def __init__(self,size=0,dim=0,ldb=None): self._inverted=False self._original=None if ldb: self.ldb=ldb else: self.ldb = sa.listdb_create(size,dim)
def ndarray_to_listdb(arr): ldb = sa.listdb_create(arr.shape[0], arr.shape[1]) for i,row in enumerate(arr): for j,item in enumerate(row): if item != 0: ldb.push(int(i), int(j), int(round(item * 100000000))) return SMH(ldb=ldb)
def csr_to_listdb(csr): ldb = sa.listdb_create(csr.shape[0], csr.shape[1]) coo = csr.tocoo() for i,j,v in itertools.izip(coo.row, coo.col, coo.data): ldb.push(int(i), int(j), int(round(v * 100000000))) return SMH(ldb=ldb)
def ndarray_to_listdb(arr): """ Converts a numpy multidimensional array to a ListDB structure """ ldb = sa.listdb_create(arr.shape[0], arr.shape[1]) for i,row in enumerate(arr): for j,v in enumerate(row): if v != 0: ldb.push(int(i), int(j), int(round(v))) return ListDB(ldb=ldb)
def csr_to_listdb(csr): """ Converts a Compressed Sparse Row (CSR) matrix to a ListDB structure """ ldb = sa.listdb_create(csr.shape[0], csr.shape[1]) coo = csr.tocoo() for i,j,v in itertools.izip(coo.row, coo.col, coo.data): ldb.push(int(i), int(j), int(round(v))) return ListDB(ldb=ldb)
def __init__(self, size = 0, dim = 0, ldb = None): """ Initializes class with ListDB structure """ if ldb: self.ldb=ldb elif size == 0 and dim == 0: self.ldb = sa.ListDB() sa.listdb_init(self.ldb) else: self.ldb = sa.listdb_create(size, dim)