Skip to contents

Print the waas_means object in two ways. By default, the results are shown in the R console. The results can also be exported to the directory.

Usage

# S3 method for waas_means
print(x, export = FALSE, file.name = NULL, digits = 4, ...)

Arguments

x

An object of class waas_means.

export

A logical argument. If TRUE, a *.txt file is exported to the working directory

file.name

The name of the file if export = TRUE

digits

The significant digits to be shown. See tibble::print() for more details.

...

Currently not used.

Author

Tiago Olivoto tiagoolivoto@gmail.com

Examples

# \donttest{
library(metan)
data_means <- means_by(data_ge, ENV, GEN)
model <- waas_means(data_ge,
                    env = ENV,
                    gen = GEN,
                    resp = everything())
#> Evaluating trait GY |======================                      | 50% 00:00:00 
Evaluating trait HM |============================================| 100% 00:00:00 

print(model)
#> Variable GY 
#> ---------------------------------------------------------------------------
#> Weighted average of the absolute scores
#> ---------------------------------------------------------------------------
#> # A tibble: 24 × 22
#>    type  Code      Y      PC1      PC2      PC3      PC4      PC5      PC6
#>    <chr> <chr> <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
#>  1 GEN   G1    2.604  0.3166  -0.04417  0.03600  0.06595 -0.3125   0.4272 
#>  2 GEN   G10   2.471 -1.001   -0.5718   0.1652   0.3309  -0.1243  -0.1064 
#>  3 GEN   G2    2.744  0.1390   0.1988   0.7331  -0.4735  -0.04816 -0.2841 
#>  4 GEN   G3    2.955  0.04340 -0.1028  -0.2284  -0.1769  -0.1270  -0.1400 
#>  5 GEN   G4    2.642 -0.3251   0.4782   0.09073 -0.1417  -0.1924   0.3550 
#>  6 GEN   G5    2.537 -0.3260   0.2461  -0.2452  -0.1794   0.4662   0.03315
#>  7 GEN   G6    2.534 -0.09836  0.2429  -0.5607  -0.2377   0.05094 -0.1011 
#>  8 GEN   G7    2.741  0.2849   0.5871   0.2068   0.7085   0.2315  -0.08406
#>  9 GEN   G8    3.004  0.4995  -0.1916  -0.3191   0.1676  -0.3261  -0.2886 
#> 10 GEN   G9    2.510  0.4668  -0.8427   0.1217  -0.06385  0.3819   0.1889 
#> # … with 14 more rows, and 13 more variables: PC7 <dbl>, PC8 <dbl>, PC9 <dbl>,
#> #   WAAS <dbl>, PctResp <dbl>, PctWAAS <dbl>, wRes <dbl>, wWAAS <dbl>,
#> #   OrResp <dbl>, OrWAAS <dbl>, OrPC1 <dbl>, WAASY <dbl>, OrWAASY <dbl>
#> ---------------------------------------------------------------------------
#> Genotype-environment interaction effects
#> ---------------------------------------------------------------------------
#>           E1      E10      E11      E12      E13       E14       E2       E3
#> G1  -0.08433  0.20299  0.05797 -0.19561  0.15919 -0.178034 -0.06870  0.08657
#> G10 -0.34359 -0.43594 -0.26614 -0.38336 -0.87594  0.280297  0.16890  0.25302
#> G2   0.31116  0.05194  0.05255  0.31492  0.04877 -0.425258 -0.01881  0.43443
#> G3   0.08680 -0.11959 -0.08164 -0.12526  0.27841 -0.003381  0.14722 -0.21310
#> G4   0.10021  0.02447  0.03406 -0.04885 -0.24159  0.111726  0.04245 -0.17767
#> G5  -0.19553  0.10152  0.09430  0.21738 -0.20463  0.139260  0.09707 -0.18610
#> G6  -0.07967  0.17315  0.27261 -0.08263  0.14225  0.157130  0.25143 -0.48946
#> G7   0.18638  0.20002 -0.07060  0.27645  0.20754  0.087732 -0.63395 -0.02967
#> G8   0.04928  0.07026 -0.01423  0.06209  0.28095 -0.119465 -0.06456 -0.28373
#> G9  -0.03071 -0.26883 -0.07888 -0.03513  0.20505 -0.050007  0.07895  0.60572
#>          E4       E5       E6       E7       E8       E9
#> G1  -0.1104  0.33060  0.21644 -0.02045 -0.19388 -0.20237
#> G10  0.7987 -0.34181  0.02468  0.45775  0.36696  0.29642
#> G2  -0.0296 -0.15297 -0.19179 -0.07117 -0.56098  0.23683
#> G3   0.1776 -0.06495  0.04040 -0.11145  0.03294 -0.04404
#> G4  -0.3408 -0.09557  0.07030  0.02432 -0.20346  0.70039
#> G5  -0.1593 -0.30460 -0.09300 -0.19523  0.30885  0.37996
#> G6  -0.1316 -0.20136 -0.18745 -0.09090  0.14322  0.12328
#> G7  -0.7230  0.07075 -0.06398  0.49525 -0.01966  0.01673
#> G8   0.1331  0.57220 -0.08449 -0.05651  0.01308 -0.55800
#> G9   0.3851  0.18772  0.26887 -0.43160  0.11293 -0.94922
#> ---------------------------------------------------------------------------
#> Proportion of the variance explained
#> ---------------------------------------------------------------------------
#> [1] 34.4308 31.7875 12.9380  9.8457  4.6331  2.9861  1.8152  1.1605  0.4031
#> ---------------------------------------------------------------------------
#> Cumulative proportion of the variance explained
#> ---------------------------------------------------------------------------
#> [1]  34.43  66.22  79.16  89.00  93.64  96.62  98.44  99.60 100.00
#> 
#> 
#> 
#> Variable HM 
#> ---------------------------------------------------------------------------
#> Weighted average of the absolute scores
#> ---------------------------------------------------------------------------
#> # A tibble: 24 × 22
#>    type  Code      Y      PC1      PC2       PC3       PC4      PC5       PC6
#>    <chr> <chr> <dbl>    <dbl>    <dbl>     <dbl>     <dbl>    <dbl>     <dbl>
#>  1 GEN   G1    47.08  0.2800   0.4635   0.1740   -1.369    -1.135    0.03658 
#>  2 GEN   G10   48.51 -1.779    1.866   -0.006219  0.9219    0.1096  -0.009745
#>  3 GEN   G2    46.66  1.563    0.5518  -0.9357    0.4913    0.2843   1.184   
#>  4 GEN   G3    47.60  0.3417  -0.2012  -0.8001    0.3753   -0.4979  -1.294   
#>  5 GEN   G4    48.03 -0.2020  -1.841    0.2801    0.005954  0.8201   0.2734  
#>  6 GEN   G5    49.30  1.580    1.030    1.078    -0.2789    1.005   -0.7368  
#>  7 GEN   G6    48.73  0.5474  -0.2453   0.5324    0.4603   -1.008    0.5861  
#>  8 GEN   G7    47.97 -1.218   -0.4680   1.254    -0.05482  -0.03429  0.3366  
#>  9 GEN   G8    49.10 -0.04176 -1.241   -0.4105    0.6394   -0.1785  -0.5149  
#> 10 GEN   G9    47.90 -1.072    0.08563 -1.166    -1.191     0.6351   0.1393  
#> # … with 14 more rows, and 13 more variables: PC7 <dbl>, PC8 <dbl>, PC9 <dbl>,
#> #   WAAS <dbl>, PctResp <dbl>, PctWAAS <dbl>, wRes <dbl>, wWAAS <dbl>,
#> #   OrResp <dbl>, OrWAAS <dbl>, OrPC1 <dbl>, WAASY <dbl>, OrWAASY <dbl>
#> ---------------------------------------------------------------------------
#> Genotype-environment interaction effects
#> ---------------------------------------------------------------------------
#>          E1     E10     E11     E12      E13      E14      E2      E3       E4
#> G1   0.1169  2.0419  0.8102  1.3285 -1.15148  0.71019 -0.5385 -1.2248 -1.32481
#> G10 -0.9231 -3.0515 -0.6165  0.4685  2.17186  0.78352  0.6049  2.3485  1.58186
#> G2  -0.6598  3.4619 -0.1031 -3.5015 -2.79814 -0.25314  0.7649 -0.1381 -1.57148
#> G3  -1.0472  0.5178 -0.3805  1.5545  0.07448 -0.33052 -1.3192 -1.4155  0.15114
#> G4   0.9314 -2.5770 -0.1420  0.1264  0.01305  0.04138 -0.2940  0.4897  0.05638
#> G5   1.2557  5.4907 -3.5077 -1.6727 -0.10267 -1.00767  1.5537 -0.1093  0.45733
#> G6   0.1885  1.3902  1.4919  0.9769 -2.03648 -1.82481  1.5099  0.1235  0.69019
#> G7   0.1538 -3.1779  0.7738  0.9421  1.46210  3.15710  1.2284  0.8888 -0.21124
#> G8  -0.4658 -1.6474  1.1209  0.0559  1.62590 -1.41243  0.3989 -2.2474 -0.34743
#> G9   0.4497 -2.4486  0.5530 -0.2786  0.74138  0.13638 -3.9090  1.2847  0.51805
#>            E5       E6      E7       E8      E9
#> G1  -0.838810 -0.71481 -0.4865 -1.06981  2.3419
#> G10  2.551190 -5.09148  1.0869 -3.82981  1.9152
#> G2   2.981190  0.75519  0.6002  0.70019 -0.2381
#> G3   2.453810  1.29448 -1.0105  0.63948 -1.1822
#> G4  -2.924286  3.43305  0.4780  2.64471 -2.2770
#> G5  -0.006667 -0.39933 -1.7043 -0.70433  0.4573
#> G6  -1.073810 -0.03314  0.3952 -0.15481 -1.6431
#> G7  -2.375238 -0.55124 -1.2562 -0.48957 -0.5446
#> G8  -0.644762  1.84590  0.8242  2.24090 -1.3474
#> G9  -0.122619 -0.53862  1.0730  0.02305  2.5180
#> ---------------------------------------------------------------------------
#> Proportion of the variance explained
#> ---------------------------------------------------------------------------
#> [1] 34.6249 29.0200 10.3807  7.4461  6.1881  5.3668  4.2421  2.4215  0.3097
#> ---------------------------------------------------------------------------
#> Cumulative proportion of the variance explained
#> ---------------------------------------------------------------------------
#> [1]  34.62  63.64  74.03  81.47  87.66  93.03  97.27  99.69 100.00
#> 
#> 
#> 
# }