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authorRuediger Meier <ruediger.meier@ga-group.nl>2015-09-26 14:01:26 +0200
committerRuediger Meier <ruediger.meier@ga-group.nl>2015-09-30 23:18:55 +0200
commit08e8c1415670b029c26ae8ce0585fb9ea0b11e63 (patch)
tree38bce83f7f4bcf6ffa1c23894996135321d27939 /numpy/core/fromnumeric.py
parente6dbcead884019bd2aee802f78c41f6a9c46cd61 (diff)
downloadnumpy-08e8c1415670b029c26ae8ce0585fb9ea0b11e63.tar.gz
MAINT: corrcoef, memory usage optimization
We calculate sqrt on the small vector rather than on that huge product matrix and we combine the "outer" product with element-wise devision. So even though we have a slower loop over the rows now ... this code snippet runs about 3 times faster than before. However the speed improvement of the whole function is not really significant because cov() takes 80-99% of the time (dependent on blas/lapack implementation and number of CPU cores). More important is that we will safe 1/3 memory. For example corrcoef() for a [23k, m] matrix needs 8GB now instead of 12GB.
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