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From: Wayne Watson <sierra_mtnview@sb...>  20091130 19:56:47

Another related question. is there some statistics function that computes the mean, std. dev., min/max, etc. from a frequency distribution?  Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year.  The Science of Fear by D. Gardner Web Page: <www.speckledwithstars.net/> 
From: Wayne Watson <sierra_mtnview@sb...>  20091130 15:52:54

I'm working with a Python program that produces freq below. There are 32 bins. The bins represent 07, 814, ..., 248  255 of a set of frequencies (integer counts). 0 to 255 are the brightness pixel values from a 640x480 frame of b/w pixels. I binned 8 into each of 32 bins. One can easily see that the various bins are of a different height. However, the result is fixed height bar from 0 to 10, and a shorter single bar from about 120 to 130. The xscale goes from 0 to 140 and not from 0 to 255, or somewhere in that range. It seems like hist is clumping everything into two groups. I've changed the range parameter several times and get the same result. I'd send an attachment of the figure, but that often seems to delay a post in most of these Python mail lists. freq = [127516, 8548, 46797, 46648, 21085, 9084, 7466, 6534, 5801, 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] fig = pylab.figure() v = array(freq) plt.hist(v, bins=linspace(0,256,nplt_bins+1), normed=1, range=(30,200)) pylab.show()  Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year.  The Science of Fear by D. Gardner Web Page: <www.speckledwithstars.net/> 
From: Wayne Watson <sierra_mtnview@sb...>  20091130 16:46:55

That helped by using the original data of 256 elements. So all the large values in the array beyond 120 would be tiny bars stretched out to x of about 127516. OK, now with the original 256 elements I see some problems. Individually, they contain some high counts, so I guess they are going off scale. This is unfortunate, since the original data was put into 256 bins by hardware from 307,000 + values. It looks like what I should be feeding hist, but recreating the 307K from the 256 seems something of a waste in that it is undoing what the hardware did. Is there some graph function that will treat the input as already binned? For example, if I have [10, 7, 5], I want to see a histogram of three bars, one at x =0 of height 10, one at x=1 of height 6, and 2 of height 5. x might be some other numbers like 18.2, 46.3 and 60.1. Pierre de Buyl wrote: > Hello, > > hist takes the raw data directly, and not a histogram already computed. > > If data is an array containing your pixels, > hist(data, bins = range(0,255,8) , normed=True) should do what you expect > > The code you sent adequately counts 13 occurences for 0 in freq and > one at 121, with some rescaling. > > Pierre > > Le 30 nov. 09 à 16:52, Wayne Watson a écrit : > >> I'm working with a Python program that produces freq below. There are 32 >> bins. The bins represent 07, 814, ..., 248  255 of a set of >> frequencies (integer counts). 0 to 255 are the brightness pixel values >> from a 640x480 frame of b/w pixels. I binned 8 into each of 32 bins. One >> can easily see that the various bins are of a different height. However, >> the result is fixed height bar from 0 to 10, and a shorter single bar >> from about 120 to 130. The xscale goes from 0 to 140 and not from 0 to >> 255, or somewhere in that range. It seems like hist is clumping >> everything into two groups. I've changed the range parameter several >> times and get the same result. I'd send an attachment of the figure, but >> that often seems to delay a post in most of these Python mail lists. >> >> freq = [127516, 8548, 46797, 46648, 21085, 9084, 7466, 6534, 5801, >> 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0, >> 0, 0, 0, 0, 0, 0, 0, 0] >> fig = pylab.figure() >> v = array(freq) >> plt.hist(v, bins=linspace(0,256,nplt_bins+1), normed=1, range=(30,200)) >> pylab.show() >> >>  >> Wayne Watson (Watson Adventures, Prop., Nevada City, CA) > >  Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year.  The Science of Fear by D. Gardner Web Page: <www.speckledwithstars.net/> 
From: Pierre de Buyl <pdebuyl@ul...>  20091130 17:37:34

bar does what you need. import numpy as np import matplotlib.pyplot as plt freq = np.array( [127516, 8548, 46797, 46648, 21085, 9084, 7466, 6534, 5801, 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] ) fig = plt.figure() plt.bar(range(0,255,8),freq*1./freq.sum(),width=8) # the 1. avoid an integer division that gives 0 everywhere. # width=8 specifies that each bins takes 8 units of width, corresponding to the spacing in range(0,255,8) plt.show() Le 30 nov. 09 à 17:46, Wayne Watson a écrit : > That helped by using the original data of 256 elements. So all the > large values in the array beyond 120 would be tiny bars stretched > out to x of about 127516. OK, now with the original 256 > elements I see some problems. > > Individually, they contain some high counts, so I guess they are > going off scale. This is unfortunate, since the original data > was put into 256 bins by hardware from 307,000 + values. It looks > like what I should be feeding hist, but recreating the 307K from > the 256 seems something of a waste in that it is undoing what the > hardware did. Is there some graph function that will treat the > input as already binned? For example, if I have [10, 7, 5], I want > to see a histogram of three bars, one at x =0 of height 10, one at > x=1 of height 6, and 2 of height 5. x might be some other numbers > like 18.2, 46.3 and 60.1. > > Pierre de Buyl wrote: >> Hello, >> >> hist takes the raw data directly, and not a histogram already >> computed. >> >> If data is an array containing your pixels, >> hist(data, bins = range(0,255,8) , normed=True) should do what you >> expect >> >> The code you sent adequately counts 13 occurences for 0 in freq >> and one at 121, with some rescaling. >> >> Pierre >> >> Le 30 nov. 09 à 16:52, Wayne Watson a écrit : >> >>> I'm working with a Python program that produces freq below. There >>> are 32 >>> bins. The bins represent 07, 814, ..., 248  255 of a set of >>> frequencies (integer counts). 0 to 255 are the brightness pixel >>> values >>> from a 640x480 frame of b/w pixels. I binned 8 into each of 32 >>> bins. One >>> can easily see that the various bins are of a different height. >>> However, >>> the result is fixed height bar from 0 to 10, and a shorter single >>> bar >>> from about 120 to 130. The xscale goes from 0 to 140 and not >>> from 0 to >>> 255, or somewhere in that range. It seems like hist is clumping >>> everything into two groups. I've changed the range parameter several >>> times and get the same result. I'd send an attachment of the >>> figure, but >>> that often seems to delay a post in most of these Python mail lists. >>> >>> freq = [127516, 8548, 46797, 46648, 21085, 9084, 7466, 6534, 5801, >>> 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, >>> 0, 0, 0, >>> 0, 0, 0, 0, 0, 0, 0, 0] >>> fig = pylab.figure() >>> v = array(freq) >>> plt.hist(v, bins=linspace(0,256,nplt_bins+1), normed=1, range= >>> (30,200)) >>> pylab.show() >>> >>>  >>> Wayne Watson (Watson Adventures, Prop., Nevada City, CA) >> >> > >  > Wayne Watson (Watson Adventures, Prop., Nevada City, CA) > > (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) > Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 > feet The popular press and many > authorities believe the number > of pedifiles that prowl the web is 50,00. There are no > figures that support this. The number of children below > 18 years of age kidnapped by strangers is 1 in 600,00, > or 115 per year.  The Science of Fear by D. Gardner > Web Page: <www.speckledwithstars.net/> > 
From: Wayne Watson <sierra_mtnview@sb...>  20091130 19:54:48

Thanks. Very good. Pierre de Buyl wrote: > bar does what you need. > > import numpy as np > import matplotlib.pyplot as plt > > freq = np.array( [127516, 8548, 46797, 46648, 21085, 9084, 7466, > 6534, 5801, > 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0, > 0, 0, 0, 0, 0, 0, 0, 0] ) > > fig = plt.figure() > plt.bar(range(0,255,8),freq*1./freq.sum(),width=8) > # the 1. avoid an integer division that gives 0 everywhere. > # width=8 specifies that each bins takes 8 units of width, > corresponding to the spacing in range(0,255,8) > plt.show() > > Le 30 nov. 09 à 17:46, Wayne Watson a écrit : > >> That helped by using the original data of 256 elements. So all the >> large values in the array beyond 120 would be tiny bars stretched >> out to x of about 127516. OK, now with the original 256 elements >> I see some problems. >> >> Individually, they contain some high counts, so I guess they are >> going off scale. This is unfortunate, since the original data was >> put into 256 bins by hardware from 307,000 + values. It looks like >> what I should be feeding hist, but recreating the 307K from the 256 >> seems something of a waste in that it is undoing what the hardware >> did. Is there some graph function that will treat the input as >> already binned? For example, if I have [10, 7, 5], I want to see a >> histogram of three bars, one at x =0 of height 10, one at x=1 of >> height 6, and 2 of height 5. x might be some other numbers like >> 18.2, 46.3 and 60.1. >> >> Pierre de Buyl wrote: >>> Hello, >>> >>> hist takes the raw data directly, and not a histogram already computed. >>> >>> If data is an array containing your pixels, >>> hist(data, bins = range(0,255,8) , normed=True) should do what you >>> expect >>> >>> The code you sent adequately counts 13 occurences for 0 in freq and >>> one at 121, with some rescaling. >>> >>> Pierre >>> >>> Le 30 nov. 09 à 16:52, Wayne Watson a écrit : >>> >>>> I'm working with a Python program that produces freq below. There >>>> are 32 >>>> bins. The bins represent 07, 814, ..., 248  255 of a set of >>>> frequencies (integer counts). 0 to 255 are the brightness pixel values >>>> from a 640x480 frame of b/w pixels. I binned 8 into each of 32 >>>> bins. One >>>> can easily see that the various bins are of a different height. >>>> However, >>>> the result is fixed height bar from 0 to 10, and a shorter single bar >>>> from about 120 to 130. The xscale goes from 0 to 140 and not from >>>> 0 to >>>> 255, or somewhere in that range. It seems like hist is clumping >>>> everything into two groups. I've changed the range parameter several >>>> times and get the same result. I'd send an attachment of the >>>> figure, but >>>> that often seems to delay a post in most of these Python mail lists. >>>> >>>> freq = [127516, 8548, 46797, 46648, 21085, 9084, 7466, 6534, 5801, >>>> 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, >>>> 0, 0, >>>> 0, 0, 0, 0, 0, 0, 0, 0] >>>> fig = pylab.figure() >>>> v = array(freq) >>>> plt.hist(v, bins=linspace(0,256,nplt_bins+1), normed=1, >>>> range=(30,200)) >>>> pylab.show() >>>> >>>>  >>>> Wayne Watson (Watson Adventures, Prop., Nevada City, CA) >>> >>> >> >>  >> Wayne Watson (Watson Adventures, Prop., Nevada City, CA) >> >> (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) >> Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 >> feet The popular press and many authorities >> believe the number >> of pedifiles that prowl the web is 50,00. There are no >> figures that support this. The number of children below >> 18 years of age kidnapped by strangers is 1 in 600,00, >> or 115 per year.  The Science of Fear by D. Gardner >> Web Page: <www.speckledwithstars.net/> >> > >  Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year.  The Science of Fear by D. Gardner Web Page: <www.speckledwithstars.net/> 
From: Wayne Watson <sierra_mtnview@sb...>  20091130 19:56:47

Another related question. is there some statistics function that computes the mean, std. dev., min/max, etc. from a frequency distribution?  Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year.  The Science of Fear by D. Gardner Web Page: <www.speckledwithstars.net/> 