Mercurial > repos > eschen42 > w4mcorcov

comparison w4mcorcov_calc.R @ 4:8bba31f628da draft

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planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 8f2dc8b66666340275cd8967e09c504720528462
author eschen42
date Sun, 04 Mar 2018 14:51:42 -0500
parents 5aaab36bc523
children 50f60f94c034
comparison
equal deleted inserted replaced
3:5aaab36bc523 4:8bba31f628da
7 #### OPLS-DA 7 #### OPLS-DA
8 algoC <- "nipals" 8 algoC <- "nipals"
9 9
10 do_detail_plot <- function(x_dataMatrix, x_predictor, x_is_match, x_algorithm, x_prefix, x_show_labels, x_show_loado_labels, x_progress = print, x_env, x_crossval_i) { 10 do_detail_plot <- function(x_dataMatrix, x_predictor, x_is_match, x_algorithm, x_prefix, x_show_labels, x_show_loado_labels, x_progress = print, x_env, x_crossval_i) {
11 off <- function(x) if (x_show_labels == "0") 0 else x 11 off <- function(x) if (x_show_labels == "0") 0 else x
12 if (x_is_match && ncol(x_dataMatrix) > 0 && length(unique(x_predictor))> 1) { 12 if ( x_is_match && ncol(x_dataMatrix) > 0 && length(unique(x_predictor))> 1 && x_crossval_i < nrow(x_dataMatrix) ) {
13 my_oplsda <- opls( 13 my_oplsda <- opls(
14 x = x_dataMatrix 14 x = x_dataMatrix
15 , y = x_predictor 15 , y = x_predictor
16 , algoC = x_algorithm 16 , algoC = x_algorithm
17 , predI = 1 17 , predI = 1
119 my_typevc <- c("(dummy)","overview","(dummy)") 119 my_typevc <- c("(dummy)","overview","(dummy)")
120 } 120 }
121 for (my_type in my_typevc) { 121 for (my_type in my_typevc) {
122 if (my_type %in% typeVc) { 122 if (my_type %in% typeVc) {
123 # print(sprintf("plotting type %s", my_type)) 123 # print(sprintf("plotting type %s", my_type))
124 plot( 124 tryCatch({
125 x = my_oplsda 125 plot(
126 , typeVc = my_type 126 x = my_oplsda
127 , parCexN = 0.4 127 , typeVc = my_type
128 , parDevNewL = FALSE 128 , parCexN = 0.4
129 , parLayL = TRUE 129 , parDevNewL = FALSE
130 , parEllipsesL = TRUE 130 , parLayL = TRUE
131 , parEllipsesL = TRUE
131 ) 132 )
133 }, error = function(e) {
134 x_progress(sprintf("factor level %s or %s may have only one sample", fctr_lvl_1, fctr_lvl_2))
135 })
132 } else { 136 } else {
133 # print("plotting dummy graph") 137 # print("plotting dummy graph")
134 plot(x=1, y=1, xaxt="n", yaxt="n", xlab="", ylab="", type="n") 138 plot(x=1, y=1, xaxt="n", yaxt="n", xlab="", ylab="", type="n")
135 text(x=1, y=1, labels="no orthogonal projection is possible") 139 text(x=1, y=1, labels="no orthogonal projection is possible")
136 } 140 }
304 , x_algorithm = algoC 308 , x_algorithm = algoC
305 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features" 309 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features"
306 , x_show_labels = labelFeatures 310 , x_show_labels = labelFeatures
307 , x_show_loado_labels = labelOrthoFeatures 311 , x_show_loado_labels = labelOrthoFeatures
308 , x_progress = progress_action 312 , x_progress = progress_action
309 , x_crossval_i = min(7, length(chosen_samples)) 313 , x_crossval_i = min(7, length(chosen_samples))
310 , x_env = calc_env 314 , x_env = calc_env
311 ) 315 )
312 if ( is.null(my_cor_cov) ) { 316 if ( is.null(my_cor_cov) ) {
313 progress_action("NOTHING TO PLOT.") 317 progress_action("NOTHING TO PLOT.")
314 } else { 318 } else {
361 , x_algorithm = algoC 365 , x_algorithm = algoC
362 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features" 366 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features"
363 , x_show_labels = labelFeatures 367 , x_show_labels = labelFeatures
364 , x_show_loado_labels = labelOrthoFeatures 368 , x_show_loado_labels = labelOrthoFeatures
365 , x_progress = progress_action 369 , x_progress = progress_action
366 , x_crossval_i = min(7, length(chosen_samples)) 370 , x_crossval_i = min(7, length(chosen_samples))
367 , x_env = calc_env 371 , x_env = calc_env
368 ) 372 )
369 if ( is.null(my_cor_cov) ) { 373 if ( is.null(my_cor_cov) ) {
370 progress_action("NOTHING TO PLOT.") 374 progress_action("NOTHING TO PLOT.")
371 } else { 375 } else {
415 , x_algorithm = algoC 419 , x_algorithm = algoC
416 , x_prefix = "Features" 420 , x_prefix = "Features"
417 , x_show_labels = labelFeatures 421 , x_show_labels = labelFeatures
418 , x_show_loado_labels = labelOrthoFeatures 422 , x_show_loado_labels = labelOrthoFeatures
419 , x_progress = progress_action 423 , x_progress = progress_action
420 , x_crossval_i = min(7, length(chosen_samples)) 424 , x_crossval_i = min(7, length(chosen_samples))
421 , x_env = calc_env 425 , x_env = calc_env
422 ) 426 )
423 if ( is.null(my_cor_cov) ) { 427 if ( is.null(my_cor_cov) ) {
424 progress_action("NOTHING TO PLOT") 428 progress_action("NOTHING TO PLOT")
425 } else { 429 } else {
461 , x_algorithm = algoC 465 , x_algorithm = algoC
462 , x_prefix = "Features" 466 , x_prefix = "Features"
463 , x_show_labels = labelFeatures 467 , x_show_labels = labelFeatures
464 , x_show_loado_labels = labelOrthoFeatures 468 , x_show_loado_labels = labelOrthoFeatures
465 , x_progress = progress_action 469 , x_progress = progress_action
466 , x_crossval_i = min(7, length(chosen_samples)) 470 , x_crossval_i = min(7, length(chosen_samples))
467 , x_env = calc_env 471 , x_env = calc_env
468 ) 472 )
469 if ( is.null(my_cor_cov) ) { 473 if ( is.null(my_cor_cov) ) {
470 progress_action("NOTHING TO PLOT") 474 progress_action("NOTHING TO PLOT")
471 } else { 475 } else {