Standardize circumplex scales using normative data
Source:R/tidying_functions.R
norm_standardize.RdTake in a data frame containing circumplex scales, angle definitions for each scale, and normative data (from the package or custom) and return that same data frame with each specified circumplex scale transformed into standard scores (i.e., z-scores) based on comparison to the normative data.
Usage
norm_standardize(
data,
scales,
angles = octants(),
instrument,
sample = 1,
prefix = "",
suffix = "_z",
append = TRUE
)Arguments
- data
Required. A data frame or matrix containing at least circumplex scales.
- scales
Required. A character vector containing the column names, or a numeric vector containing the column indexes, for the variables (scale scores) to be standardized.
- angles
Required. A numeric vector containing the angular displacement of each circumplex scale included in
scales(in degrees). Can use theoctants(),poles(), orquadrants()convenience functions.- instrument
Required. An instrument object from the package. To see the available circumplex instruments, see
instruments().- sample
Required. An integer corresponding to the normative sample to use in standardizing the scale scores (default = 1). See
?normsto see the normative samples available for an instrument.- prefix
Optional. A string to include at the beginning of the newly calculated scale variables' names, before the scale name and
suffix(default = "").- suffix
Optional. A string to include at the end of the newly calculated scale variables' names, after the scale name and
prefix(default = "_z").- append
Optional. A logical that determines whether the calculated standardized scores should be added as columns to
datain the output or the standardized scores alone should be output (default = TRUE).
Examples
data("jz2017")
instrument("iipsc")
norm_standardize(jz2017, scales = 2:9, instrument = iipsc, sample = 1)
#> Gender PA BC DE FG HI JK LM NO PARPD SCZPD SZTPD ASPD
#> 1 Female 1.50 1.50 1.25 1.00 2.00 2.50 2.25 2.50 4 3 7 7
#> 2 Female 0.00 0.25 0.00 0.25 1.25 1.75 2.25 2.25 1 0 2 0
#> 3 Female 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 1 0 4
#> 4 Male 2.00 1.75 1.75 2.50 2.00 1.75 2.00 2.50 1 0 0 0
#> 5 Female 0.25 0.50 0.25 0.00 0.00 0.00 0.00 0.00 0 0 0 0
#> 6 Male 1.50 1.75 2.25 1.75 2.00 1.25 2.25 2.50 5 5 7 5
#> 7 Male 2.00 1.75 1.75 2.00 1.50 1.25 1.25 1.75 3 6 7 3
#> 8 Female 0.00 0.25 0.25 0.25 1.00 1.25 1.25 1.00 0 0 1 0
#> 9 Female 0.00 0.00 0.00 0.00 0.25 0.25 1.00 0.00 0 1 0 0
#> 10 Male 0.75 2.00 1.75 2.50 2.00 1.50 2.00 2.25 4 5 5 2
#> 11 Male 1.75 1.75 1.50 1.50 1.50 2.00 2.00 2.00 3 3 6 4
#> 12 Male 0.50 0.75 0.50 1.00 1.00 1.25 0.75 1.00 1 3 4 5
#> 13 Female 1.25 2.00 1.25 1.50 2.50 3.00 3.00 2.75 6 2 7 3
#> 14 Male 0.25 0.25 0.00 0.00 0.50 0.50 0.75 0.75 3 0 2 4
#> 15 Female 0.25 0.00 0.00 0.00 0.25 0.00 0.25 0.50 4 1 3 0
#> 16 Female 1.00 0.25 0.25 0.00 0.50 0.75 1.50 0.25 2 1 0 1
#> 17 Female 0.25 0.75 0.00 0.00 0.00 0.00 0.00 0.00 4 1 2 1
#> 18 Female 0.50 0.50 0.25 0.25 2.25 2.75 3.50 0.00 2 1 3 0
#> 19 Male 0.25 0.25 0.25 1.00 0.50 0.50 1.00 0.00 1 1 2 1
#> 20 Female 0.25 0.50 0.00 0.50 3.00 3.25 2.75 2.00 1 0 1 1
#> 21 Male 0.25 0.50 0.75 1.00 1.00 1.00 0.25 0.00 2 0 5 3
#> 22 Female 0.25 0.50 0.75 1.00 0.25 0.25 1.75 0.25 4 2 2 0
#> 23 Male 0.25 0.75 2.50 2.00 2.00 2.50 1.50 0.50 1 1 1 2
#> 24 Male 0.50 1.00 1.00 1.00 1.25 1.25 1.25 1.25 5 2 3 1
#> 25 Female 0.00 1.50 1.00 1.00 3.00 2.50 2.00 0.25 3 0 3 0
#> 26 Female 1.25 1.00 2.00 1.75 1.50 1.00 1.25 1.25 6 1 5 5
#> 27 Male 0.00 0.00 0.00 0.00 0.00 0.25 1.00 0.50 0 0 0 0
#> 28 Male 0.50 0.00 0.25 0.00 0.75 1.00 1.00 1.25 1 0 2 4
#> 29 Male 0.50 1.00 0.75 0.25 0.75 0.50 3.25 0.25 6 2 5 3
#> 30 Male 0.75 0.50 0.50 0.75 1.75 1.00 1.25 1.00 3 5 6 3
#> 31 Male 0.00 0.00 0.00 0.00 0.50 0.25 0.50 0.00 2 2 2 0
#> 32 Male 1.00 0.25 0.25 0.00 0.25 0.25 0.75 0.75 2 1 2 3
#> 33 Male 0.25 0.25 0.00 0.50 1.00 1.00 1.50 0.00 1 1 0 0
#> 34 Male 0.75 0.75 0.50 2.25 2.00 0.75 0.00 0.50 0 2 6 2
#> 35 Male 0.75 1.75 2.25 2.75 2.75 2.75 2.50 1.00 2 3 2 3
#> 36 Male 0.75 1.25 1.50 1.00 1.00 1.75 2.50 0.00 6 4 6 2
#> 37 Male 0.75 0.75 0.25 0.00 1.50 1.75 1.25 0.75 1 1 1 2
#> 38 Female 0.25 0.25 0.25 0.00 0.50 1.25 1.25 0.50 3 0 0 2
#> 39 Male 0.75 0.75 0.25 0.00 1.00 0.75 1.25 1.00 4 0 4 4
#> 40 Male 0.00 1.25 2.50 3.00 2.75 3.00 2.75 1.50 5 5 7 3
#> 41 Female 0.00 0.00 0.00 0.00 0.25 0.50 1.50 1.25 0 0 1 2
#> 42 Female 1.75 0.00 0.00 0.00 0.00 0.00 1.75 1.50 2 1 0 4
#> 43 Female 0.50 0.00 0.00 0.00 0.00 0.00 1.50 1.00 0 0 2 2
#> 44 Female 0.25 0.00 0.00 0.00 0.00 0.25 0.50 0.00 0 1 1 0
#> 45 Female 0.00 0.00 0.00 0.00 0.50 0.25 0.75 1.25 1 1 1 1
#> 46 Female 0.00 0.00 0.75 0.00 0.25 1.00 1.75 0.50 2 0 4 1
#> 47 Female 0.00 0.00 0.00 0.00 1.00 1.00 0.75 0.00 2 0 0 2
#> 48 Male 0.25 0.00 0.00 0.25 0.50 0.75 1.50 0.00 0 0 1 0
#> 49 Female 0.00 0.00 0.00 0.50 0.25 0.00 1.00 0.00 4 2 4 4
#> 50 Male 0.00 0.25 0.75 1.00 2.25 2.00 1.50 0.00 2 0 1 2
#> 51 Female 0.25 0.75 4.00 1.25 2.75 1.75 2.50 0.50 7 2 5 1
#> 52 Male 1.00 1.50 1.50 2.00 1.75 1.00 1.50 2.25 2 4 3 4
#> 53 Female 0.25 0.25 0.00 0.00 0.75 1.50 1.50 1.75 3 1 0 0
#> 54 Female 0.00 0.00 0.00 0.50 3.00 2.25 3.00 0.00 0 0 2 0
#> 55 Male 1.25 1.25 1.25 1.50 1.50 2.00 2.25 0.75 1 4 6 4
#> 56 Male 1.00 1.25 0.50 2.00 1.25 2.25 2.50 0.50 5 2 4 5
#> 57 Female 0.75 0.75 0.00 0.25 1.25 1.25 1.50 1.50 3 0 3 3
#> 58 Female 0.00 0.00 0.00 0.00 0.00 0.00 0.50 0.00 3 0 1 0
#> 59 Male 0.25 0.25 1.00 2.00 1.50 0.50 1.00 1.00 2 0 3 0
#> 60 Female 1.50 0.75 0.00 0.00 0.00 0.00 0.75 0.25 0 1 0 3
#> 61 Male 0.50 0.50 2.00 1.75 1.25 1.25 1.75 0.25 2 3 5 1
#> 62 Male 0.50 1.00 1.25 1.75 2.25 1.75 1.00 1.25 3 1 2 0
#> 63 Female 0.75 0.25 0.00 0.00 0.00 0.00 0.50 0.25 0 2 2 2
#> 64 Male 1.25 2.00 2.50 2.00 2.00 2.50 2.00 1.25 5 1 5 3
#> 65 Female 1.00 0.75 1.50 3.00 3.25 2.25 2.25 1.25 2 0 3 0
#> 66 Female 0.00 0.50 0.00 0.25 1.00 1.25 3.00 0.50 1 2 2 0
#> 67 Male 0.00 0.00 0.00 0.00 0.00 0.25 0.25 0.00 0 0 3 1
#> 68 Female 0.00 0.50 0.25 0.00 0.75 0.50 3.75 1.00 2 2 3 1
#> 69 Male 0.75 1.75 0.50 0.75 1.00 1.00 1.00 0.75 2 2 2 4
#> 70 Male 0.25 0.75 0.25 0.00 0.75 1.00 1.50 1.00 0 0 0 3
#> 71 Female 0.50 0.00 0.00 0.00 0.00 0.75 2.00 1.75 1 0 2 0
#> 72 Male 0.00 0.25 0.00 0.00 0.00 0.00 0.75 0.25 3 1 1 4
#> 73 Female 1.25 0.50 0.75 1.25 1.75 0.25 1.25 0.50 3 0 0 1
#> 74 Male 0.50 0.75 1.25 2.00 2.00 1.50 1.25 2.50 0 0 1 3
#> 75 Female 0.00 0.50 0.00 0.00 0.75 0.75 1.75 0.00 2 1 1 0
#> 76 Female 0.75 0.50 0.00 0.00 1.75 1.25 1.75 2.50 3 0 4 3
#> 77 Male 1.25 0.75 2.00 2.00 2.50 2.75 2.75 2.75 3 5 3 1
#> 78 Female 1.75 0.25 0.50 0.00 0.00 0.00 0.75 0.25 4 4 3 3
#> 79 Male 0.25 0.00 0.25 0.00 0.00 0.25 1.50 0.50 4 1 4 4
#> 80 Female 0.00 0.00 0.00 0.00 0.00 0.00 1.50 1.25 1 0 0 0
#> 81 Female 0.50 0.50 0.75 0.25 1.25 0.75 1.00 1.50 1 1 2 2
#> 82 Male 1.00 0.75 2.50 0.50 1.00 1.50 0.00 1.00 4 4 1 3
#> 83 Male 1.00 1.25 1.25 1.75 1.25 1.50 1.75 1.00 0 1 7 1
#> 84 Female 1.00 0.50 0.25 0.50 0.50 0.00 0.50 0.75 2 0 0 3
#> 85 Male 0.75 1.25 0.25 0.25 0.00 0.00 0.25 0.50 3 0 1 6
#> 86 Female 1.50 1.00 0.75 1.00 1.00 1.00 2.00 3.00 5 0 4 2
#> 87 Female 0.25 0.00 0.00 1.00 2.25 2.25 3.00 1.75 1 1 1 0
#> 88 Female 0.25 0.75 0.25 0.25 1.00 1.50 1.50 1.00 2 1 2 0
#> 89 Female 0.75 0.25 0.00 0.25 1.00 1.25 1.50 3.75 1 1 0 0
#> 90 Female 0.75 0.25 0.50 1.00 1.50 1.25 2.25 1.25 3 0 3 1
#> 91 Male 0.00 0.50 0.50 0.00 0.25 0.00 1.50 0.75 1 2 4 2
#> 92 Female 1.00 0.50 1.00 2.00 1.25 1.25 1.00 0.50 3 1 4 1
#> 93 Male 0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.50 1 0 2 1
#> 94 Male 0.25 0.75 0.25 1.00 1.25 1.50 1.00 0.75 4 3 5 0
#> 95 Male 0.75 0.50 0.50 1.25 1.75 1.25 2.25 2.75 3 0 5 4
#> 96 Female 0.00 0.00 0.75 0.00 0.75 1.00 1.50 0.25 4 1 3 0
#> 97 Male 0.25 0.75 0.75 1.50 1.50 1.25 2.75 1.00 5 2 6 2
#> 98 Male 1.00 0.75 0.00 0.00 0.00 0.25 0.00 0.50 3 0 1 4
#> 99 Female 0.50 0.25 0.25 0.00 0.25 1.00 0.75 0.25 3 1 1 3
#> 100 Female 0.25 0.25 0.75 1.00 0.50 0.50 0.75 0.50 4 1 7 1
#> 101 Female 1.25 1.00 0.25 0.25 0.00 0.00 0.00 1.00 3 1 3 0
#> 102 Male 0.00 1.00 1.00 1.75 1.00 1.00 0.50 0.50 1 0 0 1
#> 103 Female 0.50 0.25 0.00 0.25 1.75 1.75 1.25 1.50 0 1 1 0
#> 104 Female 0.75 0.50 1.25 0.50 1.75 2.00 1.50 0.50 3 1 4 0
#> 105 Female 0.25 0.75 1.25 1.25 2.50 3.00 3.25 2.25 5 1 3 4
#> 106 Female 0.00 0.00 0.00 0.00 0.50 0.25 0.75 0.50 0 0 1 0
#> 107 Female 0.50 0.25 0.00 0.00 0.75 1.00 0.50 2.50 1 0 1 2
#> 108 Male 0.00 0.00 0.00 0.50 1.25 0.75 1.75 0.25 1 0 2 0
#> 109 Female 2.50 1.75 1.00 0.25 0.50 1.00 0.75 2.25 5 1 3 6
#> 110 Male 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3 4 5 3
#> 111 Male 1.50 2.00 2.25 2.75 2.00 2.00 1.25 0.75 4 4 5 6
#> 112 Female 0.50 0.00 0.00 0.00 0.25 0.25 0.00 0.00 0 1 0 0
#> 113 Male 1.25 1.50 0.50 0.50 1.50 1.75 0.50 0.25 2 4 4 0
#> 114 Male 0.00 0.00 0.50 1.00 1.25 1.50 1.25 1.75 2 2 6 3
#> 115 Female 0.25 0.00 0.00 0.00 1.75 2.00 1.00 0.50 4 1 0 0
#> 116 Male 0.00 0.25 0.00 0.00 0.00 0.00 1.25 0.00 0 0 3 3
#> 117 Male 1.00 0.75 1.00 1.25 1.50 1.50 2.00 0.75 1 1 3 1
#> 118 Female 0.00 0.00 0.00 0.25 2.75 3.50 3.25 1.00 0 0 2 1
#> 119 Male 0.75 0.75 0.25 0.75 0.25 0.50 1.25 0.50 3 3 4 6
#> 120 Male 1.00 0.75 1.00 0.75 0.50 0.25 1.00 0.00 6 2 4 6
#> 121 Female 0.75 0.75 1.00 1.00 1.00 1.00 1.00 1.00 0 0 0 0
#> 122 Female 0.25 0.25 1.00 0.50 0.75 0.75 0.25 0.00 5 1 4 0
#> 123 Male 0.75 0.25 0.50 0.75 1.00 1.00 0.75 0.75 3 0 0 3
#> 124 Male 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 0 2 0
#> 125 Male 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 3 4 4 4
#> 126 Male 0.50 0.75 0.75 1.00 1.00 1.00 1.00 0.75 1 2 0 1
#> 127 Male 0.00 0.00 0.00 0.25 0.00 0.25 0.25 0.00 1 0 0 0
#> 128 Female 0.25 0.00 0.00 0.00 0.75 0.75 1.50 0.25 1 0 0 3
#> 129 Male 0.75 0.50 0.25 0.00 1.00 0.50 1.50 1.25 1 1 0 1
#> 130 Male 2.00 2.00 0.75 1.00 1.50 2.50 1.00 0.75 7 2 5 3
#> 131 Male 0.00 0.25 0.00 0.00 0.00 0.50 0.25 0.25 2 1 3 0
#> 132 Female 0.25 0.25 0.00 0.00 1.25 1.25 0.75 1.25 3 1 1 0
#> 133 Female 0.00 0.50 0.50 0.75 1.75 2.50 2.75 1.75 6 0 1 3
#> 134 Female 0.25 0.50 0.25 0.25 2.00 1.25 1.25 2.00 2 0 1 0
#> 135 Male 1.25 1.25 0.50 0.50 2.25 1.50 2.25 1.50 1 0 1 1
#> 136 Female 2.25 0.50 0.00 0.50 1.75 3.00 4.00 1.25 1 1 2 3
#> 137 Male 0.25 0.25 0.75 2.25 2.00 1.50 1.25 0.25 2 1 1 0
#> 138 Male 0.25 0.75 0.00 0.50 1.00 1.00 1.00 1.25 2 2 4 4
#> 139 Male 1.25 1.50 1.25 1.50 1.25 1.00 2.00 2.00 3 2 3 2
#> 140 Male 0.00 0.50 0.50 0.25 1.25 1.75 1.25 0.50 3 1 0 0
#> 141 Male 0.25 0.25 0.25 0.25 0.75 0.50 0.50 0.00 2 1 1 2
#> 142 Male 1.00 0.50 0.75 2.50 1.25 2.00 3.00 0.25 2 2 0 3
#> 143 Male 0.50 1.00 1.00 1.25 1.50 1.50 1.75 1.00 4 3 4 2
#> 144 Male 0.25 1.00 0.00 0.00 0.25 0.50 0.25 0.00 2 1 5 0
#> 145 Male 2.50 1.50 0.25 0.00 0.25 1.25 1.75 2.00 5 0 2 4
#> 146 Female 0.50 0.50 1.00 1.25 0.25 0.50 1.50 0.25 3 2 2 1
#> 147 Male 0.25 0.25 1.00 0.25 1.00 1.25 1.00 0.50 0 0 1 1
#> 148 Male 0.00 0.50 0.50 1.75 0.50 1.00 0.50 0.25 1 3 2 0
#> 149 Female 1.25 1.25 1.75 1.75 1.00 0.75 0.25 0.25 4 4 2 1
#> 150 Female 0.25 0.00 0.00 0.25 0.75 1.00 1.25 1.00 1 2 3 0
#> 151 Male 0.50 1.00 0.00 0.25 1.00 1.50 0.75 1.00 6 1 2 5
#> 152 Male 0.50 0.00 0.00 0.00 0.25 0.00 0.00 0.25 1 0 1 3
#> 153 Female 1.25 0.75 1.50 2.75 2.50 2.75 1.00 1.00 5 1 3 1
#> 154 Male 1.50 0.50 0.75 0.25 0.75 1.00 1.75 1.50 5 1 6 3
#> 155 Male 1.75 1.00 1.50 0.75 1.00 1.00 1.25 1.00 1 0 1 1
#> 156 Female 0.50 0.00 0.00 0.00 0.00 0.00 0.75 0.75 1 0 0 2
#> 157 Male 1.00 0.75 0.00 0.25 1.25 1.00 0.75 1.25 1 1 0 0
#> 158 Female 0.50 1.00 1.25 0.75 2.00 2.25 1.50 1.75 5 0 2 0
#> 159 Female 0.00 0.75 1.00 0.25 2.50 2.00 2.25 0.00 3 0 3 1
#> 160 Male 0.75 0.75 0.75 0.00 1.00 2.25 2.75 3.25 4 1 4 2
#> 161 Male 0.00 1.25 0.75 0.25 1.75 1.75 1.75 0.00 2 2 3 0
#> 162 Female 0.50 0.50 0.50 1.00 0.50 0.25 1.25 1.25 5 4 6 4
#> 163 Male 0.50 0.25 0.25 0.00 0.75 0.75 1.00 0.25 3 0 5 1
#> 164 Male 1.50 2.00 1.75 1.75 1.25 1.50 2.25 2.00 5 5 7 6
#> 165 Female 0.00 0.00 0.00 0.00 0.25 0.00 0.25 0.00 0 0 4 0
#> 166 Male 1.00 0.75 0.00 0.50 0.25 0.00 0.50 0.00 1 0 0 4
#> 167 Female 0.00 0.75 0.00 0.75 3.00 3.25 3.00 1.00 4 0 0 1
#> 168 Female 0.50 0.50 1.50 1.50 2.50 2.75 2.25 1.25 2 1 1 0
#> 169 Female 0.00 0.00 0.25 1.25 1.25 1.75 3.25 0.75 1 0 1 0
#> 170 Female 0.75 0.25 0.25 0.25 1.00 1.00 1.75 1.50 0 0 1 1
#> 171 Female 0.00 0.25 0.00 0.75 0.75 0.25 0.50 0.25 4 0 1 4
#> 172 Female 0.00 0.00 0.00 0.00 0.00 0.25 0.75 0.00 1 1 2 0
#> 173 Female 0.50 0.00 0.25 1.25 2.50 1.75 1.50 1.00 2 1 3 0
#> 174 Female 0.00 0.00 0.00 0.25 3.00 3.00 1.75 0.50 1 0 0 1
#> 175 Male 1.00 0.75 0.00 0.00 0.25 1.00 1.25 2.00 1 0 4 1
#> 176 Female 0.25 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1 1 4 1
#> 177 Female 0.00 0.00 0.00 0.00 0.00 0.25 1.00 0.00 2 0 2 3
#> 178 Female 1.00 0.50 0.50 1.25 0.50 0.75 1.75 0.50 4 2 4 2
#> 179 Male 0.00 0.25 0.75 0.25 0.00 1.00 2.75 0.50 2 0 1 0
#> 180 Male 0.50 0.75 0.50 0.00 0.25 0.00 1.50 1.00 4 1 2 2
#> 181 Female 0.50 0.25 0.50 1.50 1.00 1.75 2.50 2.00 2 1 4 0
#> 182 Male 1.75 1.75 0.25 0.00 0.25 0.75 0.50 2.00 2 1 2 0
#> 183 Female 0.50 1.25 0.50 0.25 1.50 2.00 1.50 1.00 1 1 1 0
#> 184 Female 0.00 0.25 0.00 0.00 2.00 1.25 1.75 1.50 0 0 1 0
#> 185 Female 0.75 0.75 1.00 0.25 0.25 0.75 2.00 0.25 2 0 2 1
#> 186 Male 0.00 0.25 0.00 0.00 0.25 0.50 2.00 1.25 1 1 2 1
#> 187 Female 0.00 0.25 0.25 0.25 0.75 1.25 1.25 0.75 3 1 2 0
#> 188 Male 1.00 1.00 0.25 0.00 0.00 0.50 0.75 1.25 3 2 5 2
#> 189 Female 0.75 0.75 0.00 0.00 0.75 0.75 1.75 2.00 1 1 4 2
#> 190 Male 0.25 0.75 1.25 1.75 1.75 1.75 1.75 0.75 6 1 4 4
#> 191 Female 0.00 0.75 1.25 0.00 1.75 1.50 1.75 1.00 3 1 3 1
#> 192 Male 1.50 1.25 0.75 0.75 1.25 1.50 1.25 3.25 6 4 4 1
#> 193 Female 0.00 0.25 0.50 1.00 3.00 3.00 2.25 0.25 3 2 3 1
#> 194 Male 0.50 0.50 0.25 0.25 0.25 0.75 1.25 1.00 0 0 2 1
#> 195 Male 0.25 0.25 1.00 0.25 0.00 0.25 1.00 0.25 2 0 1 0
#> 196 Female 1.00 1.75 0.50 1.00 1.75 2.00 2.75 2.50 5 1 5 3
#> 197 Female 0.25 0.50 0.75 1.25 1.75 1.50 1.25 0.75 1 0 0 1
#> 198 Female 0.25 0.50 0.50 1.00 2.25 2.75 1.75 0.00 2 0 2 0
#> 199 Female 0.75 0.00 0.00 0.00 0.00 0.00 0.25 0.00 3 0 1 4
#> 200 Male 0.25 0.00 0.00 0.00 0.00 0.00 0.75 1.00 0 1 4 2
#> 201 Male 0.00 0.00 0.00 0.25 1.25 0.50 1.25 0.50 3 0 4 1
#> 202 Male 0.25 0.50 1.00 1.25 1.75 1.25 0.75 0.25 1 1 2 1
#> 203 Female 0.00 0.00 0.50 0.00 0.50 0.75 0.50 0.00 0 0 0 1
#> 204 Male 0.75 1.00 0.75 2.00 1.25 1.25 1.25 0.75 2 1 4 2
#> 205 Female 0.00 0.00 0.00 0.25 0.25 0.50 0.25 0.25 1 0 0 1
#> 206 Female 0.75 0.50 0.25 0.00 0.00 0.25 0.50 0.50 0 0 2 0
#> 207 Male 1.50 0.50 1.25 0.00 1.25 0.75 0.50 0.75 3 0 4 4
#> 208 Male 0.25 0.00 0.25 0.50 0.25 0.25 0.50 0.50 0 0 0 2
#> 209 Male 0.25 1.25 1.25 3.00 1.25 1.50 1.75 0.75 1 1 4 1
#> 210 Female 1.25 0.50 0.75 0.00 1.00 1.00 1.25 1.00 1 2 0 1
#> 211 Male 0.25 0.00 0.75 0.00 2.50 2.50 2.50 0.75 2 0 3 3
#> 212 Female 0.75 0.50 1.75 1.25 0.75 1.25 1.25 1.25 2 1 2 1
#> 213 Female 0.75 0.00 0.25 0.50 0.50 0.75 0.75 0.75 3 0 1 1
#> 214 Female 0.25 0.50 0.00 0.00 1.75 2.25 2.25 1.50 0 2 2 3
#> 215 Male 1.50 1.50 1.75 2.50 2.25 2.25 2.25 1.50 4 5 7 3
#> 216 Male 1.00 0.75 0.25 0.25 0.75 0.75 1.00 0.25 4 0 5 2
#> 217 Female 1.00 0.50 0.25 0.25 0.25 0.25 0.25 0.50 1 1 0 2
#> 218 Female 0.00 0.50 1.25 1.25 2.25 3.00 2.25 0.00 3 2 2 4
#> 219 Male 1.00 0.75 0.25 2.00 1.50 1.00 0.75 0.25 0 3 3 2
#> 220 Male 1.25 1.50 1.50 1.00 2.75 1.75 2.75 2.25 2 3 6 4
#> 221 Male 0.50 0.75 0.75 0.00 0.25 1.00 1.50 0.25 1 1 4 0
#> 222 Male 1.25 1.25 1.25 1.50 1.25 1.25 1.50 1.50 3 0 1 0
#> 223 Male 0.00 0.50 0.25 0.00 0.00 0.25 0.50 0.25 2 1 4 5
#> 224 Male 0.50 0.00 0.00 1.00 0.50 0.50 1.75 0.00 3 2 1 1
#> 225 Female 1.50 0.50 0.00 0.00 0.25 0.75 1.25 2.50 4 0 0 2
#> 226 Female 0.50 0.25 0.00 1.75 1.75 1.50 1.50 1.00 1 1 0 0
#> 227 Male 0.75 1.00 0.75 1.00 1.25 1.00 1.00 1.00 4 2 2 1
#> 228 Female 0.00 0.00 0.00 0.25 1.50 1.25 1.50 0.25 2 0 2 1
#> 229 Male 1.00 0.25 0.00 0.00 0.25 0.25 1.00 1.25 2 0 1 0
#> 230 Female 0.00 0.25 0.25 1.25 2.25 2.00 2.00 1.00 2 0 0 0
#> 231 Male 0.50 0.25 0.25 0.00 1.00 0.50 0.75 0.25 2 0 0 2
#> 232 Male 0.75 0.75 1.00 0.25 0.25 0.75 1.25 1.50 1 0 1 5
#> 233 Female 0.00 0.00 2.50 3.50 4.00 3.00 3.25 0.00 1 2 3 1
#> 234 Male 0.00 0.00 0.00 0.25 0.75 0.50 0.75 0.25 2 1 0 0
#> 235 Male 0.75 1.75 1.75 3.50 3.00 2.00 2.50 2.50 3 2 5 1
#> 236 Female 0.50 0.25 0.50 0.00 0.00 0.50 0.75 2.00 3 2 1 2
#> 237 Female 0.25 0.00 0.50 1.00 1.75 0.75 1.75 0.00 3 2 1 1
#> 238 Female 0.00 0.00 0.00 0.50 4.00 3.00 3.00 3.00 0 0 1 2
#> 239 Male 0.50 0.50 0.50 0.25 0.25 1.00 1.25 0.75 3 0 0 2
#> 240 Female 0.25 0.50 1.50 1.50 2.25 2.50 2.00 1.75 3 0 2 1
#> 241 Female 1.25 1.00 0.00 0.25 0.50 1.50 1.50 1.50 4 0 2 2
#> 242 Female 1.25 0.25 0.25 0.00 0.25 1.00 2.00 1.25 3 2 2 1
#> 243 Male 2.50 1.75 2.00 2.25 2.25 2.25 1.50 1.00 0 1 1 4
#> 244 Male 0.50 0.50 0.25 1.25 1.75 2.00 1.25 1.25 1 0 4 1
#> 245 Male 0.75 0.75 1.50 0.50 2.50 2.00 1.75 1.25 3 1 0 1
#> 246 Female 0.75 1.00 0.00 0.25 1.25 1.25 1.50 1.00 3 2 2 1
#> 247 Female 0.75 0.25 0.75 1.25 2.75 3.50 2.25 1.50 5 0 2 0
#> 248 Female 0.25 1.25 2.50 3.25 1.50 2.00 3.25 0.00 6 3 3 0
#> 249 Male 0.00 0.00 0.00 0.00 1.50 1.75 1.50 0.25 2 0 1 0
#> 250 Male 0.25 0.00 0.25 1.50 1.75 1.50 1.75 0.00 1 0 1 2
#> 251 Female 0.50 0.25 0.50 0.50 0.50 0.75 1.25 0.00 4 1 3 1
#> 252 Male 0.00 0.00 0.00 0.00 1.00 1.25 0.75 0.50 2 0 0 1
#> 253 Male 0.25 0.25 0.00 0.50 1.25 0.75 2.00 2.50 1 1 1 0
#> 254 Female 1.00 0.50 0.75 0.50 1.25 2.00 2.50 1.25 7 3 5 2
#> 255 Female 0.25 0.25 1.25 0.50 1.25 1.50 2.50 1.25 4 0 3 2
#> 256 Female 3.25 1.25 0.75 0.50 0.25 0.00 0.50 0.00 3 2 0 0
#> 257 Male 2.00 0.75 1.00 1.00 1.00 0.75 1.25 1.00 6 2 2 5
#> 258 Female 1.00 0.75 0.25 0.50 1.75 1.50 1.50 2.00 2 0 0 2
#> 259 Female 0.00 0.00 0.00 0.25 1.25 1.50 1.25 0.50 1 0 1 0
#> 260 Female 0.25 0.00 0.00 0.00 1.25 1.50 3.00 0.00 2 1 0 0
#> 261 Male 0.00 0.00 0.00 0.25 1.50 0.75 1.25 0.25 2 0 0 1
#> 262 Female 0.25 0.00 0.00 0.00 1.00 1.00 1.75 0.25 2 1 3 1
#> 263 Male 0.00 0.25 0.25 0.50 0.75 0.50 0.75 0.25 4 1 3 4
#> 264 Female 0.50 0.50 1.00 1.25 0.25 0.50 0.25 0.50 1 1 3 1
#> 265 Female 1.00 0.25 0.25 0.25 1.50 1.50 1.25 2.25 3 0 1 1
#> 266 Female 2.50 1.25 0.50 0.50 1.50 1.00 1.25 2.00 5 0 6 3
#> 267 Male 0.00 0.50 0.50 0.50 0.75 1.50 2.25 1.25 5 2 5 4
#> 268 Male 0.50 0.50 0.00 0.75 1.00 1.00 0.75 0.00 3 2 2 1
#> 269 Male 0.50 0.50 0.00 0.25 0.50 0.50 2.00 0.75 3 0 3 3
#> 270 Male 0.25 0.50 0.50 1.25 1.75 1.50 1.75 1.00 2 0 1 0
#> 271 Female 0.50 1.50 0.25 2.25 2.25 2.25 0.75 0.00 3 3 4 0
#> 272 Male 0.75 0.50 0.50 0.50 0.75 1.00 1.00 0.50 1 0 2 0
#> 273 Male 1.25 2.00 1.00 1.75 3.00 3.50 3.25 3.00 4 2 4 5
#> 274 Male 0.50 0.25 0.00 0.00 0.00 0.00 0.50 0.50 3 1 3 1
#> 275 Male 0.00 0.50 0.25 1.00 0.50 1.25 1.75 0.75 4 0 4 0
#> 276 Female 0.50 0.50 1.00 1.75 1.50 1.25 1.75 1.00 3 2 3 2
#> 277 Female 0.75 0.50 0.50 1.00 1.50 1.00 1.00 1.00 4 0 3 4
#> 278 Female 0.25 0.00 0.00 0.00 0.00 0.25 0.25 0.75 0 0 0 0
#> 279 Male 0.50 0.75 1.25 1.25 0.00 0.25 2.00 1.25 5 1 4 1
#> 280 Male 1.00 0.50 0.25 0.00 0.25 1.00 1.00 1.00 3 1 5 0
#> 281 Male 0.50 0.75 0.00 0.25 1.25 1.50 0.50 0.00 2 0 1 0
#> 282 Female 0.25 0.75 1.50 1.00 0.00 0.00 0.75 0.00 4 2 5 1
#> 283 Male 0.50 0.25 0.00 1.00 0.50 0.50 1.00 0.50 1 1 2 1
#> 284 Female 0.50 0.25 2.25 0.50 0.50 1.25 1.00 1.00 2 0 2 3
#> 285 Female 0.25 0.50 0.50 1.00 1.25 1.50 1.00 0.00 3 1 3 1
#> 286 Male 0.75 0.25 0.00 0.75 1.75 1.25 2.00 0.50 2 0 0 1
#> 287 Female 0.00 0.25 0.25 0.50 1.00 1.00 1.50 1.00 0 0 0 0
#> 288 Male 0.00 0.00 0.50 0.00 0.00 0.00 0.50 0.00 4 1 2 4
#> 289 Female 1.00 1.25 0.00 0.25 0.00 0.75 2.75 1.50 4 0 3 3
#> 290 Male 1.00 1.50 1.75 1.50 2.50 2.75 2.50 0.75 1 1 2 1
#> 291 Female 1.00 0.00 0.00 0.00 1.00 1.00 0.75 0.25 3 1 2 1
#> 292 Female 0.00 0.00 0.00 0.50 1.25 0.75 1.00 0.00 2 0 2 2
#> 293 Female 0.00 0.00 0.00 0.50 1.00 2.50 3.00 2.75 3 0 5 2
#> 294 Male 0.75 1.00 0.50 0.75 0.75 0.25 1.50 0.25 5 0 3 2
#> 295 Male 0.00 0.00 0.00 0.00 0.00 0.75 0.75 0.50 0 0 0 3
#> 296 Male 0.50 0.25 0.75 1.00 0.75 1.00 1.75 0.25 1 1 1 3
#> 297 Female 0.25 0.25 0.00 0.25 2.75 3.00 3.25 2.25 2 1 2 2
#> 298 Female 1.00 2.00 1.00 0.25 1.00 2.00 1.00 1.50 5 4 3 3
#> 299 Male 1.50 1.75 0.25 0.00 1.25 1.75 1.75 1.75 5 0 2 2
#> 300 Female 0.75 0.25 0.00 0.25 0.50 2.00 3.50 3.00 2 0 1 2
#> 301 Male 1.25 0.75 1.75 2.25 2.25 1.75 2.00 0.50 2 2 6 2
#> 302 Female 0.75 0.25 1.25 1.00 0.75 2.00 2.75 1.50 3 2 1 0
#> 303 Male 0.25 0.00 0.50 0.25 0.75 0.50 1.00 0.50 1 1 1 2
#> 304 Female 1.50 1.25 1.00 1.00 1.75 1.75 1.75 2.00 3 1 3 2
#> 305 Female 0.00 0.00 0.25 0.00 1.25 1.00 2.50 1.00 2 2 1 0
#> 306 Female 0.00 1.00 0.25 0.00 2.75 3.00 2.25 1.75 5 0 3 1
#> 307 Female 0.00 0.00 0.00 0.00 0.00 0.25 0.75 0.00 1 1 3 0
#> 308 Male 0.00 0.00 0.00 0.25 1.25 1.00 1.75 0.50 1 0 0 2
#> 309 Female 0.75 1.00 0.25 0.00 1.25 1.75 1.75 1.50 4 0 1 2
#> 310 Female 0.25 0.50 0.00 0.00 0.75 0.25 2.00 3.25 2 0 2 0
#> 311 Male 0.00 0.25 0.00 0.00 0.00 0.25 0.25 0.50 4 1 2 2
#> 312 Female 2.25 2.00 0.75 0.75 0.50 0.00 2.25 0.25 6 2 4 4
#> 313 Male 0.00 1.00 0.50 0.50 2.50 2.25 3.00 1.75 4 2 5 0
#> 314 Female 0.50 1.00 1.50 0.00 0.00 0.75 1.25 0.50 5 3 3 3
#> 315 Male 1.00 0.75 0.75 0.00 1.75 1.25 2.75 1.25 6 1 4 3
#> 316 Female 0.75 0.50 0.00 0.00 0.25 0.75 2.00 2.50 3 0 3 4
#> 317 Female 1.75 1.25 2.00 1.75 2.00 3.50 4.00 1.25 6 3 5 5
#> 318 Female 0.50 1.75 2.25 0.25 1.25 2.25 3.00 1.25 4 2 2 1
#> 319 Female 0.00 0.25 0.00 0.00 0.75 0.75 1.25 1.25 1 0 1 2
#> 320 Female 0.75 0.00 0.00 0.00 0.00 0.00 0.50 1.00 3 2 4 3
#> 321 Female 0.50 0.50 0.75 0.00 0.25 0.25 1.50 1.25 2 1 2 0
#> 322 Male 0.50 0.25 0.75 1.25 1.00 0.75 1.25 0.25 3 1 4 1
#> 323 Female 0.00 0.00 0.00 1.00 1.00 1.00 0.75 0.50 3 0 0 1
#> 324 Male 1.00 0.50 0.00 0.00 0.00 0.00 0.75 1.00 2 0 1 3
#> 325 Female 1.50 0.75 1.50 0.50 1.50 1.75 2.25 0.50 6 3 2 2
#> 326 Male 0.25 0.75 0.75 0.75 0.50 0.50 0.75 0.25 2 0 0 4
#> 327 Female 0.00 0.25 0.00 0.50 0.50 0.75 1.50 0.25 1 0 2 0
#> 328 Female 1.50 0.75 1.00 0.25 0.25 1.25 1.50 1.00 6 2 5 2
#> 329 Female 0.00 0.00 0.50 1.75 3.00 2.75 2.00 0.75 0 1 2 1
#> 330 Female 0.75 0.50 0.25 1.50 1.50 1.25 0.75 1.00 3 0 4 1
#> 331 Female 1.00 2.50 0.25 0.00 0.25 0.75 1.25 1.50 6 0 2 3
#> 332 Male 0.75 0.50 1.00 0.75 1.75 0.75 1.50 1.00 1 0 0 1
#> 333 Female 0.50 0.50 2.25 2.75 2.00 2.50 0.25 0.25 5 3 3 4
#> 334 Female 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1 0 1 1
#> 335 Male 0.50 0.75 0.00 1.25 0.50 0.50 1.00 0.50 3 2 4 3
#> 336 Male 0.25 0.00 0.00 0.75 0.25 0.25 0.75 0.25 3 2 3 4
#> 337 Male 0.00 0.00 1.50 3.50 1.25 0.00 2.00 0.00 3 3 4 2
#> 338 Female 0.50 0.25 0.00 1.00 0.50 0.25 0.00 0.00 1 2 0 0
#> 339 Female 0.00 0.00 0.00 0.00 0.25 0.50 1.50 0.25 1 2 0 0
#> 340 Male 0.00 0.00 0.00 0.00 0.75 0.50 0.75 0.25 2 0 3 0
#> 341 Male 0.25 0.50 0.00 0.00 0.00 1.00 1.75 1.00 4 0 4 2
#> 342 Female 1.50 0.75 0.25 1.25 2.50 2.75 2.25 2.50 0 1 0 0
#> 343 Female 0.50 0.25 0.75 0.00 0.00 0.25 0.75 1.00 3 2 3 5
#> 344 Female 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 1 0 1
#> 345 Male 0.00 0.00 0.00 0.00 0.00 0.50 1.00 0.25 0 1 1 0
#> 346 Male 0.00 0.00 0.25 0.75 2.25 2.75 2.25 1.00 5 2 5 2
#> 347 Male 0.50 0.75 0.75 1.75 1.25 1.00 0.50 0.25 2 0 2 1
#> 348 Female 0.00 0.25 0.00 0.00 0.75 0.50 1.25 1.25 0 0 1 0
#> 349 Male 0.50 0.00 0.00 0.00 0.25 0.25 0.50 0.00 2 1 3 0
#> 350 Male 0.25 0.00 0.00 1.50 1.75 2.25 2.00 1.25 1 0 2 0
#> 351 Male 0.00 0.50 0.00 0.50 0.75 0.25 0.00 0.00 1 3 2 1
#> 352 Male 0.00 0.00 0.00 0.00 0.25 0.50 0.25 0.00 0 1 1 0
#> 353 Female 0.25 0.00 0.75 1.25 1.50 2.00 0.75 0.75 2 2 7 2
#> 354 Male 0.00 0.00 0.00 0.00 0.00 0.50 0.25 0.50 2 1 3 3
#> 355 Female 0.25 0.00 0.25 0.00 0.00 0.00 1.00 0.50 3 2 2 0
#> 356 Male 0.25 0.25 0.00 0.75 1.25 1.50 1.25 0.50 1 0 2 0
#> 357 Male 0.25 0.00 0.75 0.00 0.00 0.00 0.00 1.25 1 0 3 0
#> 358 Male 0.25 0.00 1.00 1.25 0.00 0.25 1.00 0.00 1 2 0 2
#> 359 Female 0.00 0.00 0.00 0.25 0.75 0.50 0.75 0.00 0 1 1 1
#> 360 Female 0.50 0.25 0.00 0.00 3.00 3.00 2.75 2.50 0 0 2 0
#> 361 Male 0.25 0.50 0.00 0.50 0.75 0.75 1.00 1.75 2 0 1 0
#> 362 Male 1.00 1.00 0.00 1.75 1.00 0.25 1.50 0.75 3 1 4 0
#> 363 Male 0.00 0.00 0.00 0.00 0.25 0.00 0.75 0.25 0 0 1 0
#> 364 Male 0.75 1.75 2.00 1.25 0.75 0.25 0.25 0.25 4 3 4 3
#> 365 Male 0.25 0.00 0.00 0.00 1.25 1.00 1.50 1.50 3 1 2 2
#> 366 Female 0.50 0.25 0.75 1.00 1.00 1.25 3.00 1.00 5 1 4 2
#> 367 Female 1.50 1.00 1.00 1.25 0.00 0.75 1.00 1.50 4 2 3 1
#> 368 Male 1.00 1.00 0.50 1.25 1.25 1.25 1.25 0.50 4 0 5 1
#> 369 Female 1.75 1.00 1.25 1.25 1.00 1.50 1.25 1.25 4 2 4 4
#> 370 Female 0.25 0.50 0.25 0.00 1.50 1.25 1.00 0.25 0 0 0 1
#> 371 Female 0.00 0.00 0.50 0.50 1.00 1.00 0.75 0.00 2 3 2 2
#> 372 Female 0.50 0.25 0.00 0.00 2.00 2.50 3.25 0.75 0 0 0 0
#> 373 Female 0.50 0.50 0.00 0.25 1.25 1.00 1.50 1.50 3 1 2 0
#> 374 Male 0.25 0.75 0.25 0.25 1.00 0.50 1.75 1.75 3 0 1 0
#> 375 Male 0.50 1.25 0.75 1.50 2.75 3.00 2.00 0.75 4 3 3 3
#> 376 Male 0.75 0.00 0.00 0.25 0.25 0.25 0.50 1.00 0 1 0 1
#> 377 Female 0.00 0.50 1.00 1.25 1.50 1.00 1.50 0.00 4 3 3 2
#> 378 Male 0.25 0.50 1.50 0.25 0.25 0.50 0.50 0.25 2 1 1 3
#> 379 Male 0.25 0.25 1.00 1.00 2.25 1.25 1.50 0.50 1 1 1 2
#> 380 Male 0.00 0.25 0.25 1.25 0.75 0.50 0.25 0.50 1 1 3 2
#> 381 Male 0.50 1.00 0.50 0.25 0.50 0.50 1.00 0.50 2 0 3 5
#> 382 Female 0.00 1.00 1.75 1.25 3.25 2.50 2.25 1.50 3 2 6 2
#> 383 Male 0.25 0.25 0.25 0.25 0.75 0.25 0.00 0.25 1 1 1 4
#> 384 Male 0.25 1.00 0.50 0.00 0.00 0.00 1.00 0.00 2 1 2 3
#> 385 Female 0.00 0.50 0.25 0.50 2.00 2.50 2.75 1.00 2 1 2 0
#> 386 Female 0.25 0.25 0.50 0.75 0.75 0.00 0.75 0.50 4 1 4 2
#> 387 Female 0.75 1.00 1.25 1.25 2.25 2.00 1.75 1.75 6 2 3 6
#> 388 Female 0.75 0.50 0.50 0.00 0.75 0.75 1.00 0.25 3 1 1 2
#> 389 Male 0.75 2.25 1.75 2.50 2.50 2.75 1.75 0.25 3 3 5 3
#> 390 Female 0.75 0.25 0.50 0.50 1.00 0.50 0.50 1.00 0 0 0 1
#> 391 Female 0.25 0.25 0.75 0.00 1.75 1.25 0.50 0.75 2 1 0 4
#> 392 Male 0.25 0.50 0.00 1.00 1.25 1.50 2.00 0.75 1 0 0 0
#> 393 Male 1.50 1.25 1.00 1.00 2.50 2.00 2.00 0.75 2 2 2 4
#> 394 Male 0.25 0.00 0.00 0.75 1.50 0.50 1.25 0.25 0 0 0 1
#> 395 Male 1.50 1.50 1.50 1.50 1.50 1.25 1.00 1.00 6 3 4 4
#> 396 Female 0.25 0.00 0.25 0.00 1.25 0.75 1.00 0.25 0 1 4 1
#> 397 Male 0.75 1.25 0.50 1.00 1.50 1.50 0.50 0.75 5 1 4 0
#> 398 Male 0.75 0.25 1.25 0.00 1.75 2.00 1.25 0.75 3 2 1 5
#> 399 Male 0.50 0.25 0.00 1.00 1.50 1.50 0.75 0.25 1 0 3 0
#> 400 Female 0.50 0.50 1.00 1.00 1.50 1.00 0.75 0.75 4 1 5 5
#> 401 Female 0.00 0.00 0.00 0.75 1.50 1.50 2.50 0.25 1 0 4 0
#> 402 Male 0.25 0.50 0.50 0.50 0.25 0.50 0.50 0.00 0 0 0 2
#> 403 Female 0.25 0.00 0.00 0.00 0.00 0.00 0.75 0.00 0 0 0 0
#> 404 Female 0.00 0.00 0.75 1.25 1.25 1.25 2.00 0.00 1 1 0 0
#> 405 Female 0.00 0.00 0.50 0.00 2.25 2.25 2.00 0.50 2 0 1 0
#> 406 Male 0.75 1.25 1.50 2.25 1.00 1.00 1.75 0.75 7 1 6 5
#> 407 Female 2.50 2.00 1.75 1.75 2.00 1.50 1.75 2.00 3 4 6 2
#> 408 Male 0.50 0.00 0.25 0.00 2.00 1.25 0.75 0.50 1 1 3 0
#> 409 Male 0.75 1.75 1.50 0.00 1.00 0.25 0.50 3.00 2 1 3 1
#> 410 Female 0.00 0.00 0.00 0.50 2.00 1.50 3.00 1.50 3 2 3 1
#> 411 Female 0.25 0.00 0.00 0.25 1.00 0.50 0.50 0.00 0 0 0 0
#> 412 Male 0.25 0.50 1.50 1.50 2.25 0.75 1.00 0.25 2 1 3 1
#> 413 Female 0.75 1.00 1.50 1.00 2.75 2.75 3.50 0.00 3 1 2 1
#> 414 Female 0.00 0.25 1.00 1.00 3.00 3.25 2.75 1.75 2 0 1 1
#> 415 Female 0.25 0.00 0.00 0.00 3.00 2.75 3.50 2.75 0 0 0 1
#> 416 Male 0.25 0.00 0.50 1.25 2.25 1.75 2.00 2.00 0 3 0 2
#> 417 Female 0.75 0.00 0.00 0.00 0.75 1.00 1.50 1.50 0 0 0 0
#> 418 Female 0.00 0.00 0.50 0.25 1.25 1.00 1.00 0.25 1 2 4 1
#> 419 Male 0.00 1.25 0.00 0.00 0.75 0.50 3.25 1.25 4 1 5 2
#> 420 Male 0.00 0.00 0.00 0.00 1.00 0.50 1.00 0.25 0 1 0 1
#> 421 Male 0.75 1.00 0.25 1.25 1.75 1.00 1.00 0.25 3 0 2 0
#> 422 Male 1.00 1.25 0.75 0.75 2.00 1.75 2.50 1.75 3 0 2 1
#> 423 Female 0.25 0.25 0.00 0.00 0.75 1.00 1.50 0.50 0 0 0 2
#> 424 Female 1.25 1.00 1.00 0.00 1.50 1.50 2.00 0.25 4 0 2 1
#> 425 Male 1.00 0.25 0.50 0.00 0.25 0.75 1.00 1.25 3 2 4 2
#> 426 Male 0.50 0.50 1.00 1.75 1.00 0.50 0.25 0.50 2 1 3 1
#> 427 Male 0.00 0.00 0.00 0.25 0.75 1.25 0.75 1.25 1 2 2 2
#> 428 Female 0.50 0.00 0.00 0.00 0.25 0.25 1.00 0.00 2 0 1 0
#> 429 Male 1.75 1.25 1.50 2.50 2.75 1.50 1.75 1.00 3 0 1 0
#> 430 Male 1.00 1.25 2.00 2.75 2.50 3.25 3.25 1.00 5 1 6 1
#> 431 Female 0.00 0.00 0.25 0.50 1.25 1.00 0.50 0.50 0 0 3 0
#> 432 Male 2.25 1.75 0.50 0.25 0.25 0.75 1.75 2.50 6 3 4 7
#> 433 Male 1.75 1.00 0.25 0.25 1.00 1.50 2.25 1.50 2 0 4 4
#> 434 Male 0.50 0.75 0.00 0.00 0.00 0.00 0.75 1.00 2 0 1 2
#> 435 Female 0.00 0.25 1.75 1.00 2.50 3.00 3.25 1.00 4 3 3 1
#> 436 Female 0.50 0.50 1.00 0.00 0.00 0.00 1.00 1.00 3 1 3 1
#> 437 Female 0.00 0.00 0.00 0.25 0.25 0.25 0.00 0.25 0 0 0 1
#> 438 Female 0.50 1.25 1.00 1.00 2.75 3.00 2.50 1.50 4 1 6 2
#> 439 Female 0.00 0.25 0.00 0.25 1.25 1.25 0.50 0.75 1 1 0 4
#> 440 Male 0.25 0.50 1.00 0.50 1.00 0.75 1.00 0.00 2 0 3 1
#> 441 Female 1.25 1.25 0.75 0.75 0.75 0.75 0.25 1.75 7 0 5 5
#> 442 Male 0.50 1.25 0.00 1.00 1.25 1.50 1.75 1.00 3 1 1 1
#> 443 Male 0.00 0.00 0.00 0.00 0.25 0.00 0.75 0.25 1 0 1 2
#> 444 Male 1.00 0.00 0.25 0.25 0.50 0.25 2.50 0.25 3 2 3 1
#> 445 Female 1.50 1.00 0.00 0.00 0.25 1.00 1.75 2.25 2 2 1 4
#> 446 Male 0.00 0.50 0.25 0.00 0.75 1.75 3.00 1.50 5 1 3 0
#> 447 Female 0.75 0.25 1.00 0.75 1.25 1.50 2.00 0.25 2 0 2 0
#> 448 Female 0.50 0.50 0.50 0.50 1.50 1.75 1.75 1.75 3 0 1 0
#> 449 Female 0.00 0.00 0.50 0.50 3.00 3.00 2.75 0.00 3 0 1 1
#> 450 Female 0.75 0.75 1.75 1.75 1.50 1.00 1.25 1.25 5 2 6 5
#> 451 Female 0.25 0.25 0.00 0.50 1.00 1.50 1.75 1.00 1 1 2 0
#> 452 Female 0.25 0.25 0.50 0.25 0.25 0.25 1.00 0.25 4 2 3 0
#> 453 Female 0.25 0.25 1.00 1.50 2.50 3.00 2.25 1.00 2 0 0 2
#> 454 Female 0.75 0.00 0.50 0.00 0.00 0.75 1.25 1.00 2 2 0 0
#> 455 Female 0.25 0.25 0.25 0.00 0.25 1.75 2.25 0.25 1 0 2 2
#> 456 Female 0.00 0.50 0.75 2.00 3.25 2.25 2.25 0.25 1 2 5 1
#> 457 Male 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 2 1 1 0
#> 458 Male 1.25 1.00 2.00 3.00 1.75 0.50 0.75 0.50 5 2 7 6
#> 459 Male 3.00 3.00 3.00 3.00 1.25 0.25 0.00 1.75 4 4 7 1
#> 460 Female 0.75 2.00 1.50 2.75 3.25 3.75 2.75 1.75 4 1 2 1
#> 461 Female 0.00 0.25 1.00 0.50 0.50 1.00 1.00 0.00 4 1 1 1
#> 462 Male 0.50 1.50 0.50 1.75 1.50 1.50 1.25 2.00 3 0 2 5
#> 463 Female 0.00 0.00 0.00 0.25 1.00 1.75 1.75 1.25 2 1 4 2
#> 464 Female 0.75 0.50 1.00 1.50 0.50 0.75 1.00 1.00 3 0 4 1
#> 465 Female 0.00 0.00 0.00 0.00 1.00 1.25 1.75 0.75 0 0 0 0
#> 466 Female 0.25 0.50 0.50 0.00 0.75 0.50 1.25 0.25 0 0 1 0
#> 467 Female 0.75 0.50 0.25 0.50 0.75 0.75 1.00 0.00 0 0 1 0
#> 468 Female 0.00 0.25 0.00 0.25 1.25 1.50 2.25 1.75 2 1 1 0
#> 469 Female 1.75 0.50 0.25 0.00 0.00 0.00 0.75 1.50 3 1 2 6
#> 470 Female 0.25 0.25 0.25 0.00 1.75 2.75 2.25 2.75 1 0 3 1
#> 471 Female 0.25 0.00 0.00 1.00 2.00 1.75 1.00 0.00 4 0 0 0
#> 472 Male 1.25 0.75 0.75 0.50 0.50 0.50 1.50 2.50 1 1 3 2
#> 473 Female 0.25 0.75 0.75 2.00 3.50 2.75 2.25 2.25 6 4 2 3
#> 474 Female 1.00 0.75 1.25 1.25 1.25 0.75 1.25 0.75 3 1 6 3
#> 475 Female 0.00 0.25 0.25 0.00 1.75 2.50 2.25 0.50 1 0 4 0
#> 476 Female 1.75 1.75 1.50 1.00 1.00 0.25 0.75 1.25 3 3 2 2
#> 477 Male 0.00 1.75 0.50 0.75 1.50 1.50 0.75 0.50 1 0 1 0
#> 478 Female 0.50 0.25 0.50 0.00 0.25 0.25 0.75 0.50 2 1 4 3
#> 479 Female 0.00 0.75 2.00 1.75 2.50 2.50 1.75 1.00 2 0 1 1
#> 480 Female 0.25 0.00 0.75 0.75 2.50 2.50 2.75 0.00 0 1 1 1
#> 481 Male 0.25 0.25 1.00 2.00 1.75 1.50 2.50 0.50 1 1 4 0
#> 482 Female 0.75 1.50 0.00 2.00 2.75 2.00 3.00 1.50 2 1 3 3
#> 483 Female 1.25 1.00 2.25 0.50 1.50 1.50 1.50 2.25 3 1 4 2
#> 484 Female 0.00 1.50 0.50 1.25 2.25 2.50 2.00 0.75 2 4 2 0
#> 485 Female 0.25 0.50 1.50 0.75 1.50 1.25 1.25 0.50 3 0 1 2
#> 486 Male 1.50 2.50 1.00 0.75 0.75 1.00 0.75 2.25 1 2 2 2
#> 487 Female 0.00 0.00 0.00 0.00 2.75 1.50 2.50 1.75 2 0 5 1
#> 488 Female 0.75 0.75 0.50 0.00 0.25 0.00 1.50 0.25 4 1 2 1
#> 489 Male 0.50 1.00 2.00 2.50 0.75 1.25 2.00 2.50 1 1 1 0
#> 490 Male 0.00 0.50 1.25 0.00 1.00 1.00 1.50 1.75 3 2 1 1
#> 491 Male 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4 0 4 2
#> 492 Female 0.50 1.75 0.75 1.25 1.75 1.25 2.00 1.00 5 1 5 3
#> 493 Male 0.00 0.75 0.00 1.25 2.50 2.00 2.00 1.75 3 1 4 4
#> 494 Male 0.00 0.75 1.25 1.00 1.50 1.75 1.75 0.50 2 1 2 2
#> 495 Male 0.50 0.25 0.50 0.75 1.50 1.00 2.00 0.25 3 1 2 1
#> 496 Female 0.00 0.00 0.00 0.75 2.00 1.75 1.75 0.50 0 0 1 0
#> 497 Female 2.00 1.25 0.25 1.00 0.00 0.25 0.75 1.00 5 0 3 2
#> 498 Female 0.50 0.50 0.00 0.00 0.25 0.50 0.75 0.00 2 1 2 0
#> 499 Female 0.00 0.00 0.50 1.50 2.00 2.50 1.50 1.25 0 0 2 1
#> 500 Female 0.25 0.50 0.00 0.00 1.25 1.50 2.00 1.25 4 0 2 2
#> 501 Male 1.25 1.50 0.25 0.00 0.00 0.00 0.25 0.75 2 1 1 4
#> 502 Female 0.00 0.50 0.00 0.00 0.75 0.75 0.75 1.00 1 0 2 0
#> 503 Female 1.00 1.00 0.50 0.50 3.75 2.50 2.50 2.00 4 0 0 0
#> 504 Female 0.00 0.00 0.00 0.00 0.00 0.00 0.75 1.25 2 2 1 2
#> 505 Female 0.50 0.50 0.50 0.25 0.25 0.75 1.25 0.75 1 1 0 2
#> 506 Female 1.00 1.00 0.00 0.50 0.00 1.50 1.25 1.50 4 1 3 3
#> 507 Male 1.00 1.25 0.25 0.25 0.25 0.75 1.50 1.50 3 1 2 1
#> 508 Female 0.00 0.00 0.25 0.50 1.75 1.75 1.25 0.00 1 0 3 0
#> 509 Female 0.50 0.00 0.00 0.00 0.00 0.00 0.25 0.50 2 0 2 4
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#> 511 Male 1.25 0.75 1.00 2.00 1.75 1.25 0.75 0.25 4 4 5 2
#> 512 Female 1.50 0.25 0.00 0.00 0.50 0.50 1.75 0.75 4 2 2 2
#> 513 Female 0.25 0.00 0.00 0.00 0.00 0.25 0.25 0.75 0 1 1 0
#> 514 Female 0.00 0.25 0.00 0.25 1.25 1.50 1.75 1.50 1 0 2 0
#> 515 Female 0.00 0.00 0.00 0.00 1.00 2.00 2.75 1.75 2 0 3 0
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#> 517 Male 0.50 0.00 0.00 0.50 1.50 1.50 3.00 1.50 4 2 2 1
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#> 520 Male 0.50 1.00 1.25 1.50 1.00 1.00 1.25 0.50 4 0 5 4
#> 521 Female 2.00 1.50 0.75 0.00 0.00 0.00 0.00 1.50 5 2 0 3
#> 522 Female 0.25 1.75 1.25 4.00 4.00 2.25 2.75 1.25 4 2 4 2
#> 523 Female 0.25 0.50 0.00 0.50 2.25 2.75 4.00 0.25 3 0 4 0
#> 524 Female 0.00 0.00 0.00 0.00 0.25 1.00 0.75 0.75 1 1 4 1
#> 525 Female 1.25 1.00 0.75 1.00 1.50 1.25 1.25 3.00 6 0 3 0
#> 526 Female 0.25 0.25 0.00 0.00 0.00 0.00 1.50 0.25 1 1 0 1
#> 527 Female 1.75 0.25 0.50 1.75 0.50 0.00 1.00 1.00 5 2 3 3
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#> 529 Male 0.25 0.25 0.00 0.25 0.50 0.75 1.25 0.50 3 0 3 1
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#> 532 Male 0.50 0.50 1.00 1.75 2.25 1.75 1.25 0.75 3 1 1 1
#> 533 Female 0.25 0.25 0.00 0.50 1.00 0.75 0.50 0.75 0 0 1 0
#> 534 Female 0.50 0.25 1.75 1.00 1.50 1.25 2.50 2.75 5 2 4 1
#> 535 Male 0.00 0.25 1.00 0.00 0.25 0.00 0.50 2.25 4 6 4 5
#> 536 Female 0.50 0.75 0.50 0.25 0.75 0.25 0.75 1.50 1 1 1 5
#> 537 Male 1.00 0.25 0.75 0.00 0.50 0.50 1.75 1.00 4 0 4 1
#> 538 Male 0.00 0.00 0.00 0.50 0.50 1.75 1.75 0.00 0 1 1 3
#> 539 Female 0.50 0.25 0.50 0.50 0.50 0.25 0.00 0.00 1 2 0 1
#> 540 Male 0.00 0.50 2.25 0.75 0.00 0.25 0.00 0.25 1 3 3 2
#> 541 Female 0.00 0.25 2.00 3.25 4.00 3.00 2.75 0.00 2 2 2 0
#> 542 Female 0.25 0.00 0.00 0.50 0.75 1.00 0.75 1.50 0 3 2 0
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#> 544 Male 0.25 0.50 1.25 1.50 1.75 1.00 1.00 0.00 2 1 3 0
#> 545 Male 0.25 0.00 0.00 0.00 0.00 0.50 0.50 0.25 2 1 1 0
#> 546 Male 1.50 1.25 1.75 2.00 1.75 2.25 2.00 1.75 0 1 1 3
#> 547 Male 0.50 0.50 0.00 1.00 0.00 0.00 0.75 0.75 3 1 4 1
#> 548 Female 0.25 0.25 0.00 0.25 0.50 1.00 0.50 1.00 2 0 0 0
#> 549 Male 0.25 1.00 2.00 3.50 3.25 2.75 1.25 1.00 3 3 3 2
#> 550 Female 2.00 3.00 4.00 1.75 1.75 0.75 0.00 0.25 5 5 6 6
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#> 552 Male 0.25 0.00 0.00 0.00 1.25 1.25 0.75 0.00 0 0 1 2
#> 553 Male 0.50 1.00 3.25 0.50 0.00 0.50 0.00 0.00 1 2 2 3
#> 554 Male 0.75 1.00 0.75 2.50 2.25 2.25 1.75 0.25 3 2 2 1
#> 555 Female 0.25 0.00 1.00 2.50 2.00 1.75 2.50 0.25 3 2 1 1
#> 556 Male 0.75 0.00 1.00 1.75 1.00 0.50 0.50 0.50 1 1 0 0
#> 557 Male 1.00 1.50 0.50 0.50 0.50 0.25 0.00 0.00 2 3 3 1
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#> 560 Male 0.00 0.00 0.00 0.00 1.00 1.25 1.75 2.50 5 0 4 4
#> 561 Female 1.00 1.00 1.50 2.75 2.50 1.75 1.50 1.50 0 0 1 0
#> 562 Female 0.50 0.75 2.25 1.50 1.75 0.75 0.75 1.00 1 2 2 1
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#> 564 Male 0.00 0.50 0.00 0.75 0.00 0.25 0.25 0.00 3 2 4 4
#> 565 Male 0.75 0.50 0.25 0.00 0.00 0.25 0.25 0.00 2 1 1 2
#> 566 Male 0.75 0.25 1.25 0.75 0.75 0.25 1.25 1.25 0 3 5 3
#> 567 Female 0.50 0.50 0.00 0.25 1.00 1.25 1.75 1.50 0 0 0 1
#> 568 Male 0.25 1.50 1.00 0.50 1.25 0.75 1.25 0.25 5 2 2 2
#> 569 Female 0.00 0.00 1.25 2.00 3.25 2.50 2.25 0.00 3 1 7 2
#> 570 Male 0.75 0.50 0.25 0.75 1.25 0.75 1.75 1.75 1 1 3 0
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#> 574 Male 0.00 1.00 1.75 3.25 2.25 1.50 0.50 0.00 3 5 1 4
#> 575 Male 0.50 0.75 0.75 0.00 1.75 2.25 2.25 0.75 3 2 2 4
#> 576 Female 0.75 0.75 2.00 2.75 2.25 1.50 0.25 0.50 2 3 4 0
#> 577 Male 0.50 0.75 0.75 0.75 0.75 0.75 1.25 1.50 1 1 2 1
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#> 580 Female 0.50 0.00 1.00 1.00 0.00 0.00 0.50 0.75 3 1 1 0
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#> 584 Male 1.75 1.00 0.75 0.50 0.50 0.50 0.25 0.75 1 1 2 6
#> 585 Male 0.50 0.50 0.25 0.25 0.00 0.75 0.75 0.00 2 2 2 3
#> 586 Male 0.25 0.50 1.00 1.25 1.00 2.25 3.00 1.75 0 0 2 1
#> 587 Female 0.00 0.75 0.00 1.00 4.00 2.75 3.50 1.00 4 4 4 0
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#> 589 Male 1.25 1.00 1.50 0.25 1.75 2.00 1.75 1.25 6 1 2 2
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#> 595 Female 0.25 0.50 1.00 0.00 2.00 2.75 3.25 0.00 0 1 1 0
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#> 598 Male 0.75 0.50 1.00 0.50 1.25 1.00 1.25 0.25 3 1 2 1
#> 599 Male 0.00 0.50 1.25 0.50 2.50 2.25 2.25 1.00 2 2 4 2
#> 600 Male 0.00 0.75 2.25 3.00 3.50 2.75 3.00 1.00 5 2 3 0
#> 601 Male 0.00 0.75 0.50 0.00 0.25 0.25 0.50 0.00 3 3 5 0
#> 602 Male 0.00 0.50 0.50 1.25 1.25 0.75 0.75 0.25 4 2 7 3
#> 603 Female 0.00 0.50 1.25 2.00 2.00 1.50 1.50 0.75 3 4 6 1
#> 604 Male 0.50 0.25 0.50 1.50 1.75 1.25 1.25 0.00 1 0 1 5
#> 605 Male 1.00 0.25 0.00 0.00 0.00 0.25 0.50 1.50 1 1 2 3
#> 606 Female 0.50 0.50 1.50 0.00 2.75 3.25 3.50 1.75 3 2 4 3
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#> 608 Male 0.75 0.00 0.75 0.50 1.25 1.75 1.50 0.00 0 2 0 0
#> 609 Male 1.25 0.50 0.00 0.25 1.00 1.75 1.50 1.00 2 0 3 1
#> 610 Male 1.00 0.75 0.00 0.25 0.75 0.75 1.75 1.25 4 0 5 4
#> 611 Female 0.00 0.75 0.50 0.75 2.75 2.50 2.25 2.00 3 0 1 0
#> 612 Male 1.25 1.75 1.50 0.00 0.00 0.25 1.25 0.00 5 0 0 4
#> 613 Male 0.00 0.00 0.00 0.50 0.50 0.50 0.75 1.00 1 1 4 1
#> 614 Male 0.00 1.25 1.50 0.50 0.00 0.00 0.50 0.25 3 3 4 0
#> 615 Male 0.00 0.00 0.25 1.50 2.75 2.00 1.75 1.00 0 0 2 1
#> 616 Male 1.75 0.50 0.75 1.50 0.50 0.25 0.75 0.50 4 0 4 5
#> 617 Female 0.25 0.25 0.00 0.00 0.00 0.25 1.00 1.25 1 0 2 0
#> 618 Male 0.75 0.25 1.00 0.75 2.25 2.75 2.50 0.25 3 0 5 4
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#> 620 Female 0.25 0.25 0.25 0.25 0.75 1.00 1.50 0.25 1 1 0 1
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#> 622 Male 1.00 1.00 1.50 1.25 1.75 0.75 1.00 0.25 4 0 2 0
#> 623 Male 0.50 0.50 0.25 2.00 2.00 2.00 2.00 0.50 2 3 5 5
#> 624 Female 0.25 1.75 2.25 3.25 3.50 2.75 1.75 0.50 5 3 3 1
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#> 626 Female 0.75 0.75 0.75 2.50 3.25 2.00 3.25 1.50 4 3 2 0
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#> 636 Male 0.75 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0 0 0 1
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#> 645 Male 0.75 1.25 0.75 2.50 1.00 1.75 1.25 0.00 6 1 4 2
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#> 648 Male 0.50 0.00 1.00 0.75 0.75 1.25 2.00 0.50 3 1 4 2
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#> 650 Female 0.50 0.25 0.75 0.50 2.25 2.25 2.50 1.75 5 3 3 1
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#> 652 Male 0.75 1.75 0.00 0.50 0.25 1.25 1.50 1.00 4 1 1 3
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#> 675 Female 0.00 0.75 0.00 0.00 3.00 3.00 2.25 1.00 4 1 1 0
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#> 678 Male 0.25 0.00 0.00 0.00 0.25 0.25 2.00 0.50 1 0 2 3
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#> 680 Female 0.50 0.00 0.25 0.00 0.00 0.00 3.25 1.00 2 1 4 1
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#> 682 Female 0.25 0.25 0.50 1.50 1.50 1.25 1.00 0.00 2 0 1 1
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#> 686 Male 0.50 0.25 0.50 1.50 4.00 2.50 2.00 1.00 2 0 0 2
#> 687 Male 0.00 0.50 0.25 0.00 0.00 0.25 0.25 0.00 3 1 1 1
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#> 694 Male 0.75 1.50 0.50 0.00 1.00 1.00 0.75 0.50 2 0 3 6
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#> 1118 Male 1.50 1.25 1.75 0.75 2.00 1.50 1.75 0.50 7 2 6 4
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#> 1163 Female 0.00 0.00 0.00 0.00 0.00 0.00 2.25 0.00 1 1 3 1
#> 1164 Male 0.00 0.50 0.25 0.25 0.00 0.25 0.75 0.50 2 3 2 1
#> 1165 Female 0.50 0.25 0.00 0.25 0.25 0.25 0.25 0.50 3 0 2 1
#> 1166 Female 1.00 0.00 0.00 0.00 0.00 0.00 1.00 0.75 4 0 2 0
#> BORPD HISPD NARPD AVPD DPNPD OCPD PA_z BC_z DE_z
#> 1 8 4 6 3 4 6 1.12121212 1.0253623 0.4093567
#> 2 1 2 3 0 1 0 -1.15151515 -0.7862319 -1.0526316
#> 3 1 5 4 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 4 1 0 0 0 0 0 1.87878788 1.3876812 0.9941520
#> 5 1 0 0 1 0 0 -0.77272727 -0.4239130 -0.7602339
#> 6 4 4 7 2 0 3 1.12121212 1.3876812 1.5789474
#> 7 2 3 6 6 7 6 1.87878788 1.3876812 0.9941520
#> 8 2 1 1 1 1 5 -1.15151515 -0.7862319 -0.7602339
#> 9 0 1 0 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 10 5 4 5 5 4 2 -0.01515152 1.7500000 0.9941520
#> 11 4 4 5 2 5 4 1.50000000 1.3876812 0.7017544
#> 12 6 3 6 5 5 6 -0.39393939 -0.0615942 -0.4678363
#> 13 6 4 5 3 5 5 0.74242424 1.7500000 0.4093567
#> 14 3 2 2 1 0 2 -0.77272727 -0.7862319 -1.0526316
#> 15 1 3 3 1 1 4 -0.77272727 -1.1485507 -1.0526316
#> 16 2 1 3 2 0 3 0.36363636 -0.7862319 -0.7602339
#> 17 2 2 5 3 1 3 -0.77272727 -0.0615942 -1.0526316
#> 18 2 2 3 3 1 4 -0.39393939 -0.4239130 -0.7602339
#> 19 1 0 1 2 2 2 -0.77272727 -0.7862319 -0.7602339
#> 20 2 2 2 0 2 2 -0.77272727 -0.4239130 -1.0526316
#> 21 1 3 4 2 2 2 -0.77272727 -0.4239130 -0.1754386
#> 22 1 3 2 4 0 3 -0.77272727 -0.4239130 -0.1754386
#> 23 3 3 2 7 4 1 -0.77272727 -0.0615942 1.8713450
#> 24 2 0 3 3 0 2 -0.39393939 0.3007246 0.1169591
#> 25 6 1 2 3 3 4 -1.15151515 1.0253623 0.1169591
#> 26 7 5 6 5 3 2 0.74242424 0.3007246 1.2865497
#> 27 1 0 0 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 28 2 2 3 0 0 4 -0.39393939 -1.1485507 -0.7602339
#> 29 5 2 4 1 4 6 -0.39393939 0.3007246 -0.1754386
#> 30 7 4 4 4 5 4 -0.01515152 -0.4239130 -0.4678363
#> 31 1 0 1 4 3 5 -1.15151515 -1.1485507 -1.0526316
#> 32 5 2 5 1 1 5 0.36363636 -0.7862319 -0.7602339
#> 33 1 0 1 1 0 2 -0.77272727 -0.7862319 -1.0526316
#> 34 2 2 4 2 1 3 -0.01515152 -0.0615942 -0.4678363
#> 35 4 2 5 6 6 3 -0.01515152 1.3876812 1.5789474
#> 36 4 1 1 4 3 3 -0.01515152 0.6630435 0.7017544
#> 37 3 3 4 1 1 4 -0.01515152 -0.0615942 -0.7602339
#> 38 3 3 2 3 1 4 -0.77272727 -0.7862319 -0.7602339
#> 39 3 4 3 1 0 4 -0.01515152 -0.0615942 -0.7602339
#> 40 5 3 2 7 5 5 -1.15151515 0.6630435 1.8713450
#> 41 0 1 0 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 42 4 4 5 0 3 3 1.50000000 -1.1485507 -1.0526316
#> 43 2 1 0 0 0 1 -0.39393939 -1.1485507 -1.0526316
#> 44 1 3 2 2 0 4 -0.77272727 -1.1485507 -1.0526316
#> 45 2 2 1 1 1 3 -1.15151515 -1.1485507 -1.0526316
#> 46 1 3 3 1 0 4 -1.15151515 -1.1485507 -0.1754386
#> 47 2 4 3 2 4 2 -1.15151515 -1.1485507 -1.0526316
#> 48 0 1 2 1 0 2 -0.77272727 -1.1485507 -1.0526316
#> 49 5 1 2 4 1 4 -1.15151515 -1.1485507 -1.0526316
#> 50 3 2 1 4 3 2 -1.15151515 -0.7862319 -0.1754386
#> 51 5 2 4 7 4 4 -0.77272727 -0.0615942 3.6257310
#> 52 6 2 3 0 6 4 0.36363636 1.0253623 0.7017544
#> 53 5 3 2 5 4 4 -0.77272727 -0.7862319 -1.0526316
#> 54 0 0 1 2 1 3 -1.15151515 -1.1485507 -1.0526316
#> 55 6 4 5 5 4 4 0.74242424 0.6630435 0.4093567
#> 56 5 4 2 5 1 6 0.36363636 0.6630435 -0.4678363
#> 57 2 3 3 3 1 2 -0.01515152 -0.0615942 -1.0526316
#> 58 1 2 1 1 1 0 -1.15151515 -1.1485507 -1.0526316
#> 59 3 0 2 0 0 3 -0.77272727 -0.7862319 0.1169591
#> 60 1 1 2 1 0 1 1.12121212 -0.0615942 -1.0526316
#> 61 4 1 2 6 2 5 -0.39393939 -0.4239130 1.2865497
#> 62 1 2 1 4 2 0 -0.39393939 0.3007246 0.4093567
#> 63 2 2 2 2 2 1 -0.01515152 -0.7862319 -1.0526316
#> 64 3 4 6 2 1 5 0.74242424 1.7500000 1.8713450
#> 65 2 2 1 7 2 2 0.36363636 -0.0615942 0.7017544
#> 66 0 0 0 2 0 1 -1.15151515 -0.4239130 -1.0526316
#> 67 2 1 1 0 0 3 -1.15151515 -1.1485507 -1.0526316
#> 68 4 2 3 2 0 4 -1.15151515 -0.4239130 -0.7602339
#> 69 2 1 3 0 2 3 -0.01515152 1.3876812 -0.4678363
#> 70 1 1 1 1 0 0 -0.77272727 -0.0615942 -0.7602339
#> 71 3 2 1 1 2 1 -0.39393939 -1.1485507 -1.0526316
#> 72 2 0 2 0 0 3 -1.15151515 -0.7862319 -1.0526316
#> 73 2 2 5 2 3 5 0.74242424 -0.4239130 -0.1754386
#> 74 3 3 2 1 1 4 -0.39393939 -0.0615942 0.4093567
#> 75 4 1 0 1 2 6 -1.15151515 -0.4239130 -1.0526316
#> 76 2 4 3 1 2 2 -0.01515152 -0.4239130 -1.0526316
#> 77 7 4 2 6 4 4 0.74242424 -0.0615942 1.2865497
#> 78 5 3 7 2 2 3 1.50000000 -0.7862319 -0.4678363
#> 79 3 1 2 2 2 5 -0.77272727 -1.1485507 -0.7602339
#> 80 1 0 0 0 1 0 -1.15151515 -1.1485507 -1.0526316
#> 81 6 6 8 1 2 4 -0.39393939 -0.4239130 -0.1754386
#> 82 5 3 6 5 3 4 0.36363636 -0.0615942 1.8713450
#> 83 4 2 3 4 3 4 0.36363636 0.6630435 0.4093567
#> 84 1 2 0 1 1 3 0.36363636 -0.4239130 -0.7602339
#> 85 6 6 5 3 4 3 -0.01515152 0.6630435 -0.7602339
#> 86 5 4 6 4 3 4 1.12121212 0.3007246 -0.1754386
#> 87 1 3 2 1 1 3 -0.77272727 -1.1485507 -1.0526316
#> 88 2 3 5 1 1 2 -0.77272727 -0.0615942 -0.7602339
#> 89 1 5 1 3 0 2 -0.01515152 -0.7862319 -1.0526316
#> 90 3 4 3 2 6 5 -0.01515152 -0.7862319 -0.4678363
#> 91 2 3 3 3 1 2 -1.15151515 -0.4239130 -0.4678363
#> 92 3 3 3 7 6 7 0.36363636 -0.4239130 0.1169591
#> 93 2 1 2 3 2 1 -0.39393939 -1.1485507 -1.0526316
#> 94 1 4 2 6 5 7 -0.77272727 -0.0615942 -0.7602339
#> 95 3 2 4 0 2 3 -0.01515152 -0.4239130 -0.4678363
#> 96 3 0 4 1 3 3 -1.15151515 -1.1485507 -0.1754386
#> 97 4 1 2 0 0 4 -0.77272727 -0.0615942 -0.1754386
#> 98 2 3 2 0 2 5 0.36363636 -0.0615942 -1.0526316
#> 99 1 1 1 2 1 3 -0.39393939 -0.7862319 -0.7602339
#> 100 7 2 3 4 4 4 -0.77272727 -0.7862319 -0.1754386
#> 101 3 3 4 1 0 2 0.74242424 0.3007246 -0.7602339
#> 102 1 0 1 2 1 2 -1.15151515 0.3007246 0.1169591
#> 103 1 3 0 3 2 2 -0.39393939 -0.7862319 -1.0526316
#> 104 1 2 3 4 2 2 -0.01515152 -0.4239130 0.4093567
#> 105 3 0 1 2 2 4 -0.77272727 -0.0615942 0.4093567
#> 106 1 1 1 1 1 1 -1.15151515 -1.1485507 -1.0526316
#> 107 2 3 1 1 1 3 -0.39393939 -0.7862319 -1.0526316
#> 108 1 0 3 2 0 3 -1.15151515 -1.1485507 -1.0526316
#> 109 3 5 5 2 4 5 2.63636364 1.3876812 0.1169591
#> 110 5 4 5 3 3 2 -1.15151515 -1.1485507 -1.0526316
#> 111 6 3 6 5 4 2 1.12121212 1.7500000 1.5789474
#> 112 0 0 0 0 0 0 -0.39393939 -1.1485507 -1.0526316
#> 113 2 2 4 0 1 2 0.74242424 1.0253623 -0.4678363
#> 114 2 1 2 5 4 2 -1.15151515 -1.1485507 -0.4678363
#> 115 0 1 1 3 1 4 -0.77272727 -1.1485507 -1.0526316
#> 116 2 0 0 0 0 1 -1.15151515 -0.7862319 -1.0526316
#> 117 1 0 0 1 2 1 0.36363636 -0.0615942 0.1169591
#> 118 1 2 1 1 1 2 -1.15151515 -1.1485507 -1.0526316
#> 119 5 4 5 4 5 0 -0.01515152 -0.0615942 -0.7602339
#> 120 2 1 3 2 0 4 0.36363636 -0.0615942 0.1169591
#> 121 0 0 0 0 1 0 -0.01515152 -0.0615942 0.1169591
#> 122 3 1 2 4 1 3 -0.77272727 -0.7862319 0.1169591
#> 123 2 1 1 2 1 3 -0.01515152 -0.7862319 -0.4678363
#> 124 1 2 1 2 0 2 -1.15151515 -1.1485507 -1.0526316
#> 125 3 3 3 4 5 5 1.87878788 1.7500000 1.2865497
#> 126 1 0 0 1 0 1 -0.39393939 -0.0615942 -0.1754386
#> 127 3 1 3 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 128 3 0 2 0 1 2 -0.77272727 -1.1485507 -1.0526316
#> 129 2 2 0 2 0 3 -0.01515152 -0.4239130 -0.7602339
#> 130 5 3 4 4 1 6 1.87878788 1.7500000 -0.1754386
#> 131 1 2 0 0 1 3 -1.15151515 -0.7862319 -1.0526316
#> 132 2 1 1 2 1 3 -0.77272727 -0.7862319 -1.0526316
#> 133 3 2 3 3 1 4 -1.15151515 -0.4239130 -0.4678363
#> 134 2 7 3 1 1 3 -0.77272727 -0.4239130 -0.7602339
#> 135 2 1 1 0 0 1 0.74242424 0.6630435 -0.4678363
#> 136 3 1 2 0 1 5 2.25757576 -0.4239130 -1.0526316
#> 137 2 1 3 4 0 4 -0.77272727 -0.7862319 -0.1754386
#> 138 3 4 1 1 0 2 -0.77272727 -0.0615942 -1.0526316
#> 139 2 0 1 4 4 5 0.74242424 1.0253623 0.4093567
#> 140 1 1 1 1 0 1 -1.15151515 -0.4239130 -0.4678363
#> 141 2 1 1 1 1 3 -0.77272727 -0.7862319 -0.7602339
#> 142 4 1 2 5 1 3 0.36363636 -0.4239130 -0.1754386
#> 143 5 3 4 6 3 6 -0.39393939 0.3007246 0.1169591
#> 144 1 0 2 1 0 1 -0.77272727 0.3007246 -1.0526316
#> 145 4 6 5 3 3 5 2.63636364 1.0253623 -0.7602339
#> 146 1 1 4 2 1 5 -0.39393939 -0.4239130 0.1169591
#> 147 1 1 4 0 3 3 -0.77272727 -0.7862319 0.1169591
#> 148 4 1 1 0 0 5 -1.15151515 -0.4239130 -0.4678363
#> 149 2 1 3 3 2 3 0.74242424 0.6630435 0.9941520
#> 150 0 1 0 2 1 3 -0.77272727 -1.1485507 -1.0526316
#> 151 2 5 6 3 4 5 -0.39393939 0.3007246 -1.0526316
#> 152 0 1 2 1 0 0 -0.39393939 -1.1485507 -1.0526316
#> 153 2 3 3 6 4 5 0.74242424 -0.0615942 0.7017544
#> 154 3 5 8 1 3 5 1.12121212 -0.4239130 -0.1754386
#> 155 2 1 4 1 0 3 1.50000000 0.3007246 0.7017544
#> 156 1 2 1 3 3 2 -0.39393939 -1.1485507 -1.0526316
#> 157 1 0 0 2 0 1 0.36363636 -0.0615942 -1.0526316
#> 158 3 1 1 4 2 2 -0.39393939 0.3007246 0.4093567
#> 159 1 1 2 2 3 4 -1.15151515 -0.0615942 0.1169591
#> 160 4 6 5 4 3 6 -0.01515152 -0.0615942 -0.1754386
#> 161 4 1 2 5 2 1 -1.15151515 0.6630435 -0.1754386
#> 162 5 2 3 4 1 2 -0.39393939 -0.4239130 -0.4678363
#> 163 3 3 4 3 2 4 -0.39393939 -0.7862319 -0.7602339
#> 164 7 5 5 5 6 6 1.12121212 1.7500000 0.9941520
#> 165 2 1 1 1 0 3 -1.15151515 -1.1485507 -1.0526316
#> 166 2 0 2 0 0 2 0.36363636 -0.0615942 -1.0526316
#> 167 4 3 3 3 5 4 -1.15151515 -0.0615942 -1.0526316
#> 168 3 2 3 1 0 4 -0.39393939 -0.4239130 0.7017544
#> 169 1 3 2 5 1 4 -1.15151515 -1.1485507 -0.7602339
#> 170 3 1 2 0 1 3 -0.01515152 -0.7862319 -0.7602339
#> 171 3 3 4 3 2 4 -1.15151515 -0.7862319 -1.0526316
#> 172 0 2 4 2 1 3 -1.15151515 -1.1485507 -1.0526316
#> 173 2 1 3 4 1 3 -0.39393939 -1.1485507 -0.7602339
#> 174 1 3 0 3 3 2 -1.15151515 -1.1485507 -1.0526316
#> 175 1 3 1 1 1 3 0.36363636 -0.0615942 -1.0526316
#> 176 1 1 1 0 1 1 -0.77272727 -1.1485507 -1.0526316
#> 177 2 1 2 0 0 3 -1.15151515 -1.1485507 -1.0526316
#> 178 5 3 4 3 3 5 0.36363636 -0.4239130 -0.4678363
#> 179 3 0 1 0 0 1 -1.15151515 -0.7862319 -0.1754386
#> 180 2 1 3 2 0 3 -0.39393939 -0.0615942 -0.4678363
#> 181 2 1 3 3 1 2 -0.39393939 -0.7862319 -0.4678363
#> 182 2 2 1 1 0 2 1.50000000 1.3876812 -0.7602339
#> 183 2 3 3 4 2 5 -0.39393939 0.6630435 -0.4678363
#> 184 2 1 0 1 0 3 -1.15151515 -0.7862319 -1.0526316
#> 185 1 2 1 2 1 4 -0.01515152 -0.0615942 0.1169591
#> 186 2 1 1 3 2 4 -1.15151515 -0.7862319 -1.0526316
#> 187 2 3 5 3 1 4 -1.15151515 -0.7862319 -0.7602339
#> 188 3 2 3 1 1 6 0.36363636 0.3007246 -0.7602339
#> 189 1 2 2 2 1 3 -0.01515152 -0.0615942 -1.0526316
#> 190 3 0 3 1 3 6 -0.77272727 -0.0615942 0.4093567
#> 191 1 2 4 1 0 4 -1.15151515 -0.0615942 0.4093567
#> 192 5 7 6 4 2 5 1.12121212 0.6630435 -0.1754386
#> 193 1 2 4 4 2 5 -1.15151515 -0.7862319 -0.4678363
#> 194 1 2 1 2 0 2 -0.39393939 -0.4239130 -0.7602339
#> 195 2 0 0 3 0 3 -0.77272727 -0.7862319 0.1169591
#> 196 4 5 6 0 5 4 0.36363636 1.3876812 -0.4678363
#> 197 1 2 2 3 1 3 -0.77272727 -0.4239130 -0.1754386
#> 198 0 1 1 6 3 4 -0.77272727 -0.4239130 -0.4678363
#> 199 3 2 5 2 0 4 -0.01515152 -1.1485507 -1.0526316
#> 200 1 3 2 0 1 1 -0.77272727 -1.1485507 -1.0526316
#> 201 1 2 2 0 1 4 -1.15151515 -1.1485507 -1.0526316
#> 202 2 3 1 3 2 3 -0.77272727 -0.4239130 0.1169591
#> 203 1 0 0 1 0 0 -1.15151515 -1.1485507 -0.4678363
#> 204 4 0 3 5 1 6 -0.01515152 0.3007246 -0.1754386
#> 205 2 4 1 3 1 3 -1.15151515 -1.1485507 -1.0526316
#> 206 2 3 2 3 3 2 -0.01515152 -0.4239130 -0.7602339
#> 207 4 5 8 4 6 3 1.12121212 -0.4239130 0.4093567
#> 208 2 0 0 0 1 0 -0.77272727 -1.1485507 -0.7602339
#> 209 4 2 3 6 3 1 -0.77272727 0.6630435 0.4093567
#> 210 1 0 2 1 0 4 0.74242424 -0.4239130 -0.1754386
#> 211 2 2 2 1 1 1 -0.77272727 -1.1485507 -0.1754386
#> 212 3 1 3 1 1 4 -0.01515152 -0.4239130 0.9941520
#> 213 2 3 4 1 2 6 -0.01515152 -1.1485507 -0.7602339
#> 214 3 4 1 1 3 3 -0.77272727 -0.4239130 -1.0526316
#> 215 6 6 3 3 2 4 1.12121212 1.0253623 0.9941520
#> 216 2 0 1 1 0 4 0.36363636 -0.0615942 -0.7602339
#> 217 1 2 3 1 1 0 0.36363636 -0.4239130 -0.7602339
#> 218 3 1 3 2 4 4 -1.15151515 -0.4239130 0.4093567
#> 219 4 1 0 5 1 6 0.36363636 -0.0615942 -0.7602339
#> 220 5 7 7 4 5 3 0.74242424 1.0253623 0.7017544
#> 221 1 0 1 1 0 0 -0.39393939 -0.0615942 -0.1754386
#> 222 3 1 3 2 2 1 0.74242424 0.6630435 0.4093567
#> 223 1 1 3 0 0 4 -1.15151515 -0.4239130 -0.7602339
#> 224 2 1 1 1 0 4 -0.39393939 -1.1485507 -1.0526316
#> 225 3 4 4 2 2 2 1.12121212 -0.4239130 -1.0526316
#> 226 2 0 1 3 0 2 -0.39393939 -0.7862319 -1.0526316
#> 227 2 0 2 2 1 2 -0.01515152 0.3007246 -0.1754386
#> 228 1 1 1 1 0 1 -1.15151515 -1.1485507 -1.0526316
#> 229 2 1 0 0 0 1 0.36363636 -0.7862319 -1.0526316
#> 230 4 1 2 5 4 2 -1.15151515 -0.7862319 -0.7602339
#> 231 1 3 3 4 0 1 -0.39393939 -0.7862319 -0.7602339
#> 232 1 2 2 0 1 3 -0.01515152 -0.0615942 0.1169591
#> 233 1 1 0 6 3 2 -1.15151515 -1.1485507 1.8713450
#> 234 3 1 0 1 1 2 -1.15151515 -1.1485507 -1.0526316
#> 235 2 3 4 5 2 7 -0.01515152 1.3876812 0.9941520
#> 236 4 3 1 3 0 4 -0.39393939 -0.7862319 -0.4678363
#> 237 2 1 1 4 0 1 -0.77272727 -1.1485507 -0.4678363
#> 238 2 3 1 0 2 2 -1.15151515 -1.1485507 -1.0526316
#> 239 0 0 0 0 0 1 -0.39393939 -0.4239130 -0.4678363
#> 240 4 1 1 4 2 4 -0.77272727 -0.4239130 0.7017544
#> 241 6 4 3 4 2 5 0.74242424 0.3007246 -1.0526316
#> 242 4 1 0 3 1 5 0.74242424 -0.7862319 -0.7602339
#> 243 2 2 2 0 3 1 2.63636364 1.3876812 1.2865497
#> 244 3 3 2 6 5 3 -0.39393939 -0.4239130 -0.7602339
#> 245 2 2 3 1 3 3 -0.01515152 -0.0615942 0.7017544
#> 246 2 4 3 5 3 4 -0.01515152 0.3007246 -1.0526316
#> 247 0 3 2 4 5 2 -0.01515152 -0.7862319 -0.1754386
#> 248 3 1 2 7 2 6 -0.77272727 0.6630435 1.8713450
#> 249 2 1 1 1 0 5 -1.15151515 -1.1485507 -1.0526316
#> 250 4 2 2 3 1 5 -0.77272727 -1.1485507 -0.7602339
#> 251 5 3 3 2 0 4 -0.39393939 -0.7862319 -0.4678363
#> 252 3 1 2 1 1 3 -1.15151515 -1.1485507 -1.0526316
#> 253 2 2 1 4 2 4 -0.77272727 -0.7862319 -1.0526316
#> 254 5 3 4 5 5 5 0.36363636 -0.4239130 -0.1754386
#> 255 3 3 1 5 1 7 -0.77272727 -0.7862319 0.4093567
#> 256 2 2 2 2 0 6 3.77272727 0.6630435 -0.1754386
#> 257 6 1 7 6 4 6 1.87878788 -0.0615942 0.1169591
#> 258 4 2 3 4 2 6 0.36363636 -0.0615942 -0.7602339
#> 259 2 2 0 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 260 1 0 0 2 0 3 -0.77272727 -1.1485507 -1.0526316
#> 261 1 1 0 1 1 1 -1.15151515 -1.1485507 -1.0526316
#> 262 1 2 0 1 0 2 -0.77272727 -1.1485507 -1.0526316
#> 263 4 1 2 1 1 3 -1.15151515 -0.7862319 -0.7602339
#> 264 2 2 5 0 0 5 -0.39393939 -0.4239130 0.1169591
#> 265 3 6 6 1 2 2 0.36363636 -0.7862319 -0.7602339
#> 266 4 5 7 6 7 5 2.63636364 0.6630435 -0.4678363
#> 267 2 3 5 1 3 4 -1.15151515 -0.4239130 -0.4678363
#> 268 3 4 4 1 0 2 -0.39393939 -0.4239130 -1.0526316
#> 269 3 2 2 2 3 5 -0.39393939 -0.4239130 -1.0526316
#> 270 3 1 0 3 2 2 -0.77272727 -0.4239130 -0.4678363
#> 271 1 2 4 3 3 5 -0.39393939 1.0253623 -0.7602339
#> 272 1 1 1 2 0 3 -0.01515152 -0.4239130 -0.4678363
#> 273 6 5 6 3 3 2 0.74242424 1.7500000 0.1169591
#> 274 2 2 2 0 0 4 -0.39393939 -0.7862319 -1.0526316
#> 275 3 2 3 4 2 4 -1.15151515 -0.4239130 -0.7602339
#> 276 4 2 4 6 3 2 -0.39393939 -0.4239130 0.1169591
#> 277 6 2 2 7 2 3 -0.01515152 -0.4239130 -0.4678363
#> 278 3 1 1 1 0 2 -0.77272727 -1.1485507 -1.0526316
#> 279 2 2 4 1 1 4 -0.39393939 -0.0615942 0.4093567
#> 280 2 4 3 1 0 3 0.36363636 -0.4239130 -0.7602339
#> 281 2 1 2 4 1 5 -0.39393939 -0.0615942 -1.0526316
#> 282 5 1 4 2 0 2 -0.77272727 -0.0615942 0.7017544
#> 283 3 1 1 2 0 3 -0.39393939 -0.7862319 -1.0526316
#> 284 2 4 3 5 1 5 -0.39393939 -0.7862319 1.5789474
#> 285 0 1 3 1 2 2 -0.77272727 -0.4239130 -0.4678363
#> 286 2 1 1 1 1 3 -0.01515152 -0.7862319 -1.0526316
#> 287 0 1 2 2 1 1 -1.15151515 -0.7862319 -0.7602339
#> 288 1 2 3 1 0 2 -1.15151515 -1.1485507 -0.4678363
#> 289 6 3 1 0 2 2 0.36363636 0.6630435 -1.0526316
#> 290 2 1 5 6 3 6 0.36363636 1.0253623 0.9941520
#> 291 4 2 5 2 2 6 0.36363636 -1.1485507 -1.0526316
#> 292 1 2 2 3 0 1 -1.15151515 -1.1485507 -1.0526316
#> 293 3 5 3 4 4 3 -1.15151515 -1.1485507 -1.0526316
#> 294 2 0 2 0 1 4 -0.01515152 0.3007246 -0.4678363
#> 295 2 2 2 1 0 2 -1.15151515 -1.1485507 -1.0526316
#> 296 1 1 2 1 1 4 -0.39393939 -0.7862319 -0.1754386
#> 297 2 3 2 1 3 6 -0.77272727 -0.7862319 -1.0526316
#> 298 5 3 5 6 4 4 0.36363636 1.7500000 0.1169591
#> 299 5 2 3 3 3 2 1.12121212 1.3876812 -0.7602339
#> 300 3 4 7 2 5 5 -0.01515152 -0.7862319 -1.0526316
#> 301 3 1 3 5 4 4 0.74242424 -0.0615942 0.9941520
#> 302 5 2 3 5 1 1 -0.01515152 -0.7862319 0.4093567
#> 303 1 0 2 4 1 2 -0.77272727 -1.1485507 -0.4678363
#> 304 2 4 4 2 1 2 1.12121212 0.6630435 0.1169591
#> 305 1 1 1 0 1 2 -1.15151515 -1.1485507 -0.7602339
#> 306 1 1 1 3 3 4 -1.15151515 0.3007246 -0.7602339
#> 307 3 0 2 2 1 6 -1.15151515 -1.1485507 -1.0526316
#> 308 2 1 1 3 1 2 -1.15151515 -1.1485507 -1.0526316
#> 309 2 4 1 3 1 4 -0.01515152 0.3007246 -0.7602339
#> 310 1 4 5 2 2 4 -0.77272727 -0.4239130 -1.0526316
#> 311 2 4 2 2 2 4 -1.15151515 -0.7862319 -1.0526316
#> 312 4 1 2 3 1 4 2.25757576 1.7500000 -0.1754386
#> 313 1 2 4 1 1 2 -1.15151515 0.3007246 -0.4678363
#> 314 6 2 4 4 4 4 -0.39393939 0.3007246 0.7017544
#> 315 4 3 2 0 2 4 0.36363636 -0.0615942 -0.1754386
#> 316 5 3 3 3 5 4 -0.01515152 -0.4239130 -1.0526316
#> 317 4 3 3 6 4 2 1.50000000 0.6630435 1.2865497
#> 318 4 4 5 4 3 4 -0.39393939 1.3876812 1.5789474
#> 319 1 1 0 2 1 2 -1.15151515 -0.7862319 -1.0526316
#> 320 4 4 2 6 1 5 -0.01515152 -1.1485507 -1.0526316
#> 321 1 1 3 0 1 4 -0.39393939 -0.4239130 -0.1754386
#> 322 1 1 3 3 3 3 -0.39393939 -0.7862319 -0.1754386
#> 323 2 2 1 2 0 1 -1.15151515 -1.1485507 -1.0526316
#> 324 2 3 2 3 0 4 0.36363636 -0.4239130 -1.0526316
#> 325 4 4 4 5 3 5 1.12121212 -0.0615942 0.7017544
#> 326 1 0 2 3 2 2 -0.77272727 -0.0615942 -0.1754386
#> 327 1 0 3 2 0 2 -1.15151515 -0.7862319 -1.0526316
#> 328 5 2 2 5 3 5 1.12121212 -0.0615942 0.1169591
#> 329 2 1 1 4 1 5 -1.15151515 -1.1485507 -0.4678363
#> 330 3 2 2 3 0 4 -0.01515152 -0.4239130 -0.7602339
#> 331 4 4 6 1 2 5 0.36363636 2.4746377 -0.7602339
#> 332 3 0 1 1 1 1 -0.01515152 -0.4239130 0.1169591
#> 333 2 4 2 6 1 3 -0.39393939 -0.4239130 1.5789474
#> 334 0 0 1 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 335 4 5 2 6 2 5 -0.39393939 -0.0615942 -1.0526316
#> 336 1 2 0 0 0 1 -0.77272727 -1.1485507 -1.0526316
#> 337 2 0 2 1 0 3 -1.15151515 -1.1485507 0.7017544
#> 338 2 0 1 1 0 2 -0.39393939 -0.7862319 -1.0526316
#> 339 1 0 1 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 340 2 1 0 0 1 2 -1.15151515 -1.1485507 -1.0526316
#> 341 5 2 2 0 2 3 -0.77272727 -0.4239130 -1.0526316
#> 342 5 2 2 2 3 3 1.12121212 -0.0615942 -0.7602339
#> 343 2 0 3 2 3 4 -0.39393939 -0.7862319 -0.1754386
#> 344 2 0 0 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 345 1 0 1 2 0 3 -1.15151515 -1.1485507 -1.0526316
#> 346 4 3 3 6 2 4 -1.15151515 -1.1485507 -0.7602339
#> 347 1 3 2 6 1 4 -0.39393939 -0.0615942 -0.1754386
#> 348 0 2 0 1 1 5 -1.15151515 -0.7862319 -1.0526316
#> 349 1 2 0 3 1 3 -0.39393939 -1.1485507 -1.0526316
#> 350 2 1 0 3 1 1 -0.77272727 -1.1485507 -1.0526316
#> 351 2 2 3 1 0 3 -1.15151515 -0.4239130 -1.0526316
#> 352 2 4 4 2 3 3 -1.15151515 -1.1485507 -1.0526316
#> 353 2 2 4 6 6 1 -0.77272727 -1.1485507 -0.1754386
#> 354 2 1 4 2 0 5 -1.15151515 -1.1485507 -1.0526316
#> 355 2 0 1 1 0 4 -0.77272727 -1.1485507 -0.7602339
#> 356 2 0 2 1 1 3 -0.77272727 -0.7862319 -1.0526316
#> 357 1 3 2 3 0 3 -0.77272727 -1.1485507 -0.1754386
#> 358 1 1 1 1 0 3 -0.77272727 -1.1485507 0.1169591
#> 359 0 0 2 1 1 4 -1.15151515 -1.1485507 -1.0526316
#> 360 2 3 0 2 2 5 -0.39393939 -0.7862319 -1.0526316
#> 361 3 3 1 1 1 3 -0.77272727 -0.4239130 -1.0526316
#> 362 1 3 1 4 1 3 0.36363636 0.3007246 -1.0526316
#> 363 1 2 2 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 364 2 1 4 4 0 2 -0.01515152 1.3876812 1.2865497
#> 365 4 3 5 3 3 2 -0.77272727 -1.1485507 -1.0526316
#> 366 6 5 7 6 5 6 -0.39393939 -0.7862319 -0.1754386
#> 367 4 1 4 3 0 5 1.12121212 0.3007246 0.1169591
#> 368 4 2 2 6 3 4 0.36363636 0.3007246 -0.4678363
#> 369 5 3 4 3 3 2 1.50000000 0.3007246 0.4093567
#> 370 1 0 0 0 1 0 -0.77272727 -0.4239130 -0.7602339
#> 371 3 3 3 3 3 3 -1.15151515 -1.1485507 -0.4678363
#> 372 1 1 0 1 0 1 -0.39393939 -0.7862319 -1.0526316
#> 373 3 3 3 3 2 5 -0.39393939 -0.4239130 -1.0526316
#> 374 2 1 0 3 1 5 -0.77272727 -0.0615942 -0.7602339
#> 375 5 2 4 7 3 7 -0.39393939 0.6630435 -0.1754386
#> 376 2 3 1 3 2 1 -0.01515152 -1.1485507 -1.0526316
#> 377 5 1 1 7 3 3 -1.15151515 -0.4239130 0.1169591
#> 378 2 2 2 3 1 2 -0.77272727 -0.4239130 0.7017544
#> 379 3 0 1 1 3 2 -0.77272727 -0.7862319 0.1169591
#> 380 2 1 1 4 2 3 -1.15151515 -0.7862319 -0.7602339
#> 381 2 0 1 0 0 4 -0.39393939 0.3007246 -0.4678363
#> 382 4 5 2 5 4 3 -1.15151515 0.3007246 0.9941520
#> 383 1 1 0 2 0 1 -0.77272727 -0.7862319 -0.7602339
#> 384 2 1 0 1 0 4 -0.77272727 0.3007246 -0.4678363
#> 385 2 1 1 3 0 5 -1.15151515 -0.4239130 -0.7602339
#> 386 4 2 4 1 0 3 -0.77272727 -0.7862319 -0.4678363
#> 387 7 4 5 5 5 4 -0.01515152 0.3007246 0.4093567
#> 388 1 0 1 2 1 2 -0.01515152 -0.4239130 -0.4678363
#> 389 5 3 2 5 4 5 -0.01515152 2.1123188 0.9941520
#> 390 1 0 2 3 0 3 -0.01515152 -0.7862319 -0.4678363
#> 391 4 3 1 0 4 1 -0.77272727 -0.7862319 -0.1754386
#> 392 3 2 1 2 3 4 -0.77272727 -0.4239130 -1.0526316
#> 393 6 5 4 4 2 3 1.12121212 0.6630435 0.1169591
#> 394 0 1 1 1 1 3 -0.77272727 -1.1485507 -1.0526316
#> 395 4 2 3 1 1 2 1.12121212 1.0253623 0.7017544
#> 396 1 2 2 2 0 4 -0.77272727 -1.1485507 -0.7602339
#> 397 2 1 0 4 2 4 -0.01515152 0.6630435 -0.4678363
#> 398 2 1 2 0 1 5 -0.01515152 -0.7862319 0.4093567
#> 399 2 3 3 2 1 4 -0.39393939 -0.7862319 -1.0526316
#> 400 3 5 6 5 3 4 -0.39393939 -0.4239130 0.1169591
#> 401 1 1 2 3 1 3 -1.15151515 -1.1485507 -1.0526316
#> 402 3 1 1 0 0 1 -0.77272727 -0.4239130 -0.4678363
#> 403 0 0 0 0 0 0 -0.77272727 -1.1485507 -1.0526316
#> 404 1 1 0 3 1 3 -1.15151515 -1.1485507 -0.1754386
#> 405 1 1 3 2 2 3 -1.15151515 -1.1485507 -0.4678363
#> 406 6 3 5 5 3 4 -0.01515152 0.6630435 0.7017544
#> 407 5 3 6 3 3 4 2.63636364 1.7500000 0.9941520
#> 408 0 3 4 3 0 4 -0.39393939 -1.1485507 -0.7602339
#> 409 2 2 4 3 3 5 -0.01515152 1.3876812 0.7017544
#> 410 4 2 3 2 1 4 -1.15151515 -1.1485507 -1.0526316
#> 411 1 1 0 0 0 0 -0.77272727 -1.1485507 -1.0526316
#> 412 1 1 3 2 2 4 -0.77272727 -0.4239130 0.7017544
#> 413 2 2 4 4 3 4 -0.01515152 0.3007246 0.7017544
#> 414 2 1 0 1 2 4 -1.15151515 -0.7862319 0.1169591
#> 415 2 5 2 4 5 3 -0.77272727 -1.1485507 -1.0526316
#> 416 6 3 4 2 1 2 -0.77272727 -1.1485507 -0.4678363
#> 417 1 4 3 3 3 3 -0.01515152 -1.1485507 -1.0526316
#> 418 4 3 4 2 1 4 -1.15151515 -1.1485507 -0.4678363
#> 419 3 2 1 1 3 5 -1.15151515 0.6630435 -1.0526316
#> 420 1 3 1 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 421 4 1 0 2 2 3 -0.01515152 0.3007246 -0.7602339
#> 422 2 2 3 0 0 4 0.36363636 0.6630435 -0.1754386
#> 423 0 1 2 1 0 1 -0.77272727 -0.7862319 -1.0526316
#> 424 4 2 4 0 0 3 0.74242424 0.3007246 0.1169591
#> 425 1 5 3 3 1 3 0.36363636 -0.7862319 -0.4678363
#> 426 1 1 3 6 2 5 -0.39393939 -0.4239130 0.1169591
#> 427 4 3 2 4 2 4 -1.15151515 -1.1485507 -1.0526316
#> 428 1 1 0 2 0 2 -0.39393939 -1.1485507 -1.0526316
#> 429 4 5 5 6 1 5 1.50000000 0.6630435 0.7017544
#> 430 4 2 3 6 6 6 0.36363636 0.6630435 1.2865497
#> 431 1 2 1 2 1 2 -1.15151515 -1.1485507 -0.7602339
#> 432 8 5 5 7 2 5 2.25757576 1.3876812 -0.4678363
#> 433 4 4 7 1 3 5 1.50000000 0.3007246 -0.7602339
#> 434 3 1 2 1 0 3 -0.39393939 -0.0615942 -1.0526316
#> 435 3 3 3 6 5 3 -1.15151515 -0.7862319 0.9941520
#> 436 2 2 3 2 1 3 -0.39393939 -0.4239130 0.1169591
#> 437 2 1 2 2 0 3 -1.15151515 -1.1485507 -1.0526316
#> 438 4 3 4 7 5 6 -0.39393939 0.6630435 0.1169591
#> 439 2 5 1 1 1 3 -1.15151515 -0.7862319 -1.0526316
#> 440 0 1 1 0 0 3 -0.77272727 -0.4239130 0.1169591
#> 441 8 5 6 5 4 4 0.74242424 0.6630435 -0.1754386
#> 442 3 1 2 1 1 4 -0.39393939 0.6630435 -1.0526316
#> 443 2 1 0 1 1 2 -1.15151515 -1.1485507 -1.0526316
#> 444 3 1 4 2 0 3 0.36363636 -1.1485507 -0.7602339
#> 445 3 2 4 2 1 5 1.12121212 0.3007246 -1.0526316
#> 446 0 1 2 4 3 6 -1.15151515 -0.4239130 -0.7602339
#> 447 2 0 2 4 2 4 -0.01515152 -0.7862319 0.1169591
#> 448 4 2 3 3 4 4 -0.39393939 -0.4239130 -0.4678363
#> 449 3 0 1 3 2 5 -1.15151515 -1.1485507 -0.4678363
#> 450 6 2 6 7 6 6 -0.01515152 -0.0615942 0.9941520
#> 451 2 1 0 3 2 5 -0.77272727 -0.7862319 -1.0526316
#> 452 1 4 4 2 0 4 -0.77272727 -0.7862319 -0.4678363
#> 453 2 2 1 4 3 3 -0.77272727 -0.7862319 0.1169591
#> 454 1 0 2 1 0 1 -0.01515152 -1.1485507 -0.4678363
#> 455 1 1 0 0 1 2 -0.77272727 -0.7862319 -0.7602339
#> 456 2 2 0 4 2 3 -1.15151515 -0.4239130 -0.1754386
#> 457 2 1 1 0 0 1 -1.15151515 -0.7862319 -1.0526316
#> 458 5 7 8 6 1 6 0.74242424 0.3007246 1.2865497
#> 459 6 3 4 7 3 5 3.39393939 3.1992754 2.4561404
#> 460 6 3 4 7 6 4 -0.01515152 1.7500000 0.7017544
#> 461 1 0 0 4 1 1 -1.15151515 -0.7862319 0.1169591
#> 462 3 7 4 3 1 6 -0.39393939 1.0253623 -0.4678363
#> 463 1 1 1 2 1 2 -1.15151515 -1.1485507 -1.0526316
#> 464 3 3 5 5 3 2 -0.01515152 -0.4239130 0.1169591
#> 465 1 2 0 2 1 4 -1.15151515 -1.1485507 -1.0526316
#> 466 2 0 1 0 0 2 -0.77272727 -0.4239130 -0.4678363
#> 467 0 0 1 1 0 4 -0.01515152 -0.4239130 -0.7602339
#> 468 3 3 1 0 1 2 -1.15151515 -0.7862319 -1.0526316
#> 469 5 4 4 1 2 5 1.50000000 -0.4239130 -0.7602339
#> 470 2 4 2 0 3 4 -0.77272727 -0.7862319 -0.7602339
#> 471 2 0 0 3 1 5 -0.77272727 -1.1485507 -1.0526316
#> 472 2 3 3 1 1 3 0.74242424 -0.0615942 -0.1754386
#> 473 6 5 3 6 4 5 -0.77272727 -0.0615942 -0.1754386
#> 474 4 2 2 5 3 4 0.36363636 -0.0615942 0.4093567
#> 475 1 0 2 1 3 3 -1.15151515 -0.7862319 -0.7602339
#> 476 5 1 5 2 0 5 1.50000000 1.3876812 0.7017544
#> 477 2 2 4 4 2 3 -1.15151515 1.3876812 -0.4678363
#> 478 4 5 6 3 3 3 -0.39393939 -0.7862319 -0.4678363
#> 479 2 2 1 4 2 5 -1.15151515 -0.0615942 1.2865497
#> 480 2 2 2 2 3 2 -0.77272727 -1.1485507 -0.1754386
#> 481 2 3 2 4 1 5 -0.77272727 -0.7862319 0.1169591
#> 482 2 4 1 6 0 4 -0.01515152 1.0253623 -1.0526316
#> 483 3 4 2 3 4 3 0.74242424 0.3007246 1.5789474
#> 484 4 2 2 4 2 7 -1.15151515 1.0253623 -0.4678363
#> 485 3 4 3 3 2 4 -0.77272727 -0.4239130 0.7017544
#> 486 6 4 4 4 1 1 1.12121212 2.4746377 0.1169591
#> 487 2 4 2 5 2 3 -1.15151515 -1.1485507 -1.0526316
#> 488 2 1 3 3 0 4 -0.01515152 -0.0615942 -0.4678363
#> 489 3 0 1 5 1 5 -0.39393939 0.3007246 1.2865497
#> 490 4 2 3 2 2 1 -1.15151515 -0.4239130 0.4093567
#> 491 2 1 3 3 2 2 -1.15151515 -1.1485507 -1.0526316
#> 492 5 3 3 5 5 5 -0.39393939 1.3876812 -0.1754386
#> 493 4 3 4 4 3 4 -1.15151515 -0.0615942 -1.0526316
#> 494 3 1 1 3 2 2 -1.15151515 -0.0615942 0.4093567
#> 495 1 0 2 0 1 4 -0.39393939 -0.7862319 -0.4678363
#> 496 1 1 0 1 0 1 -1.15151515 -1.1485507 -1.0526316
#> 497 4 2 1 5 2 2 1.87878788 0.6630435 -0.7602339
#> 498 2 2 1 1 2 4 -0.39393939 -0.4239130 -1.0526316
#> 499 2 1 4 1 1 3 -1.15151515 -1.1485507 -0.4678363
#> 500 3 3 3 2 1 3 -0.77272727 -0.4239130 -1.0526316
#> 501 1 2 2 1 3 2 0.74242424 1.0253623 -0.7602339
#> 502 2 2 0 2 3 4 -1.15151515 -0.4239130 -1.0526316
#> 503 4 3 3 5 2 6 0.36363636 0.3007246 -0.4678363
#> 504 2 1 1 1 1 3 -1.15151515 -1.1485507 -1.0526316
#> 505 1 2 2 1 1 5 -0.39393939 -0.4239130 -0.4678363
#> 506 3 2 3 4 3 4 0.36363636 0.3007246 -1.0526316
#> 507 4 4 4 1 2 4 0.36363636 0.6630435 -0.7602339
#> 508 0 2 2 2 0 3 -1.15151515 -1.1485507 -0.7602339
#> 509 2 2 1 0 2 3 -0.39393939 -1.1485507 -1.0526316
#> 510 4 1 3 2 1 6 -0.39393939 -1.1485507 0.9941520
#> 511 2 2 3 5 3 5 0.74242424 -0.0615942 0.1169591
#> 512 3 2 2 0 1 4 1.12121212 -0.7862319 -1.0526316
#> 513 1 2 2 1 0 3 -0.77272727 -1.1485507 -1.0526316
#> 514 1 1 0 1 4 4 -1.15151515 -0.7862319 -1.0526316
#> 515 2 3 2 3 4 1 -1.15151515 -1.1485507 -1.0526316
#> 516 1 3 2 2 3 3 1.12121212 0.3007246 -0.4678363
#> 517 1 1 2 0 1 4 -0.39393939 -1.1485507 -1.0526316
#> 518 3 2 3 2 2 3 1.87878788 -0.0615942 -1.0526316
#> 519 8 7 5 6 8 3 3.01515152 2.1123188 -0.7602339
#> 520 4 2 4 4 5 3 -0.39393939 0.3007246 0.4093567
#> 521 6 5 4 0 0 2 1.87878788 1.0253623 -0.1754386
#> 522 4 2 1 4 3 3 -0.77272727 1.3876812 0.4093567
#> 523 2 4 3 4 6 5 -0.77272727 -0.4239130 -1.0526316
#> 524 0 2 3 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 525 5 5 6 7 2 5 0.74242424 0.3007246 -0.1754386
#> 526 2 1 2 0 0 2 -0.77272727 -0.7862319 -1.0526316
#> 527 6 4 5 4 5 2 1.50000000 -0.7862319 -0.4678363
#> 528 1 1 0 0 1 1 -0.77272727 -1.1485507 -1.0526316
#> 529 1 0 2 4 3 5 -0.77272727 -0.7862319 -1.0526316
#> 530 3 5 5 3 3 5 -0.01515152 0.6630435 -0.7602339
#> 531 2 1 0 2 4 3 -1.15151515 -0.4239130 -0.7602339
#> 532 2 0 3 3 2 3 -0.39393939 -0.4239130 0.1169591
#> 533 3 1 2 3 1 2 -0.77272727 -0.7862319 -1.0526316
#> 534 4 5 6 6 4 6 -0.39393939 -0.7862319 0.9941520
#> 535 6 4 4 5 5 5 -1.15151515 -0.7862319 0.1169591
#> 536 2 2 4 1 1 2 -0.39393939 -0.0615942 -0.4678363
#> 537 3 3 4 0 3 5 0.36363636 -0.7862319 -0.1754386
#> 538 1 1 1 0 1 2 -1.15151515 -1.1485507 -1.0526316
#> 539 2 1 1 0 2 4 -0.39393939 -0.7862319 -0.4678363
#> 540 2 1 0 3 0 4 -1.15151515 -0.4239130 1.5789474
#> 541 2 0 2 6 0 2 -1.15151515 -0.7862319 1.2865497
#> 542 2 1 2 0 0 2 -0.77272727 -1.1485507 -1.0526316
#> 543 2 1 1 4 1 2 -1.15151515 0.3007246 3.3333333
#> 544 3 0 0 3 2 1 -0.77272727 -0.4239130 0.4093567
#> 545 2 0 2 0 0 2 -0.77272727 -1.1485507 -1.0526316
#> 546 2 2 0 3 1 3 1.12121212 0.6630435 0.9941520
#> 547 5 1 3 2 1 2 -0.39393939 -0.4239130 -1.0526316
#> 548 0 1 0 0 0 3 -0.77272727 -0.7862319 -1.0526316
#> 549 5 1 2 6 4 6 -0.77272727 0.3007246 1.2865497
#> 550 6 3 5 7 2 2 1.87878788 3.1992754 3.6257310
#> 551 2 0 2 3 0 3 -1.15151515 -0.7862319 0.1169591
#> 552 1 0 0 0 1 0 -0.77272727 -1.1485507 -1.0526316
#> 553 2 1 2 0 1 3 -0.39393939 0.3007246 2.7485380
#> 554 1 1 1 6 3 2 -0.01515152 0.3007246 -0.1754386
#> 555 2 0 1 6 3 2 -0.77272727 -1.1485507 0.1169591
#> 556 2 0 2 3 0 2 -0.01515152 -1.1485507 0.1169591
#> 557 1 0 1 2 1 2 0.36363636 1.0253623 -0.4678363
#> 558 0 0 1 0 0 1 -1.15151515 -0.7862319 -0.7602339
#> 559 1 2 2 1 1 4 -0.77272727 -0.4239130 -0.4678363
#> 560 5 5 3 3 2 3 -1.15151515 -1.1485507 -1.0526316
#> 561 0 1 0 0 1 0 0.36363636 0.3007246 0.7017544
#> 562 1 0 1 1 0 3 -0.39393939 -0.0615942 1.5789474
#> 563 2 1 1 4 1 7 -0.39393939 -0.0615942 0.7017544
#> 564 2 0 1 0 0 2 -1.15151515 -0.4239130 -1.0526316
#> 565 2 2 2 0 0 1 -0.01515152 -0.4239130 -0.7602339
#> 566 3 3 3 1 1 2 -0.01515152 -0.7862319 0.4093567
#> 567 1 2 1 0 1 0 -0.39393939 -0.4239130 -1.0526316
#> 568 3 1 1 3 0 2 -0.77272727 1.0253623 0.1169591
#> 569 3 1 1 3 3 5 -1.15151515 -1.1485507 0.4093567
#> 570 3 2 1 1 0 1 -0.01515152 -0.4239130 -0.7602339
#> 571 3 1 1 0 0 3 -1.15151515 -1.1485507 -1.0526316
#> 572 1 0 2 2 1 0 -0.39393939 -0.7862319 -0.4678363
#> 573 1 1 0 2 1 3 -1.15151515 -0.7862319 0.4093567
#> 574 4 1 1 7 3 1 -1.15151515 0.3007246 0.9941520
#> 575 3 4 2 2 2 4 -0.39393939 -0.0615942 -0.1754386
#> 576 3 1 2 2 2 4 -0.01515152 -0.0615942 1.2865497
#> 577 1 1 1 1 1 0 -0.39393939 -0.0615942 -0.1754386
#> 578 0 2 1 0 1 2 1.87878788 -0.0615942 0.1169591
#> 579 3 1 2 3 3 5 -0.77272727 -1.1485507 -0.4678363
#> 580 2 1 1 5 0 6 -0.39393939 -1.1485507 0.1169591
#> 581 4 1 3 4 2 1 0.36363636 1.0253623 0.1169591
#> 582 1 2 0 1 0 0 -0.77272727 -0.4239130 -0.4678363
#> 583 6 7 5 7 6 5 1.87878788 1.3876812 -0.1754386
#> 584 2 1 3 0 0 1 1.50000000 0.3007246 -0.1754386
#> 585 4 1 0 1 0 3 -0.39393939 -0.4239130 -0.7602339
#> 586 5 2 3 3 4 5 -0.77272727 -0.4239130 0.1169591
#> 587 4 1 0 4 3 4 -1.15151515 -0.0615942 -1.0526316
#> 588 3 1 3 6 4 3 -0.77272727 1.0253623 1.8713450
#> 589 4 8 6 5 2 5 0.74242424 0.3007246 0.7017544
#> 590 2 3 2 1 0 1 -1.15151515 -1.1485507 -0.1754386
#> 591 4 2 2 6 2 5 -1.15151515 2.1123188 1.2865497
#> 592 1 2 2 7 3 5 -0.77272727 0.6630435 1.2865497
#> 593 3 2 2 3 3 2 -0.39393939 -1.1485507 -1.0526316
#> 594 1 0 2 1 0 1 -0.39393939 -0.4239130 0.4093567
#> 595 1 1 0 1 0 1 -0.77272727 -0.4239130 0.1169591
#> 596 2 1 2 0 0 3 -0.01515152 0.3007246 -1.0526316
#> 597 3 4 4 1 1 4 1.12121212 -0.0615942 -0.7602339
#> 598 4 1 1 4 1 2 -0.01515152 -0.4239130 0.1169591
#> 599 3 2 3 3 1 4 -1.15151515 -0.4239130 0.4093567
#> 600 1 1 0 5 3 4 -1.15151515 -0.0615942 1.5789474
#> 601 3 0 3 2 1 3 -1.15151515 -0.0615942 -0.4678363
#> 602 2 1 1 4 1 2 -1.15151515 -0.4239130 -0.4678363
#> 603 5 2 3 4 3 5 -1.15151515 -0.4239130 0.4093567
#> 604 3 1 1 5 2 0 -0.39393939 -0.7862319 -0.4678363
#> 605 1 1 2 0 0 1 0.36363636 -0.7862319 -1.0526316
#> 606 2 3 3 2 3 5 -0.39393939 -0.4239130 0.7017544
#> 607 1 1 1 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 608 0 0 3 1 2 4 -0.01515152 -1.1485507 -0.1754386
#> 609 2 0 2 4 3 4 0.74242424 -0.4239130 -1.0526316
#> 610 3 1 2 3 4 3 0.36363636 -0.0615942 -1.0526316
#> 611 1 0 1 5 4 4 -1.15151515 -0.0615942 -0.4678363
#> 612 2 0 2 0 0 1 0.74242424 1.3876812 0.7017544
#> 613 4 3 1 3 5 3 -1.15151515 -1.1485507 -1.0526316
#> 614 1 1 2 0 0 4 -1.15151515 0.6630435 0.7017544
#> 615 2 2 4 6 2 3 -1.15151515 -1.1485507 -0.7602339
#> 616 1 4 4 3 3 5 1.50000000 -0.4239130 -0.1754386
#> 617 2 4 1 2 1 5 -0.77272727 -0.7862319 -1.0526316
#> 618 4 2 3 3 3 6 -0.01515152 -0.7862319 0.1169591
#> 619 2 2 3 2 2 3 1.87878788 1.7500000 1.2865497
#> 620 1 0 2 2 0 2 -0.77272727 -0.7862319 -0.7602339
#> 621 3 2 4 3 2 4 -1.15151515 -0.4239130 0.1169591
#> 622 1 1 3 2 1 2 0.36363636 0.3007246 0.7017544
#> 623 4 2 3 7 3 5 -0.39393939 -0.4239130 -0.7602339
#> 624 4 2 2 7 4 5 -0.77272727 1.3876812 1.5789474
#> 625 1 0 3 0 0 0 -1.15151515 -0.7862319 -1.0526316
#> 626 3 2 3 5 2 5 -0.01515152 -0.0615942 -0.1754386
#> 627 3 3 2 2 3 5 -0.01515152 0.3007246 -0.4678363
#> 628 0 0 0 0 1 1 -0.77272727 -1.1485507 -1.0526316
#> 629 2 2 2 5 1 4 -0.77272727 -0.4239130 -0.1754386
#> 630 6 1 3 0 0 3 1.12121212 0.6630435 0.4093567
#> 631 1 1 1 0 0 0 -0.01515152 -0.4239130 -0.1754386
#> 632 7 2 4 7 5 6 -0.77272727 -0.0615942 -0.4678363
#> 633 0 0 1 2 1 0 -0.77272727 -1.1485507 -1.0526316
#> 634 1 1 3 2 0 1 -1.15151515 -1.1485507 -0.4678363
#> 635 0 0 0 1 1 3 -0.39393939 -0.4239130 -1.0526316
#> 636 1 2 0 1 1 2 -0.01515152 -1.1485507 -1.0526316
#> 637 2 3 2 3 1 4 -0.39393939 -0.0615942 0.1169591
#> 638 4 4 5 5 4 4 -1.15151515 -0.4239130 -0.1754386
#> 639 2 1 2 1 2 3 0.36363636 -0.4239130 -1.0526316
#> 640 1 1 1 0 1 2 -0.39393939 -1.1485507 -1.0526316
#> 641 3 4 4 3 1 5 -0.01515152 -0.7862319 -0.7602339
#> 642 6 2 4 4 3 4 -0.01515152 -0.7862319 -0.1754386
#> 643 3 3 5 0 1 2 -0.01515152 -0.4239130 -1.0526316
#> 644 3 3 4 2 2 6 -1.15151515 -0.4239130 -0.4678363
#> 645 3 1 0 6 4 2 -0.01515152 0.6630435 -0.1754386
#> 646 1 4 1 4 2 4 -1.15151515 -1.1485507 -1.0526316
#> 647 2 1 0 3 1 0 -0.77272727 -1.1485507 -1.0526316
#> 648 1 0 3 1 1 3 -0.39393939 -1.1485507 0.1169591
#> 649 1 1 2 2 0 4 -1.15151515 -1.1485507 -1.0526316
#> 650 1 1 2 2 1 3 -0.39393939 -0.7862319 -0.1754386
#> 651 4 7 5 5 3 5 0.36363636 0.3007246 -0.4678363
#> 652 2 5 3 3 3 1 -0.01515152 1.3876812 -1.0526316
#> 653 2 1 1 1 1 1 -0.77272727 -0.4239130 -1.0526316
#> 654 5 5 4 5 4 3 -0.77272727 -0.7862319 0.7017544
#> 655 2 1 2 5 2 4 -1.15151515 -1.1485507 -1.0526316
#> 656 2 0 2 4 0 1 -0.77272727 1.0253623 -0.1754386
#> 657 3 0 0 1 0 5 0.36363636 -0.4239130 1.2865497
#> 658 2 2 1 3 1 5 -0.39393939 -0.4239130 -0.7602339
#> 659 1 1 1 1 0 1 -0.39393939 -1.1485507 -0.7602339
#> 660 2 1 2 0 0 1 0.36363636 -0.4239130 -1.0526316
#> 661 2 0 2 0 0 3 -0.77272727 -1.1485507 -0.1754386
#> 662 4 2 3 1 0 5 0.74242424 -0.0615942 -0.4678363
#> 663 4 3 4 3 2 3 0.74242424 -0.0615942 0.1169591
#> 664 2 1 2 0 1 3 -1.15151515 -1.1485507 -1.0526316
#> 665 7 3 3 4 3 5 2.25757576 2.1123188 0.9941520
#> 666 5 4 3 5 2 4 0.74242424 1.3876812 -0.4678363
#> 667 5 1 5 1 1 6 -0.39393939 0.3007246 1.5789474
#> 668 2 2 1 3 0 3 0.36363636 -0.0615942 -0.7602339
#> 669 0 0 1 3 1 4 -0.77272727 -1.1485507 0.4093567
#> 670 2 1 1 3 1 4 -0.77272727 -0.7862319 -0.4678363
#> 671 2 2 2 1 1 2 -0.01515152 -0.7862319 -1.0526316
#> 672 2 1 2 1 0 4 -0.77272727 1.0253623 2.1637427
#> 673 4 2 3 6 1 4 -1.15151515 -0.4239130 -0.7602339
#> 674 2 3 2 4 1 3 -0.01515152 -0.4239130 -0.4678363
#> 675 1 2 3 5 2 3 -1.15151515 -0.0615942 -1.0526316
#> 676 5 2 5 2 0 3 -0.01515152 -0.0615942 0.4093567
#> 677 2 5 2 2 5 4 -0.01515152 -1.1485507 -1.0526316
#> 678 2 4 1 1 1 2 -0.77272727 -1.1485507 -1.0526316
#> 679 1 0 2 2 0 2 0.74242424 0.3007246 -0.7602339
#> 680 3 1 3 1 1 2 -0.39393939 -1.1485507 -0.7602339
#> 681 3 2 1 2 2 4 0.36363636 -0.4239130 0.9941520
#> 682 2 0 1 3 2 3 -0.77272727 -0.7862319 -0.4678363
#> 683 1 2 2 5 2 2 -0.77272727 -0.0615942 0.4093567
#> 684 5 5 3 4 4 6 1.12121212 -0.0615942 -0.1754386
#> 685 5 2 4 2 0 5 1.12121212 -0.0615942 -0.4678363
#> 686 1 2 1 2 3 3 -0.39393939 -0.7862319 -0.4678363
#> 687 2 1 0 3 2 1 -1.15151515 -0.4239130 -0.7602339
#> 688 7 1 5 3 1 5 3.01515152 2.4746377 2.1637427
#> 689 3 3 1 2 1 3 -0.39393939 -1.1485507 -1.0526316
#> 690 2 2 2 1 0 2 -0.77272727 -1.1485507 -1.0526316
#> 691 3 2 1 3 5 2 -1.15151515 -0.4239130 -0.1754386
#> 692 2 5 5 2 1 5 0.74242424 -0.4239130 -1.0526316
#> 693 2 4 3 1 1 1 0.36363636 0.6630435 -1.0526316
#> 694 2 2 5 2 0 5 -0.01515152 1.0253623 -0.4678363
#> 695 2 4 3 0 0 2 -1.15151515 -1.1485507 -1.0526316
#> 696 1 0 0 0 0 0 -1.15151515 -1.1485507 -1.0526316
#> 697 4 4 2 3 0 3 0.36363636 -0.0615942 -0.1754386
#> 698 1 4 3 4 2 3 -1.15151515 -0.4239130 -0.4678363
#> 699 3 2 6 4 1 6 0.36363636 -0.4239130 0.9941520
#> 700 1 2 2 1 0 3 -0.77272727 -0.0615942 -1.0526316
#> 701 0 1 1 0 0 3 -1.15151515 -1.1485507 -1.0526316
#> 702 0 0 2 4 1 2 -1.15151515 -0.7862319 -1.0526316
#> 703 1 1 1 0 1 1 -0.77272727 -1.1485507 -1.0526316
#> 704 2 1 1 0 0 3 0.36363636 -1.1485507 -0.4678363
#> 705 1 1 2 2 0 5 -1.15151515 -1.1485507 -1.0526316
#> 706 1 1 0 2 0 2 -1.15151515 -0.4239130 1.5789474
#> 707 1 1 0 0 0 4 0.74242424 -0.7862319 -1.0526316
#> 708 2 1 4 3 0 2 -1.15151515 0.6630435 0.7017544
#> 709 4 3 2 6 5 2 -0.39393939 -0.0615942 -0.1754386
#> 710 1 3 2 1 1 3 -0.39393939 -0.7862319 -0.7602339
#> 711 4 3 3 6 4 3 0.74242424 1.0253623 -1.0526316
#> 712 1 2 1 1 0 2 -1.15151515 -0.7862319 -0.4678363
#> 713 0 0 1 0 1 3 -1.15151515 -1.1485507 -0.7602339
#> 714 2 4 3 0 1 5 0.74242424 -1.1485507 -1.0526316
#> 715 2 3 3 0 0 4 -0.39393939 -1.1485507 -1.0526316
#> 716 2 2 2 0 1 5 -1.15151515 -1.1485507 -0.7602339
#> 717 0 0 2 1 0 2 -0.77272727 -0.0615942 -0.7602339
#> 718 3 3 2 4 3 5 -1.15151515 -0.7862319 -1.0526316
#> 719 4 2 0 4 4 2 -1.15151515 -0.7862319 -1.0526316
#> 720 6 1 2 5 6 5 -0.39393939 -0.7862319 0.1169591
#> 721 4 5 6 5 2 6 2.25757576 1.0253623 -1.0526316
#> 722 1 4 1 6 1 5 -0.77272727 -0.0615942 0.4093567
#> 723 3 0 1 6 2 4 -0.39393939 -0.4239130 3.6257310
#> 724 5 3 2 2 2 4 3.01515152 1.3876812 -0.4678363
#> 725 2 4 3 2 2 3 -1.15151515 -0.4239130 -0.7602339
#> 726 3 3 2 3 2 3 -0.01515152 -0.7862319 -0.7602339
#> 727 4 1 1 1 0 2 -0.39393939 -0.7862319 -1.0526316
#> 728 1 2 2 0 1 2 0.36363636 -0.0615942 -1.0526316
#> 729 3 4 5 0 2 3 0.74242424 -0.0615942 -1.0526316
#> 730 2 1 0 1 2 3 -0.01515152 0.3007246 -0.7602339
#> 731 1 0 1 4 0 3 -0.77272727 -0.0615942 -0.4678363
#> 732 3 4 3 0 2 3 -0.77272727 -1.1485507 -1.0526316
#> 733 7 4 4 7 7 5 -0.01515152 1.3876812 0.9941520
#> 734 3 4 2 4 3 4 -0.01515152 -0.7862319 -1.0526316
#> 735 2 2 3 0 1 3 -0.77272727 -1.1485507 -1.0526316
#> 736 3 4 4 4 3 5 -0.77272727 -0.7862319 -1.0526316
#> 737 1 1 1 1 1 4 -0.39393939 -0.4239130 -0.4678363
#> 738 0 0 4 2 0 3 -0.39393939 1.3876812 0.1169591
#> 739 1 2 2 5 1 5 -0.77272727 -0.7862319 -1.0526316
#> 740 4 2 3 4 2 5 -1.15151515 -0.4239130 0.9941520
#> 741 3 2 1 3 2 4 -1.15151515 -0.7862319 -1.0526316
#> 742 2 5 4 2 2 2 -0.39393939 -1.1485507 -1.0526316
#> 743 2 5 4 0 0 4 -0.39393939 -0.7862319 -1.0526316
#> 744 4 4 5 3 3 5 -0.39393939 -0.4239130 -0.4678363
#> 745 3 1 4 2 1 4 -1.15151515 -1.1485507 -0.7602339
#> 746 2 1 1 1 4 3 -0.77272727 -1.1485507 -1.0526316
#> 747 0 4 2 1 2 4 -1.15151515 -0.7862319 -0.7602339
#> 748 3 1 0 0 2 5 1.12121212 -0.7862319 0.1169591
#> 749 5 1 2 5 3 2 -0.77272727 -0.0615942 -1.0526316
#> 750 4 4 3 6 2 5 -0.77272727 -0.4239130 -1.0526316
#> 751 2 0 2 3 2 2 -0.39393939 1.3876812 -0.1754386
#> 752 1 1 3 3 2 3 -0.39393939 -1.1485507 -1.0526316
#> 753 5 5 5 3 4 2 -0.01515152 2.8369565 1.2865497
#> 754 4 2 1 2 3 4 -0.39393939 -1.1485507 -1.0526316
#> 755 2 5 7 4 4 4 -1.15151515 0.3007246 -0.4678363
#> 756 3 0 1 1 2 1 -1.15151515 -1.1485507 -1.0526316
#> 757 1 4 2 0 1 0 -0.77272727 -1.1485507 -1.0526316
#> 758 3 4 0 3 3 5 -0.77272727 -0.0615942 -0.4678363
#> 759 2 1 1 2 2 3 -1.15151515 -0.7862319 -1.0526316
#> 760 7 2 5 5 5 1 -0.77272727 -0.7862319 -1.0526316
#> 761 2 1 0 5 2 0 -1.15151515 -1.1485507 -1.0526316
#> 762 1 1 1 2 1 2 0.74242424 -0.4239130 -0.1754386
#> 763 0 0 0 0 0 0 -1.15151515 -1.1485507 -0.7602339
#> 764 2 1 1 2 2 0 -0.39393939 -0.4239130 0.1169591
#> 765 1 1 4 1 0 5 -0.39393939 0.3007246 0.9941520
#> 766 2 0 3 1 0 4 0.36363636 0.3007246 -0.1754386
#> 767 2 4 2 4 4 2 -1.15151515 -0.4239130 -1.0526316
#> 768 1 1 0 0 0 1 -1.15151515 -1.1485507 -1.0526316
#> 769 2 1 3 4 3 6 1.12121212 1.0253623 1.5789474
#> 770 2 4 1 0 1 2 -1.15151515 -1.1485507 -1.0526316
#> 771 6 3 1 6 3 2 0.36363636 1.3876812 0.7017544
#> 772 4 3 4 5 4 4 -0.39393939 1.7500000 0.4093567
#> 773 2 1 2 5 3 5 -0.77272727 -0.7862319 0.4093567
#> 774 6 2 4 5 3 3 -0.39393939 -1.1485507 0.9941520
#> 775 2 3 4 6 4 5 -0.77272727 -0.7862319 0.1169591
#> 776 1 1 0 0 1 2 -1.15151515 -1.1485507 -1.0526316
#> 777 2 1 1 0 0 0 -0.39393939 -1.1485507 -1.0526316
#> 778 2 1 2 1 0 3 -1.15151515 -0.0615942 -0.4678363
#> 779 2 2 2 7 3 3 -0.39393939 0.3007246 0.7017544
#> 780 2 2 3 2 1 5 0.36363636 0.3007246 1.2865497
#> 781 2 0 0 3 2 4 0.74242424 0.6630435 0.7017544
#> 782 1 1 1 2 1 4 -0.39393939 -1.1485507 -1.0526316
#> 783 2 1 1 2 0 1 -0.77272727 -0.7862319 0.1169591
#> 784 3 2 4 2 1 2 1.12121212 0.6630435 -0.4678363
#> 785 1 0 0 0 0 0 0.74242424 1.3876812 1.2865497
#> 786 7 4 6 7 8 5 1.12121212 0.6630435 0.1169591
#> 787 5 3 2 5 1 6 0.36363636 1.0253623 -0.1754386
#> 788 0 2 0 3 3 6 -0.77272727 -0.4239130 -0.7602339
#> 789 2 2 2 4 0 4 0.74242424 -0.0615942 -0.7602339
#> 790 3 3 3 3 2 6 -0.01515152 -0.7862319 -0.1754386
#> 791 2 0 1 7 3 4 0.36363636 1.7500000 0.9941520
#> 792 2 1 1 1 0 0 -0.01515152 -0.0615942 -0.4678363
#> 793 1 1 1 1 1 2 -1.15151515 -1.1485507 -0.7602339
#> 794 3 1 3 2 0 2 -0.01515152 -0.4239130 0.1169591
#> 795 3 2 7 0 0 2 -0.39393939 -0.4239130 0.1169591
#> 796 4 6 4 6 5 4 -1.15151515 -0.7862319 -0.4678363
#> 797 4 1 2 6 1 7 -0.39393939 -0.4239130 0.1169591
#> 798 1 1 1 5 0 5 -0.77272727 -1.1485507 -0.7602339
#> 799 1 1 2 5 0 3 -0.77272727 -0.0615942 -0.7602339
#> 800 3 4 3 5 4 6 -0.77272727 0.3007246 -0.7602339
#> 801 4 2 5 6 1 4 -0.01515152 1.0253623 1.2865497
#> 802 2 0 1 4 1 2 -1.15151515 -0.0615942 2.7485380
#> 803 3 2 4 6 0 4 1.12121212 -0.4239130 -0.4678363
#> 804 2 1 0 3 1 2 -0.01515152 1.0253623 0.1169591
#> 805 4 1 0 3 2 4 -0.77272727 -1.1485507 -0.1754386
#> 806 1 2 3 5 4 4 -1.15151515 -0.0615942 0.1169591
#> 807 2 0 0 0 1 0 -1.15151515 -0.7862319 -1.0526316
#> 808 6 7 5 7 8 4 1.12121212 -0.4239130 -0.4678363
#> 809 2 0 0 4 1 2 -1.15151515 -1.1485507 0.1169591
#> 810 2 1 2 3 0 3 -0.39393939 -1.1485507 -0.7602339
#> 811 2 1 1 1 1 1 0.36363636 -0.4239130 -0.7602339
#> 812 0 4 3 6 6 3 -0.77272727 -0.0615942 1.5789474
#> 813 2 0 3 0 0 4 -0.39393939 -0.4239130 -0.4678363
#> 814 2 3 0 4 1 3 -0.77272727 -1.1485507 -0.4678363
#> 815 3 2 0 4 2 2 -1.15151515 -1.1485507 0.4093567
#> 816 1 1 3 4 2 4 -1.15151515 -0.4239130 -0.7602339
#> 817 2 2 2 2 0 2 1.87878788 -0.4239130 -0.4678363
#> 818 3 2 4 7 2 7 -0.39393939 -0.0615942 1.2865497
#> 819 4 2 4 4 2 4 -0.39393939 -0.0615942 -1.0526316
#> 820 3 2 0 1 0 2 -0.39393939 -0.7862319 0.1169591
#> 821 4 3 2 5 3 2 -0.39393939 -0.7862319 -0.7602339
#> 822 1 1 1 0 0 3 0.74242424 -1.1485507 -0.7602339
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#> 824 7 6 3 3 4 6 2.25757576 0.6630435 -0.1754386
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#> 826 5 4 3 3 1 2 -0.39393939 -0.4239130 -1.0526316
#> 827 4 1 3 3 1 5 -1.15151515 -0.0615942 2.4561404
#> 828 1 2 2 2 4 4 -0.77272727 -1.1485507 -1.0526316
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#> 831 2 0 3 3 1 2 -0.39393939 -0.4239130 -0.7602339
#> 832 4 1 2 0 1 3 0.74242424 -0.0615942 -1.0526316
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#> 834 0 0 3 1 0 7 0.36363636 -0.4239130 -1.0526316
#> 835 3 1 2 0 1 2 0.74242424 -0.7862319 -0.1754386
#> 836 3 3 3 5 6 5 -0.77272727 -0.0615942 0.1169591
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#> 838 0 0 0 0 0 1 1.87878788 0.3007246 0.1169591
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#> 841 3 3 3 0 1 6 1.50000000 1.0253623 0.1169591
#> 842 4 4 4 3 1 6 2.63636364 0.6630435 0.4093567
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#> 844 2 0 2 3 1 2 -0.77272727 -0.4239130 -1.0526316
#> 845 4 1 2 2 3 6 1.12121212 1.3876812 0.7017544
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#> 850 5 4 4 6 6 6 -0.39393939 0.3007246 0.7017544
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#> 865 1 0 4 3 1 3 1.50000000 -0.4239130 0.4093567
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#> 882 4 1 2 6 2 2 -0.77272727 0.3007246 -0.4678363
#> 883 4 2 2 3 1 4 1.50000000 1.3876812 -0.4678363
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#> 887 2 1 2 3 1 5 -0.01515152 1.3876812 -0.1754386
#> 888 2 2 2 0 0 3 -0.01515152 -0.4239130 0.1169591
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#> 893 5 4 5 6 5 5 -0.39393939 -0.0615942 0.1169591
#> 894 0 1 2 6 0 4 -1.15151515 -0.7862319 0.1169591
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#> 904 4 0 0 1 0 5 -1.15151515 -0.7862319 0.4093567
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#> 906 2 1 0 2 0 2 -0.77272727 -0.7862319 0.1169591
#> 907 2 1 2 3 2 4 -0.39393939 -0.4239130 -0.7602339
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#> 911 2 6 6 4 1 4 1.12121212 0.6630435 0.1169591
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#> 938 3 3 2 2 0 4 0.36363636 -0.4239130 0.4093567
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#> 940 2 3 3 2 1 2 -1.15151515 -1.1485507 0.7017544
#> 941 5 5 5 5 3 3 1.87878788 -0.0615942 0.1169591
#> 942 3 1 1 4 1 6 -1.15151515 -0.4239130 0.7017544
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#> 950 0 1 2 7 1 4 -1.15151515 -0.7862319 0.4093567
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#> 985 0 0 1 3 1 3 -0.77272727 -0.7862319 -0.1754386
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#> 987 5 2 1 5 2 4 -0.39393939 0.3007246 2.1637427
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#> 996 1 1 2 1 2 4 -0.39393939 -1.1485507 -1.0526316
#> 997 0 0 0 0 1 1 -0.01515152 -0.7862319 -1.0526316
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#> 999 3 1 2 3 4 4 -0.77272727 -0.0615942 0.4093567
#> 1000 0 5 7 4 5 4 1.87878788 1.7500000 1.2865497
#> 1001 2 0 0 0 0 1 -0.39393939 -0.0615942 -0.7602339
#> 1002 4 1 0 1 0 5 -0.77272727 -0.4239130 -0.7602339
#> 1003 4 1 1 3 4 4 -0.77272727 0.3007246 1.5789474
#> 1004 2 0 1 3 2 3 -0.39393939 -0.0615942 -0.4678363
#> 1005 4 5 5 4 1 4 1.50000000 1.3876812 0.9941520
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#> 1009 1 1 2 2 0 3 -0.01515152 -0.7862319 1.2865497
#> 1010 1 1 3 1 1 3 -1.15151515 -1.1485507 -0.4678363
#> 1011 4 2 1 2 2 4 -0.39393939 -0.0615942 0.4093567
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#> 1013 1 0 1 2 2 4 0.74242424 0.6630435 0.1169591
#> 1014 2 6 7 3 6 5 -0.01515152 0.3007246 0.1169591
#> 1015 4 1 2 2 2 4 -1.15151515 0.3007246 0.1169591
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#> 1018 0 0 1 2 0 0 -1.15151515 -1.1485507 -1.0526316
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#> 1022 4 1 5 0 0 5 0.36363636 -0.7862319 0.1169591
#> 1023 4 0 4 3 1 5 1.50000000 1.0253623 -0.1754386
#> 1024 0 0 2 5 0 2 -1.15151515 -0.7862319 0.1169591
#> 1025 3 3 0 2 1 1 -1.15151515 -0.4239130 -0.7602339
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#> 1035 3 2 2 2 0 2 -0.39393939 -0.7862319 -0.4678363
#> 1036 1 1 0 2 0 2 -0.77272727 -0.7862319 -0.4678363
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#> 1051 1 1 1 2 1 3 -1.15151515 -0.4239130 -0.1754386
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#> 1060 1 1 2 2 2 3 -0.39393939 -0.4239130 -1.0526316
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#> 1081 2 5 4 2 2 2 -0.77272727 -0.0615942 0.7017544
#> 1082 3 4 3 5 3 5 -0.39393939 0.6630435 -0.4678363
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#> 1085 0 2 0 2 0 2 -1.15151515 0.3007246 -0.7602339
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#> 1090 2 3 0 3 2 3 -1.15151515 -1.1485507 -1.0526316
#> 1091 4 5 4 4 4 2 -1.15151515 -0.7862319 -1.0526316
#> 1092 3 3 2 3 4 6 -0.01515152 -0.0615942 -1.0526316
#> 1093 1 2 0 1 1 1 -0.77272727 -1.1485507 -1.0526316
#> 1094 2 2 0 4 2 3 -0.01515152 0.3007246 0.4093567
#> 1095 1 1 3 0 2 4 -0.77272727 -0.4239130 -0.4678363
#> 1096 5 2 0 5 6 1 -0.39393939 0.6630435 0.4093567
#> 1097 3 2 3 4 5 3 -1.15151515 -0.7862319 -1.0526316
#> 1098 3 4 2 5 4 6 -0.77272727 -0.4239130 0.1169591
#> 1099 2 1 2 4 3 4 -0.77272727 -0.0615942 0.4093567
#> 1100 5 5 3 7 5 6 -0.77272727 0.3007246 -0.1754386
#> 1101 2 4 3 1 2 4 1.12121212 -0.7862319 -0.4678363
#> 1102 2 0 0 3 1 4 -1.15151515 -0.7862319 1.5789474
#> 1103 3 3 2 3 3 1 0.36363636 0.6630435 -0.7602339
#> 1104 2 2 3 4 0 4 -0.39393939 -0.4239130 -0.1754386
#> 1105 4 4 2 3 3 2 -1.15151515 -1.1485507 -1.0526316
#> 1106 1 1 0 6 3 2 -0.77272727 0.3007246 1.2865497
#> 1107 1 2 2 1 0 4 0.36363636 -0.4239130 -1.0526316
#> 1108 3 4 5 3 4 5 -0.77272727 -0.7862319 -0.7602339
#> 1109 3 1 4 5 1 3 -1.15151515 -1.1485507 1.2865497
#> 1110 1 1 3 0 0 3 -0.01515152 0.3007246 1.8713450
#> 1111 2 0 4 2 2 2 -1.15151515 1.0253623 2.7485380
#> 1112 2 1 6 2 2 5 -1.15151515 1.7500000 1.8713450
#> 1113 2 2 1 0 0 3 -1.15151515 -1.1485507 -1.0526316
#> 1114 2 2 0 2 1 2 -0.77272727 -1.1485507 -1.0526316
#> 1115 7 2 5 5 2 2 2.25757576 3.1992754 2.4561404
#> 1116 4 6 3 3 1 5 -0.77272727 -1.1485507 -1.0526316
#> 1117 5 3 5 5 5 5 1.50000000 1.0253623 0.1169591
#> 1118 4 4 5 4 0 4 1.12121212 0.6630435 0.9941520
#> 1119 7 3 2 4 2 5 0.36363636 -0.0615942 -0.1754386
#> 1120 2 2 2 2 1 3 -1.15151515 -0.7862319 -1.0526316
#> 1121 2 2 2 2 2 5 -0.39393939 -0.7862319 0.9941520
#> 1122 2 0 0 4 1 6 -1.15151515 -0.7862319 -1.0526316
#> 1123 0 1 0 1 0 1 -0.77272727 -1.1485507 -1.0526316
#> 1124 7 4 6 4 4 5 -0.01515152 0.3007246 -0.1754386
#> 1125 3 4 4 2 0 4 -0.77272727 -1.1485507 -1.0526316
#> 1126 0 1 1 1 0 2 -1.15151515 -1.1485507 -0.7602339
#> 1127 2 3 2 5 2 3 -0.77272727 -0.4239130 -1.0526316
#> 1128 1 2 2 3 1 3 -0.01515152 -0.0615942 -0.7602339
#> 1129 0 3 1 0 0 1 -1.15151515 -0.7862319 -0.4678363
#> 1130 2 2 1 6 0 2 -1.15151515 -0.4239130 0.4093567
#> 1131 3 3 3 3 2 6 -0.77272727 -0.4239130 -1.0526316
#> 1132 7 5 3 4 7 7 1.50000000 2.1123188 -0.1754386
#> 1133 9 6 9 7 8 7 0.36363636 -0.0615942 -1.0526316
#> 1134 2 2 3 3 3 3 1.12121212 1.3876812 0.9941520
#> 1135 4 1 1 3 1 4 0.36363636 -0.4239130 0.1169591
#> 1136 4 4 4 4 2 4 0.36363636 1.0253623 0.4093567
#> 1137 3 2 1 1 1 4 -1.15151515 -1.1485507 -0.1754386
#> 1138 1 2 2 1 0 1 -0.77272727 -0.7862319 -0.4678363
#> 1139 4 5 5 5 3 6 0.36363636 -0.0615942 -0.4678363
#> 1140 2 3 2 1 2 0 -1.15151515 -1.1485507 -1.0526316
#> 1141 5 6 3 4 8 4 -0.39393939 0.6630435 0.1169591
#> 1142 4 3 2 3 0 1 -0.01515152 -0.0615942 -0.7602339
#> 1143 4 7 5 5 5 3 0.36363636 2.1123188 -0.4678363
#> 1144 3 3 2 3 2 4 -0.01515152 -0.0615942 0.1169591
#> 1145 1 5 4 3 2 4 -0.77272727 -1.1485507 -1.0526316
#> 1146 2 0 2 0 0 2 -0.01515152 -0.7862319 -1.0526316
#> 1147 2 0 3 3 1 5 -0.77272727 -1.1485507 -1.0526316
#> 1148 2 2 3 1 2 5 -0.01515152 -0.7862319 -0.1754386
#> 1149 4 3 0 0 1 2 -1.15151515 -1.1485507 -0.7602339
#> 1150 2 5 2 5 4 3 -1.15151515 -1.1485507 -1.0526316
#> 1151 0 1 2 5 1 4 -1.15151515 -1.1485507 -0.7602339
#> 1152 4 1 2 7 3 5 -0.39393939 -0.0615942 -0.7602339
#> 1153 0 2 2 0 1 2 -1.15151515 -1.1485507 -1.0526316
#> 1154 6 1 1 4 1 2 0.36363636 0.3007246 -1.0526316
#> 1155 1 4 0 4 2 6 -0.39393939 -0.7862319 -1.0526316
#> 1156 2 3 3 2 0 3 -1.15151515 -1.1485507 -0.7602339
#> 1157 2 2 3 2 0 3 -0.77272727 -0.4239130 -1.0526316
#> 1158 6 2 2 5 3 2 -1.15151515 -0.7862319 0.1169591
#> 1159 2 3 1 5 1 3 -1.15151515 -1.1485507 -1.0526316
#> 1160 2 1 0 0 0 2 -1.15151515 -0.7862319 -1.0526316
#> 1161 3 1 1 5 0 2 -1.15151515 -1.1485507 -1.0526316
#> 1162 5 2 3 6 3 4 -1.15151515 0.3007246 0.1169591
#> 1163 1 0 1 1 0 0 -1.15151515 -1.1485507 -1.0526316
#> 1164 2 2 3 2 0 1 -1.15151515 -0.4239130 -0.7602339
#> 1165 2 0 3 1 0 2 -0.39393939 -0.7862319 -1.0526316
#> 1166 5 3 2 5 1 5 0.36363636 -1.1485507 -1.0526316
#> FG_z HI_z JK_z LM_z NO_z
#> 1 -0.05013193 0.63387978 1.3079179 0.95151515 1.84375
#> 2 -0.84168865 -0.18579235 0.4281525 0.95151515 1.53125
#> 3 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 4 1.53298153 0.63387978 0.4281525 0.64848485 1.84375
#> 5 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 6 0.74142480 0.63387978 -0.1583578 0.95151515 1.84375
#> 7 1.00527704 0.08743169 -0.1583578 -0.26060606 0.90625
#> 8 -0.84168865 -0.45901639 -0.1583578 -0.26060606 -0.03125
#> 9 -1.10554090 -1.27868852 -1.3313783 -0.56363636 -1.28125
#> 10 1.53298153 0.63387978 0.1348974 0.64848485 1.53125
#> 11 0.47757256 0.08743169 0.7214076 0.64848485 1.21875
#> 12 -0.05013193 -0.45901639 -0.1583578 -0.86666667 -0.03125
#> 13 0.47757256 1.18032787 1.8944282 1.86060606 2.15625
#> 14 -1.10554090 -1.00546448 -1.0381232 -0.86666667 -0.34375
#> 15 -1.10554090 -1.27868852 -1.6246334 -1.47272727 -0.65625
#> 16 -1.10554090 -1.00546448 -0.7448680 0.04242424 -0.96875
#> 17 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 18 -0.84168865 0.90710383 1.6011730 2.46666667 -1.28125
#> 19 -0.05013193 -1.00546448 -1.0381232 -0.56363636 -1.28125
#> 20 -0.57783641 1.72677596 2.1876833 1.55757576 1.21875
#> 21 -0.05013193 -0.45901639 -0.4516129 -1.47272727 -1.28125
#> 22 -0.05013193 -1.27868852 -1.3313783 0.34545455 -0.96875
#> 23 1.00527704 0.63387978 1.3079179 0.04242424 -0.65625
#> 24 -0.05013193 -0.18579235 -0.1583578 -0.26060606 0.28125
#> 25 -0.05013193 1.72677596 1.3079179 0.64848485 -0.96875
#> 26 0.74142480 0.08743169 -0.4516129 -0.26060606 0.28125
#> 27 -1.10554090 -1.55191257 -1.3313783 -0.56363636 -0.65625
#> 28 -1.10554090 -0.73224044 -0.4516129 -0.56363636 0.28125
#> 29 -0.84168865 -0.73224044 -1.0381232 2.16363636 -0.96875
#> 30 -0.31398417 0.36065574 -0.4516129 -0.26060606 -0.03125
#> 31 -1.10554090 -1.00546448 -1.3313783 -1.16969697 -1.28125
#> 32 -1.10554090 -1.27868852 -1.3313783 -0.86666667 -0.34375
#> 33 -0.57783641 -0.45901639 -0.4516129 0.04242424 -1.28125
#> 34 1.26912929 0.63387978 -0.7448680 -1.77575758 -0.65625
#> 35 1.79683377 1.45355191 1.6011730 1.25454545 -0.03125
#> 36 -0.05013193 -0.45901639 0.4281525 1.25454545 -1.28125
#> 37 -1.10554090 0.08743169 0.4281525 -0.26060606 -0.34375
#> 38 -1.10554090 -1.00546448 -0.1583578 -0.26060606 -0.65625
#> 39 -1.10554090 -0.45901639 -0.7448680 -0.26060606 -0.03125
#> 40 2.06068602 1.45355191 1.8944282 1.55757576 0.59375
#> 41 -1.10554090 -1.27868852 -1.0381232 0.04242424 0.28125
#> 42 -1.10554090 -1.55191257 -1.6246334 0.34545455 0.59375
#> 43 -1.10554090 -1.55191257 -1.6246334 0.04242424 -0.03125
#> 44 -1.10554090 -1.55191257 -1.3313783 -1.16969697 -1.28125
#> 45 -1.10554090 -1.00546448 -1.3313783 -0.86666667 0.28125
#> 46 -1.10554090 -1.27868852 -0.4516129 0.34545455 -0.65625
#> 47 -1.10554090 -0.45901639 -0.4516129 -0.86666667 -1.28125
#> 48 -0.84168865 -1.00546448 -0.7448680 0.04242424 -1.28125
#> 49 -0.57783641 -1.27868852 -1.6246334 -0.56363636 -1.28125
#> 50 -0.05013193 0.90710383 0.7214076 0.04242424 -1.28125
#> 51 0.21372032 1.45355191 0.4281525 1.25454545 -0.65625
#> 52 1.00527704 0.36065574 -0.4516129 0.04242424 1.53125
#> 53 -1.10554090 -0.73224044 0.1348974 0.04242424 0.90625
#> 54 -0.57783641 1.72677596 1.0146628 1.86060606 -1.28125
#> 55 0.47757256 0.08743169 0.7214076 0.95151515 -0.34375
#> 56 1.00527704 -0.18579235 1.0146628 1.25454545 -0.65625
#> 57 -0.84168865 -0.18579235 -0.1583578 0.04242424 0.59375
#> 58 -1.10554090 -1.55191257 -1.6246334 -1.16969697 -1.28125
#> 59 1.00527704 0.08743169 -1.0381232 -0.56363636 -0.03125
#> 60 -1.10554090 -1.55191257 -1.6246334 -0.86666667 -0.96875
#> 61 0.74142480 -0.18579235 -0.1583578 0.34545455 -0.96875
#> 62 0.74142480 0.90710383 0.4281525 -0.56363636 0.28125
#> 63 -1.10554090 -1.55191257 -1.6246334 -1.16969697 -0.96875
#> 64 1.00527704 0.63387978 1.3079179 0.64848485 0.28125
#> 65 2.06068602 2.00000000 1.0146628 0.95151515 0.28125
#> 66 -0.84168865 -0.45901639 -0.1583578 1.86060606 -0.65625
#> 67 -1.10554090 -1.55191257 -1.3313783 -1.47272727 -1.28125
#> 68 -1.10554090 -0.73224044 -1.0381232 2.76969697 -0.03125
#> 69 -0.31398417 -0.45901639 -0.4516129 -0.56363636 -0.34375
#> 70 -1.10554090 -0.73224044 -0.4516129 0.04242424 -0.03125
#> 71 -1.10554090 -1.55191257 -0.7448680 0.64848485 0.90625
#> 72 -1.10554090 -1.55191257 -1.6246334 -0.86666667 -0.96875
#> 73 0.21372032 0.36065574 -1.3313783 -0.26060606 -0.65625
#> 74 1.00527704 0.63387978 0.1348974 -0.26060606 1.84375
#> 75 -1.10554090 -0.73224044 -0.7448680 0.34545455 -1.28125
#> 76 -1.10554090 0.36065574 -0.1583578 0.34545455 1.84375
#> 77 1.00527704 1.18032787 1.6011730 1.55757576 2.15625
#> 78 -1.10554090 -1.55191257 -1.6246334 -0.86666667 -0.96875
#> 79 -1.10554090 -1.55191257 -1.3313783 0.04242424 -0.65625
#> 80 -1.10554090 -1.55191257 -1.6246334 0.04242424 0.28125
#> 81 -0.84168865 -0.18579235 -0.7448680 -0.56363636 0.59375
#> 82 -0.57783641 -0.45901639 0.1348974 -1.77575758 -0.03125
#> 83 0.74142480 -0.18579235 0.1348974 0.34545455 -0.03125
#> 84 -0.57783641 -1.00546448 -1.6246334 -1.16969697 -0.34375
#> 85 -0.84168865 -1.55191257 -1.6246334 -1.47272727 -0.65625
#> 86 -0.05013193 -0.45901639 -0.4516129 0.64848485 2.46875
#> 87 -0.05013193 0.90710383 1.0146628 1.86060606 0.90625
#> 88 -0.84168865 -0.45901639 0.1348974 0.04242424 -0.03125
#> 89 -0.84168865 -0.45901639 -0.1583578 0.04242424 3.40625
#> 90 -0.05013193 0.08743169 -0.1583578 0.95151515 0.28125
#> 91 -1.10554090 -1.27868852 -1.6246334 0.04242424 -0.34375
#> 92 1.00527704 -0.18579235 -0.1583578 -0.56363636 -0.65625
#> 93 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -0.65625
#> 94 -0.05013193 -0.18579235 0.1348974 -0.56363636 -0.34375
#> 95 0.21372032 0.36065574 -0.1583578 0.95151515 2.15625
#> 96 -1.10554090 -0.73224044 -0.4516129 0.04242424 -0.96875
#> 97 0.47757256 0.08743169 -0.1583578 1.55757576 -0.03125
#> 98 -1.10554090 -1.55191257 -1.3313783 -1.77575758 -0.65625
#> 99 -1.10554090 -1.27868852 -0.4516129 -0.86666667 -0.96875
#> 100 -0.05013193 -1.00546448 -1.0381232 -0.86666667 -0.65625
#> 101 -0.84168865 -1.55191257 -1.6246334 -1.77575758 -0.03125
#> 102 0.74142480 -0.45901639 -0.4516129 -1.16969697 -0.65625
#> 103 -0.84168865 0.36065574 0.4281525 -0.26060606 0.59375
#> 104 -0.57783641 0.36065574 0.7214076 0.04242424 -0.65625
#> 105 0.21372032 1.18032787 1.8944282 2.16363636 1.53125
#> 106 -1.10554090 -1.00546448 -1.3313783 -0.86666667 -0.65625
#> 107 -1.10554090 -0.73224044 -0.4516129 -1.16969697 1.84375
#> 108 -0.57783641 -0.18579235 -0.7448680 0.34545455 -0.96875
#> 109 -0.84168865 -1.00546448 -0.4516129 -0.86666667 1.53125
#> 110 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 111 1.79683377 0.63387978 0.7214076 -0.26060606 -0.34375
#> 112 -1.10554090 -1.27868852 -1.3313783 -1.77575758 -1.28125
#> 113 -0.57783641 0.08743169 0.4281525 -1.16969697 -0.96875
#> 114 -0.05013193 -0.18579235 0.1348974 -0.26060606 0.90625
#> 115 -1.10554090 0.36065574 0.7214076 -0.56363636 -0.65625
#> 116 -1.10554090 -1.55191257 -1.6246334 -0.26060606 -1.28125
#> 117 0.21372032 0.08743169 0.1348974 0.64848485 -0.34375
#> 118 -0.84168865 1.45355191 2.4809384 2.16363636 -0.03125
#> 119 -0.31398417 -1.27868852 -1.0381232 -0.26060606 -0.65625
#> 120 -0.31398417 -1.00546448 -1.3313783 -0.56363636 -1.28125
#> 121 -0.05013193 -0.45901639 -0.4516129 -0.56363636 -0.03125
#> 122 -0.57783641 -0.73224044 -0.7448680 -1.47272727 -1.28125
#> 123 -0.31398417 -0.45901639 -0.4516129 -0.86666667 -0.34375
#> 124 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 125 1.00527704 0.63387978 0.7214076 0.64848485 1.21875
#> 126 -0.05013193 -0.45901639 -0.4516129 -0.56363636 -0.34375
#> 127 -0.84168865 -1.55191257 -1.3313783 -1.47272727 -1.28125
#> 128 -1.10554090 -0.73224044 -0.7448680 0.04242424 -0.96875
#> 129 -1.10554090 -0.45901639 -1.0381232 0.04242424 0.28125
#> 130 -0.05013193 0.08743169 1.3079179 -0.56363636 -0.34375
#> 131 -1.10554090 -1.55191257 -1.0381232 -1.47272727 -0.96875
#> 132 -1.10554090 -0.18579235 -0.1583578 -0.86666667 0.28125
#> 133 -0.31398417 0.36065574 1.3079179 1.55757576 0.90625
#> 134 -0.84168865 0.63387978 -0.1583578 -0.26060606 1.21875
#> 135 -0.57783641 0.90710383 0.1348974 0.95151515 0.59375
#> 136 -0.57783641 0.36065574 1.8944282 3.07272727 0.28125
#> 137 1.26912929 0.63387978 0.1348974 -0.26060606 -0.96875
#> 138 -0.57783641 -0.45901639 -0.4516129 -0.56363636 0.28125
#> 139 0.47757256 -0.18579235 -0.4516129 0.64848485 1.21875
#> 140 -0.84168865 -0.18579235 0.4281525 -0.26060606 -0.65625
#> 141 -0.84168865 -0.73224044 -1.0381232 -1.16969697 -1.28125
#> 142 1.53298153 -0.18579235 0.7214076 1.86060606 -0.96875
#> 143 0.21372032 0.08743169 0.1348974 0.34545455 -0.03125
#> 144 -1.10554090 -1.27868852 -1.0381232 -1.47272727 -1.28125
#> 145 -1.10554090 -1.27868852 -0.1583578 0.34545455 1.21875
#> 146 0.21372032 -1.27868852 -1.0381232 0.04242424 -0.96875
#> 147 -0.84168865 -0.45901639 -0.1583578 -0.56363636 -0.65625
#> 148 0.74142480 -1.00546448 -0.4516129 -1.16969697 -0.96875
#> 149 0.74142480 -0.45901639 -0.7448680 -1.47272727 -0.96875
#> 150 -0.84168865 -0.73224044 -0.4516129 -0.26060606 -0.03125
#> 151 -0.84168865 -0.45901639 0.1348974 -0.86666667 -0.03125
#> 152 -1.10554090 -1.27868852 -1.6246334 -1.77575758 -0.96875
#> 153 1.79683377 1.18032787 1.6011730 -0.56363636 -0.03125
#> 154 -0.84168865 -0.73224044 -0.4516129 0.34545455 0.59375
#> 155 -0.31398417 -0.45901639 -0.4516129 -0.26060606 -0.03125
#> 156 -1.10554090 -1.55191257 -1.6246334 -0.86666667 -0.34375
#> 157 -0.84168865 -0.18579235 -0.4516129 -0.86666667 0.28125
#> 158 -0.31398417 0.63387978 1.0146628 0.04242424 0.90625
#> 159 -0.84168865 1.18032787 0.7214076 0.95151515 -1.28125
#> 160 -1.10554090 -0.45901639 1.0146628 1.55757576 2.78125
#> 161 -0.84168865 0.36065574 0.4281525 0.34545455 -1.28125
#> 162 -0.05013193 -1.00546448 -1.3313783 -0.26060606 0.28125
#> 163 -1.10554090 -0.73224044 -0.7448680 -0.56363636 -0.96875
#> 164 0.74142480 -0.18579235 0.1348974 0.95151515 1.21875
#> 165 -1.10554090 -1.27868852 -1.6246334 -1.47272727 -1.28125
#> 166 -0.57783641 -1.27868852 -1.6246334 -1.16969697 -1.28125
#> 167 -0.31398417 1.72677596 2.1876833 1.86060606 -0.03125
#> 168 0.47757256 1.18032787 1.6011730 0.95151515 0.28125
#> 169 0.21372032 -0.18579235 0.4281525 2.16363636 -0.34375
#> 170 -0.84168865 -0.45901639 -0.4516129 0.34545455 0.59375
#> 171 -0.31398417 -0.73224044 -1.3313783 -1.16969697 -0.96875
#> 172 -1.10554090 -1.55191257 -1.3313783 -0.86666667 -1.28125
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#> 255 -0.57783641 -0.18579235 0.1348974 1.25454545 0.28125
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#> 267 -0.57783641 -0.73224044 0.1348974 0.95151515 0.28125
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#> 270 0.21372032 0.36065574 0.1348974 0.34545455 -0.03125
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#> 316 -1.10554090 -1.27868852 -0.7448680 0.64848485 1.84375
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#> 405 -1.10554090 0.90710383 1.0146628 0.64848485 -0.65625
#> 406 1.26912929 -0.45901639 -0.4516129 0.34545455 -0.34375
#> 407 0.74142480 0.63387978 0.1348974 0.34545455 1.21875
#> 408 -1.10554090 0.63387978 -0.1583578 -0.86666667 -0.65625
#> 409 -1.10554090 -0.45901639 -1.3313783 -1.16969697 2.46875
#> 410 -0.57783641 0.63387978 0.1348974 1.86060606 0.59375
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#> 415 -1.10554090 1.72677596 1.6011730 2.46666667 2.15625
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#> 422 -0.31398417 0.63387978 0.4281525 1.25454545 0.90625
#> 423 -1.10554090 -0.73224044 -0.4516129 0.04242424 -0.65625
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#> 425 -1.10554090 -1.27868852 -0.7448680 -0.56363636 0.28125
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#> 427 -0.84168865 -0.73224044 -0.1583578 -0.86666667 0.28125
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#> 429 1.53298153 1.45355191 0.1348974 0.34545455 -0.03125
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#> 431 -0.57783641 -0.18579235 -0.4516129 -1.16969697 -0.65625
#> 432 -0.84168865 -1.27868852 -0.7448680 0.34545455 1.84375
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#> 440 -0.57783641 -0.45901639 -0.7448680 -0.56363636 -1.28125
#> 441 -0.31398417 -0.73224044 -0.7448680 -1.47272727 0.90625
#> 442 -0.05013193 -0.18579235 0.1348974 0.34545455 -0.03125
#> 443 -1.10554090 -1.27868852 -1.6246334 -0.86666667 -0.96875
#> 444 -0.84168865 -1.00546448 -1.3313783 1.25454545 -0.96875
#> 445 -1.10554090 -1.27868852 -0.4516129 0.34545455 1.53125
#> 446 -1.10554090 -0.73224044 0.4281525 1.86060606 0.59375
#> 447 -0.31398417 -0.18579235 0.1348974 0.64848485 -0.96875
#> 448 -0.57783641 0.08743169 0.4281525 0.34545455 0.90625
#> 449 -0.57783641 1.72677596 1.8944282 1.55757576 -1.28125
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#> 451 -0.57783641 -0.45901639 0.1348974 0.34545455 -0.03125
#> 452 -0.84168865 -1.27868852 -1.3313783 -0.56363636 -0.96875
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#> 454 -1.10554090 -1.55191257 -0.7448680 -0.26060606 -0.03125
#> 455 -1.10554090 -1.27868852 0.4281525 0.95151515 -0.96875
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#> 457 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 458 2.06068602 0.36065574 -1.0381232 -0.86666667 -0.65625
#> 459 2.06068602 -0.18579235 -1.3313783 -1.77575758 0.90625
#> 460 1.79683377 2.00000000 2.7741935 1.55757576 0.90625
#> 461 -0.57783641 -1.00546448 -0.4516129 -0.56363636 -1.28125
#> 462 0.74142480 0.08743169 0.1348974 -0.26060606 1.21875
#> 463 -0.84168865 -0.45901639 0.4281525 0.34545455 0.28125
#> 464 0.47757256 -1.00546448 -0.7448680 -0.56363636 -0.03125
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#> 467 -0.57783641 -0.73224044 -0.7448680 -0.56363636 -1.28125
#> 468 -0.84168865 -0.18579235 0.1348974 0.95151515 0.90625
#> 469 -1.10554090 -1.55191257 -1.6246334 -0.86666667 0.59375
#> 470 -1.10554090 0.36065574 1.6011730 0.95151515 2.15625
#> 471 -0.05013193 0.63387978 0.4281525 -0.56363636 -1.28125
#> 472 -0.57783641 -1.00546448 -1.0381232 0.04242424 1.84375
#> 473 1.00527704 2.27322404 1.6011730 0.95151515 1.53125
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#> 475 -1.10554090 0.36065574 1.3079179 0.95151515 -0.65625
#> 476 -0.05013193 -0.45901639 -1.3313783 -0.86666667 0.28125
#> 477 -0.31398417 0.08743169 0.1348974 -0.86666667 -0.65625
#> 478 -1.10554090 -1.27868852 -1.3313783 -0.86666667 -0.65625
#> 479 0.74142480 1.18032787 1.3079179 0.34545455 -0.03125
#> 480 -0.31398417 1.18032787 1.3079179 1.55757576 -1.28125
#> 481 1.00527704 0.36065574 0.1348974 1.25454545 -0.65625
#> 482 1.00527704 1.45355191 0.7214076 1.86060606 0.59375
#> 483 -0.57783641 0.08743169 0.1348974 0.04242424 1.53125
#> 484 0.21372032 0.90710383 1.3079179 0.64848485 -0.34375
#> 485 -0.31398417 0.08743169 -0.1583578 -0.26060606 -0.65625
#> 486 -0.31398417 -0.73224044 -0.4516129 -0.86666667 1.53125
#> 487 -1.10554090 1.45355191 0.1348974 1.25454545 0.90625
#> 488 -1.10554090 -1.27868852 -1.6246334 0.04242424 -0.96875
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#> 490 -1.10554090 -0.45901639 -0.4516129 0.04242424 0.90625
#> 491 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -1.28125
#> 492 0.21372032 0.36065574 -0.1583578 0.64848485 -0.03125
#> 493 0.21372032 1.18032787 0.7214076 0.64848485 0.90625
#> 494 -0.05013193 0.08743169 0.4281525 0.34545455 -0.65625
#> 495 -0.31398417 0.08743169 -0.4516129 0.64848485 -0.96875
#> 496 -0.31398417 0.63387978 0.4281525 0.34545455 -0.65625
#> 497 -0.05013193 -1.55191257 -1.3313783 -0.86666667 -0.03125
#> 498 -1.10554090 -1.27868852 -1.0381232 -0.86666667 -1.28125
#> 499 0.47757256 0.63387978 1.3079179 0.04242424 0.28125
#> 500 -1.10554090 -0.18579235 0.1348974 0.64848485 0.28125
#> 501 -1.10554090 -1.55191257 -1.6246334 -1.47272727 -0.34375
#> 502 -1.10554090 -0.73224044 -0.7448680 -0.86666667 -0.03125
#> 503 -0.57783641 2.54644809 1.3079179 1.25454545 1.21875
#> 504 -1.10554090 -1.55191257 -1.6246334 -0.86666667 0.28125
#> 505 -0.84168865 -1.27868852 -0.7448680 -0.26060606 -0.34375
#> 506 -0.57783641 -1.55191257 0.1348974 -0.26060606 0.59375
#> 507 -0.84168865 -1.27868852 -0.7448680 0.04242424 0.59375
#> 508 -0.57783641 0.36065574 0.4281525 -0.26060606 -1.28125
#> 509 -1.10554090 -1.55191257 -1.6246334 -1.47272727 -0.65625
#> 510 -1.10554090 1.18032787 1.8944282 3.07272727 -1.28125
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#> 513 -1.10554090 -1.55191257 -1.3313783 -1.47272727 -0.34375
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#> 515 -1.10554090 -0.45901639 0.7214076 1.55757576 0.90625
#> 516 -0.84168865 -1.27868852 -1.0381232 -0.26060606 1.21875
#> 517 -0.57783641 0.08743169 0.1348974 1.86060606 0.59375
#> 518 -1.10554090 -1.55191257 -1.6246334 -1.16969697 -0.34375
#> 519 0.74142480 1.72677596 0.7214076 0.64848485 2.78125
#> 520 0.47757256 -0.45901639 -0.4516129 -0.26060606 -0.65625
#> 521 -1.10554090 -1.55191257 -1.6246334 -1.77575758 0.59375
#> 522 3.11609499 2.81967213 1.0146628 1.55757576 0.28125
#> 523 -0.57783641 0.90710383 1.6011730 3.07272727 -0.96875
#> 524 -1.10554090 -1.27868852 -0.4516129 -0.86666667 -0.34375
#> 525 -0.05013193 0.08743169 -0.1583578 -0.26060606 2.46875
#> 526 -1.10554090 -1.55191257 -1.6246334 0.04242424 -0.96875
#> 527 0.74142480 -1.00546448 -1.6246334 -0.56363636 -0.03125
#> 528 -1.10554090 -1.00546448 -1.3313783 -1.16969697 -1.28125
#> 529 -0.84168865 -1.00546448 -0.7448680 -0.26060606 -0.65625
#> 530 -0.05013193 0.90710383 1.6011730 1.86060606 1.21875
#> 531 -1.10554090 -1.00546448 -1.3313783 -1.77575758 -1.28125
#> 532 0.74142480 0.90710383 0.4281525 -0.26060606 -0.34375
#> 533 -0.57783641 -0.45901639 -0.7448680 -1.16969697 -0.34375
#> 534 -0.05013193 0.08743169 -0.1583578 1.25454545 2.15625
#> 535 -1.10554090 -1.27868852 -1.6246334 -1.16969697 1.53125
#> 536 -0.84168865 -0.73224044 -1.3313783 -0.86666667 0.59375
#> 537 -1.10554090 -1.00546448 -1.0381232 0.34545455 -0.03125
#> 538 -0.57783641 -1.00546448 0.4281525 0.34545455 -1.28125
#> 539 -0.57783641 -1.00546448 -1.3313783 -1.77575758 -1.28125
#> 540 -0.31398417 -1.55191257 -1.3313783 -1.77575758 -0.96875
#> 541 2.32453826 2.81967213 1.8944282 1.55757576 -1.28125
#> 542 -0.57783641 -0.73224044 -0.4516129 -0.86666667 0.59375
#> 543 -0.57783641 -1.00546448 -1.0381232 -0.56363636 -1.28125
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#> 545 -1.10554090 -1.55191257 -1.0381232 -1.16969697 -0.96875
#> 546 1.00527704 0.36065574 1.0146628 0.64848485 0.90625
#> 547 -0.05013193 -1.55191257 -1.6246334 -0.86666667 -0.34375
#> 548 -0.84168865 -1.00546448 -0.4516129 -1.16969697 -0.03125
#> 549 2.58839050 2.00000000 1.6011730 -0.26060606 -0.03125
#> 550 0.74142480 0.36065574 -0.7448680 -1.77575758 -0.96875
#> 551 0.47757256 -1.00546448 -0.4516129 -0.56363636 -0.96875
#> 552 -1.10554090 -0.18579235 -0.1583578 -0.86666667 -1.28125
#> 553 -0.57783641 -1.55191257 -1.0381232 -1.77575758 -1.28125
#> 554 1.53298153 0.90710383 1.0146628 0.34545455 -0.96875
#> 555 1.53298153 0.63387978 0.4281525 1.25454545 -0.96875
#> 556 0.74142480 -0.45901639 -1.0381232 -1.16969697 -0.65625
#> 557 -0.57783641 -1.00546448 -1.3313783 -1.77575758 -1.28125
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#> 559 -0.84168865 -1.55191257 -1.3313783 -0.56363636 -1.28125
#> 560 -1.10554090 -0.45901639 -0.1583578 0.34545455 1.84375
#> 561 1.79683377 1.18032787 0.4281525 0.04242424 0.59375
#> 562 0.47757256 0.36065574 -0.7448680 -0.86666667 -0.03125
#> 563 -0.31398417 2.54644809 1.8944282 0.95151515 -1.28125
#> 564 -0.31398417 -1.55191257 -1.3313783 -1.47272727 -1.28125
#> 565 -1.10554090 -1.55191257 -1.3313783 -1.47272727 -1.28125
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#> 567 -0.84168865 -0.45901639 -0.1583578 0.34545455 0.59375
#> 568 -0.57783641 -0.18579235 -0.7448680 -0.26060606 -0.96875
#> 569 1.00527704 2.00000000 1.3079179 0.95151515 -1.28125
#> 570 -0.31398417 -0.18579235 -0.7448680 0.34545455 0.90625
#> 571 -1.10554090 -0.45901639 -1.0381232 -0.26060606 -0.65625
#> 572 0.47757256 -0.45901639 -0.4516129 -0.56363636 -0.03125
#> 573 -0.05013193 -1.00546448 -0.4516129 -0.86666667 -0.96875
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#> 578 -1.10554090 -1.00546448 -1.0381232 -1.16969697 -1.28125
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#> 581 -0.05013193 -0.73224044 -0.7448680 -0.26060606 0.28125
#> 582 -0.31398417 -0.45901639 -0.7448680 -0.26060606 0.28125
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#> 585 -0.84168865 -1.55191257 -0.7448680 -0.86666667 -1.28125
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#> 590 -0.05013193 -0.73224044 -1.0381232 -1.16969697 -0.96875
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#> 599 -0.57783641 1.18032787 1.0146628 0.95151515 -0.03125
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#> 601 -1.10554090 -1.27868852 -1.3313783 -1.16969697 -1.28125
#> 602 0.21372032 -0.18579235 -0.7448680 -0.86666667 -0.96875
#> 603 1.00527704 0.63387978 0.1348974 0.04242424 -0.34375
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#> 606 -1.10554090 1.45355191 2.1876833 2.46666667 0.90625
#> 607 -0.84168865 -1.27868852 -1.3313783 -1.47272727 -1.28125
#> 608 -0.57783641 -0.18579235 0.4281525 0.04242424 -1.28125
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#> 610 -0.84168865 -0.73224044 -0.7448680 0.34545455 0.28125
#> 611 -0.31398417 1.45355191 1.3079179 0.95151515 1.21875
#> 612 -1.10554090 -1.55191257 -1.3313783 -0.26060606 -1.28125
#> 613 -0.57783641 -1.00546448 -1.0381232 -0.86666667 -0.03125
#> 614 -0.57783641 -1.55191257 -1.6246334 -1.16969697 -0.96875
#> 615 0.47757256 1.45355191 0.7214076 0.34545455 -0.03125
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#> 617 -1.10554090 -1.55191257 -1.3313783 -0.56363636 0.28125
#> 618 -0.31398417 0.90710383 1.6011730 1.25454545 -0.96875
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#> 620 -0.84168865 -0.73224044 -0.4516129 0.04242424 -0.96875
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#> 623 1.00527704 0.63387978 0.7214076 0.64848485 -0.65625
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#> 634 -0.84168865 0.36065574 0.7214076 0.34545455 0.59375
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#> 638 -0.31398417 0.08743169 0.1348974 -0.26060606 -0.03125
#> 639 -0.84168865 -0.45901639 0.1348974 1.25454545 1.21875
#> 640 -1.10554090 -1.55191257 -1.6246334 -1.47272727 -0.96875
#> 641 -1.10554090 -0.45901639 0.1348974 1.86060606 1.53125
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#> 649 -1.10554090 -0.73224044 -0.4516129 0.34545455 -0.96875
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#> 892 -0.05013193 -0.45901639 -0.4516129 -0.56363636 -1.28125
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#> 895 -0.84168865 -0.18579235 -0.4516129 -0.56363636 -0.65625
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#> 905 -0.57783641 -0.45901639 -0.1583578 0.64848485 0.90625
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#> 910 -1.10554090 0.63387978 0.7214076 0.64848485 -0.65625
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#> 944 -1.10554090 -0.73224044 0.1348974 1.55757576 0.28125
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#> 947 -1.10554090 0.63387978 1.3079179 3.07272727 -0.03125
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#> 949 2.06068602 1.45355191 0.1348974 0.04242424 -1.28125
#> 950 1.79683377 -0.18579235 0.4281525 0.64848485 -1.28125
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#> 956 -1.10554090 0.08743169 0.4281525 1.25454545 -1.28125
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#> 975 -1.10554090 0.08743169 0.1348974 0.95151515 -1.28125
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#> 986 -0.31398417 0.08743169 -0.1583578 -0.56363636 0.90625
#> 987 1.26912929 0.63387978 0.1348974 1.86060606 -0.03125
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#> 989 -0.84168865 -1.27868852 -1.0381232 -1.47272727 -0.96875
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#> 998 1.00527704 0.63387978 0.7214076 0.64848485 1.21875
#> 999 1.00527704 0.63387978 1.0146628 1.25454545 -1.28125
#> 1000 1.00527704 0.08743169 1.3079179 0.95151515 1.21875
#> 1001 -0.84168865 0.08743169 -0.1583578 -0.86666667 -1.28125
#> 1002 -0.57783641 0.63387978 0.4281525 -0.26060606 -0.03125
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#> 1005 -0.05013193 1.45355191 2.1876833 0.34545455 2.78125
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#> 1015 -0.57783641 -0.45901639 -0.7448680 -0.86666667 -0.96875
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#> 1036 -0.05013193 -1.00546448 -0.7448680 -0.86666667 -0.65625
#> 1037 -0.84168865 0.36065574 -0.1583578 -0.26060606 -0.65625
#> 1038 0.21372032 -0.45901639 -0.4516129 -1.16969697 -0.65625
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#> 1045 -1.10554090 -1.55191257 -1.3313783 -1.77575758 -0.96875
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#> 1060 -1.10554090 0.08743169 0.7214076 0.34545455 -0.96875
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#> 1062 -1.10554090 -1.55191257 -1.3313783 -0.86666667 -0.96875
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#> 1069 -0.84168865 0.90710383 0.7214076 0.34545455 -0.65625
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#> 1071 -0.05013193 -1.27868852 -1.0381232 -0.86666667 -0.96875
#> 1072 -0.31398417 -0.18579235 0.1348974 -0.86666667 -0.65625
#> 1073 -1.10554090 -1.00546448 -0.4516129 0.64848485 0.28125
#> 1074 -0.84168865 0.08743169 0.1348974 1.55757576 -0.65625
#> 1075 -1.10554090 -1.55191257 -1.3313783 -1.16969697 -1.28125
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#> 1078 -1.10554090 -1.00546448 -0.7448680 -1.16969697 -0.96875
#> 1079 -0.31398417 1.72677596 2.7741935 2.46666667 -0.03125
#> 1080 1.26912929 0.63387978 -0.1583578 0.95151515 2.78125
#> 1081 -0.84168865 0.36065574 0.1348974 -0.56363636 -0.65625
#> 1082 1.53298153 2.00000000 1.3079179 0.34545455 0.59375
#> 1083 -1.10554090 -1.00546448 -0.7448680 -1.47272727 -1.28125
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#> 1085 -0.84168865 -1.00546448 -0.7448680 -1.47272727 -0.96875
#> 1086 -0.57783641 -1.00546448 -1.0381232 0.64848485 0.90625
#> 1087 -0.57783641 -0.18579235 0.1348974 1.25454545 -0.03125
#> 1088 -0.57783641 -1.55191257 -1.3313783 -1.16969697 0.59375
#> 1089 -0.84168865 -0.18579235 -0.1583578 -0.86666667 -0.96875
#> 1090 -0.05013193 1.45355191 1.3079179 1.55757576 1.84375
#> 1091 -0.05013193 0.63387978 1.0146628 0.04242424 0.90625
#> 1092 -1.10554090 0.08743169 -0.1583578 -0.86666667 -1.28125
#> 1093 -0.84168865 -0.73224044 -0.7448680 -0.86666667 0.28125
#> 1094 -0.31398417 -0.18579235 -0.7448680 -0.26060606 1.21875
#> 1095 -0.31398417 -0.45901639 -1.3313783 -0.56363636 -1.28125
#> 1096 1.26912929 -0.18579235 -0.1583578 0.64848485 1.53125
#> 1097 -0.05013193 0.63387978 1.3079179 1.55757576 1.53125
#> 1098 1.79683377 1.72677596 1.8944282 0.95151515 1.84375
#> 1099 -0.57783641 -0.45901639 0.1348974 0.64848485 0.90625
#> 1100 1.00527704 2.81967213 2.4809384 0.64848485 -0.03125
#> 1101 -0.84168865 -0.18579235 -0.7448680 -0.26060606 1.53125
#> 1102 1.00527704 0.90710383 0.4281525 0.04242424 -1.28125
#> 1103 -0.31398417 0.36065574 -0.1583578 0.95151515 -0.34375
#> 1104 -0.57783641 0.08743169 0.4281525 1.25454545 1.21875
#> 1105 -1.10554090 1.18032787 2.1876833 2.76969697 1.53125
#> 1106 1.26912929 2.27322404 2.1876833 1.55757576 -0.96875
#> 1107 -1.10554090 -1.55191257 -1.3313783 0.34545455 0.90625
#> 1108 -0.57783641 2.81967213 2.7741935 1.86060606 -0.03125
#> 1109 1.26912929 2.27322404 -0.1583578 0.04242424 -1.28125
#> 1110 -0.57783641 -0.45901639 -0.4516129 -0.86666667 -1.28125
#> 1111 -0.05013193 1.45355191 0.4281525 -1.47272727 -1.28125
#> 1112 -0.05013193 -0.45901639 -0.4516129 -0.26060606 0.28125
#> 1113 -1.10554090 -1.55191257 -1.0381232 -0.56363636 -0.96875
#> 1114 -0.84168865 -0.45901639 -0.1583578 -0.56363636 -0.96875
#> 1115 0.74142480 -0.73224044 0.1348974 1.25454545 2.15625
#> 1116 -1.10554090 -1.27868852 -1.3313783 -1.16969697 -0.65625
#> 1117 0.21372032 0.90710383 0.1348974 -0.26060606 1.21875
#> 1118 -0.31398417 0.63387978 0.1348974 0.34545455 -0.65625
#> 1119 0.21372032 -0.73224044 -0.1583578 2.76969697 0.90625
#> 1120 -1.10554090 -0.18579235 0.1348974 -0.26060606 -0.65625
#> 1121 -0.05013193 0.08743169 -0.1583578 1.25454545 -0.65625
#> 1122 -0.31398417 -1.00546448 -0.1583578 -1.16969697 -1.28125
#> 1123 -1.10554090 -0.73224044 -0.7448680 -1.47272727 -0.96875
#> 1124 -1.10554090 -1.55191257 -1.6246334 0.95151515 1.21875
#> 1125 -1.10554090 0.08743169 -0.4516129 0.64848485 1.21875
#> 1126 -1.10554090 -1.00546448 -1.0381232 -1.77575758 -1.28125
#> 1127 -1.10554090 -1.27868852 -1.6246334 -0.26060606 -0.03125
#> 1128 -1.10554090 -0.18579235 0.4281525 0.64848485 0.59375
#> 1129 -1.10554090 0.08743169 0.1348974 -0.56363636 -0.03125
#> 1130 2.06068602 0.08743169 -0.1583578 -0.26060606 -0.96875
#> 1131 -1.10554090 -0.45901639 -1.0381232 0.04242424 -0.96875
#> 1132 -0.57783641 -0.18579235 0.1348974 1.55757576 2.46875
#> 1133 0.21372032 -1.00546448 -0.1583578 0.64848485 2.78125
#> 1134 0.21372032 0.36065574 0.7214076 0.64848485 1.21875
#> 1135 -0.84168865 -0.18579235 -0.7448680 -0.86666667 -0.65625
#> 1136 -0.57783641 -1.27868852 -1.6246334 -1.77575758 -0.03125
#> 1137 -1.10554090 0.90710383 0.4281525 2.16363636 -0.96875
#> 1138 -0.57783641 -1.00546448 -0.7448680 0.04242424 -0.65625
#> 1139 -0.57783641 -0.73224044 -1.0381232 -0.26060606 1.84375
#> 1140 -1.10554090 0.90710383 0.1348974 -0.56363636 -0.96875
#> 1141 -1.10554090 1.45355191 1.8944282 0.64848485 0.90625
#> 1142 -0.57783641 -1.00546448 0.7214076 1.55757576 -0.65625
#> 1143 0.47757256 -0.18579235 -0.4516129 0.04242424 -0.03125
#> 1144 0.74142480 0.90710383 0.4281525 0.64848485 -1.28125
#> 1145 -0.84168865 -0.45901639 0.1348974 0.34545455 0.90625
#> 1146 -1.10554090 -1.55191257 -1.6246334 -1.77575758 -0.96875
#> 1147 -0.05013193 -0.45901639 -0.1583578 -1.16969697 -0.34375
#> 1148 -1.10554090 -1.55191257 -0.4516129 1.25454545 0.28125
#> 1149 -0.57783641 -0.45901639 -0.4516129 0.04242424 -0.96875
#> 1150 0.47757256 1.72677596 1.3079179 2.76969697 -0.96875
#> 1151 -1.10554090 -0.73224044 -0.1583578 0.34545455 -1.28125
#> 1152 0.21372032 1.45355191 1.0146628 1.55757576 -0.34375
#> 1153 -1.10554090 -1.55191257 -1.6246334 -1.47272727 -1.28125
#> 1154 -0.57783641 -1.55191257 -1.3313783 0.34545455 1.53125
#> 1155 -0.84168865 -0.18579235 -0.4516129 -0.26060606 -0.34375
#> 1156 -1.10554090 -0.73224044 -0.4516129 0.34545455 -0.34375
#> 1157 -0.84168865 0.63387978 0.1348974 1.25454545 0.28125
#> 1158 -0.57783641 2.54644809 3.0674487 1.25454545 -1.28125
#> 1159 -1.10554090 -0.45901639 -0.7448680 -1.77575758 -1.28125
#> 1160 -0.84168865 -1.27868852 -1.0381232 -0.56363636 -0.96875
#> 1161 -0.31398417 -1.00546448 -0.4516129 1.25454545 0.28125
#> 1162 1.53298153 1.18032787 1.3079179 0.34545455 -0.03125
#> 1163 -1.10554090 -1.55191257 -1.6246334 0.95151515 -1.28125
#> 1164 -0.84168865 -1.55191257 -1.3313783 -0.86666667 -0.65625
#> 1165 -0.84168865 -1.27868852 -1.3313783 -1.47272727 -0.65625
#> 1166 -1.10554090 -1.55191257 -1.6246334 -0.56363636 -0.34375