
=
2.
*
dky2
+
1
;
if
(
dkx
==
1
&&
dky
==
1
){
/* the size is 1 */
if
(
x
>
-
xmx
&&
x
<
xmx
)
{
if
(
y
>
-
ymx
&&
y
<
ymx
)
{
ix
=
(
int
)(
ax
*
x
+
bx
)
-
1
;
iy
=
(
int
)(
ay
*
y
+
by
)
-
1
;
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
;
}
}
}
else
{
ix
=
(
int
)(
ax
*
x
+
bx
)
-
1
;
/* center of the grid */
iy
=
(
int
)(
ay
*
y
+
by
)
-
1
;
sigma2
=
sigma
*
sigma
;
pisig
=
1.
/
(
2.
*
PI
*
sigma2
);
ds
=
(
1.
/
ax
)
*
(
1.
/
ay
);
sum
=
0
;
//printf("%f %d %d %d %d\n",sigma,dkx,dky,kxx,kyy);
/* bornes */
xin
=
ix
-
dkx2
;
yin
=
iy
-
dky2
;
xfi
=
ix
+
dkx2
+
1
;
yfi
=
iy
+
dky2
+
1
;
if
(
xin
<
0
){
xin
=
0
;}
if
(
yin
<
0
){
yin
=
0
;}
if
(
xfi
>
kxx
-
1
){
xfi
=
kxx
-
1
;}
if
(
yfi
>
kyy
-
1
){
yfi
=
kyy
-
1
;}
if
(
xfi
>
xin
&&
yfi
>
yin
)
{
/* loop over the grid */
for
(
ixx
=
xin
;
ixx
<
xfi
;
ixx
++
){
for
(
iyy
=
yin
;
iyy
<
yfi
;
iyy
++
){
gaus
=
ds
*
pisig
*
exp
(
0.5
*
(
-
((
float
)(
ix
-
ixx
)
/
(
ax
*
sigma
))
*
((
float
)(
ix
-
ixx
)
/
(
ax
*
sigma
))
-
((
float
)(
iy
-
iyy
)
/
(
ay
*
sigma
))
*
((
float
)(
iy
-
iyy
)
/
(
ay
*
sigma
)))
);
sum
=
sum
+
gaus
;
dseo
[
ixx
][
iyy
]
=
dseo
[
ixx
][
iyy
]
+
gm
*
gaus
;
}
}
}
}
}
/* normalisation */
/*
if(mm!=0.){
for (ix=0;ix<kxx;ix++) {
for (iy=0;iy<kyy;iy++) {
dseo[ix][iy]=dseo[ix][iy]/mm;
}
}
}
*/
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
ky
-
j
-
1
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mapone */
/*********************************/
static
PyObject
*
mapping_mapone
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
float
xmx
,
ymx
,
xc
,
yc
,
zc
;
int
view
;
PyArrayObject
*
mat
;
int
kx
,
ky
;
int
kxx
,
kyy
;
int
kxx2
,
kyy2
;
int
n
,
i
,
j
;
int
ix
,
iy
,
xi
,
yi
,
zi
;
npy_intp
ld
[
2
];
float
ax
,
ay
,
bx
,
by
;
float
dseo
[
kxmax2d
][
kymax2d
];
float
mm
[
kxmax2d
][
kymax2d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)(ff)(fff)i"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
,
&
xmx
,
&
ymx
,
&
xc
,
&
yc
,
&
zc
,
&
view
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* set image dimension */
kxx
=
kx
;
kyy
=
ky
;
kxx2
=
kxx
/
2
;
kyy2
=
kyy
/
2
;
ax
=
kxx2
/
xmx
;
ay
=
kyy2
/
ymx
;
bx
=
kxx2
+
1.
;
by
=
kyy2
+
1.
;
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float0"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kxx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
kyy
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
mm
[
ix
][
iy
]
=
0.
;
}
}
/* choose the view */
if
(
view
==
1
){
/*xz*/
xi
=
0
;
yi
=
2
;
xc
=
xc
;
yc
=
zc
;
}
if
(
view
==
2
){
/*xy*/
xi
=
0
;
yi
=
1
;
xc
=
xc
;
yc
=
yc
;
}
if
(
view
==
3
){
/*yz*/
xi
=
1
;
yi
=
2
;
xc
=
yc
;
yc
=
zc
;
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
xi
*
pos
->
strides
[
1
])
-
xc
;
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
yi
*
pos
->
strides
[
1
])
-
yc
;
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
if
(
x
>
-
xmx
&&
x
<
xmx
)
{
if
(
y
>
-
ymx
&&
y
<
ymx
)
{
ix
=
(
int
)(
ax
*
x
+
bx
)
-
1
;
iy
=
(
int
)(
ay
*
y
+
by
)
-
1
;
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
*
am
;
mm
[
ix
][
iy
]
=
mm
[
ix
][
iy
]
+
gm
;
}
}
}
/* normalisation */
for
(
ix
=
0
;
ix
<
kxx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
kyy
;
iy
++
)
{
if
(
mm
[
ix
][
iy
]
!=
0
){
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
/
(
float
)
mm
[
ix
][
iy
];
}
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
ky
-
j
-
1
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mapn */
/*********************************/
static
PyObject
*
mapping_mapn
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
float
xmx
,
ymx
,
xc
,
yc
,
zc
;
int
view
;
PyArrayObject
*
mat
;
int
kx
,
ky
;
int
kxx
,
kyy
;
int
kxx2
,
kyy2
;
int
n
,
i
,
j
;
int
ix
,
iy
,
xi
,
yi
,
zi
;
npy_intp
ld
[
2
];
float
ax
,
ay
,
bx
,
by
;
float
dseo
[
kxmax2d
][
kymax2d
];
int
nn
[
kxmax2d
][
kymax2d
];
float
x
,
y
,
z
,
gm
,
am
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOO(ii)(ff)(fff)i"
,
&
pos
,
&
gmm
,
&
amp
,
&
kx
,
&
ky
,
&
xmx
,
&
ymx
,
&
xc
,
&
yc
,
&
zc
,
&
view
))
return
NULL
;
/* check max size of matrix */
if
(
kx
>
kxmax2d
||
ky
>
kymax2d
){
PyErr_SetString
(
PyExc_ValueError
,
"dimension of argument 3 is too large."
);
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* set image dimension */
kxx
=
kx
;
kyy
=
ky
;
kxx2
=
kxx
/
2
;
kyy2
=
kyy
/
2
;
ax
=
kxx2
/
xmx
;
ay
=
kyy2
/
ymx
;
bx
=
kxx2
+
1.
;
by
=
kyy2
+
1.
;
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float0"
);
return
NULL
;
}
/* number of particules */
n
=
pos
->
dimensions
[
0
];
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kxx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
kyy
;
iy
++
)
{
dseo
[
ix
][
iy
]
=
0.
;
nn
[
ix
][
iy
]
=
0
;
}
}
/* choose the view */
if
(
view
==
1
){
/*xz*/
xi
=
0
;
yi
=
2
;
xc
=
xc
;
yc
=
zc
;
}
if
(
view
==
2
){
/*xy*/
xi
=
0
;
yi
=
1
;
xc
=
xc
;
yc
=
yc
;
}
if
(
view
==
3
){
/*yz*/
xi
=
1
;
yi
=
2
;
xc
=
yc
;
yc
=
zc
;
}
/* full dseo : loop over all points in pos*/
for
(
i
=
0
;
i
<
pos
->
dimensions
[
0
];
i
++
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
xi
*
pos
->
strides
[
1
])
-
xc
;
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
yi
*
pos
->
strides
[
1
])
-
yc
;
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
if
(
x
>
-
xmx
&&
x
<
xmx
)
{
if
(
y
>
-
ymx
&&
y
<
ymx
)
{
ix
=
(
int
)(
ax
*
x
+
bx
)
-
1
;
iy
=
(
int
)(
ay
*
y
+
by
)
-
1
;
dseo
[
ix
][
iy
]
=
dseo
[
ix
][
iy
]
+
gm
*
am
;
nn
[
ix
][
iy
]
=
nn
[
ix
][
iy
]
+
1
;
}
}
}
// /* check the statistic */
// for (ix=0;ix<kxx;ix++) {
// for (iy=0;iy<kyy;iy++) {
// if(nn[ix][iy]<=2){
// dseo[ix][iy]=0.;
// }
// }
// }
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
ky
-
j
-
1
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
i
][
j
]
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* mkmap3dnsph */
/*********************************/
#define KERNEL_COEFF_1 2.546479089470
#define KERNEL_COEFF_2 15.278874536822
#define KERNEL_COEFF_5 5.092958178941
/*! returns the maximum of two integers
*/
int
imax
(
int
x
,
int
y
)
{
if
(
x
>
y
)
return
x
;
else
return
y
;
}
/*! returns the minimum of two integers
*/
int
imin
(
int
x
,
int
y
)
{
if
(
x
<
y
)
return
x
;
else
return
y
;
}
static
PyObject
*
mapping_mkmap3dslicesph
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
rsp
=
NULL
;
PyArrayObject
*
mat
;
int
kx
,
ky
,
kz
;
float
xmin
,
xmax
,
ymin
,
ymax
,
zmin
,
zmax
;
int
n
,
i
,
j
,
k
;
int
ix
,
iy
,
iz
;
npy_intp
ld
[
2
];
int
izz
;
float
*
dseo
;
float
x
,
y
,
z
,
gm
,
am
,
r
;
float
xx
,
yy
,
zz
;
float
fx
,
fy
,
fz
;
size_t
bytes
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOOO(iii)(ff)(ff)(ff)i"
,
&
pos
,
&
gmm
,
&
amp
,
&
rsp
,
&
kx
,
&
ky
,
&
kz
,
&
xmin
,
&
xmax
,
&
ymin
,
&
ymax
,
&
zmin
,
&
zmax
,
&
izz
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
ky
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
ix
*
ky
+
iy
]
=
0.
;
}
}
n
=
pos
->
dimensions
[
0
];
/* some constants */
fx
=
(
kx
-
1
)
/
(
xmax
-
xmin
);
fy
=
(
ky
-
1
)
/
(
ymax
-
ymin
);
fz
=
(
kz
-
1
)
/
(
zmax
-
zmin
);
/* set xmin,ymin,zmin for each particles */
/* first slice */
int
ixx
,
iyy
;
int
iz1
,
iz2
;
float
wk
;
float
h
,
u
;
float
hinv3
;
iz1
=
0
;
iz2
=
1
;
int
ixmin
,
ixmax
;
int
iymin
,
iymax
;
int
izmin
,
izmax
;
/* loop over all particles */
for
(
i
=
0
;
i
<
n
;
i
++
)
{
z
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
2
*
pos
->
strides
[
1
]);
h
=
*
(
float
*
)
(
rsp
->
data
+
i
*
(
rsp
->
strides
[
0
]));
izmin
=
(
int
)
(((
z
-
h
)
-
zmin
)
*
fz
);
izmax
=
(
int
)
(((
z
+
h
)
-
zmin
)
*
fz
);
izmin
=
imax
(
izmin
,
0
);
izmax
=
imin
(
izmax
,
kz
-
1
);
if
(
(
izz
>=
izmin
)
&&
(
izz
<=
izmax
)
)
{
x
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
]);
y
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
]);
gm
=
*
(
float
*
)
(
gmm
->
data
+
i
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
i
*
(
amp
->
strides
[
0
]));
ixmin
=
(
int
)
(((
x
-
h
)
-
xmin
)
*
fx
);
ixmax
=
(
int
)
(((
x
+
h
)
-
xmin
)
*
fx
);
ixmin
=
imax
(
ixmin
,
0
);
ixmax
=
imin
(
ixmax
,
kx
-
1
);
iymin
=
(
int
)
(((
y
-
h
)
-
ymin
)
*
fy
);
iymax
=
(
int
)
(((
y
+
h
)
-
ymin
)
*
fy
);
iymin
=
imax
(
iymin
,
0
);
iymax
=
imin
(
iymax
,
ky
-
1
);
hinv3
=
1.0
/
(
h
*
h
*
h
)
*
(
xmax
-
xmin
)
/
kx
*
(
ymax
-
ymin
)
/
ky
*
(
zmax
-
zmin
)
/
kz
;
if
((
ixmin
==
ixmax
)
&&
(
iymin
==
iymax
)
&&
(
izmin
==
izmax
))
{
dseo
[
ixmin
*
ky
+
iymin
]
=
dseo
[
ixmin
*
ky
+
iymin
]
+
gm
*
am
;
continue
;
}
/* loop over the grid */
for
(
ixx
=
ixmin
;
ixx
<=
ixmax
;
ixx
++
)
{
for
(
iyy
=
iymin
;
iyy
<=
iymax
;
iyy
++
)
{
xx
=
(
ixx
/
fx
)
+
xmin
;
/* physical coordinate */
yy
=
(
iyy
/
fy
)
+
ymin
;
zz
=
(
izz
/
fz
)
+
zmin
;
r
=
sqrt
(
(
x
-
xx
)
*
(
x
-
xx
)
+
(
y
-
yy
)
*
(
y
-
yy
)
+
(
z
-
zz
)
*
(
z
-
zz
)
);
u
=
r
/
h
;
if
(
u
<
1
)
{
if
(
u
<
0.5
)
wk
=
hinv3
*
(
KERNEL_COEFF_1
+
KERNEL_COEFF_2
*
(
u
-
1
)
*
u
*
u
);
else
wk
=
hinv3
*
KERNEL_COEFF_5
*
(
1.0
-
u
)
*
(
1.0
-
u
)
*
(
1.0
-
u
);
dseo
[
ixx
*
ky
+
iyy
]
=
dseo
[
ixx
*
ky
+
iyy
]
+
gm
*
am
*
wk
;
}
}
}
}
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
j
+
i
*
ky
]
;
}
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
struct
points
{
int
index
;
float
h
;
float
z
;
float
izmin
;
float
izmax
;
int
next
;
int
prev
;
};
static
PyObject
*
mapping_mkmap3dsortedsph
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
pos
=
NULL
;
PyArrayObject
*
gmm
=
NULL
;
PyArrayObject
*
amp
=
NULL
;
PyArrayObject
*
rsp
=
NULL
;
PyArrayObject
*
mat
;
int
kx
,
ky
,
kz
;
float
xmin
,
xmax
,
ymin
,
ymax
,
zmin
,
zmax
;
int
n
,
i
,
j
,
k
;
int
ix
,
iy
,
iz
;
npy_intp
ld
[
2
];
int
izz
;
float
*
dseo
;
float
x
,
y
,
z
,
gm
,
am
,
r
;
float
xx
,
yy
,
zz
;
float
fx
,
fy
,
fz
;
struct
points
*
P
;
int
nP
;
size_t
bytes
;
if
(
!
PyArg_ParseTuple
(
args
,
"OOOO(iii)(ff)(ff)(ff)"
,
&
pos
,
&
gmm
,
&
amp
,
&
rsp
,
&
kx
,
&
ky
,
&
kz
,
&
xmin
,
&
xmax
,
&
ymin
,
&
ymax
,
&
zmin
,
&
zmax
))
return
NULL
;
if
(
!
(
dseo
=
malloc
(
bytes
=
kx
*
ky
*
sizeof
(
float
))))
{
printf
(
"failed to allocate memory for `dseo' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
n
=
pos
->
dimensions
[
0
];
/* allocate memory for P */
if
(
!
(
P
=
malloc
(
bytes
=
n
*
sizeof
(
struct
points
))))
{
printf
(
"failed to allocate memory for `P' (%g MB).
\n
"
,
bytes
/
(
1024.0
*
1024.0
));
return
NULL
;
}
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
/* check the size of pos */
if
(
pos
->
nd
!=
2
||
pos
->
descr
->
type_num
!=
PyArray_FLOAT
)
{
PyErr_SetString
(
PyExc_ValueError
,
"argument 1 must be two dimentionnal and of type Float32"
);
return
NULL
;
}
/* initialisation of dseo */
for
(
ix
=
0
;
ix
<
kx
;
ix
++
)
{
for
(
iy
=
0
;
iy
<
ky
;
iy
++
)
{
dseo
[
ix
*
ky
+
iy
]
=
0.
;
}
}
/* some constants */
fx
=
(
kx
-
1
)
/
(
xmax
-
xmin
);
fy
=
(
ky
-
1
)
/
(
ymax
-
ymin
);
fz
=
(
kz
-
1
)
/
(
zmax
-
zmin
);
/* set xmin,ymin,zmin for each particles */
/* first slice */
int
ixx
,
iyy
;
int
iz1
,
iz2
;
float
wk
;
float
h
,
u
;
float
hinv3
;
iz1
=
0
;
iz2
=
1
;
int
ixmin
,
ixmax
;
int
iymin
,
iymax
;
int
izmin
,
izmax
;
int
istart
;
int
nAdded
;
nP
=
0
;
nAdded
=
0
;
istart
=
0
;
for
(
iz
=
0
;
izz
<
kz
;
izz
++
)
{
i
=
nAdded
;
/* index of first particle not added */
do
{
if
(
i
==
n
)
/* no particles left to add */
break
;
z
=
*
(
float
*
)
(
pos
->
data
+
i
*
(
pos
->
strides
[
0
])
+
2
*
pos
->
strides
[
1
]);
h
=
*
(
float
*
)
(
rsp
->
data
+
i
*
(
rsp
->
strides
[
0
]));
izmin
=
imax
((
int
)
(((
z
-
h
)
-
zmin
)
*
fz
),
0
);
izmax
=
imin
((
int
)
(((
z
+
h
)
-
zmin
)
*
fz
),
kz
-
1
);
if
(
izmin
>
izz
)
/* the next particle is not in the slice, do nothing */
break
;
/* the particle enter the slice, add it */
P
[
i
].
index
=
i
;
P
[
i
].
z
=
z
;
P
[
i
].
h
=
h
;
P
[
i
].
izmin
=
izmin
;
P
[
i
].
izmax
=
izmax
;
/********************************/
/* set its position in the list */
/********************************/
/* default, first one */
if
(
nP
==
0
)
{
P
[
i
].
next
=-
1
;
}
else
{
P
[
i
].
next
=
istart
;
P
[
istart
].
prev
=
i
;
}
P
[
i
].
prev
=-
1
;
istart
=
i
;
nAdded
++
;
nP
++
;
i
++
;
/* move to next particle */
}
while
(
1
);
/***************************************/
/* loop over all particles in the list */
/***************************************/
i
=
istart
;
//printf("(%d) nP=%d\n",izz,nP);
if
(
nP
>
0
)
do
{
z
=
P
[
i
].
z
;
izmin
=
P
[
i
].
izmin
;
izmax
=
P
[
i
].
izmax
;
h
=
P
[
i
].
h
;
/* do the particle */
if
(
izmax
<
izz
)
/* the part leaves the slice */
{
if
(
nP
==
1
)
{
/* do nothing */
}
else
{
/* remove it from the list */
if
(
P
[
i
].
prev
==-
1
)
/* first one */
{
istart
=
P
[
i
].
next
;
P
[
istart
].
prev
=
-
1
;
}
else
{
if
(
P
[
i
].
next
==-
1
)
/* last one */
{
P
[
P
[
i
].
prev
].
next
=
-
1
;
}
else
/* one in the middle */
{
P
[
P
[
i
].
prev
].
next
=
P
[
i
].
next
;
P
[
P
[
i
].
next
].
prev
=
P
[
i
].
prev
;
}
}
}
nP
--
;
}
else
{
x
=
*
(
float
*
)
(
pos
->
data
+
P
[
i
].
index
*
(
pos
->
strides
[
0
])
+
0
*
pos
->
strides
[
1
]);
y
=
*
(
float
*
)
(
pos
->
data
+
P
[
i
].
index
*
(
pos
->
strides
[
0
])
+
1
*
pos
->
strides
[
1
]);
gm
=
*
(
float
*
)
(
gmm
->
data
+
P
[
i
].
index
*
(
gmm
->
strides
[
0
]));
am
=
*
(
float
*
)
(
amp
->
data
+
P
[
i
].
index
*
(
amp
->
strides
[
0
]));
ixmin
=
(
int
)
(((
x
-
h
)
-
xmin
)
*
fx
);
ixmax
=
(
int
)
(((
x
+
h
)
-
xmin
)
*
fx
);
ixmin
=
imax
(
ixmin
,
0
);
ixmax
=
imin
(
ixmax
,
kx
-
1
);
iymin
=
(
int
)
(((
y
-
h
)
-
ymin
)
*
fy
);
iymax
=
(
int
)
(((
y
+
h
)
-
ymin
)
*
fy
);
iymin
=
imax
(
iymin
,
0
);
iymax
=
imin
(
iymax
,
ky
-
1
);
hinv3
=
1.0
/
(
h
*
h
*
h
)
*
(
xmax
-
xmin
)
/
kx
*
(
ymax
-
ymin
)
/
ky
*
(
zmax
-
zmin
)
/
kz
;
/* loop over the grid */
for
(
ixx
=
ixmin
;
ixx
<=
ixmax
;
ixx
++
)
{
for
(
iyy
=
iymin
;
iyy
<=
iymax
;
iyy
++
)
{
xx
=
(
ixx
/
fx
)
+
xmin
;
/* physical coordinate */
yy
=
(
iyy
/
fy
)
+
ymin
;
zz
=
(
izz
/
fz
)
+
zmin
;
r
=
sqrt
(
(
x
-
xx
)
*
(
x
-
xx
)
+
(
y
-
yy
)
*
(
y
-
yy
)
+
(
z
-
zz
)
*
(
z
-
zz
)
);
u
=
r
/
h
;
if
(
u
<
1
)
{
if
(
u
<
0.5
)
wk
=
hinv3
*
(
KERNEL_COEFF_1
+
KERNEL_COEFF_2
*
(
u
-
1
)
*
u
*
u
);
else
wk
=
hinv3
*
KERNEL_COEFF_5
*
(
1.0
-
u
)
*
(
1.0
-
u
)
*
(
1.0
-
u
);
dseo
[
ixx
*
ky
+
iyy
]
=
dseo
[
ixx
*
ky
+
iyy
]
+
gm
*
am
*
wk
;
}
}
}
}
i
=
P
[
i
].
next
;
}
while
(
i
!=-
1
);
}
/* create the subimage */
for
(
j
=
0
;
j
<
ky
;
j
++
)
{
for
(
i
=
0
;
i
<
kx
;
i
++
)
{
*
(
float
*
)(
mat
->
data
+
i
*
(
mat
->
strides
[
0
])
+
(
j
)
*
(
mat
->
strides
[
1
]))
=
(
float
)
dseo
[
j
+
i
*
ky
]
;
}
}
free
(
dseo
);
return
PyArray_Return
(
mat
);
}
/*********************************/
/* create_line */
/*********************************/
/* http://graphics.lcs.mit.edu/~mcmillan/comp136/Lecture6/Lines.html */
static
PyObject
*
mapping_create_line
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
mat
=
NULL
;
int
x0
,
y0
,
x1
,
y1
,
color
,
width
;
int
dy
=
y1
-
y0
;
int
dx
=
x1
-
x0
;
int
stepx
,
stepy
;
if
(
!
PyArg_ParseTuple
(
args
,
"Oiiiii"
,
&
mat
,
&
x0
,
&
y0
,
&
x1
,
&
y1
,
&
color
))
return
NULL
;
/* create the output */
dy
=
y1
-
y0
;
dx
=
x1
-
x0
;
width
=
1
;
if
(
dy
<
0
)
{
dy
=
-
dy
;
stepy
=
-
width
;
}
else
{
stepy
=
width
;
}
if
(
dx
<
0
)
{
dx
=
-
dx
;
stepx
=
-
1
;
}
else
{
stepx
=
1
;
}
dy
<<=
1
;
dx
<<=
1
;
y0
*=
width
;
y1
*=
width
;
*
(
float
*
)(
mat
->
data
+
x0
*
(
mat
->
strides
[
0
])
+
y0
*
mat
->
strides
[
1
])
=
(
float
)
color
;
if
(
dx
>
dy
)
{
int
fraction
=
dy
-
(
dx
>>
1
);
while
(
x0
!=
x1
)
{
if
(
fraction
>=
0
)
{
y0
+=
stepy
;
fraction
-=
dx
;
}
x0
+=
stepx
;
fraction
+=
dy
;
*
(
float
*
)(
mat
->
data
+
x0
*
(
mat
->
strides
[
0
])
+
y0
*
mat
->
strides
[
1
])
=
(
float
)
color
;
}
}
else
{
int
fraction
=
dx
-
(
dy
>>
1
);
while
(
y0
!=
y1
)
{
if
(
fraction
>=
0
)
{
x0
+=
stepx
;
fraction
-=
dy
;
}
y0
+=
stepy
;
fraction
+=
dx
;
*
(
float
*
)(
mat
->
data
+
x0
*
(
mat
->
strides
[
0
])
+
y0
*
mat
->
strides
[
1
])
=
(
float
)
color
;
}
}
return
Py_BuildValue
(
"i"
,
1
);
}
/*********************************/
/* create_line */
/*********************************/
static
PyObject
*
mapping_create_line2
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
PyArrayObject
*
mat
;
npy_intp
ld
[
2
];
int
kx
,
ky
,
x1
,
y1
,
x2
,
y2
,
color
;
int
i
;
// loop counter
int
ystep
,
xstep
;
// the step on y and x axis
int
error
;
// the error accumulated during the increment
int
errorprev
;
// *vision the previous value of the error variable
int
x
,
y
;
// the line points
int
ddy
,
ddx
;
// compulsory variables: the double values of dy and dx
int
dx
;
int
dy
;
if
(
!
PyArg_ParseTuple
(
args
,
"iiiiiii"
,
&
kx
,
&
ky
,
&
x1
,
&
y1
,
&
x2
,
&
y2
,
&
color
))
return
NULL
;
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
y
=
y1
;
x
=
x1
;
dx
=
x2
-
x1
;
dy
=
y2
-
y1
;
*
(
short
*
)(
mat
->
data
+
x1
*
(
mat
->
strides
[
0
])
+
y1
*
mat
->
strides
[
1
])
=
color
;
// NB the last point can't be here, because of its previous point (which has to be verified)
if
(
dy
<
0
){
ystep
=
-
1
;
dy
=
-
dy
;
}
else
ystep
=
1
;
if
(
dx
<
0
){
xstep
=
-
1
;
dx
=
-
dx
;
}
else
xstep
=
1
;
ddy
=
2
*
dy
;
// work with double values for full precision
ddx
=
2
*
dx
;
if
(
ddx
>=
ddy
){
// first octant (0 <= slope <= 1)
// compulsory initialization (even for errorprev, needed when dx==dy)
errorprev
=
error
=
dx
;
// start in the middle of the square
for
(
i
=
0
;
i
<
dx
;
i
++
){
// do not use the first point (already done)
x
+=
xstep
;
error
+=
ddy
;
if
(
error
>
ddx
){
// increment y if AFTER the middle ( > )
y
+=
ystep
;
error
-=
ddx
;
// three cases (octant == right->right-top for directions below):
if
(
error
+
errorprev
<
ddx
)
// bottom square also
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
-
ystep
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
else
if
(
error
+
errorprev
>
ddx
)
// left square also
*
(
float
*
)(
mat
->
data
+
(
x
-
xstep
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
else
{
// corner: bottom and left squares also
*
(
short
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
-
ystep
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
*
(
short
*
)(
mat
->
data
+
(
x
-
xstep
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
}
}
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
errorprev
=
error
;
}
}
else
{
// the same as above
errorprev
=
error
=
dy
;
for
(
i
=
0
;
i
<
dy
;
i
++
){
y
+=
ystep
;
error
+=
ddx
;
if
(
error
>
ddy
){
x
+=
xstep
;
error
-=
ddy
;
if
(
error
+
errorprev
<
ddy
)
*
(
float
*
)(
mat
->
data
+
(
x
-
xstep
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
else
if
(
error
+
errorprev
>
ddy
)
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
-
ystep
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
else
{
*
(
float
*
)(
mat
->
data
+
(
x
-
xstep
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
-
ystep
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
}
}
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
errorprev
=
error
;
}
}
return
PyArray_Return
(
mat
);
}
/*********************************/
/* create_line */
/*********************************/
static
PyObject
*
mapping_create_line3
(
self
,
args
)
PyObject
*
self
;
PyObject
*
args
;
{
int
kx
,
ky
,
x0
,
y0
,
x1
,
y1
,
color
;
PyArrayObject
*
mat
;
float
a
,
b
;
int
x
,
y
,
dx
;
int
n
,
lx
,
ly
,
s0
,
s1
,
inv
;
npy_intp
ld
[
2
];
if
(
!
PyArg_ParseTuple
(
args
,
"iiiiiii"
,
&
kx
,
&
ky
,
&
x0
,
&
y0
,
&
x1
,
&
y1
,
&
color
))
return
NULL
;
/* create the output */
ld
[
0
]
=
kx
;
ld
[
1
]
=
ky
;
mat
=
(
PyArrayObject
*
)
PyArray_SimpleNew
(
2
,
ld
,
NPY_FLOAT
);
if
(
x0
==
x1
&&
y0
==
y1
)
{
*
(
float
*
)(
mat
->
data
+
(
x0
)
*
(
mat
->
strides
[
0
])
+
(
y0
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
return
Py_BuildValue
(
"i"
,
0
);
}
lx
=
abs
(
x1
-
x0
);
ly
=
abs
(
y1
-
y0
);
inv
=
0
;
if
(
lx
<
ly
)
{
/* swap x,y */
s0
=
x0
;
s1
=
x1
;
x0
=
y0
;
x1
=
y1
;
y0
=
s0
;
y1
=
s1
;
inv
=
1
;
}
a
=
(
float
)(
y0
-
y1
)
/
(
float
)(
x0
-
x1
);
b
=
(
float
)(
x0
*
y1
-
y0
*
x1
)
/
(
float
)(
x0
-
x1
);
/* dx */
if
(
x1
>
x0
)
{
dx
=
1
;}
else
{
dx
=-
1
;}
/* main loop */
x
=
x0
;
while
(
x
!=
x1
)
{
y
=
(
int
)
(
a
*
(
float
)
x
+
b
);
if
(
inv
){
*
(
float
*
)(
mat
->
data
+
(
y
)
*
(
mat
->
strides
[
0
])
+
(
x
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
//printf("- %d %d\n",y,x);
}
else
{
*
(
float
*
)(
mat
->
data
+
(
x
)
*
(
mat
->
strides
[
0
])
+
(
y
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
//printf("%d %d\n",x,y);
}
x
=
x
+
dx
;
}
/* last point */
if
(
inv
){
*
(
float
*
)(
mat
->
data
+
(
y1
)
*
(
mat
->
strides
[
0
])
+
(
x1
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
//printf("- %d %d\n",y1,x1);
}
else
{
*
(
float
*
)(
mat
->
data
+
(
x1
)
*
(
mat
->
strides
[
0
])
+
(
y1
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
//printf("%d %d\n",x1,y1);
}
*
(
float
*
)(
mat
->
data
+
(
96
)
*
(
mat
->
strides
[
0
])
+
(
73
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
*
(
float
*
)(
mat
->
data
+
(
94
)
*
(
mat
->
strides
[
0
])
+
(
76
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
*
(
float
*
)(
mat
->
data
+
(
92
)
*
(
mat
->
strides
[
0
])
+
(
79
)
*
mat
->
strides
[
1
])
=
(
float
)
color
;
return
PyArray_Return
(
mat
);
}
/* definition of the method table */
static
PyMethodDef
mappingMethods
[]
=
{
{
"mkmap1d"
,
mapping_mkmap1dn
,
METH_VARARGS
,
"Return a 1d mapping."
},
{
"mkmap1dn"
,
mapping_mkmap1dn
,
METH_VARARGS
,
"Return a 1d mapping."
},
{
"mkmap2d"
,
mapping_mkmap2dn
,
METH_VARARGS
,
"Return a 2d mapping."
},
{
"mkmap2dn"
,
mapping_mkmap2dn
,
METH_VARARGS
,
"Return a 2d mapping."
},
{
"mkmap3d"
,
mapping_mkmap3dn
,
METH_VARARGS
,
"Return a 3d mapping."
},
{
"mkmap3dn"
,
mapping_mkmap3dn
,
METH_VARARGS
,
"Return a 3d mapping."
},
{
"mkmap3dslicesph"
,
mapping_mkmap3dslicesph
,
METH_VARARGS
,
"Return a 3d slice (sph)."
},
{
"mkmap3dsortedsph"
,
mapping_mkmap3dsortedsph
,
METH_VARARGS
,
"Return a 3d mapping (sph)."
},
{
"mkmap1dw"
,
mapping_mkmap1dw
,
METH_VARARGS
,
"Return a 1d mapping (a particle is distributed over 2 nodes)."
},
{
"mkmap2dw"
,
mapping_mkmap2dw
,
METH_VARARGS
,
"Return a 2d mapping (a particle is distributed over 4 nodes)."
},
{
"mkmap3dw"
,
mapping_mkmap3dw
,
METH_VARARGS
,
"Return a 3d mapping (a particle is distributed over 8 nodes)."
},
{
"mkmap2dsph"
,
mapping_mkmap2dnsph
,
METH_VARARGS
,
"Return a 2d smoothed maping."
},
{
"mkmap2dnsph"
,
mapping_mkmap2dnsph
,
METH_VARARGS
,
"Return a 2d smoothed maping."
},
//{"mapzero", mapping_mapzero, METH_VARARGS,
// "Return the zero momentum. (obsolete)"},
//{"mapzerosph", mapping_mapzerosph, METH_VARARGS,
// "Return the zero momentum (softned) (obsolete)."},
//{"mapone", mapping_mapone, METH_VARARGS,
// "Return the first momentum (obsolete)."},
//{"mapn", mapping_mapn, METH_VARARGS,
// "Return the first momentum (not normalized) (obsolete)."},
{
"create_line"
,
mapping_create_line
,
METH_VARARGS
,
"Add a line in the given matrice using the Bresenham algorithm."
},
{
"create_line2"
,
mapping_create_line2
,
METH_VARARGS
,
"Add a line in the given matrice using the Bresenham algorithm."
},
{
"create_line3"
,
mapping_create_line3
,
METH_VARARGS
,
"Add a line in the given matrice using a personal algorithm."
},
{
NULL
,
NULL
,
0
,
NULL
}
/* Sentinel */
};
void
initmapping
(
void
)
{
(
void
)
Py_InitModule
(
"mapping"
,
mappingMethods
);
import_array
();
}
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