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Python tritools.TriAnalyzer方法代码示例

本文整理汇总了Python中matplotlib.tri.tritools.TriAnalyzer方法的典型用法代码示例。如果您正苦于以下问题:Python tritools.TriAnalyzer方法的具体用法?Python tritools.TriAnalyzer怎么用?Python tritools.TriAnalyzer使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在matplotlib.tri.tritools的用法示例。


在下文中一共展示了tritools.TriAnalyzer方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: __init__

# 需要导入模块: from matplotlib.tri import tritools [as 别名]
# 或者: from matplotlib.tri.tritools import TriAnalyzer [as 别名]
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() 
开发者ID:ktraunmueller,项目名称:Computable,代码行数:42,代码来源:triinterpolate.py

示例2: __init__

# 需要导入模块: from matplotlib.tri import tritools [as 别名]
# 或者: from matplotlib.tri.tritools import TriAnalyzer [as 别名]
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() 
开发者ID:PacktPublishing,项目名称:Mastering-Elasticsearch-7.0,代码行数:42,代码来源:triinterpolate.py


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