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Andreas Klöckner
grudge
Commits
a6cb8d1a
Commit
a6cb8d1a
authored
4 years ago
by
Alexandru Fikl
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add some docs
parent
225bdcba
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1 merge request
!69
DG on Surfaces
Pipeline
#65234
failed
4 years ago
Stage: test
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1 changed file
grudge/symbolic/primitives.py
+26
-2
26 additions, 2 deletions
grudge/symbolic/primitives.py
with
26 additions
and
2 deletions
grudge/symbolic/primitives.py
+
26
−
2
View file @
a6cb8d1a
...
...
@@ -503,11 +503,24 @@ def mv_nodes(ambient_dim, dd=None):
def
forward_metric_nth_derivative
(
xyz_axis
,
ref_axes
,
dd
=
None
):
r
"""
Pointwise metric derivatives representing
Pointwise metric derivatives representing
repeated derivatives
.. math::
\frac{\partial x_{\mathrm{xyz\_axis}} }{\partial r_{\mathrm{rst\_axis}} }
\frac{\partial^n x_{\mathrm{xyz\_axis}} }{\partial r_{\mathrm{ref\_axes}}}
where *ref_axes* is a multi-index description.
:arg ref_axes: a :class:`tuple` of tuples indicating indices of
coordinate axes of the reference element to the number of derivatives
which will be taken. For example, the value ``((0, 2), (1, 1))``
indicates taking the second derivative with respect to the first
axis and the first derivative with respect to the second
axis. Each axis must occur only once and the tuple must be sorted
by the axis index.
May also be a singile integer *i*, which is viewed as equivalent
to ``((i, 1),)``.
"""
if
isinstance
(
ref_axes
,
int
):
...
...
@@ -546,6 +559,14 @@ def forward_metric_nth_derivative(xyz_axis, ref_axes, dd=None):
def
forward_metric_derivative
(
xyz_axis
,
rst_axis
,
dd
=
None
):
r
"""
Pointwise metric derivatives representing
.. math::
\frac{\partial x_{\mathrm{xyz\_axis}} }{\partial r_{\mathrm{rst\_axis}}}
"""
return
forward_metric_nth_derivative
(
xyz_axis
,
rst_axis
,
dd
=
dd
)
...
...
@@ -800,6 +821,8 @@ def normal(dd, ambient_dim, dim=None):
def
summed_curvature
(
ambient_dim
,
dim
=
None
,
dd
=
None
):
"""
Sum of the principal curvatures
"""
if
dim
is
None
:
dim
=
ambient_dim
-
1
...
...
@@ -814,6 +837,7 @@ def summed_curvature(ambient_dim, dim=None, dd=None):
def
mean_curvature
(
ambient_dim
,
dim
=
None
,
dd
=
None
):
"""
Averaged (by dimension) sum of the principal curvatures.
"""
return
1.0
/
(
ambient_dim
-
1.0
)
*
summed_curvature
(
ambient_dim
,
dim
=
dim
,
dd
=
dd
)
# }}}
...
...
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