import numpy as np
from numpy import ndarray
import dexplo._utils as utils
from dexplo._frame import DataFrame
import dexplo._libs.validate_arrays as va
def _check_1d_arrays(a: ndarray, b: ndarray, kind: str, tol: float = 10 ** -4) -> bool:
if kind == 'O':
if not va.is_equal_1d_object(a, b):
raise AssertionError(f'The values of the columns are not equal')
return True
elif kind == 'f':
with np.errstate(invalid='ignore'):
criteria1 = np.abs(a - b) < tol
criteria2 = np.isnan(a) & np.isnan(b)
criteria3 = np.isinf(a) & np.isinf(b)
return (criteria1 | criteria2 | criteria3).all()
else:
try:
np.testing.assert_array_equal(a, b)
except AssertionError:
return False
return True
def assert_frame_equal(df1: DataFrame, df2: DataFrame) -> None:
if df1.shape != df2.shape:
raise AssertionError('DataFrame shapes are not equal, '
f'{df1.shape} != {df2.shape}')
for i, col in enumerate(df1.columns):
if df2.columns[i] != col:
raise AssertionError(f'column number {i} in left DataFrame not equal to right '
f'{col} != {df2.columns[i]}')
kind1, loc1 = df1._get_col_dtype_loc(col) # type: str, int
arr1: ndarray = df1._data[kind1][:, loc1]
kind2, loc2 = df2._get_col_dtype_loc(col) # type: str, int
arr2: ndarray = df2._data[kind2][:, loc2]
if kind1 != kind2:
dtype1 = utils.convert_kind_to_dtype(kind1)
dtype2 = utils.convert_kind_to_dtype(kind2)
raise AssertionError(f'The data types of column {col} are not '
f'equal. {dtype1} != {dtype2}')
if kind1 == 'S':
srm1 = df1._str_reverse_map[loc1]
srm2 = df2._str_reverse_map[loc2]
if not va.is_equal_str_cat_array(arr1, arr2, srm1, srm2):
raise AssertionError(f'The values of column {col} are not equal')
elif not _check_1d_arrays(arr1, arr2, kind1):
raise AssertionError(f'The values of column {col} are not equal')
def assert_array_equal(arr1, arr2, check_dtype=True):
if arr1.shape != arr2.shape:
raise AssertionError(f'Array shapes not equal: {arr1.shape} != {arr2.shape}')
if check_dtype and arr1.dtype.kind != arr2.dtype.kind:
raise AssertionError(f'Array data types not equal: {arr1.dtype} != {arr2.dtype}')
if arr1.ndim == 1:
if not _check_1d_arrays(arr1, arr2, arr1.dtype.kind):
raise AssertionError('Arrays not equal')
else:
for i in range(arr1.shape[1]):
if not _check_1d_arrays(arr1[:, i], arr2[:, i], arr1.dtype.kind):
raise AssertionError(f'Column {i} not equal')
def assert_dict_list(d1, d2):
for key, values1 in d1.items():
for v1, v2 in zip(values1, d2[key]):
if v1 != v2:
if isinstance(v1, (float, np.floating)) and np.isnan(v1) and \
isinstance(v2, (float, np.floating)) and np.isnan(v2):
continue
raise AssertionError('Lists are not equal')
