Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F92429577
py_engine.py
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Wed, Nov 20, 05:43
Size
16 KB
Mime Type
text/x-python
Expires
Fri, Nov 22, 05:43 (2 d)
Engine
blob
Format
Raw Data
Handle
22259705
Attached To
rAKA akantu
py_engine.py
View Options
#!/usr/bin/env python3
""" py_engine.py: feengine tester"""
__author__
=
"Nicolas Richart"
__credits__
=
[
"Nicolas Richart <nicolas.richart@epfl.ch>"
,
]
__copyright__
=
"Copyright (©) 2016-2021 EPFL (Ecole Polytechnique Fédérale"
\
" de Lausanne) Laboratory (LSMS - Laboratoire de Simulation"
\
" en Mécanique des Solides)"
__license__
=
"LGPLv3"
__all__
=
[
'Shapes'
]
import
numpy
as
np
import
numpy.polynomial.polynomial
as
poly
# pylint: disable=missing-docstring, invalid-name, too-many-instance-attributes
# flake8: noqa
class
Shapes
:
"""Python version of the shape functions for test purposes"""
# pylint: disable=bad-whitespace, line-too-long
NATURAL_COORDS
=
{
(
1
,
'quadrangle'
):
np
.
array
([[
-
1.
],
[
1.
],
[
0.
]]),
(
2
,
'quadrangle'
):
np
.
array
([[
-
1.
,
-
1.
],
[
1.
,
-
1.
],
[
1.
,
1.
],
[
-
1.
,
1.
],
[
0.
,
-
1.
],
[
1.
,
0.
],
[
0.
,
1.
],
[
-
1.
,
0.
]]),
(
3
,
'quadrangle'
):
np
.
array
([[
-
1.
,
-
1.
,
-
1.
],
[
1.
,
-
1.
,
-
1.
],
[
1.
,
1.
,
-
1.
],
[
-
1.
,
1.
,
-
1.
],
[
-
1.
,
-
1.
,
1.
],
[
1.
,
-
1.
,
1.
],
[
1.
,
1.
,
1.
],
[
-
1.
,
1.
,
1.
],
[
0.
,
-
1.
,
-
1.
],
[
1.
,
0.
,
-
1.
],
[
0.
,
1.
,
-
1.
],
[
-
1.
,
0.
,
-
1.
],
[
-
1.
,
-
1.
,
0.
],
[
1.
,
-
1.
,
0.
],
[
1.
,
1.
,
0.
],
[
-
1.
,
1.
,
0.
],
[
0.
,
-
1.
,
1.
],
[
1.
,
0.
,
1.
],
[
0.
,
1.
,
1.
],
[
-
1.
,
0.
,
1.
]]),
(
2
,
'triangle'
):
np
.
array
([[
0.
,
0.
],
[
1.
,
0.
],
[
0.
,
1
],
[
.
5
,
0.
],
[
.
5
,
.
5
],
[
0.
,
.
5
]]),
(
3
,
'triangle'
):
np
.
array
([[
0.
,
0.
,
0.
],
[
1.
,
0.
,
0.
],
[
0.
,
1.
,
0.
],
[
0.
,
0.
,
1.
],
[
.
5
,
0.
,
0.
],
[
.
5
,
.
5
,
0.
],
[
0.
,
.
5
,
0.
],
[
0.
,
0.
,
.
5
],
[
.
5
,
0.
,
.
5
],
[
0.
,
.
5
,
.
5
]]),
(
3
,
'pentahedron'
):
np
.
array
([[
-
1.
,
1.
,
0.
],
[
-
1.
,
0.
,
1.
],
[
-
1.
,
0.
,
0.
],
[
1.
,
1.
,
0.
],
[
1.
,
0.
,
1.
],
[
1.
,
0.
,
0.
],
[
-
1.
,
.
5
,
.
5
],
[
-
1.
,
0.
,
.
5
],
[
-
1.
,
.
5
,
0.
],
[
0.
,
1.
,
0.
],
[
0.
,
0.
,
1.
],
[
0.
,
0.
,
0.
],
[
1.
,
.
5
,
.
5
],
[
1.
,
0.
,
.
5
],
[
1.
,
.
5
,
0.
],
[
0.
,
.
5
,
.
5
],
[
0.
,
0.
,
.
5
],
[
0.
,
.
5
,
0.
]]),
}
QUADRATURE_W
=
{
(
1
,
'quadrangle'
,
1
):
np
.
array
([
2.
]),
(
1
,
'quadrangle'
,
2
):
np
.
array
([
1.
,
1.
]),
(
2
,
'triangle'
,
1
):
np
.
array
([
1.
/
2.
]),
(
2
,
'triangle'
,
2
):
np
.
array
([
1.
,
1.
,
1.
])
/
6.
,
(
3
,
'triangle'
,
1
):
np
.
array
([
1.
/
6.
]),
(
3
,
'triangle'
,
2
):
np
.
array
([
1.
,
1.
,
1.
,
1.
])
/
24.
,
(
2
,
'quadrangle'
,
1
):
np
.
array
([
1.
,
1.
,
1.
,
1.
]),
(
2
,
'quadrangle'
,
2
):
np
.
array
([
1.
,
1.
,
1.
,
1.
]),
(
3
,
'quadrangle'
,
1
):
np
.
array
([
1.
,
1.
,
1.
,
1.
,
1.
,
1.
,
1.
,
1.
]),
(
3
,
'quadrangle'
,
2
):
np
.
array
([
1.
,
1.
,
1.
,
1.
,
1.
,
1.
,
1.
,
1.
]),
(
3
,
'pentahedron'
,
1
):
np
.
array
([
1.
,
1.
,
1.
,
1.
,
1.
,
1.
])
/
6.
,
(
3
,
'pentahedron'
,
2
):
np
.
array
([
1.
,
1.
,
1.
,
1.
,
1.
,
1.
])
/
6.
,
}
_tet_a
=
(
5.
-
np
.
sqrt
(
5.
))
/
20.
_tet_b
=
(
5.
+
3.
*
np
.
sqrt
(
5.
))
/
20.
QUADRATURE_G
=
{
(
1
,
'quadrangle'
,
1
):
np
.
array
([[
0.
]]),
(
1
,
'quadrangle'
,
2
):
np
.
array
([[
-
1.
],
[
1.
]])
/
np
.
sqrt
(
3.
),
(
2
,
'triangle'
,
1
):
np
.
array
([[
1.
,
1.
]])
/
3.
,
(
2
,
'triangle'
,
2
):
np
.
array
([[
1.
/
6.
,
1.
/
6.
],
[
2.
/
3
,
1.
/
6
],
[
1.
/
6.
,
2.
/
3.
]]),
(
3
,
'triangle'
,
1
):
np
.
array
([[
1.
,
1.
,
1.
]])
/
4.
,
(
3
,
'triangle'
,
2
):
np
.
array
([[
_tet_a
,
_tet_a
,
_tet_a
],
[
_tet_b
,
_tet_a
,
_tet_a
],
[
_tet_a
,
_tet_b
,
_tet_a
],
[
_tet_a
,
_tet_a
,
_tet_b
]]),
(
2
,
'quadrangle'
,
1
):
np
.
array
([[
-
1.
,
-
1.
],
[
1.
,
-
1.
],
[
-
1.
,
1.
],
[
1.
,
1.
]])
/
np
.
sqrt
(
3.
),
(
2
,
'quadrangle'
,
2
):
np
.
array
([[
-
1.
,
-
1.
],
[
1.
,
-
1.
],
[
-
1.
,
1.
],
[
1.
,
1.
]])
/
np
.
sqrt
(
3.
),
(
3
,
'quadrangle'
,
1
):
np
.
array
([[
-
1.
,
-
1.
,
-
1.
],
[
1.
,
-
1.
,
-
1.
],
[
-
1.
,
1.
,
-
1.
],
[
1.
,
1.
,
-
1.
],
[
-
1.
,
-
1.
,
1.
],
[
1.
,
-
1.
,
1.
],
[
-
1.
,
1.
,
1.
],
[
1.
,
1.
,
1.
]])
/
np
.
sqrt
(
3.
),
(
3
,
'quadrangle'
,
2
):
np
.
array
([[
-
1.
,
-
1.
,
-
1.
],
[
1.
,
-
1.
,
-
1.
],
[
-
1.
,
1.
,
-
1.
],
[
1.
,
1.
,
-
1.
],
[
-
1.
,
-
1.
,
1.
],
[
1.
,
-
1.
,
1.
],
[
-
1.
,
1.
,
1.
],
[
1.
,
1.
,
1.
]])
/
np
.
sqrt
(
3.
),
(
3
,
'pentahedron'
,
1
):
np
.
array
([[
-
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
1.
/
6.
],
[
-
1.
/
np
.
sqrt
(
3.
),
2.
/
3.
,
1.
/
6.
],
[
-
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
2.
/
3.
],
[
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
1.
/
6.
],
[
1.
/
np
.
sqrt
(
3.
),
2.
/
3.
,
1.
/
6.
],
[
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
2.
/
3.
]]),
(
3
,
'pentahedron'
,
2
):
np
.
array
([[
-
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
1.
/
6.
],
[
-
1.
/
np
.
sqrt
(
3.
),
2.
/
3.
,
1.
/
6.
],
[
-
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
2.
/
3.
],
[
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
1.
/
6.
],
[
1.
/
np
.
sqrt
(
3.
),
2.
/
3.
,
1.
/
6.
],
[
1.
/
np
.
sqrt
(
3.
),
1.
/
6.
,
2.
/
3.
]]),
}
ELEMENT_TYPES
=
{
'_segment_2'
:
(
'quadrangle'
,
1
,
'lagrange'
,
1
,
2
),
'_segment_3'
:
(
'quadrangle'
,
2
,
'lagrange'
,
1
,
3
),
'_triangle_3'
:
(
'triangle'
,
1
,
'lagrange'
,
2
,
3
),
'_triangle_6'
:
(
'triangle'
,
2
,
'lagrange'
,
2
,
6
),
'_quadrangle_4'
:
(
'quadrangle'
,
1
,
'serendip'
,
2
,
4
),
'_quadrangle_8'
:
(
'quadrangle'
,
2
,
'serendip'
,
2
,
8
),
'_tetrahedron_4'
:
(
'triangle'
,
1
,
'lagrange'
,
3
,
4
),
'_tetrahedron_10'
:
(
'triangle'
,
2
,
'lagrange'
,
3
,
10
),
'_pentahedron_6'
:
(
'pentahedron'
,
1
,
'lagrange'
,
3
,
6
),
'_pentahedron_15'
:
(
'pentahedron'
,
2
,
'lagrange'
,
3
,
15
),
'_hexahedron_8'
:
(
'quadrangle'
,
1
,
'serendip'
,
3
,
8
),
'_hexahedron_20'
:
(
'quadrangle'
,
2
,
'serendip'
,
3
,
20
),
}
MONOMES
=
{(
1
,
'quadrangle'
):
np
.
array
([[
0
],
[
1
],
[
2
],
[
3
],
[
4
],
[
5
]]),
(
2
,
'triangle'
):
np
.
array
([[
0
,
0
],
# 1
[
1
,
0
],
[
0
,
1
],
# x y
[
2
,
0
],
[
1
,
1
],
[
0
,
2
]]),
# x^2 x.y y^2
(
2
,
'quadrangle'
):
np
.
array
([[
0
,
0
],
[
1
,
0
],
[
1
,
1
],
[
0
,
1
],
[
2
,
0
],
[
2
,
1
],
[
1
,
2
],
[
0
,
2
]]),
(
3
,
'triangle'
):
np
.
array
([[
0
,
0
,
0
],
[
1
,
0
,
0
],
[
0
,
1
,
0
],
[
0
,
0
,
1
],
[
2
,
0
,
0
],
[
1
,
1
,
0
],
[
0
,
2
,
0
],
[
0
,
1
,
1
],
[
0
,
0
,
2
],
[
1
,
0
,
1
]]),
(
3
,
'quadrangle'
):
np
.
array
([[
0
,
0
,
0
],
[
1
,
0
,
0
],
[
0
,
1
,
0
],
[
0
,
0
,
1
],
[
1
,
1
,
0
],
[
1
,
0
,
1
],
[
0
,
1
,
1
],
[
1
,
1
,
1
],
[
2
,
0
,
0
],
[
0
,
2
,
0
],
[
0
,
0
,
2
],
[
2
,
1
,
0
],
[
2
,
0
,
1
],
[
2
,
1
,
1
],
[
1
,
2
,
0
],
[
0
,
2
,
1
],
[
1
,
2
,
1
],
[
1
,
0
,
2
],
[
0
,
1
,
2
],
[
1
,
1
,
2
]])}
SHAPES
=
{
(
3
,
'pentahedron'
,
1
):
np
.
array
([
[[[
0.
,
0.
],
[
1.
,
0.
]],
[[
0.
,
0.
],
[
-
1.
,
0.
]]],
[[[
0.
,
1.
],
[
0.
,
0.
]],
[[
0.
,
-
1.
],
[
0.
,
0.
]]],
[[[
1.
,
-
1.
],
[
-
1.
,
0.
]],
[[
-
1.
,
1.
],
[
1.
,
0.
]]],
[[[
0.
,
0.
],
[
1.
,
0.
]],
[[
0.
,
0.
],
[
1.
,
0.
]]],
[[[
0.
,
1.
],
[
0.
,
0.
]],
[[
0.
,
1.
],
[
0.
,
0.
]]],
[[[
1.
,
-
1.
],
[
-
1.
,
0.
]],
[[
1.
,
-
1.
],
[
-
1.
,
0.
]]]
])
/
2.
,
(
3
,
'pentahedron'
,
2
):
np
.
array
([
# 0
[[[
0.
,
0.
,
0.
],
[
-
1.
,
0.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.5
,
0.
,
0.
],
[
-
1.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.5
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 1
[[[
0.
,
-
1.
,
1.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.5
,
-
1.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.5
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 2
[[[
0.
,
-
1.
,
1.
],
[
-
1.
,
2.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
-
0.5
,
1.5
,
-
1.
],
[
1.5
,
-
2.
,
0.
],
[
-
1.
,
0.
,
0.
]],
[[
0.5
,
-
0.5
,
0.
],
[
-
0.5
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 3
[[[
0.
,
0.
,
0.
],
[
-
1.
,
0.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
-
0.5
,
0.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.5
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 4
[[[
0.
,
-
1.
,
1.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
-
0.5
,
1.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.5
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 5
[[[
0.
,
-
1.
,
1.
],
[
-
1.
,
2.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
0.5
,
-
1.5
,
1.
],
[
-
1.5
,
2.
,
0.
],
[
1.
,
0.
,
0.
]],
[[
0.5
,
-
0.5
,
0.
],
[
-
0.5
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 6
[[[
0.
,
0.
,
0.
],
[
0.
,
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
-
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 7
[[[
0.
,
2.
,
-
2.
],
[
0.
,
-
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
-
2.
,
2.
],
[
0.
,
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 8
[[[
0.
,
0.
,
0.
],
[
2.
,
-
2.
,
0.
],
[
-
2.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
-
2.
,
2.
,
0.
],
[
2.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 9
[[[
0.
,
0.
,
0.
],
[
1.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
-
1.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 10
[[[
0.
,
1.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
-
1.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 11
[[[
1.
,
-
1.
,
0.
],
[
-
1.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
-
1.
,
1.
,
0.
],
[
1.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 12
[[[
0.
,
0.
,
0.
],
[
0.
,
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 13
[[[
0.
,
2.
,
-
2.
],
[
0.
,
-
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
2.
,
-
2.
],
[
0.
,
-
2.
,
0.
],
[
0.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
# 14
[[[
0.
,
0.
,
0.
],
[
2.
,
-
2.
,
0.
],
[
-
2.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
2.
,
-
2.
,
0.
],
[
-
2.
,
0.
,
0.
]],
[[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
],
[
0.
,
0.
,
0.
]]],
])}
# pylint: enable=bad-whitespace, line-too-long
def
__init__
(
self
,
element
):
self
.
_shape
,
self
.
_order
,
self
.
_inter_poly
,
self
.
_dim
,
\
self
.
_nnodes
=
self
.
ELEMENT_TYPES
[
element
]
self
.
_ksi
=
self
.
NATURAL_COORDS
[(
self
.
_dim
,
self
.
_shape
)][:
self
.
_nnodes
]
self
.
_g
=
self
.
QUADRATURE_G
[(
self
.
_dim
,
self
.
_shape
,
self
.
_order
)]
self
.
_w
=
self
.
QUADRATURE_W
[(
self
.
_dim
,
self
.
_shape
,
self
.
_order
)]
self
.
_poly_shape
=
()
self
.
_monome
=
[]
def
polyval
(
self
,
x
,
p
):
if
self
.
_dim
==
1
:
return
poly
.
polyval
(
x
[
0
],
p
)
if
self
.
_dim
==
2
:
return
poly
.
polyval2d
(
x
[
0
],
x
[
1
],
p
)
if
self
.
_dim
==
3
:
return
poly
.
polyval3d
(
x
[
0
],
x
[
1
],
x
[
2
],
p
)
return
None
def
shape_from_monomes
(
self
):
momo
=
self
.
MONOMES
[(
self
.
_dim
,
self
.
_shape
)][:
self
.
_nnodes
]
_shapes
=
list
(
momo
[
0
])
for
s
,
_
in
enumerate
(
_shapes
):
_shapes
[
s
]
=
max
(
momo
[:,
s
])
+
1
self
.
_poly_shape
=
tuple
(
_shapes
)
self
.
_monome
=
[]
for
m
in
momo
:
p
=
np
.
zeros
(
self
.
_poly_shape
)
p
[
tuple
(
m
)]
=
1
self
.
_monome
.
append
(
p
)
# evaluate polynomial constant for shapes
_x
=
self
.
_ksi
_xe
=
np
.
zeros
((
self
.
_nnodes
,
self
.
_nnodes
))
for
n
in
range
(
self
.
_nnodes
):
_xe
[:,
n
]
=
[
self
.
polyval
(
_x
[
n
],
m
)
for
m
in
self
.
_monome
]
_a
=
np
.
linalg
.
inv
(
_xe
)
_n
=
np
.
zeros
((
self
.
_nnodes
,)
+
self
.
_monome
[
0
]
.
shape
)
# set shapes polynomials
for
n
in
range
(
self
.
_nnodes
):
for
m
in
range
(
len
(
self
.
_monome
)):
_n
[
n
]
+=
_a
[
n
,
m
]
*
self
.
_monome
[
m
]
return
_n
def
compute_shapes
(
self
):
if
(
self
.
_dim
,
self
.
_shape
)
in
self
.
MONOMES
:
return
self
.
shape_from_monomes
()
_n
=
self
.
SHAPES
[(
self
.
_dim
,
self
.
_shape
,
self
.
_order
)]
self
.
_poly_shape
=
_n
[
0
]
.
shape
return
_n
# pylint: disable=too-many-locals,too-many-branches
def
precompute
(
self
,
**
kwargs
):
X
=
np
.
array
(
kwargs
[
"X"
],
copy
=
False
)
nb_element
=
X
.
shape
[
0
]
X
=
X
.
reshape
(
nb_element
,
self
.
_nnodes
,
self
.
_dim
)
_x
=
self
.
_ksi
_n
=
self
.
compute_shapes
()
# sanity check on shapes
for
n
in
range
(
self
.
_nnodes
):
for
m
in
range
(
self
.
_nnodes
):
v
=
self
.
polyval
(
_x
[
n
],
_n
[
m
])
ve
=
1.
if
n
==
m
else
0.
test
=
np
.
isclose
(
v
,
ve
)
if
not
test
:
raise
Exception
(
"Most probably an error in the shapes evaluation"
)
# compute shapes derivatives
_b
=
np
.
zeros
((
self
.
_dim
,
self
.
_nnodes
,)
+
self
.
_poly_shape
)
for
d
in
range
(
self
.
_dim
):
for
n
in
range
(
self
.
_nnodes
):
_der
=
poly
.
polyder
(
_n
[
n
],
axis
=
d
)
_mshape
=
np
.
array
(
self
.
_poly_shape
)
_mshape
[
d
]
=
_mshape
[
d
]
-
_der
.
shape
[
d
]
_mshape
=
tuple
(
_mshape
)
_comp
=
np
.
zeros
(
_mshape
)
if
self
.
_dim
==
1
:
_bt
=
np
.
hstack
((
_der
,
_comp
))
else
:
if
d
==
0
:
_bt
=
np
.
vstack
((
_der
,
_comp
))
if
d
==
1
:
_bt
=
np
.
hstack
((
_der
,
_comp
))
if
d
==
2
:
_bt
=
np
.
dstack
((
_der
,
_comp
))
_b
[
d
,
n
]
=
_bt
_nb_quads
=
len
(
self
.
_g
)
_nq
=
np
.
zeros
((
_nb_quads
,
self
.
_nnodes
))
_bq
=
np
.
zeros
((
_nb_quads
,
self
.
_dim
,
self
.
_nnodes
))
# evaluate shapes and shapes derivatives on gauss points
for
q
in
range
(
_nb_quads
):
_g
=
self
.
_g
[
q
]
for
n
in
range
(
self
.
_nnodes
):
_nq
[
q
,
n
]
=
self
.
polyval
(
_g
,
_n
[
n
])
for
d
in
range
(
self
.
_dim
):
_bq
[
q
,
d
,
n
]
=
self
.
polyval
(
_g
,
_b
[
d
,
n
])
_j
=
np
.
array
(
kwargs
[
'j'
],
copy
=
False
)
.
reshape
((
nb_element
,
_nb_quads
))
_B
=
np
.
array
(
kwargs
[
'B'
],
copy
=
False
)
.
reshape
((
nb_element
,
_nb_quads
,
self
.
_nnodes
,
self
.
_dim
))
_N
=
np
.
array
(
kwargs
[
'N'
],
copy
=
False
)
.
reshape
((
nb_element
,
_nb_quads
,
self
.
_nnodes
))
_Q
=
kwargs
[
'Q'
]
if
np
.
linalg
.
norm
(
_Q
-
self
.
_g
.
T
)
>
1e-15
:
raise
Exception
(
'Not using the same quadrature'
' points norm({0} - {1}) = {2}'
.
format
(
_Q
,
self
.
_g
.
T
,
np
.
linalg
.
norm
(
_Q
-
self
.
_g
.
T
)))
for
e
in
range
(
nb_element
):
for
q
in
range
(
_nb_quads
):
_J
=
np
.
matmul
(
_bq
[
q
],
X
[
e
])
if
np
.
linalg
.
norm
(
_N
[
e
,
q
]
-
_nq
[
q
])
>
1e-10
:
print
(
"{0},{1}"
.
format
(
e
,
q
))
print
(
_N
[
e
,
q
])
print
(
_nq
[
q
])
_N
[
e
,
q
]
=
_nq
[
q
]
_tmp
=
np
.
matmul
(
np
.
linalg
.
inv
(
_J
),
_bq
[
q
])
_B
[
e
,
q
]
=
_tmp
.
T
_j
[
e
,
q
]
=
np
.
linalg
.
det
(
_J
)
*
self
.
_w
[
q
]
Event Timeline
Log In to Comment