Here, we demonstrate how to convert a dense matrix to a sparse matrix using thesparse()function. The codeSparseFromDense = sparse(DenseMatrix)takes a dense identity matrix (eye(3)) and efficiently creates a sparse representation, resulting in theSparseFromDensematrix. ...
The underlying representation of these classes is a numpy matrix, but the class ensures that the structure of that matrix is valid for the particular group represented: SO(2), SE(2), SO(3), SE(3). Any operation that is not valid for the group will return a matrix rather than a pose...
some numpy type can't be used whereas the plain python type can be used: import hppfcl as fcl from pyrr import Matrix44 transformation = Matrix44.identity(dtype="f4")) (scale_x, scale_y, scale_z), _, _ = transformation.decompose() fcl.Box(scale_x, scale_y, scale_z) > fcl.Box...
Apart from array object attributes, such as ``ndim``, ``device``, and ``dtype``, all operations in this standard return arrays (or tuples of arrays), including those operations, such as ``mean``, ``var``, and ``std``, from which some common array libraries (e.g., NumPy) retu...
The underlying representation of these classes is a numpy matrix, but the class ensures that the structure of that matrix is valid for the particular group represented: SO(2), SE(2), SO(3), SE(3). Any operation that is not valid for the group will return a matrix rather than a pose...