scipy.sparse.
get_index_dtype#
- scipy.sparse.get_index_dtype(arrays=(), maxval=None, check_contents=False)[source]#
- Based on input (integer) arrays a, determine a suitable index data type that can hold the data in the arrays. - Parameters:
- arraystuple of array_like
- Input arrays whose types/contents to check 
- maxvalfloat, optional
- Maximum value needed 
- check_contentsbool, optional
- Whether to check the values in the arrays and not just their types. Default: False (check only the types) 
 
- Returns:
- dtypedtype
- Suitable index data type (int32 or int64) 
 
 - Examples - >>> import numpy as np >>> from scipy import sparse >>> # select index dtype based on shape >>> shape = (3, 3) >>> idx_dtype = sparse.get_index_dtype(maxval=max(shape)) >>> data = [1.1, 3.0, 1.5] >>> indices = np.array([0, 1, 0], dtype=idx_dtype) >>> indptr = np.array([0, 2, 3, 3], dtype=idx_dtype) >>> A = sparse.csr_array((data, indices, indptr), shape=shape) >>> A.indptr.dtype dtype('int32') - >>> # select based on larger of existing arrays and shape >>> shape = (3, 3) >>> idx_dtype = sparse.get_index_dtype(A.indptr, maxval=max(shape)) >>> idx_dtype <class 'numpy.int32'>