2008年11月14日金曜日

Power Law:(20)Jobless celebration?

(2008/11/09:celebration)
とうとう退職しました。
離職祝いで、1年ぶりに家族と、近くの居酒屋に行った。
i quitted. i went to the nearby tavern with the family by the jobless celebration.
Dining out is after an interval of one year?

予算枠は考えるが、一品ごとの値段は気にせず、飲み食いした。これは一般的でしょう。
The price of each goods was not anxiously, and ate and drank though thought about the budget frame. This might be general.

レシートは以下でした。
The receipt was the following.


値段を眺めていると、「Power Law」がみえたような気がした。
When the price was looked at, I thought that it saw "Power Law".

値段のランキングのみで傾向を見た。
The tendency was seen only in the ranking of the price.

A,Bを求める。
A and B are obtained.

y = -0.5775x + 7.2361
->
LN(y) = -0.5775 * LN(x) + 7.2361

LN
(x, y)=(1, exp(7.2361)),(14, exp(-0.5775 * LN(14) + 7.2361))
=(1, 1388.67),(14, 302.49)
Relative value)
=(1, 1388.67/302.49),(14, 1)
=(1, 4.59),(14, 1)
A=-0.5774
B=4.59

~~~
散布図を示す。
The scatter chart is shown.

http://humanbeing-etcman.blogspot.com/2008/11/power-law19colored-categorylna-lnblucas.html

file:powerlaw-18-a-b.txt
->
file:powerlaw-20-a-b.txt
以下を追加。

"A","B","memo","Category","Category_code"
-0.5774,4.59,"Power Law:(20)",Economy...human activity,3

今回追加した点は、Lucas(n=9)のライン。そのラインには、「human_activity」があります。
The point added this time is a line in Lucas(n=9). In the line, there is "human_activity".

-2.154,3162,"Power Law:(9),p.129,Fig.9",web...human activity,3
~~~
番外)
巷では、地域振興券の第二段をやるらしい。
ばらまきで、広く薄く配布して何が変わるのか?
10年以上を見越した新規産業を創生するための資金と年代を問わず雇用する
国営企業の創設を望む。最終的に民営化するにしても。
一極集中で、現状を打開し、全体を牽引してゆくものを真剣に考えるべきだ。
The second step of the Local Development Coupon seems to do on the street.
Is it distributed by the distribution widely and thinly and what changes? It is necessary to use it for the capital to do new industry that foresees ten years or more in Tscu.
Even if you finally privatize it The foundation of the managed company that employs it regardless of the age is hoped for.
It seriously thinks about the one to pull the whole by remedying the present situation by the excessive concentration.
~~~
end

2008年11月10日月曜日

Power Law:(19)colored Category,LN(A)-LN(B),Lucas By R

(2008/11/09-2008/11/10)

目的,Purpose)
Power Law:(18)のデータをプロットする。
The data of Power Law:(18) is plotted.

[1]Lucasを別のデータでセットし、配列で値をセットする。
[1]Lucas is set by another data, and the value is set by the array.

例,Example)
Lucas:n=5
abline(log(11), log(exp(5)), col="gray", lty=2)
->
abline(log(Lucas[11]), log(exp(5)), col="gray", lty=2)

[2]ファイル分割しないで、カテゴリ別に色分けできないか?
[2]Can the plot be colored according to the category without file divided?

~~~
powerlaw-18-a-b.txt にカテゴリコードを追加する。
The following category code is added to powerlaw-18-a-b.txt.

# 1,bio:blue
# 2,nature:green
# 3,human_activity:red
# 4,industry:gray
# 5,electric:orange

# 999,unknow,black

~~~
file:powerlaw-18-a-b.txt
===
"A","B","memo","Category","Category_code"
-3.21,104660,"Power Law:(5),p.182,Fig.5-39(a)",Industry?,4
-2.457,4102.56,"Power Law:(5),p.182,Fig.5-39(b)",Industry?,4
-2.416,5.95e3,"Power Law:(5),p.182,Fig.5-39(c)",Industry?,4
-1.246,74,"Power Law:(5),p.128,Fig.4-14",Nature,4
-1.1818,5.337e4,"Power Law:(5),p.111,Fig.4-3",Electric,5
-1.092,24.926,"Power Law:(5),p.61,Fig.2-16(2)",Nature,2
-1.035,63.065,"Power Law:(5),p.123,Fig.4-10",Electric,5
-1.013,17.635,"Power Law:(5),p.63,Fig.2-18",Economy...human activity,3
-1.0123,20.75,"Power Law:(5),p.60,Fig.2-15",Economy...human activity,3
-1,1e4,"Power Law:(5),p.62,Fig.2-17",Culture?...human activity,3
-1.0,5.62e3,"Power Law:(5),p.175,Fig.5-33",Bio,1
-1,100,"Power Law:(5),p.125,Fig.4-12",Nature,2
-0.991,18.52,"Power Law:(5),p.61,Fig.2-16(1)",Nature,2
-0.767,200,"Power Law:(5),p.108,Fig.4-1",Electric,5
-0.353,58.214,"Power Law:(4),table.1",Bio,1
-0.29758,15.5,"Power Law:(3),p.242,Fig.44",Bio,1
-0.249,31.174,"Power Law:(7),p.27,Fig.3-1",Bio,1
-0.249,159.9,"Power Law:(7),p.36,Fig.3-2",Bio,1
-0.249,212.878,"Power Law:(7),p.36,Fig.3-2",Bio,1
-0.74,23.2,"Power Law:(8),p.22,Fig.2",Bio,1
-0.518,390,"Power Law:(8),p.24,Fig.3",Bio,1
-0.692,6.971e3,"Power Law:(8),p.26,Fig.4",Bio,1
-2.154,3162,"Power Law:(9),p.129,Fig.9",web...human activity,3
-6.179,1.234e5,"Power Law:(10),p.37,table",Nature...human,2
-2.1,1e6,"Power Law:(11),Fig.1",web...human activity,3
-0.863,6.66,"Power Law:(18),Benfords Law",unknown...,999
===

~~~
[R-0]Rプログラミングを確認する。
[R-0]R programming is confirmed.

~~~
[R-1]単品plot,Single plot

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[1])), log(data_ab$B[1]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, ann=F)
:OK

~~~
[R-2]for文,for sentence

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(xx) with Lucas")
for (i in 1:26){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, ann=F)
par(new=T)
}

~~~
[R-3]データ長の判断,Judgment of data length

data_ab = read.csv("powerlaw-18-a-b.txt");
> length(data_ab)
[1] 5
> length(data_ab$A)
[1] 26
>
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(xx) with Lucas")
for (i in 1:length(data_ab$A)){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, ann=F)
par(new=T)
}

~~~
[R-4]色分け,colored plots

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(xx) with Lucas")
par(new=T)
#
for (i in 1:length(data_ab$A)){
# 1,bio:blue
if (data_ab$Category_code[i] == 1){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="blue", pch=20, ann=F)
}
# 2,nature:green
else if (data_ab$Category_code[i] == 2){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="green", pch=20, ann=F)
}
# 3,human_activity:red
else if (data_ab$Category_code[i] == 3){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="red", pch=20, ann=F)
}
# 4,industry:gray
else if (data_ab$Category_code[i] == 4){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="gray", pch=20, ann=F)
}
# 5,electric:orange
else if (data_ab$Category_code[i] == 5){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, ann=F)
}
#
else{
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15), col="black", pch=20, ann=F)
}
par(new=T)
}


~~~
[R-5]Rの配列の使い方,How to use of the array of R

> category_col = c("blue", "green", "red", "gray", "orange")
> category_col
[1] "blue" "green" "red" "gray" "orange"
>

> category_col[0]
character(0)
> category_col[1]
[1] "blue"
> category_col[2]
[1] "green"
> category_col[3]
[1] "red"
> category_col[4]
[1] "gray"
> category_col[5]
[1] "orange"
>

~~~
category = c("bio", "nature", "human_activity", "industry", "electric")
category_col = c("blue", "green", "red", "gray", "orange")

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(xx) with Lucas")
par(new=T)
#
for (i in 1:length(data_ab$A)){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15),
col=category_col[data_ab$Category_code[i]], pch=20, ann=F)
par(new=T)
}

~~~
[R-6]欠損値の判断,Judgment of missing value

> is.na(category_col[999])
[1] TRUE
> is.na(category_col[1])
[1] FALSE
> is.na(category_col[0])
logical(0)
>

> if(is.na(category_col[999])) aaa=1 else aaa=0
> aaa
[1] 1
>

~~~
category = c("bio", "nature", "human_activity", "industry", "electric")
category_col = c("blue", "green", "red", "gray", "orange")

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(xx) with Lucas")
par(new=T)
#
for (i in 1:length(data_ab$A)){
if(!is.na(category_col[data_ab$Category_code[i]])){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15),
col=category_col[data_ab$Category_code[i]], pch=20, ann=F)
}
else{
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15),
col="black", pch=20, ann=F)
}
par(new=T)
}


~~~
[R-7]リュカ数を配列にする,The number of Lucas is arranged.

[before]

#Lucas:n=5
abline(log(11), log(exp(5)), col="gray", lty=2)
#Lucas:n=6
abline(log(18), log(exp(5)), col="gray", lty=2)
#Lucas:n=7
abline(log(29), log(exp(5)), col="gray", lty=2)
#Lucas:n=8
abline(log(47), log(exp(5)), col="gray", lty=2)
#Lucas:n=9
abline(log(76), log(exp(5)), col="gray", lty=2)
#Lucas:n=10
abline(log(123), log(exp(5)), col="gray", lty=2)
#Lucas:n=12
abline(log(322), log(exp(5)), col="gray", lty=2)
#Lucas:n=14
abline(log(843), log(exp(5)), col="gray", lty=2)
#Lucas:n=18
abline(log(5778), log(exp(5)), col="gray", lty=2)
#Lucas:n=19
abline(log(9349), log(exp(5)), col="gray", lty=2)
#Lucas:n=21
abline(log(24476), log(exp(5)), col="gray", lty=2)
#Lucas:n=22
abline(log(39603), log(exp(5)), col="gray", lty=2)
#Lucas:n=25
abline(log(167761), log(exp(5)), col="gray", lty=2)
#Lucas:n=26
abline(log(271443), log(exp(5)), col="gray", lty=2)
abline(v = log(1), col="red")

~~~
[after]

Lucas = c(1, 3, 4, 7, 11, 18, 29, 47, 76, 123, 199, 322, 521, 843, 1364, 2207, 3571,
5778, 9349, 15127, 24476, 39603, 64079, 103682, 167761, 271443, 439204,
710647, 1149851, 1860498, 3010349, 4870847, 7881196, 12752043)

> Lucas
[1] 1 3 4 7 11 18 29
[8] 47 76 123 199 322 521 843
[15] 1364 2207 3571 5778 9349 15127 24476
[22] 39603 64079 103682 167761 271443 439204 710647
[29] 1149851 1860498 3010349 4870847 7881196 12752043
>

Lucas_b_distribution = c(5, 6, 7, 8, 9, 10, 12, 14, 18, 19, 21, 22, 25, 26)

for (i in 1:length(Lucas_b_distribution)){
abline(log(Lucas[Lucas_b_distribution[i]]), log(exp(5)), col="gray", lty=2)
}
abline(v = log(1), col="red")

~~~
[R-8]現時点の最終版,Present, final version

category = c("bio", "nature", "human_activity", "industry", "electric")
category_col = c("blue", "green", "red", "gray", "orange")

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A[0])), log(data_ab$B[0]), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15),
col="orange", pch=20, main="Scatter chart:a-b, Power Law(18) with Lucas")
par(new=T)
#
for (i in 1:length(data_ab$A)){
if(!is.na(category_col[data_ab$Category_code[i]])){
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15),
col=category_col[data_ab$Category_code[i]], pch=20, ann=F)
}
else{
plot(log(abs(data_ab$A[i])), log(data_ab$B[i]), xlim=c(-2, 2), ylim=c(1, 15),
col="black", pch=20, ann=F)
}
par(new=T)
}
#
Lucas = c(1, 3, 4, 7, 11, 18, 29, 47, 76, 123, 199, 322, 521, 843, 1364, 2207, 3571,
5778, 9349, 15127, 24476, 39603, 64079, 103682, 167761, 271443, 439204,
710647, 1149851, 1860498, 3010349, 4870847, 7881196, 12752043)

Lucas_b_distribution = c(5, 6, 7, 8, 9, 10, 12, 14, 18, 19, 21, 22, 25, 26)

for (i in 1:length(Lucas_b_distribution)){
abline(log(Lucas[Lucas_b_distribution[i]]), log(exp(5)), col="gray", lty=2)
}
abline(v = log(1), col="red")

~~~
end

Power Law:(18)Benfords Law

(2008/11/08)
DO図書館):再読,Rereading

黄金比はすべてを美しくするか?―最も謎め... マリオ リヴィオ、Mario Livio、 斉藤 隆央 (単行本 - 2005/12)
p.286-290:Article on Benfords Law
The Golden Ratio /The Story of Phi, the World's Most Astonishing Number by Mario Livio

ベンフォードの法則を再び思い出す。
Benfords law is recalled again.
~~~
http://en.wikipedia.org/wiki/Benfords_law

d p
1 30.1%
2 17.6%
3 12.5%
4 9.7%
5 7.9%
6 6.7%
7 5.8%
8 5.1%
9 4.6%
~~~
べき乗傾向をチェック。
Power Law tendency is checked.



A,Bを求める。
A and B are obtained.

y = -0.8631x -1.1606
->
ln(y) = -0.8631*ln(x) -1.1606

LN
(x, y)=(1, exp(-1.1606)),(9, exp(-0.8631*ln(9) -1.1606)
=(1, 0.313),(9, 0.047)
Relative value)
=(1, 0.313/0.047),(9, 1)
=(1, 6.66),(9, 1)
A=-0.863
B=6.66

~~~
http://humanbeing-etcman.blogspot.com/2008/11/power-law11graph-structure-in-web.html
Power Law:(11)のデータに、追加。
It adds it to the data of Power Law:(11).

"A","B","memo","Category"
-0.863,6.66,"Power Law:(18),Benfords Law",unknown...

powerlaw-11-a-b.txt + (this data) = powerlaw-18-a-b.txt

~~~
Rでplotする。
Plot is done by R.
:リュカ数の場合,in case of Lucas number

data_ab = read.csv("powerlaw-18-a-b.txt");
plot(log(abs(data_ab$A)), log(data_ab$B), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(1, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(18) with Lucas")
abline(log(11), log(exp(5)), col="gray", lty=2)
abline(log(18), log(exp(5)), col="gray", lty=2)
abline(log(29), log(exp(5)), col="gray", lty=2)
abline(log(47), log(exp(5)), col="gray", lty=2)
abline(log(76), log(exp(5)), col="gray", lty=2)
abline(log(123), log(exp(5)), col="gray", lty=2)
abline(log(322), log(exp(5)), col="gray", lty=2)
abline(log(843), log(exp(5)), col="gray", lty=2)
abline(log(5778), log(exp(5)), col="gray", lty=2)
abline(log(9349), log(exp(5)), col="gray", lty=2)
abline(log(24476), log(exp(5)), col="gray", lty=2)
abline(log(39603), log(exp(5)), col="gray", lty=2)
abline(log(167761), log(exp(5)), col="gray", lty=2)
abline(log(271443), log(exp(5)), col="gray", lty=2)
abline(v = log(1), col="red")



今回追加したデータは、Lucas(n=5,11)のラインに引っかかっている。
The data added this time is caught to the line of Lucas(n=5,11).
~~~
end

2008年11月4日火曜日

Power Law:(17)Graph with Lucas number

Power Law:(11)のデータに、リュカ数の基準線を引いてみる。
Rのabline(a, b)を使用する。
切片(A=0)にリュカ数の何番目かをセットし、傾きをexp(5.008) -> exp(5)とする。
The base point lines of the number of Lucas are pulled to the data of Power Law:(11).
abline(a, b) of R is used.
The number of Lucas is set in cut (A=0), and the inclination is assumed the exp(5.008) -> exp(5).
~~~
[1]リュカ数の場合,in case of Lucas number
data_ab <- read.csv("powerlaw-11-a-b.txt");
plot(log(abs(data_ab$A)), log(data_ab$B), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(3, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(11) with Lucas")

Lucas:n=5
abline(log(11), log(exp(5)), col="gray", lty=2)

Lucas:n=6
abline(log(18), log(exp(5)), col="gray", lty=2)

Lucas:n=7
abline(log(29), log(exp(5)), col="gray", lty=2)

Lucas:n=8
abline(log(47), log(exp(5)), col="gray", lty=2)

Lucas:n=9
abline(log(76), log(exp(5)), col="gray", lty=2)

Lucas:n=10
abline(log(123), log(exp(5)), col="gray", lty=2)

~~~
Lucas:n=12
abline(log(322), log(exp(5)), col="gray", lty=2)

Lucas:n=14
abline(log(843), log(exp(5)), col="gray", lty=2)

Lucas:n=18
abline(log(5778), log(exp(5)), col="gray", lty=2)

Lucas:n=19
abline(log(9349), log(exp(5)), col="gray", lty=2)

Lucas:n=21
abline(log(24476), log(exp(5)), col="gray", lty=2)

Lucas:n=22
abline(log(39603), log(exp(5)), col="gray", lty=2)

Lucas:n=25
abline(log(167761), log(exp(5)), col="gray", lty=2)

Lucas:n=26
abline(log(271443), log(exp(5)), col="gray", lty=2)

abline(v = log(1), col="red")


~~~
[2]フィボナッチ数の場合,in case of Fibonacci number
Power Law:(15)では、グラフから読み取った数字からリュカ数が近いと見ているが、
フィボナッチのグラフではどうなっているかをみる
It sees how to become it in Fibonacci's graph though it is thought that the
number of Lucas is near from the figure read from the graph in Power Law:(15).

data_ab <- read.csv("powerlaw-11-a-b.txt");
plot(log(abs(data_ab$A)), log(data_ab$B), xlab="log(abs(a))", ylab="log(b)", xlim=c(-2, 2), ylim=c(3, 15), col="orange", pch=20, main="Scatter chart:a-b, Power Law(11) with Fibonacci")

Fibonacci:n=7
abline(log(13), log(exp(5)), col="gray", lty=2)

Fibonacci:n=8
abline(log(21), log(exp(5)), col="gray", lty=2)

Fibonacci:n=9
abline(log(34), log(exp(5)), col="gray", lty=2)

Fibonacci:n=10
abline(log(55), log(exp(5)), col="gray", lty=2)

Fibonacci:n=11
abline(log(89), log(exp(5)), col="gray", lty=2)

Fibonacci:n=12 :???
abline(log(144), log(exp(5)), col="gray", lty=2)

Fibonacci:n=14
abline(log(377), log(exp(5)), col="gray", lty=2)

Fibonacci:n=15
abline(log(610), log(exp(5)), col="gray", lty=2)

~~~
Fibonacci:n=20
abline(log(6765), log(exp(5)), col="gray", lty=2)

Fibonacci:n=21
abline(log(10946), log(exp(5)), col="gray", lty=2)

Fibonacci:n=22
abline(log(17711), log(exp(5)), col="gray", lty=2)

Fibonacci:n=23
abline(log(28657), log(exp(5)), col="gray", lty=2)

Fibonacci:n=24
abline(log(46368), log(exp(5)), col="gray", lty=2)

Fibonacci:n=26
abline(log(121393), log(exp(5)), col="gray", lty=2)

Fibonacci:n=27
abline(log(196418), log(exp(5)), col="gray", lty=2)

abline(v = log(1), col="red")


~~~
end

Power Law:(16)Fibonacci number & Lucas number

「さとらんど」でのフィボナッチ数が伏線なのか?

(2008/10/31)
SA図書館)ハローワークの帰りに、立ち寄った。離職のタイミングが近づいている。
i stopped by the return of the employment agency. The timing of the resignation approaches.

~~~
周期の特異点のアイデアを求めて、借りた。
i borrowed for the idea of the significant point of the cycle.

フィボナッチ数の小宇宙(ミクロコスモス)... 中村 滋 (単行本 - 2002/9)

[1]p.218,最初の100個のフィボナッチ数とその素因数分解、途中まで。
[1]p.218,The first 100 numbers of Fibonacci and the factorization on prime numbers,On the way.



[2]p.220,最初の100個のリュカ数とその素因数分解、途中まで。
[2]p.220,The first 100 numbers of Ruca and the factorization on prime numbers,On the way.

~~~
end

Power Law:(15)Hypothesis:LN(A)=0,the distribution of B ="Lucas number"

(2008/11/01)midnight


~~~
2008/11/02)02:45-
傾き,slope)

y=75/8=9.375
x=51.5/27.5=1.872

y/x=9.375/1.872=5.008

exp(5.008)=149.6

傾きは、5.008
slope is 5.008.
~~~
end

Power Law:(14)Category Tendency to LN(A) - LN(B)

(2008/11/01)
Power Law:(11)のデータをカテゴリごとにプロットを色分けしてみる。
基準線は傾向が見えなくなるので、外す。
何が見えるか?
The plot is classified by each category by using the data of Power Law:(11).
Because the tendency disappears to the base point line, it removes.
What do you see?
~~~
[1]
Power Law:(13)で使用したファイル:powerlaw-11-a-b.txt を使う。
カテゴリごとにファイルを分ける。
The file used with Power Law:(13): Powerlaw-11-a-b.txt is used.
The file is divided by each category.
~~~
[1-1]category="Bio",9 records
file:powerlaw-11-a-b-bio.txt
===
"A","B","memo","Category"
-1.0,5.62e3,"Power Law:(5),p.175,Fig.5-33",Bio
-0.353,58.214,"Power Law:(4),table.1",Bio
-0.29758,15.5,"Power Law:(3),p.242,Fig.44",Bio
-0.249,31.174,"Power Law:(7),p.27,Fig.3-1",Bio
-0.249,159.9,"Power Law:(7),p.36,Fig.3-2",Bio
-0.249,212.878,"Power Law:(7),p.36,Fig.3-2",Bio
-0.74,23.2,"Power Law:(8),p.22,Fig.2",Bio
-0.518,390,"Power Law:(8),p.24,Fig.3",Bio
-0.692,6.971e3,"Power Law:(8),p.26,Fig.4",Bio
===

~~~
[1-2]category="Electric",3 records
file:powerlaw-11-a-b-electric.txt
===
"A","B","memo","Category"
-1.1818,5.337e4,"Power Law:(5),p.111,Fig.4-3",Electric
-1.035,63.065,"Power Law:(5),p.123,Fig.4-10",Electric
-0.767,200,"Power Law:(5),p.108,Fig.4-1",Electric
===

~~~
[1-3]category="human activity",5 records
file:powerlaw-11-a-b-human_activity.txt
===
"A","B","memo","Category"
-1.013,17.635,"Power Law:(5),p.63,Fig.2-18",Economy...human activity
-1.0123,20.75,"Power Law:(5),p.60,Fig.2-15",Economy...human activity
-1,1e4,"Power Law:(5),p.62,Fig.2-17",Culture?...human activity
-2.154,3162,"Power Law:(9),p.129,Fig.9",web...human activity
-2.1,1e6,"Power Law:(11),Fig.1",web...human activity
===

~~~
[1-4]category="Industry",3 records
file:powerlaw-11-a-b-industry.txt
===
"A","B","memo","Category"
-3.21,104660,"Power Law:(5),p.182,Fig.5-39(a)",Industry?
-2.457,4102.56,"Power Law:(5),p.182,Fig.5-39(b)",Industry?
-2.416,5.95e3,"Power Law:(5),p.182,Fig.5-39(c)",Industry?
===

~~~
[1-5]category="Nature",5 records
file:powerlaw-11-a-b-nature.txt
===
"A","B","memo","Category"
-1.246,74,"Power Law:(5),p.128,Fig.4-14",Nature
-1.092,24.926,"Power Law:(5),p.61,Fig.2-16(2)",Nature
-1,100,"Power Law:(5),p.125,Fig.4-12",Nature
-0.991,18.52,"Power Law:(5),p.61,Fig.2-16(1)",Nature
-6.179,1.234e5,"Power Law:(10),p.37,table",Nature...human
===

~~~
[2]カテゴリごとに色分けする。
It classifies it by the category.

data_ab_bio <- read.csv("powerlaw-11-a-b-bio.txt");
plot(log(abs(data_ab_bio$A)), log(data_ab_bio$B), xlim=c(-2, 2), ylim=c(3, 15), col="blue", pch=20, xlab="log(abs(a))", ylab="log(b)")
par(new=T)
data_ab_nature <- read.csv("powerlaw-11-a-b-nature.txt");
plot(log(abs(data_ab_nature$A)), log(data_ab_nature$B), xlim=c(-2, 2), ylim=c(3, 15), col="green", pch=20, ann=F)
par(new=T)
data_ab_human_activity <- read.csv("powerlaw-11-a-b-human_activity.txt");
plot(log(abs(data_ab_human_activity$A)), log(data_ab_human_activity$B), xlim=c(-2, 2), ylim=c(3, 15), col="red", pch=20, ann=F)
par(new=T)
data_ab_industry <- read.csv("powerlaw-11-a-b-industry.txt");
plot(log(abs(data_ab_industry$A)), log(data_ab_industry$B), xlim=c(-2, 2), ylim=c(3, 15), col="gray", pch=20, ann=F)
par(new=T)
data_ab_electric <- read.csv("powerlaw-11-a-b-electric.txt");
plot(log(abs(data_ab_electric$A)), log(data_ab_electric$B), xlim=c(-2, 2), ylim=c(3, 15), col="orange", pch=20, ann=F)
par(new=T)
title(main="Scatter chart:a-b, Power Law(11) category")

~~~
bio:blue
nature:green
human_activity:red
industry:gray
electric:orange

~~~
end