On 9/7/06, Martin Spacek <[EMAIL PROTECTED]> wrote:
I don't know about count, but you can gin up something like this
In [78]: a = ran.randint(0,2, size=(10,))
In [79]: a
Out[79]: array([0, 1, 0, 1, 1, 0, 0, 1, 1, 1])
In [80]: b = sort(a)
In [81]: b.searchsorted(1, side='right') - b.searchsorted(1, side='left')
Out[81]: 6
Which counts the number of ones in a.
Well, 1.1 == 1.1000000000000001 and that doesn't change. You probably need to use different precisions to run into problems.
Chuck
What's the most straightforward way to count, say, the number of 1s or
Trues in the array? Or the number of any integer?
I was surprised to discover recently that there isn't a count() method
as there is for Python lists. Sorry if this has been discussed already,
but I'm wondering if there's a reason for its absence.
I don't know about count, but you can gin up something like this
In [78]: a = ran.randint(0,2, size=(10,))
In [79]: a
Out[79]: array([0, 1, 0, 1, 1, 0, 0, 1, 1, 1])
In [80]: b = sort(a)
In [81]: b.searchsorted(1, side='right') - b.searchsorted(1, side='left')
Out[81]: 6
Which counts the number of ones in a.
I came across a thread in March:
http://aspn.activestate.com/ASPN/Mail/Message/numpy-discussion/3066460
that talked a bit about this in terms of speed, but what about just the
convenience of having a count() method?
Looks like masked arrays have a count method, don't know much about them
though.
Also, I understand the inaccuracies when converting between binary and
decimal floating point representations, and therefore making counting of
a specific float value in an array somewhat undefined, yet it seems to
work in Python lists:
>>> 1.1
1.1000000000000001
>>> a=[1.1, 1.1, 1.2]
>>> a
[1.1000000000000001, 1.1000000000000001, 1.2]
>>> a.count(1.1)
2
>>> a.count(1.1000000000000001)
2
>>> a.count(1.2)
1
Well, 1.1 == 1.1000000000000001 and that doesn't change. You probably need to use different precisions to run into problems.
Chuck
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