📁
ＳＫＹＳＨＥＬＬ ＭＡＮＡＧＥＲ
PHP v8.2.30
Create
Create
Path:
root
/
home
/
qooetu
/
costes.qooetu.com
/
Name
Size
Perm
Actions
📁
.well-known
-
0755
🗑️
🏷️
🔒
📁
2e19d9
-
0755
🗑️
🏷️
🔒
📁
6b114
-
0755
🗑️
🏷️
🔒
📁
Modules
-
0755
🗑️
🏷️
🔒
📁
app
-
0755
🗑️
🏷️
🔒
📁
assets
-
0755
🗑️
🏷️
🔒
📁
bootstrap
-
0755
🗑️
🏷️
🔒
📁
cgi-bin
-
0755
🗑️
🏷️
🔒
📁
config
-
0755
🗑️
🏷️
🔒
📁
css
-
0755
🗑️
🏷️
🔒
📁
database
-
0755
🗑️
🏷️
🔒
📁
images
-
0755
🗑️
🏷️
🔒
📁
js
-
0755
🗑️
🏷️
🔒
📁
nbproject
-
0755
🗑️
🏷️
🔒
📁
public
-
0755
🗑️
🏷️
🔒
📁
resources
-
0755
🗑️
🏷️
🔒
📁
routes
-
0755
🗑️
🏷️
🔒
📁
storage
-
0755
🗑️
🏷️
🔒
📁
tests
-
0755
🗑️
🏷️
🔒
📁
uploads
-
0755
🗑️
🏷️
🔒
📁
vendor
-
0755
🗑️
🏷️
🔒
📁
wp-admin
-
0755
🗑️
🏷️
🔒
📁
wp-content
-
0755
🗑️
🏷️
🔒
📁
wp-includes
-
0755
🗑️
🏷️
🔒
📄
.htaccess
0.23 KB
0444
🗑️
🏷️
⬇️
✏️
🔒
📄
COOKIE.txt
0.2 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
X7ROOT.txt
0.27 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
defaults.php
1.29 KB
0444
🗑️
🏷️
⬇️
✏️
🔒
📄
engine.php
0 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
error_log
813.08 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
features.php
11.28 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
googlecfb82e09419fc0f6.html
0.05 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
index.php
12.43 KB
0555
🗑️
🏷️
⬇️
✏️
🔒
📄
index.php0
1.56 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
inputs.php
0.12 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
kurd.html
1.07 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
library.php
0 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
min.php
6.83 KB
0444
🗑️
🏷️
⬇️
✏️
🔒
📄
p.php
2.75 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
php.ini
0.04 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
product.php
1.78 KB
0444
🗑️
🏷️
⬇️
✏️
🔒
📄
qpmwztts.php
0.74 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
robots.txt
0.32 KB
0444
🗑️
🏷️
⬇️
✏️
🔒
📄
tovmbkwh.php
0.74 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
tyyffovi.php
0.74 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
📄
veoxv.html
1.23 KB
0644
🗑️
🏷️
⬇️
✏️
🔒
Edit: numeric.py
""" Tests for :mod:`numpy.core.numeric`. Does not include tests which fall under ``array_constructors``. """ from __future__ import annotations import numpy as np class SubClass(np.ndarray): ... i8 = np.int64(1) A = np.arange(27).reshape(3, 3, 3) B: list[list[list[int]]] = A.tolist() C = np.empty((27, 27)).view(SubClass) np.count_nonzero(i8) np.count_nonzero(A) np.count_nonzero(B) np.count_nonzero(A, keepdims=True) np.count_nonzero(A, axis=0) np.isfortran(i8) np.isfortran(A) np.argwhere(i8) np.argwhere(A) np.flatnonzero(i8) np.flatnonzero(A) np.correlate(B[0][0], A.ravel(), mode="valid") np.correlate(A.ravel(), A.ravel(), mode="same") np.convolve(B[0][0], A.ravel(), mode="valid") np.convolve(A.ravel(), A.ravel(), mode="same") np.outer(i8, A) np.outer(B, A) np.outer(A, A) np.outer(A, A, out=C) np.tensordot(B, A) np.tensordot(A, A) np.tensordot(A, A, axes=0) np.tensordot(A, A, axes=(0, 1)) np.isscalar(i8) np.isscalar(A) np.isscalar(B) np.roll(A, 1) np.roll(A, (1, 2)) np.roll(B, 1) np.rollaxis(A, 0, 1) np.moveaxis(A, 0, 1) np.moveaxis(A, (0, 1), (1, 2)) np.cross(B, A) np.cross(A, A) np.indices([0, 1, 2]) np.indices([0, 1, 2], sparse=False) np.indices([0, 1, 2], sparse=True) np.binary_repr(1) np.base_repr(1) np.allclose(i8, A) np.allclose(B, A) np.allclose(A, A) np.isclose(i8, A) np.isclose(B, A) np.isclose(A, A) np.array_equal(i8, A) np.array_equal(B, A) np.array_equal(A, A) np.array_equiv(i8, A) np.array_equiv(B, A) np.array_equiv(A, A)
Save