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caes 2017-03-15 10:49:15 -04:00
parent 84f5d7b05f
commit 48e7a7db42
9 changed files with 1741 additions and 0 deletions
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src/sed/magdziarz/.RData Normal file
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data=read.csv("components.csv",header=T)
plot(data,log="xy",ylim=c(.0003,.1),xlim=c(.001,1000))
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_sum = data$blackbody_sum_1 + data$comptonization + data$excess
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_error = data$total - data$test_sum
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
warnings()
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
head(data)
mean(data$total - data$test_error)
mean((data$total - data$test_error)^2)
mean(sqrt((data$total - data$test_error)^2))
data$test_sum = data$blackbody_sum_2 + data$comptonization + data$excess
mean(sqrt((data$total - data$test_error)^2))
mean(sqrt((data$total - data$test_sum)^2))
data$test_sum = data$blackbody_sum_1 + data$comptonization + data$excess
mean(sqrt((data$total - data$test_sum)^2))
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_error = data$total - data$test_sum
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_sum = data$blackbody_sum_2 + data$comptonization + data$excess
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_error = data$total - data$test_sum
mean(sqrt((data$total - data$test_sum)^2))
rms
?rms
library(rms)
data$test_error = data$total - data$test_sum
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_error_sq = (data$total - data$test_sum)^2
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data = read.csv("components.csv",header=t)
data = read.csv("components.csv",header=T)
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
data$test_sum_1 = data$blackbody_sum_1 + data$comptonization + data$excess
data$err_1_sq = (data$total - data$test_sum)^2
data$test_sum_2 = data$blackbody_sum_2 + data$comptonization + data$excess
data$err_2_sq = (data$total - data$test_sum_2)^2
data$err_1_sq = (data$total - data$test_sum_1)^2
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
warnings()
data$err_1_sq = (data$total - data$test_sum)^2
data$err_1_sq = (data$total - data$test_sum_1)^2
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
attach(data)
plot(err_1_sq ~ energy..keV.)
plot(err_2_sq ~ energy..keV.)
head(err_1_sq)
head(err_2_sq)
plot(err_2_sq ~ energy..keV.,log="x")
plot(err_1_sq ~ energy..keV.,log="x")
plot(total ~ energy..keV.,log="x")
contour()
?read.table
TOTL1216 = read.table("../../../TOTL1216.tab",header=T)
head(TOTL1216)
contour(TOTL1216)
man contour()
?contour
contour(TOTL1216$Hden,TOTL1216$Phi.H.,TOTL1216$Eq_Width.A.)
?contour
contour(TOTL1216$Phi.H.,TOTL1216$Hden,TOTL1216$Eq_Width.A.)
TOTL1216
contour(TOTL1216$Phi.H.,TOTL1216$Hden,TOTL1216$Eq_Width.A.)
contour(y = TOTL1216$Phi.H.,x = TOTL1216$Hden,z = TOTL1216$Eq_Width.A.)
?contour
?contour
contour(seq(1:4),seq(5:8),seq(3:6))
?contour
?op
?op
?opar
?contour
filled.contour
?filled.contour
filled.contour(seq(1:4),seq(5:8),seq(3:6))
contour(y = TOTL1216$Phi.H.,x = TOTL1216$Hden,z = TOTL1216$Eq_Width.A.)
TOTL1216$Hden
TOTL1216$Phi.H.
?sort
TOTL1216[order(TOTL1216$Phi.H.,TOTL1216$Hden)]
TOTL1216[order(Phi.H.,Hden)]
TOTL1216[order(TOTL1216$Phi.H.,Hden)]
TOTL1216[order(TOTL1216$Phi.H.,Hden),]
TOTL1216[order(TOTL1216$Phi.H.,TOTL1216$Hden),]
TOTL1216[order(TOTL1216$Hden,TOTL1216$Phi.H.),]
library(ggplot)
library(ggplot2)
library(ggplot2)
ggplot(Statsrep, aes(x=X, y=Y, z=Zn)) +
geom_density2d()
ggplot(Statsrep, aes(x=TOTL1216$Hden, y=TOTL1216$Phi.H., z=TOTL1216$Eq_Width.A.)) +
ggplot(Statsrep, aes(x=TOTL1216$Hden, y=TOTL1216$Phi.H., z=TOTL1216$Eq_Width.A.)) + geom_density2d()
library(stats)
ggplot(Statsrep, aes(x=TOTL1216$Hden, y=TOTL1216$Phi.H., z=TOTL1216$Eq_Width.A.)) + geom_density2d()
?ggplot
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_density2d()
TOTL1216$Eq_Width.A.
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_density2d()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_density2d()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.))
?ggplot
?interp
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_contour()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_contour(alpha=0.5)
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) + geom_contour(alpha=1)
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) +
geom_tile() +
coord_equal() +
geom_contour(color = "white", alpha = 0.5) +
s
theme_bw()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) +
geom_tile() +
coord_equal() +
geom_contour(color = "white", alpha = 0.5) +
theme_bw()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) +
geom_tile("TOTL 1216") +
coord_equal() +
geom_contour(color = "white", alpha = 0.5) +
theme_bw()
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) +
geom_tile() +
coord_equal() +
geom_contour(color = "white", alpha = 0.5) +
theme_bw()
?ggplot
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
plot(err_1_sq ~ energy..keV.)
plot(err_1_sq ~ energy..keV.,log="x")
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
plot(err_2_sq ~ energy..keV.,log="x")
plot(total ~ energy..keV.,log="x")
mean(sqrt((data$total - data$test_sum)^2))
mean(sqrt((data$total - data$test_sum_1)/data$total))
mean((data$total - data$test_sum_1)/data$total)
mean((data$total - data$test_sum_2)/data$total)
plot(data,log="xy",ylim=c(.0003,.2),xlim=c(.001,1000))
ggplot(TOTL1216, aes(x=Hden, y=Phi.H., z=Eq_Width.A.)) +
geom_tile() +
coord_equal() +
geom_contour(color = "white", alpha = 0.5) +
theme_bw()
q()

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src/sed/magdziarz/components.csv Normal file
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energy (keV),total,blackbody_sum_1,blackbody_sum_2,comptonization,excess
0.00100088,0.007052,0.00380963,0.00689602,0.00315011,0.000256716
0.00100097,0.00705274,0.00381008,0.0068968,0.00315038,0.000256738
0.00103176,0.00731913,0.00397244,0.00718025,0.00324849,0.000264733
0.00103256,0.00732605,0.00397667,0.00718762,0.00325103,0.00026494
0.00111537,0.00805117,0.00442237,0.00796368,0.00351498,0.000286451
0.00116725,0.00851172,0.00470811,0.00845975,0.00373939,0.000299938
0.00123692,0.00913732,0.00504126,0.00913732,0.00404642,0.000318059
0.00124792,0.00921958,0.0050942,0.00921958,0.0040955,0.000320922
0.0012767,0.00943475,0.00519604,0.00943475,0.00422459,0.000328412
0.00133715,0.0098869,0.00540897,0.0098869,0.00449917,0.000344151
0.00134899,0.00999022,0.00545052,0.00999022,0.00455348,0.000347234
0.00138015,0.010263,0.00560713,0.010263,0.00469727,0.000355353
0.00142956,0.0106977,0.00585714,0.0106977,0.00492764,0.000370404
0.00144129,0.0108138,0.0059168,0.0108138,0.00498275,0.000373991
0.00147554,0.0111545,0.00609167,0.0111545,0.00507252,0.000384494
0.00157539,0.0121622,0.006607,0.0121622,0.00533142,0.000415363
0.00157752,0.0121839,0.00661809,0.0121839,0.00533992,0.000416025
0.00165242,0.0129539,0.00701002,0.0129539,0.00564021,0.000438934
0.00168426,0.0131433,0.00717795,0.0131433,0.00576863,0.000448722
0.00170542,0.0132686,0.00728993,0.0132686,0.00584195,0.000455241
0.00172366,0.0133763,0.00738675,0.0133763,0.00590517,0.000461809
0.00180616,0.0138603,0.00760908,0.0138603,0.00619126,0.00049182
0.00182074,0.0139736,0.007648,0.0139736,0.00624186,0.000497176
0.00182336,0.0139939,0.00765497,0.0139939,0.00625416,0.000498139
0.00188394,0.0144645,0.00781532,0.0144645,0.00654069,0.000517717
0.00194938,0.014973,0.00813645,0.014973,0.00685404,0.00053899
0.00195252,0.0149974,0.0081519,0.0149974,0.00686917,0.000540124
0.00201415,0.0155573,0.00845623,0.0155573,0.00716806,0.00056252
0.00208746,0.0162273,0.00872281,0.0162273,0.00752803,0.000589436
0.00212823,0.016548,0.00887055,0.016548,0.0077303,0.000604533
0.00217726,0.0169339,0.0090477,0.0169339,0.00784278,0.000622804
0.00225661,0.0175585,0.00938142,0.0175585,0.00802288,0.000652641
0.00232614,0.0182909,0.00967398,0.0182909,0.0081788,0.000679055
0.00235596,0.0186074,0.0097995,0.0186074,0.00830261,0.000690459
0.00241267,0.0192131,0.0100382,0.0192131,0.00853881,0.000698854
0.0024869,0.0197252,0.0103508,0.0197252,0.00884951,0.000709699
0.00257494,0.0203301,0.0107216,0.0203301,0.00908668,0.000722356
0.00260806,0.0205569,0.0108612,0.0205569,0.00917541,0.00073176
0.00271828,0.0214362,0.0113258,0.0214362,0.00946875,0.000763061
0.00275059,0.0216941,0.0114621,0.0216941,0.00960707,0.00077224
0.00278359,0.0219575,0.0115491,0.0219575,0.00974869,0.000781615
0.00278819,0.0219942,0.0115612,0.0219942,0.00976847,0.000783355
0.0029761,0.0234947,0.0120495,0.0234947,0.0105825,0.000855268
0.00300638,0.0237366,0.0121271,0.0237366,0.0107147,0.000862818
0.00301412,0.0237985,0.0121508,0.0237985,0.0107486,0.000864748
0.00317707,0.0247704,0.0126471,0.0247704,0.0114661,0.000905194
0.00321712,0.0250074,0.0127681,0.0250074,0.0115758,0.00091509
0.00328608,0.025414,0.0129757,0.025414,0.011764,0.000932097
0.00329455,0.0254638,0.0129969,0.0254638,0.011787,0.000934182
0.00347266,0.0266547,0.0134382,0.0266547,0.0122684,0.000977876
0.00347766,0.026688,0.0134505,0.026688,0.0122837,0.000979096
0.00356136,0.0272448,0.0136549,0.0272448,0.01254,0.00100695
0.00359166,0.0274209,0.0137285,0.0274209,0.0126326,0.00101706
0.00371801,0.0281512,0.0140329,0.0281512,0.0130175,0.00105939
0.0037539,0.0283576,0.0141186,0.0283576,0.0131265,0.00106826
0.00389271,0.0291513,0.0144476,0.0291513,0.0134874,0.00110247
0.00392566,0.0293387,0.014525,0.0293387,0.0135726,0.00111057
0.00401911,0.0298682,0.014758,0.0298682,0.0138133,0.00113349
0.00425488,0.0311911,0.015338,0.0311911,0.0144142,0.00119781
0.00433873,0.0315796,0.0155418,0.0315796,0.0146259,0.00122065
0.00465055,0.0330008,0.0158596,0.0330008,0.0154042,0.00130549
0.00468931,0.0331557,0.015898,0.0331557,0.0155,0.00131602
0.0050682,0.0346416,0.0162624,0.0346416,0.0164263,0.00141885
0.00513968,0.0349164,0.0163554,0.0349164,0.016599,0.00143822
0.00519153,0.0350752,0.0164224,0.0350752,0.0167239,0.00145226
0.00535758,0.035578,0.0166343,0.035578,0.0171219,0.00148155
0.0056743,0.0365138,0.0169621,0.0365138,0.0178725,0.00153652
0.00568002,0.0365304,0.0169679,0.0365304,0.017886,0.0015377
0.00572662,0.0366824,0.0170151,0.0366824,0.0179955,0.00154728
0.00572785,0.0366864,0.0170147,0.0366864,0.0179984,0.00154753
0.00620222,0.0382001,0.0168813,0.0382001,0.01893,0.00164404
0.00620795,0.038218,0.0168798,0.038218,0.0189411,0.00164535
0.00626049,0.0382914,0.0168657,0.0382914,0.0190426,0.00165744
0.00639785,0.0384808,0.0168295,0.0384808,0.0192362,0.00168896
0.00670451,0.0388928,0.0167319,0.0388928,0.0196606,0.00175903
0.00686,0.0390961,0.0166843,0.0390961,0.0198718,0.00178193
0.006991,0.0391729,0.0166451,0.0391729,0.0200478,0.00180105
0.00740968,0.03941,0.0163691,0.03941,0.0205987,0.00186114
0.00755458,0.0394893,0.0162783,0.0394893,0.0207855,0.00188414
0.00766474,0.0395486,0.0161272,0.0395486,0.0209262,0.00190152
0.00809872,0.0397752,0.0155652,0.0397752,0.0214703,0.00196912
0.00817305,0.0398129,0.0154739,0.0398129,0.0215619,0.00197929
0.00853198,0.0399908,0.0150514,0.0399908,0.021985,0.00202788
0.00856388,0.0400063,0.0150088,0.0400063,0.0220221,0.00203215
0.00895053,0.0396539,0.0145136,0.0396539,0.0224661,0.00208342
0.00903229,0.0395817,0.0144137,0.0395817,0.0225586,0.002092
0.00932098,0.0393329,0.0140732,0.0393329,0.0228011,0.00212197
0.00956727,0.0391279,0.0137056,0.0391279,0.0230041,0.00214713
0.0098915,0.0386924,0.0132498,0.0386924,0.0232661,0.00217973
0.00998143,0.038575,0.0131286,0.038575,0.0233377,0.00218977
0.0100702,0.0384605,0.0130112,0.0384605,0.0233592,0.00219965
0.0105699,0.0378401,0.0122854,0.0378401,0.0234768,0.00225445
0.0107597,0.0376558,0.0120289,0.0370588,0.0235202,0.00227494
0.0111523,0.0372876,0.0112103,0.0355344,0.0236078,0.00231675
0.0119395,0.0365967,0.00980323,0.0328045,0.0237605,0.00239844
0.0122009,0.0362427,0.00939439,0.0319821,0.0238092,0.00242499
0.0125521,0.0357842,0.00888454,0.0313323,0.0238732,0.00246021
0.0126301,0.0356848,0.00878409,0.0311921,0.0238872,0.00246797
0.0131828,0.0350055,0.00812037,0.0302405,0.0239841,0.00249212
0.0131902,0.0349968,0.00811207,0.0302177,0.0239853,0.00249244
0.0132625,0.034911,0.00803109,0.0299945,0.0239977,0.00249554
0.0138586,0.034229,0.00725943,0.0282589,0.0240977,0.00252062
0.0139567,0.0341208,0.00708952,0.0279898,0.0241138,0.00252467
0.0140848,0.0339812,0.0068754,0.0276453,0.0241346,0.00253408
0.0145718,0.0334668,0.00613402,0.0260194,0.0242123,0.0025694
0.015596,0.0324622,0.00488351,0.0230516,0.0243682,0.00264145
0.0156321,0.0324285,0.00484569,0.0229566,0.0243736,0.00264353
0.0160748,0.0320247,0.00454456,0.0218416,0.024438,0.00266873
0.0160817,0.0320185,0.00454008,0.0218263,0.024439,0.00266912
0.0160983,0.0320037,0.00452936,0.0217898,0.024439,0.00267005
0.0163348,0.0317426,0.0043801,0.0212782,0.0244399,0.00268332
0.01688,0.0311625,0.00391489,0.0201699,0.0244419,0.00271342
0.0169853,0.0310538,0.00381804,0.0199666,0.0244422,0.00271916
0.0172348,0.0308004,0.00360024,0.0189953,0.0244431,0.00273267
0.0177838,0.0302626,0.00317311,0.0170639,0.024445,0.00275902
0.0179674,0.0301689,0.0030445,0.0164749,0.0244456,0.00276771
0.0181382,0.0300829,0.0029307,0.0159506,0.0244462,0.00277574
0.0191648,0.029587,0.00234786,0.0144184,0.0244494,0.00282291
0.0192434,0.0295504,0.00230944,0.014238,0.0244497,0.00282645
0.0192583,0.0295435,0.00230118,0.0142042,0.0244497,0.00282712
0.0196673,0.0293566,0.00208742,0.0133157,0.024451,0.00284738
0.0198053,0.0292947,0.0020028,0.0130326,0.0244514,0.00285416
0.0198666,0.0292674,0.00196652,0.0128957,0.0244516,0.00285715
0.0200743,0.029187,0.0018491,0.0124451,0.0244522,0.00286727
0.0204664,0.0290381,0.00164904,0.0116485,0.0244055,0.00288618
0.0211505,0.0287866,0.00135741,0.010529,0.0243262,0.0029186
0.0212182,0.0287623,0.00133198,0.0104145,0.0243185,0.00292177
0.021282,0.0287395,0.00131837,0.0103081,0.0243113,0.00292476
0.0218565,0.0285377,0.00120359,0.00941069,0.0242473,0.00294253
0.0219265,0.0285136,0.00119051,0.00926912,0.0242396,0.00294467
0.0224095,0.0283497,0.00107606,0.0083589,0.0241874,0.0029593
0.0224273,0.0283438,0.00106757,0.0083275,0.0241855,0.00295983
0.0230797,0.0281296,0.000801613,0.00726847,0.0241872,0.0029792
0.0233876,0.0280311,0.000702182,0.00697834,0.024188,0.00298819
0.0235174,0.0279901,0.000690342,0.00686067,0.0241883,0.00299196
0.0238511,0.027886,0.000661084,0.00656991,0.0241892,0.00300489
0.0241693,0.0277884,0.000634696,0.00627878,0.02419,0.0030171
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0.0246473,0.0276508,0.000573652,0.00587213,0.0241911,0.00303524
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297.908,0.00292716,1.53701e-31,1.9493e-17,4.42972e-24,0.00292716
304.457,0.0026162,1.32704e-31,1.80959e-17,3.60707e-24,0.0026162
311.164,0.0023647,1.14542e-31,1.67966e-17,2.936e-24,0.0023647
318.005,0.00211349,9.88949e-32,1.55928e-17,2.39075e-24,0.00211349
324.997,0.00188897,8.5385e-32,1.44753e-17,1.94676e-24,0.00188897
332.142,0.0016883,7.37206e-32,1.34379e-17,1.58522e-24,0.0016883
339.458,0.001526,6.36313e-32,1.2473e-17,1.2903e-24,0.001526
346.922,0.00136389,5.49387e-32,1.15791e-17,1.05067e-24,0.00136389
350.639,0.00121896,5.11224e-32,1.11646e-17,9.50029e-25,0.00121896
358.348,0.00108947,4.41386e-32,1.03645e-17,7.73597e-25,0.00108947
366.226,0.000973734,3.81089e-32,9.62166e-18,6.2993e-25,0.000973734
374.278,0.000870292,3.29028e-32,8.93209e-18,5.12944e-25,0.000870292
378.289,0.000777818,3.06173e-32,8.61238e-18,4.63809e-25,0.000777818
386.622,0.000703044,2.6427e-32,7.99398e-18,3.7752e-25,0.000703044
395.122,0.000628358,2.28168e-32,7.42106e-18,3.0741e-25,0.000628358
399.356,0.000561591,2.12319e-32,7.15544e-18,2.77963e-25,0.000561591
408.136,0.000501931,1.83314e-32,6.64262e-18,2.26342e-25,0.000501931
412.51,0.000448598,1.7058e-32,6.40486e-18,2.0466e-25,0.000448598
421.579,0.000400942,1.47277e-32,5.94584e-18,1.66652e-25,0.000400942
1 energy (keV) total blackbody_sum_1 blackbody_sum_2 comptonization excess
2 0.00100088 0.007052 0.00380963 0.00689602 0.00315011 0.000256716
3 0.00100097 0.00705274 0.00381008 0.0068968 0.00315038 0.000256738
4 0.00103176 0.00731913 0.00397244 0.00718025 0.00324849 0.000264733
5 0.00103256 0.00732605 0.00397667 0.00718762 0.00325103 0.00026494
6 0.00111537 0.00805117 0.00442237 0.00796368 0.00351498 0.000286451
7 0.00116725 0.00851172 0.00470811 0.00845975 0.00373939 0.000299938
8 0.00123692 0.00913732 0.00504126 0.00913732 0.00404642 0.000318059
9 0.00124792 0.00921958 0.0050942 0.00921958 0.0040955 0.000320922
10 0.0012767 0.00943475 0.00519604 0.00943475 0.00422459 0.000328412
11 0.00133715 0.0098869 0.00540897 0.0098869 0.00449917 0.000344151
12 0.00134899 0.00999022 0.00545052 0.00999022 0.00455348 0.000347234
13 0.00138015 0.010263 0.00560713 0.010263 0.00469727 0.000355353
14 0.00142956 0.0106977 0.00585714 0.0106977 0.00492764 0.000370404
15 0.00144129 0.0108138 0.0059168 0.0108138 0.00498275 0.000373991
16 0.00147554 0.0111545 0.00609167 0.0111545 0.00507252 0.000384494
17 0.00157539 0.0121622 0.006607 0.0121622 0.00533142 0.000415363
18 0.00157752 0.0121839 0.00661809 0.0121839 0.00533992 0.000416025
19 0.00165242 0.0129539 0.00701002 0.0129539 0.00564021 0.000438934
20 0.00168426 0.0131433 0.00717795 0.0131433 0.00576863 0.000448722
21 0.00170542 0.0132686 0.00728993 0.0132686 0.00584195 0.000455241
22 0.00172366 0.0133763 0.00738675 0.0133763 0.00590517 0.000461809
23 0.00180616 0.0138603 0.00760908 0.0138603 0.00619126 0.00049182
24 0.00182074 0.0139736 0.007648 0.0139736 0.00624186 0.000497176
25 0.00182336 0.0139939 0.00765497 0.0139939 0.00625416 0.000498139
26 0.00188394 0.0144645 0.00781532 0.0144645 0.00654069 0.000517717
27 0.00194938 0.014973 0.00813645 0.014973 0.00685404 0.00053899
28 0.00195252 0.0149974 0.0081519 0.0149974 0.00686917 0.000540124
29 0.00201415 0.0155573 0.00845623 0.0155573 0.00716806 0.00056252
30 0.00208746 0.0162273 0.00872281 0.0162273 0.00752803 0.000589436
31 0.00212823 0.016548 0.00887055 0.016548 0.0077303 0.000604533
32 0.00217726 0.0169339 0.0090477 0.0169339 0.00784278 0.000622804
33 0.00225661 0.0175585 0.00938142 0.0175585 0.00802288 0.000652641
34 0.00232614 0.0182909 0.00967398 0.0182909 0.0081788 0.000679055
35 0.00235596 0.0186074 0.0097995 0.0186074 0.00830261 0.000690459
36 0.00241267 0.0192131 0.0100382 0.0192131 0.00853881 0.000698854
37 0.0024869 0.0197252 0.0103508 0.0197252 0.00884951 0.000709699
38 0.00257494 0.0203301 0.0107216 0.0203301 0.00908668 0.000722356
39 0.00260806 0.0205569 0.0108612 0.0205569 0.00917541 0.00073176
40 0.00271828 0.0214362 0.0113258 0.0214362 0.00946875 0.000763061
41 0.00275059 0.0216941 0.0114621 0.0216941 0.00960707 0.00077224
42 0.00278359 0.0219575 0.0115491 0.0219575 0.00974869 0.000781615
43 0.00278819 0.0219942 0.0115612 0.0219942 0.00976847 0.000783355
44 0.0029761 0.0234947 0.0120495 0.0234947 0.0105825 0.000855268
45 0.00300638 0.0237366 0.0121271 0.0237366 0.0107147 0.000862818
46 0.00301412 0.0237985 0.0121508 0.0237985 0.0107486 0.000864748
47 0.00317707 0.0247704 0.0126471 0.0247704 0.0114661 0.000905194
48 0.00321712 0.0250074 0.0127681 0.0250074 0.0115758 0.00091509
49 0.00328608 0.025414 0.0129757 0.025414 0.011764 0.000932097
50 0.00329455 0.0254638 0.0129969 0.0254638 0.011787 0.000934182
51 0.00347266 0.0266547 0.0134382 0.0266547 0.0122684 0.000977876
52 0.00347766 0.026688 0.0134505 0.026688 0.0122837 0.000979096
53 0.00356136 0.0272448 0.0136549 0.0272448 0.01254 0.00100695
54 0.00359166 0.0274209 0.0137285 0.0274209 0.0126326 0.00101706
55 0.00371801 0.0281512 0.0140329 0.0281512 0.0130175 0.00105939
56 0.0037539 0.0283576 0.0141186 0.0283576 0.0131265 0.00106826
57 0.00389271 0.0291513 0.0144476 0.0291513 0.0134874 0.00110247
58 0.00392566 0.0293387 0.014525 0.0293387 0.0135726 0.00111057
59 0.00401911 0.0298682 0.014758 0.0298682 0.0138133 0.00113349
60 0.00425488 0.0311911 0.015338 0.0311911 0.0144142 0.00119781
61 0.00433873 0.0315796 0.0155418 0.0315796 0.0146259 0.00122065
62 0.00465055 0.0330008 0.0158596 0.0330008 0.0154042 0.00130549
63 0.00468931 0.0331557 0.015898 0.0331557 0.0155 0.00131602
64 0.0050682 0.0346416 0.0162624 0.0346416 0.0164263 0.00141885
65 0.00513968 0.0349164 0.0163554 0.0349164 0.016599 0.00143822
66 0.00519153 0.0350752 0.0164224 0.0350752 0.0167239 0.00145226
67 0.00535758 0.035578 0.0166343 0.035578 0.0171219 0.00148155
68 0.0056743 0.0365138 0.0169621 0.0365138 0.0178725 0.00153652
69 0.00568002 0.0365304 0.0169679 0.0365304 0.017886 0.0015377
70 0.00572662 0.0366824 0.0170151 0.0366824 0.0179955 0.00154728
71 0.00572785 0.0366864 0.0170147 0.0366864 0.0179984 0.00154753
72 0.00620222 0.0382001 0.0168813 0.0382001 0.01893 0.00164404
73 0.00620795 0.038218 0.0168798 0.038218 0.0189411 0.00164535
74 0.00626049 0.0382914 0.0168657 0.0382914 0.0190426 0.00165744
75 0.00639785 0.0384808 0.0168295 0.0384808 0.0192362 0.00168896
76 0.00670451 0.0388928 0.0167319 0.0388928 0.0196606 0.00175903
77 0.00686 0.0390961 0.0166843 0.0390961 0.0198718 0.00178193
78 0.006991 0.0391729 0.0166451 0.0391729 0.0200478 0.00180105
79 0.00740968 0.03941 0.0163691 0.03941 0.0205987 0.00186114
80 0.00755458 0.0394893 0.0162783 0.0394893 0.0207855 0.00188414
81 0.00766474 0.0395486 0.0161272 0.0395486 0.0209262 0.00190152
82 0.00809872 0.0397752 0.0155652 0.0397752 0.0214703 0.00196912
83 0.00817305 0.0398129 0.0154739 0.0398129 0.0215619 0.00197929
84 0.00853198 0.0399908 0.0150514 0.0399908 0.021985 0.00202788
85 0.00856388 0.0400063 0.0150088 0.0400063 0.0220221 0.00203215
86 0.00895053 0.0396539 0.0145136 0.0396539 0.0224661 0.00208342
87 0.00903229 0.0395817 0.0144137 0.0395817 0.0225586 0.002092
88 0.00932098 0.0393329 0.0140732 0.0393329 0.0228011 0.00212197
89 0.00956727 0.0391279 0.0137056 0.0391279 0.0230041 0.00214713
90 0.0098915 0.0386924 0.0132498 0.0386924 0.0232661 0.00217973
91 0.00998143 0.038575 0.0131286 0.038575 0.0233377 0.00218977
92 0.0100702 0.0384605 0.0130112 0.0384605 0.0233592 0.00219965
93 0.0105699 0.0378401 0.0122854 0.0378401 0.0234768 0.00225445
94 0.0107597 0.0376558 0.0120289 0.0370588 0.0235202 0.00227494
95 0.0111523 0.0372876 0.0112103 0.0355344 0.0236078 0.00231675
96 0.0119395 0.0365967 0.00980323 0.0328045 0.0237605 0.00239844
97 0.0122009 0.0362427 0.00939439 0.0319821 0.0238092 0.00242499
98 0.0125521 0.0357842 0.00888454 0.0313323 0.0238732 0.00246021
99 0.0126301 0.0356848 0.00878409 0.0311921 0.0238872 0.00246797
100 0.0131828 0.0350055 0.00812037 0.0302405 0.0239841 0.00249212
101 0.0131902 0.0349968 0.00811207 0.0302177 0.0239853 0.00249244
102 0.0132625 0.034911 0.00803109 0.0299945 0.0239977 0.00249554
103 0.0138586 0.034229 0.00725943 0.0282589 0.0240977 0.00252062
104 0.0139567 0.0341208 0.00708952 0.0279898 0.0241138 0.00252467
105 0.0140848 0.0339812 0.0068754 0.0276453 0.0241346 0.00253408
106 0.0145718 0.0334668 0.00613402 0.0260194 0.0242123 0.0025694
107 0.015596 0.0324622 0.00488351 0.0230516 0.0243682 0.00264145
108 0.0156321 0.0324285 0.00484569 0.0229566 0.0243736 0.00264353
109 0.0160748 0.0320247 0.00454456 0.0218416 0.024438 0.00266873
110 0.0160817 0.0320185 0.00454008 0.0218263 0.024439 0.00266912
111 0.0160983 0.0320037 0.00452936 0.0217898 0.024439 0.00267005
112 0.0163348 0.0317426 0.0043801 0.0212782 0.0244399 0.00268332
113 0.01688 0.0311625 0.00391489 0.0201699 0.0244419 0.00271342
114 0.0169853 0.0310538 0.00381804 0.0199666 0.0244422 0.00271916
115 0.0172348 0.0308004 0.00360024 0.0189953 0.0244431 0.00273267
116 0.0177838 0.0302626 0.00317311 0.0170639 0.024445 0.00275902
117 0.0179674 0.0301689 0.0030445 0.0164749 0.0244456 0.00276771
118 0.0181382 0.0300829 0.0029307 0.0159506 0.0244462 0.00277574
119 0.0191648 0.029587 0.00234786 0.0144184 0.0244494 0.00282291
120 0.0192434 0.0295504 0.00230944 0.014238 0.0244497 0.00282645
121 0.0192583 0.0295435 0.00230118 0.0142042 0.0244497 0.00282712
122 0.0196673 0.0293566 0.00208742 0.0133157 0.024451 0.00284738
123 0.0198053 0.0292947 0.0020028 0.0130326 0.0244514 0.00285416
124 0.0198666 0.0292674 0.00196652 0.0128957 0.0244516 0.00285715
125 0.0200743 0.029187 0.0018491 0.0124451 0.0244522 0.00286727
126 0.0204664 0.0290381 0.00164904 0.0116485 0.0244055 0.00288618
127 0.0211505 0.0287866 0.00135741 0.010529 0.0243262 0.0029186
128 0.0212182 0.0287623 0.00133198 0.0104145 0.0243185 0.00292177
129 0.021282 0.0287395 0.00131837 0.0103081 0.0243113 0.00292476
130 0.0218565 0.0285377 0.00120359 0.00941069 0.0242473 0.00294253
131 0.0219265 0.0285136 0.00119051 0.00926912 0.0242396 0.00294467
132 0.0224095 0.0283497 0.00107606 0.0083589 0.0241874 0.0029593
133 0.0224273 0.0283438 0.00106757 0.0083275 0.0241855 0.00295983
134 0.0230797 0.0281296 0.000801613 0.00726847 0.0241872 0.0029792
135 0.0233876 0.0280311 0.000702182 0.00697834 0.024188 0.00298819
136 0.0235174 0.0279901 0.000690342 0.00686067 0.0241883 0.00299196
137 0.0238511 0.027886 0.000661084 0.00656991 0.0241892 0.00300489
138 0.0241693 0.0277884 0.000634696 0.00627878 0.02419 0.0030171
139 0.0245202 0.0276827 0.000589171 0.00597684 0.0241908 0.00303044
140 0.0246473 0.0276508 0.000573652 0.00587213 0.0241911 0.00303524
141 0.0247007 0.0276375 0.000567271 0.00580681 0.0241912 0.00303726
142 0.0247808 0.0276175 0.000554997 0.0057105 0.0241914 0.00304027
143 0.0251891 0.0275171 0.000496995 0.00524832 0.0241123 0.00305551
144 0.0257429 0.027384 0.000429101 0.00469078 0.0240075 0.00307592
145 0.0262784 0.0272586 0.000373391 0.00440315 0.0239086 0.00309537
146 0.0266034 0.027184 0.00034365 0.00423995 0.0238498 0.00309546
147 0.0269317 0.0271097 0.000316323 0.00395764 0.0237913 0.00309555
148 0.027091 0.0270741 0.000303969 0.00382869 0.0237632 0.0030956
149 0.0276843 0.0270162 0.000262596 0.00339009 0.0236602 0.00309576
150 0.0277765 0.0270073 0.000256766 0.00332738 0.0236509 0.00309579
151 0.0287036 0.0269197 0.000205693 0.00276699 0.0235585 0.00313965
152 0.0290112 0.0268913 0.000191405 0.00247298 0.0235285 0.00315402
153 0.029649 0.0268335 0.000165257 0.00221027 0.0234676 0.00318354
154 0.0302665 0.0267789 0.000143781 0.0019871 0.02341 0.00321177
155 0.0303009 0.0267758 0.000142681 0.00197547 0.0234069 0.00321334
156 0.0312868 0.0266912 0.000114932 0.00142623 0.0233177 0.00325772
157 0.0323326 0.0266045 9.20442e-05 0.00128915 0.0232265 0.00330394
158 0.032679 0.0265764 8.56504e-05 0.00115217 0.023197 0.00331906
159 0.0333975 0.0265193 7.39498e-05 0.00102977 0.0231369 0.00335013
160 0.0338141 0.0264868 6.80101e-05 0.000965915 0.0231027 0.00336797
161 0.0341318 0.0264874 6.38475e-05 0.000920379 0.023077 0.00338149
162 0.034302 0.0264877 6.17374e-05 0.000846964 0.0230633 0.0033887
163 0.0348507 0.0264888 5.54618e-05 0.000649701 0.0230197 0.00339429
164 0.0356169 0.0264902 4.78852e-05 0.000580682 0.0229601 0.00340195
165 0.0364 0.0264916 4.13437e-05 0.000518994 0.0229006 0.00340964
166 0.0365228 0.0264918 4.0414e-05 0.000502745 0.0228914 0.00341083
167 0.0367916 0.0264923 3.84606e-05 0.000469089 0.0228919 0.00341342
168 0.0373626 0.0264933 3.46613e-05 0.00043323 0.0228927 0.00341888
169 0.0376005 0.0264766 3.32065e-05 0.000419257 0.0228931 0.00342113
170 0.0383259 0.0264266 2.91856e-05 0.000392736 0.0228941 0.00342792
171 0.0388556 0.0263907 2.66015e-05 0.000374728 0.0228949 0.00344395
172 0.0408055 0.0262632 1.91108e-05 0.000316957 0.0228976 0.00350172
173 0.0417419 0.0262043 1.63952e-05 0.000293294 0.0228463 0.00352883
174 0.0423533 0.0262053 1.48615e-05 0.000279067 0.0228135 0.00354631
175 0.0455884 0.02621 9.03962e-06 0.000216968 0.0226479 0.00362711
176 0.0466366 0.0262114 7.75289e-06 0.00020074 0.022597 0.00365244
177 0.0473258 0.0261734 7.02153e-06 0.000190918 0.0225643 0.00366888
178 0.0509319 0.0259839 4.27585e-06 0.000148522 0.0224009 0.00376158
179 0.052103 0.0259256 3.66721e-06 0.000137413 0.0223553 0.00379075
180 0.052299 0.0259258 3.57541e-06 0.000135661 0.0223478 0.00379559
181 0.0582127 0.0259326 1.73413e-06 9.40502e-05 0.022134 0.00392211
182 0.0584391 0.0259328 1.68925e-06 9.281e-05 0.0221263 0.00392678
183 0.0645773 0.0259391 8.60429e-07 6.59577e-05 0.0219289 0.004017
184 0.0649969 0.0259395 8.23598e-07 6.45129e-05 0.0219162 0.00402497
185 0.0650387 0.0259396 8.20027e-07 6.43711e-05 0.0219148 0.00402576
186 0.072159 0.0256743 4.06522e-07 4.51238e-05 0.0216907 0.00415584
187 0.0726154 0.0256583 3.89572e-07 4.41613e-05 0.0216772 0.0041644
188 0.0726621 0.0256567 3.87882e-07 4.40642e-05 0.021674 0.00416527
189 0.0802288 0.0256629 1.9866e-07 3.14027e-05 0.0212006 0.00430212
190 0.0811825 0.0256636 1.8342e-07 3.0159e-05 0.0211758 0.00431874
191 0.0896327 0.0256698 9.39686e-08 2.14962e-05 0.0209694 0.00446057
192 0.0897019 0.0256699 9.34798e-08 2.14395e-05 0.020968 0.00446169
193 0.0952414 0.0255181 6.23652e-08 1.74672e-05 0.0208606 0.00454979
194 0.100216 0.0253899 4.42171e-08 1.46761e-05 0.0207698 0.00459752
195 0.106419 0.0253936 2.94739e-08 1.19516e-05 0.0206631 0.00465445
196 0.111968 0.0253968 2.09091e-08 1.00448e-05 0.0205733 0.00470858
197 0.11566 0.0253988 1.67939e-08 8.98982e-06 0.0205162 0.00474345
198 0.117596 0.0253998 1.50126e-08 8.49373e-06 0.0204825 0.0047614
199 0.125097 0.0254037 9.88741e-09 6.87499e-06 0.0203576 0.00485237
200 0.129217 0.0254057 7.9437e-09 6.15383e-06 0.0202924 0.00490074
201 0.131403 0.0254067 7.09293e-09 5.81083e-06 0.0202588 0.00492597
202 0.139766 0.0254105 4.67551e-09 4.70548e-06 0.0201355 0.00503034
203 0.144363 0.0253709 3.75746e-09 4.21251e-06 0.0200711 0.00508596
204 0.145211 0.0253637 3.61177e-09 4.129e-06 0.0200582 0.00509609
205 0.159506 0.0252491 1.91554e-09 2.99504e-06 0.0198517 0.00519511
206 0.162252 0.0252283 1.70693e-09 2.8252e-06 0.0198213 0.00521332
207 0.174458 0.0251402 1.0458e-09 2.2046e-06 0.0196927 0.00538709
208 0.17931 0.0251419 8.68926e-10 2.00721e-06 0.0196443 0.00545431
209 0.190641 0.0251457 5.74439e-10 1.62778e-06 0.0195366 0.00553085
210 0.198144 0.025148 4.42591e-10 1.42647e-06 0.0194691 0.00557962
211 0.203554 0.0251497 3.68965e-10 1.30094e-06 0.0194221 0.00562454
212 0.212995 0.0251525 2.71638e-10 1.1141e-06 0.0192464 0.00570097
213 0.227403 0.0249717 1.74576e-10 8.9067e-07 0.0189956 0.00581314
214 0.235337 0.0248775 1.3848e-10 7.92113e-07 0.018924 0.00587278
215 0.251257 0.0247169 8.89981e-11 6.33255e-07 0.018788 0.00598833
216 0.258632 0.0246462 7.32003e-11 5.73604e-07 0.0186794 0.00604013
217 0.262922 0.0246062 6.55028e-11 5.42228e-07 0.0186179 0.00606053
218 0.280695 0.0246101 4.21094e-11 4.33548e-07 0.0183754 0.00614233
219 0.288984 0.0246118 3.45945e-11 3.92478e-07 0.0182737 0.00617908
220 0.290513 0.0246122 3.33835e-11 3.85461e-07 0.0182553 0.00619016
221 0.319352 0.0243828 1.76158e-11 2.78883e-07 0.0179288 0.00639247
222 0.324565 0.0243437 1.57908e-11 2.63861e-07 0.0178735 0.00642774
223 0.35291 0.0243487 8.97007e-12 1.98166e-07 0.0175903 0.00661324
224 0.354229 0.0243489 8.7468e-12 1.95653e-07 0.0175778 0.0066183
225 0.362623 0.0243503 7.46706e-12 1.80595e-07 0.0174955 0.00665014
226 0.394326 0.0241492 4.23926e-12 1.35592e-07 0.0172041 0.00676537
227 0.395733 0.0241407 4.13854e-12 1.33951e-07 0.0171918 0.00677356
228 0.405127 0.0240848 3.53201e-12 1.23624e-07 0.0171021 0.00682778
229 0.435763 0.0239117 2.15866e-12 9.63474e-08 0.0168264 0.00699902
230 0.437224 0.0239038 2.11043e-12 9.52514e-08 0.0168139 0.00700619
231 0.452614 0.0238221 1.67068e-12 8.46245e-08 0.0165549 0.00708077
232 0.486924 0.0234372 1.01989e-12 6.59144e-08 0.0160209 0.00724093
233 0.500068 0.0232984 8.51956e-13 6.01757e-08 0.0158306 0.00730676
234 0.538092 0.0229587 5.19335e-13 4.68368e-08 0.0153184 0.007491
235 0.558659 0.0227868 4.03102e-13 4.11984e-08 0.0150628 0.00757409
236 0.589519 0.0225153 2.80346e-13 3.42791e-08 0.0147037 0.00769481
237 0.617232 0.0222859 2.0556e-13 2.92958e-08 0.0143291 0.00779948
238 0.651244 0.0218881 1.43086e-13 2.43863e-08 0.0139038 0.0079235
239 0.681917 0.0215524 1.04855e-13 2.08351e-08 0.013426 0.00803148
240 0.711468 0.0211866 7.87313e-14 1.80216e-08 0.0130001 0.00813231
241 0.761749 0.0206107 4.96406e-14 1.42686e-08 0.0122511 0.00829729
242 0.768691 0.020506 4.66901e-14 1.38327e-08 0.0121549 0.00831945
243 0.841507 0.0194895 2.5336e-14 1.01507e-08 0.0109087 0.00854387
244 0.919366 0.0184287 1.39368e-14 7.50033e-09 0.00981384 0.00876915
245 0.927346 0.0183394 1.31465e-14 7.2819e-09 0.00971298 0.00879147
246 1.00172 0.0175616 7.80758e-15 5.59342e-09 0.00858531 0.00899321
247 1.01563 0.0174261 7.11319e-15 5.33577e-09 0.0083669 0.00902976
248 1.03582 0.0171797 6.22746e-15 4.98836e-09 0.00806467 0.0090822
249 1.07012 0.0167796 4.99745e-15 4.46248e-09 0.00758836 0.00914304
250 1.09736 0.0164772 4.21712e-15 4.09494e-09 0.00717181 0.00919026
251 1.15738 0.0159315 2.94311e-15 3.4132e-09 0.0063633 0.00929112
252 1.19448 0.0156168 2.37828e-15 3.06414e-09 0.005928 0.00939126
253 1.19889 0.0155804 2.31975e-15 3.02574e-09 0.00588802 0.00940304
254 1.26208 0.014984 1.63971e-15 2.53833e-09 0.00535855 0.00956859
255 1.279 0.0148332 1.49865e-15 2.42532e-09 0.00514364 0.00961199
256 1.30427 0.0146144 1.31318e-15 2.26841e-09 0.00484355 0.00967609
257 1.30976 0.0145678 1.27642e-15 2.23603e-09 0.00479699 0.00968992
258 1.36289 0.014182 9.75788e-16 1.95176e-09 0.00437816 0.00982173
259 1.40838 0.0138712 7.81695e-16 1.74447e-09 0.00391317 0.00993193
260 1.4134 0.0138379 7.63122e-16 1.72336e-09 0.00385984 0.00994395
261 1.44683 0.0136213 6.51659e-16 1.59096e-09 0.00352733 0.0100081
262 1.53704 0.0131101 4.33121e-16 1.29372e-09 0.00279399 0.0101759
263 1.5807 0.0128799 3.58465e-16 1.17555e-09 0.00261985 0.0102546
264 1.60612 0.012788 3.2184e-16 1.11313e-09 0.00252554 0.0102997
265 1.65974 0.012601 2.57823e-16 9.94904e-10 0.0022573 0.0103931
266 1.74628 0.0123169 1.82903e-16 8.3617e-10 0.00162758 0.0105394
267 1.75202 0.0123088 1.78894e-16 8.2684e-10 0.00159357 0.0105489
268 1.83077 0.0122008 1.32931e-16 7.11422e-10 0.00144046 0.0106772
269 1.87102 0.0121477 1.14772e-16 6.60436e-10 0.00128743 0.0107413
270 1.88625 0.012128 1.08656e-16 6.42378e-10 0.00121567 0.0107652
271 1.95088 0.0120464 8.65404e-17 5.72471e-10 0.000957846 0.0108892
272 1.97479 0.0119807 7.97049e-17 5.49113e-10 0.000878754 0.0109344
273 2.04071 0.0118055 6.38509e-17 4.90793e-10 0.000785423 0.011057
274 2.08446 0.0116937 5.53283e-17 4.56455e-10 0.000711827 0.011137
275 2.08567 0.0116906 5.51124e-17 4.55552e-10 0.000709918 0.0111435
276 2.15524 0.0115198 4.41564e-17 4.07198e-10 0.000539539 0.0115198
277 2.17726 0.0115319 4.12262e-17 3.93286e-10 0.000495563 0.0115319
278 2.24994 0.0115713 3.3026e-17 3.51516e-10 0.00044293 0.0115713
279 2.2995 0.0115975 2.85061e-17 3.26276e-10 0.00040035 0.0115975
280 2.32424 0.0116103 2.65182e-17 3.14551e-10 0.000361853 0.0116103
281 2.40807 0.0116531 2.08744e-17 2.78659e-10 0.000258924 0.0116531
282 2.66112 0.0120555 1.06294e-17 1.98007e-10 0.000100745 0.0120555
283 2.97342 0.0123329 5.02346e-18 1.35483e-10 3.53152e-05 0.0123329
284 3.28587 0.0127588 2.55798e-18 9.627e-11 1.37409e-05 0.0127588
285 3.67165 0.0131998 1.20855e-18 6.58614e-11 4.81477e-06 0.0131998
286 4.0573 0.0135031 6.15582e-19 4.6806e-11 1.87415e-06 0.0135031
287 4.53365 0.0139698 2.9084e-19 3.20215e-11 6.56697e-07 0.0139698
288 5.01006 0.0144522 1.48098e-19 2.27535e-11 2.55516e-07 0.0144522
289 5.59826 0.0149517 6.99709e-20 1.55664e-11 8.95321e-08 0.0149517
290 6.18655 0.0154681 3.56297e-20 1.1061e-11 3.48362e-08 0.0154681
291 6.91288 0.0160027 1.68337e-20 7.56721e-12 1.22065e-08 0.0160027
292 7.6393 0.0165554 8.57185e-21 5.37703e-12 4.74947e-09 0.0165554
293 8.53619 0.0171276 4.04989e-21 3.6786e-12 1.6642e-09 0.0171276
294 9.4328 0.0175211 2.06283e-21 2.61429e-12 6.47791e-10 0.0175211
295 10.4245 0.0183311 1.0501e-21 1.85736e-12 2.51948e-10 0.0183311
296 11.6479 0.0187528 4.96279e-22 1.27087e-12 8.83178e-11 0.0187528
297 12.8718 0.0194004 2.52709e-22 9.03041e-13 3.43638e-11 0.0194004
298 14.3831 0.0200709 1.19396e-22 6.17799e-13 1.2041e-11 0.0200709
299 15.8945 0.0207641 6.07972e-23 4.3899e-13 4.68505e-12 0.0207641
300 17.7606 0.0214818 2.87245e-23 3.00327e-13 1.64163e-12 0.0214818
301 19.6277 0.0224748 1.46225e-23 2.13372e-13 6.38487e-13 0.0224748
302 21.9312 0.0229918 6.91059e-24 1.45996e-13 2.23815e-13 0.0229918
303 24.2358 0.0237858 3.51892e-24 1.03741e-13 8.70847e-14 0.0237858
304 27.0812 0.0246079 1.66256e-24 7.09722e-14 3.05143e-14 0.0246079
305 29.9257 0.0251733 8.46833e-25 5.04381e-14 1.18777e-14 0.0251733
306 33.4391 0.0260434 4.00098e-25 3.45064e-14 4.16191e-15 0.0260434
307 36.9514 0.0266418 2.03792e-25 2.45228e-14 1.62002e-15 0.0266418
308 41.2879 0.0272547 9.63121e-26 1.67793e-14 5.67883e-16 0.0272547
309 46.1333 0.0278816 4.55172e-26 1.14809e-14 1.99065e-16 0.0278816
310 50.9789 0.0285222 2.31844e-26 8.15921e-15 7.74862e-17 0.0285222
311 56.9567 0.02853 1.09633e-26 5.58443e-15 2.7184e-17 0.02853
312 62.9365 0.0288594 5.58583e-27 3.9693e-15 1.05857e-17 0.0288594
313 70.3165 0.0288672 2.6414e-27 2.71672e-15 3.7137e-18 0.0288672
314 78.5585 0.0285523 1.24941e-27 1.85969e-15 1.30338e-18 0.0285523
315 86.7913 0.0276126 6.37316e-28 1.3226e-15 5.08371e-19 0.0276126
316 95.8829 0.0264055 3.25184e-28 9.40766e-16 1.98365e-19 0.0264055
317 105.927 0.0252511 1.65922e-28 6.69167e-16 7.74015e-20 0.0252511
318 115.727 0.0238767 9.12706e-29 4.94445e-16 3.35506e-20 0.0238767
319 126.424 0.0220755 5.02352e-29 3.65451e-16 1.45547e-20 0.0220755
320 136.586 0.0204095 2.97997e-29 2.80547e-16 7.01129e-21 0.0204095
321 145.938 0.0188688 1.9052e-29 2.23692e-16 3.75045e-21 0.0188688
322 155.931 0.0174444 1.21806e-29 1.78359e-16 2.00618e-21 0.0174444
323 164.756 0.0157687 8.39797e-30 1.47752e-16 1.19261e-21 0.0157687
324 174.088 0.014415 5.78834e-30 1.2238e-16 7.0868e-22 0.014415
325 183.941 0.0130303 3.9908e-30 1.01379e-16 4.21287e-22 0.0130303
326 192.209 0.0117783 2.96545e-30 8.72277e-17 2.78098e-22 0.0117783
327 200.839 0.0105276 2.20418e-30 7.50626e-17 1.83651e-22 0.0105276
328 209.866 0.00951609 1.63786e-30 6.45847e-17 1.21231e-22 0.00951609
329 219.299 0.00860174 1.21705e-30 5.55694e-17 8.00263e-23 0.00860174
330 226.629 0.00777504 9.74687e-31 4.96602e-17 5.86601e-23 0.00777504
331 234.194 0.00694927 7.80813e-31 4.43858e-17 4.3016e-23 0.00694927
332 242.022 0.00628138 6.25322e-31 3.96659e-17 3.15312e-23 0.00628138
333 250.101 0.00561425 5.0094e-31 3.5453e-17 2.31221e-23 0.00561425
334 258.449 0.00501797 4.01299e-31 3.16876e-17 1.69556e-23 0.00501797
335 267.088 0.0045357 3.21384e-31 2.8318e-17 1.24287e-23 0.0045357
336 272.959 0.00405386 2.7748e-31 2.62885e-17 1.01205e-23 0.00405386
337 282.083 0.00366425 2.22222e-31 2.3493e-17 7.41844e-24 0.00366425
338 288.285 0.00327499 1.91865e-31 2.18093e-17 6.04074e-24 0.00327499
339 297.908 0.00292716 1.53701e-31 1.9493e-17 4.42972e-24 0.00292716
340 304.457 0.0026162 1.32704e-31 1.80959e-17 3.60707e-24 0.0026162
341 311.164 0.0023647 1.14542e-31 1.67966e-17 2.936e-24 0.0023647
342 318.005 0.00211349 9.88949e-32 1.55928e-17 2.39075e-24 0.00211349
343 324.997 0.00188897 8.5385e-32 1.44753e-17 1.94676e-24 0.00188897
344 332.142 0.0016883 7.37206e-32 1.34379e-17 1.58522e-24 0.0016883
345 339.458 0.001526 6.36313e-32 1.2473e-17 1.2903e-24 0.001526
346 346.922 0.00136389 5.49387e-32 1.15791e-17 1.05067e-24 0.00136389
347 350.639 0.00121896 5.11224e-32 1.11646e-17 9.50029e-25 0.00121896
348 358.348 0.00108947 4.41386e-32 1.03645e-17 7.73597e-25 0.00108947
349 366.226 0.000973734 3.81089e-32 9.62166e-18 6.2993e-25 0.000973734
350 374.278 0.000870292 3.29028e-32 8.93209e-18 5.12944e-25 0.000870292
351 378.289 0.000777818 3.06173e-32 8.61238e-18 4.63809e-25 0.000777818
352 386.622 0.000703044 2.6427e-32 7.99398e-18 3.7752e-25 0.000703044
353 395.122 0.000628358 2.28168e-32 7.42106e-18 3.0741e-25 0.000628358
354 399.356 0.000561591 2.12319e-32 7.15544e-18 2.77963e-25 0.000561591
355 408.136 0.000501931 1.83314e-32 6.64262e-18 2.26342e-25 0.000501931
356 412.51 0.000448598 1.7058e-32 6.40486e-18 2.0466e-25 0.000448598
357 421.579 0.000400942 1.47277e-32 5.94584e-18 1.66652e-25 0.000400942

191
src/sed/mehdipour/generate_sed.cpp Normal file
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#include "agn.hpp"
int main(int argc, char const *argv[])
{
std::cout
<< "Setting up environment.\n";
bool debug=true;
// Create 2d table using n bins, linear values of SED. The
// agn em source class has a function for this. A
// std::map<double,double> represents the table.
int n = 1000;
agn::sed_table SED;
const char* table_filename = "agn_source_table";
const char* debug_filename = "agn_source_debug";
const char* cloudyscript_filename = "agn_source_cloudyscript";
std::ofstream table_file( table_filename,
std::ofstream::out
);
std::ofstream debug_file( debug_filename,
std::ofstream::out
);
std::ofstream cloudyscript_file(cloudyscript_filename,
std::ofstream::out
);
if(debug) std::cout
<< "Debug mode.\n";
std::cout
<< "Creating agn sed object.\n";
// agn em source spectrum arguments
double T=4e6,
alpha_ox = -1.20,
alpha_x = -0.670,
alpha_uv = -1.30,
cutoff_uv_rydberg = .25,
cutoff_xray_rydberg = .1,
log_radius_in_cm=16.7272;;
agn::sed_pow_law agnsource(
T,
alpha_ox,
alpha_x,
alpha_uv,
cutoff_uv_rydberg,
cutoff_xray_rydberg,
log_radius_in_cm
);
if(debug) debug_file
<< "cutoff_uv_eV: "
<< agnsource._cutoff_uv_eV
<< "\n"
<< "cutoff_xray_eV: "
<< agnsource._cutoff_xray_eV
<< "\n"
<< "xray coefficient: "
<< agnsource._xray_coefficient
<< "\n\n";
std::cout
<< "Evaluating relative spectral intensity for "
<< n
<< " photon energy bins.\n";
SED = agnsource.histogram_table(n);
std::cout
<< "Printing SED table to file "
<< table_filename
<< "\n";
table_file << agn::format_sed_table(SED);
std::cout
<< "Printing CLOUDY interpolate command syntax to file "
<< cloudyscript_filename
<< "\n";
cloudyscript_file << agn::cloudy_interpolate_str(SED);
std::cout
<< "Closing files. Goodbye.\n";
debug_file.close();
cloudyscript_file.close();
table_file.close();
return 0;
}
double agn::hnu_at(int i,int n) {
double relative_coord=(double)(i)/n;
double x_coord = relative_coord*CONT_WIDTH_X + CONT_MIN_X;
return pow(10,x_coord);
}
agn::sed_table agn::sed_pow_law::histogram_table(int n){
agn::sed_table output;
double max=0,min=1,hnu;
for(int i=0; i<n; i++) {
hnu = hnu_at(i,n);
output.value[hnu] = this->sed(hnu);
if (output.value[hnu] > max) max = output.value[hnu];
if (output.value[hnu] < min) min = output.value[hnu];
}
// Add a final point at 100 KeV
hnu = 1e5;
output.value[hnu] = this->sed(hnu);
return output;
}
double agn::sed_pow_law::sed(double hnu) {
double magnitude=0.0;
magnitude += this->eval_uv(hnu);
magnitude += this->eval_xray(hnu);
if (magnitude < agn::CONT_MIN_VAL) return agn::CONT_MIN_VAL;
return magnitude;
}
double agn::sed_pow_law::eval_uv(double hnu) {
double bigbump_kT = _T
* agn::BOLTZMANN_CONST;
double magnitude = pow(hnu,(1+_alpha_uv))
* exp(-(hnu)/bigbump_kT)
* exp(-(_cutoff_uv_eV/hnu))
* _scaling_factor;
if (magnitude < agn::CONT_MIN_VAL) return agn::CONT_MIN_VAL;
return magnitude;
}
double agn::sed_pow_law::eval_xray(double hnu) {
return _xray_coefficient
* pow(hnu/2000,1+_alpha_x)
* exp(-_cutoff_xray_eV/hnu)
* _scaling_factor;
}
double agn::sed_pow_law::SED_at_2KeV() {
double ELe_at_2500A_no_scale = eval_uv(IN_EV_2500A)
/ _scaling_factor;
double energy_ratio = 2000/IN_EV_2500A;
// Returns EL[e] at 2 KeV
return ELe_at_2500A_no_scale
* pow(energy_ratio,_alpha_ox + 1);
}
agn::sed_pow_law::sed_pow_law (
double T,
double alpha_ox,
double alpha_x,
double alpha_uv,
double cutoff_uv_rydberg,
double cutoff_xray_rydberg,
double log_radius_in_cm,
double scaling_factor
):
_T(T),
_alpha_ox(alpha_ox),
_alpha_x(alpha_x),
_alpha_uv(alpha_uv),
_cutoff_uv_rydberg(cutoff_uv_rydberg),
_cutoff_xray_rydberg(cutoff_xray_rydberg),
_log_radius_in_cm(log_radius_in_cm),
_scaling_factor(scaling_factor)
{
_cutoff_uv_eV = cutoff_uv_rydberg*RYDBERG_UNIT_EV;
_cutoff_xray_eV = cutoff_xray_rydberg*RYDBERG_UNIT_EV;
_radius_in_cm = pow(10,log_radius_in_cm);
_radius_in_cm_squared = _radius_in_cm*_radius_in_cm;
_xray_coefficient = agn::sed_pow_law::SED_at_2KeV();
}

116
src/sed/mehdipour/ngc5548_magdziarz.py Executable file
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""" A program to recreate the average spectrum fit for ngc 5548 in Magdziarz et al 1998 """
import math
import scipy
import numpy
PI=3.14159265358979323846;
PLANCK_CONST=4.135668e-15; # in eV * s
BOLTZMANN_CONST=0.00008617332385; # in eV / K
RYDBERG_CONST=1.0973731568539e7; # in 1 / m
RYDBERG_UNIT_EV=13.60569252; # in eV
RYDBERG_UNIT_ANGSTROM=1e10/RYDBERG_CONST; # in A
CONT_MIN_ENERGY_keV = 1e-3;
CONT_MAX_ENERGY_keV = 1e2;
CONT_MIN_X = math.log10(CONT_MIN_ENERGY_keV);
CONT_MAX_X = math.log10(CONT_MAX_ENERGY_keV);
CONT_WIDTH_X = CONT_MAX_X - CONT_MIN_X;
CONT_MIN_VAL = 1e-35;
""" Cloudy's continuum domain, for reference, version 13.3 """
CLOUDY_EMM = 1.001e-8; # in Rydberg
CLOUDY_EGAMRY = 7.354e6; # in Rydberg
CLOUDY_MIN_EV = CLOUDY_EMM*RYDBERG_UNIT_EV;
CLOUDY_MAX_EV = CLOUDY_EGAMRY*RYDBERG_UNIT_EV;
IN_EV_2500A = 12398.41929/2500;
""" Curve Parameters from MNRAS 301 Mdagziarz 1998 """
α_HC = 0.86
# Soft Excess
α_SE_sec2_1 = 1.1 # Quoted consistent with Korista 1995 and Marshall 1997
kT_SE_sec2_1 = .56
# Comtonization fitted to ROSAT data
# ξ =
# OSSE data fit
α_HC = 0.86
R = 0.96
E_cutoff_HC = .120 # keV, phase 1
F_HC = .38 # keV cm⁻² s⁻¹
# E_cutoff_HC = 118 # keV, phase 3
# F_HC = .61 # keV cm⁻² s⁻¹
# Section 3.3 values
kT_SE_sec3_2 = .270 # keV
α_SE_sec3_2 = 1.13
kT_HC_sec3_2 = 55 # keV
α_HC_sec3_2 = .76
def hν_at(i,n):
""" returns hν coordinate of bin i out of n """
relative_coord = i/n
x_coord = relative_coord*CONT_WIDTH_X + CONT_MIN_X;
return math.pow(10,x_coord);
def histogram_table(n):
output = []
# max=0,min=1
indices = range(n)
for i in range(0,n):
hν = hν_at(i,n);
value = (hν,sed(hν))
# if (output.value[hν] > max) max = output.value[hν];
# if (output.value[hν] < min) min = output.value[hν];
output.append(value)
# Add a final point at 100 KeV
hν = 1e2;
value = sed(hν);
output.append((hν,value))
return output;
def sed(hν):
magnitude=0.0;
magnitude += powlaw_cutoff(hν,α_HC,E_cutoff_HC,1) # OSSE data fit
# magnitude += powlaw_cutoff(hν,α_SE_sec2_1,kT_SE_sec2_1,1)
# magnitude += powlaw_cutoff(hν,α_SE_sec3_2,kT_SE_sec3_2,1)
#magnitude += compt_approx(hν,-1.3,.345,.0034,1)
if magnitude < CONT_MIN_VAL: return CONT_MIN_VAL
# magnitude = CONT_MIN_VAL;
return magnitude;
def powlaw_cutoff(hν,α,E_cutoff,norm):
low_cutoff = .1
resultant = norm
resultant *= math.exp(-hν/E_cutoff)
#resultant *= math.exp(-low_cutoff/hν)
resultant *= math.pow(hν,1+α)
return resultant
def compt_approx(hν,α,kT_keV,cutoff_keV,norm):
magnitude = math.pow(hν,(1+α))
magnitude *= math.exp(-(hν/kT_keV))
magnitude *= math.exp(-(cutoff_keV/hν))
magnitude *= norm
return magnitude
test_table = histogram_table(500)
for pair in test_table:
print (pair[0],pair[1])

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src/sed/mehdipour/powlaw-cutoff.pl Executable file
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#!/usr/local/bin/perl
use strict; use warnings; use 5.010; use utf8;
use IO::Handle;
use File::Temp "tempfile";
open(my $spectrum_file,"spectrum");
# my @x = ();
# my @y = ();
# my($xi,$yi);
# ($xi,$yi)=(0,0);
# while(my $line = <$spectrum_file>) {
# $line =~ /([0-9\.]+)\s+([0-9\.]+)/;
# ($x[$xi],$y[$yi])=($1,$2);
# $xi++; $yi++;
# }
# while (my $line = <$spectrum_file>) {
# print $line;
# }
my($T,$N) = tempfile("spectrum-XXXXXXXX", "UNLINK", 1);
# for my $t (100..500)
# { say $T $t*sin($t*0.1), " ", $t*cos($t*0.1); }
while (my $_ = <$spectrum_file>) {
chomp;
say $T $_;
}
close $T;
open my $P, "|-", "gnuplot" or die;
printflush $P qq[
unset key
set logscale xy
set xrange [.001,1000]
plot "$N"
];
<STDIN>;
close $P;
# sub histogram_table(n) {
# my @output = ()
# my @x = ()
# my @y = ()
# output.append(x)
# output.append(y)
# max=0
# min=1
# indices = range(n)
# for i in range(0,n):
# hνᗉkeVᗆ = hνᗉkeVᗆ_at(i,n);
# x.append(hνᗉkeVᗆ)
# value = total(hνᗉkeVᗆ,1,1,1)
# y.append(value)
# if (value > max): max = value;
# if (value < min): min = value;
# # Add a final point at 100 KeV
# hνᗉkeVᗆ = 1e2;
# x.append(hνᗉkeVᗆ)
# y.append(total(hνᗉkeVᗆ,1,1,1))
# output.append(x)
# output.append(y)
# return output;
# }
close($spectrum_file)
__END__

139
src/sed/mehdipour/powlaw-cutoff.py Executable file
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""" A program to recreate the average spectrum fit for ngc 5548 in Magdziarz et al 1998 """
import math
import scipy
import numpy
import matplotlib.pyplot as plt
PI=3.14159265358979323846;
PLANCK_CONST=4.135668e-15; # in eV * s
# Boltzman Constant
kᵦᗉeVᓯKᗆ=0.00008617332385; # in eV / K
kᵦᗉkeVᓯKᗆ=kᵦᗉeVᓯKᗆ/1000;
RYDBERG_CONST=1.0973731568539e7; # in 1 / m
RYDBERG_UNITᗉeVᗆ=13.60569252; # in eV
RYDBERG_UNIT_ANGSTROM=1e10/RYDBERG_CONST; # in A
CONT_MIN_ENERGYᗉkeVᗆ = 1e-3;
CONT_MAX_ENERGYᗉkeVᗆ = 1e2;
CONT_MIN_XᗉkeVᗆ = math.log10(CONT_MIN_ENERGYᗉkeVᗆ);
CONT_MAX_XᗉkeVᗆ = math.log10(CONT_MAX_ENERGYᗉkeVᗆ);
CONT_WIDTH_XᗉkeVᗆ = CONT_MAX_XᗉkeVᗆ - CONT_MIN_XᗉkeVᗆ;
CONT_MIN_VAL = 1e-35;
""" Cloudy's continuum domain, for reference, version 13.3 """
CLOUDY_EMMᗉRydbergᗆ = 1.001e-8; # in Rydberg
CLOUDY_EγᗉRydbergᗆ = 7.354e6; # in Rydberg
CLOUDY_MINᗉeVᗆ= CLOUDY_EMMᗉRydbergᗆ*RYDBERG_UNITᗉeVᗆ;
CLOUDY_MAXᗉeVᗆ= CLOUDY_EγᗉRydbergᗆ*RYDBERG_UNITᗉeVᗆ;
hcᓯ2500ᗉeVᗆ = 12398.41929/2500;
""" Returns the SED as a histrogram (list of floats) with n bins"""
# def histogram_table(n):
# output = []
# # max=0,min=1
# indices = range(n)
# for i in range(0,n):
# hνᗉkeVᗆ = hνᗉkeVᗆ_at(i,n);
# value = (hνᗉkeVᗆ,sum(hνᗉkeVᗆ))
# # if (output.value[hνᗉkeVᗆ] > max) max = output.value[hνᗉkeVᗆ];
# # if (output.value[hνᗉkeVᗆ] < min) min = output.value[hνᗉkeVᗆ];
# output.append(value)
#
# # Add a final point at 100 KeV
# hνᗉkeVᗆ = 1e2;
# value = sum(hνᗉkeVᗆ);
# output.append((hνᗉkeVᗆ,value))
# return output;
def histogram_table(n):
output = []
x = []
y = []
output.append(x)
output.append(y)
max=0
min=1
indices = range(n)
for i in range(0,n):
hνᗉkeVᗆ = hνᗉkeVᗆ_at(i,n);
x.append(hνᗉkeVᗆ)
value = total(hνᗉkeVᗆ,1,1,1)
y.append(value)
if (value > max): max = value;
if (value < min): min = value;
# Add a final point at 100 KeV
hνᗉkeVᗆ = 1e2;
x.append(hνᗉkeVᗆ)
y.append(total(hνᗉkeVᗆ,1,1,1))
output.append(x)
output.append(y)
return output;
# Sums 2 power-law cutoff functions and the disk contribution at energy coordinate hνᗉkeVᗆ in keV.
# Coefficients should be equal to functions at hνᗉkeVᗆ = ?? keV
def total(hνᗉkeVᗆ,C1=1.0,C2=1.0,C3=1.0):
magnitude=0.0
# accretion disk blackbody continuum has α=1/3
magnitude += powlaw_cutoff(hνᗉkeVᗆ,1/3,3e3,6e6,C1)
magnitude += powlaw_cutoff(hνᗉkeVᗆ,-1.1,.01/kᵦᗉkeVᓯKᗆ,1/kᵦᗉkeVᓯKᗆ,C2)
magnitude += powlaw_cutoff(hνᗉkeVᗆ,-0.8,.01/kᵦᗉkeVᓯKᗆ,100/kᵦᗉkeVᓯKᗆ,C3)
if magnitude < CONT_MIN_VAL: return CONT_MIN_VAL
# print (magnitude)
return magnitude;
def hνᗉkeVᗆ_at(i,n):
""" returns hνᗉkeVᗆ coordinate in keV of bin i out of n """
relative_coord = i/n
hν = relative_coord*CONT_WIDTH_XᗉkeVᗆ + CONT_MIN_XᗉkeVᗆ
return math.pow(10,hν)
def powlaw_cutoff(hνᗉkeVᗆ,α,T1,T2,coefficient):
resultant = coefficient
resultant *= math.exp(-hνᗉkeVᗆ/(kᵦᗉkeVᓯKᗆ*T1))
resultant *= math.exp(-kᵦᗉkeVᓯKᗆ*T2/hνᗉkeVᗆ)
resultant *= math.pow(hνᗉkeVᗆ,1+α)
#print(math.exp(-hνᗉkeVᗆ/(kᵦᗉkeVᓯKᗆ*T1)))
#print(-hνᗉkeVᗆ/(kᵦᗉkeVᓯKᗆ*T1))
#print(math.exp(-kᵦᗉkeVᓯKᗆ*T2/hνᗉkeVᗆ))
#print(math.pow(hνᗉkeVᗆ,1+α))
#print(resultant)
#print("──────────────────────────────────────────────────────────────────────────")
return resultant
test_table = histogram_table(500)
fig = plt.figure()
sed_plot = fig.add_subplot(111)
sed_plot.set_xscale("log")
sed_plot.set_yscale("log")
sed_plot.set_xlim(CONT_MIN_XᗉkeVᗆ,CONT_MAX_XᗉkeVᗆ)
sed_plot.set_ylim(1e-1,1e2)
sed_plot.set_aspect(1)
sed_plot.set_title("log-log plot of SED")
sed_plot.plot(test_table[0],test_table[1])
fig.show()
#for pair in test_table:
# print (pair[0],pair[1])
# index=0
# for energy in test_table[0]:
# print (energy,test_table[1][index])
# index += 1

219
src/sed/mehdipour/sed.hpp Normal file
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#ifndef sed_hpp
#define sed_hpp
#include "agn.hpp"
namespace agn {
// Continuum domain, step size constant in log space
``const double CONT_MIN_ENERGY=1e-2; // eV
const double CONT_MAX_ENERGY=1e5; // eV
const double CONT_MIN_X=log10(CONT_MIN_ENERGY);
const double CONT_MAX_X=log10(CONT_MAX_ENERGY);
const double CONT_WIDTH_X=CONT_MAX_X - CONT_MIN_X;
const double CONT_MIN_VAL=1e-35;
// Cloudy's continuum domain, for reference, version 13.3
const double CLOUDY_EMM = 1.001e-8; // in Rydberg
const double CLOUDY_EGAMRY = 7.354e6; // in Rydberg
const double CLOUDY_MIN_EV=CLOUDY_EMM*RYDBERG_UNIT_EV;
const double CLOUDY_MAX_EV=CLOUDY_EGAMRY*RYDBERG_UNIT_EV;
const double IN_EV_2500A=12398.41929/2500;
// SEDs are represented by 2d histogram tables.
struct sed_table {
std::string header;
table_1d value;
};
class sed_pow_law {
public:
// Continuum output functions
// Returns histogram with n bins evenly space in log space
sed_table histogram_table(int n);
// Argument is photon energy in eV
double sed(double hnu);
double eval_uv(double hnu);
double eval_xray(double hnu);
// Determined differently to be of use as the
// xray coefficient.
double SED_at_2KeV();
// Continuum shape arguments
double _T; //TCut
double _alpha_ox;
double _alpha_x;
double _alpha_uv;
double _cutoff_uv_rydberg;
double _cutoff_xray_rydberg;
double _log_radius_in_cm;
// Derived values
double _cutoff_uv_eV; // IRCut
double _cutoff_xray_eV; // lowend_cutoff
double _radius_in_cm;
double _radius_in_cm_squared;
double _scaling_factor;
double _xray_coefficient;
sed_pow_law (
double T,
double alpha_ox,
double alpha_x,
double alpha_uv,
double cutoff_uv_rydberg,
double cutoff_xray_rydberg,
double log_radius_in_cm,
double scaling_factor = 1.0
// EL[e] model scaling factor
// double scaling_factor = 1.39666E44
);
};
// Returns coord in eV for given relative coord.
double hnu_at(int i,int n);
// Takes an SED table as input and returns a string with format:
// '<h*nu>\t<flux>\n' for each energy-flux pair
std::string format_sed_table(sed_table table);
// Read continuum from file with '<h*nu>\t<flux>\n' formatting.
// Will ignore up to 1 header.
sed_table read_sed_table(std::ifstream& table_file);
// Does the same but converts hnu from rydberg to eV.
sed_table read_and_convert_sed_table(std::ifstream& table_file);
// Cloudy takes the SED density as input. This function outputs
// the corresponding SED table's SED density function in the form
// of a cloudy input script "interpolate" command.
std::string cloudy_interpolate_str(sed_table SED);
} // end namespace agn
agn::sed_table agn::read_sed_table(std::ifstream& table_file) {
sed_table resultant;
std::string scratch;
int current_line=0;
double hnu;
std::getline(table_file,scratch);
if(!isdigit(scratch[0])) {
resultant.header = scratch;
current_line++;
}
while(!table_file.eof()) {
table_file >> hnu;
table_file >> resultant.value[hnu];
}
}
agn::sed_table agn::read_and_convert_sed_table(std::ifstream& table_file) {
sed_table resultant;
std::string scratch;
int current_line=0;
double hnu_in_ryd,hnu_in_ev,value;
std::getline(table_file,scratch);
if(!isdigit(scratch[0])) {
resultant.header = scratch;
current_line++;
}
int c=0;
while(!table_file.eof()) {
//std::cout << c;
table_file >> hnu_in_ryd;
hnu_in_ev = hnu_in_ryd*agn::RYDBERG_UNIT_EV;
table_file >> resultant.value[hnu_in_ev];
getline(table_file,scratch);
}
}
std::string agn::format_sed_table(agn::sed_table table) {
std::stringstream output;
if (!table.header.empty()) output << table.header;
output << std::setprecision(5);
agn::table2d::iterator table_iterator;
table_iterator=table.value.begin();
while(table_iterator != table.value.end()) {
output
<< std::fixed
<< table_iterator->first
<< "\t"
<< std::scientific
<< table_iterator->second
<< "\n";
table_iterator++;
}
return output.str();
}
std::string agn::cloudy_interpolate_str(agn::sed_table table) {
std::stringstream output;
agn::table2d::iterator table_iterator = table.value.begin();
// Lead in to uv bump at slope=2 in log(energy [rydberg]) space
double energy_in_rydbergs = table_iterator->first
/ agn::RYDBERG_UNIT_EV;
double log_uv_bump_start = log10( energy_in_rydbergs );
double log_lowest_value = log10(table_iterator->second
/ table_iterator->first);
double log_min_energy = log10(agn::CLOUDY_EMM)
- 1;
double log_SED_density = log_lowest_value
- 2*(log_uv_bump_start
- log_min_energy);
if ( log_SED_density < 1e-36 ) log_SED_density = 1e-36;
output
<< "interpolate ("
<< pow(10,log_min_energy)
<< " "
<< log_SED_density
<< ")";
int count=0;
while(table_iterator != table.value.end()) {
energy_in_rydbergs = table_iterator->first
/ agn::RYDBERG_UNIT_EV;
double log_SED_density = log10( table_iterator->second
/ table_iterator->first);
if ((count%5)==0) output << "\n" << "continue ";
else output << " ";
output
<< "("
<< energy_in_rydbergs
<< " "
<< log_SED_density
<< ")";
count++;
table_iterator++;
}
// Trail off at slope=-2 in log(energy [rydberg]) space
while ( energy_in_rydbergs < agn::CLOUDY_EGAMRY ) {
double log_energy = log10(energy_in_rydbergs);
energy_in_rydbergs = pow(10,log_energy+1);
log_SED_density -= 2;
output
<< "("
<< energy_in_rydbergs
<< " "
<< log_SED_density
<< ")";
}
return output.str();
}
#endif

501
src/sed/mehdipour/spectrum Normal file
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@ -0,0 +1,501 @@
0.001 1e-35
0.0010232929922807535 1e-35
0.0010471285480508996 1e-35
0.001071519305237606 1e-35
0.0010964781961431851 1e-35
0.001122018454301963 1e-35
0.0011481536214968829 1e-35
0.001174897554939529 1e-35
0.001202264434617413 1e-35
0.0012302687708123812 1e-35
0.0012589254117941675 1e-35
0.0012882495516931337 1e-35
0.0013182567385564075 1e-35
0.0013489628825916532 1e-35
0.0013803842646028853 1e-35
0.001412537544622754 1e-35
0.001445439770745928 1e-35
0.0014791083881682072 1e-35
0.0015135612484362087 1e-35
0.0015488166189124811 1e-35
0.001584893192461114 1e-35
0.0016218100973589297 1e-35
0.0016595869074375598 1e-35
0.0016982436524617442 1e-35
0.0017378008287493763 1e-35
0.0017782794100389228 1e-35
0.0018197008586099826 1e-35
0.0018620871366628676 1e-35
0.0019054607179632482 1e-35
0.0019498445997580456 1e-35
0.001995262314968879 1e-35
0.0020417379446695297 1e-35
0.0020892961308540386 1e-35
0.0021379620895022326 1e-35
0.002187761623949552 1e-35
0.00223872113856834 1e-35
0.0022908676527677724 1e-35
0.0023442288153199225 1e-35
0.00239883291901949 1e-35
0.002454708915685031 1e-35
0.0025118864315095794 1e-35
0.0025703957827688645 1e-35
0.0026302679918953813 1e-35
0.002691534803926914 1e-35
0.002754228703338166 1e-35
0.002818382931264455 1e-35
0.0028840315031266055 1e-35
0.0029512092266663842 1e-35
0.003019951720402016 1e-35
0.003090295432513592 1e-35
0.0031622776601683794 1e-35
0.003235936569296281 1e-35
0.003311311214825911 1e-35
0.0033884415613920273 1e-35
0.0034673685045253167 1e-35
0.0035481338923357532 1e-35
0.003630780547701014 1e-35
0.003715352290971728 1e-35
0.0038018939632056127 1e-35
0.003890451449942805 1e-35
0.003981071705534973 1e-35
0.004073802778041126 1e-35
0.004168693834703355 1e-35
0.004265795188015926 1e-35
0.004365158322401661 1e-35
0.0044668359215096305 1e-35
0.004570881896148752 1e-35
0.004677351412871981 1e-35
0.004786300923226385 1e-35
0.004897788193684461 1e-35
0.005011872336272725 1e-35
0.005128613839913648 1e-35
0.005248074602497723 1e-35
0.005370317963702527 1e-35
0.005495408738576248 1e-35
0.005623413251903491 1e-35
0.005754399373371567 1e-35
0.00588843655355589 1e-35
0.0060255958607435805 1e-35
0.006165950018614822 1e-35
0.00630957344480193 1e-35
0.006456542290346556 1e-35
0.006606934480075964 1e-35
0.006760829753919818 1e-35
0.006918309709189363 1e-35
0.00707945784384138 1e-35
0.007244359600749898 1e-35
0.007413102413009177 1e-35
0.007585775750291836 1e-35
0.007762471166286911 1e-35
0.007943282347242814 1e-35
0.008128305161640995 1e-35
0.008317637711026709 1e-35
0.008511380382023759 1e-35
0.008709635899560805 1e-35
0.008912509381337459 1e-35
0.009120108393559097 1e-35
0.009332543007969905 1e-35
0.009549925860214359 1e-35
0.009772372209558112 1e-35
0.01 1e-35
0.010232929922807542 1e-35
0.010471285480508996 1e-35
0.010715193052376065 1e-35
0.01096478196143185 1e-35
0.011220184543019636 1e-35
0.01148153621496883 1e-35
0.011748975549395297 1e-35
0.012022644346174132 1e-35
0.012302687708123818 1e-35
0.012589254117941675 1.3996479694365586e-35
0.012882495516931342 8.270588387595168e-35
0.013182567385564075 4.686869718494287e-34
0.01348962882591654 2.5495183758866658e-33
0.013803842646028852 1.3324555672404638e-32
0.014125375446227547 6.69650156124801e-32
0.01445439770745928 3.2390389883990527e-31
0.01479108388168208 1.5091097908171951e-30
0.01513561248436208 6.77823828047859e-30
0.01548816618912481 2.937315521425098e-29
0.015848931924611134 1.229023903677627e-28
0.0162181009735893 4.96908168781093e-28
0.016595869074375606 1.9427648570657324e-27
0.016982436524617443 7.35033495487743e-27
0.017378008287493755 2.6930458296420804e-26
0.01778279410038923 9.561578992892138e-26
0.018197008586099836 3.291978943924586e-25
0.018620871366628676 1.0997937687327044e-24
0.019054607179632473 3.567553707485399e-24
0.019498445997580455 1.1243624803203092e-23
0.0199526231496888 3.444955292838125e-23
0.020417379446695295 1.0267403190419972e-22
0.020892961308540396 2.978443886444978e-22
0.021379620895022326 8.414257076941903e-22
0.02187761623949553 2.316217559426091e-21
0.0223872113856834 6.216040568787896e-21
0.022908676527677734 1.6272230934438987e-20
0.023442288153199226 4.157203175385443e-20
0.02398832919019491 1.037033554390446e-19
0.02454708915685031 2.527160323920646e-19
0.025118864315095808 6.019034683630338e-19
0.025703957827688632 1.4017653709182508e-18
0.026302679918953815 3.1935479048228853e-18
0.026915348039269153 7.120513330808699e-18
0.02754228703338166 1.5544405019374462e-17
0.028183829312644536 3.323855537770272e-17
0.028840315031266057 6.964516155528575e-17
0.029512092266663854 1.4305116343583793e-16
0.03019951720402016 2.881441107018318e-16
0.030902954325135904 5.693873153980269e-16
0.03162277660168379 1.1041876398087576e-15
0.03235936569296283 2.1021711242266972e-15
0.03311311214825911 3.930358212034185e-15
0.033884415613920256 7.219044298575817e-15
0.034673685045253165 1.3030207068668043e-14
0.03548133892335755 2.311976844535101e-14
0.03630780547701014 4.033748022821911e-14
0.03715352290971726 6.922386914347113e-14
0.038018939632056124 1.1688255134455832e-13
0.03890451449942807 1.942277841488844e-13
0.039810717055349734 3.177301022377131e-13
0.04073802778041128 5.118050485325646e-13
0.04168693834703355 8.120079354581276e-13
0.04265795188015928 1.2692065385883532e-12
0.04365158322401661 1.9548976487697138e-12
0.04466835921509633 2.967805516254491e-12
0.04570881896148752 4.441843010381999e-12
0.046773514128719836 6.555422864803426e-12
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