from scipy.sparse import csr_matrix A = csr_matrix([[1,0,2],[0,3,0]]) >>>A <2×3 sparse matrix of type ‘<type ‘numpy.int64′>’ with 3 stored elements in Compressed Sparse Row format> >>> A.todense() matrix([[1, 0, 2], [0, 3, 0]]) >>> A.toarray() array([[1, 0, 2], [0, 3, 0]]) this is an example of how to convert a sparse matrix to a dense matrix … Read more
node_after_b == node_a will try to call node_after_b.__eq__(node_a): >>> class B(object): … def __eq__(self, other): … print “B.__eq__()” … return False … >>> class A(object): … def __eq__(self, other): … print “A.__eq__()” … return False … >>> a = A() >>> b = B() >>> a == b A.__eq__() False >>> b == a B.__eq__() … Read more
Sparsed arrays built with hashmaps are very inefficient for frequently read data. The most efficient implementations uses a Trie that allows access to a single vector where segments are distributed. A Trie can compute if an element is present in the table by performing only read-only TWO array indexing to get the effective position where … Read more
Happy to suggest a (possibly obvious) implementation of this, which could be made in pure Python or C/Cython if you’ve got time and space for new dependencies, and need it to be faster. A sparse matrix in N dimensions can assume most elements are empty, so we use a dictionary keyed on tuples: class NDSparseMatrix: … Read more
Yes, they are. They are actually hash tables internally, so you can use not only large integers but also strings, floats, or other objects. All keys get converted to strings via toString() before being added to the hash. You can confirm this with some test code: <script> var array = []; array[0] = “zero”; array[new … Read more
You can pass a numpy array or matrix as an argument when initializing a sparse matrix. For a CSR matrix, for example, you can do the following. >>> import numpy as np >>> from scipy import sparse >>> A = np.array([[1,2,0],[0,0,3],[1,0,4]]) >>> B = np.matrix([[1,2,0],[0,0,3],[1,0,4]]) >>> A array([[1, 2, 0], [0, 0, 3], [1, 0, … Read more
SparseArray can be used to replace HashMap when the key is a primitive type. There are some variants for different key/value types, even though not all of them are publicly available. Benefits are: Allocation-free No boxing Drawbacks: Generally slower, not indicated for large collections They won’t work in a non-Android project HashMap can be replaced … Read more