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Larry Price
gmsh
Commits
3e31c136
"README.txt" did not exist on "a58f392ef302614414fbf789815c9c25b4ec9f3d"
Commit
3e31c136
authored
16 years ago
by
Christophe Geuzaine
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doc/VERSIONS.txt
+4
-1
4 additions, 1 deletion
doc/VERSIONS.txt
doc/texinfo/gmsh.texi
+11
-12
11 additions, 12 deletions
doc/texinfo/gmsh.texi
with
15 additions
and
13 deletions
doc/VERSIONS.txt
+
4
−
1
View file @
3e31c136
$Id: VERSIONS.txt,v 1.42 2009-03-18 20:29:26 geuzaine Exp $
$Id: VERSIONS.txt,v 1.43 2009-03-30 08:19:28 geuzaine Exp $
2.3.2 (?): optionally copy transfinite mesh contraints during geometry
transformations.
2.3.1 (Mar 18, 2009): removed GSL dependency (Gmsh now simply uses
2.3.1 (Mar 18, 2009): removed GSL dependency (Gmsh now simply uses
Blas and Lapack); new per-window visibility; added support for
Blas and Lapack); new per-window visibility; added support for
...
...
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doc/texinfo/gmsh.texi
+
11
−
12
View file @
3e31c136
...
@@ -2969,12 +2969,12 @@ interpolation matrices used for high-order adaptive visualization.
...
@@ -2969,12 +2969,12 @@ interpolation matrices used for high-order adaptive visualization.
Let us assume that the approximation of the view's value over an element
Let us assume that the approximation of the view's value over an element
is written as a linear combination of @var
{
d
}
basis functions
is written as a linear combination of @var
{
d
}
basis functions
@var
{
f
}
[@var
{
j
}
], @var
{
j
}
=0, ..., @var
{
d
}
-1 (the coefficients being
@var
{
f
}
[@var
{
j
}
], @var
{
j
}
=0, ..., @var
{
d
}
-1 (the coefficients being
stored in @var
{
list-of-values
}
).
If
@var
{
f
}
[@var
{
j
}
] =
@var
{
p
}
[0]
stored in @var
{
list-of-values
}
).
Defining
@var
{
f
}
[@var
{
j
}
] =
@var
{
F
}
[@var
{
j
}
][0] +
@var
{
p
}
[1]
@var
{
F
}
[@var
{
j
}
]
[1] + @var
{
p
}
[2]
Sum(
@var
{
i
}
=0, ...,
@var
{
d
}
-1)
@var
{
p
}
[@var
{
i
}
]
@var
{
F
}
[@var
{
j
}
][
2] + ...
, with @var
{
p
}
[@var
{
i
}
] =
@var
{
F
}
[@var
{
j
}
][
@var
{
i
}
]
, with @var
{
p
}
[@var
{
i
}
] =
@var
{
u
}^
@var
{
P
}
[@var
{
i
}
][0] @var
{
v
}^
@var
{
P
}
[@var
{
i
}
][1]
@var
{
u
}^
@var
{
P
}
[@var
{
i
}
][0] @var
{
v
}^
@var
{
P
}
[@var
{
i
}
][1]
@var
{
w
}^
@var
{
P
}
[@var
{
i
}
][2] (@var
{
u
}
, @var
{
v
}
and @var
{
w
}
being the
@var
{
w
}^
@var
{
P
}
[@var
{
i
}
][2] (@var
{
u
}
, @var
{
v
}
and @var
{
w
}
being the
coordinates
of
the element's parameter space), then
coordinates
in
the element's parameter space), then
@var
{
val-coef-matrix
}
denotes the @var
{
d
}
x @var
{
d
}
matrix @var
{
F
}
and
@var
{
val-coef-matrix
}
denotes the @var
{
d
}
x @var
{
d
}
matrix @var
{
F
}
and
@var
{
val-exp-matrix
}
denotes the @var
{
d
}
x @var
{
3
}
matrix @var
{
P
}
.
@var
{
val-exp-matrix
}
denotes the @var
{
d
}
x @var
{
3
}
matrix @var
{
P
}
.
...
@@ -2982,14 +2982,13 @@ In the same way, let us also assume that the coordinates @var{x},
...
@@ -2982,14 +2982,13 @@ In the same way, let us also assume that the coordinates @var{x},
@var
{
y
}
and @var
{
z
}
of the element are obtained through a geometrical
@var
{
y
}
and @var
{
z
}
of the element are obtained through a geometrical
mapping from parameter space as a linear combination of @var
{
m
}
basis
mapping from parameter space as a linear combination of @var
{
m
}
basis
functions @var
{
g
}
[@var
{
j
}
], @var
{
j
}
=0, ..., @var
{
m
}
-1 (the coefficients
functions @var
{
g
}
[@var
{
j
}
], @var
{
j
}
=0, ..., @var
{
m
}
-1 (the coefficients
being stored in @var
{
list-of-coords
}
).
being stored in @var
{
list-of-coords
}
). Defining @var
{
g
}
[@var
{
j
}
] =
Sum(@var
{
i
}
=0, ..., @var
{
m
}
-1) @var
{
q
}
[@var
{
i
}
]
If @var
{
g
}
[@var
{
j
}
] = @var
{
q
}
[0] @var
{
G
}
[@var
{
j
}
][0] + @var
{
q
}
[1]
@var
{
G
}
[@var
{
j
}
][@var
{
i
}
], with @var
{
q
}
[@var
{
i
}
] =
@var
{
G
}
[@var
{
j
}
][1] + @var
{
q
}
[2] @var
{
G
}
[@var
{
j
}
][2] + ..., with
@var
{
u
}^
@var
{
Q
}
[@var
{
i
}
][0] @var
{
v
}^
@var
{
Q
}
[@var
{
i
}
][1]
@var
{
q
}
[@var
{
i
}
] = @var
{
u
}^
@var
{
Q
}
[@var
{
i
}
][0]
@var
{
w
}^
@var
{
Q
}
[@var
{
i
}
][2], then @var
{
val-coef-matrix
}
denotes the
@var
{
v
}^
@var
{
Q
}
[@var
{
i
}
][1] @var
{
w
}^
@var
{
Q
}
[@var
{
i
}
][2], then
@var
{
m
}
x @var
{
m
}
matrix @var
{
G
}
and @var
{
val-exp-matrix
}
denotes the
@var
{
val-coef-matrix
}
denotes the @var
{
m
}
x @var
{
m
}
matrix @var
{
G
}
and
@var
{
m
}
x @var
{
3
}
matrix @var
{
Q
}
.
@var
{
val-exp-matrix
}
denotes the @var
{
m
}
x @var
{
3
}
matrix @var
{
Q
}
.
Here are for example the interpolation matrices for a first order
Here are for example the interpolation matrices for a first order
quadrangle:
quadrangle:
...
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