I can imagine the hypothetical binary tilde being pretty for some kind of
equivalence. This is definitely not enough to motivate me to actually want
to add it. But I think this would read OK as equivalent:
numpy.allclose(arr1, arr2)
arr1 ~ arr2
However, the problem is that there are lots of other ways of being
equivalent other than having elements that are all close. In the examples
shown by Oscar and Aaron, we might ask whether two collections are drawn
from the same distribution. That a useful question. But would this tilde
mean the t-test? Unpaired or paired? Welch's t-test. Or maybe it should be
a Kolmogorov-Smirnov test. Or a Shapiro-Wilk test? Or Wilcoxon's
signed-rank test? Maybe Mann-Whitney's U test?
The R approach with a "formula" is just a quotation of the thing we might
test later, by whatever method. But as I've said, we already have quotes.
So code like this seems fine to me:
formula = "arr1 ~ arr2"
ks_test(formula)
welch_t(formula)
However, once I've written that, it seem to have little point not simply to
pass in the collections themselves to the various "equivalence" functions.
--
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from the bellies of the hungry; books from the hands of the
uneducated; technology from the underdeveloped; and putting
advocates of freedom in prisons. Intellectual property is
to the 21st century what the slave trade was to the 16th.
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