qmat.qcoeff.collocation ======================= .. py:module:: qmat.qcoeff.collocation .. autoapi-nested-parse:: Submodule to generate Q matrices based on Collocation .. rubric:: Examples >>> from qmat.qcoeff.collocation import Collocation >>> coll = Collocation(nNodes=4, nodeType="LEGENDRE", quadType="RADAU-RIGHT") >>> nodes, weights, Q = coll.genCoeffs() >>> S = coll.S Classes ------- .. autoapisummary:: qmat.qcoeff.collocation.Collocation Module Contents --------------- .. py:class:: Collocation(nNodes, nodeType, quadType, tLeft=0, tRight=1) .. autoapi-inheritance-diagram:: qmat.qcoeff.collocation.Collocation :parts: 1 Base class to generate :math:`Q`-coefficients for a Collocation method. :Parameters: * **nNodes** (*int*) -- Number of collocation nodes. * **nodeType** (*str*) -- Type of node distributions, see :class:`qmat.nodes` for possible choices. * **quadType** (*str*) -- Quadrature type, see :class:`qmat.nodes` for possible choices. * **tLeft** (*float, optional*) -- Left boundary for the nodes. The default is 0. * **tRight** (*float, optional*) -- Right boundary for the nodes. The default is 1. .. py:attribute:: aliases :value: ['coll'] .. py:attribute:: DEFAULT_PARAMS Defaults parameters for getInstance .. py:attribute:: approx .. py:property:: nodes :type: numpy.ndarray Nodes :math:`\tau` (:math:`c` coefficients in Butcher table) .. py:property:: Q :type: numpy.ndarray :math:`Q` coefficients (:math:`A` Butcher table) .. py:property:: weights :type: numpy.ndarray Weights :math:`\omega` (:math:`b` coefficients in Butcher table) .. py:property:: S :type: numpy.ndarray Quadrature matrix in node to node (N2N) .. py:property:: hCoeffs :type: numpy.ndarray :math:`h` interpolation coefficients for the right boundary .. py:property:: order :type: int Global convergence order of the method