nums.core.compute.numpy_compute module

class nums.core.compute.numpy_compute.ComputeCls

Bases: nums.core.compute.compute_interface.ComputeImp

advanced_assign_block_along_axis(dst_arr, src_arr, ss, axis, dst_coord, src_coord)

advanced_select_block_along_axis(dst_arr_or_args, src_arr, ss, dst_axis, src_axis, dst_coord, src_coord)

arange(start, stop, step, dtype)

arg_op(op_name, arr, block_slice, other_argoptima=None, other_optima=None)

array_compare(func_name, a, b, args)

astype(arr, dtype_str)

bop(op, a1, a2, a1_T, a2_T, axes)

bop_reduce(op, a1, a2, a1_T, a2_T)

cholesky(arr)

create_block(*src_arrs, src_params, dst_params, dst_shape, dst_shape_bc)

diag(arr, offset)

identity(value)

inv(arr)

logical_and(*bool_list)

map_uop(op_name, arr, args, kwargs)

new_block(op_name, grid_entry, grid_meta)

percentiles_from_tdigest(q, *digests)

permutation(rng_params, size)

pivot_partition(arr, pivot, op)

Return all elements in arr for which the comparsion to pivot is True.

qr(*arrays, mode='reduced', axis=None)

random_block(rng_params, rfunc_name, rfunc_args, shape, dtype)

reduce_axis(op_name, arr, axis, keepdims, transposed)

reshape(arr, shape)

select_median(arr)

Find value in arr closest to median as part of quickselect algorithm.

shape_dtype(arr)

size(arr)

split(arr, indices_or_sections, axis, transposed)

sum_reduce(*arrs)

svd(arr)

swapaxes(arr, axis1, axis2)

tdigest_chunk(arr)

touch(arr)

transpose(arr)

update_block(dst_arr, *src_arrs, src_params, dst_params)

update_block_by_index(dst_arr, src_arr, index_pairs)

weighted_median(*arr_and_weights)

Find the weighted median of an array.

where(arr, x, y, block_slice_tuples)

xlogy(arr_x, arr_y)

class nums.core.compute.numpy_compute.RNG(seed=None, jump_index=0)

Bases: nums.core.compute.compute_interface.RNGInterface

new_block_rng_params()

nums.core.compute.numpy_compute.block_rng(seed, jump_index)