mirror of
https://gitflic.ru/project/openide/openide.git
synced 2025-12-17 07:20:53 +07:00
17cb60469b
Add numpy.ndarray to html provider Add tests Merge-request: IJ-MR-115683 Merged-by: Egor Eliseev <Egor.Eliseev@jetbrains.com> GitOrigin-RevId: ea846a821c52e76bab0a45b883ad8d6c40ab469d
116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
# Copyright 2000-2023 JetBrains s.r.o. and contributors. Use of this source code is governed by the Apache 2.0 license.
|
|
import pytest
|
|
import numpy as np
|
|
import _pydevd_bundle.tables.pydevd_numpy as pandas_tables_helpers
|
|
from _pydevd_bundle.pydevd_constants import NEXT_VALUE_SEPARATOR
|
|
|
|
|
|
def check_info_np_array(arr, file):
|
|
actual = [pandas_tables_helpers.get_type(arr),
|
|
NEXT_VALUE_SEPARATOR,
|
|
pandas_tables_helpers.get_shape(arr),
|
|
NEXT_VALUE_SEPARATOR,
|
|
pandas_tables_helpers.get_head(arr),
|
|
NEXT_VALUE_SEPARATOR,
|
|
pandas_tables_helpers.get_column_types(arr)]
|
|
actual = '\n'.join(actual)
|
|
read_expected_from_file_and_compare_with_actual(
|
|
actual=actual,
|
|
expected_file=file
|
|
)
|
|
|
|
|
|
def test_simple_array():
|
|
arr = np.array([1, 2, 3])
|
|
check_info_np_array(arr, 'test_data/numpy/simple_np_array_after.txt')
|
|
|
|
|
|
def test_simple_2d_array():
|
|
arr = np.array([[True, "False", True], [True, True, False]])
|
|
check_info_np_array(arr, 'test_data/numpy/simple_2d_np_array_after.txt')
|
|
|
|
|
|
def test_2d_array():
|
|
arr = np.array([[1, 2, 3],
|
|
[4, 5, 6],
|
|
[7, 8, 9]])
|
|
check_info_np_array(arr, 'test_data/numpy/2d_np_array_after.txt')
|
|
|
|
|
|
def test_array_with_dtype():
|
|
arr = np.array([(10, 3.14, 'Hello', True),
|
|
(20, 2.71, 'World', False)],
|
|
dtype=[
|
|
("ci", "i4"),
|
|
("cf", "f4"),
|
|
("cs", "U16"),
|
|
("cb", "?")])
|
|
check_info_np_array(arr, 'test_data/numpy/np_array_with_dtype_after.txt')
|
|
|
|
|
|
def test_sorting_simple_array():
|
|
arr = np.array([1, 2, 3])
|
|
sort_by_index = _sort_array(arr, [0], [False])
|
|
expected_indexes = np.array([2, 1, 0])
|
|
expected_arr = arr[::-1]
|
|
assert _is_equals(sort_by_index.array, expected_arr)
|
|
assert _is_equals(sort_by_index.indexes, expected_indexes)
|
|
|
|
sort_by_values = _sort_array(arr, [1], [False])
|
|
assert _is_equals(sort_by_values.array, expected_arr)
|
|
assert _is_equals(sort_by_values.indexes, expected_indexes)
|
|
|
|
|
|
def test_sorting_2d_array():
|
|
arr = np.array([[1, 2, 7],
|
|
[4, 2, 2],
|
|
[7, 8, 9]])
|
|
sorted_array = _sort_array(arr, [2, 1], [True, False])
|
|
expected_indexes = np.array([1, 0, 2])
|
|
expected_arr = np.array([[4, 2, 2],
|
|
[1, 2, 7],
|
|
[7, 8, 9]])
|
|
assert _is_equals(sorted_array.array, expected_arr)
|
|
assert _is_equals(sorted_array.indexes, expected_indexes)
|
|
|
|
|
|
def test_sorting_array_with_types():
|
|
dtypes = [
|
|
("ci", "i4"),
|
|
("cf", "f4"),
|
|
("cs", "U16"),
|
|
("cb", "?")]
|
|
arr = np.array([(10, 3.14, 'a', True),
|
|
(20, 2.71, 'b', True),
|
|
(30, 2.71, 'a', True)],
|
|
dtype=dtypes)
|
|
sorted_array = _sort_array(arr, [4, 3, 2], [True, True, True])
|
|
expected_indexes = np.array([2, 0, 1])
|
|
expected_arr = np.array([(30, 2.71, 'a', True),
|
|
(10, 3.14, 'a', True),
|
|
(20, 2.71, 'b', True)],
|
|
dtype=dtypes)
|
|
assert _is_equals(sorted_array.indexes, expected_indexes)
|
|
assert _is_equals(sorted_array.array, expected_arr)
|
|
|
|
|
|
def read_expected_from_file_and_compare_with_actual(actual, expected_file):
|
|
with open(expected_file, 'r') as in_f:
|
|
expected = in_f.read()
|
|
|
|
# for a more convenient assertion fails messages here we compare string char by char
|
|
for ind, (act, exp) in enumerate(zip(actual, expected)):
|
|
assert act == exp, \
|
|
("index is %s, act part = %s, exp part = %s" %
|
|
(ind,
|
|
actual[max(0, ind - 20): min(len(actual) - 1, ind + 20)],
|
|
expected[max(0, ind - 20): min(len(actual) - 1, ind + 20)]))
|
|
|
|
|
|
def _sort_array(arr, cols, orders):
|
|
return pandas_tables_helpers._NpTable(arr).sort((cols, orders))
|
|
|
|
|
|
def _is_equals(arr_a, arr_b):
|
|
return (arr_a == arr_b).all()
|