Last updated: 2023-08-03

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f <- readRDS("snake/data/zigure/lassoF.Rds")
m <- readRDS("snake/data/zigure/lassoM.Rds")

data <- f

gg[[1]] <- ggplot(data, aes(x=nfolds, y=cor, fill=relax)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[2]] <- ggplot(data, aes(x=nfolds, y=time, fill=relax)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[3]] <- ggplot(data, aes(x=dfmax, y=cor)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[4]] <- ggplot(data, aes(x=dfmax, y=time)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

data <- m

gg[[5]] <- ggplot(data, aes(x=nfolds, y=cor, fill=relax)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[6]] <- ggplot(data, aes(x=nfolds, y=time, fill=relax)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[7]] <- ggplot(data, aes(x=dfmax, y=cor)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

gg[[8]] <- ggplot(data, aes(x=dfmax, y=time)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

Female Fold number vs. Correlation and Time

  • relax decreases correlation while increasing runtime
plot_grid(gg[[1]],gg[[2]], ncol=2)

Version Author Date
29ae1fb nklimko 2023-08-03

dfMax

  • No effect on correlation or runtime
plot_grid(gg[[3]],gg[[4]], ncol=2)

Version Author Date
29ae1fb nklimko 2023-08-03

Male Fold number vs. Correlation and Time

  • relax decreases correlation while increasing runtime
plot_grid(gg[[5]],gg[[6]], ncol=2)

Version Author Date
29ae1fb nklimko 2023-08-03

dfMax

  • No effect on correlation or runtime
plot_grid(gg[[7]],gg[[8]], ncol=2)

Version Author Date
29ae1fb nklimko 2023-08-03

Lasso Data

lassoFinal <- readRDS("snake/data/zigure/lassoFinal.Rds")

print(lassoFinal)
    method nfolds dfmax relax sex       cor     time
 1:  lasso      3  1000     0   f 0.4114329  1.58266
 2:  lasso      3  3000     0   f 0.4114329  1.58624
 3:  lasso      3  6000     0   f 0.4114329  1.59594
 4:  lasso      3 10000     0   f 0.4114329  1.61216
 5:  lasso      3  1000     1   f 0.3949298  5.31824
 6:  lasso      3  3000     1   f 0.3949298  5.33932
 7:  lasso      3  6000     1   f 0.3949298  5.32556
 8:  lasso      3 10000     1   f 0.3949298  5.29430
 9:  lasso      6  1000     0   f 0.4019169  2.86242
10:  lasso      6  3000     0   f 0.4019169  2.89012
11:  lasso      6  6000     0   f 0.4019169  2.88164
12:  lasso      6 10000     0   f 0.4019169  2.84318
13:  lasso      6  1000     1   f 0.3765922 10.39362
14:  lasso      6  3000     1   f 0.3765922 10.40682
15:  lasso      6  6000     1   f 0.3765922 10.33502
16:  lasso      6 10000     1   f 0.3765922 10.35764
17:  lasso      9  1000     0   f 0.3971659  3.40344
18:  lasso      9  3000     0   f 0.3971659  3.39002
19:  lasso      9  6000     0   f 0.3971659  3.43246
20:  lasso      9 10000     0   f 0.3971659  3.45136
21:  lasso      9  1000     1   f 0.3655954 15.47176
22:  lasso      9  3000     1   f 0.3655954 15.72020
23:  lasso      9  6000     1   f 0.3655954 15.48900
24:  lasso      9 10000     1   f 0.3655954 15.45090
25:  lasso     12  1000     0   f 0.3902660  4.03224
26:  lasso     12  3000     0   f 0.3902660  3.99780
27:  lasso     12  6000     0   f 0.3902660  3.97008
28:  lasso     12 10000     0   f 0.3902660  3.97230
29:  lasso     12  1000     1   f 0.3592104 21.19168
30:  lasso     12  3000     1   f 0.3592104 21.14294
31:  lasso     12  6000     1   f 0.3592104 21.10554
32:  lasso     12 10000     1   f 0.3592104 21.12618
33:  lasso      3  1000     0   m 0.3554582  1.77392
34:  lasso      3  3000     0   m 0.3554582  1.76936
35:  lasso      3  6000     0   m 0.3554582  1.80626
36:  lasso      3 10000     0   m 0.3554582  1.78518
37:  lasso      3  1000     1   m 0.3551354  5.81288
38:  lasso      3  3000     1   m 0.3551354  5.80408
39:  lasso      3  6000     1   m 0.3551354  5.79330
40:  lasso      3 10000     1   m 0.3551354  5.79640
41:  lasso      6  1000     0   m 0.3445264  3.36236
42:  lasso      6  3000     0   m 0.3445264  3.37832
43:  lasso      6  6000     0   m 0.3445264  3.34990
44:  lasso      6 10000     0   m 0.3445264  3.37334
45:  lasso      6  1000     1   m 0.3367717 11.48820
46:  lasso      6  3000     1   m 0.3367717 11.57574
47:  lasso      6  6000     1   m 0.3367717 11.50660
48:  lasso      6 10000     1   m 0.3367717 11.55544
49:  lasso      9  1000     0   m 0.3324251  4.03074
50:  lasso      9  3000     0   m 0.3324251  4.12538
51:  lasso      9  6000     0   m 0.3324251  4.04412
52:  lasso      9 10000     0   m 0.3324251  4.05018
53:  lasso      9  1000     1   m 0.3023836 17.68740
54:  lasso      9  3000     1   m 0.3023836 17.64944
55:  lasso      9  6000     1   m 0.3023836 17.70626
56:  lasso      9 10000     1   m 0.3023836 17.77086
57:  lasso     12  1000     0   m 0.3131776  4.72010
58:  lasso     12  3000     0   m 0.3131776  4.69954
59:  lasso     12  6000     0   m 0.3131776  4.76550
60:  lasso     12 10000     0   m 0.3131776  4.78924
61:  lasso     12  1000     1   m 0.2922959 23.88572
62:  lasso     12  3000     1   m 0.2922959 23.85232
63:  lasso     12  6000     1   m 0.2922959 23.82610
64:  lasso     12 10000     1   m 0.2922959 23.89548
    method nfolds dfmax relax sex       cor     time
bayesFinal <- readRDS("snake/data/zigure/bayesFinal.Rds")

data <- bayesFinal

gg[[9]] <- ggplot(data, aes(x=R2, y=cor, fill=sex)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 


gg[[10]] <- ggplot(data, aes(x=R2, y=time, fill=sex)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method=lm) 

BayesC

plot_grid(gg[[9]],gg[[10]], ncol=2)

Version Author Date
cfd86f2 nklimko 2023-08-03
print(bayesFinal)
   method  R2 sex       cor     time
1: bayesC 0.1   f 0.2656316 437.8930
2: bayesC 0.5   f 0.3115005 430.0788
3: bayesC 0.9   f 0.3180012 439.2995
4: bayesC 0.1   m 0.3944273 496.1592
5: bayesC 0.5   m 0.4232572 515.0008
6: bayesC 0.9   m 0.4312989 529.1078

Random Forest Female/Male

#0.364, 0.382 f m 

data <- readRDS("snake/data/zigure/rf.Rds")

title <- "Correlation"
tagChar <- '.'


gg[[11]] <- ggplot(data, aes(x=sex, y=cor, fill=sex)) +
           geom_violin(color = NA, width = 0.65) +
           geom_boxplot(color='#440154FF', width = 0.15) +
           theme_minimal() +
           stat_summary(fun=mean, color='#440154FF', geom='point', 
                        shape=18, size=3, show.legend=FALSE) +
           labs(x=NULL,y=title,tag=tagChar) +
           theme(legend.position='none',
                 axis.text.x = element_text(angle = -45, size=10),
                 text=element_text(size=10),
                 plot.tag = element_text(size=15)) +
           scale_fill_viridis(begin = 0.4, end=0.9,discrete=TRUE)


plot_grid(gg[[11]], ncol=1)

Version Author Date
af8605c nklimko 2023-08-03

Data Driven Female/Male

#0.364, 0.382 f m 

data <- readRDS("snake/data/zigure/dd.Rds")

title <- "Correlation"
tagChar <- '.'


gg[[12]] <- ggplot(data, aes(x=sex, y=cor, fill=sex)) +
           geom_violin(color = NA, width = 0.65) +
           geom_boxplot(color='#440154FF', width = 0.15) +
           theme_minimal() +
           stat_summary(fun=mean, color='#440154FF', geom='point', 
                        shape=18, size=3, show.legend=FALSE) +
           labs(x=NULL,y=title,tag=tagChar) +
           theme(legend.position='none',
                 axis.text.x = element_text(angle = -45, size=10),
                 text=element_text(size=10),
                 plot.tag = element_text(size=15)) +
           scale_fill_viridis(begin = 0.4, end=0.9,discrete=TRUE)


plot_grid(gg[[12]], ncol=1)

Version Author Date
6eac9d1 nklimko 2023-08-03

sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Rocky Linux 8.5 (Green Obsidian)

Matrix products: default
BLAS/LAPACK: /opt/ohpc/pub/libs/gnu9/openblas/0.3.7/lib/libopenblasp-r0.3.7.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggcorrplot_0.1.4  lubridate_1.9.2   forcats_1.0.0     stringr_1.5.0    
 [5] purrr_1.0.1       readr_2.1.4       tidyr_1.3.0       tibble_3.2.1     
 [9] tidyverse_2.0.0   scales_1.2.1      viridis_0.6.2     viridisLite_0.4.2
[13] qqman_0.1.8       cowplot_1.1.1     ggplot2_3.4.2     data.table_1.14.8
[17] dplyr_1.1.2       workflowr_1.7.0  

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.11       lattice_0.21-8    getPass_0.2-2     ps_1.7.5         
 [5] rprojroot_2.0.3   digest_0.6.33     utf8_1.2.3        R6_2.5.1         
 [9] evaluate_0.21     httr_1.4.5        highr_0.10        pillar_1.9.0     
[13] rlang_1.1.1       rstudioapi_0.15.0 whisker_0.4.1     callr_3.7.3      
[17] jquerylib_0.1.4   Matrix_1.6-0      rmarkdown_2.23    labeling_0.4.2   
[21] splines_4.1.2     munsell_0.5.0     compiler_4.1.2    httpuv_1.6.9     
[25] xfun_0.39         pkgconfig_2.0.3   mgcv_1.9-0        htmltools_0.5.5  
[29] tidyselect_1.2.0  gridExtra_2.3     fansi_1.0.4       calibrate_1.7.7  
[33] tzdb_0.3.0        withr_2.5.0       later_1.3.1       MASS_7.3-60      
[37] grid_4.1.2        nlme_3.1-162      jsonlite_1.8.7    gtable_0.3.3     
[41] lifecycle_1.0.3   git2r_0.31.0      magrittr_2.0.3    cli_3.6.1        
[45] stringi_1.7.12    cachem_1.0.8      farver_2.1.1      fs_1.6.3         
[49] promises_1.2.0.1  bslib_0.5.0       generics_0.1.3    vctrs_0.6.2      
[53] tools_4.1.2       glue_1.6.2        hms_1.1.3         processx_3.8.2   
[57] fastmap_1.1.1     yaml_2.3.7        timechange_0.2.0  colorspace_2.1-0 
[61] knitr_1.43        sass_0.4.7