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What's the periodic of the folding results? #1
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Hey there, thanks for mailing.
I'm afraid I'm not sure of exactly what you're asking. Do you think you
could send me some examples of the input/output your getting from ffancy,
as well as the commands you are using to run it? That might help to make
things clearer.
Cheers,
- Andrew
…On Fri, Jul 14, 2017 at 10:05 AM, desword ***@***.***> wrote:
Thanks for your code. I have one question that how to determine which
periodicity belongs to my signal? For example, now I have test and get the
folding sum distribution with periodic range from 0 to N. Then, how to
determine which periodic is correct? According to the biggest folding sum
peak that the periodic has?
For example, I have obtained three folding sum distribution with periodic
(3, 4, 5), and distributions are [0:2, 1:5, 2: 10, 3:2 ], [0:2, 1:5, 2:8,
3:2, 4:2], [0:2, 1:5, 2:2, 3:2, 4:2, 5:4 ]. The tuple (x, y), where x means
the phase and y means the sum. And the example maybe not practical, but I
want to know is which periodic should I choose? Is it the periodic 3
because its corresponding distribution has the biggest folding sum *2:10*
?
Thanks!
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Sorry for the late response. I am asking how to determine the periodic according to the FFA results. In my implementation, I first want to fold all the possible periodic, and then find the periodic with the highest folding sum. However, I find it is wrong. because any results that is the order of the correct periodic would be treated as the correct periodic. And the periodic would be one if I pick the periodic with the largest folding sum. For example, the correct periodic is 120, however, when I fold the signal with periodic one, I will have the highest folding sum. here is my matlab code. thanks |
by the way, how to contact you conveniently? your email is invalid. |
Thanks again for writing. This means of communication is alright, but if
you wish to email me more directly, my address is indeed
acameron@mpifr-bonn.mpg.de. That address should work just fine.
As for the FFA, I describe several methods of evaluating the results of the
FFA in the paper I published (
http://adsabs.harvard.edu/abs/2017MNRAS.468.1994C). But to explain it again
briefly:
Say you have a dataset that is N samples long, and there is a signal with
period P samples hidden in that dataset. Running a *single* execution of
the FFA will search from a period of P samples to P + 1 samples, and will
output N/P folded signal profiles which have incremental periods between P
and P+1. Note that the FFA works only when N/P = 2^x, so in order to search
over any value of P, you have to modify your value of N slightly.
Now, the FFA only produces the folded profiles - it does not tell you which
of those profiles contains the best signal. That is where you need
something like a "Profile Evaluation Algorithm" which analyses these folded
profiles and comes up with a number which can be treated like a S/N value
for each profile. In my paper, I analyse two different techniques, labeled
Algorithm 1 & 2.
I hope that helps. Have a read of the paper if you haven't already, and let
me know if you have any other questions.
Cheers,
- Andrew
PS. What sort of compile error are you getting? Perhaps I can help.
…On Sun, Jul 23, 2017 at 5:23 AM, desword ***@***.***> wrote:
by the way, how to contact you conveniently? your email is invalid.
***@***.***
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Thanks! I will deep into this paper. Following is the error msg:
Following is the version of GCC:
|
Answering this on my phone, but at a guess: all the missing functions
appear to be from math.h, which should be part of your GCC but apparently
isn't. I'd double check that first.
Cheers,
…-Andrew
On 31 Jul 2017 10:17 AM, "desword" <notifications@github.com> wrote:
Thanks! I will deep into this paper.
Following is the error msg:
gcc -Wall -Werror -lm ffancy.o dataarray.o ffa.o ffadata.o mad.o metric1.o
metric2.o metric3.o metric4.o metric5.o metric7.o metric8.o paddedarray.o
power2resizer.o equalstrings.o whitenoise.o runningmedian.o -o ffancy
ffancy.o: In function main': ffancy.c:(.text+0x97e): undefined reference to
pow'
dataarray.o: In function basicPulsarDataArray': dataarray.c:(.text+0x62):
undefined reference toceil'
dataarray.o: In function readASCIIDataArray': dataarray.c:(.text+0x280):
undefined reference toceil'
dataarray.o: In function readFloatDataArray': dataarray.c:(.text+0x49b):
undefined reference toceil'
dataarray.o: In function readSIGPYPROCDataArray':
dataarray.c:(.text+0x6ab): undefined reference toceil'
dataarray.o: In function dereddenDataArray': dataarray.c:(.text+0xdd7):
undefined reference toceil'
ffa.o: In function massFFA': ffa.c:(.text+0x18a): undefined reference to
fmod'
ffa.c:(.text+0x220): undefined reference to pow' ffa.c:(.text+0x31d):
undefined reference topow'
ffa.o: In function singleFFA': ffa.c:(.text+0x63a): undefined reference to
log2'
ffa.c:(.text+0x874): undefined reference to pow' ffa.c:(.text+0x8bc):
undefined reference toceil'
ffa.c:(.text+0x8df): undefined reference to floor' mad.o: In functionmad':
mad.c:(.text+0xb5): undefined reference to floor' mad.o: In function
getDeviances':
mad.c:(.text+0x2de): undefined reference to floor' metric1.o: In function
postMadMatchedFilterMetric':
metric1.c:(.text+0x63): undefined reference to log2'
metric1.c:(.text+0x7a): undefined reference toceil'
metric1.c:(.text+0x20d): undefined reference to sqrt'
metric1.c:(.text+0x24c): undefined reference tosqrt'
metric2.o: In function kondratievMFMetric': metric2.c:(.text+0x63):
undefined reference tolog2'
metric2.c:(.text+0x7a): undefined reference to ceil' metric4.o: In function
maxminMetric':
metric4.c:(.text+0x1a7): undefined reference to pow'
metric4.c:(.text+0x1dd): undefined reference tosqrt'
metric5.o: In function kondratievMetric': metric5.c:(.text+0x110):
undefined reference toceil'
metric5.c:(.text+0x202): undefined reference to pow'
metric5.c:(.text+0x238): undefined reference tosqrt'
power2resizer.o: In function power2Resizer': power2resizer.c:(.text+0x1d):
undefined reference tolog2'
power2resizer.c:(.text+0x3c): undefined reference to ceil'
power2resizer.c:(.text+0x66): undefined reference topow'
whitenoise.o: In function generateWhiteNoise': whitenoise.c:(.text+0xbe):
undefined reference tolog'
whitenoise.c:(.text+0xcf): undefined reference to sqrt'
whitenoise.c:(.text+0xea): undefined reference tocos'
whitenoise.c:(.text+0x109): undefined reference to log'
whitenoise.c:(.text+0x11a): undefined reference tosqrt'
whitenoise.c:(.text+0x135): undefined reference to `sin'
collect2: error: ld returned 1 exit status
make: *** [ffancy] Error 1
Following is the version of GCC:
gcc -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/4.8/lto-wrapper
Target: x86_64-linux-gnu
Thread model: posix
gcc version 4.8.4 (Ubuntu 4.8.4-2ubuntu1~14.04.3)
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Thanks for your code. I have one question that how to determine which periodicity belongs to my signal? For example, now I have test and get the folding sum distribution with periodic range from 0 to N. Then, how to determine which periodic is correct? According to the biggest folding sum peak that the periodic has?
For example, I have obtained three folding sum distribution with periodic (3, 4, 5), and distributions are [0:2, 1:5, 2: 10, 3:2 ], [0:2, 1:5, 2:8, 3:2, 4:2], [0:2, 1:5, 2:2, 3:2, 4:2, 5:4 ]. The tuple (x, y), where x means the phase and y means the sum. And the example maybe not practical, but I want to know is which periodic should I choose? Is it the periodic 3 because its corresponding distribution has the biggest folding sum 2:10 ?
Thanks!
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