3. Convert NumPy Matrix to Array Using ravel() Thenumpy.ravel()function is used to create a contiguous flattened array from a given input array. This function returns a flattened one-dimensional array, meaning it collapses the input array into a flat, contiguous sequence. 3.1 Syntax of ravel(...
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abc.Sequence): return [convert_numpy_to_tensor(data) for data in raw_data] else: return raw_data Example 13Source File: datasets.py From RFHO with MIT License 5 votes def convert_sparse_matrix_to_sparse_tensor(X): if isinstance(X, sc_sp.csr.csr_matrix): coo = X.tocoo() indices...
from scipy.sparse import identity as sparse_identity from qiskit_dynamics.arraylias.alias import ArrayLike, _to_dense, _numpy_multi_dispatch def _kron(A, B): return _numpy_multi_dispatch(A, B, path="kron") def vec_commutator( A: Union[ArrayLike, csr_matrix, List[csr_matrix]] ) -> ...
emit dgRMatrix objects. These are pretty unusual (and useless), we should coerce them into dgCMatrix objects instead. I notice that the sparse format is already column sparse compressed, so it may be more efficient to avoid a round-trip through Python (and converting to/from the row-format)...
from numpy import array, sqrt, real, imag, pi from math import asin from scipy.sparse import dok_matrix, hstack from collections import defaultdict, deque from loadcase import load_case def build_U_matrices(G, B): S2 = sqrt(2) n = G.shape[0] Ureal = dok_mat...
numpy.matrixlib.defmatrix.matrixprint(A_dense,type(A_dense))print('--- See two row of matrix equal or not: ---')print((numpy.equal(A_dense[5], A_dense[6])).all())# print('to_numpy_array:\n', nx.to_numpy_array(D, nodelist=list(range(len(D.nodes)))# print('to_dict_of...
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