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In [1]: import numpy.random\n \n In [2]: rng = np.random.default_rng()\n \n In [3]: %timeit -n 1 rng.standard_normal(100000)\n    ...: %timeit -n 1 numpy.random.standard_normal(100000)\n    ...: \n-1.18 ms +- 377 us per loop (mean +- std. dev. of 7 runs, 1 loop each)\n-2.59 ms +- 150 us per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+The slowest run took 25.45 times longer than the fastest. This could mean that an intermediate result is being cached.\n+7.9 ms +- 10.9 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+The slowest run took 17.03 times longer than the fastest. This could mean that an intermediate result is being cached.\n+22.6 ms +- 14.5 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n 
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In [4]: %timeit -n 1 rng.standard_exponential(100000)\n    ...: %timeit -n 1 numpy.random.standard_exponential(100000)\n    ...: \n-1e+03 us +- 21 us per loop (mean +- std. dev. of 7 runs, 1 loop each)\n-3.51 ms +- 2 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+The slowest run took 25.80 times longer than the fastest. This could mean that an intermediate result is being cached.\n+7.31 ms +- 10 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+The slowest run took 23.75 times longer than the fastest. This could mean that an intermediate result is being cached.\n+17.8 ms +- 15.3 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n 
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In [5]: %timeit -n 1 rng.standard_gamma(3.0, 100000)\n    ...: %timeit -n 1 numpy.random.standard_gamma(3.0, 100000)\n    ...: \n-4.08 ms +- 1.83 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n-14.5 ms +- 3.3 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+The slowest run took 17.38 times longer than the fastest. This could mean that an intermediate result is being cached.\n+20.2 ms +- 16 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n+38.9 ms +- 13.8 ms per loop (mean +- std. dev. of 7 runs, 1 loop each)\n 
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In [6]: rng = np.random.default_rng()\n \n In [7]: rng.random(3, dtype=np.float64)\n-Out[7]: array([0.47169714, 0.42051301, 0.52594313])\n+Out[7]: array([0.51992473, 0.27779742, 0.44925707])\n \n In [8]: rng.random(3, dtype=np.float32)\n-Out[8]: array([0.4693439 , 0.77238125, 0.15599883], dtype=float32)\n+Out[8]: array([0.06649375, 0.7478386 , 0.7303245 ], dtype=float32)\n \n In [9]: rng.integers(0, 256, size=3, dtype=np.uint8)\n-Out[9]: array([178,  80,   5], dtype=uint8)\n+Out[9]: array([89, 61, 33], dtype=uint8)\n 
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