本文整理匯總了Python中matplotlib.tri.tritools.TriAnalyzer方法的典型用法代碼示例。如果您正苦於以下問題：Python tritools.TriAnalyzer方法的具體用法？Python tritools.TriAnalyzer怎麽用？Python tritools.TriAnalyzer使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類matplotlib.tri.tritools的用法示例。
在下文中一共展示了tritools.TriAnalyzer方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: __init__
# 需要導入模塊: from matplotlib.tri import tritools [as 別名]
# 或者: from matplotlib.tri.tritools import TriAnalyzer [as 別名]
def __init__(self, triangulation, z, kind='min_E', trifinder=None,
dz=None):
TriInterpolator.__init__(self, triangulation, z, trifinder)
# Loads the underlying c++ _triangulation.
# (During loading, reordering of triangulation._triangles may occur so
# that all final triangles are now anti-clockwise)
self._triangulation.get_cpp_triangulation()
# To build the stiffness matrix and avoid zero-energy spurious modes
# we will only store internally the valid (unmasked) triangles and
# the necessary (used) points coordinates.
# 2 renumbering tables need to be computed and stored:
# - a triangle renum table in order to translate the result from a
# TriFinder instance into the internal stored triangle number.
# - a node renum table to overwrite the self._z values into the new
# (used) node numbering.
tri_analyzer = TriAnalyzer(self._triangulation)
(compressed_triangles, compressed_x, compressed_y, tri_renum,
node_renum) = tri_analyzer._get_compressed_triangulation(True, True)
self._triangles = compressed_triangles
self._tri_renum = tri_renum
# Taking into account the node renumbering in self._z:
node_mask = (node_renum == -1)
self._z[node_renum[~node_mask]] = self._z
self._z = self._z[~node_mask]
# Computing scale factors
self._unit_x = np.max(compressed_x) - np.min(compressed_x)
self._unit_y = np.max(compressed_y) - np.min(compressed_y)
self._pts = np.vstack((compressed_x/float(self._unit_x),
compressed_y/float(self._unit_y))).T
# Computing triangle points
self._tris_pts = self._pts[self._triangles]
# Computing eccentricities
self._eccs = self._compute_tri_eccentricities(self._tris_pts)
# Computing dof estimations for HCT triangle shape function
self._dof = self._compute_dof(kind, dz=dz)
# Loading HCT element
self._ReferenceElement = _ReducedHCT_Element() 示例2: __init__
# 需要導入模塊: from matplotlib.tri import tritools [as 別名]
# 或者: from matplotlib.tri.tritools import TriAnalyzer [as 別名]
def __init__(self, triangulation, z, kind='min_E', trifinder=None,
dz=None):
TriInterpolator.__init__(self, triangulation, z, trifinder)
# Loads the underlying c++ _triangulation.
# (During loading, reordering of triangulation._triangles may occur so
# that all final triangles are now anti-clockwise)
self._triangulation.get_cpp_triangulation()
# To build the stiffness matrix and avoid zero-energy spurious modes
# we will only store internally the valid (unmasked) triangles and
# the necessary (used) points coordinates.
# 2 renumbering tables need to be computed and stored:
# - a triangle renum table in order to translate the result from a
# TriFinder instance into the internal stored triangle number.
# - a node renum table to overwrite the self._z values into the new
# (used) node numbering.
tri_analyzer = TriAnalyzer(self._triangulation)
(compressed_triangles, compressed_x, compressed_y, tri_renum,
node_renum) = tri_analyzer._get_compressed_triangulation(True, True)
self._triangles = compressed_triangles
self._tri_renum = tri_renum
# Taking into account the node renumbering in self._z:
node_mask = (node_renum == -1)
self._z[node_renum[~node_mask]] = self._z
self._z = self._z[~node_mask]
# Computing scale factors
self._unit_x = np.ptp(compressed_x)
self._unit_y = np.ptp(compressed_y)
self._pts = np.column_stack([compressed_x / self._unit_x,
compressed_y / self._unit_y])
# Computing triangle points
self._tris_pts = self._pts[self._triangles]
# Computing eccentricities
self._eccs = self._compute_tri_eccentricities(self._tris_pts)
# Computing dof estimations for HCT triangle shape function
self._dof = self._compute_dof(kind, dz=dz)
# Loading HCT element
self._ReferenceElement = _ReducedHCT_Element()