R/DVCS_data_import.R
In rcarcasses/HQCD-P: An R package for the Holographic Pomeron
Defines functions
loadData.DVCSSigma
# load all the data and put it in the proper format
#' @export
loadData.DVCSSigma <- function(dvcs) {
# This function creates vectors with the values of W, Q2, sigma and deltaSigma
# of the data used by Marko in his DVCS paper with Miguel
# Getting data from 761990 folder
# Getting data from Table1.csv file
W <- c(82, 82, 82, 82) # W = sqrt(s) and |t| < 1
Q2 <- c(8.75, 15.5, 25.0, 55.0) # Q2 is in GeV**2
sigma <- c(3.59, 1.38, 0.58, 0.13) # sigma is in NB
# Summing the square of statistical and systematic errors assuming they are independent
deltaSigma <- c(sqrt(0.21*0.21+0.41*0.41), sqrt(0.1*0.1+0.21+0.21), sqrt(0.09*0.09+0.09*0.09), sqrt(0.03*0.03+0.04*0.04))
# Getting data from Table2.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0))
sigma <- c(sigma, c(2.91, 3.96, 4.78, 5.55, 6.56))
deltaSigma <- c(deltaSigma, c(sqrt(0.2*0.2+0.25*0.25), sqrt(0.32*0.32+0.37*0.37), sqrt(0.41**2+0.57**2), sqrt(0.57**2+0.88**2), sqrt(1.17**2+1.77**2)))
# Getting data from Table3.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0, 45.0, 70.0, 90.0, 110.0, 130.0, 45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0, 15.5, 15.5, 15.5, 15.5, 15.5, 25.0, 25.0, 25.0, 25.0, 25.0))
sigma <- c(sigma, c(2.6, 3.15, 5.25, 5.11, 5.88, 0.94, 1.54, 0.95, 1.69, 2.06, 0.35, 0.36, 0.83, 0.9, 0.9))
deltaSigma <- c(deltaSigma, c(sqrt(0.24**2+0.24**2), sqrt(0.4**2+0.33**2), sqrt(0.55**2+0.55**2), sqrt(0.71**2+0.76**2), sqrt(1.89**2+1.26**2)))
deltaSigma <- c(deltaSigma, c(sqrt(0.1**2+0.1**2), sqrt(0.17**2+0.14**2), sqrt(0.2**2+0.17**2), sqrt(0.31**2+0.33**2), sqrt(0.51**2+0.56**2)))
deltaSigma <- c(deltaSigma, c(sqrt(0.13**2+0.07**2), sqrt(0.1**2+0.05**2), sqrt(0.18**2+0.09**2), sqrt(0.23**2+0.18**2), sqrt(0.36**2+0.32**2)))
# Getting data from 805219 folder
# Getting data from Table1.csv file
W <- c(W, c(104.0, 104.0, 104.0, 104.0, 104.0, 104.0))
Q2 <- c(Q2, c(3.25, 7.5, 12.5, 20.0, 32.5, 70.0))
sigma <- c(sigma, c(21.28, 5.87, 3.27, 1.23, 0.55, 0.16))
deltaSigma <- c(deltaSigma, c(sqrt(0.92**2+max(1.02, 1.34)**2), sqrt(0.42**+max(0.14, 0.3)**2), sqrt(0.33**2+max(0.07, 0.16)**2), sqrt(0.21**2+max(0.05, 0.08)**2), sqrt(0.18**2+0.04**2), sqrt(0.07**2+0.02**2)))
# Gettind data from Table2.csv file
W <- c(W, c(50.0, 70.0, 90.0, 110.0, 130.0, 155.0))
Q2 <- c(Q2, c(3.2, 3.2, 3.2, 3.2, 3.2, 3.2))
sigma <- c(sigma, c(14.47, 20.38, 17.95, 20.65, 26.42, 27.6))
deltaSigma <- c(deltaSigma, c(sqrt(1.05**2+max(0.5, 0.88)**2), sqrt(1.57**2+max(1.01, 1.99)**2), sqrt(1.35**2+max(0.64, 0.93)**2), sqrt(1.26**2+max(0.59, 1.16)**2), sqrt(1.84**2+max(0.79, 0.88)**2), sqrt(3.74**2+max(2.01, 3.34)**2)))
# Getting data from Table3.csv file
W <- c(W, c(52.5, 77.5, 102.5, 127.5, 155.0))
Q2 <- c(Q2, c(2.4, 2.4, 2.4, 2.4, 2.4))
sigma <- c(sigma, c(27.06, 22.36, 26.49, 35.94, 35.72))
deltaSigma <- c(deltaSigma, c(sqrt(3.44**2+max(4.37, 4.42)**2), sqrt(3.11**2+max(3.4, 1.73)**2), sqrt(1.89**2+max(0.89, 1.44)**2), sqrt(2.63**2+max(1.81, 1.89)**2), sqrt(9.47**2+max(3.01, 2.94)**2)))
W <- c(W, c(155.0, 155.0, 155.0))
Q2 <- c(Q2, c(6.2, 9.9, 18.0))
sigma <- c(sigma, c(16.93, 6.15, 2.21))
deltaSigma <- c(deltaSigma, c(sqrt(2.43**2+max(1.37, 1.4)**2), sqrt(1.67**2+0.51**2), sqrt(0.82**2+0.18**2)))
# Getting data from 827347 folder
# Getting data from Table1.csv file
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(8.75, 15.5, 25.0, 55.0))
sigma <- c(sigma, c(3.87, 1.46, 0.55, 0.16))
deltaSigma <- c(deltaSigma, c(sqrt(0.15**2+0.41**2), sqrt(0.07**2+0.18**2), sqrt(0.07**2+0.08**2), sqrt(0.02**2+0.03)))
# Getting data from Table2.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(10.0, 10., 10., 10., 10.))
sigma <- c(sigma, c(2.23, 2.92, 3.63, 3.71, 4.37))
deltaSigma <- c(deltaSigma, c(sqrt(0.11**2+0.19**2), sqrt(0.16**2+0.27**2), sqrt(0.22**2+0.4**2), sqrt(0.29**2+0.61**2), sqrt(0.6**2+1.16**2)))
# Getting data from Table3.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0))
sigma <- c(sigma, c(3.06, 3.54, 4.93, 5.16, 5.62))
deltaSigma <- c(deltaSigma, c(sqrt(0.18**2+0.25**2), sqrt(0.29**2+0.34**2), sqrt(0.39**2+0.52**2), sqrt(0.51**2+0.74**2), sqrt(1.34**2+1.19**2)))
data.frame(Q2, W, sigma, deltaSigma)
}
#' @export
loadData.DVCSDSigma <- function(dvcs) {
# This function creates vectors with the values of W, Q2, dsigma and deltaSigma
# of the data used by Marko in his DVCS paper with Miguel
# Getting data from 761990 folder
# Getting data from Table4.csv
W <- c(82.0, 82.0, 82.0, 82.0)
Q2 <- c(8.0, 8.0, 8.0, 8.0)
t <- c(0.1, 0.3, 0.5, 0.8)
dsigma <- c(13.1, 4.69, 1.37, 0.19)
deltaDSigma <- c(sqrt(1.1**2+1.85**2), sqrt(0.45**2+0.55**2), sqrt(0.21**2+0.23**2), sqrt(0.04**2+0.06**2))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(15.5, 15.5, 15.5, 15.5))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.37, 1.02, 0.49, 0.12))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.47**2+0.86**2), sqrt(0.16**2+0.18**2), sqrt(0.08**2+0.08**2), sqrt(0.02**2+0.02**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(25., 25., 25., 25.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.41, 0.71, 0.28, 0.04))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.4**2+0.43**2), sqrt(0.16**2+0.08**2), sqrt(0.07**2+0.04**2), sqrt(0.01**2+0.02**2)))
# Getting data from Table5.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.99, 1.45, 0.49, 0.12))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.66**2+0.54**2), sqrt(0.29**2+0.18**2), sqrt(0.14**2+0.08**2), sqrt(0.03**2+0.03**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(7.78, 2.74, 0.81, 0.19))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.69**2+0.87**2), sqrt(0.31**2+0.3**2), sqrt(0.14**2+0.11**2), sqrt(0.03**2+0.03**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(10.9, 3.47, 1.49, 0.19))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.14**2+2.36**2), sqrt(0.42**2+0.53**2), sqrt(0.21**2+0.24**2), sqrt(0.04**2+0.06**2)))
# Getting data from Table8.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(8.1, 2.3, 0.45, 0.16))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.22**2+0.82**2), sqrt(0.54**2+0.28**2), sqrt(0.22**2+0.1**2), sqrt(0.06**2+0.03**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(10.0, 4.35, 1.08, 0.13))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.3**2+1.27**2), sqrt(0.63**2+0.46**2), sqrt(0.27**2+0.17**2), sqrt(0.06**2+0.04**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(16.0, 5.45, 1.96, 0.21))
deltaDSigma <- c(deltaDSigma, c(sqrt(2.11**2+2.74**2), sqrt(0.8**2+0.73**2), sqrt(0.41**2+0.35**2), sqrt(0.09**2+0.08**2)))
# Getting data from Table9.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.06, 0.33, 0.22, 0.04))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.28**2+0.28**2), sqrt(0.07**2+0.07**2), sqrt(0.06**2+0.06**2), sqrt(0.01**2+0.01**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(2.38, 0.67, 0.24, 0.07))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.29**2+0.26**2), sqrt(0.12**2+0.07**2), sqrt(0.05**2+0.03**2), sqrt(0.01**2+0.02**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(2.98, 0.89, 0.44, 0.06))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.49**2+0.85**2), sqrt(0.17**2+0.17**2), sqrt(0.08**2+0.08**2), sqrt(0.02**2+0.02**2)))
# Getting data from 805219 folder
# Getting data from Table4.csv file
W <- c(W, c(104.0, 104.0, 104.0, 104.0))
Q2 <- c(Q2, c(3.2, 3.2, 3.2, 3.2))
t <- c(t, c(0.14, 0.25, 0.36, 0.47))
dsigma <- c(dsigma, c(34.6, 32.7, 19.6, 5.7))
deltaDSigma <- c(deltaDSigma, c(sqrt(9.6**2+2.4**2), sqrt(9.4**2+2.3**2), sqrt(7.5**2+1.4**2), sqrt(4.1**2+0.4**2)))
# Getting data from 827347 folder
# Getting data from Table4.csv file
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(13.3, 4.82, 1.26, 0.21))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.8**2+1.73**2), sqrt(0.32**2+0.5**2), sqrt(0.14**2+0.18**2), sqrt(0.03**2+0.04**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(15.5, 15.5, 15.5, 15.5))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.33, 1.24, 0.45, 0.1))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.35**2+0.65**2), sqrt(0.13**2+0.16**2), sqrt(0.06**2+0.05**2), sqrt(0.01**2+0.02**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(25.0, 25.0, 25.0, 25.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.68, 0.49, 0.18, 0.05))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.31**2+0.42**2), sqrt(0.1**2+0.08**2), sqrt(0.04**2+0.03**2), sqrt(0.01**2+0.01**2)))
# Getting data from Table5.csv file
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.77, 1.62, 0.69, 0.1))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.5**2+0.49**2), sqrt(0.23**2+0.18**2), sqrt(0.11**2+0.07**2), sqrt(0.02**2+0.01**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(7.81, 2.88, 0.91, 0.16))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.51**2+0.85**2), sqrt(0.22**2+0.28**2), sqrt(0.1**2+0.1**2), sqrt(0.02**2+0.02**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(11., 3.71, 1.18, 0.24))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.85**2+2.23**2), sqrt(0.31**2+0.49**2), sqrt(0.13**2+0.16**2), sqrt(0.03**2+0.04**2)))
data.frame(Q2, W, t = -t, dsigma, deltaDSigma)
}
rcarcasses/HQCD-P documentation built on May 7, 2019, 9:33 a.m.
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Defines functions loadData.DVCSSigma
# load all the data and put it in the proper format
#' @export
loadData.DVCSSigma <- function(dvcs) {
# This function creates vectors with the values of W, Q2, sigma and deltaSigma
# of the data used by Marko in his DVCS paper with Miguel
# Getting data from 761990 folder
# Getting data from Table1.csv file
W <- c(82, 82, 82, 82) # W = sqrt(s) and |t| < 1
Q2 <- c(8.75, 15.5, 25.0, 55.0) # Q2 is in GeV**2
sigma <- c(3.59, 1.38, 0.58, 0.13) # sigma is in NB
# Summing the square of statistical and systematic errors assuming they are independent
deltaSigma <- c(sqrt(0.21*0.21+0.41*0.41), sqrt(0.1*0.1+0.21+0.21), sqrt(0.09*0.09+0.09*0.09), sqrt(0.03*0.03+0.04*0.04))
# Getting data from Table2.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0))
sigma <- c(sigma, c(2.91, 3.96, 4.78, 5.55, 6.56))
deltaSigma <- c(deltaSigma, c(sqrt(0.2*0.2+0.25*0.25), sqrt(0.32*0.32+0.37*0.37), sqrt(0.41**2+0.57**2), sqrt(0.57**2+0.88**2), sqrt(1.17**2+1.77**2)))
# Getting data from Table3.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0, 45.0, 70.0, 90.0, 110.0, 130.0, 45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0, 15.5, 15.5, 15.5, 15.5, 15.5, 25.0, 25.0, 25.0, 25.0, 25.0))
sigma <- c(sigma, c(2.6, 3.15, 5.25, 5.11, 5.88, 0.94, 1.54, 0.95, 1.69, 2.06, 0.35, 0.36, 0.83, 0.9, 0.9))
deltaSigma <- c(deltaSigma, c(sqrt(0.24**2+0.24**2), sqrt(0.4**2+0.33**2), sqrt(0.55**2+0.55**2), sqrt(0.71**2+0.76**2), sqrt(1.89**2+1.26**2)))
deltaSigma <- c(deltaSigma, c(sqrt(0.1**2+0.1**2), sqrt(0.17**2+0.14**2), sqrt(0.2**2+0.17**2), sqrt(0.31**2+0.33**2), sqrt(0.51**2+0.56**2)))
deltaSigma <- c(deltaSigma, c(sqrt(0.13**2+0.07**2), sqrt(0.1**2+0.05**2), sqrt(0.18**2+0.09**2), sqrt(0.23**2+0.18**2), sqrt(0.36**2+0.32**2)))
# Getting data from 805219 folder
# Getting data from Table1.csv file
W <- c(W, c(104.0, 104.0, 104.0, 104.0, 104.0, 104.0))
Q2 <- c(Q2, c(3.25, 7.5, 12.5, 20.0, 32.5, 70.0))
sigma <- c(sigma, c(21.28, 5.87, 3.27, 1.23, 0.55, 0.16))
deltaSigma <- c(deltaSigma, c(sqrt(0.92**2+max(1.02, 1.34)**2), sqrt(0.42**+max(0.14, 0.3)**2), sqrt(0.33**2+max(0.07, 0.16)**2), sqrt(0.21**2+max(0.05, 0.08)**2), sqrt(0.18**2+0.04**2), sqrt(0.07**2+0.02**2)))
# Gettind data from Table2.csv file
W <- c(W, c(50.0, 70.0, 90.0, 110.0, 130.0, 155.0))
Q2 <- c(Q2, c(3.2, 3.2, 3.2, 3.2, 3.2, 3.2))
sigma <- c(sigma, c(14.47, 20.38, 17.95, 20.65, 26.42, 27.6))
deltaSigma <- c(deltaSigma, c(sqrt(1.05**2+max(0.5, 0.88)**2), sqrt(1.57**2+max(1.01, 1.99)**2), sqrt(1.35**2+max(0.64, 0.93)**2), sqrt(1.26**2+max(0.59, 1.16)**2), sqrt(1.84**2+max(0.79, 0.88)**2), sqrt(3.74**2+max(2.01, 3.34)**2)))
# Getting data from Table3.csv file
W <- c(W, c(52.5, 77.5, 102.5, 127.5, 155.0))
Q2 <- c(Q2, c(2.4, 2.4, 2.4, 2.4, 2.4))
sigma <- c(sigma, c(27.06, 22.36, 26.49, 35.94, 35.72))
deltaSigma <- c(deltaSigma, c(sqrt(3.44**2+max(4.37, 4.42)**2), sqrt(3.11**2+max(3.4, 1.73)**2), sqrt(1.89**2+max(0.89, 1.44)**2), sqrt(2.63**2+max(1.81, 1.89)**2), sqrt(9.47**2+max(3.01, 2.94)**2)))
W <- c(W, c(155.0, 155.0, 155.0))
Q2 <- c(Q2, c(6.2, 9.9, 18.0))
sigma <- c(sigma, c(16.93, 6.15, 2.21))
deltaSigma <- c(deltaSigma, c(sqrt(2.43**2+max(1.37, 1.4)**2), sqrt(1.67**2+0.51**2), sqrt(0.82**2+0.18**2)))
# Getting data from 827347 folder
# Getting data from Table1.csv file
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(8.75, 15.5, 25.0, 55.0))
sigma <- c(sigma, c(3.87, 1.46, 0.55, 0.16))
deltaSigma <- c(deltaSigma, c(sqrt(0.15**2+0.41**2), sqrt(0.07**2+0.18**2), sqrt(0.07**2+0.08**2), sqrt(0.02**2+0.03)))
# Getting data from Table2.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(10.0, 10., 10., 10., 10.))
sigma <- c(sigma, c(2.23, 2.92, 3.63, 3.71, 4.37))
deltaSigma <- c(deltaSigma, c(sqrt(0.11**2+0.19**2), sqrt(0.16**2+0.27**2), sqrt(0.22**2+0.4**2), sqrt(0.29**2+0.61**2), sqrt(0.6**2+1.16**2)))
# Getting data from Table3.csv file
W <- c(W, c(45.0, 70.0, 90.0, 110.0, 130.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0, 8.0))
sigma <- c(sigma, c(3.06, 3.54, 4.93, 5.16, 5.62))
deltaSigma <- c(deltaSigma, c(sqrt(0.18**2+0.25**2), sqrt(0.29**2+0.34**2), sqrt(0.39**2+0.52**2), sqrt(0.51**2+0.74**2), sqrt(1.34**2+1.19**2)))
data.frame(Q2, W, sigma, deltaSigma)
}
#' @export
loadData.DVCSDSigma <- function(dvcs) {
# This function creates vectors with the values of W, Q2, dsigma and deltaSigma
# of the data used by Marko in his DVCS paper with Miguel
# Getting data from 761990 folder
# Getting data from Table4.csv
W <- c(82.0, 82.0, 82.0, 82.0)
Q2 <- c(8.0, 8.0, 8.0, 8.0)
t <- c(0.1, 0.3, 0.5, 0.8)
dsigma <- c(13.1, 4.69, 1.37, 0.19)
deltaDSigma <- c(sqrt(1.1**2+1.85**2), sqrt(0.45**2+0.55**2), sqrt(0.21**2+0.23**2), sqrt(0.04**2+0.06**2))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(15.5, 15.5, 15.5, 15.5))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.37, 1.02, 0.49, 0.12))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.47**2+0.86**2), sqrt(0.16**2+0.18**2), sqrt(0.08**2+0.08**2), sqrt(0.02**2+0.02**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(25., 25., 25., 25.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.41, 0.71, 0.28, 0.04))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.4**2+0.43**2), sqrt(0.16**2+0.08**2), sqrt(0.07**2+0.04**2), sqrt(0.01**2+0.02**2)))
# Getting data from Table5.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.99, 1.45, 0.49, 0.12))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.66**2+0.54**2), sqrt(0.29**2+0.18**2), sqrt(0.14**2+0.08**2), sqrt(0.03**2+0.03**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(7.78, 2.74, 0.81, 0.19))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.69**2+0.87**2), sqrt(0.31**2+0.3**2), sqrt(0.14**2+0.11**2), sqrt(0.03**2+0.03**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(10., 10., 10., 10.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(10.9, 3.47, 1.49, 0.19))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.14**2+2.36**2), sqrt(0.42**2+0.53**2), sqrt(0.21**2+0.24**2), sqrt(0.04**2+0.06**2)))
# Getting data from Table8.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(8.1, 2.3, 0.45, 0.16))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.22**2+0.82**2), sqrt(0.54**2+0.28**2), sqrt(0.22**2+0.1**2), sqrt(0.06**2+0.03**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(10.0, 4.35, 1.08, 0.13))
deltaDSigma <- c(deltaDSigma, c(sqrt(1.3**2+1.27**2), sqrt(0.63**2+0.46**2), sqrt(0.27**2+0.17**2), sqrt(0.06**2+0.04**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(8., 8., 8., 8.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(16.0, 5.45, 1.96, 0.21))
deltaDSigma <- c(deltaDSigma, c(sqrt(2.11**2+2.74**2), sqrt(0.8**2+0.73**2), sqrt(0.41**2+0.35**2), sqrt(0.09**2+0.08**2)))
# Getting data from Table9.csv
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.06, 0.33, 0.22, 0.04))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.28**2+0.28**2), sqrt(0.07**2+0.07**2), sqrt(0.06**2+0.06**2), sqrt(0.01**2+0.01**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(2.38, 0.67, 0.24, 0.07))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.29**2+0.26**2), sqrt(0.12**2+0.07**2), sqrt(0.05**2+0.03**2), sqrt(0.01**2+0.02**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(20., 20., 20., 20.))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(2.98, 0.89, 0.44, 0.06))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.49**2+0.85**2), sqrt(0.17**2+0.17**2), sqrt(0.08**2+0.08**2), sqrt(0.02**2+0.02**2)))
# Getting data from 805219 folder
# Getting data from Table4.csv file
W <- c(W, c(104.0, 104.0, 104.0, 104.0))
Q2 <- c(Q2, c(3.2, 3.2, 3.2, 3.2))
t <- c(t, c(0.14, 0.25, 0.36, 0.47))
dsigma <- c(dsigma, c(34.6, 32.7, 19.6, 5.7))
deltaDSigma <- c(deltaDSigma, c(sqrt(9.6**2+2.4**2), sqrt(9.4**2+2.3**2), sqrt(7.5**2+1.4**2), sqrt(4.1**2+0.4**2)))
# Getting data from 827347 folder
# Getting data from Table4.csv file
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(8.0, 8.0, 8.0, 8.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(13.3, 4.82, 1.26, 0.21))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.8**2+1.73**2), sqrt(0.32**2+0.5**2), sqrt(0.14**2+0.18**2), sqrt(0.03**2+0.04**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(15.5, 15.5, 15.5, 15.5))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.33, 1.24, 0.45, 0.1))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.35**2+0.65**2), sqrt(0.13**2+0.16**2), sqrt(0.06**2+0.05**2), sqrt(0.01**2+0.02**2)))
W <- c(W, c(82.0, 82.0, 82.0, 82.0))
Q2 <- c(Q2, c(25.0, 25.0, 25.0, 25.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(1.68, 0.49, 0.18, 0.05))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.31**2+0.42**2), sqrt(0.1**2+0.08**2), sqrt(0.04**2+0.03**2), sqrt(0.01**2+0.01**2)))
# Getting data from Table5.csv file
W <- c(W, c(40.0, 40.0, 40.0, 40.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(4.77, 1.62, 0.69, 0.1))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.5**2+0.49**2), sqrt(0.23**2+0.18**2), sqrt(0.11**2+0.07**2), sqrt(0.02**2+0.01**2)))
W <- c(W, c(70.0, 70.0, 70.0, 70.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(7.81, 2.88, 0.91, 0.16))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.51**2+0.85**2), sqrt(0.22**2+0.28**2), sqrt(0.1**2+0.1**2), sqrt(0.02**2+0.02**2)))
W <- c(W, c(100.0, 100.0, 100.0, 100.0))
Q2 <- c(Q2, c(10.0, 10.0, 10.0, 10.0))
t <- c(t, c(0.1, 0.3, 0.5, 0.8))
dsigma <- c(dsigma, c(11., 3.71, 1.18, 0.24))
deltaDSigma <- c(deltaDSigma, c(sqrt(0.85**2+2.23**2), sqrt(0.31**2+0.49**2), sqrt(0.13**2+0.16**2), sqrt(0.03**2+0.04**2)))
data.frame(Q2, W, t = -t, dsigma, deltaDSigma)
}
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