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author | Ross Barnowski <rossbar@berkeley.edu> | 2020-04-25 11:44:09 -0700 |
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committer | Ross Barnowski <rossbar@berkeley.edu> | 2020-04-25 13:19:22 -0700 |
commit | b751304ec2d1781256d53e1c2faa0908b398240d (patch) | |
tree | 31997c016cea3b26673ee12c1c69bd3a3a84e01e /doc | |
parent | 619422b493eaf88c42373af1725ac0aa2297fa91 (diff) | |
download | numpy-b751304ec2d1781256d53e1c2faa0908b398240d.tar.gz |
DOC,BLD: Limit timeit iterations in random docs.
Limiting the number of loops performed in the %timeit evaluation
results in a ~20% speedup in the time it takes to build the
documentation.
The results of the "benchmarking" are less accurate from the limited
number of evaluations, but the relationship between the timing
between the legacy and Generator sampling methods is preserved.
Diffstat (limited to 'doc')
-rw-r--r-- | doc/source/reference/random/new-or-different.rst | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/doc/source/reference/random/new-or-different.rst b/doc/source/reference/random/new-or-different.rst index b3bddb443..ed55c71bf 100644 --- a/doc/source/reference/random/new-or-different.rst +++ b/doc/source/reference/random/new-or-different.rst @@ -69,18 +69,18 @@ And in more detail: from numpy.random import Generator, PCG64 import numpy.random rg = Generator(PCG64()) - %timeit rg.standard_normal(100000) - %timeit numpy.random.standard_normal(100000) + %timeit -n 1 rg.standard_normal(100000) + %timeit -n 1 numpy.random.standard_normal(100000) .. ipython:: python - %timeit rg.standard_exponential(100000) - %timeit numpy.random.standard_exponential(100000) + %timeit -n 1 rg.standard_exponential(100000) + %timeit -n 1 numpy.random.standard_exponential(100000) .. ipython:: python - %timeit rg.standard_gamma(3.0, 100000) - %timeit numpy.random.standard_gamma(3.0, 100000) + %timeit -n 1 rg.standard_gamma(3.0, 100000) + %timeit -n 1 numpy.random.standard_gamma(3.0, 100000) * Optional ``dtype`` argument that accepts ``np.float32`` or ``np.float64`` to produce either single or double prevision uniform random variables for |