In other words, there is no such thing as a “column vector.”
It’s a matrix with “dimension“ 2.
A better way to phrase this is “has 2 axes” or, in J lingo,
as Don Guinn said, it’s about ranks.
You said
rvec =: 1 2 3
rather than
rvec =: 1 3 $ 1 2 3
but with cvec you told j to build a matrix aka rank 2 array
for rvec to be on par with cvec you’ll need
1 3 $ 1 2 3
mean =: +/ % #
$ $ mean rvec =: 1 3 $ 1 2 3
1
Am 15.04.20 um 19:37 schrieb Don Guinn:
The rank is reduced by one. So the rank 2 is reduced to one.
On Wed, Apr 15, 2020, 11:33 AM Thomas Bulka <[email protected]> wrote:
Hello everyone,
I do have some difficulties in understanding a certain behavior. Let's
assume, I define the classical mean verb, a row vector and a column
vector:
mean =: +/ % #
rvec =: 1 2 3
cvec =: 3 1 $ 1 2 3
When I apply mean to rvec I get the result 2 (as expected), which
happens to be a scalar ($$ mean rvec yields 0). When I apply mean to
cvec the result is a vector ($$ mean cvec yields 1). I'd like to
understand, why this behavior has been chosen. Do you have any hints for
me?
Regards,
Thomas
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