env <- new.env()
load("../data.rda", envir = env)
This example is not computationally interesting, but I present a brute force way of depicting the representations in R, given the relevant information provided on page 683.
curve(dnorm(x, mean = 58, sd = 4), 40, 110, ylim = c(0, .2), xlab = "", ylab = "", col = "green")
text(58, .11, "Type 2", cex = .75)
curve(dnorm(x, mean = 70, sd = 4), add = TRUE, col = "blue")
text(70, .11, "Type 1", cex = .75)
curve(dnorm(x, mean = 84, sd = 4), add = TRUE, col = "red")
text(84, .11, "Type 4", cex = .75)
curve(dnorm(x, mean = 90, sd = 4), add = TRUE)
text(90, .11, "Type 3", cex = .75)
points(c(51, 78), c(0, 0), pch = 19)
df <- get("CH16TA01", envir = env)
names(df) <- c("y", "x1", "x2")
One may be tempted to use xtabs and addmargins to accomplish a similar table, but there are 2 problems with this. First, the sums of package sums or the means of package means, cannot be calculated in addmargins and requires processing the resultant margin table. Second, xtabs automatically fills the non-combination as 0. This posses problems for the means.
Regardless, getting an accurate count requires a little trickery. The reason is that the use of length will recognize NA or 0 as a record in the count. Instead, if you have NA you can say sum(!is.na(x)) to boolean (unit) sum all the non-NA values. In a similar fashion below, we simply boolean sum the values that are nonzero. The rest are processed using tapply, which is the preferred vector way of handling grouped operations. There is also by that is more flexible in that it can handle non-vector (data frame) objects.
cbind('Table' = addmargins(xtabs(y ~ x1 + x2, df), 2),
'Mean' = tapply(df$y, df$x1, mean),
'n' = tapply(df$y, df$x1, function(r) sum(r > 0)))
## 1 2 3 4 5 Sum Mean n
## 1 11 17 16 14 15 73 14.6 5
## 2 12 10 15 19 11 67 13.4 5
## 3 23 20 18 17 0 78 19.5 4
## 4 27 33 22 26 28 136 27.2 5
with(df, c("Y.." = sum(tapply(y, x1, sum)),
"Ybar." = mean(tapply(y, x1, mean)),
"n.." = sum(tapply(y, x1, function(r) sum(r > 0)))))
## Y.. Ybar. n..
## 354.00 18.68 19.00
Since the last chapter demonstrated how convoluted it can become to plot some of these diagrams, we shall make use of xyplot (lattice) to simply our results. Though, as shown below, it can be convoluted to properly specify xyplot parameters, too!
In this example, we make use of RColorBrewer to get good color combinations. The function brewer.pal takes in the number of categories and color palette you want. See the Color Brewer website for examples (generally associated with choropleth mapping).
Note, the coloring isn't important for this analysis because we're not looking at the within-subject (store) variability, but if we were, we would want to see how they change, and maybe even plot the connecting lines as in the examples in Chapter 15. An alternative here would be to use ggplot (ggplot2). It has a lot of parameters, but a far superior semantics in controlling your plotting objects and how you specify parameters. For instance, a simple version of this plot would be the following.
ggplot(df, aes(factor(x1), y)) + geom_point()
library(lattice)
library(RColorBrewer)
pal <- brewer.pal(5, "Set1")
xyplot(y ~ factor(x1), df, groups = x2, auto.key = list(columns = 5),
par.settings = simpleTheme(col = pal, pch = 19),
xlab = "Package Design", ylab = "Cases Sold", main = "Summary Plot")
Since all that is really going on in this manual calculation is to take the difference of the value from its mean (centering) for a given group, we can use tapply or by on the response, splitting it by the factor and using scale to center the group. For convenience, we'll simply append these residuals to the data frame to make a table.
df <- transform(df, u = unlist(tapply(y, x1, scale, scale = FALSE)))
addmargins(xtabs(u ~ x1 + x2, df, sparse = TRUE), 2) # Their sums are as 0 as it gets in R.
## 1 2 3 4 5 Sum
## 1 -3.6 2.4 1.4 -0.6 0.4 1.776e-15
## 2 -1.4 -3.4 1.6 5.6 -2.4 -1.776e-15
## 3 3.5 0.5 -1.5 -2.5 0.0 0.000e+00
## 4 -0.2 5.8 -5.2 -1.2 0.8 3.553e-15
Note that “Root Mean Square Error” is just the “Residual Standard Error” in the aov output. Also, “C. Total” is just the aggregate.
Included here are examples of the aov object which encodes the same information. The utility of aov comes out when you need to use different error structures. In this case, just using lm and anova on such an object is congruent to using aov and summary.lm on such an object–i.e., summary on an aov is the same as anova on an lm object and summary.lm on an aov is the same as summary on an lm object.
df <- transform(df, x1 = factor(x1))
fit <- lm(y ~ x1 - 1, df) # This is the cell means model
anova(fit)
## Analysis of Variance Table
##
## Response: y
## Df Sum Sq Mean Sq F value Pr(>F)
## x1 4 7184 1796 170 2.6e-12 ***
## Residuals 15 158 11
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(aov(y ~ factor(x1) - 1, df)) # Same as anova(fit)
## Df Sum Sq Mean Sq F value Pr(>F)
## factor(x1) 4 7184 1796 170 2.6e-12 ***
## Residuals 15 158 11
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(fit) # Notice that the coefficients are just the group means
##
## Call:
## lm(formula = y ~ x1 - 1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.20 -1.95 -0.20 1.50 5.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## x11 14.60 1.45 10.05 4.7e-08 ***
## x12 13.40 1.45 9.23 1.4e-07 ***
## x13 19.50 1.62 12.01 4.3e-09 ***
## x14 27.20 1.45 18.73 8.2e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.25 on 15 degrees of freedom
## Multiple R-squared: 0.978, Adjusted R-squared: 0.973
## F-statistic: 170 on 4 and 15 DF, p-value: 2.64e-12
summary.lm(aov(fit)) # Same as summary(fit)
##
## Call:
## aov(formula = fit)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.20 -1.95 -0.20 1.50 5.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## x11 14.60 1.45 10.05 4.7e-08 ***
## x12 13.40 1.45 9.23 1.4e-07 ***
## x13 19.50 1.62 12.01 4.3e-09 ***
## x14 27.20 1.45 18.73 8.2e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.25 on 15 degrees of freedom
## Multiple R-squared: 0.978, Adjusted R-squared: 0.973
## F-statistic: 170 on 4 and 15 DF, p-value: 2.64e-12
confint(fit)
## 2.5 % 97.5 %
## x11 11.50 17.70
## x12 10.30 16.50
## x13 16.04 22.96
## x14 24.10 30.30
summary(fit)$f[1] <= qf(1-.05, 4-1, 19-4) # F-test; Conclude H0?
## value
## FALSE
In the next chapter, this will be recognized as defining contrasts (here defined on page 708). In R, you can define a matrix for that contrast and set it up as the contrast to use when you do your linear fit. In this way, the linear model will contain the comparison information you want. Since this would otherwise be a tedious task of recoding variables to run a regression on them, I'll leave that as an exercise to the interested reader.
# ANOVA as Regression Model (16.79)
contrasts(df$x1) <- matrix(c(1, 0, 0, -1, 0, 1, 0, -1, 0, 0, 1, -1), 4, 3)
fit <- lm(y ~ x1, df)
model.matrix(fit)
## (Intercept) x11 x12 x13
## 11 1 1 0 0
## 12 1 1 0 0
## 13 1 1 0 0
## 14 1 1 0 0
## 15 1 1 0 0
## 21 1 0 1 0
## 22 1 0 1 0
## 23 1 0 1 0
## 24 1 0 1 0
## 25 1 0 1 0
## 31 1 0 0 1
## 32 1 0 0 1
## 33 1 0 0 1
## 34 1 0 0 1
## 41 1 -1 -1 -1
## 42 1 -1 -1 -1
## 43 1 -1 -1 -1
## 44 1 -1 -1 -1
## 45 1 -1 -1 -1
## attr(,"assign")
## [1] 0 1 1 1
## attr(,"contrasts")
## attr(,"contrasts")$x1
## [,1] [,2] [,3]
## 1 1 0 0
## 2 0 1 0
## 3 0 0 1
## 4 -1 -1 -1
summary(fit)
##
## Call:
## lm(formula = y ~ x1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.20 -1.95 -0.20 1.50 5.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.675 0.749 24.95 1.3e-13 ***
## x11 -4.075 1.271 -3.21 0.00588 **
## x12 -5.275 1.271 -4.15 0.00085 ***
## x13 0.825 1.371 0.60 0.55622
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.25 on 15 degrees of freedom
## Multiple R-squared: 0.788, Adjusted R-squared: 0.746
## F-statistic: 18.6 on 3 and 15 DF, p-value: 2.58e-05
anova(fit)
## Analysis of Variance Table
##
## Response: y
## Df Sum Sq Mean Sq F value Pr(>F)
## x1 3 588 196.1 18.6 2.6e-05 ***
## Residuals 15 158 10.5
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# ANOVA as Factor Effects Model with Weighted Means (16.82)
contrasts(df$x1) <- matrix(c(1, 0, 0, -1, 0, 1, 0, -1, 0, 0, 1, -0.8), 4, 3)
fit <- lm(y ~ x1, df)
model.matrix(fit)
## (Intercept) x11 x12 x13
## 11 1 1 0 0.0
## 12 1 1 0 0.0
## 13 1 1 0 0.0
## 14 1 1 0 0.0
## 15 1 1 0 0.0
## 21 1 0 1 0.0
## 22 1 0 1 0.0
## 23 1 0 1 0.0
## 24 1 0 1 0.0
## 25 1 0 1 0.0
## 31 1 0 0 1.0
## 32 1 0 0 1.0
## 33 1 0 0 1.0
## 34 1 0 0 1.0
## 41 1 -1 -1 -0.8
## 42 1 -1 -1 -0.8
## 43 1 -1 -1 -0.8
## 44 1 -1 -1 -0.8
## 45 1 -1 -1 -0.8
## attr(,"assign")
## [1] 0 1 1 1
## attr(,"contrasts")
## attr(,"contrasts")$x1
## [,1] [,2] [,3]
## 1 1 0 0.0
## 2 0 1 0.0
## 3 0 0 1.0
## 4 -1 -1 -0.8
summary(fit)
##
## Call:
## lm(formula = y ~ x1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.20 -1.95 -0.20 1.50 5.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.632 0.745 25.01 1.2e-13 ***
## x11 -4.032 1.247 -3.23 0.00556 **
## x12 -5.232 1.247 -4.20 0.00078 ***
## x13 0.868 1.443 0.60 0.55622
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.25 on 15 degrees of freedom
## Multiple R-squared: 0.788, Adjusted R-squared: 0.746
## F-statistic: 18.6 on 3 and 15 DF, p-value: 2.58e-05
anova(fit)
## Analysis of Variance Table
##
## Response: y
## Df Sum Sq Mean Sq F value Pr(>F)
## x1 3 588 196.1 18.6 2.6e-05 ***
## Residuals 15 158 10.5
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# ANOVA as Cell Means Model (16.85)
contrasts(df$x1) <- matrix(c(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1), 4, 4)
fit <- lm(y ~ x1 - 1, df) # This is the original model fitted
model.matrix(fit)
## x11 x12 x13 x14
## 11 1 0 0 0
## 12 1 0 0 0
## 13 1 0 0 0
## 14 1 0 0 0
## 15 1 0 0 0
## 21 0 1 0 0
## 22 0 1 0 0
## 23 0 1 0 0
## 24 0 1 0 0
## 25 0 1 0 0
## 31 0 0 1 0
## 32 0 0 1 0
## 33 0 0 1 0
## 34 0 0 1 0
## 41 0 0 0 1
## 42 0 0 0 1
## 43 0 0 0 1
## 44 0 0 0 1
## 45 0 0 0 1
## attr(,"assign")
## [1] 1 1 1 1
## attr(,"contrasts")
## attr(,"contrasts")$x1
## [,1] [,2] [,3]
## 1 1 0 0
## 2 0 1 0
## 3 0 0 1
## 4 0 0 0
summary(fit)
##
## Call:
## lm(formula = y ~ x1 - 1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.20 -1.95 -0.20 1.50 5.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## x11 14.60 1.45 10.05 4.7e-08 ***
## x12 13.40 1.45 9.23 1.4e-07 ***
## x13 19.50 1.62 12.01 4.3e-09 ***
## x14 27.20 1.45 18.73 8.2e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.25 on 15 degrees of freedom
## Multiple R-squared: 0.978, Adjusted R-squared: 0.973
## F-statistic: 170 on 4 and 15 DF, p-value: 2.64e-12
anova(fit)
## Analysis of Variance Table
##
## Response: y
## Df Sum Sq Mean Sq F value Pr(>F)
## x1 4 7184 1796 170 2.6e-12 ***
## Residuals 15 158 11
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Since there is no algorithm to compute this example we had to devise one. It should come as rather straight-forward. The Xi's are as in the above examples. The 'y' will hold the 1,680 cases of 9-sequences consisting of the response variables. The 'ti' implies the treatment group. In this case t1 is the first group (3-sequence) and t12 is the composite of t1 and t2. The 'remainder' function is a wrapper for grabing a subset of 'set' based on those values not in 'x'. The 'seq6' is the 6-sequence remainder after t1 is defined. The whole process took less than 10 seconds on a 2.4 GHz processor. As for the output, the columns are arbitrarily labeled 1-9. Clearly they represent the three treatment groups based on groups of three. The function 'f' uses the matrix algebra discussed in Ch. 5. It is possible to get away with merely fitting an 'lm' object, and then extract the f-statistic in a single call. However, this requires a lot of additional work for each of the 1680 rows. That approach took somewhere between 30-60 seconds to produce the same result.
remainder <- function(x, set) set[!set %in% x]
f <- function(Y, X) {
Y <- matrix(Y) # Turn row-vector into column
p <- ncol(X)
n <- nrow(X)
J <- matrix(1, n, n) # (5.18)
H <- X %*% solve(t(X) %*% X) %*% t(X) # (5.73a)
SSE <- t(Y) %*% (diag(n) - H) %*% Y # (5.89b)
SSR <- t(Y) %*% (H - (1/n)*J) %*% Y # (5.89c)
fstar <- (SSR / (p - 1)) / (SSE / (n - p)) # (6.39b)
}
base <- c(1.1, 0.5, -2.1, 4.2, 3.7, 0.8, 3.2, 2.8, 6.3)
t2 <- t12 <- t123 <- list()
y <- NULL
X <- cbind(
X1 = c(1, 1, 1, 0, 0, 0, 0, 0, 0),
X2 = c(0, 0, 0, 1, 1, 1, 0, 0, 0),
X3 = c(0, 0, 0, 0, 0, 0, 1, 1, 1))
t1 <- t(combn(base, 3))
seq6 <- t(combn(base, 3, remainder, set = base))
for (i in 1:84) t2[[i]] <- t(combn(seq6[i, ], 3))
for (i in 1:84) t12[[i]] <- cbind(t1[i, 1], t1[i, 2], t1[i, 3], t2[[i]])
for (i in 1:84)
t123[[i]] <- cbind(t12[[i]], t(apply(t12[[i]], 1, remainder, set = base)))
for (i in 1:84) y <- rbind(y, t123[[i]])
fstar <- apply(y, 1, function(Y) f(Y, X))
hist(fstar, freq = FALSE, ylim = c(0, 1), col = "gray90", main = "")
curve(df(x, 2, 6), add = TRUE, lwd = 2)
# LAST EXAMPLE FOR CHAPTER, fyi
# BIG OUTPUT TO FOLLOW!
cbind(y, data.frame(f = fstar))
## 1 2 3 4 5 6 7 8 9 f
## 1 1.1 0.5 -2.1 4.2 3.7 0.8 3.2 2.8 6.3 4.38658
## 2 1.1 0.5 -2.1 4.2 3.7 3.2 0.8 2.8 6.3 3.73562
## 3 1.1 0.5 -2.1 4.2 3.7 2.8 0.8 3.2 6.3 3.67030
## 4 1.1 0.5 -2.1 4.2 3.7 6.3 0.8 3.2 2.8 8.37571
## 5 1.1 0.5 -2.1 4.2 0.8 3.2 3.7 2.8 6.3 4.93225
## 6 1.1 0.5 -2.1 4.2 0.8 2.8 3.7 3.2 6.3 5.54835
## 7 1.1 0.5 -2.1 4.2 0.8 6.3 3.7 3.2 2.8 3.79383
## 8 1.1 0.5 -2.1 4.2 3.2 2.8 3.7 0.8 6.3 3.68042
## 9 1.1 0.5 -2.1 4.2 3.2 6.3 3.7 0.8 2.8 6.65439
## 10 1.1 0.5 -2.1 4.2 2.8 6.3 3.7 0.8 3.2 5.73492
## 11 1.1 0.5 -2.1 3.7 0.8 3.2 4.2 2.8 6.3 5.73492
## 12 1.1 0.5 -2.1 3.7 0.8 2.8 4.2 3.2 6.3 6.65439
## 13 1.1 0.5 -2.1 3.7 0.8 6.3 4.2 3.2 2.8 3.68042
## 14 1.1 0.5 -2.1 3.7 3.2 2.8 4.2 0.8 6.3 3.79383
## 15 1.1 0.5 -2.1 3.7 3.2 6.3 4.2 0.8 2.8 5.54835
## 16 1.1 0.5 -2.1 3.7 2.8 6.3 4.2 0.8 3.2 4.93225
## 17 1.1 0.5 -2.1 0.8 3.2 2.8 4.2 3.7 6.3 8.37571
## 18 1.1 0.5 -2.1 0.8 3.2 6.3 4.2 3.7 2.8 3.67030
## 19 1.1 0.5 -2.1 0.8 2.8 6.3 4.2 3.7 3.2 3.73562
## 20 1.1 0.5 -2.1 3.2 2.8 6.3 4.2 3.7 0.8 4.38658
## 21 1.1 0.5 4.2 -2.1 3.7 0.8 3.2 2.8 6.3 1.57916
## 22 1.1 0.5 4.2 -2.1 3.7 3.2 0.8 2.8 6.3 0.33162
## 23 1.1 0.5 4.2 -2.1 3.7 2.8 0.8 3.2 6.3 0.44638
## 24 1.1 0.5 4.2 -2.1 3.7 6.3 0.8 3.2 2.8 0.04580
## 25 1.1 0.5 4.2 -2.1 0.8 3.2 3.7 2.8 6.3 2.13459
## 26 1.1 0.5 4.2 -2.1 0.8 2.8 3.7 3.2 6.3 2.73977
## 27 1.1 0.5 4.2 -2.1 0.8 6.3 3.7 3.2 2.8 0.28292
## 28 1.1 0.5 4.2 -2.1 3.2 2.8 3.7 0.8 6.3 0.62815
## 29 1.1 0.5 4.2 -2.1 3.2 6.3 3.7 0.8 2.8 0.03321
## 30 1.1 0.5 4.2 -2.1 2.8 6.3 3.7 0.8 3.2 0.03823
## 31 1.1 0.5 4.2 3.7 0.8 3.2 -2.1 2.8 6.3 0.03823
## 32 1.1 0.5 4.2 3.7 0.8 2.8 -2.1 3.2 6.3 0.03321
## 33 1.1 0.5 4.2 3.7 0.8 6.3 -2.1 3.2 2.8 0.62815
## 34 1.1 0.5 4.2 3.7 3.2 2.8 -2.1 0.8 6.3 0.28292
## 35 1.1 0.5 4.2 3.7 3.2 6.3 -2.1 0.8 2.8 2.73977
## 36 1.1 0.5 4.2 3.7 2.8 6.3 -2.1 0.8 3.2 2.13459
## 37 1.1 0.5 4.2 0.8 3.2 2.8 -2.1 3.7 6.3 0.04580
## 38 1.1 0.5 4.2 0.8 3.2 6.3 -2.1 3.7 2.8 0.44638
## 39 1.1 0.5 4.2 0.8 2.8 6.3 -2.1 3.7 3.2 0.33162
## 40 1.1 0.5 4.2 3.2 2.8 6.3 -2.1 3.7 0.8 1.57916
## 41 1.1 0.5 3.7 -2.1 4.2 0.8 3.2 2.8 6.3 1.44507
## 42 1.1 0.5 3.7 -2.1 4.2 3.2 0.8 2.8 6.3 0.31906
## 43 1.1 0.5 3.7 -2.1 4.2 2.8 0.8 3.2 6.3 0.42226
## 44 1.1 0.5 3.7 -2.1 4.2 6.3 0.8 3.2 2.8 0.10159
## 45 1.1 0.5 3.7 -2.1 0.8 3.2 4.2 2.8 6.3 2.62679
## 46 1.1 0.5 3.7 -2.1 0.8 2.8 4.2 3.2 6.3 3.39884
## 47 1.1 0.5 3.7 -2.1 0.8 6.3 4.2 3.2 2.8 0.39429
## 48 1.1 0.5 3.7 -2.1 3.2 2.8 4.2 0.8 6.3 0.80041
## 49 1.1 0.5 3.7 -2.1 3.2 6.3 4.2 0.8 2.8 0.07559
## 50 1.1 0.5 3.7 -2.1 2.8 6.3 4.2 0.8 3.2 0.08940
## 51 1.1 0.5 3.7 4.2 0.8 3.2 -2.1 2.8 6.3 0.08940
## 52 1.1 0.5 3.7 4.2 0.8 2.8 -2.1 3.2 6.3 0.07559
## 53 1.1 0.5 3.7 4.2 0.8 6.3 -2.1 3.2 2.8 0.80041
## 54 1.1 0.5 3.7 4.2 3.2 2.8 -2.1 0.8 6.3 0.39429
## 55 1.1 0.5 3.7 4.2 3.2 6.3 -2.1 0.8 2.8 3.39884
## 56 1.1 0.5 3.7 4.2 2.8 6.3 -2.1 0.8 3.2 2.62679
## 57 1.1 0.5 3.7 0.8 3.2 2.8 -2.1 4.2 6.3 0.10159
## 58 1.1 0.5 3.7 0.8 3.2 6.3 -2.1 4.2 2.8 0.42226
## 59 1.1 0.5 3.7 0.8 2.8 6.3 -2.1 4.2 3.2 0.31906
## 60 1.1 0.5 3.7 3.2 2.8 6.3 -2.1 4.2 0.8 1.44507
## 61 1.1 0.5 0.8 -2.1 4.2 3.7 3.2 2.8 6.3 1.57916
## 62 1.1 0.5 0.8 -2.1 4.2 3.2 3.7 2.8 6.3 1.93875
## 63 1.1 0.5 0.8 -2.1 4.2 2.8 3.7 3.2 6.3 2.31562
## 64 1.1 0.5 0.8 -2.1 4.2 6.3 3.7 3.2 2.8 0.78148
## 65 1.1 0.5 0.8 -2.1 3.7 3.2 4.2 2.8 6.3 2.42568
## 66 1.1 0.5 0.8 -2.1 3.7 2.8 4.2 3.2 6.3 2.94758
## 67 1.1 0.5 0.8 -2.1 3.7 6.3 4.2 3.2 2.8 0.84087
## 68 1.1 0.5 0.8 -2.1 3.2 2.8 4.2 3.7 6.3 3.85519
## 69 1.1 0.5 0.8 -2.1 3.2 6.3 4.2 3.7 2.8 0.93704
## 70 1.1 0.5 0.8 -2.1 2.8 6.3 4.2 3.7 3.2 1.04409
## 71 1.1 0.5 0.8 4.2 3.7 3.2 -2.1 2.8 6.3 1.04409
## 72 1.1 0.5 0.8 4.2 3.7 2.8 -2.1 3.2 6.3 0.93704
## 73 1.1 0.5 0.8 4.2 3.7 6.3 -2.1 3.2 2.8 3.85519
## 74 1.1 0.5 0.8 4.2 3.2 2.8 -2.1 3.7 6.3 0.84087
## 75 1.1 0.5 0.8 4.2 3.2 6.3 -2.1 3.7 2.8 2.94758
## 76 1.1 0.5 0.8 4.2 2.8 6.3 -2.1 3.7 3.2 2.42568
## 77 1.1 0.5 0.8 3.7 3.2 2.8 -2.1 4.2 6.3 0.78148
## 78 1.1 0.5 0.8 3.7 3.2 6.3 -2.1 4.2 2.8 2.31562
## 79 1.1 0.5 0.8 3.7 2.8 6.3 -2.1 4.2 3.2 1.93875
## 80 1.1 0.5 0.8 3.2 2.8 6.3 -2.1 4.2 3.7 1.57916
## 81 1.1 0.5 3.2 -2.1 4.2 3.7 0.8 2.8 6.3 0.33162
## 82 1.1 0.5 3.2 -2.1 4.2 0.8 3.7 2.8 6.3 1.80926
## 83 1.1 0.5 3.2 -2.1 4.2 2.8 3.7 0.8 6.3 0.57512
## 84 1.1 0.5 3.2 -2.1 4.2 6.3 3.7 0.8 2.8 0.14592
## 85 1.1 0.5 3.2 -2.1 3.7 0.8 4.2 2.8 6.3 2.42568
## 86 1.1 0.5 3.2 -2.1 3.7 2.8 4.2 0.8 6.3 0.77112
## 87 1.1 0.5 3.2 -2.1 3.7 6.3 4.2 0.8 2.8 0.13249
## 88 1.1 0.5 3.2 -2.1 0.8 2.8 4.2 3.7 6.3 4.34958
## 89 1.1 0.5 3.2 -2.1 0.8 6.3 4.2 3.7 2.8 0.54175
## 90 1.1 0.5 3.2 -2.1 2.8 6.3 4.2 3.7 0.8 0.16492
## 91 1.1 0.5 3.2 4.2 3.7 0.8 -2.1 2.8 6.3 0.16492
## 92 1.1 0.5 3.2 4.2 3.7 2.8 -2.1 0.8 6.3 0.54175
## 93 1.1 0.5 3.2 4.2 3.7 6.3 -2.1 0.8 2.8 4.34958
## 94 1.1 0.5 3.2 4.2 0.8 2.8 -2.1 3.7 6.3 0.13249
## 95 1.1 0.5 3.2 4.2 0.8 6.3 -2.1 3.7 2.8 0.77112
## 96 1.1 0.5 3.2 4.2 2.8 6.3 -2.1 3.7 0.8 2.42568
## 97 1.1 0.5 3.2 3.7 0.8 2.8 -2.1 4.2 6.3 0.14592
## 98 1.1 0.5 3.2 3.7 0.8 6.3 -2.1 4.2 2.8 0.57512
## 99 1.1 0.5 3.2 3.7 2.8 6.3 -2.1 4.2 0.8 1.80926
## 100 1.1 0.5 3.2 0.8 2.8 6.3 -2.1 4.2 3.7 0.33162
## 101 1.1 0.5 2.8 -2.1 4.2 3.7 0.8 3.2 6.3 0.44638
## 102 1.1 0.5 2.8 -2.1 4.2 0.8 3.7 3.2 6.3 2.19029
## 103 1.1 0.5 2.8 -2.1 4.2 3.2 3.7 0.8 6.3 0.58677
## 104 1.1 0.5 2.8 -2.1 4.2 6.3 3.7 0.8 3.2 0.19895
## 105 1.1 0.5 2.8 -2.1 3.7 0.8 4.2 3.2 6.3 2.94758
## 106 1.1 0.5 2.8 -2.1 3.7 3.2 4.2 0.8 6.3 0.77112
## 107 1.1 0.5 2.8 -2.1 3.7 6.3 4.2 0.8 3.2 0.19431
## 108 1.1 0.5 2.8 -2.1 0.8 3.2 4.2 3.7 6.3 4.07554
## 109 1.1 0.5 2.8 -2.1 0.8 6.3 4.2 3.7 3.2 0.69143
## 110 1.1 0.5 2.8 -2.1 3.2 6.3 4.2 3.7 0.8 0.21296
## 111 1.1 0.5 2.8 4.2 3.7 0.8 -2.1 3.2 6.3 0.21296
## 112 1.1 0.5 2.8 4.2 3.7 3.2 -2.1 0.8 6.3 0.69143
## 113 1.1 0.5 2.8 4.2 3.7 6.3 -2.1 0.8 3.2 4.07554
## 114 1.1 0.5 2.8 4.2 0.8 3.2 -2.1 3.7 6.3 0.19431
## 115 1.1 0.5 2.8 4.2 0.8 6.3 -2.1 3.7 3.2 0.77112
## 116 1.1 0.5 2.8 4.2 3.2 6.3 -2.1 3.7 0.8 2.94758
## 117 1.1 0.5 2.8 3.7 0.8 3.2 -2.1 4.2 6.3 0.19895
## 118 1.1 0.5 2.8 3.7 0.8 6.3 -2.1 4.2 3.2 0.58677
## 119 1.1 0.5 2.8 3.7 3.2 6.3 -2.1 4.2 0.8 2.19029
## 120 1.1 0.5 2.8 0.8 3.2 6.3 -2.1 4.2 3.7 0.44638
## 121 1.1 0.5 6.3 -2.1 4.2 3.7 0.8 3.2 2.8 0.04580
## 122 1.1 0.5 6.3 -2.1 4.2 0.8 3.7 3.2 2.8 0.61089
## 123 1.1 0.5 6.3 -2.1 4.2 3.2 3.7 0.8 2.8 0.07774
## 124 1.1 0.5 6.3 -2.1 4.2 2.8 3.7 0.8 3.2 0.11961
## 125 1.1 0.5 6.3 -2.1 3.7 0.8 4.2 3.2 2.8 0.84087
## 126 1.1 0.5 6.3 -2.1 3.7 3.2 4.2 0.8 2.8 0.13249
## 127 1.1 0.5 6.3 -2.1 3.7 2.8 4.2 0.8 3.2 0.19431
## 128 1.1 0.5 6.3 -2.1 0.8 3.2 4.2 3.7 2.8 1.14071
## 129 1.1 0.5 6.3 -2.1 0.8 2.8 4.2 3.7 3.2 1.44867
## 130 1.1 0.5 6.3 -2.1 3.2 2.8 4.2 3.7 0.8 0.29718
## 131 1.1 0.5 6.3 4.2 3.7 0.8 -2.1 3.2 2.8 0.29718
## 132 1.1 0.5 6.3 4.2 3.7 3.2 -2.1 0.8 2.8 1.44867
## 133 1.1 0.5 6.3 4.2 3.7 2.8 -2.1 0.8 3.2 1.14071
## 134 1.1 0.5 6.3 4.2 0.8 3.2 -2.1 3.7 2.8 0.19431
## 135 1.1 0.5 6.3 4.2 0.8 2.8 -2.1 3.7 3.2 0.13249
## 136 1.1 0.5 6.3 4.2 3.2 2.8 -2.1 3.7 0.8 0.84087
## 137 1.1 0.5 6.3 3.7 0.8 3.2 -2.1 4.2 2.8 0.11961
## 138 1.1 0.5 6.3 3.7 0.8 2.8 -2.1 4.2 3.2 0.07774
## 139 1.1 0.5 6.3 3.7 3.2 2.8 -2.1 4.2 0.8 0.61089
## 140 1.1 0.5 6.3 0.8 3.2 2.8 -2.1 4.2 3.7 0.04580
## 141 1.1 -2.1 4.2 0.5 3.7 0.8 3.2 2.8 6.3 1.38923
## 142 1.1 -2.1 4.2 0.5 3.7 3.2 0.8 2.8 6.3 0.55548
## 143 1.1 -2.1 4.2 0.5 3.7 2.8 0.8 3.2 6.3 0.62337
## 144 1.1 -2.1 4.2 0.5 3.7 6.3 0.8 3.2 2.8 0.66561
## 145 1.1 -2.1 4.2 0.5 0.8 3.2 3.7 2.8 6.3 1.75935
## 146 1.1 -2.1 4.2 0.5 0.8 2.8 3.7 3.2 6.3 2.14660
## 147 1.1 -2.1 4.2 0.5 0.8 6.3 3.7 3.2 2.8 0.52926
## 148 1.1 -2.1 4.2 0.5 3.2 2.8 3.7 0.8 6.3 0.74036
## 149 1.1 -2.1 4.2 0.5 3.2 6.3 3.7 0.8 2.8 0.57048
## 150 1.1 -2.1 4.2 0.5 2.8 6.3 3.7 0.8 3.2 0.51798
## 151 1.1 -2.1 4.2 3.7 0.8 3.2 0.5 2.8 6.3 0.51798
## 152 1.1 -2.1 4.2 3.7 0.8 2.8 0.5 3.2 6.3 0.57048
## 153 1.1 -2.1 4.2 3.7 0.8 6.3 0.5 3.2 2.8 0.74036
## 154 1.1 -2.1 4.2 3.7 3.2 2.8 0.5 0.8 6.3 0.52926
## 155 1.1 -2.1 4.2 3.7 3.2 6.3 0.5 0.8 2.8 2.14660
## 156 1.1 -2.1 4.2 3.7 2.8 6.3 0.5 0.8 3.2 1.75935
## 157 1.1 -2.1 4.2 0.8 3.2 2.8 0.5 3.7 6.3 0.66561
## 158 1.1 -2.1 4.2 0.8 3.2 6.3 0.5 3.7 2.8 0.62337
## 159 1.1 -2.1 4.2 0.8 2.8 6.3 0.5 3.7 3.2 0.55548
## 160 1.1 -2.1 4.2 3.2 2.8 6.3 0.5 3.7 0.8 1.38923
## 161 1.1 -2.1 3.7 0.5 4.2 0.8 3.2 2.8 6.3 1.49224
## 162 1.1 -2.1 3.7 0.5 4.2 3.2 0.8 2.8 6.3 0.69577
## 163 1.1 -2.1 3.7 0.5 4.2 2.8 0.8 3.2 6.3 0.75631
## 164 1.1 -2.1 3.7 0.5 4.2 6.3 0.8 3.2 2.8 0.92021
## 165 1.1 -2.1 3.7 0.5 0.8 3.2 4.2 2.8 6.3 2.34272
## 166 1.1 -2.1 3.7 0.5 0.8 2.8 4.2 3.2 6.3 2.86674
## 167 1.1 -2.1 3.7 0.5 0.8 6.3 4.2 3.2 2.8 0.73909
## 168 1.1 -2.1 3.7 0.5 3.2 2.8 4.2 0.8 6.3 1.01679
## 169 1.1 -2.1 3.7 0.5 3.2 6.3 4.2 0.8 2.8 0.70885
## 170 1.1 -2.1 3.7 0.5 2.8 6.3 4.2 0.8 3.2 0.66439
## 171 1.1 -2.1 3.7 4.2 0.8 3.2 0.5 2.8 6.3 0.66439
## 172 1.1 -2.1 3.7 4.2 0.8 2.8 0.5 3.2 6.3 0.70885
## 173 1.1 -2.1 3.7 4.2 0.8 6.3 0.5 3.2 2.8 1.01679
## 174 1.1 -2.1 3.7 4.2 3.2 2.8 0.5 0.8 6.3 0.73909
## 175 1.1 -2.1 3.7 4.2 3.2 6.3 0.5 0.8 2.8 2.86674
## 176 1.1 -2.1 3.7 4.2 2.8 6.3 0.5 0.8 3.2 2.34272
## 177 1.1 -2.1 3.7 0.8 3.2 2.8 0.5 4.2 6.3 0.92021
## 178 1.1 -2.1 3.7 0.8 3.2 6.3 0.5 4.2 2.8 0.75631
## 179 1.1 -2.1 3.7 0.8 2.8 6.3 0.5 4.2 3.2 0.69577
## 180 1.1 -2.1 3.7 3.2 2.8 6.3 0.5 4.2 0.8 1.49224
## 181 1.1 -2.1 0.8 0.5 4.2 3.7 3.2 2.8 6.3 3.77918
## 182 1.1 -2.1 0.8 0.5 4.2 3.2 3.7 2.8 6.3 4.27189
## 183 1.1 -2.1 0.8 0.5 4.2 2.8 3.7 3.2 6.3 4.81954
## 184 1.1 -2.1 0.8 0.5 4.2 6.3 3.7 3.2 2.8 3.14003
## 185 1.1 -2.1 0.8 0.5 3.7 3.2 4.2 2.8 6.3 4.98404
## 186 1.1 -2.1 0.8 0.5 3.7 2.8 4.2 3.2 6.3 5.78723
## 187 1.1 -2.1 0.8 0.5 3.7 6.3 4.2 3.2 2.8 3.07228
## 188 1.1 -2.1 0.8 0.5 3.2 2.8 4.2 3.7 6.3 7.26200
## 189 1.1 -2.1 0.8 0.5 3.2 6.3 4.2 3.7 2.8 3.08907
## 190 1.1 -2.1 0.8 0.5 2.8 6.3 4.2 3.7 3.2 3.16410
## 191 1.1 -2.1 0.8 4.2 3.7 3.2 0.5 2.8 6.3 3.16410
## 192 1.1 -2.1 0.8 4.2 3.7 2.8 0.5 3.2 6.3 3.08907
## 193 1.1 -2.1 0.8 4.2 3.7 6.3 0.5 3.2 2.8 7.26200
## 194 1.1 -2.1 0.8 4.2 3.2 2.8 0.5 3.7 6.3 3.07228
## 195 1.1 -2.1 0.8 4.2 3.2 6.3 0.5 3.7 2.8 5.78723
## 196 1.1 -2.1 0.8 4.2 2.8 6.3 0.5 3.7 3.2 4.98404
## 197 1.1 -2.1 0.8 3.7 3.2 2.8 0.5 4.2 6.3 3.14003
## 198 1.1 -2.1 0.8 3.7 3.2 6.3 0.5 4.2 2.8 4.81954
## 199 1.1 -2.1 0.8 3.7 2.8 6.3 0.5 4.2 3.2 4.27189
## 200 1.1 -2.1 0.8 3.2 2.8 6.3 0.5 4.2 3.7 3.77918
## 201 1.1 -2.1 3.2 0.5 4.2 3.7 0.8 2.8 6.3 0.88150
## 202 1.1 -2.1 3.2 0.5 4.2 0.8 3.7 2.8 6.3 2.00842
## 203 1.1 -2.1 3.2 0.5 4.2 2.8 3.7 0.8 6.3 1.03520
## 204 1.1 -2.1 3.2 0.5 4.2 6.3 3.7 0.8 2.8 1.08765
## 205 1.1 -2.1 3.2 0.5 3.7 0.8 4.2 2.8 6.3 2.49613
## 206 1.1 -2.1 3.2 0.5 3.7 2.8 4.2 0.8 6.3 1.18082
## 207 1.1 -2.1 3.2 0.5 3.7 6.3 4.2 0.8 2.8 0.96970
## 208 1.1 -2.1 3.2 0.5 0.8 2.8 4.2 3.7 6.3 3.92855
## 209 1.1 -2.1 3.2 0.5 0.8 6.3 4.2 3.7 2.8 1.01166
## 210 1.1 -2.1 3.2 0.5 2.8 6.3 4.2 3.7 0.8 0.85702
## 211 1.1 -2.1 3.2 4.2 3.7 0.8 0.5 2.8 6.3 0.85702
## 212 1.1 -2.1 3.2 4.2 3.7 2.8 0.5 0.8 6.3 1.01166
## 213 1.1 -2.1 3.2 4.2 3.7 6.3 0.5 0.8 2.8 3.92855
## 214 1.1 -2.1 3.2 4.2 0.8 2.8 0.5 3.7 6.3 0.96970
## 215 1.1 -2.1 3.2 4.2 0.8 6.3 0.5 3.7 2.8 1.18082
## 216 1.1 -2.1 3.2 4.2 2.8 6.3 0.5 3.7 0.8 2.49613
## 217 1.1 -2.1 3.2 3.7 0.8 2.8 0.5 4.2 6.3 1.08765
## 218 1.1 -2.1 3.2 3.7 0.8 6.3 0.5 4.2 2.8 1.03520
## 219 1.1 -2.1 3.2 3.7 2.8 6.3 0.5 4.2 0.8 2.00842
## 220 1.1 -2.1 3.2 0.8 2.8 6.3 0.5 4.2 3.7 0.88150
## 221 1.1 -2.1 2.8 0.5 4.2 3.7 0.8 3.2 6.3 1.11670
## 222 1.1 -2.1 2.8 0.5 4.2 0.8 3.7 3.2 6.3 2.56561
## 223 1.1 -2.1 2.8 0.5 4.2 3.2 3.7 0.8 6.3 1.21121
## 224 1.1 -2.1 2.8 0.5 4.2 6.3 3.7 0.8 3.2 1.26176
## 225 1.1 -2.1 2.8 0.5 3.7 0.8 4.2 3.2 6.3 3.20931
## 226 1.1 -2.1 2.8 0.5 3.7 3.2 4.2 0.8 6.3 1.35278
## 227 1.1 -2.1 2.8 0.5 3.7 6.3 4.2 0.8 3.2 1.14929
## 228 1.1 -2.1 2.8 0.5 0.8 3.2 4.2 3.7 6.3 4.13517
## 229 1.1 -2.1 2.8 0.5 0.8 6.3 4.2 3.7 3.2 1.29000
## 230 1.1 -2.1 2.8 0.5 3.2 6.3 4.2 3.7 0.8 1.08007
## 231 1.1 -2.1 2.8 4.2 3.7 0.8 0.5 3.2 6.3 1.08007
## 232 1.1 -2.1 2.8 4.2 3.7 3.2 0.5 0.8 6.3 1.29000
## 233 1.1 -2.1 2.8 4.2 3.7 6.3 0.5 0.8 3.2 4.13517
## 234 1.1 -2.1 2.8 4.2 0.8 3.2 0.5 3.7 6.3 1.14929
## 235 1.1 -2.1 2.8 4.2 0.8 6.3 0.5 3.7 3.2 1.35278
## 236 1.1 -2.1 2.8 4.2 3.2 6.3 0.5 3.7 0.8 3.20931
## 237 1.1 -2.1 2.8 3.7 0.8 3.2 0.5 4.2 6.3 1.26176
## 238 1.1 -2.1 2.8 3.7 0.8 6.3 0.5 4.2 3.2 1.21121
## 239 1.1 -2.1 2.8 3.7 3.2 6.3 0.5 4.2 0.8 2.56561
## 240 1.1 -2.1 2.8 0.8 3.2 6.3 0.5 4.2 3.7 1.11670
## 241 1.1 -2.1 6.3 0.5 4.2 3.7 0.8 3.2 2.8 0.10159
## 242 1.1 -2.1 6.3 0.5 4.2 0.8 3.7 3.2 2.8 0.27560
## 243 1.1 -2.1 6.3 0.5 4.2 3.2 3.7 0.8 2.8 0.07774
## 244 1.1 -2.1 6.3 0.5 4.2 2.8 3.7 0.8 3.2 0.07430
## 245 1.1 -2.1 6.3 0.5 3.7 0.8 4.2 3.2 2.8 0.39429
## 246 1.1 -2.1 6.3 0.5 3.7 3.2 4.2 0.8 2.8 0.07559
## 247 1.1 -2.1 6.3 0.5 3.7 2.8 4.2 0.8 3.2 0.08940
## 248 1.1 -2.1 6.3 0.5 0.8 3.2 4.2 3.7 2.8 0.55032
## 249 1.1 -2.1 6.3 0.5 0.8 2.8 4.2 3.7 3.2 0.70822
## 250 1.1 -2.1 6.3 0.5 3.2 2.8 4.2 3.7 0.8 0.12670
## 251 1.1 -2.1 6.3 4.2 3.7 0.8 0.5 3.2 2.8 0.12670
## 252 1.1 -2.1 6.3 4.2 3.7 3.2 0.5 0.8 2.8 0.70822
## 253 1.1 -2.1 6.3 4.2 3.7 2.8 0.5 0.8 3.2 0.55032
## 254 1.1 -2.1 6.3 4.2 0.8 3.2 0.5 3.7 2.8 0.08940
## 255 1.1 -2.1 6.3 4.2 0.8 2.8 0.5 3.7 3.2 0.07559
## 256 1.1 -2.1 6.3 4.2 3.2 2.8 0.5 3.7 0.8 0.39429
## 257 1.1 -2.1 6.3 3.7 0.8 3.2 0.5 4.2 2.8 0.07430
## 258 1.1 -2.1 6.3 3.7 0.8 2.8 0.5 4.2 3.2 0.07774
## 259 1.1 -2.1 6.3 3.7 3.2 2.8 0.5 4.2 0.8 0.27560
## 260 1.1 -2.1 6.3 0.8 3.2 2.8 0.5 4.2 3.7 0.10159
## 261 1.1 4.2 3.7 0.5 -2.1 0.8 3.2 2.8 6.3 5.16772
## 262 1.1 4.2 3.7 0.5 -2.1 3.2 0.8 2.8 6.3 1.18241
## 263 1.1 4.2 3.7 0.5 -2.1 2.8 0.8 3.2 6.3 1.47854
## 264 1.1 4.2 3.7 0.5 -2.1 6.3 0.8 3.2 2.8 0.20175
## 265 1.1 4.2 3.7 0.5 0.8 3.2 -2.1 2.8 6.3 0.22331
## 266 1.1 4.2 3.7 0.5 0.8 2.8 -2.1 3.2 6.3 0.27901
## 267 1.1 4.2 3.7 0.5 0.8 6.3 -2.1 3.2 2.8 0.31356
## 268 1.1 4.2 3.7 0.5 3.2 2.8 -2.1 0.8 6.3 0.17679
## 269 1.1 4.2 3.7 0.5 3.2 6.3 -2.1 0.8 2.8 1.25024
## 270 1.1 4.2 3.7 0.5 2.8 6.3 -2.1 0.8 3.2 1.00000
## 271 1.1 4.2 3.7 -2.1 0.8 3.2 0.5 2.8 6.3 1.00000
## 272 1.1 4.2 3.7 -2.1 0.8 2.8 0.5 3.2 6.3 1.25024
## 273 1.1 4.2 3.7 -2.1 0.8 6.3 0.5 3.2 2.8 0.17679
## 274 1.1 4.2 3.7 -2.1 3.2 2.8 0.5 0.8 6.3 0.31356
## 275 1.1 4.2 3.7 -2.1 3.2 6.3 0.5 0.8 2.8 0.27901
## 276 1.1 4.2 3.7 -2.1 2.8 6.3 0.5 0.8 3.2 0.22331
## 277 1.1 4.2 3.7 0.8 3.2 2.8 0.5 -2.1 6.3 0.20175
## 278 1.1 4.2 3.7 0.8 3.2 6.3 0.5 -2.1 2.8 1.47854
## 279 1.1 4.2 3.7 0.8 2.8 6.3 0.5 -2.1 3.2 1.18241
## 280 1.1 4.2 3.7 3.2 2.8 6.3 0.5 -2.1 0.8 5.16772
## 281 1.1 4.2 0.8 0.5 -2.1 3.7 3.2 2.8 6.3 1.68739
## 282 1.1 4.2 0.8 0.5 -2.1 3.2 3.7 2.8 6.3 2.29007
## 283 1.1 4.2 0.8 0.5 -2.1 2.8 3.7 3.2 6.3 2.95402
## 284 1.1 4.2 0.8 0.5 -2.1 6.3 3.7 3.2 2.8 0.29916
## 285 1.1 4.2 0.8 0.5 3.7 3.2 -2.1 2.8 6.3 0.01824
## 286 1.1 4.2 0.8 0.5 3.7 2.8 -2.1 3.2 6.3 0.01824
## 287 1.1 4.2 0.8 0.5 3.7 6.3 -2.1 3.2 2.8 0.54575
## 288 1.1 4.2 0.8 0.5 3.2 2.8 -2.1 3.7 6.3 0.03698
## 289 1.1 4.2 0.8 0.5 3.2 6.3 -2.1 3.7 2.8 0.37970
## 290 1.1 4.2 0.8 0.5 2.8 6.3 -2.1 3.7 3.2 0.27511
## 291 1.1 4.2 0.8 -2.1 3.7 3.2 0.5 2.8 6.3 0.27511
## 292 1.1 4.2 0.8 -2.1 3.7 2.8 0.5 3.2 6.3 0.37970
## 293 1.1 4.2 0.8 -2.1 3.7 6.3 0.5 3.2 2.8 0.03698
## 294 1.1 4.2 0.8 -2.1 3.2 2.8 0.5 3.7 6.3 0.54575
## 295 1.1 4.2 0.8 -2.1 3.2 6.3 0.5 3.7 2.8 0.01824
## 296 1.1 4.2 0.8 -2.1 2.8 6.3 0.5 3.7 3.2 0.01824
## 297 1.1 4.2 0.8 3.7 3.2 2.8 0.5 -2.1 6.3 0.29916
## 298 1.1 4.2 0.8 3.7 3.2 6.3 0.5 -2.1 2.8 2.95402
## 299 1.1 4.2 0.8 3.7 2.8 6.3 0.5 -2.1 3.2 2.29007
## 300 1.1 4.2 0.8 3.2 2.8 6.3 0.5 -2.1 3.7 1.68739
## 301 1.1 4.2 3.2 0.5 -2.1 3.7 0.8 2.8 6.3 0.92511
## 302 1.1 4.2 3.2 0.5 -2.1 0.8 3.7 2.8 6.3 5.78723
## 303 1.1 4.2 3.2 0.5 -2.1 2.8 3.7 0.8 6.3 1.56207
## 304 1.1 4.2 3.2 0.5 -2.1 6.3 3.7 0.8 2.8 0.16264
## 305 1.1 4.2 3.2 0.5 3.7 0.8 -2.1 2.8 6.3 0.13160
## 306 1.1 4.2 3.2 0.5 3.7 2.8 -2.1 0.8 6.3 0.13160
## 307 1.1 4.2 3.2 0.5 3.7 6.3 -2.1 0.8 2.8 1.31270
## 308 1.1 4.2 3.2 0.5 0.8 2.8 -2.1 3.7 6.3 0.25236
## 309 1.1 4.2 3.2 0.5 0.8 6.3 -2.1 3.7 2.8 0.20268
## 310 1.1 4.2 3.2 0.5 2.8 6.3 -2.1 3.7 0.8 0.77370
## 311 1.1 4.2 3.2 -2.1 3.7 0.8 0.5 2.8 6.3 0.77370
## 312 1.1 4.2 3.2 -2.1 3.7 2.8 0.5 0.8 6.3 0.20268
## 313 1.1 4.2 3.2 -2.1 3.7 6.3 0.5 0.8 2.8 0.25236
## 314 1.1 4.2 3.2 -2.1 0.8 2.8 0.5 3.7 6.3 1.31270
## 315 1.1 4.2 3.2 -2.1 0.8 6.3 0.5 3.7 2.8 0.13160
## 316 1.1 4.2 3.2 -2.1 2.8 6.3 0.5 3.7 0.8 0.13160
## 317 1.1 4.2 3.2 3.7 0.8 2.8 0.5 -2.1 6.3 0.16264
## 318 1.1 4.2 3.2 3.7 0.8 6.3 0.5 -2.1 2.8 1.56207
## 319 1.1 4.2 3.2 3.7 2.8 6.3 0.5 -2.1 0.8 5.78723
## 320 1.1 4.2 3.2 0.8 2.8 6.3 0.5 -2.1 3.7 0.92511
## 321 1.1 4.2 2.8 0.5 -2.1 3.7 0.8 3.2 6.3 0.97616
## 322 1.1 4.2 2.8 0.5 -2.1 0.8 3.7 3.2 6.3 6.50022
## 323 1.1 4.2 2.8 0.5 -2.1 3.2 3.7 0.8 6.3 1.31523
## 324 1.1 4.2 2.8 0.5 -2.1 6.3 3.7 0.8 3.2 0.14817
## 325 1.1 4.2 2.8 0.5 3.7 0.8 -2.1 3.2 6.3 0.11212
## 326 1.1 4.2 2.8 0.5 3.7 3.2 -2.1 0.8 6.3 0.11212
## 327 1.1 4.2 2.8 0.5 3.7 6.3 -2.1 0.8 3.2 1.10060
## 328 1.1 4.2 2.8 0.5 0.8 3.2 -2.1 3.7 6.3 0.17725
## 329 1.1 4.2 2.8 0.5 0.8 6.3 -2.1 3.7 3.2 0.13517
## 330 1.1 4.2 2.8 0.5 3.2 6.3 -2.1 3.7 0.8 0.81292
## 331 1.1 4.2 2.8 -2.1 3.7 0.8 0.5 3.2 6.3 0.81292
## 332 1.1 4.2 2.8 -2.1 3.7 3.2 0.5 0.8 6.3 0.13517
## 333 1.1 4.2 2.8 -2.1 3.7 6.3 0.5 0.8 3.2 0.17725
## 334 1.1 4.2 2.8 -2.1 0.8 3.2 0.5 3.7 6.3 1.10060
## 335 1.1 4.2 2.8 -2.1 0.8 6.3 0.5 3.7 3.2 0.11212
## 336 1.1 4.2 2.8 -2.1 3.2 6.3 0.5 3.7 0.8 0.11212
## 337 1.1 4.2 2.8 3.7 0.8 3.2 0.5 -2.1 6.3 0.14817
## 338 1.1 4.2 2.8 3.7 0.8 6.3 0.5 -2.1 3.2 1.31523
## 339 1.1 4.2 2.8 3.7 3.2 6.3 0.5 -2.1 0.8 6.50022
## 340 1.1 4.2 2.8 0.8 3.2 6.3 0.5 -2.1 3.7 0.97616
## 341 1.1 4.2 6.3 0.5 -2.1 3.7 0.8 3.2 2.8 1.33222
## 342 1.1 4.2 6.3 0.5 -2.1 0.8 3.7 3.2 2.8 4.65103
## 343 1.1 4.2 6.3 0.5 -2.1 3.2 3.7 0.8 2.8 1.56586
## 344 1.1 4.2 6.3 0.5 -2.1 2.8 3.7 0.8 3.2 1.80926
## 345 1.1 4.2 6.3 0.5 3.7 0.8 -2.1 3.2 2.8 0.92861
## 346 1.1 4.2 6.3 0.5 3.7 3.2 -2.1 0.8 2.8 1.62146
## 347 1.1 4.2 6.3 0.5 3.7 2.8 -2.1 0.8 3.2 1.41742
## 348 1.1 4.2 6.3 0.5 0.8 3.2 -2.1 3.7 2.8 0.90769
## 349 1.1 4.2 6.3 0.5 0.8 2.8 -2.1 3.7 3.2 0.91603
## 350 1.1 4.2 6.3 0.5 3.2 2.8 -2.1 3.7 0.8 1.22252
## 351 1.1 4.2 6.3 -2.1 3.7 0.8 0.5 3.2 2.8 1.22252
## 352 1.1 4.2 6.3 -2.1 3.7 3.2 0.5 0.8 2.8 0.91603
## 353 1.1 4.2 6.3 -2.1 3.7 2.8 0.5 0.8 3.2 0.90769
## 354 1.1 4.2 6.3 -2.1 0.8 3.2 0.5 3.7 2.8 1.41742
## 355 1.1 4.2 6.3 -2.1 0.8 2.8 0.5 3.7 3.2 1.62146
## 356 1.1 4.2 6.3 -2.1 3.2 2.8 0.5 3.7 0.8 0.92861
## 357 1.1 4.2 6.3 3.7 0.8 3.2 0.5 -2.1 2.8 1.80926
## 358 1.1 4.2 6.3 3.7 0.8 2.8 0.5 -2.1 3.2 1.56586
## 359 1.1 4.2 6.3 3.7 3.2 2.8 0.5 -2.1 0.8 4.65103
## 360 1.1 4.2 6.3 0.8 3.2 2.8 0.5 -2.1 3.7 1.33222
## 361 1.1 3.7 0.8 0.5 -2.1 4.2 3.2 2.8 6.3 1.51899
## 362 1.1 3.7 0.8 0.5 -2.1 3.2 4.2 2.8 6.3 2.79111
## 363 1.1 3.7 0.8 0.5 -2.1 2.8 4.2 3.2 6.3 3.63612
## 364 1.1 3.7 0.8 0.5 -2.1 6.3 4.2 3.2 2.8 0.40374
## 365 1.1 3.7 0.8 0.5 4.2 3.2 -2.1 2.8 6.3 0.05595
## 366 1.1 3.7 0.8 0.5 4.2 2.8 -2.1 3.2 6.3 0.04749
## 367 1.1 3.7 0.8 0.5 4.2 6.3 -2.1 3.2 2.8 0.69143
## 368 1.1 3.7 0.8 0.5 3.2 2.8 -2.1 4.2 6.3 0.08594
## 369 1.1 3.7 0.8 0.5 3.2 6.3 -2.1 4.2 2.8 0.34885
## 370 1.1 3.7 0.8 0.5 2.8 6.3 -2.1 4.2 3.2 0.25573
## 371 1.1 3.7 0.8 -2.1 4.2 3.2 0.5 2.8 6.3 0.25573
## 372 1.1 3.7 0.8 -2.1 4.2 2.8 0.5 3.2 6.3 0.34885
## 373 1.1 3.7 0.8 -2.1 4.2 6.3 0.5 3.2 2.8 0.08594
## 374 1.1 3.7 0.8 -2.1 3.2 2.8 0.5 4.2 6.3 0.69143
## 375 1.1 3.7 0.8 -2.1 3.2 6.3 0.5 4.2 2.8 0.04749
## 376 1.1 3.7 0.8 -2.1 2.8 6.3 0.5 4.2 3.2 0.05595
## 377 1.1 3.7 0.8 4.2 3.2 2.8 0.5 -2.1 6.3 0.40374
## 378 1.1 3.7 0.8 4.2 3.2 6.3 0.5 -2.1 2.8 3.63612
## 379 1.1 3.7 0.8 4.2 2.8 6.3 0.5 -2.1 3.2 2.79111
## 380 1.1 3.7 0.8 3.2 2.8 6.3 0.5 -2.1 4.2 1.51899
## 381 1.1 3.7 3.2 0.5 -2.1 4.2 0.8 2.8 6.3 0.72895
## 382 1.1 3.7 3.2 0.5 -2.1 0.8 4.2 2.8 6.3 6.71832
## 383 1.1 3.7 3.2 0.5 -2.1 2.8 4.2 0.8 6.3 1.69840
## 384 1.1 3.7 3.2 0.5 -2.1 6.3 4.2 0.8 2.8 0.14682
## 385 1.1 3.7 3.2 0.5 4.2 0.8 -2.1 2.8 6.3 0.06617
## 386 1.1 3.7 3.2 0.5 4.2 2.8 -2.1 0.8 6.3 0.10948
## 387 1.1 3.7 3.2 0.5 4.2 6.3 -2.1 0.8 2.8 1.42097
## 388 1.1 3.7 3.2 0.5 0.8 2.8 -2.1 4.2 6.3 0.24996
## 389 1.1 3.7 3.2 0.5 0.8 6.3 -2.1 4.2 2.8 0.12094
## 390 1.1 3.7 3.2 0.5 2.8 6.3 -2.1 4.2 0.8 0.60085
## 391 1.1 3.7 3.2 -2.1 4.2 0.8 0.5 2.8 6.3 0.60085
## 392 1.1 3.7 3.2 -2.1 4.2 2.8 0.5 0.8 6.3 0.12094
## 393 1.1 3.7 3.2 -2.1 4.2 6.3 0.5 0.8 2.8 0.24996
## 394 1.1 3.7 3.2 -2.1 0.8 2.8 0.5 4.2 6.3 1.42097
## 395 1.1 3.7 3.2 -2.1 0.8 6.3 0.5 4.2 2.8 0.10948
## 396 1.1 3.7 3.2 -2.1 2.8 6.3 0.5 4.2 0.8 0.06617
## 397 1.1 3.7 3.2 4.2 0.8 2.8 0.5 -2.1 6.3 0.14682
## 398 1.1 3.7 3.2 4.2 0.8 6.3 0.5 -2.1 2.8 1.69840
## 399 1.1 3.7 3.2 4.2 2.8 6.3 0.5 -2.1 0.8 6.71832
## 400 1.1 3.7 3.2 0.8 2.8 6.3 0.5 -2.1 4.2 0.72895
## 401 1.1 3.7 2.8 0.5 -2.1 4.2 0.8 3.2 6.3 0.78799
## 402 1.1 3.7 2.8 0.5 -2.1 0.8 4.2 3.2 6.3 7.80609
## 403 1.1 3.7 2.8 0.5 -2.1 3.2 4.2 0.8 6.3 1.45497
## 404 1.1 3.7 2.8 0.5 -2.1 6.3 4.2 0.8 3.2 0.15042
## 405 1.1 3.7 2.8 0.5 4.2 0.8 -2.1 3.2 6.3 0.05595
## 406 1.1 3.7 2.8 0.5 4.2 3.2 -2.1 0.8 6.3 0.10772
## 407 1.1 3.7 2.8 0.5 4.2 6.3 -2.1 0.8 3.2 1.21444
## 408 1.1 3.7 2.8 0.5 0.8 3.2 -2.1 4.2 6.3 0.18415
## 409 1.1 3.7 2.8 0.5 0.8 6.3 -2.1 4.2 3.2 0.07387
## 410 1.1 3.7 2.8 0.5 3.2 6.3 -2.1 4.2 0.8 0.64860
## 411 1.1 3.7 2.8 -2.1 4.2 0.8 0.5 3.2 6.3 0.64860
## 412 1.1 3.7 2.8 -2.1 4.2 3.2 0.5 0.8 6.3 0.07387
## 413 1.1 3.7 2.8 -2.1 4.2 6.3 0.5 0.8 3.2 0.18415
## 414 1.1 3.7 2.8 -2.1 0.8 3.2 0.5 4.2 6.3 1.21444
## 415 1.1 3.7 2.8 -2.1 0.8 6.3 0.5 4.2 3.2 0.10772
## 416 1.1 3.7 2.8 -2.1 3.2 6.3 0.5 4.2 0.8 0.05595
## 417 1.1 3.7 2.8 4.2 0.8 3.2 0.5 -2.1 6.3 0.15042
## 418 1.1 3.7 2.8 4.2 0.8 6.3 0.5 -2.1 3.2 1.45497
## 419 1.1 3.7 2.8 4.2 3.2 6.3 0.5 -2.1 0.8 7.80609
## 420 1.1 3.7 2.8 0.8 3.2 6.3 0.5 -2.1 4.2 0.78799
## 421 1.1 3.7 6.3 0.5 -2.1 4.2 0.8 3.2 2.8 0.97975
## 422 1.1 3.7 6.3 0.5 -2.1 0.8 4.2 3.2 2.8 4.46929
## 423 1.1 3.7 6.3 0.5 -2.1 3.2 4.2 0.8 2.8 1.39274
## 424 1.1 3.7 6.3 0.5 -2.1 2.8 4.2 0.8 3.2 1.63703
## 425 1.1 3.7 6.3 0.5 4.2 0.8 -2.1 3.2 2.8 0.72580
## 426 1.1 3.7 6.3 0.5 4.2 3.2 -2.1 0.8 2.8 1.44867
## 427 1.1 3.7 6.3 0.5 4.2 2.8 -2.1 0.8 3.2 1.24287
## 428 1.1 3.7 6.3 0.5 0.8 3.2 -2.1 4.2 2.8 0.68834
## 429 1.1 3.7 6.3 0.5 0.8 2.8 -2.1 4.2 3.2 0.70822
## 430 1.1 3.7 6.3 0.5 3.2 2.8 -2.1 4.2 0.8 0.89731
## 431 1.1 3.7 6.3 -2.1 4.2 0.8 0.5 3.2 2.8 0.89731
## 432 1.1 3.7 6.3 -2.1 4.2 3.2 0.5 0.8 2.8 0.70822
## 433 1.1 3.7 6.3 -2.1 4.2 2.8 0.5 0.8 3.2 0.68834
## 434 1.1 3.7 6.3 -2.1 0.8 3.2 0.5 4.2 2.8 1.24287
## 435 1.1 3.7 6.3 -2.1 0.8 2.8 0.5 4.2 3.2 1.44867
## 436 1.1 3.7 6.3 -2.1 3.2 2.8 0.5 4.2 0.8 0.72580
## 437 1.1 3.7 6.3 4.2 0.8 3.2 0.5 -2.1 2.8 1.63703
## 438 1.1 3.7 6.3 4.2 0.8 2.8 0.5 -2.1 3.2 1.39274
## 439 1.1 3.7 6.3 4.2 3.2 2.8 0.5 -2.1 0.8 4.46929
## 440 1.1 3.7 6.3 0.8 3.2 2.8 0.5 -2.1 4.2 0.97975
## 441 1.1 0.8 3.2 0.5 -2.1 4.2 3.7 2.8 6.3 1.87963
## 442 1.1 0.8 3.2 0.5 -2.1 3.7 4.2 2.8 6.3 2.53622
## 443 1.1 0.8 3.2 0.5 -2.1 2.8 4.2 3.7 6.3 4.62452
## 444 1.1 0.8 3.2 0.5 -2.1 6.3 4.2 3.7 2.8 0.54346
## 445 1.1 0.8 3.2 0.5 4.2 3.7 -2.1 2.8 6.3 0.11652
## 446 1.1 0.8 3.2 0.5 4.2 2.8 -2.1 3.7 6.3 0.09679
## 447 1.1 0.8 3.2 0.5 4.2 6.3 -2.1 3.7 2.8 0.65466
## 448 1.1 0.8 3.2 0.5 3.7 2.8 -2.1 4.2 6.3 0.11652
## 449 1.1 0.8 3.2 0.5 3.7 6.3 -2.1 4.2 2.8 0.47851
## 450 1.1 0.8 3.2 0.5 2.8 6.3 -2.1 4.2 3.7 0.26055
## 451 1.1 0.8 3.2 -2.1 4.2 3.7 0.5 2.8 6.3 0.26055
## 452 1.1 0.8 3.2 -2.1 4.2 2.8 0.5 3.7 6.3 0.47851
## 453 1.1 0.8 3.2 -2.1 4.2 6.3 0.5 3.7 2.8 0.11652
## 454 1.1 0.8 3.2 -2.1 3.7 2.8 0.5 4.2 6.3 0.65466
## 455 1.1 0.8 3.2 -2.1 3.7 6.3 0.5 4.2 2.8 0.09679
## 456 1.1 0.8 3.2 -2.1 2.8 6.3 0.5 4.2 3.7 0.11652
## 457 1.1 0.8 3.2 4.2 3.7 2.8 0.5 -2.1 6.3 0.54346
## 458 1.1 0.8 3.2 4.2 3.7 6.3 0.5 -2.1 2.8 4.62452
## 459 1.1 0.8 3.2 4.2 2.8 6.3 0.5 -2.1 3.7 2.53622
## 460 1.1 0.8 3.2 3.7 2.8 6.3 0.5 -2.1 4.2 1.87963
## 461 1.1 0.8 2.8 0.5 -2.1 4.2 3.7 3.2 6.3 2.25722
## 462 1.1 0.8 2.8 0.5 -2.1 3.7 4.2 3.2 6.3 3.06057
## 463 1.1 0.8 2.8 0.5 -2.1 3.2 4.2 3.7 6.3 4.27189
## 464 1.1 0.8 2.8 0.5 -2.1 6.3 4.2 3.7 3.2 0.68587
## 465 1.1 0.8 2.8 0.5 4.2 3.7 -2.1 3.2 6.3 0.15765
## 466 1.1 0.8 2.8 0.5 4.2 3.2 -2.1 3.7 6.3 0.14637
## 467 1.1 0.8 2.8 0.5 4.2 6.3 -2.1 3.7 3.2 0.64739
## 468 1.1 0.8 2.8 0.5 3.7 3.2 -2.1 4.2 6.3 0.15765
## 469 1.1 0.8 2.8 0.5 3.7 6.3 -2.1 4.2 3.2 0.48291
## 470 1.1 0.8 2.8 0.5 3.2 6.3 -2.1 4.2 3.7 0.35805
## 471 1.1 0.8 2.8 -2.1 4.2 3.7 0.5 3.2 6.3 0.35805
## 472 1.1 0.8 2.8 -2.1 4.2 3.2 0.5 3.7 6.3 0.48291
## 473 1.1 0.8 2.8 -2.1 4.2 6.3 0.5 3.7 3.2 0.15765
## 474 1.1 0.8 2.8 -2.1 3.7 3.2 0.5 4.2 6.3 0.64739
## 475 1.1 0.8 2.8 -2.1 3.7 6.3 0.5 4.2 3.2 0.14637
## 476 1.1 0.8 2.8 -2.1 3.2 6.3 0.5 4.2 3.7 0.15765
## 477 1.1 0.8 2.8 4.2 3.7 3.2 0.5 -2.1 6.3 0.68587
## 478 1.1 0.8 2.8 4.2 3.7 6.3 0.5 -2.1 3.2 4.27189
## 479 1.1 0.8 2.8 4.2 3.2 6.3 0.5 -2.1 3.7 3.06057
## 480 1.1 0.8 2.8 3.7 3.2 6.3 0.5 -2.1 4.2 2.25722
## 481 1.1 0.8 6.3 0.5 -2.1 4.2 3.7 3.2 2.8 0.70760
## 482 1.1 0.8 6.3 0.5 -2.1 3.7 4.2 3.2 2.8 0.96113
## 483 1.1 0.8 6.3 0.5 -2.1 3.2 4.2 3.7 2.8 1.29335
## 484 1.1 0.8 6.3 0.5 -2.1 2.8 4.2 3.7 3.2 1.63703
## 485 1.1 0.8 6.3 0.5 4.2 3.7 -2.1 3.2 2.8 0.28979
## 486 1.1 0.8 6.3 0.5 4.2 3.2 -2.1 3.7 2.8 0.19431
## 487 1.1 0.8 6.3 0.5 4.2 2.8 -2.1 3.7 3.2 0.13785
## 488 1.1 0.8 6.3 0.5 3.7 3.2 -2.1 4.2 2.8 0.12626
## 489 1.1 0.8 6.3 0.5 3.7 2.8 -2.1 4.2 3.2 0.08940
## 490 1.1 0.8 6.3 0.5 3.2 2.8 -2.1 4.2 3.7 0.06360
## 491 1.1 0.8 6.3 -2.1 4.2 3.7 0.5 3.2 2.8 0.06360
## 492 1.1 0.8 6.3 -2.1 4.2 3.2 0.5 3.7 2.8 0.08940
## 493 1.1 0.8 6.3 -2.1 4.2 2.8 0.5 3.7 3.2 0.12626
## 494 1.1 0.8 6.3 -2.1 3.7 3.2 0.5 4.2 2.8 0.13785
## 495 1.1 0.8 6.3 -2.1 3.7 2.8 0.5 4.2 3.2 0.19431
## 496 1.1 0.8 6.3 -2.1 3.2 2.8 0.5 4.2 3.7 0.28979
## 497 1.1 0.8 6.3 4.2 3.7 3.2 0.5 -2.1 2.8 1.63703
## 498 1.1 0.8 6.3 4.2 3.7 2.8 0.5 -2.1 3.2 1.29335
## 499 1.1 0.8 6.3 4.2 3.2 2.8 0.5 -2.1 3.7 0.96113
## 500 1.1 0.8 6.3 3.7 3.2 2.8 0.5 -2.1 4.2 0.70760
## 501 1.1 3.2 2.8 0.5 -2.1 4.2 3.7 0.8 6.3 0.89524
## 502 1.1 3.2 2.8 0.5 -2.1 3.7 4.2 0.8 6.3 1.22009
## 503 1.1 3.2 2.8 0.5 -2.1 0.8 4.2 3.7 6.3 9.89514
## 504 1.1 3.2 2.8 0.5 -2.1 6.3 4.2 3.7 0.8 0.17542
## 505 1.1 3.2 2.8 0.5 4.2 3.7 -2.1 0.8 6.3 0.12537
## 506 1.1 3.2 2.8 0.5 4.2 0.8 -2.1 3.7 6.3 0.06233
## 507 1.1 3.2 2.8 0.5 4.2 6.3 -2.1 3.7 0.8 1.01459
## 508 1.1 3.2 2.8 0.5 3.7 0.8 -2.1 4.2 6.3 0.12537
## 509 1.1 3.2 2.8 0.5 3.7 6.3 -2.1 4.2 0.8 0.73845
## 510 1.1 3.2 2.8 0.5 0.8 6.3 -2.1 4.2 3.7 0.03572
## 511 1.1 3.2 2.8 -2.1 4.2 3.7 0.5 0.8 6.3 0.03572
## 512 1.1 3.2 2.8 -2.1 4.2 0.8 0.5 3.7 6.3 0.73845
## 513 1.1 3.2 2.8 -2.1 4.2 6.3 0.5 3.7 0.8 0.12537
## 514 1.1 3.2 2.8 -2.1 3.7 0.8 0.5 4.2 6.3 1.01459
## 515 1.1 3.2 2.8 -2.1 3.7 6.3 0.5 4.2 0.8 0.06233
## 516 1.1 3.2 2.8 -2.1 0.8 6.3 0.5 4.2 3.7 0.12537
## 517 1.1 3.2 2.8 4.2 3.7 0.8 0.5 -2.1 6.3 0.17542
## 518 1.1 3.2 2.8 4.2 3.7 6.3 0.5 -2.1 0.8 9.89514
## 519 1.1 3.2 2.8 4.2 0.8 6.3 0.5 -2.1 3.7 1.22009
## 520 1.1 3.2 2.8 3.7 0.8 6.3 0.5 -2.1 4.2 0.89524
## 521 1.1 3.2 6.3 0.5 -2.1 4.2 3.7 0.8 2.8 0.84758
## 522 1.1 3.2 6.3 0.5 -2.1 3.7 4.2 0.8 2.8 1.03076
## 523 1.1 3.2 6.3 0.5 -2.1 0.8 4.2 3.7 2.8 4.41894
## 524 1.1 3.2 6.3 0.5 -2.1 2.8 4.2 3.7 0.8 1.52270
## 525 1.1 3.2 6.3 0.5 4.2 3.7 -2.1 0.8 2.8 1.33051
## 526 1.1 3.2 6.3 0.5 4.2 0.8 -2.1 3.7 2.8 0.52587
## 527 1.1 3.2 6.3 0.5 4.2 2.8 -2.1 3.7 0.8 0.91464
## 528 1.1 3.2 6.3 0.5 3.7 0.8 -2.1 4.2 2.8 0.50901
## 529 1.1 3.2 6.3 0.5 3.7 2.8 -2.1 4.2 0.8 0.76081
## 530 1.1 3.2 6.3 0.5 0.8 2.8 -2.1 4.2 3.7 0.54975
## 531 1.1 3.2 6.3 -2.1 4.2 3.7 0.5 0.8 2.8 0.54975
## 532 1.1 3.2 6.3 -2.1 4.2 0.8 0.5 3.7 2.8 0.76081
## 533 1.1 3.2 6.3 -2.1 4.2 2.8 0.5 3.7 0.8 0.50901
## 534 1.1 3.2 6.3 -2.1 3.7 0.8 0.5 4.2 2.8 0.91464
## 535 1.1 3.2 6.3 -2.1 3.7 2.8 0.5 4.2 0.8 0.52587
## 536 1.1 3.2 6.3 -2.1 0.8 2.8 0.5 4.2 3.7 1.33051
## 537 1.1 3.2 6.3 4.2 3.7 0.8 0.5 -2.1 2.8 1.52270
## 538 1.1 3.2 6.3 4.2 3.7 2.8 0.5 -2.1 0.8 4.41894
## 539 1.1 3.2 6.3 4.2 0.8 2.8 0.5 -2.1 3.7 1.03076
## 540 1.1 3.2 6.3 3.7 0.8 2.8 0.5 -2.1 4.2 0.84758
## 541 1.1 2.8 6.3 0.5 -2.1 4.2 3.7 0.8 3.2 0.77112
## 542 1.1 2.8 6.3 0.5 -2.1 3.7 4.2 0.8 3.2 0.96113
## 543 1.1 2.8 6.3 0.5 -2.1 0.8 4.2 3.7 3.2 4.46929
## 544 1.1 2.8 6.3 0.5 -2.1 3.2 4.2 3.7 0.8 1.21121
## 545 1.1 2.8 6.3 0.5 4.2 3.7 -2.1 0.8 3.2 1.05303
## 546 1.1 2.8 6.3 0.5 4.2 0.8 -2.1 3.7 3.2 0.39954
## 547 1.1 2.8 6.3 0.5 4.2 3.2 -2.1 3.7 0.8 0.84087
## 548 1.1 2.8 6.3 0.5 3.7 0.8 -2.1 4.2 3.2 0.39429
## 549 1.1 2.8 6.3 0.5 3.7 3.2 -2.1 4.2 0.8 0.68032
## 550 1.1 2.8 6.3 0.5 0.8 3.2 -2.1 4.2 3.7 0.41536
## 551 1.1 2.8 6.3 -2.1 4.2 3.7 0.5 0.8 3.2 0.41536
## 552 1.1 2.8 6.3 -2.1 4.2 0.8 0.5 3.7 3.2 0.68032
## 553 1.1 2.8 6.3 -2.1 4.2 3.2 0.5 3.7 0.8 0.39429
## 554 1.1 2.8 6.3 -2.1 3.7 0.8 0.5 4.2 3.2 0.84087
## 555 1.1 2.8 6.3 -2.1 3.7 3.2 0.5 4.2 0.8 0.39954
## 556 1.1 2.8 6.3 -2.1 0.8 3.2 0.5 4.2 3.7 1.05303
## 557 1.1 2.8 6.3 4.2 3.7 0.8 0.5 -2.1 3.2 1.21121
## 558 1.1 2.8 6.3 4.2 3.7 3.2 0.5 -2.1 0.8 4.46929
## 559 1.1 2.8 6.3 4.2 0.8 3.2 0.5 -2.1 3.7 0.96113
## 560 1.1 2.8 6.3 3.7 0.8 3.2 0.5 -2.1 4.2 0.77112
## 561 0.5 -2.1 4.2 1.1 3.7 0.8 3.2 2.8 6.3 1.51899
## 562 0.5 -2.1 4.2 1.1 3.7 3.2 0.8 2.8 6.3 0.72895
## 563 0.5 -2.1 4.2 1.1 3.7 2.8 0.8 3.2 6.3 0.78799
## 564 0.5 -2.1 4.2 1.1 3.7 6.3 0.8 3.2 2.8 0.97975
## 565 0.5 -2.1 4.2 1.1 0.8 3.2 3.7 2.8 6.3 1.87963
## 566 0.5 -2.1 4.2 1.1 0.8 2.8 3.7 3.2 6.3 2.25722
## 567 0.5 -2.1 4.2 1.1 0.8 6.3 3.7 3.2 2.8 0.70760
## 568 0.5 -2.1 4.2 1.1 3.2 2.8 3.7 0.8 6.3 0.89524
## 569 0.5 -2.1 4.2 1.1 3.2 6.3 3.7 0.8 2.8 0.84758
## 570 0.5 -2.1 4.2 1.1 2.8 6.3 3.7 0.8 3.2 0.77112
## 571 0.5 -2.1 4.2 3.7 0.8 3.2 1.1 2.8 6.3 0.77112
## 572 0.5 -2.1 4.2 3.7 0.8 2.8 1.1 3.2 6.3 0.84758
## 573 0.5 -2.1 4.2 3.7 0.8 6.3 1.1 3.2 2.8 0.89524
## 574 0.5 -2.1 4.2 3.7 3.2 2.8 1.1 0.8 6.3 0.70760
## 575 0.5 -2.1 4.2 3.7 3.2 6.3 1.1 0.8 2.8 2.25722
## 576 0.5 -2.1 4.2 3.7 2.8 6.3 1.1 0.8 3.2 1.87963
## 577 0.5 -2.1 4.2 0.8 3.2 2.8 1.1 3.7 6.3 0.97975
## 578 0.5 -2.1 4.2 0.8 3.2 6.3 1.1 3.7 2.8 0.78799
## 579 0.5 -2.1 4.2 0.8 2.8 6.3 1.1 3.7 3.2 0.72895
## 580 0.5 -2.1 4.2 3.2 2.8 6.3 1.1 3.7 0.8 1.51899
## 581 0.5 -2.1 3.7 1.1 4.2 0.8 3.2 2.8 6.3 1.68739
## 582 0.5 -2.1 3.7 1.1 4.2 3.2 0.8 2.8 6.3 0.92511
## 583 0.5 -2.1 3.7 1.1 4.2 2.8 0.8 3.2 6.3 0.97616
## 584 0.5 -2.1 3.7 1.1 4.2 6.3 0.8 3.2 2.8 1.33222
## 585 0.5 -2.1 3.7 1.1 0.8 3.2 4.2 2.8 6.3 2.53622
## 586 0.5 -2.1 3.7 1.1 0.8 2.8 4.2 3.2 6.3 3.06057
## 587 0.5 -2.1 3.7 1.1 0.8 6.3 4.2 3.2 2.8 0.96113
## 588 0.5 -2.1 3.7 1.1 3.2 2.8 4.2 0.8 6.3 1.22009
## 589 0.5 -2.1 3.7 1.1 3.2 6.3 4.2 0.8 2.8 1.03076
## 590 0.5 -2.1 3.7 1.1 2.8 6.3 4.2 0.8 3.2 0.96113
## 591 0.5 -2.1 3.7 4.2 0.8 3.2 1.1 2.8 6.3 0.96113
## 592 0.5 -2.1 3.7 4.2 0.8 2.8 1.1 3.2 6.3 1.03076
## 593 0.5 -2.1 3.7 4.2 0.8 6.3 1.1 3.2 2.8 1.22009
## 594 0.5 -2.1 3.7 4.2 3.2 2.8 1.1 0.8 6.3 0.96113
## 595 0.5 -2.1 3.7 4.2 3.2 6.3 1.1 0.8 2.8 3.06057
## 596 0.5 -2.1 3.7 4.2 2.8 6.3 1.1 0.8 3.2 2.53622
## 597 0.5 -2.1 3.7 0.8 3.2 2.8 1.1 4.2 6.3 1.33222
## 598 0.5 -2.1 3.7 0.8 3.2 6.3 1.1 4.2 2.8 0.97616
## 599 0.5 -2.1 3.7 0.8 2.8 6.3 1.1 4.2 3.2 0.92511
## 600 0.5 -2.1 3.7 3.2 2.8 6.3 1.1 4.2 0.8 1.68739
## 601 0.5 -2.1 0.8 1.1 4.2 3.7 3.2 2.8 6.3 5.16772
## 602 0.5 -2.1 0.8 1.1 4.2 3.2 3.7 2.8 6.3 5.78723
## 603 0.5 -2.1 0.8 1.1 4.2 2.8 3.7 3.2 6.3 6.50022
## 604 0.5 -2.1 0.8 1.1 4.2 6.3 3.7 3.2 2.8 4.65103
## 605 0.5 -2.1 0.8 1.1 3.7 3.2 4.2 2.8 6.3 6.71832
## 606 0.5 -2.1 0.8 1.1 3.7 2.8 4.2 3.2 6.3 7.80609
## 607 0.5 -2.1 0.8 1.1 3.7 6.3 4.2 3.2 2.8 4.46929
## 608 0.5 -2.1 0.8 1.1 3.2 2.8 4.2 3.7 6.3 9.89514
## 609 0.5 -2.1 0.8 1.1 3.2 6.3 4.2 3.7 2.8 4.41894
## 610 0.5 -2.1 0.8 1.1 2.8 6.3 4.2 3.7 3.2 4.46929
## 611 0.5 -2.1 0.8 4.2 3.7 3.2 1.1 2.8 6.3 4.46929
## 612 0.5 -2.1 0.8 4.2 3.7 2.8 1.1 3.2 6.3 4.41894
## 613 0.5 -2.1 0.8 4.2 3.7 6.3 1.1 3.2 2.8 9.89514
## 614 0.5 -2.1 0.8 4.2 3.2 2.8 1.1 3.7 6.3 4.46929
## 615 0.5 -2.1 0.8 4.2 3.2 6.3 1.1 3.7 2.8 7.80609
## 616 0.5 -2.1 0.8 4.2 2.8 6.3 1.1 3.7 3.2 6.71832
## 617 0.5 -2.1 0.8 3.7 3.2 2.8 1.1 4.2 6.3 4.65103
## 618 0.5 -2.1 0.8 3.7 3.2 6.3 1.1 4.2 2.8 6.50022
## 619 0.5 -2.1 0.8 3.7 2.8 6.3 1.1 4.2 3.2 5.78723
## 620 0.5 -2.1 0.8 3.2 2.8 6.3 1.1 4.2 3.7 5.16772
## 621 0.5 -2.1 3.2 1.1 4.2 3.7 0.8 2.8 6.3 1.18241
## 622 0.5 -2.1 3.2 1.1 4.2 0.8 3.7 2.8 6.3 2.29007
## 623 0.5 -2.1 3.2 1.1 4.2 2.8 3.7 0.8 6.3 1.31523
## 624 0.5 -2.1 3.2 1.1 4.2 6.3 3.7 0.8 2.8 1.56586
## 625 0.5 -2.1 3.2 1.1 3.7 0.8 4.2 2.8 6.3 2.79111
## 626 0.5 -2.1 3.2 1.1 3.7 2.8 4.2 0.8 6.3 1.45497
## 627 0.5 -2.1 3.2 1.1 3.7 6.3 4.2 0.8 2.8 1.39274
## 628 0.5 -2.1 3.2 1.1 0.8 2.8 4.2 3.7 6.3 4.27189
## 629 0.5 -2.1 3.2 1.1 0.8 6.3 4.2 3.7 2.8 1.29335
## 630 0.5 -2.1 3.2 1.1 2.8 6.3 4.2 3.7 0.8 1.21121
## 631 0.5 -2.1 3.2 4.2 3.7 0.8 1.1 2.8 6.3 1.21121
## 632 0.5 -2.1 3.2 4.2 3.7 2.8 1.1 0.8 6.3 1.29335
## 633 0.5 -2.1 3.2 4.2 3.7 6.3 1.1 0.8 2.8 4.27189
## 634 0.5 -2.1 3.2 4.2 0.8 2.8 1.1 3.7 6.3 1.39274
## 635 0.5 -2.1 3.2 4.2 0.8 6.3 1.1 3.7 2.8 1.45497
## 636 0.5 -2.1 3.2 4.2 2.8 6.3 1.1 3.7 0.8 2.79111
## 637 0.5 -2.1 3.2 3.7 0.8 2.8 1.1 4.2 6.3 1.56586
## 638 0.5 -2.1 3.2 3.7 0.8 6.3 1.1 4.2 2.8 1.31523
## 639 0.5 -2.1 3.2 3.7 2.8 6.3 1.1 4.2 0.8 2.29007
## 640 0.5 -2.1 3.2 0.8 2.8 6.3 1.1 4.2 3.7 1.18241
## 641 0.5 -2.1 2.8 1.1 4.2 3.7 0.8 3.2 6.3 1.47854
## 642 0.5 -2.1 2.8 1.1 4.2 0.8 3.7 3.2 6.3 2.95402
## 643 0.5 -2.1 2.8 1.1 4.2 3.2 3.7 0.8 6.3 1.56207
## 644 0.5 -2.1 2.8 1.1 4.2 6.3 3.7 0.8 3.2 1.80926
## 645 0.5 -2.1 2.8 1.1 3.7 0.8 4.2 3.2 6.3 3.63612
## 646 0.5 -2.1 2.8 1.1 3.7 3.2 4.2 0.8 6.3 1.69840
## 647 0.5 -2.1 2.8 1.1 3.7 6.3 4.2 0.8 3.2 1.63703
## 648 0.5 -2.1 2.8 1.1 0.8 3.2 4.2 3.7 6.3 4.62452
## 649 0.5 -2.1 2.8 1.1 0.8 6.3 4.2 3.7 3.2 1.63703
## 650 0.5 -2.1 2.8 1.1 3.2 6.3 4.2 3.7 0.8 1.52270
## 651 0.5 -2.1 2.8 4.2 3.7 0.8 1.1 3.2 6.3 1.52270
## 652 0.5 -2.1 2.8 4.2 3.7 3.2 1.1 0.8 6.3 1.63703
## 653 0.5 -2.1 2.8 4.2 3.7 6.3 1.1 0.8 3.2 4.62452
## 654 0.5 -2.1 2.8 4.2 0.8 3.2 1.1 3.7 6.3 1.63703
## 655 0.5 -2.1 2.8 4.2 0.8 6.3 1.1 3.7 3.2 1.69840
## 656 0.5 -2.1 2.8 4.2 3.2 6.3 1.1 3.7 0.8 3.63612
## 657 0.5 -2.1 2.8 3.7 0.8 3.2 1.1 4.2 6.3 1.80926
## 658 0.5 -2.1 2.8 3.7 0.8 6.3 1.1 4.2 3.2 1.56207
## 659 0.5 -2.1 2.8 3.7 3.2 6.3 1.1 4.2 0.8 2.95402
## 660 0.5 -2.1 2.8 0.8 3.2 6.3 1.1 4.2 3.7 1.47854
## 661 0.5 -2.1 6.3 1.1 4.2 3.7 0.8 3.2 2.8 0.20175
## 662 0.5 -2.1 6.3 1.1 4.2 0.8 3.7 3.2 2.8 0.29916
## 663 0.5 -2.1 6.3 1.1 4.2 3.2 3.7 0.8 2.8 0.16264
## 664 0.5 -2.1 6.3 1.1 4.2 2.8 3.7 0.8 3.2 0.14817
## 665 0.5 -2.1 6.3 1.1 3.7 0.8 4.2 3.2 2.8 0.40374
## 666 0.5 -2.1 6.3 1.1 3.7 3.2 4.2 0.8 2.8 0.14682
## 667 0.5 -2.1 6.3 1.1 3.7 2.8 4.2 0.8 3.2 0.15042
## 668 0.5 -2.1 6.3 1.1 0.8 3.2 4.2 3.7 2.8 0.54346
## 669 0.5 -2.1 6.3 1.1 0.8 2.8 4.2 3.7 3.2 0.68587
## 670 0.5 -2.1 6.3 1.1 3.2 2.8 4.2 3.7 0.8 0.17542
## 671 0.5 -2.1 6.3 4.2 3.7 0.8 1.1 3.2 2.8 0.17542
## 672 0.5 -2.1 6.3 4.2 3.7 3.2 1.1 0.8 2.8 0.68587
## 673 0.5 -2.1 6.3 4.2 3.7 2.8 1.1 0.8 3.2 0.54346
## 674 0.5 -2.1 6.3 4.2 0.8 3.2 1.1 3.7 2.8 0.15042
## 675 0.5 -2.1 6.3 4.2 0.8 2.8 1.1 3.7 3.2 0.14682
## 676 0.5 -2.1 6.3 4.2 3.2 2.8 1.1 3.7 0.8 0.40374
## 677 0.5 -2.1 6.3 3.7 0.8 3.2 1.1 4.2 2.8 0.14817
## 678 0.5 -2.1 6.3 3.7 0.8 2.8 1.1 4.2 3.2 0.16264
## 679 0.5 -2.1 6.3 3.7 3.2 2.8 1.1 4.2 0.8 0.29916
## 680 0.5 -2.1 6.3 0.8 3.2 2.8 1.1 4.2 3.7 0.20175
## 681 0.5 4.2 3.7 1.1 -2.1 0.8 3.2 2.8 6.3 3.77918
## 682 0.5 4.2 3.7 1.1 -2.1 3.2 0.8 2.8 6.3 0.88150
## 683 0.5 4.2 3.7 1.1 -2.1 2.8 0.8 3.2 6.3 1.11670
## 684 0.5 4.2 3.7 1.1 -2.1 6.3 0.8 3.2 2.8 0.10159
## 685 0.5 4.2 3.7 1.1 0.8 3.2 -2.1 2.8 6.3 0.11652
## 686 0.5 4.2 3.7 1.1 0.8 2.8 -2.1 3.2 6.3 0.15765
## 687 0.5 4.2 3.7 1.1 0.8 6.3 -2.1 3.2 2.8 0.28979
## 688 0.5 4.2 3.7 1.1 3.2 2.8 -2.1 0.8 6.3 0.12537
## 689 0.5 4.2 3.7 1.1 3.2 6.3 -2.1 0.8 2.8 1.33051
## 690 0.5 4.2 3.7 1.1 2.8 6.3 -2.1 0.8 3.2 1.05303
## 691 0.5 4.2 3.7 -2.1 0.8 3.2 1.1 2.8 6.3 1.05303
## 692 0.5 4.2 3.7 -2.1 0.8 2.8 1.1 3.2 6.3 1.33051
## 693 0.5 4.2 3.7 -2.1 0.8 6.3 1.1 3.2 2.8 0.12537
## 694 0.5 4.2 3.7 -2.1 3.2 2.8 1.1 0.8 6.3 0.28979
## 695 0.5 4.2 3.7 -2.1 3.2 6.3 1.1 0.8 2.8 0.15765
## 696 0.5 4.2 3.7 -2.1 2.8 6.3 1.1 0.8 3.2 0.11652
## 697 0.5 4.2 3.7 0.8 3.2 2.8 1.1 -2.1 6.3 0.10159
## 698 0.5 4.2 3.7 0.8 3.2 6.3 1.1 -2.1 2.8 1.11670
## 699 0.5 4.2 3.7 0.8 2.8 6.3 1.1 -2.1 3.2 0.88150
## 700 0.5 4.2 3.7 3.2 2.8 6.3 1.1 -2.1 0.8 3.77918
## 701 0.5 4.2 0.8 1.1 -2.1 3.7 3.2 2.8 6.3 1.49224
## 702 0.5 4.2 0.8 1.1 -2.1 3.2 3.7 2.8 6.3 2.00842
## 703 0.5 4.2 0.8 1.1 -2.1 2.8 3.7 3.2 6.3 2.56561
## 704 0.5 4.2 0.8 1.1 -2.1 6.3 3.7 3.2 2.8 0.27560
## 705 0.5 4.2 0.8 1.1 3.7 3.2 -2.1 2.8 6.3 0.06617
## 706 0.5 4.2 0.8 1.1 3.7 2.8 -2.1 3.2 6.3 0.05595
## 707 0.5 4.2 0.8 1.1 3.7 6.3 -2.1 3.2 2.8 0.72580
## 708 0.5 4.2 0.8 1.1 3.2 2.8 -2.1 3.7 6.3 0.06233
## 709 0.5 4.2 0.8 1.1 3.2 6.3 -2.1 3.7 2.8 0.52587
## 710 0.5 4.2 0.8 1.1 2.8 6.3 -2.1 3.7 3.2 0.39954
## 711 0.5 4.2 0.8 -2.1 3.7 3.2 1.1 2.8 6.3 0.39954
## 712 0.5 4.2 0.8 -2.1 3.7 2.8 1.1 3.2 6.3 0.52587
## 713 0.5 4.2 0.8 -2.1 3.7 6.3 1.1 3.2 2.8 0.06233
## 714 0.5 4.2 0.8 -2.1 3.2 2.8 1.1 3.7 6.3 0.72580
## 715 0.5 4.2 0.8 -2.1 3.2 6.3 1.1 3.7 2.8 0.05595
## 716 0.5 4.2 0.8 -2.1 2.8 6.3 1.1 3.7 3.2 0.06617
## 717 0.5 4.2 0.8 3.7 3.2 2.8 1.1 -2.1 6.3 0.27560
## 718 0.5 4.2 0.8 3.7 3.2 6.3 1.1 -2.1 2.8 2.56561
## 719 0.5 4.2 0.8 3.7 2.8 6.3 1.1 -2.1 3.2 2.00842
## 720 0.5 4.2 0.8 3.2 2.8 6.3 1.1 -2.1 3.7 1.49224
## 721 0.5 4.2 3.2 1.1 -2.1 3.7 0.8 2.8 6.3 0.69577
## 722 0.5 4.2 3.2 1.1 -2.1 0.8 3.7 2.8 6.3 4.27189
## 723 0.5 4.2 3.2 1.1 -2.1 2.8 3.7 0.8 6.3 1.21121
## 724 0.5 4.2 3.2 1.1 -2.1 6.3 3.7 0.8 2.8 0.07774
## 725 0.5 4.2 3.2 1.1 3.7 0.8 -2.1 2.8 6.3 0.05595
## 726 0.5 4.2 3.2 1.1 3.7 2.8 -2.1 0.8 6.3 0.10772
## 727 0.5 4.2 3.2 1.1 3.7 6.3 -2.1 0.8 2.8 1.44867
## 728 0.5 4.2 3.2 1.1 0.8 2.8 -2.1 3.7 6.3 0.14637
## 729 0.5 4.2 3.2 1.1 0.8 6.3 -2.1 3.7 2.8 0.19431
## 730 0.5 4.2 3.2 1.1 2.8 6.3 -2.1 3.7 0.8 0.84087
## 731 0.5 4.2 3.2 -2.1 3.7 0.8 1.1 2.8 6.3 0.84087
## 732 0.5 4.2 3.2 -2.1 3.7 2.8 1.1 0.8 6.3 0.19431
## 733 0.5 4.2 3.2 -2.1 3.7 6.3 1.1 0.8 2.8 0.14637
## 734 0.5 4.2 3.2 -2.1 0.8 2.8 1.1 3.7 6.3 1.44867
## 735 0.5 4.2 3.2 -2.1 0.8 6.3 1.1 3.7 2.8 0.10772
## 736 0.5 4.2 3.2 -2.1 2.8 6.3 1.1 3.7 0.8 0.05595
## 737 0.5 4.2 3.2 3.7 0.8 2.8 1.1 -2.1 6.3 0.07774
## 738 0.5 4.2 3.2 3.7 0.8 6.3 1.1 -2.1 2.8 1.21121
## 739 0.5 4.2 3.2 3.7 2.8 6.3 1.1 -2.1 0.8 4.27189
## 740 0.5 4.2 3.2 0.8 2.8 6.3 1.1 -2.1 3.7 0.69577
## 741 0.5 4.2 2.8 1.1 -2.1 3.7 0.8 3.2 6.3 0.75631
## 742 0.5 4.2 2.8 1.1 -2.1 0.8 3.7 3.2 6.3 4.81954
## 743 0.5 4.2 2.8 1.1 -2.1 3.2 3.7 0.8 6.3 1.03520
## 744 0.5 4.2 2.8 1.1 -2.1 6.3 3.7 0.8 3.2 0.07430
## 745 0.5 4.2 2.8 1.1 3.7 0.8 -2.1 3.2 6.3 0.04749
## 746 0.5 4.2 2.8 1.1 3.7 3.2 -2.1 0.8 6.3 0.10948
## 747 0.5 4.2 2.8 1.1 3.7 6.3 -2.1 0.8 3.2 1.24287
## 748 0.5 4.2 2.8 1.1 0.8 3.2 -2.1 3.7 6.3 0.09679
## 749 0.5 4.2 2.8 1.1 0.8 6.3 -2.1 3.7 3.2 0.13785
## 750 0.5 4.2 2.8 1.1 3.2 6.3 -2.1 3.7 0.8 0.91464
## 751 0.5 4.2 2.8 -2.1 3.7 0.8 1.1 3.2 6.3 0.91464
## 752 0.5 4.2 2.8 -2.1 3.7 3.2 1.1 0.8 6.3 0.13785
## 753 0.5 4.2 2.8 -2.1 3.7 6.3 1.1 0.8 3.2 0.09679
## 754 0.5 4.2 2.8 -2.1 0.8 3.2 1.1 3.7 6.3 1.24287
## 755 0.5 4.2 2.8 -2.1 0.8 6.3 1.1 3.7 3.2 0.10948
## 756 0.5 4.2 2.8 -2.1 3.2 6.3 1.1 3.7 0.8 0.04749
## 757 0.5 4.2 2.8 3.7 0.8 3.2 1.1 -2.1 6.3 0.07430
## 758 0.5 4.2 2.8 3.7 0.8 6.3 1.1 -2.1 3.2 1.03520
## 759 0.5 4.2 2.8 3.7 3.2 6.3 1.1 -2.1 0.8 4.81954
## 760 0.5 4.2 2.8 0.8 3.2 6.3 1.1 -2.1 3.7 0.75631
## 761 0.5 4.2 6.3 1.1 -2.1 3.7 0.8 3.2 2.8 0.92021
## 762 0.5 4.2 6.3 1.1 -2.1 0.8 3.7 3.2 2.8 3.14003
## 763 0.5 4.2 6.3 1.1 -2.1 3.2 3.7 0.8 2.8 1.08765
## 764 0.5 4.2 6.3 1.1 -2.1 2.8 3.7 0.8 3.2 1.26176
## 765 0.5 4.2 6.3 1.1 3.7 0.8 -2.1 3.2 2.8 0.69143
## 766 0.5 4.2 6.3 1.1 3.7 3.2 -2.1 0.8 2.8 1.42097
## 767 0.5 4.2 6.3 1.1 3.7 2.8 -2.1 0.8 3.2 1.21444
## 768 0.5 4.2 6.3 1.1 0.8 3.2 -2.1 3.7 2.8 0.65466
## 769 0.5 4.2 6.3 1.1 0.8 2.8 -2.1 3.7 3.2 0.64739
## 770 0.5 4.2 6.3 1.1 3.2 2.8 -2.1 3.7 0.8 1.01459
## 771 0.5 4.2 6.3 -2.1 3.7 0.8 1.1 3.2 2.8 1.01459
## 772 0.5 4.2 6.3 -2.1 3.7 3.2 1.1 0.8 2.8 0.64739
## 773 0.5 4.2 6.3 -2.1 3.7 2.8 1.1 0.8 3.2 0.65466
## 774 0.5 4.2 6.3 -2.1 0.8 3.2 1.1 3.7 2.8 1.21444
## 775 0.5 4.2 6.3 -2.1 0.8 2.8 1.1 3.7 3.2 1.42097
## 776 0.5 4.2 6.3 -2.1 3.2 2.8 1.1 3.7 0.8 0.69143
## 777 0.5 4.2 6.3 3.7 0.8 3.2 1.1 -2.1 2.8 1.26176
## 778 0.5 4.2 6.3 3.7 0.8 2.8 1.1 -2.1 3.2 1.08765
## 779 0.5 4.2 6.3 3.7 3.2 2.8 1.1 -2.1 0.8 3.14003
## 780 0.5 4.2 6.3 0.8 3.2 2.8 1.1 -2.1 3.7 0.92021
## 781 0.5 3.7 0.8 1.1 -2.1 4.2 3.2 2.8 6.3 1.38923
## 782 0.5 3.7 0.8 1.1 -2.1 3.2 4.2 2.8 6.3 2.49613
## 783 0.5 3.7 0.8 1.1 -2.1 2.8 4.2 3.2 6.3 3.20931
## 784 0.5 3.7 0.8 1.1 -2.1 6.3 4.2 3.2 2.8 0.39429
## 785 0.5 3.7 0.8 1.1 4.2 3.2 -2.1 2.8 6.3 0.13160
## 786 0.5 3.7 0.8 1.1 4.2 2.8 -2.1 3.2 6.3 0.11212
## 787 0.5 3.7 0.8 1.1 4.2 6.3 -2.1 3.2 2.8 0.92861
## 788 0.5 3.7 0.8 1.1 3.2 2.8 -2.1 4.2 6.3 0.12537
## 789 0.5 3.7 0.8 1.1 3.2 6.3 -2.1 4.2 2.8 0.50901
## 790 0.5 3.7 0.8 1.1 2.8 6.3 -2.1 4.2 3.2 0.39429
## 791 0.5 3.7 0.8 -2.1 4.2 3.2 1.1 2.8 6.3 0.39429
## 792 0.5 3.7 0.8 -2.1 4.2 2.8 1.1 3.2 6.3 0.50901
## 793 0.5 3.7 0.8 -2.1 4.2 6.3 1.1 3.2 2.8 0.12537
## 794 0.5 3.7 0.8 -2.1 3.2 2.8 1.1 4.2 6.3 0.92861
## 795 0.5 3.7 0.8 -2.1 3.2 6.3 1.1 4.2 2.8 0.11212
## 796 0.5 3.7 0.8 -2.1 2.8 6.3 1.1 4.2 3.2 0.13160
## 797 0.5 3.7 0.8 4.2 3.2 2.8 1.1 -2.1 6.3 0.39429
## 798 0.5 3.7 0.8 4.2 3.2 6.3 1.1 -2.1 2.8 3.20931
## 799 0.5 3.7 0.8 4.2 2.8 6.3 1.1 -2.1 3.2 2.49613
## 800 0.5 3.7 0.8 3.2 2.8 6.3 1.1 -2.1 4.2 1.38923
## 801 0.5 3.7 3.2 1.1 -2.1 4.2 0.8 2.8 6.3 0.55548
## 802 0.5 3.7 3.2 1.1 -2.1 0.8 4.2 2.8 6.3 4.98404
## 803 0.5 3.7 3.2 1.1 -2.1 2.8 4.2 0.8 6.3 1.35278
## 804 0.5 3.7 3.2 1.1 -2.1 6.3 4.2 0.8 2.8 0.07559
## 805 0.5 3.7 3.2 1.1 4.2 0.8 -2.1 2.8 6.3 0.01824
## 806 0.5 3.7 3.2 1.1 4.2 2.8 -2.1 0.8 6.3 0.11212
## 807 0.5 3.7 3.2 1.1 4.2 6.3 -2.1 0.8 2.8 1.62146
## 808 0.5 3.7 3.2 1.1 0.8 2.8 -2.1 4.2 6.3 0.15765
## 809 0.5 3.7 3.2 1.1 0.8 6.3 -2.1 4.2 2.8 0.12626
## 810 0.5 3.7 3.2 1.1 2.8 6.3 -2.1 4.2 0.8 0.68032
## 811 0.5 3.7 3.2 -2.1 4.2 0.8 1.1 2.8 6.3 0.68032
## 812 0.5 3.7 3.2 -2.1 4.2 2.8 1.1 0.8 6.3 0.12626
## 813 0.5 3.7 3.2 -2.1 4.2 6.3 1.1 0.8 2.8 0.15765
## 814 0.5 3.7 3.2 -2.1 0.8 2.8 1.1 4.2 6.3 1.62146
## 815 0.5 3.7 3.2 -2.1 0.8 6.3 1.1 4.2 2.8 0.11212
## 816 0.5 3.7 3.2 -2.1 2.8 6.3 1.1 4.2 0.8 0.01824
## 817 0.5 3.7 3.2 4.2 0.8 2.8 1.1 -2.1 6.3 0.07559
## 818 0.5 3.7 3.2 4.2 0.8 6.3 1.1 -2.1 2.8 1.35278
## 819 0.5 3.7 3.2 4.2 2.8 6.3 1.1 -2.1 0.8 4.98404
## 820 0.5 3.7 3.2 0.8 2.8 6.3 1.1 -2.1 4.2 0.55548
## 821 0.5 3.7 2.8 1.1 -2.1 4.2 0.8 3.2 6.3 0.62337
## 822 0.5 3.7 2.8 1.1 -2.1 0.8 4.2 3.2 6.3 5.78723
## 823 0.5 3.7 2.8 1.1 -2.1 3.2 4.2 0.8 6.3 1.18082
## 824 0.5 3.7 2.8 1.1 -2.1 6.3 4.2 0.8 3.2 0.08940
## 825 0.5 3.7 2.8 1.1 4.2 0.8 -2.1 3.2 6.3 0.01824
## 826 0.5 3.7 2.8 1.1 4.2 3.2 -2.1 0.8 6.3 0.13160
## 827 0.5 3.7 2.8 1.1 4.2 6.3 -2.1 0.8 3.2 1.41742
## 828 0.5 3.7 2.8 1.1 0.8 3.2 -2.1 4.2 6.3 0.11652
## 829 0.5 3.7 2.8 1.1 0.8 6.3 -2.1 4.2 3.2 0.08940
## 830 0.5 3.7 2.8 1.1 3.2 6.3 -2.1 4.2 0.8 0.76081
## 831 0.5 3.7 2.8 -2.1 4.2 0.8 1.1 3.2 6.3 0.76081
## 832 0.5 3.7 2.8 -2.1 4.2 3.2 1.1 0.8 6.3 0.08940
## 833 0.5 3.7 2.8 -2.1 4.2 6.3 1.1 0.8 3.2 0.11652
## 834 0.5 3.7 2.8 -2.1 0.8 3.2 1.1 4.2 6.3 1.41742
## 835 0.5 3.7 2.8 -2.1 0.8 6.3 1.1 4.2 3.2 0.13160
## 836 0.5 3.7 2.8 -2.1 3.2 6.3 1.1 4.2 0.8 0.01824
## 837 0.5 3.7 2.8 4.2 0.8 3.2 1.1 -2.1 6.3 0.08940
## 838 0.5 3.7 2.8 4.2 0.8 6.3 1.1 -2.1 3.2 1.18082
## 839 0.5 3.7 2.8 4.2 3.2 6.3 1.1 -2.1 0.8 5.78723
## 840 0.5 3.7 2.8 0.8 3.2 6.3 1.1 -2.1 4.2 0.62337
## 841 0.5 3.7 6.3 1.1 -2.1 4.2 0.8 3.2 2.8 0.66561
## 842 0.5 3.7 6.3 1.1 -2.1 0.8 4.2 3.2 2.8 3.07228
## 843 0.5 3.7 6.3 1.1 -2.1 3.2 4.2 0.8 2.8 0.96970
## 844 0.5 3.7 6.3 1.1 -2.1 2.8 4.2 0.8 3.2 1.14929
## 845 0.5 3.7 6.3 1.1 4.2 0.8 -2.1 3.2 2.8 0.54575
## 846 0.5 3.7 6.3 1.1 4.2 3.2 -2.1 0.8 2.8 1.31270
## 847 0.5 3.7 6.3 1.1 4.2 2.8 -2.1 0.8 3.2 1.10060
## 848 0.5 3.7 6.3 1.1 0.8 3.2 -2.1 4.2 2.8 0.47851
## 849 0.5 3.7 6.3 1.1 0.8 2.8 -2.1 4.2 3.2 0.48291
## 850 0.5 3.7 6.3 1.1 3.2 2.8 -2.1 4.2 0.8 0.73845
## 851 0.5 3.7 6.3 -2.1 4.2 0.8 1.1 3.2 2.8 0.73845
## 852 0.5 3.7 6.3 -2.1 4.2 3.2 1.1 0.8 2.8 0.48291
## 853 0.5 3.7 6.3 -2.1 4.2 2.8 1.1 0.8 3.2 0.47851
## 854 0.5 3.7 6.3 -2.1 0.8 3.2 1.1 4.2 2.8 1.10060
## 855 0.5 3.7 6.3 -2.1 0.8 2.8 1.1 4.2 3.2 1.31270
## 856 0.5 3.7 6.3 -2.1 3.2 2.8 1.1 4.2 0.8 0.54575
## 857 0.5 3.7 6.3 4.2 0.8 3.2 1.1 -2.1 2.8 1.14929
## 858 0.5 3.7 6.3 4.2 0.8 2.8 1.1 -2.1 3.2 0.96970
## 859 0.5 3.7 6.3 4.2 3.2 2.8 1.1 -2.1 0.8 3.07228
## 860 0.5 3.7 6.3 0.8 3.2 2.8 1.1 -2.1 4.2 0.66561
## 861 0.5 0.8 3.2 1.1 -2.1 4.2 3.7 2.8 6.3 1.75935
## 862 0.5 0.8 3.2 1.1 -2.1 3.7 4.2 2.8 6.3 2.34272
## 863 0.5 0.8 3.2 1.1 -2.1 2.8 4.2 3.7 6.3 4.13517
## 864 0.5 0.8 3.2 1.1 -2.1 6.3 4.2 3.7 2.8 0.55032
## 865 0.5 0.8 3.2 1.1 4.2 3.7 -2.1 2.8 6.3 0.22331
## 866 0.5 0.8 3.2 1.1 4.2 2.8 -2.1 3.7 6.3 0.17725
## 867 0.5 0.8 3.2 1.1 4.2 6.3 -2.1 3.7 2.8 0.90769
## 868 0.5 0.8 3.2 1.1 3.7 2.8 -2.1 4.2 6.3 0.18415
## 869 0.5 0.8 3.2 1.1 3.7 6.3 -2.1 4.2 2.8 0.68834
## 870 0.5 0.8 3.2 1.1 2.8 6.3 -2.1 4.2 3.7 0.41536
## 871 0.5 0.8 3.2 -2.1 4.2 3.7 1.1 2.8 6.3 0.41536
## 872 0.5 0.8 3.2 -2.1 4.2 2.8 1.1 3.7 6.3 0.68834
## 873 0.5 0.8 3.2 -2.1 4.2 6.3 1.1 3.7 2.8 0.18415
## 874 0.5 0.8 3.2 -2.1 3.7 2.8 1.1 4.2 6.3 0.90769
## 875 0.5 0.8 3.2 -2.1 3.7 6.3 1.1 4.2 2.8 0.17725
## 876 0.5 0.8 3.2 -2.1 2.8 6.3 1.1 4.2 3.7 0.22331
## 877 0.5 0.8 3.2 4.2 3.7 2.8 1.1 -2.1 6.3 0.55032
## 878 0.5 0.8 3.2 4.2 3.7 6.3 1.1 -2.1 2.8 4.13517
## 879 0.5 0.8 3.2 4.2 2.8 6.3 1.1 -2.1 3.7 2.34272
## 880 0.5 0.8 3.2 3.7 2.8 6.3 1.1 -2.1 4.2 1.75935
## 881 0.5 0.8 2.8 1.1 -2.1 4.2 3.7 3.2 6.3 2.14660
## 882 0.5 0.8 2.8 1.1 -2.1 3.7 4.2 3.2 6.3 2.86674
## 883 0.5 0.8 2.8 1.1 -2.1 3.2 4.2 3.7 6.3 3.92855
## 884 0.5 0.8 2.8 1.1 -2.1 6.3 4.2 3.7 3.2 0.70822
## 885 0.5 0.8 2.8 1.1 4.2 3.7 -2.1 3.2 6.3 0.27901
## 886 0.5 0.8 2.8 1.1 4.2 3.2 -2.1 3.7 6.3 0.25236
## 887 0.5 0.8 2.8 1.1 4.2 6.3 -2.1 3.7 3.2 0.91603
## 888 0.5 0.8 2.8 1.1 3.7 3.2 -2.1 4.2 6.3 0.24996
## 889 0.5 0.8 2.8 1.1 3.7 6.3 -2.1 4.2 3.2 0.70822
## 890 0.5 0.8 2.8 1.1 3.2 6.3 -2.1 4.2 3.7 0.54975
## 891 0.5 0.8 2.8 -2.1 4.2 3.7 1.1 3.2 6.3 0.54975
## 892 0.5 0.8 2.8 -2.1 4.2 3.2 1.1 3.7 6.3 0.70822
## 893 0.5 0.8 2.8 -2.1 4.2 6.3 1.1 3.7 3.2 0.24996
## 894 0.5 0.8 2.8 -2.1 3.7 3.2 1.1 4.2 6.3 0.91603
## 895 0.5 0.8 2.8 -2.1 3.7 6.3 1.1 4.2 3.2 0.25236
## 896 0.5 0.8 2.8 -2.1 3.2 6.3 1.1 4.2 3.7 0.27901
## 897 0.5 0.8 2.8 4.2 3.7 3.2 1.1 -2.1 6.3 0.70822
## 898 0.5 0.8 2.8 4.2 3.7 6.3 1.1 -2.1 3.2 3.92855
## 899 0.5 0.8 2.8 4.2 3.2 6.3 1.1 -2.1 3.7 2.86674
## 900 0.5 0.8 2.8 3.7 3.2 6.3 1.1 -2.1 4.2 2.14660
## 901 0.5 0.8 6.3 1.1 -2.1 4.2 3.7 3.2 2.8 0.52926
## 902 0.5 0.8 6.3 1.1 -2.1 3.7 4.2 3.2 2.8 0.73909
## 903 0.5 0.8 6.3 1.1 -2.1 3.2 4.2 3.7 2.8 1.01166
## 904 0.5 0.8 6.3 1.1 -2.1 2.8 4.2 3.7 3.2 1.29000
## 905 0.5 0.8 6.3 1.1 4.2 3.7 -2.1 3.2 2.8 0.31356
## 906 0.5 0.8 6.3 1.1 4.2 3.2 -2.1 3.7 2.8 0.20268
## 907 0.5 0.8 6.3 1.1 4.2 2.8 -2.1 3.7 3.2 0.13517
## 908 0.5 0.8 6.3 1.1 3.7 3.2 -2.1 4.2 2.8 0.12094
## 909 0.5 0.8 6.3 1.1 3.7 2.8 -2.1 4.2 3.2 0.07387
## 910 0.5 0.8 6.3 1.1 3.2 2.8 -2.1 4.2 3.7 0.03572
## 911 0.5 0.8 6.3 -2.1 4.2 3.7 1.1 3.2 2.8 0.03572
## 912 0.5 0.8 6.3 -2.1 4.2 3.2 1.1 3.7 2.8 0.07387
## 913 0.5 0.8 6.3 -2.1 4.2 2.8 1.1 3.7 3.2 0.12094
## 914 0.5 0.8 6.3 -2.1 3.7 3.2 1.1 4.2 2.8 0.13517
## 915 0.5 0.8 6.3 -2.1 3.7 2.8 1.1 4.2 3.2 0.20268
## 916 0.5 0.8 6.3 -2.1 3.2 2.8 1.1 4.2 3.7 0.31356
## 917 0.5 0.8 6.3 4.2 3.7 3.2 1.1 -2.1 2.8 1.29000
## 918 0.5 0.8 6.3 4.2 3.7 2.8 1.1 -2.1 3.2 1.01166
## 919 0.5 0.8 6.3 4.2 3.2 2.8 1.1 -2.1 3.7 0.73909
## 920 0.5 0.8 6.3 3.7 3.2 2.8 1.1 -2.1 4.2 0.52926
## 921 0.5 3.2 2.8 1.1 -2.1 4.2 3.7 0.8 6.3 0.74036
## 922 0.5 3.2 2.8 1.1 -2.1 3.7 4.2 0.8 6.3 1.01679
## 923 0.5 3.2 2.8 1.1 -2.1 0.8 4.2 3.7 6.3 7.26200
## 924 0.5 3.2 2.8 1.1 -2.1 6.3 4.2 3.7 0.8 0.12670
## 925 0.5 3.2 2.8 1.1 4.2 3.7 -2.1 0.8 6.3 0.17679
## 926 0.5 3.2 2.8 1.1 4.2 0.8 -2.1 3.7 6.3 0.03698
## 927 0.5 3.2 2.8 1.1 4.2 6.3 -2.1 3.7 0.8 1.22252
## 928 0.5 3.2 2.8 1.1 3.7 0.8 -2.1 4.2 6.3 0.08594
## 929 0.5 3.2 2.8 1.1 3.7 6.3 -2.1 4.2 0.8 0.89731
## 930 0.5 3.2 2.8 1.1 0.8 6.3 -2.1 4.2 3.7 0.06360
## 931 0.5 3.2 2.8 -2.1 4.2 3.7 1.1 0.8 6.3 0.06360
## 932 0.5 3.2 2.8 -2.1 4.2 0.8 1.1 3.7 6.3 0.89731
## 933 0.5 3.2 2.8 -2.1 4.2 6.3 1.1 3.7 0.8 0.08594
## 934 0.5 3.2 2.8 -2.1 3.7 0.8 1.1 4.2 6.3 1.22252
## 935 0.5 3.2 2.8 -2.1 3.7 6.3 1.1 4.2 0.8 0.03698
## 936 0.5 3.2 2.8 -2.1 0.8 6.3 1.1 4.2 3.7 0.17679
## 937 0.5 3.2 2.8 4.2 3.7 0.8 1.1 -2.1 6.3 0.12670
## 938 0.5 3.2 2.8 4.2 3.7 6.3 1.1 -2.1 0.8 7.26200
## 939 0.5 3.2 2.8 4.2 0.8 6.3 1.1 -2.1 3.7 1.01679
## 940 0.5 3.2 2.8 3.7 0.8 6.3 1.1 -2.1 4.2 0.74036
## 941 0.5 3.2 6.3 1.1 -2.1 4.2 3.7 0.8 2.8 0.57048
## 942 0.5 3.2 6.3 1.1 -2.1 3.7 4.2 0.8 2.8 0.70885
## 943 0.5 3.2 6.3 1.1 -2.1 0.8 4.2 3.7 2.8 3.08907
## 944 0.5 3.2 6.3 1.1 -2.1 2.8 4.2 3.7 0.8 1.08007
## 945 0.5 3.2 6.3 1.1 4.2 3.7 -2.1 0.8 2.8 1.25024
## 946 0.5 3.2 6.3 1.1 4.2 0.8 -2.1 3.7 2.8 0.37970
## 947 0.5 3.2 6.3 1.1 4.2 2.8 -2.1 3.7 0.8 0.81292
## 948 0.5 3.2 6.3 1.1 3.7 0.8 -2.1 4.2 2.8 0.34885
## 949 0.5 3.2 6.3 1.1 3.7 2.8 -2.1 4.2 0.8 0.64860
## 950 0.5 3.2 6.3 1.1 0.8 2.8 -2.1 4.2 3.7 0.35805
## 951 0.5 3.2 6.3 -2.1 4.2 3.7 1.1 0.8 2.8 0.35805
## 952 0.5 3.2 6.3 -2.1 4.2 0.8 1.1 3.7 2.8 0.64860
## 953 0.5 3.2 6.3 -2.1 4.2 2.8 1.1 3.7 0.8 0.34885
## 954 0.5 3.2 6.3 -2.1 3.7 0.8 1.1 4.2 2.8 0.81292
## 955 0.5 3.2 6.3 -2.1 3.7 2.8 1.1 4.2 0.8 0.37970
## 956 0.5 3.2 6.3 -2.1 0.8 2.8 1.1 4.2 3.7 1.25024
## 957 0.5 3.2 6.3 4.2 3.7 0.8 1.1 -2.1 2.8 1.08007
## 958 0.5 3.2 6.3 4.2 3.7 2.8 1.1 -2.1 0.8 3.08907
## 959 0.5 3.2 6.3 4.2 0.8 2.8 1.1 -2.1 3.7 0.70885
## 960 0.5 3.2 6.3 3.7 0.8 2.8 1.1 -2.1 4.2 0.57048
## 961 0.5 2.8 6.3 1.1 -2.1 4.2 3.7 0.8 3.2 0.51798
## 962 0.5 2.8 6.3 1.1 -2.1 3.7 4.2 0.8 3.2 0.66439
## 963 0.5 2.8 6.3 1.1 -2.1 0.8 4.2 3.7 3.2 3.16410
## 964 0.5 2.8 6.3 1.1 -2.1 3.2 4.2 3.7 0.8 0.85702
## 965 0.5 2.8 6.3 1.1 4.2 3.7 -2.1 0.8 3.2 1.00000
## 966 0.5 2.8 6.3 1.1 4.2 0.8 -2.1 3.7 3.2 0.27511
## 967 0.5 2.8 6.3 1.1 4.2 3.2 -2.1 3.7 0.8 0.77370
## 968 0.5 2.8 6.3 1.1 3.7 0.8 -2.1 4.2 3.2 0.25573
## 969 0.5 2.8 6.3 1.1 3.7 3.2 -2.1 4.2 0.8 0.60085
## 970 0.5 2.8 6.3 1.1 0.8 3.2 -2.1 4.2 3.7 0.26055
## 971 0.5 2.8 6.3 -2.1 4.2 3.7 1.1 0.8 3.2 0.26055
## 972 0.5 2.8 6.3 -2.1 4.2 0.8 1.1 3.7 3.2 0.60085
## 973 0.5 2.8 6.3 -2.1 4.2 3.2 1.1 3.7 0.8 0.25573
## 974 0.5 2.8 6.3 -2.1 3.7 0.8 1.1 4.2 3.2 0.77370
## 975 0.5 2.8 6.3 -2.1 3.7 3.2 1.1 4.2 0.8 0.27511
## 976 0.5 2.8 6.3 -2.1 0.8 3.2 1.1 4.2 3.7 1.00000
## 977 0.5 2.8 6.3 4.2 3.7 0.8 1.1 -2.1 3.2 0.85702
## 978 0.5 2.8 6.3 4.2 3.7 3.2 1.1 -2.1 0.8 3.16410
## 979 0.5 2.8 6.3 4.2 0.8 3.2 1.1 -2.1 3.7 0.66439
## 980 0.5 2.8 6.3 3.7 0.8 3.2 1.1 -2.1 4.2 0.51798
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## 982 -2.1 4.2 3.7 1.1 0.5 3.2 0.8 2.8 6.3 0.33162
## 983 -2.1 4.2 3.7 1.1 0.5 2.8 0.8 3.2 6.3 0.44638
## 984 -2.1 4.2 3.7 1.1 0.5 6.3 0.8 3.2 2.8 0.04580
## 985 -2.1 4.2 3.7 1.1 0.8 3.2 0.5 2.8 6.3 0.26055
## 986 -2.1 4.2 3.7 1.1 0.8 2.8 0.5 3.2 6.3 0.35805
## 987 -2.1 4.2 3.7 1.1 0.8 6.3 0.5 3.2 2.8 0.06360
## 988 -2.1 4.2 3.7 1.1 3.2 2.8 0.5 0.8 6.3 0.03572
## 989 -2.1 4.2 3.7 1.1 3.2 6.3 0.5 0.8 2.8 0.54975
## 990 -2.1 4.2 3.7 1.1 2.8 6.3 0.5 0.8 3.2 0.41536
## 991 -2.1 4.2 3.7 0.5 0.8 3.2 1.1 2.8 6.3 0.41536
## 992 -2.1 4.2 3.7 0.5 0.8 2.8 1.1 3.2 6.3 0.54975
## 993 -2.1 4.2 3.7 0.5 0.8 6.3 1.1 3.2 2.8 0.03572
## 994 -2.1 4.2 3.7 0.5 3.2 2.8 1.1 0.8 6.3 0.06360
## 995 -2.1 4.2 3.7 0.5 3.2 6.3 1.1 0.8 2.8 0.35805
## 996 -2.1 4.2 3.7 0.5 2.8 6.3 1.1 0.8 3.2 0.26055
## 997 -2.1 4.2 3.7 0.8 3.2 2.8 1.1 0.5 6.3 0.04580
## 998 -2.1 4.2 3.7 0.8 3.2 6.3 1.1 0.5 2.8 0.44638
## 999 -2.1 4.2 3.7 0.8 2.8 6.3 1.1 0.5 3.2 0.33162
## 1000 -2.1 4.2 3.7 3.2 2.8 6.3 1.1 0.5 0.8 1.57916
## 1001 -2.1 4.2 0.8 1.1 0.5 3.7 3.2 2.8 6.3 1.44507
## 1002 -2.1 4.2 0.8 1.1 0.5 3.2 3.7 2.8 6.3 1.80926
## 1003 -2.1 4.2 0.8 1.1 0.5 2.8 3.7 3.2 6.3 2.19029
## 1004 -2.1 4.2 0.8 1.1 0.5 6.3 3.7 3.2 2.8 0.61089
## 1005 -2.1 4.2 0.8 1.1 3.7 3.2 0.5 2.8 6.3 0.60085
## 1006 -2.1 4.2 0.8 1.1 3.7 2.8 0.5 3.2 6.3 0.64860
## 1007 -2.1 4.2 0.8 1.1 3.7 6.3 0.5 3.2 2.8 0.89731
## 1008 -2.1 4.2 0.8 1.1 3.2 2.8 0.5 3.7 6.3 0.73845
## 1009 -2.1 4.2 0.8 1.1 3.2 6.3 0.5 3.7 2.8 0.76081
## 1010 -2.1 4.2 0.8 1.1 2.8 6.3 0.5 3.7 3.2 0.68032
## 1011 -2.1 4.2 0.8 0.5 3.7 3.2 1.1 2.8 6.3 0.68032
## 1012 -2.1 4.2 0.8 0.5 3.7 2.8 1.1 3.2 6.3 0.76081
## 1013 -2.1 4.2 0.8 0.5 3.7 6.3 1.1 3.2 2.8 0.73845
## 1014 -2.1 4.2 0.8 0.5 3.2 2.8 1.1 3.7 6.3 0.89731
## 1015 -2.1 4.2 0.8 0.5 3.2 6.3 1.1 3.7 2.8 0.64860
## 1016 -2.1 4.2 0.8 0.5 2.8 6.3 1.1 3.7 3.2 0.60085
## 1017 -2.1 4.2 0.8 3.7 3.2 2.8 1.1 0.5 6.3 0.61089
## 1018 -2.1 4.2 0.8 3.7 3.2 6.3 1.1 0.5 2.8 2.19029
## 1019 -2.1 4.2 0.8 3.7 2.8 6.3 1.1 0.5 3.2 1.80926
## 1020 -2.1 4.2 0.8 3.2 2.8 6.3 1.1 0.5 3.7 1.44507
## 1021 -2.1 4.2 3.2 1.1 0.5 3.7 0.8 2.8 6.3 0.31906
## 1022 -2.1 4.2 3.2 1.1 0.5 0.8 3.7 2.8 6.3 1.93875
## 1023 -2.1 4.2 3.2 1.1 0.5 2.8 3.7 0.8 6.3 0.58677
## 1024 -2.1 4.2 3.2 1.1 0.5 6.3 3.7 0.8 2.8 0.07774
## 1025 -2.1 4.2 3.2 1.1 3.7 0.8 0.5 2.8 6.3 0.25573
## 1026 -2.1 4.2 3.2 1.1 3.7 2.8 0.5 0.8 6.3 0.07387
## 1027 -2.1 4.2 3.2 1.1 3.7 6.3 0.5 0.8 2.8 0.70822
## 1028 -2.1 4.2 3.2 1.1 0.8 2.8 0.5 3.7 6.3 0.48291
## 1029 -2.1 4.2 3.2 1.1 0.8 6.3 0.5 3.7 2.8 0.08940
## 1030 -2.1 4.2 3.2 1.1 2.8 6.3 0.5 3.7 0.8 0.39429
## 1031 -2.1 4.2 3.2 0.5 3.7 0.8 1.1 2.8 6.3 0.39429
## 1032 -2.1 4.2 3.2 0.5 3.7 2.8 1.1 0.8 6.3 0.08940
## 1033 -2.1 4.2 3.2 0.5 3.7 6.3 1.1 0.8 2.8 0.48291
## 1034 -2.1 4.2 3.2 0.5 0.8 2.8 1.1 3.7 6.3 0.70822
## 1035 -2.1 4.2 3.2 0.5 0.8 6.3 1.1 3.7 2.8 0.07387
## 1036 -2.1 4.2 3.2 0.5 2.8 6.3 1.1 3.7 0.8 0.25573
## 1037 -2.1 4.2 3.2 3.7 0.8 2.8 1.1 0.5 6.3 0.07774
## 1038 -2.1 4.2 3.2 3.7 0.8 6.3 1.1 0.5 2.8 0.58677
## 1039 -2.1 4.2 3.2 3.7 2.8 6.3 1.1 0.5 0.8 1.93875
## 1040 -2.1 4.2 3.2 0.8 2.8 6.3 1.1 0.5 3.7 0.31906
## 1041 -2.1 4.2 2.8 1.1 0.5 3.7 0.8 3.2 6.3 0.42226
## 1042 -2.1 4.2 2.8 1.1 0.5 0.8 3.7 3.2 6.3 2.31562
## 1043 -2.1 4.2 2.8 1.1 0.5 3.2 3.7 0.8 6.3 0.57512
## 1044 -2.1 4.2 2.8 1.1 0.5 6.3 3.7 0.8 3.2 0.11961
## 1045 -2.1 4.2 2.8 1.1 3.7 0.8 0.5 3.2 6.3 0.34885
## 1046 -2.1 4.2 2.8 1.1 3.7 3.2 0.5 0.8 6.3 0.12094
## 1047 -2.1 4.2 2.8 1.1 3.7 6.3 0.5 0.8 3.2 0.68834
## 1048 -2.1 4.2 2.8 1.1 0.8 3.2 0.5 3.7 6.3 0.47851
## 1049 -2.1 4.2 2.8 1.1 0.8 6.3 0.5 3.7 3.2 0.12626
## 1050 -2.1 4.2 2.8 1.1 3.2 6.3 0.5 3.7 0.8 0.50901
## 1051 -2.1 4.2 2.8 0.5 3.7 0.8 1.1 3.2 6.3 0.50901
## 1052 -2.1 4.2 2.8 0.5 3.7 3.2 1.1 0.8 6.3 0.12626
## 1053 -2.1 4.2 2.8 0.5 3.7 6.3 1.1 0.8 3.2 0.47851
## 1054 -2.1 4.2 2.8 0.5 0.8 3.2 1.1 3.7 6.3 0.68834
## 1055 -2.1 4.2 2.8 0.5 0.8 6.3 1.1 3.7 3.2 0.12094
## 1056 -2.1 4.2 2.8 0.5 3.2 6.3 1.1 3.7 0.8 0.34885
## 1057 -2.1 4.2 2.8 3.7 0.8 3.2 1.1 0.5 6.3 0.11961
## 1058 -2.1 4.2 2.8 3.7 0.8 6.3 1.1 0.5 3.2 0.57512
## 1059 -2.1 4.2 2.8 3.7 3.2 6.3 1.1 0.5 0.8 2.31562
## 1060 -2.1 4.2 2.8 0.8 3.2 6.3 1.1 0.5 3.7 0.42226
## 1061 -2.1 4.2 6.3 1.1 0.5 3.7 0.8 3.2 2.8 0.10159
## 1062 -2.1 4.2 6.3 1.1 0.5 0.8 3.7 3.2 2.8 0.78148
## 1063 -2.1 4.2 6.3 1.1 0.5 3.2 3.7 0.8 2.8 0.14592
## 1064 -2.1 4.2 6.3 1.1 0.5 2.8 3.7 0.8 3.2 0.19895
## 1065 -2.1 4.2 6.3 1.1 3.7 0.8 0.5 3.2 2.8 0.08594
## 1066 -2.1 4.2 6.3 1.1 3.7 3.2 0.5 0.8 2.8 0.24996
## 1067 -2.1 4.2 6.3 1.1 3.7 2.8 0.5 0.8 3.2 0.18415
## 1068 -2.1 4.2 6.3 1.1 0.8 3.2 0.5 3.7 2.8 0.11652
## 1069 -2.1 4.2 6.3 1.1 0.8 2.8 0.5 3.7 3.2 0.15765
## 1070 -2.1 4.2 6.3 1.1 3.2 2.8 0.5 3.7 0.8 0.12537
## 1071 -2.1 4.2 6.3 0.5 3.7 0.8 1.1 3.2 2.8 0.12537
## 1072 -2.1 4.2 6.3 0.5 3.7 3.2 1.1 0.8 2.8 0.15765
## 1073 -2.1 4.2 6.3 0.5 3.7 2.8 1.1 0.8 3.2 0.11652
## 1074 -2.1 4.2 6.3 0.5 0.8 3.2 1.1 3.7 2.8 0.18415
## 1075 -2.1 4.2 6.3 0.5 0.8 2.8 1.1 3.7 3.2 0.24996
## 1076 -2.1 4.2 6.3 0.5 3.2 2.8 1.1 3.7 0.8 0.08594
## 1077 -2.1 4.2 6.3 3.7 0.8 3.2 1.1 0.5 2.8 0.19895
## 1078 -2.1 4.2 6.3 3.7 0.8 2.8 1.1 0.5 3.2 0.14592
## 1079 -2.1 4.2 6.3 3.7 3.2 2.8 1.1 0.5 0.8 0.78148
## 1080 -2.1 4.2 6.3 0.8 3.2 2.8 1.1 0.5 3.7 0.10159
## 1081 -2.1 3.7 0.8 1.1 0.5 4.2 3.2 2.8 6.3 1.57916
## 1082 -2.1 3.7 0.8 1.1 0.5 3.2 4.2 2.8 6.3 2.42568
## 1083 -2.1 3.7 0.8 1.1 0.5 2.8 4.2 3.2 6.3 2.94758
## 1084 -2.1 3.7 0.8 1.1 0.5 6.3 4.2 3.2 2.8 0.84087
## 1085 -2.1 3.7 0.8 1.1 4.2 3.2 0.5 2.8 6.3 0.77370
## 1086 -2.1 3.7 0.8 1.1 4.2 2.8 0.5 3.2 6.3 0.81292
## 1087 -2.1 3.7 0.8 1.1 4.2 6.3 0.5 3.2 2.8 1.22252
## 1088 -2.1 3.7 0.8 1.1 3.2 2.8 0.5 4.2 6.3 1.01459
## 1089 -2.1 3.7 0.8 1.1 3.2 6.3 0.5 4.2 2.8 0.91464
## 1090 -2.1 3.7 0.8 1.1 2.8 6.3 0.5 4.2 3.2 0.84087
## 1091 -2.1 3.7 0.8 0.5 4.2 3.2 1.1 2.8 6.3 0.84087
## 1092 -2.1 3.7 0.8 0.5 4.2 2.8 1.1 3.2 6.3 0.91464
## 1093 -2.1 3.7 0.8 0.5 4.2 6.3 1.1 3.2 2.8 1.01459
## 1094 -2.1 3.7 0.8 0.5 3.2 2.8 1.1 4.2 6.3 1.22252
## 1095 -2.1 3.7 0.8 0.5 3.2 6.3 1.1 4.2 2.8 0.81292
## 1096 -2.1 3.7 0.8 0.5 2.8 6.3 1.1 4.2 3.2 0.77370
## 1097 -2.1 3.7 0.8 4.2 3.2 2.8 1.1 0.5 6.3 0.84087
## 1098 -2.1 3.7 0.8 4.2 3.2 6.3 1.1 0.5 2.8 2.94758
## 1099 -2.1 3.7 0.8 4.2 2.8 6.3 1.1 0.5 3.2 2.42568
## 1100 -2.1 3.7 0.8 3.2 2.8 6.3 1.1 0.5 4.2 1.57916
## 1101 -2.1 3.7 3.2 1.1 0.5 4.2 0.8 2.8 6.3 0.33162
## 1102 -2.1 3.7 3.2 1.1 0.5 0.8 4.2 2.8 6.3 2.42568
## 1103 -2.1 3.7 3.2 1.1 0.5 2.8 4.2 0.8 6.3 0.77112
## 1104 -2.1 3.7 3.2 1.1 0.5 6.3 4.2 0.8 2.8 0.13249
## 1105 -2.1 3.7 3.2 1.1 4.2 0.8 0.5 2.8 6.3 0.27511
## 1106 -2.1 3.7 3.2 1.1 4.2 2.8 0.5 0.8 6.3 0.13517
## 1107 -2.1 3.7 3.2 1.1 4.2 6.3 0.5 0.8 2.8 0.91603
## 1108 -2.1 3.7 3.2 1.1 0.8 2.8 0.5 4.2 6.3 0.64739
## 1109 -2.1 3.7 3.2 1.1 0.8 6.3 0.5 4.2 2.8 0.13785
## 1110 -2.1 3.7 3.2 1.1 2.8 6.3 0.5 4.2 0.8 0.39954
## 1111 -2.1 3.7 3.2 0.5 4.2 0.8 1.1 2.8 6.3 0.39954
## 1112 -2.1 3.7 3.2 0.5 4.2 2.8 1.1 0.8 6.3 0.13785
## 1113 -2.1 3.7 3.2 0.5 4.2 6.3 1.1 0.8 2.8 0.64739
## 1114 -2.1 3.7 3.2 0.5 0.8 2.8 1.1 4.2 6.3 0.91603
## 1115 -2.1 3.7 3.2 0.5 0.8 6.3 1.1 4.2 2.8 0.13517
## 1116 -2.1 3.7 3.2 0.5 2.8 6.3 1.1 4.2 0.8 0.27511
## 1117 -2.1 3.7 3.2 4.2 0.8 2.8 1.1 0.5 6.3 0.13249
## 1118 -2.1 3.7 3.2 4.2 0.8 6.3 1.1 0.5 2.8 0.77112
## 1119 -2.1 3.7 3.2 4.2 2.8 6.3 1.1 0.5 0.8 2.42568
## 1120 -2.1 3.7 3.2 0.8 2.8 6.3 1.1 0.5 4.2 0.33162
## 1121 -2.1 3.7 2.8 1.1 0.5 4.2 0.8 3.2 6.3 0.44638
## 1122 -2.1 3.7 2.8 1.1 0.5 0.8 4.2 3.2 6.3 2.94758
## 1123 -2.1 3.7 2.8 1.1 0.5 3.2 4.2 0.8 6.3 0.77112
## 1124 -2.1 3.7 2.8 1.1 0.5 6.3 4.2 0.8 3.2 0.19431
## 1125 -2.1 3.7 2.8 1.1 4.2 0.8 0.5 3.2 6.3 0.37970
## 1126 -2.1 3.7 2.8 1.1 4.2 3.2 0.5 0.8 6.3 0.20268
## 1127 -2.1 3.7 2.8 1.1 4.2 6.3 0.5 0.8 3.2 0.90769
## 1128 -2.1 3.7 2.8 1.1 0.8 3.2 0.5 4.2 6.3 0.65466
## 1129 -2.1 3.7 2.8 1.1 0.8 6.3 0.5 4.2 3.2 0.19431
## 1130 -2.1 3.7 2.8 1.1 3.2 6.3 0.5 4.2 0.8 0.52587
## 1131 -2.1 3.7 2.8 0.5 4.2 0.8 1.1 3.2 6.3 0.52587
## 1132 -2.1 3.7 2.8 0.5 4.2 3.2 1.1 0.8 6.3 0.19431
## 1133 -2.1 3.7 2.8 0.5 4.2 6.3 1.1 0.8 3.2 0.65466
## 1134 -2.1 3.7 2.8 0.5 0.8 3.2 1.1 4.2 6.3 0.90769
## 1135 -2.1 3.7 2.8 0.5 0.8 6.3 1.1 4.2 3.2 0.20268
## 1136 -2.1 3.7 2.8 0.5 3.2 6.3 1.1 4.2 0.8 0.37970
## 1137 -2.1 3.7 2.8 4.2 0.8 3.2 1.1 0.5 6.3 0.19431
## 1138 -2.1 3.7 2.8 4.2 0.8 6.3 1.1 0.5 3.2 0.77112
## 1139 -2.1 3.7 2.8 4.2 3.2 6.3 1.1 0.5 0.8 2.94758
## 1140 -2.1 3.7 2.8 0.8 3.2 6.3 1.1 0.5 4.2 0.44638
## 1141 -2.1 3.7 6.3 1.1 0.5 4.2 0.8 3.2 2.8 0.04580
## 1142 -2.1 3.7 6.3 1.1 0.5 0.8 4.2 3.2 2.8 0.84087
## 1143 -2.1 3.7 6.3 1.1 0.5 3.2 4.2 0.8 2.8 0.13249
## 1144 -2.1 3.7 6.3 1.1 0.5 2.8 4.2 0.8 3.2 0.19431
## 1145 -2.1 3.7 6.3 1.1 4.2 0.8 0.5 3.2 2.8 0.03698
## 1146 -2.1 3.7 6.3 1.1 4.2 3.2 0.5 0.8 2.8 0.25236
## 1147 -2.1 3.7 6.3 1.1 4.2 2.8 0.5 0.8 3.2 0.17725
## 1148 -2.1 3.7 6.3 1.1 0.8 3.2 0.5 4.2 2.8 0.09679
## 1149 -2.1 3.7 6.3 1.1 0.8 2.8 0.5 4.2 3.2 0.14637
## 1150 -2.1 3.7 6.3 1.1 3.2 2.8 0.5 4.2 0.8 0.06233
## 1151 -2.1 3.7 6.3 0.5 4.2 0.8 1.1 3.2 2.8 0.06233
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## 1153 -2.1 3.7 6.3 0.5 4.2 2.8 1.1 0.8 3.2 0.09679
## 1154 -2.1 3.7 6.3 0.5 0.8 3.2 1.1 4.2 2.8 0.17725
## 1155 -2.1 3.7 6.3 0.5 0.8 2.8 1.1 4.2 3.2 0.25236
## 1156 -2.1 3.7 6.3 0.5 3.2 2.8 1.1 4.2 0.8 0.03698
## 1157 -2.1 3.7 6.3 4.2 0.8 3.2 1.1 0.5 2.8 0.19431
## 1158 -2.1 3.7 6.3 4.2 0.8 2.8 1.1 0.5 3.2 0.13249
## 1159 -2.1 3.7 6.3 4.2 3.2 2.8 1.1 0.5 0.8 0.84087
## 1160 -2.1 3.7 6.3 0.8 3.2 2.8 1.1 0.5 4.2 0.04580
## 1161 -2.1 0.8 3.2 1.1 0.5 4.2 3.7 2.8 6.3 2.13459
## 1162 -2.1 0.8 3.2 1.1 0.5 3.7 4.2 2.8 6.3 2.62679
## 1163 -2.1 0.8 3.2 1.1 0.5 2.8 4.2 3.7 6.3 4.07554
## 1164 -2.1 0.8 3.2 1.1 0.5 6.3 4.2 3.7 2.8 1.14071
## 1165 -2.1 0.8 3.2 1.1 4.2 3.7 0.5 2.8 6.3 1.00000
## 1166 -2.1 0.8 3.2 1.1 4.2 2.8 0.5 3.7 6.3 1.10060
## 1167 -2.1 0.8 3.2 1.1 4.2 6.3 0.5 3.7 2.8 1.41742
## 1168 -2.1 0.8 3.2 1.1 3.7 2.8 0.5 4.2 6.3 1.21444
## 1169 -2.1 0.8 3.2 1.1 3.7 6.3 0.5 4.2 2.8 1.24287
## 1170 -2.1 0.8 3.2 1.1 2.8 6.3 0.5 4.2 3.7 1.05303
## 1171 -2.1 0.8 3.2 0.5 4.2 3.7 1.1 2.8 6.3 1.05303
## 1172 -2.1 0.8 3.2 0.5 4.2 2.8 1.1 3.7 6.3 1.24287
## 1173 -2.1 0.8 3.2 0.5 4.2 6.3 1.1 3.7 2.8 1.21444
## 1174 -2.1 0.8 3.2 0.5 3.7 2.8 1.1 4.2 6.3 1.41742
## 1175 -2.1 0.8 3.2 0.5 3.7 6.3 1.1 4.2 2.8 1.10060
## 1176 -2.1 0.8 3.2 0.5 2.8 6.3 1.1 4.2 3.7 1.00000
## 1177 -2.1 0.8 3.2 4.2 3.7 2.8 1.1 0.5 6.3 1.14071
## 1178 -2.1 0.8 3.2 4.2 3.7 6.3 1.1 0.5 2.8 4.07554
## 1179 -2.1 0.8 3.2 4.2 2.8 6.3 1.1 0.5 3.7 2.62679
## 1180 -2.1 0.8 3.2 3.7 2.8 6.3 1.1 0.5 4.2 2.13459
## 1181 -2.1 0.8 2.8 1.1 0.5 4.2 3.7 3.2 6.3 2.73977
## 1182 -2.1 0.8 2.8 1.1 0.5 3.7 4.2 3.2 6.3 3.39884
## 1183 -2.1 0.8 2.8 1.1 0.5 3.2 4.2 3.7 6.3 4.34958
## 1184 -2.1 0.8 2.8 1.1 0.5 6.3 4.2 3.7 3.2 1.44867
## 1185 -2.1 0.8 2.8 1.1 4.2 3.7 0.5 3.2 6.3 1.25024
## 1186 -2.1 0.8 2.8 1.1 4.2 3.2 0.5 3.7 6.3 1.31270
## 1187 -2.1 0.8 2.8 1.1 4.2 6.3 0.5 3.7 3.2 1.62146
## 1188 -2.1 0.8 2.8 1.1 3.7 3.2 0.5 4.2 6.3 1.42097
## 1189 -2.1 0.8 2.8 1.1 3.7 6.3 0.5 4.2 3.2 1.44867
## 1190 -2.1 0.8 2.8 1.1 3.2 6.3 0.5 4.2 3.7 1.33051
## 1191 -2.1 0.8 2.8 0.5 4.2 3.7 1.1 3.2 6.3 1.33051
## 1192 -2.1 0.8 2.8 0.5 4.2 3.2 1.1 3.7 6.3 1.44867
## 1193 -2.1 0.8 2.8 0.5 4.2 6.3 1.1 3.7 3.2 1.42097
## 1194 -2.1 0.8 2.8 0.5 3.7 3.2 1.1 4.2 6.3 1.62146
## 1195 -2.1 0.8 2.8 0.5 3.7 6.3 1.1 4.2 3.2 1.31270
## 1196 -2.1 0.8 2.8 0.5 3.2 6.3 1.1 4.2 3.7 1.25024
## 1197 -2.1 0.8 2.8 4.2 3.7 3.2 1.1 0.5 6.3 1.44867
## 1198 -2.1 0.8 2.8 4.2 3.7 6.3 1.1 0.5 3.2 4.34958
## 1199 -2.1 0.8 2.8 4.2 3.2 6.3 1.1 0.5 3.7 3.39884
## 1200 -2.1 0.8 2.8 3.7 3.2 6.3 1.1 0.5 4.2 2.73977
## 1201 -2.1 0.8 6.3 1.1 0.5 4.2 3.7 3.2 2.8 0.28292
## 1202 -2.1 0.8 6.3 1.1 0.5 3.7 4.2 3.2 2.8 0.39429
## 1203 -2.1 0.8 6.3 1.1 0.5 3.2 4.2 3.7 2.8 0.54175
## 1204 -2.1 0.8 6.3 1.1 0.5 2.8 4.2 3.7 3.2 0.69143
## 1205 -2.1 0.8 6.3 1.1 4.2 3.7 0.5 3.2 2.8 0.17679
## 1206 -2.1 0.8 6.3 1.1 4.2 3.2 0.5 3.7 2.8 0.13160
## 1207 -2.1 0.8 6.3 1.1 4.2 2.8 0.5 3.7 3.2 0.11212
## 1208 -2.1 0.8 6.3 1.1 3.7 3.2 0.5 4.2 2.8 0.10948
## 1209 -2.1 0.8 6.3 1.1 3.7 2.8 0.5 4.2 3.2 0.10772
## 1210 -2.1 0.8 6.3 1.1 3.2 2.8 0.5 4.2 3.7 0.12537
## 1211 -2.1 0.8 6.3 0.5 4.2 3.7 1.1 3.2 2.8 0.12537
## 1212 -2.1 0.8 6.3 0.5 4.2 3.2 1.1 3.7 2.8 0.10772
## 1213 -2.1 0.8 6.3 0.5 4.2 2.8 1.1 3.7 3.2 0.10948
## 1214 -2.1 0.8 6.3 0.5 3.7 3.2 1.1 4.2 2.8 0.11212
## 1215 -2.1 0.8 6.3 0.5 3.7 2.8 1.1 4.2 3.2 0.13160
## 1216 -2.1 0.8 6.3 0.5 3.2 2.8 1.1 4.2 3.7 0.17679
## 1217 -2.1 0.8 6.3 4.2 3.7 3.2 1.1 0.5 2.8 0.69143
## 1218 -2.1 0.8 6.3 4.2 3.7 2.8 1.1 0.5 3.2 0.54175
## 1219 -2.1 0.8 6.3 4.2 3.2 2.8 1.1 0.5 3.7 0.39429
## 1220 -2.1 0.8 6.3 3.7 3.2 2.8 1.1 0.5 4.2 0.28292
## 1221 -2.1 3.2 2.8 1.1 0.5 4.2 3.7 0.8 6.3 0.62815
## 1222 -2.1 3.2 2.8 1.1 0.5 3.7 4.2 0.8 6.3 0.80041
## 1223 -2.1 3.2 2.8 1.1 0.5 0.8 4.2 3.7 6.3 3.85519
## 1224 -2.1 3.2 2.8 1.1 0.5 6.3 4.2 3.7 0.8 0.29718
## 1225 -2.1 3.2 2.8 1.1 4.2 3.7 0.5 0.8 6.3 0.31356
## 1226 -2.1 3.2 2.8 1.1 4.2 0.8 0.5 3.7 6.3 0.54575
## 1227 -2.1 3.2 2.8 1.1 4.2 6.3 0.5 3.7 0.8 0.92861
## 1228 -2.1 3.2 2.8 1.1 3.7 0.8 0.5 4.2 6.3 0.69143
## 1229 -2.1 3.2 2.8 1.1 3.7 6.3 0.5 4.2 0.8 0.72580
## 1230 -2.1 3.2 2.8 1.1 0.8 6.3 0.5 4.2 3.7 0.28979
## 1231 -2.1 3.2 2.8 0.5 4.2 3.7 1.1 0.8 6.3 0.28979
## 1232 -2.1 3.2 2.8 0.5 4.2 0.8 1.1 3.7 6.3 0.72580
## 1233 -2.1 3.2 2.8 0.5 4.2 6.3 1.1 3.7 0.8 0.69143
## 1234 -2.1 3.2 2.8 0.5 3.7 0.8 1.1 4.2 6.3 0.92861
## 1235 -2.1 3.2 2.8 0.5 3.7 6.3 1.1 4.2 0.8 0.54575
## 1236 -2.1 3.2 2.8 0.5 0.8 6.3 1.1 4.2 3.7 0.31356
## 1237 -2.1 3.2 2.8 4.2 3.7 0.8 1.1 0.5 6.3 0.29718
## 1238 -2.1 3.2 2.8 4.2 3.7 6.3 1.1 0.5 0.8 3.85519
## 1239 -2.1 3.2 2.8 4.2 0.8 6.3 1.1 0.5 3.7 0.80041
## 1240 -2.1 3.2 2.8 3.7 0.8 6.3 1.1 0.5 4.2 0.62815
## 1241 -2.1 3.2 6.3 1.1 0.5 4.2 3.7 0.8 2.8 0.03321
## 1242 -2.1 3.2 6.3 1.1 0.5 3.7 4.2 0.8 2.8 0.07559
## 1243 -2.1 3.2 6.3 1.1 0.5 0.8 4.2 3.7 2.8 0.93704
## 1244 -2.1 3.2 6.3 1.1 0.5 2.8 4.2 3.7 0.8 0.21296
## 1245 -2.1 3.2 6.3 1.1 4.2 3.7 0.5 0.8 2.8 0.27901
## 1246 -2.1 3.2 6.3 1.1 4.2 0.8 0.5 3.7 2.8 0.01824
## 1247 -2.1 3.2 6.3 1.1 4.2 2.8 0.5 3.7 0.8 0.11212
## 1248 -2.1 3.2 6.3 1.1 3.7 0.8 0.5 4.2 2.8 0.04749
## 1249 -2.1 3.2 6.3 1.1 3.7 2.8 0.5 4.2 0.8 0.05595
## 1250 -2.1 3.2 6.3 1.1 0.8 2.8 0.5 4.2 3.7 0.15765
## 1251 -2.1 3.2 6.3 0.5 4.2 3.7 1.1 0.8 2.8 0.15765
## 1252 -2.1 3.2 6.3 0.5 4.2 0.8 1.1 3.7 2.8 0.05595
## 1253 -2.1 3.2 6.3 0.5 4.2 2.8 1.1 3.7 0.8 0.04749
## 1254 -2.1 3.2 6.3 0.5 3.7 0.8 1.1 4.2 2.8 0.11212
## 1255 -2.1 3.2 6.3 0.5 3.7 2.8 1.1 4.2 0.8 0.01824
## 1256 -2.1 3.2 6.3 0.5 0.8 2.8 1.1 4.2 3.7 0.27901
## 1257 -2.1 3.2 6.3 4.2 3.7 0.8 1.1 0.5 2.8 0.21296
## 1258 -2.1 3.2 6.3 4.2 3.7 2.8 1.1 0.5 0.8 0.93704
## 1259 -2.1 3.2 6.3 4.2 0.8 2.8 1.1 0.5 3.7 0.07559
## 1260 -2.1 3.2 6.3 3.7 0.8 2.8 1.1 0.5 4.2 0.03321
## 1261 -2.1 2.8 6.3 1.1 0.5 4.2 3.7 0.8 3.2 0.03823
## 1262 -2.1 2.8 6.3 1.1 0.5 3.7 4.2 0.8 3.2 0.08940
## 1263 -2.1 2.8 6.3 1.1 0.5 0.8 4.2 3.7 3.2 1.04409
## 1264 -2.1 2.8 6.3 1.1 0.5 3.2 4.2 3.7 0.8 0.16492
## 1265 -2.1 2.8 6.3 1.1 4.2 3.7 0.5 0.8 3.2 0.22331
## 1266 -2.1 2.8 6.3 1.1 4.2 0.8 0.5 3.7 3.2 0.01824
## 1267 -2.1 2.8 6.3 1.1 4.2 3.2 0.5 3.7 0.8 0.13160
## 1268 -2.1 2.8 6.3 1.1 3.7 0.8 0.5 4.2 3.2 0.05595
## 1269 -2.1 2.8 6.3 1.1 3.7 3.2 0.5 4.2 0.8 0.06617
## 1270 -2.1 2.8 6.3 1.1 0.8 3.2 0.5 4.2 3.7 0.11652
## 1271 -2.1 2.8 6.3 0.5 4.2 3.7 1.1 0.8 3.2 0.11652
## 1272 -2.1 2.8 6.3 0.5 4.2 0.8 1.1 3.7 3.2 0.06617
## 1273 -2.1 2.8 6.3 0.5 4.2 3.2 1.1 3.7 0.8 0.05595
## 1274 -2.1 2.8 6.3 0.5 3.7 0.8 1.1 4.2 3.2 0.13160
## 1275 -2.1 2.8 6.3 0.5 3.7 3.2 1.1 4.2 0.8 0.01824
## 1276 -2.1 2.8 6.3 0.5 0.8 3.2 1.1 4.2 3.7 0.22331
## 1277 -2.1 2.8 6.3 4.2 3.7 0.8 1.1 0.5 3.2 0.16492
## 1278 -2.1 2.8 6.3 4.2 3.7 3.2 1.1 0.5 0.8 1.04409
## 1279 -2.1 2.8 6.3 4.2 0.8 3.2 1.1 0.5 3.7 0.08940
## 1280 -2.1 2.8 6.3 3.7 0.8 3.2 1.1 0.5 4.2 0.03823
## 1281 4.2 3.7 0.8 1.1 0.5 -2.1 3.2 2.8 6.3 4.38658
## 1282 4.2 3.7 0.8 1.1 0.5 3.2 -2.1 2.8 6.3 0.16492
## 1283 4.2 3.7 0.8 1.1 0.5 2.8 -2.1 3.2 6.3 0.21296
## 1284 4.2 3.7 0.8 1.1 0.5 6.3 -2.1 3.2 2.8 0.29718
## 1285 4.2 3.7 0.8 1.1 -2.1 3.2 0.5 2.8 6.3 0.85702
## 1286 4.2 3.7 0.8 1.1 -2.1 2.8 0.5 3.2 6.3 1.08007
## 1287 4.2 3.7 0.8 1.1 -2.1 6.3 0.5 3.2 2.8 0.12670
## 1288 4.2 3.7 0.8 1.1 3.2 2.8 0.5 -2.1 6.3 0.17542
## 1289 4.2 3.7 0.8 1.1 3.2 6.3 0.5 -2.1 2.8 1.52270
## 1290 4.2 3.7 0.8 1.1 2.8 6.3 0.5 -2.1 3.2 1.21121
## 1291 4.2 3.7 0.8 0.5 -2.1 3.2 1.1 2.8 6.3 1.21121
## 1292 4.2 3.7 0.8 0.5 -2.1 2.8 1.1 3.2 6.3 1.52270
## 1293 4.2 3.7 0.8 0.5 -2.1 6.3 1.1 3.2 2.8 0.17542
## 1294 4.2 3.7 0.8 0.5 3.2 2.8 1.1 -2.1 6.3 0.12670
## 1295 4.2 3.7 0.8 0.5 3.2 6.3 1.1 -2.1 2.8 1.08007
## 1296 4.2 3.7 0.8 0.5 2.8 6.3 1.1 -2.1 3.2 0.85702
## 1297 4.2 3.7 0.8 -2.1 3.2 2.8 1.1 0.5 6.3 0.29718
## 1298 4.2 3.7 0.8 -2.1 3.2 6.3 1.1 0.5 2.8 0.21296
## 1299 4.2 3.7 0.8 -2.1 2.8 6.3 1.1 0.5 3.2 0.16492
## 1300 4.2 3.7 0.8 3.2 2.8 6.3 1.1 0.5 -2.1 4.38658
## 1301 4.2 3.7 3.2 1.1 0.5 -2.1 0.8 2.8 6.3 3.73562
## 1302 4.2 3.7 3.2 1.1 0.5 0.8 -2.1 2.8 6.3 1.04409
## 1303 4.2 3.7 3.2 1.1 0.5 2.8 -2.1 0.8 6.3 0.69143
## 1304 4.2 3.7 3.2 1.1 0.5 6.3 -2.1 0.8 2.8 1.44867
## 1305 4.2 3.7 3.2 1.1 -2.1 0.8 0.5 2.8 6.3 3.16410
## 1306 4.2 3.7 3.2 1.1 -2.1 2.8 0.5 0.8 6.3 1.29000
## 1307 4.2 3.7 3.2 1.1 -2.1 6.3 0.5 0.8 2.8 0.70822
## 1308 4.2 3.7 3.2 1.1 0.8 2.8 0.5 -2.1 6.3 0.68587
## 1309 4.2 3.7 3.2 1.1 0.8 6.3 0.5 -2.1 2.8 1.63703
## 1310 4.2 3.7 3.2 1.1 2.8 6.3 0.5 -2.1 0.8 4.46929
## 1311 4.2 3.7 3.2 0.5 -2.1 0.8 1.1 2.8 6.3 4.46929
## 1312 4.2 3.7 3.2 0.5 -2.1 2.8 1.1 0.8 6.3 1.63703
## 1313 4.2 3.7 3.2 0.5 -2.1 6.3 1.1 0.8 2.8 0.68587
## 1314 4.2 3.7 3.2 0.5 0.8 2.8 1.1 -2.1 6.3 0.70822
## 1315 4.2 3.7 3.2 0.5 0.8 6.3 1.1 -2.1 2.8 1.29000
## 1316 4.2 3.7 3.2 0.5 2.8 6.3 1.1 -2.1 0.8 3.16410
## 1317 4.2 3.7 3.2 -2.1 0.8 2.8 1.1 0.5 6.3 1.44867
## 1318 4.2 3.7 3.2 -2.1 0.8 6.3 1.1 0.5 2.8 0.69143
## 1319 4.2 3.7 3.2 -2.1 2.8 6.3 1.1 0.5 0.8 1.04409
## 1320 4.2 3.7 3.2 0.8 2.8 6.3 1.1 0.5 -2.1 3.73562
## 1321 4.2 3.7 2.8 1.1 0.5 -2.1 0.8 3.2 6.3 3.67030
## 1322 4.2 3.7 2.8 1.1 0.5 0.8 -2.1 3.2 6.3 0.93704
## 1323 4.2 3.7 2.8 1.1 0.5 3.2 -2.1 0.8 6.3 0.54175
## 1324 4.2 3.7 2.8 1.1 0.5 6.3 -2.1 0.8 3.2 1.14071
## 1325 4.2 3.7 2.8 1.1 -2.1 0.8 0.5 3.2 6.3 3.08907
## 1326 4.2 3.7 2.8 1.1 -2.1 3.2 0.5 0.8 6.3 1.01166
## 1327 4.2 3.7 2.8 1.1 -2.1 6.3 0.5 0.8 3.2 0.55032
## 1328 4.2 3.7 2.8 1.1 0.8 3.2 0.5 -2.1 6.3 0.54346
## 1329 4.2 3.7 2.8 1.1 0.8 6.3 0.5 -2.1 3.2 1.29335
## 1330 4.2 3.7 2.8 1.1 3.2 6.3 0.5 -2.1 0.8 4.41894
## 1331 4.2 3.7 2.8 0.5 -2.1 0.8 1.1 3.2 6.3 4.41894
## 1332 4.2 3.7 2.8 0.5 -2.1 3.2 1.1 0.8 6.3 1.29335
## 1333 4.2 3.7 2.8 0.5 -2.1 6.3 1.1 0.8 3.2 0.54346
## 1334 4.2 3.7 2.8 0.5 0.8 3.2 1.1 -2.1 6.3 0.55032
## 1335 4.2 3.7 2.8 0.5 0.8 6.3 1.1 -2.1 3.2 1.01166
## 1336 4.2 3.7 2.8 0.5 3.2 6.3 1.1 -2.1 0.8 3.08907
## 1337 4.2 3.7 2.8 -2.1 0.8 3.2 1.1 0.5 6.3 1.14071
## 1338 4.2 3.7 2.8 -2.1 0.8 6.3 1.1 0.5 3.2 0.54175
## 1339 4.2 3.7 2.8 -2.1 3.2 6.3 1.1 0.5 0.8 0.93704
## 1340 4.2 3.7 2.8 0.8 3.2 6.3 1.1 0.5 -2.1 3.67030
## 1341 4.2 3.7 6.3 1.1 0.5 -2.1 0.8 3.2 2.8 8.37571
## 1342 4.2 3.7 6.3 1.1 0.5 0.8 -2.1 3.2 2.8 3.85519
## 1343 4.2 3.7 6.3 1.1 0.5 3.2 -2.1 0.8 2.8 4.34958
## 1344 4.2 3.7 6.3 1.1 0.5 2.8 -2.1 0.8 3.2 4.07554
## 1345 4.2 3.7 6.3 1.1 -2.1 0.8 0.5 3.2 2.8 7.26200
## 1346 4.2 3.7 6.3 1.1 -2.1 3.2 0.5 0.8 2.8 3.92855
## 1347 4.2 3.7 6.3 1.1 -2.1 2.8 0.5 0.8 3.2 4.13517
## 1348 4.2 3.7 6.3 1.1 0.8 3.2 0.5 -2.1 2.8 4.62452
## 1349 4.2 3.7 6.3 1.1 0.8 2.8 0.5 -2.1 3.2 4.27189
## 1350 4.2 3.7 6.3 1.1 3.2 2.8 0.5 -2.1 0.8 9.89514
## 1351 4.2 3.7 6.3 0.5 -2.1 0.8 1.1 3.2 2.8 9.89514
## 1352 4.2 3.7 6.3 0.5 -2.1 3.2 1.1 0.8 2.8 4.27189
## 1353 4.2 3.7 6.3 0.5 -2.1 2.8 1.1 0.8 3.2 4.62452
## 1354 4.2 3.7 6.3 0.5 0.8 3.2 1.1 -2.1 2.8 4.13517
## 1355 4.2 3.7 6.3 0.5 0.8 2.8 1.1 -2.1 3.2 3.92855
## 1356 4.2 3.7 6.3 0.5 3.2 2.8 1.1 -2.1 0.8 7.26200
## 1357 4.2 3.7 6.3 -2.1 0.8 3.2 1.1 0.5 2.8 4.07554
## 1358 4.2 3.7 6.3 -2.1 0.8 2.8 1.1 0.5 3.2 4.34958
## 1359 4.2 3.7 6.3 -2.1 3.2 2.8 1.1 0.5 0.8 3.85519
## 1360 4.2 3.7 6.3 0.8 3.2 2.8 1.1 0.5 -2.1 8.37571
## 1361 4.2 0.8 3.2 1.1 0.5 -2.1 3.7 2.8 6.3 4.93225
## 1362 4.2 0.8 3.2 1.1 0.5 3.7 -2.1 2.8 6.3 0.08940
## 1363 4.2 0.8 3.2 1.1 0.5 2.8 -2.1 3.7 6.3 0.19431
## 1364 4.2 0.8 3.2 1.1 0.5 6.3 -2.1 3.7 2.8 0.19431
## 1365 4.2 0.8 3.2 1.1 -2.1 3.7 0.5 2.8 6.3 0.66439
## 1366 4.2 0.8 3.2 1.1 -2.1 2.8 0.5 3.7 6.3 1.14929
## 1367 4.2 0.8 3.2 1.1 -2.1 6.3 0.5 3.7 2.8 0.08940
## 1368 4.2 0.8 3.2 1.1 3.7 2.8 0.5 -2.1 6.3 0.15042
## 1369 4.2 0.8 3.2 1.1 3.7 6.3 0.5 -2.1 2.8 1.63703
## 1370 4.2 0.8 3.2 1.1 2.8 6.3 0.5 -2.1 3.7 0.96113
## 1371 4.2 0.8 3.2 0.5 -2.1 3.7 1.1 2.8 6.3 0.96113
## 1372 4.2 0.8 3.2 0.5 -2.1 2.8 1.1 3.7 6.3 1.63703
## 1373 4.2 0.8 3.2 0.5 -2.1 6.3 1.1 3.7 2.8 0.15042
## 1374 4.2 0.8 3.2 0.5 3.7 2.8 1.1 -2.1 6.3 0.08940
## 1375 4.2 0.8 3.2 0.5 3.7 6.3 1.1 -2.1 2.8 1.14929
## 1376 4.2 0.8 3.2 0.5 2.8 6.3 1.1 -2.1 3.7 0.66439
## 1377 4.2 0.8 3.2 -2.1 3.7 2.8 1.1 0.5 6.3 0.19431
## 1378 4.2 0.8 3.2 -2.1 3.7 6.3 1.1 0.5 2.8 0.19431
## 1379 4.2 0.8 3.2 -2.1 2.8 6.3 1.1 0.5 3.7 0.08940
## 1380 4.2 0.8 3.2 3.7 2.8 6.3 1.1 0.5 -2.1 4.93225
## 1381 4.2 0.8 2.8 1.1 0.5 -2.1 3.7 3.2 6.3 5.54835
## 1382 4.2 0.8 2.8 1.1 0.5 3.7 -2.1 3.2 6.3 0.07559
## 1383 4.2 0.8 2.8 1.1 0.5 3.2 -2.1 3.7 6.3 0.13249
## 1384 4.2 0.8 2.8 1.1 0.5 6.3 -2.1 3.7 3.2 0.13249
## 1385 4.2 0.8 2.8 1.1 -2.1 3.7 0.5 3.2 6.3 0.70885
## 1386 4.2 0.8 2.8 1.1 -2.1 3.2 0.5 3.7 6.3 0.96970
## 1387 4.2 0.8 2.8 1.1 -2.1 6.3 0.5 3.7 3.2 0.07559
## 1388 4.2 0.8 2.8 1.1 3.7 3.2 0.5 -2.1 6.3 0.14682
## 1389 4.2 0.8 2.8 1.1 3.7 6.3 0.5 -2.1 3.2 1.39274
## 1390 4.2 0.8 2.8 1.1 3.2 6.3 0.5 -2.1 3.7 1.03076
## 1391 4.2 0.8 2.8 0.5 -2.1 3.7 1.1 3.2 6.3 1.03076
## 1392 4.2 0.8 2.8 0.5 -2.1 3.2 1.1 3.7 6.3 1.39274
## 1393 4.2 0.8 2.8 0.5 -2.1 6.3 1.1 3.7 3.2 0.14682
## 1394 4.2 0.8 2.8 0.5 3.7 3.2 1.1 -2.1 6.3 0.07559
## 1395 4.2 0.8 2.8 0.5 3.7 6.3 1.1 -2.1 3.2 0.96970
## 1396 4.2 0.8 2.8 0.5 3.2 6.3 1.1 -2.1 3.7 0.70885
## 1397 4.2 0.8 2.8 -2.1 3.7 3.2 1.1 0.5 6.3 0.13249
## 1398 4.2 0.8 2.8 -2.1 3.7 6.3 1.1 0.5 3.2 0.13249
## 1399 4.2 0.8 2.8 -2.1 3.2 6.3 1.1 0.5 3.7 0.07559
## 1400 4.2 0.8 2.8 3.7 3.2 6.3 1.1 0.5 -2.1 5.54835
## 1401 4.2 0.8 6.3 1.1 0.5 -2.1 3.7 3.2 2.8 3.79383
## 1402 4.2 0.8 6.3 1.1 0.5 3.7 -2.1 3.2 2.8 0.80041
## 1403 4.2 0.8 6.3 1.1 0.5 3.2 -2.1 3.7 2.8 0.77112
## 1404 4.2 0.8 6.3 1.1 0.5 2.8 -2.1 3.7 3.2 0.77112
## 1405 4.2 0.8 6.3 1.1 -2.1 3.7 0.5 3.2 2.8 1.01679
## 1406 4.2 0.8 6.3 1.1 -2.1 3.2 0.5 3.7 2.8 1.18082
## 1407 4.2 0.8 6.3 1.1 -2.1 2.8 0.5 3.7 3.2 1.35278
## 1408 4.2 0.8 6.3 1.1 3.7 3.2 0.5 -2.1 2.8 1.69840
## 1409 4.2 0.8 6.3 1.1 3.7 2.8 0.5 -2.1 3.2 1.45497
## 1410 4.2 0.8 6.3 1.1 3.2 2.8 0.5 -2.1 3.7 1.22009
## 1411 4.2 0.8 6.3 0.5 -2.1 3.7 1.1 3.2 2.8 1.22009
## 1412 4.2 0.8 6.3 0.5 -2.1 3.2 1.1 3.7 2.8 1.45497
## 1413 4.2 0.8 6.3 0.5 -2.1 2.8 1.1 3.7 3.2 1.69840
## 1414 4.2 0.8 6.3 0.5 3.7 3.2 1.1 -2.1 2.8 1.35278
## 1415 4.2 0.8 6.3 0.5 3.7 2.8 1.1 -2.1 3.2 1.18082
## 1416 4.2 0.8 6.3 0.5 3.2 2.8 1.1 -2.1 3.7 1.01679
## 1417 4.2 0.8 6.3 -2.1 3.7 3.2 1.1 0.5 2.8 0.77112
## 1418 4.2 0.8 6.3 -2.1 3.7 2.8 1.1 0.5 3.2 0.77112
## 1419 4.2 0.8 6.3 -2.1 3.2 2.8 1.1 0.5 3.7 0.80041
## 1420 4.2 0.8 6.3 3.7 3.2 2.8 1.1 0.5 -2.1 3.79383
## 1421 4.2 3.2 2.8 1.1 0.5 -2.1 3.7 0.8 6.3 3.68042
## 1422 4.2 3.2 2.8 1.1 0.5 3.7 -2.1 0.8 6.3 0.39429
## 1423 4.2 3.2 2.8 1.1 0.5 0.8 -2.1 3.7 6.3 0.84087
## 1424 4.2 3.2 2.8 1.1 0.5 6.3 -2.1 3.7 0.8 0.84087
## 1425 4.2 3.2 2.8 1.1 -2.1 3.7 0.5 0.8 6.3 0.73909
## 1426 4.2 3.2 2.8 1.1 -2.1 0.8 0.5 3.7 6.3 3.07228
## 1427 4.2 3.2 2.8 1.1 -2.1 6.3 0.5 3.7 0.8 0.39429
## 1428 4.2 3.2 2.8 1.1 3.7 0.8 0.5 -2.1 6.3 0.40374
## 1429 4.2 3.2 2.8 1.1 3.7 6.3 0.5 -2.1 0.8 4.46929
## 1430 4.2 3.2 2.8 1.1 0.8 6.3 0.5 -2.1 3.7 0.96113
## 1431 4.2 3.2 2.8 0.5 -2.1 3.7 1.1 0.8 6.3 0.96113
## 1432 4.2 3.2 2.8 0.5 -2.1 0.8 1.1 3.7 6.3 4.46929
## 1433 4.2 3.2 2.8 0.5 -2.1 6.3 1.1 3.7 0.8 0.40374
## 1434 4.2 3.2 2.8 0.5 3.7 0.8 1.1 -2.1 6.3 0.39429
## 1435 4.2 3.2 2.8 0.5 3.7 6.3 1.1 -2.1 0.8 3.07228
## 1436 4.2 3.2 2.8 0.5 0.8 6.3 1.1 -2.1 3.7 0.73909
## 1437 4.2 3.2 2.8 -2.1 3.7 0.8 1.1 0.5 6.3 0.84087
## 1438 4.2 3.2 2.8 -2.1 3.7 6.3 1.1 0.5 0.8 0.84087
## 1439 4.2 3.2 2.8 -2.1 0.8 6.3 1.1 0.5 3.7 0.39429
## 1440 4.2 3.2 2.8 3.7 0.8 6.3 1.1 0.5 -2.1 3.68042
## 1441 4.2 3.2 6.3 1.1 0.5 -2.1 3.7 0.8 2.8 6.65439
## 1442 4.2 3.2 6.3 1.1 0.5 3.7 -2.1 0.8 2.8 3.39884
## 1443 4.2 3.2 6.3 1.1 0.5 0.8 -2.1 3.7 2.8 2.94758
## 1444 4.2 3.2 6.3 1.1 0.5 2.8 -2.1 3.7 0.8 2.94758
## 1445 4.2 3.2 6.3 1.1 -2.1 3.7 0.5 0.8 2.8 2.86674
## 1446 4.2 3.2 6.3 1.1 -2.1 0.8 0.5 3.7 2.8 5.78723
## 1447 4.2 3.2 6.3 1.1 -2.1 2.8 0.5 3.7 0.8 3.20931
## 1448 4.2 3.2 6.3 1.1 3.7 0.8 0.5 -2.1 2.8 3.63612
## 1449 4.2 3.2 6.3 1.1 3.7 2.8 0.5 -2.1 0.8 7.80609
## 1450 4.2 3.2 6.3 1.1 0.8 2.8 0.5 -2.1 3.7 3.06057
## 1451 4.2 3.2 6.3 0.5 -2.1 3.7 1.1 0.8 2.8 3.06057
## 1452 4.2 3.2 6.3 0.5 -2.1 0.8 1.1 3.7 2.8 7.80609
## 1453 4.2 3.2 6.3 0.5 -2.1 2.8 1.1 3.7 0.8 3.63612
## 1454 4.2 3.2 6.3 0.5 3.7 0.8 1.1 -2.1 2.8 3.20931
## 1455 4.2 3.2 6.3 0.5 3.7 2.8 1.1 -2.1 0.8 5.78723
## 1456 4.2 3.2 6.3 0.5 0.8 2.8 1.1 -2.1 3.7 2.86674
## 1457 4.2 3.2 6.3 -2.1 3.7 0.8 1.1 0.5 2.8 2.94758
## 1458 4.2 3.2 6.3 -2.1 3.7 2.8 1.1 0.5 0.8 2.94758
## 1459 4.2 3.2 6.3 -2.1 0.8 2.8 1.1 0.5 3.7 3.39884
## 1460 4.2 3.2 6.3 3.7 0.8 2.8 1.1 0.5 -2.1 6.65439
## 1461 4.2 2.8 6.3 1.1 0.5 -2.1 3.7 0.8 3.2 5.73492
## 1462 4.2 2.8 6.3 1.1 0.5 3.7 -2.1 0.8 3.2 2.62679
## 1463 4.2 2.8 6.3 1.1 0.5 0.8 -2.1 3.7 3.2 2.42568
## 1464 4.2 2.8 6.3 1.1 0.5 3.2 -2.1 3.7 0.8 2.42568
## 1465 4.2 2.8 6.3 1.1 -2.1 3.7 0.5 0.8 3.2 2.34272
## 1466 4.2 2.8 6.3 1.1 -2.1 0.8 0.5 3.7 3.2 4.98404
## 1467 4.2 2.8 6.3 1.1 -2.1 3.2 0.5 3.7 0.8 2.49613
## 1468 4.2 2.8 6.3 1.1 3.7 0.8 0.5 -2.1 3.2 2.79111
## 1469 4.2 2.8 6.3 1.1 3.7 3.2 0.5 -2.1 0.8 6.71832
## 1470 4.2 2.8 6.3 1.1 0.8 3.2 0.5 -2.1 3.7 2.53622
## 1471 4.2 2.8 6.3 0.5 -2.1 3.7 1.1 0.8 3.2 2.53622
## 1472 4.2 2.8 6.3 0.5 -2.1 0.8 1.1 3.7 3.2 6.71832
## 1473 4.2 2.8 6.3 0.5 -2.1 3.2 1.1 3.7 0.8 2.79111
## 1474 4.2 2.8 6.3 0.5 3.7 0.8 1.1 -2.1 3.2 2.49613
## 1475 4.2 2.8 6.3 0.5 3.7 3.2 1.1 -2.1 0.8 4.98404
## 1476 4.2 2.8 6.3 0.5 0.8 3.2 1.1 -2.1 3.7 2.34272
## 1477 4.2 2.8 6.3 -2.1 3.7 0.8 1.1 0.5 3.2 2.42568
## 1478 4.2 2.8 6.3 -2.1 3.7 3.2 1.1 0.5 0.8 2.42568
## 1479 4.2 2.8 6.3 -2.1 0.8 3.2 1.1 0.5 3.7 2.62679
## 1480 4.2 2.8 6.3 3.7 0.8 3.2 1.1 0.5 -2.1 5.73492
## 1481 3.7 0.8 3.2 1.1 0.5 -2.1 4.2 2.8 6.3 5.73492
## 1482 3.7 0.8 3.2 1.1 0.5 4.2 -2.1 2.8 6.3 0.03823
## 1483 3.7 0.8 3.2 1.1 0.5 2.8 -2.1 4.2 6.3 0.19895
## 1484 3.7 0.8 3.2 1.1 0.5 6.3 -2.1 4.2 2.8 0.11961
## 1485 3.7 0.8 3.2 1.1 -2.1 4.2 0.5 2.8 6.3 0.51798
## 1486 3.7 0.8 3.2 1.1 -2.1 2.8 0.5 4.2 6.3 1.26176
## 1487 3.7 0.8 3.2 1.1 -2.1 6.3 0.5 4.2 2.8 0.07430
## 1488 3.7 0.8 3.2 1.1 4.2 2.8 0.5 -2.1 6.3 0.14817
## 1489 3.7 0.8 3.2 1.1 4.2 6.3 0.5 -2.1 2.8 1.80926
## 1490 3.7 0.8 3.2 1.1 2.8 6.3 0.5 -2.1 4.2 0.77112
## 1491 3.7 0.8 3.2 0.5 -2.1 4.2 1.1 2.8 6.3 0.77112
## 1492 3.7 0.8 3.2 0.5 -2.1 2.8 1.1 4.2 6.3 1.80926
## 1493 3.7 0.8 3.2 0.5 -2.1 6.3 1.1 4.2 2.8 0.14817
## 1494 3.7 0.8 3.2 0.5 4.2 2.8 1.1 -2.1 6.3 0.07430
## 1495 3.7 0.8 3.2 0.5 4.2 6.3 1.1 -2.1 2.8 1.26176
## 1496 3.7 0.8 3.2 0.5 2.8 6.3 1.1 -2.1 4.2 0.51798
## 1497 3.7 0.8 3.2 -2.1 4.2 2.8 1.1 0.5 6.3 0.11961
## 1498 3.7 0.8 3.2 -2.1 4.2 6.3 1.1 0.5 2.8 0.19895
## 1499 3.7 0.8 3.2 -2.1 2.8 6.3 1.1 0.5 4.2 0.03823
## 1500 3.7 0.8 3.2 4.2 2.8 6.3 1.1 0.5 -2.1 5.73492
## 1501 3.7 0.8 2.8 1.1 0.5 -2.1 4.2 3.2 6.3 6.65439
## 1502 3.7 0.8 2.8 1.1 0.5 4.2 -2.1 3.2 6.3 0.03321
## 1503 3.7 0.8 2.8 1.1 0.5 3.2 -2.1 4.2 6.3 0.14592
## 1504 3.7 0.8 2.8 1.1 0.5 6.3 -2.1 4.2 3.2 0.07774
## 1505 3.7 0.8 2.8 1.1 -2.1 4.2 0.5 3.2 6.3 0.57048
## 1506 3.7 0.8 2.8 1.1 -2.1 3.2 0.5 4.2 6.3 1.08765
## 1507 3.7 0.8 2.8 1.1 -2.1 6.3 0.5 4.2 3.2 0.07774
## 1508 3.7 0.8 2.8 1.1 4.2 3.2 0.5 -2.1 6.3 0.16264
## 1509 3.7 0.8 2.8 1.1 4.2 6.3 0.5 -2.1 3.2 1.56586
## 1510 3.7 0.8 2.8 1.1 3.2 6.3 0.5 -2.1 4.2 0.84758
## 1511 3.7 0.8 2.8 0.5 -2.1 4.2 1.1 3.2 6.3 0.84758
## 1512 3.7 0.8 2.8 0.5 -2.1 3.2 1.1 4.2 6.3 1.56586
## 1513 3.7 0.8 2.8 0.5 -2.1 6.3 1.1 4.2 3.2 0.16264
## 1514 3.7 0.8 2.8 0.5 4.2 3.2 1.1 -2.1 6.3 0.07774
## 1515 3.7 0.8 2.8 0.5 4.2 6.3 1.1 -2.1 3.2 1.08765
## 1516 3.7 0.8 2.8 0.5 3.2 6.3 1.1 -2.1 4.2 0.57048
## 1517 3.7 0.8 2.8 -2.1 4.2 3.2 1.1 0.5 6.3 0.07774
## 1518 3.7 0.8 2.8 -2.1 4.2 6.3 1.1 0.5 3.2 0.14592
## 1519 3.7 0.8 2.8 -2.1 3.2 6.3 1.1 0.5 4.2 0.03321
## 1520 3.7 0.8 2.8 4.2 3.2 6.3 1.1 0.5 -2.1 6.65439
## 1521 3.7 0.8 6.3 1.1 0.5 -2.1 4.2 3.2 2.8 3.68042
## 1522 3.7 0.8 6.3 1.1 0.5 4.2 -2.1 3.2 2.8 0.62815
## 1523 3.7 0.8 6.3 1.1 0.5 3.2 -2.1 4.2 2.8 0.57512
## 1524 3.7 0.8 6.3 1.1 0.5 2.8 -2.1 4.2 3.2 0.58677
## 1525 3.7 0.8 6.3 1.1 -2.1 4.2 0.5 3.2 2.8 0.74036
## 1526 3.7 0.8 6.3 1.1 -2.1 3.2 0.5 4.2 2.8 1.03520
## 1527 3.7 0.8 6.3 1.1 -2.1 2.8 0.5 4.2 3.2 1.21121
## 1528 3.7 0.8 6.3 1.1 4.2 3.2 0.5 -2.1 2.8 1.56207
## 1529 3.7 0.8 6.3 1.1 4.2 2.8 0.5 -2.1 3.2 1.31523
## 1530 3.7 0.8 6.3 1.1 3.2 2.8 0.5 -2.1 4.2 0.89524
## 1531 3.7 0.8 6.3 0.5 -2.1 4.2 1.1 3.2 2.8 0.89524
## 1532 3.7 0.8 6.3 0.5 -2.1 3.2 1.1 4.2 2.8 1.31523
## 1533 3.7 0.8 6.3 0.5 -2.1 2.8 1.1 4.2 3.2 1.56207
## 1534 3.7 0.8 6.3 0.5 4.2 3.2 1.1 -2.1 2.8 1.21121
## 1535 3.7 0.8 6.3 0.5 4.2 2.8 1.1 -2.1 3.2 1.03520
## 1536 3.7 0.8 6.3 0.5 3.2 2.8 1.1 -2.1 4.2 0.74036
## 1537 3.7 0.8 6.3 -2.1 4.2 3.2 1.1 0.5 2.8 0.58677
## 1538 3.7 0.8 6.3 -2.1 4.2 2.8 1.1 0.5 3.2 0.57512
## 1539 3.7 0.8 6.3 -2.1 3.2 2.8 1.1 0.5 4.2 0.62815
## 1540 3.7 0.8 6.3 4.2 3.2 2.8 1.1 0.5 -2.1 3.68042
## 1541 3.7 3.2 2.8 1.1 0.5 -2.1 4.2 0.8 6.3 3.79383
## 1542 3.7 3.2 2.8 1.1 0.5 4.2 -2.1 0.8 6.3 0.28292
## 1543 3.7 3.2 2.8 1.1 0.5 0.8 -2.1 4.2 6.3 0.78148
## 1544 3.7 3.2 2.8 1.1 0.5 6.3 -2.1 4.2 0.8 0.61089
## 1545 3.7 3.2 2.8 1.1 -2.1 4.2 0.5 0.8 6.3 0.52926
## 1546 3.7 3.2 2.8 1.1 -2.1 0.8 0.5 4.2 6.3 3.14003
## 1547 3.7 3.2 2.8 1.1 -2.1 6.3 0.5 4.2 0.8 0.27560
## 1548 3.7 3.2 2.8 1.1 4.2 0.8 0.5 -2.1 6.3 0.29916
## 1549 3.7 3.2 2.8 1.1 4.2 6.3 0.5 -2.1 0.8 4.65103
## 1550 3.7 3.2 2.8 1.1 0.8 6.3 0.5 -2.1 4.2 0.70760
## 1551 3.7 3.2 2.8 0.5 -2.1 4.2 1.1 0.8 6.3 0.70760
## 1552 3.7 3.2 2.8 0.5 -2.1 0.8 1.1 4.2 6.3 4.65103
## 1553 3.7 3.2 2.8 0.5 -2.1 6.3 1.1 4.2 0.8 0.29916
## 1554 3.7 3.2 2.8 0.5 4.2 0.8 1.1 -2.1 6.3 0.27560
## 1555 3.7 3.2 2.8 0.5 4.2 6.3 1.1 -2.1 0.8 3.14003
## 1556 3.7 3.2 2.8 0.5 0.8 6.3 1.1 -2.1 4.2 0.52926
## 1557 3.7 3.2 2.8 -2.1 4.2 0.8 1.1 0.5 6.3 0.61089
## 1558 3.7 3.2 2.8 -2.1 4.2 6.3 1.1 0.5 0.8 0.78148
## 1559 3.7 3.2 2.8 -2.1 0.8 6.3 1.1 0.5 4.2 0.28292
## 1560 3.7 3.2 2.8 4.2 0.8 6.3 1.1 0.5 -2.1 3.79383
## 1561 3.7 3.2 6.3 1.1 0.5 -2.1 4.2 0.8 2.8 5.54835
## 1562 3.7 3.2 6.3 1.1 0.5 4.2 -2.1 0.8 2.8 2.73977
## 1563 3.7 3.2 6.3 1.1 0.5 0.8 -2.1 4.2 2.8 2.31562
## 1564 3.7 3.2 6.3 1.1 0.5 2.8 -2.1 4.2 0.8 2.19029
## 1565 3.7 3.2 6.3 1.1 -2.1 4.2 0.5 0.8 2.8 2.14660
## 1566 3.7 3.2 6.3 1.1 -2.1 0.8 0.5 4.2 2.8 4.81954
## 1567 3.7 3.2 6.3 1.1 -2.1 2.8 0.5 4.2 0.8 2.56561
## 1568 3.7 3.2 6.3 1.1 4.2 0.8 0.5 -2.1 2.8 2.95402
## 1569 3.7 3.2 6.3 1.1 4.2 2.8 0.5 -2.1 0.8 6.50022
## 1570 3.7 3.2 6.3 1.1 0.8 2.8 0.5 -2.1 4.2 2.25722
## 1571 3.7 3.2 6.3 0.5 -2.1 4.2 1.1 0.8 2.8 2.25722
## 1572 3.7 3.2 6.3 0.5 -2.1 0.8 1.1 4.2 2.8 6.50022
## 1573 3.7 3.2 6.3 0.5 -2.1 2.8 1.1 4.2 0.8 2.95402
## 1574 3.7 3.2 6.3 0.5 4.2 0.8 1.1 -2.1 2.8 2.56561
## 1575 3.7 3.2 6.3 0.5 4.2 2.8 1.1 -2.1 0.8 4.81954
## 1576 3.7 3.2 6.3 0.5 0.8 2.8 1.1 -2.1 4.2 2.14660
## 1577 3.7 3.2 6.3 -2.1 4.2 0.8 1.1 0.5 2.8 2.19029
## 1578 3.7 3.2 6.3 -2.1 4.2 2.8 1.1 0.5 0.8 2.31562
## 1579 3.7 3.2 6.3 -2.1 0.8 2.8 1.1 0.5 4.2 2.73977
## 1580 3.7 3.2 6.3 4.2 0.8 2.8 1.1 0.5 -2.1 5.54835
## 1581 3.7 2.8 6.3 1.1 0.5 -2.1 4.2 0.8 3.2 4.93225
## 1582 3.7 2.8 6.3 1.1 0.5 4.2 -2.1 0.8 3.2 2.13459
## 1583 3.7 2.8 6.3 1.1 0.5 0.8 -2.1 4.2 3.2 1.93875
## 1584 3.7 2.8 6.3 1.1 0.5 3.2 -2.1 4.2 0.8 1.80926
## 1585 3.7 2.8 6.3 1.1 -2.1 4.2 0.5 0.8 3.2 1.75935
## 1586 3.7 2.8 6.3 1.1 -2.1 0.8 0.5 4.2 3.2 4.27189
## 1587 3.7 2.8 6.3 1.1 -2.1 3.2 0.5 4.2 0.8 2.00842
## 1588 3.7 2.8 6.3 1.1 4.2 0.8 0.5 -2.1 3.2 2.29007
## 1589 3.7 2.8 6.3 1.1 4.2 3.2 0.5 -2.1 0.8 5.78723
## 1590 3.7 2.8 6.3 1.1 0.8 3.2 0.5 -2.1 4.2 1.87963
## 1591 3.7 2.8 6.3 0.5 -2.1 4.2 1.1 0.8 3.2 1.87963
## 1592 3.7 2.8 6.3 0.5 -2.1 0.8 1.1 4.2 3.2 5.78723
## 1593 3.7 2.8 6.3 0.5 -2.1 3.2 1.1 4.2 0.8 2.29007
## 1594 3.7 2.8 6.3 0.5 4.2 0.8 1.1 -2.1 3.2 2.00842
## 1595 3.7 2.8 6.3 0.5 4.2 3.2 1.1 -2.1 0.8 4.27189
## 1596 3.7 2.8 6.3 0.5 0.8 3.2 1.1 -2.1 4.2 1.75935
## 1597 3.7 2.8 6.3 -2.1 4.2 0.8 1.1 0.5 3.2 1.80926
## 1598 3.7 2.8 6.3 -2.1 4.2 3.2 1.1 0.5 0.8 1.93875
## 1599 3.7 2.8 6.3 -2.1 0.8 3.2 1.1 0.5 4.2 2.13459
## 1600 3.7 2.8 6.3 4.2 0.8 3.2 1.1 0.5 -2.1 4.93225
## 1601 0.8 3.2 2.8 1.1 0.5 -2.1 4.2 3.7 6.3 8.37571
## 1602 0.8 3.2 2.8 1.1 0.5 4.2 -2.1 3.7 6.3 0.04580
## 1603 0.8 3.2 2.8 1.1 0.5 3.7 -2.1 4.2 6.3 0.10159
## 1604 0.8 3.2 2.8 1.1 0.5 6.3 -2.1 4.2 3.7 0.04580
## 1605 0.8 3.2 2.8 1.1 -2.1 4.2 0.5 3.7 6.3 0.66561
## 1606 0.8 3.2 2.8 1.1 -2.1 3.7 0.5 4.2 6.3 0.92021
## 1607 0.8 3.2 2.8 1.1 -2.1 6.3 0.5 4.2 3.7 0.10159
## 1608 0.8 3.2 2.8 1.1 4.2 3.7 0.5 -2.1 6.3 0.20175
## 1609 0.8 3.2 2.8 1.1 4.2 6.3 0.5 -2.1 3.7 1.33222
## 1610 0.8 3.2 2.8 1.1 3.7 6.3 0.5 -2.1 4.2 0.97975
## 1611 0.8 3.2 2.8 0.5 -2.1 4.2 1.1 3.7 6.3 0.97975
## 1612 0.8 3.2 2.8 0.5 -2.1 3.7 1.1 4.2 6.3 1.33222
## 1613 0.8 3.2 2.8 0.5 -2.1 6.3 1.1 4.2 3.7 0.20175
## 1614 0.8 3.2 2.8 0.5 4.2 3.7 1.1 -2.1 6.3 0.10159
## 1615 0.8 3.2 2.8 0.5 4.2 6.3 1.1 -2.1 3.7 0.92021
## 1616 0.8 3.2 2.8 0.5 3.7 6.3 1.1 -2.1 4.2 0.66561
## 1617 0.8 3.2 2.8 -2.1 4.2 3.7 1.1 0.5 6.3 0.04580
## 1618 0.8 3.2 2.8 -2.1 4.2 6.3 1.1 0.5 3.7 0.10159
## 1619 0.8 3.2 2.8 -2.1 3.7 6.3 1.1 0.5 4.2 0.04580
## 1620 0.8 3.2 2.8 4.2 3.7 6.3 1.1 0.5 -2.1 8.37571
## 1621 0.8 3.2 6.3 1.1 0.5 -2.1 4.2 3.7 2.8 3.67030
## 1622 0.8 3.2 6.3 1.1 0.5 4.2 -2.1 3.7 2.8 0.44638
## 1623 0.8 3.2 6.3 1.1 0.5 3.7 -2.1 4.2 2.8 0.42226
## 1624 0.8 3.2 6.3 1.1 0.5 2.8 -2.1 4.2 3.7 0.44638
## 1625 0.8 3.2 6.3 1.1 -2.1 4.2 0.5 3.7 2.8 0.62337
## 1626 0.8 3.2 6.3 1.1 -2.1 3.7 0.5 4.2 2.8 0.75631
## 1627 0.8 3.2 6.3 1.1 -2.1 2.8 0.5 4.2 3.7 1.11670
## 1628 0.8 3.2 6.3 1.1 4.2 3.7 0.5 -2.1 2.8 1.47854
## 1629 0.8 3.2 6.3 1.1 4.2 2.8 0.5 -2.1 3.7 0.97616
## 1630 0.8 3.2 6.3 1.1 3.7 2.8 0.5 -2.1 4.2 0.78799
## 1631 0.8 3.2 6.3 0.5 -2.1 4.2 1.1 3.7 2.8 0.78799
## 1632 0.8 3.2 6.3 0.5 -2.1 3.7 1.1 4.2 2.8 0.97616
## 1633 0.8 3.2 6.3 0.5 -2.1 2.8 1.1 4.2 3.7 1.47854
## 1634 0.8 3.2 6.3 0.5 4.2 3.7 1.1 -2.1 2.8 1.11670
## 1635 0.8 3.2 6.3 0.5 4.2 2.8 1.1 -2.1 3.7 0.75631
## 1636 0.8 3.2 6.3 0.5 3.7 2.8 1.1 -2.1 4.2 0.62337
## 1637 0.8 3.2 6.3 -2.1 4.2 3.7 1.1 0.5 2.8 0.44638
## 1638 0.8 3.2 6.3 -2.1 4.2 2.8 1.1 0.5 3.7 0.42226
## 1639 0.8 3.2 6.3 -2.1 3.7 2.8 1.1 0.5 4.2 0.44638
## 1640 0.8 3.2 6.3 4.2 3.7 2.8 1.1 0.5 -2.1 3.67030
## 1641 0.8 2.8 6.3 1.1 0.5 -2.1 4.2 3.7 3.2 3.73562
## 1642 0.8 2.8 6.3 1.1 0.5 4.2 -2.1 3.7 3.2 0.33162
## 1643 0.8 2.8 6.3 1.1 0.5 3.7 -2.1 4.2 3.2 0.31906
## 1644 0.8 2.8 6.3 1.1 0.5 3.2 -2.1 4.2 3.7 0.33162
## 1645 0.8 2.8 6.3 1.1 -2.1 4.2 0.5 3.7 3.2 0.55548
## 1646 0.8 2.8 6.3 1.1 -2.1 3.7 0.5 4.2 3.2 0.69577
## 1647 0.8 2.8 6.3 1.1 -2.1 3.2 0.5 4.2 3.7 0.88150
## 1648 0.8 2.8 6.3 1.1 4.2 3.7 0.5 -2.1 3.2 1.18241
## 1649 0.8 2.8 6.3 1.1 4.2 3.2 0.5 -2.1 3.7 0.92511
## 1650 0.8 2.8 6.3 1.1 3.7 3.2 0.5 -2.1 4.2 0.72895
## 1651 0.8 2.8 6.3 0.5 -2.1 4.2 1.1 3.7 3.2 0.72895
## 1652 0.8 2.8 6.3 0.5 -2.1 3.7 1.1 4.2 3.2 0.92511
## 1653 0.8 2.8 6.3 0.5 -2.1 3.2 1.1 4.2 3.7 1.18241
## 1654 0.8 2.8 6.3 0.5 4.2 3.7 1.1 -2.1 3.2 0.88150
## 1655 0.8 2.8 6.3 0.5 4.2 3.2 1.1 -2.1 3.7 0.69577
## 1656 0.8 2.8 6.3 0.5 3.7 3.2 1.1 -2.1 4.2 0.55548
## 1657 0.8 2.8 6.3 -2.1 4.2 3.7 1.1 0.5 3.2 0.33162
## 1658 0.8 2.8 6.3 -2.1 4.2 3.2 1.1 0.5 3.7 0.31906
## 1659 0.8 2.8 6.3 -2.1 3.7 3.2 1.1 0.5 4.2 0.33162
## 1660 0.8 2.8 6.3 4.2 3.7 3.2 1.1 0.5 -2.1 3.73562
## 1661 3.2 2.8 6.3 1.1 0.5 -2.1 4.2 3.7 0.8 4.38658
## 1662 3.2 2.8 6.3 1.1 0.5 4.2 -2.1 3.7 0.8 1.57916
## 1663 3.2 2.8 6.3 1.1 0.5 3.7 -2.1 4.2 0.8 1.44507
## 1664 3.2 2.8 6.3 1.1 0.5 0.8 -2.1 4.2 3.7 1.57916
## 1665 3.2 2.8 6.3 1.1 -2.1 4.2 0.5 3.7 0.8 1.38923
## 1666 3.2 2.8 6.3 1.1 -2.1 3.7 0.5 4.2 0.8 1.49224
## 1667 3.2 2.8 6.3 1.1 -2.1 0.8 0.5 4.2 3.7 3.77918
## 1668 3.2 2.8 6.3 1.1 4.2 3.7 0.5 -2.1 0.8 5.16772
## 1669 3.2 2.8 6.3 1.1 4.2 0.8 0.5 -2.1 3.7 1.68739
## 1670 3.2 2.8 6.3 1.1 3.7 0.8 0.5 -2.1 4.2 1.51899
## 1671 3.2 2.8 6.3 0.5 -2.1 4.2 1.1 3.7 0.8 1.51899
## 1672 3.2 2.8 6.3 0.5 -2.1 3.7 1.1 4.2 0.8 1.68739
## 1673 3.2 2.8 6.3 0.5 -2.1 0.8 1.1 4.2 3.7 5.16772
## 1674 3.2 2.8 6.3 0.5 4.2 3.7 1.1 -2.1 0.8 3.77918
## 1675 3.2 2.8 6.3 0.5 4.2 0.8 1.1 -2.1 3.7 1.49224
## 1676 3.2 2.8 6.3 0.5 3.7 0.8 1.1 -2.1 4.2 1.38923
## 1677 3.2 2.8 6.3 -2.1 4.2 3.7 1.1 0.5 0.8 1.57916
## 1678 3.2 2.8 6.3 -2.1 4.2 0.8 1.1 0.5 3.7 1.44507
## 1679 3.2 2.8 6.3 -2.1 3.7 0.8 1.1 0.5 4.2 1.57916
## 1680 3.2 2.8 6.3 4.2 3.7 0.8 1.1 0.5 -2.1 4.38658