From 5b8020c7c18996437d9839c8f15ba1e0710ddb6f Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Tue, 25 Aug 2020 18:06:05 -0500
Subject: [PATCH] Add documentation on eager derivatives
---
grudge/eager.py | 45 +++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 45 insertions(+)
diff --git a/grudge/eager.py b/grudge/eager.py
index 407c182e..5fcd3a61 100644
--- a/grudge/eager.py
+++ b/grudge/eager.py
@@ -69,6 +69,14 @@ class EagerDGDiscretization(DGDiscretizationWithBoundaries):
return self.project(src, tgt, vec)
def project(self, src, tgt, vec):
+ """Project from one discretization to another, e.g. from the
+ volume to the boundary, or from the base to the an overintegrated
+ quadrature discretization.
+
+ :arg src: a :class:`~grudge.sym.DOFDesc`, or a value convertible to one
+ :arg tgt: a :class:`~grudge.sym.DOFDesc`, or a value convertible to one
+ :arg vec: a :class:`~meshmode.dof_array.DOFArray`
+ """
if (isinstance(vec, np.ndarray)
and vec.dtype.char == "O"
and not isinstance(vec, DOFArray)):
@@ -94,11 +102,25 @@ class EagerDGDiscretization(DGDiscretizationWithBoundaries):
return bind(self, sym.nabla(self.dim) * sym.Variable("u"), local_only=True)
def grad(self, vec):
+ r"""Return the gradient of the volume function represented by *vec*.
+
+ :arg vec: a :class:`~meshmode.dof_array.DOFArray`
+ :returns: an object array of :class:`~meshmode.dof_array.DOFArray`\ s
+ """
return self._bound_grad()(u=vec)
def div(self, vecs):
return sum(
self.grad(vec_i)[i] for i, vec_i in enumerate(vecs))
+ r"""Return the divergence of the vector volume function
+ represented by *vecs*.
+
+ :arg vec: an object array of
+ a :class:`~meshmode.dof_array.DOFArray`\ s,
+ where the last axis of the array must have length
+ matching the volume dimension.
+ :returns: a :class:`~meshmode.dof_array.DOFArray`
+ """
@memoize_method
def _bound_weak_grad(self, dd):
@@ -107,6 +129,16 @@ class EagerDGDiscretization(DGDiscretizationWithBoundaries):
local_only=True)
def weak_grad(self, *args):
+ r"""Return the "weak gradient" of the volume function represented by
+ *vec*.
+
+ May be called with ``(vecs)`` or ``(dd, vecs)``.
+
+ :arg dd: a :class:`~grudge.sym.DOFDesc`, or a value convertible to one.
+ Defaults to the base volume discretization if not provided.
+ :arg vec: a :class:`~meshmode.dof_array.DOFArray`
+ :returns: an object array of :class:`~meshmode.dof_array.DOFArray`\ s
+ """
if len(args) == 1:
vec, = args
dd = sym.DOFDesc("vol", sym.QTAG_NONE)
@@ -118,6 +150,19 @@ class EagerDGDiscretization(DGDiscretizationWithBoundaries):
return self._bound_weak_grad(dd)(u=vec)
def weak_div(self, *args):
+ r"""Return the "weak divergence" of the vector volume function
+ represented by *vecs*.
+
+ May be called with ``(vecs)`` or ``(dd, vecs)``.
+
+ :arg dd: a :class:`~grudge.sym.DOFDesc`, or a value convertible to one.
+ Defaults to the base volume discretization if not provided.
+ :arg vec: a object array of
+ a :class:`~meshmode.dof_array.DOFArray`\ s,
+ where the last axis of the array must have length
+ matching the volume dimension.
+ :returns: a :class:`~meshmode.dof_array.DOFArray`
+ """
if len(args) == 1:
vecs, = args
dd = sym.DOFDesc("vol", sym.QTAG_NONE)
--
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