--- /srv/reproducible-results/rbuild-debian/r-b-build.WRA8iwP4/b1/numpy_2.2.4+ds-1_arm64.changes +++ /srv/reproducible-results/rbuild-debian/r-b-build.WRA8iwP4/b2/numpy_2.2.4+ds-1_arm64.changes ├── Files │ @@ -1,5 +1,5 @@ │ │ - 4d67ba741c74c3da256c4171f663287f 5814136 doc optional python-numpy-doc_2.2.4+ds-1_all.deb │ + 91f90c3e4c74ae47e65c93c4714987a3 5814016 doc optional python-numpy-doc_2.2.4+ds-1_all.deb │ bcf02a7b158e3fd72ac0ca631097dbbe 14380220 debug optional python3-numpy-dbgsym_2.2.4+ds-1_arm64.deb │ 3a5b3ecec4a4b617987f388521dd977f 136096 python optional python3-numpy-dev_2.2.4+ds-1_arm64.deb │ c5979eb908a4d2251ef0d8267822664e 3604888 python optional python3-numpy_2.2.4+ds-1_arm64.deb ├── python-numpy-doc_2.2.4+ds-1_all.deb │ ├── file list │ │ @@ -1,3 +1,3 @@ │ │ -rw-r--r-- 0 0 0 4 2025-04-01 19:45:23.000000 debian-binary │ │ --rw-r--r-- 0 0 0 64868 2025-04-01 19:45:23.000000 control.tar.xz │ │ --rw-r--r-- 0 0 0 5749076 2025-04-01 19:45:23.000000 data.tar.xz │ │ +-rw-r--r-- 0 0 0 64872 2025-04-01 19:45:23.000000 control.tar.xz │ │ +-rw-r--r-- 0 0 0 5748952 2025-04-01 19:45:23.000000 data.tar.xz │ ├── control.tar.xz │ │ ├── control.tar │ │ │ ├── ./md5sums │ │ │ │ ├── ./md5sums │ │ │ │ │┄ Files differ │ ├── data.tar.xz │ │ ├── data.tar │ │ │ ├── file list │ │ │ │ @@ -2578,15 +2578,15 @@ │ │ │ │ -rw-r--r-- 0 root (0) root (0) 42758 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.wald.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 47423 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.weibull.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 45546 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generated/numpy.random.zipf.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 82403 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/random/generator.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 45982 2025-04-01 19:45:23.000000 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./usr/share/doc/python-numpy/html/reference/random/upgrading-pcg64.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 45998 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-creation.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 50957 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.array-manipulation.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 27535 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.bitwise.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 54450 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/reference/routines.char.html │ │ │ │ @@ -2755,15 +2755,15 @@ │ │ │ │ -rw-r--r-- 0 root (0) root (0) 31655 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.1-notes.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 32348 2025-04-01 19:45:23.000000 ./usr/share/doc/python-numpy/html/release/2.2.2-notes.html │ │ │ │ -rw-r--r-- 0 root (0) root (0) 32865 2025-04-01 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In [1]: import numpy.random
│ │ │ │  
│ │ │ │  In [2]: rng = np.random.default_rng()
│ │ │ │  
│ │ │ │  In [3]: %timeit -n 1 rng.standard_normal(100000)
│ │ │ │     ...: %timeit -n 1 numpy.random.standard_normal(100000)
│ │ │ │     ...: 
│ │ │ │ -1.03 ms +- 56.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -2.51 ms +- 23.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +1.03 ms +- 65.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +2.52 ms +- 38.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │  
│ │ │ │
│ │ │ │
In [4]: %timeit -n 1 rng.standard_exponential(100000)
│ │ │ │     ...: %timeit -n 1 numpy.random.standard_exponential(100000)
│ │ │ │     ...: 
│ │ │ │ -1.02 ms +- 28.1 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -1.77 ms +- 13.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +980 us +- 11.9 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +1.76 ms +- 12.8 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │  
│ │ │ │
│ │ │ │
In [5]: %timeit -n 1 rng.standard_gamma(3.0, 100000)
│ │ │ │     ...: %timeit -n 1 numpy.random.standard_gamma(3.0, 100000)
│ │ │ │     ...: 
│ │ │ │ -2.46 ms +- 25.3 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ -4.48 ms +- 17.2 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +2.49 ms +- 22.4 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │ +4.47 ms +- 15.5 us per loop (mean +- std. dev. of 7 runs, 1 loop each)
│ │ │ │  
│ │ │ │
│ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
In [6]: rng = np.random.default_rng()
│ │ │ │  
│ │ │ │  In [7]: rng.random(3, dtype=np.float64)
│ │ │ │ -Out[7]: array([0.98180209, 0.81425915, 0.17006705])
│ │ │ │ +Out[7]: array([0.66860127, 0.02797909, 0.29098487])
│ │ │ │  
│ │ │ │  In [8]: rng.random(3, dtype=np.float32)
│ │ │ │ -Out[8]: array([0.6130314 , 0.27063346, 0.4075511 ], dtype=float32)
│ │ │ │ +Out[8]: array([0.7061747 , 0.13191795, 0.6566726 ], dtype=float32)
│ │ │ │  
│ │ │ │  In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)
│ │ │ │ -Out[9]: array([95, 67, 54], dtype=uint8)
│ │ │ │ +Out[9]: array([166,  24, 143], dtype=uint8)
│ │ │ │  
│ │ │ │
│ │ │ │