# Path: dppy/utils.py
# def check_random_state(seed: object) -> np.random.RandomState:
# def inner1d(arr1, arr2=None, axis=0):
# def det_ST(array, S, T=None):
# def is_square(array):
# def is_symmetric(array):
# def is_projection(array, col_idx=None):
# def is_orthonormal_columns(array, col_idx=None):
# def is_equal_to_O_or_1(array, tol=1e-8):
# def is_in_01(array, tol=1e-8):
# def is_geq_0(array, tol=1e-8):
# def is_full_row_rank(array):
# def stable_filter(eigenvec, eigenval):
# def stable_invert_root(eigenvec, eigenval):
# def get_progress_bar(total=-1, disable=False, **kwargs):
#         def __init__(self, total=-1, disable=False, **kwargs):
#         def __enter__(self):
#         def __exit__(self, *args, **kwargs):
#         def set_postfix(self, **kwargs):
#         def update(self):
# def evaluate_L_diagonal(eval_L, X):
# def example_eval_L_linear(X, Y=None):
# def example_eval_L_polynomial(X, Y=None, p=2):
# def example_eval_L_min_kern(X, Y=None):
#     M = array[np.ix_(idx, idx)]
#     U = array[:, col_idx]
#     X = np.atleast_2d(X)
#         Y = np.atleast_2d(Y)
#     X = np.atleast_2d(X)
#         Y = X
#         Y = np.atleast_2d(Y)
#     class ProgBar(object):


import unittest
import numpy as np
import numpy.linalg as la
import numpy.random as rndm
import sys
from scipy.linalg import qr
from dppy import utils
# coding: utf8
""" Unit tests:

- :class:`TestUtils`
"""




sys.path.append('..')


class TestUtils(unittest.TestCase):
    """ Test
    """
    def test_inner1D_to_compute_inner_product_and_square_norms(self):

        shape = (10, 20, 30, 40)
        X = rndm.rand(*shape)
        Y = rndm.rand(*shape)

        for ax in range(len(shape)):
            with self.subTest(axis=ax):

                for test_inner1D in ['inner_prod', 'sq_norm']:
                    with self.subTest(test_inner1D=test_inner1D):

                        if test_inner1D == 'inner_prod':

                            self.assertTrue(

# Path: dppy/utils.py
# def check_random_state(seed: object) -> np.random.RandomState:
# def inner1d(arr1, arr2=None, axis=0):
# def det_ST(array, S, T=None):
# def is_square(array):
# def is_symmetric(array):
# def is_projection(array, col_idx=None):
# def is_orthonormal_columns(array, col_idx=None):
# def is_equal_to_O_or_1(array, tol=1e-8):
# def is_in_01(array, tol=1e-8):
# def is_geq_0(array, tol=1e-8):
# def is_full_row_rank(array):
# def stable_filter(eigenvec, eigenval):
# def stable_invert_root(eigenvec, eigenval):
# def get_progress_bar(total=-1, disable=False, **kwargs):
#         def __init__(self, total=-1, disable=False, **kwargs):
#         def __enter__(self):
#         def __exit__(self, *args, **kwargs):
#         def set_postfix(self, **kwargs):
#         def update(self):
# def evaluate_L_diagonal(eval_L, X):
# def example_eval_L_linear(X, Y=None):
# def example_eval_L_polynomial(X, Y=None, p=2):
# def example_eval_L_min_kern(X, Y=None):
#     M = array[np.ix_(idx, idx)]
#     U = array[:, col_idx]
#     X = np.atleast_2d(X)
#         Y = np.atleast_2d(Y)
#     X = np.atleast_2d(X)
#         Y = X
#         Y = np.atleast_2d(Y)
#     class ProgBar(object):


# Path: tests/test_utils.py
import unittest
import numpy as np
import numpy.linalg as la
import numpy.random as rndm
import sys
from scipy.linalg import qr
from dppy import utils

# coding: utf8
""" Unit tests:

- :class:`TestUtils`
"""




sys.path.append('..')


class TestUtils(unittest.TestCase):
    """ Test
    """
    def test_inner1D_to_compute_inner_product_and_square_norms(self):

        shape = (10, 20, 30, 40)
        X = rndm.rand(*shape)
        Y = rndm.rand(*shape)

        for ax in range(len(shape)):
            with self.subTest(axis=ax):

                for test_inner1D in ['inner_prod', 'sq_norm']:
                    with self.subTest(test_inner1D=test_inner1D):

                        if test_inner1D == 'inner_prod':

                            self.assertTrue(

                                np.allclose(utils.inner1d(X, Y, axis=ax),