| Re: histogram, how to trasfer from linear bins to logarithmic bin? [message #68155 is a reply to message #68153] |
Wed, 30 September 2009 11:58   |
JDS
Messages: 94
Registered: March 2009
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Member |
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On Sep 29, 5:51 pm, David Fanning <n...@dfanning.com> wrote:
> JDS writes:
>> This would better be described as a way to create a histogram using
>> any arbitrary bins of your own devising; pretty cool indeed, since you
>> can design those bins in whatever way is useful. It does require you
>> to sort your array beforehand, and so in this case would be less
>> efficient than just taking the histogram of the log of your data.
>
> Actually, as I realized a couple of weeks ago
> in Australia when I was teaching this example,
> the array does NOT need to be sorted in this
> example. The cutoff vector needs to be monotonically
> increasing, but the array you are partitioning does
> not need to be.
>
> I've been using this method (without sorting) to
> process quite a lot of data recently, and I am
> *extremely* pleased with how darn fast it is!
Very good point. The sort is over the bin vector, which can be (and
usually is) much shorter than the data vector. And you will likely
setup your bin boundary vector sorted to begin with. That said, for
me HISTOGRAM(ALOG10) is still faster than HISTOGRAM(VALUE_LOCATE) (see
below). You'll also note some "sky is falling" razors-edge
differences between bins if you look closely.
JD
++++++++++++++++
n=100000000L
a=randomu(sd,n)*1.e8
t=systime(1)
h=histogram(alog10(a),BINSIZE=1)
print,'Hist(log)) ',systime(1)-t
t=systime(1)
mn=min(a,MAX=mx)
mn=alog10(mn) & mx=alog10(mx)
nbin=ceil(mx-mn)
bin=10.^(mn + findgen(nbin))
h2=histogram(value_locate(bin,a))
print,'Hist(value_locate)',systime(1)-t
print,h,h2
END
Hist(log)) 1.9417701
Hist(value_locate) 3.7843559
7 60 646 6203 63126
629722
6286765 62867178 30146293
7 60 647 6202 63126
629724
6286771 62867205 30146258
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