-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathKINOMO-class.R
1278 lines (1022 loc) · 34.6 KB
/
KINOMO-class.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
#library(R.utils)
#' @include utils.R
#' @include versions.R
#' @include algorithmic.R
#' @include aheatmap.R
NULL
#' @rdname advanced
#' @name advanced-KINOMO
NULL
# declare old S3 class 'proc_time' to use it as a slot for class KINOMO
setOldClass('proc_time', prototype=numeric())
################################
# Class: KINOMO
################################
#'
setClass('KINOMO'
, representation(
misc = 'list' # misceleneaous data used during fitting
)
, contains = 'VIRTUAL')
#' @export
setGeneric('fitted', package='stats')
setMethod('fitted', signature(object='KINOMO'),
function(object, ...){
stop("KINOMO::fitted is a pure virtual method of interface 'KINOMO'. It should be overloaded in class '", class(object),"'.")
}
)
#'
setGeneric('basis', function(object, ...) standardGeneric('basis') )
#' Default method returns the value of S3 slot or attribute \code{'basis'}.
#' It returns \code{NULL} if none of these are set.
#'
#' Arguments \code{...} are not used by this method.
setMethod('basis', signature(object='ANY'),
function(object, ...){
if( is.list(object) && 'basis' %in% names(object) ) object[['basis']]
else attr(object, 'basis')
}
)
#' @param all a logical that indicates whether the complete matrix factor
#' should be returned (\code{TRUE}) or only the non-fixed part.
#' This is relevant only for formula-based KINOMO models that include fixed basis or
#' coefficient terms.
#'
setMethod('basis', signature(object='KINOMO'),
function(object, all=TRUE, ...){
if( all || !length(i <- ibterms(object)) ){
# return all coefficients
.basis(object, ...)
} else {
# remove fixed basis
.basis(object, ...)[, -i]
}
}
)
#' @export
setGeneric('.basis', function(object, ...) standardGeneric('.basis') )
setMethod('.basis', signature(object='KINOMO'),
function(object, ...){
stop("KINOMO::.basis is a pure virtual method of interface 'KINOMO'. It should be overloaded in class '", class(object),"'.")
}
)
#' @export
#' @rdname basis-coef-methods
setGeneric('basis<-', function(object, ..., value) standardGeneric('basis<-') )
#'
setReplaceMethod('basis', signature(object='KINOMO', value='ANY'),
function(object, use.dimnames = TRUE, ..., value){
# error if passed extra arguments
if( length(xargs<- list(...)) ){
stop("basis<-,KINOMO - Unused arguments: ", str_out(xargs, Inf, use.names = TRUE))
}
# backup old dimnames to reapply them on exit
if( !use.dimnames ) odn <- dimnames(object)
nb_old <- nbasis(object)
# only set non-fixed terms
if( !nbterms(object) ) .basis(object) <- value
else{
i <- ibasis(object)
.basis(object)[,i] <- value[, i]
}
# adapt coef if empty
if( !hasCoef(object) ){
x <- basis(object)
.coef(object) <- rbind(coef(object)[1:min(nb_old, ncol(x)), , drop = FALSE], matrix(NA, max(ncol(x)-nb_old, 0), 0))
# .coef(object) <- coef(object)[1:ncol(x), , drop = FALSE]
}
# check object validity
validObject(object)
# update other factor if necessary
if( use.dimnames ) basisnames(object) <- colnames(basis(object))
else if( !length(odn) ) dimnames(object) <- NULL
else dimnames(object) <- mapply(head, odn, dim(object), SIMPLIFY = FALSE)
object
}
)
#' @param value replacement value
#' @rdname basis-coef-methods
#' @export
setGeneric('.basis<-', function(object, value) standardGeneric('.basis<-') )
setReplaceMethod('.basis', signature(object='KINOMO', value='matrix'),
function(object, value){
stop("KINOMO::.basis<- is a pure virtual method of interface 'KINOMO'. It should be overloaded in class '", class(object),"'.")
}
)
#' @export
setGeneric('loadings', package='stats')
#'
#' @rdname basis-coef-methods
setMethod('loadings', 'KINOMO', function(x) basis(x) )
#' @export
setGeneric('coef', package='stats')
setMethod('coef', 'KINOMO',
function(object, all=TRUE, ...){
if( all || !length(i <- icterms(object)) ){
# return all coefficients
.coef(object, ...)
} else {
# remove fixed coefficients
.coef(object, ...)[-i, ]
}
}
)
#' @export
setGeneric('.coef', function(object, ...) standardGeneric('.coef'))
setMethod('.coef', signature(object='KINOMO'),
function(object, ...){
stop("KINOMO::.coef is a pure virtual method of interface 'KINOMO'. It should be overloaded in class '", class(object),"'.")
}
)
#' @export
#' @rdname basis-coef-methods
setGeneric('coef<-', function(object, ..., value) standardGeneric('coef<-') )
#' Default methods that calls \code{.coef<-} and check the validity of the
#' updated object.
setReplaceMethod('coef', signature(object='KINOMO', value='ANY'),
function(object, use.dimnames = TRUE, ..., value){
# error if passed extra arguments
if( length(xargs<- list(...)) ){
stop("coef<-,KINOMO - Unused arguments: ", str_out(xargs, Inf, use.names = TRUE))
}
# backup old dimnames to reapply them on exit
if( !use.dimnames ) odn <- dimnames(object)
nb_old <- nbasis(object)
# only set non-fixed terms
if( !ncterms(object) ) .coef(object) <- value
else{
i <- icoef(object)
.coef(object)[i, ] <- value[i, ]
}
# adapt basis if empty before validation
if( !hasBasis(object) ){
x <- coef(object)
.basis(object) <- cbind(basis(object)[, 1:min(nb_old, nrow(x)), drop = FALSE], matrix(NA, 0, max(nrow(x)-nb_old, 0)))
}
# check object validity
validObject(object)
# update other factor if necessary
if( use.dimnames ) basisnames(object) <- rownames(coef(object))
else if( !length(odn) ) dimnames(object) <- NULL
else dimnames(object) <- mapply(head, odn, dim(object), SIMPLIFY = FALSE)
object
}
)
#' @export
#' @rdname basis-coef-methods
setGeneric('.coef<-', function(object, value) standardGeneric('.coef<-') )
setReplaceMethod('.coef', signature(object='KINOMO', value='matrix'),
function(object, value){
stop("KINOMO::.coef<- is a pure virtual method of interface 'KINOMO'. It should be overloaded in class '", class(object),"'.")
}
)
#' @rdname basis-coef-methods
setGeneric('coefficients', package='stats')
#' Alias to \code{coef,KINOMO}, therefore also pure virtual.
setMethod('coefficients', signature(object='KINOMO'), selectMethod('coef', 'KINOMO'))
#'
setGeneric('scoef', function(object, ...) standardGeneric('scoef') )
setMethod('scoef', 'KINOMO',
function(object, scale=1){
sweep(coef(object), 2L, colSums(coef(object)) / scale, '/')
}
)
setMethod('scoef', 'matrix',
function(object, scale=1){
sweep(object, 2L, colSums(object) / scale, '/')
}
)
unit.test(scoef, {
x <- rKINOMO(3, 10, 5)
checkIdentical(colSums(scoef(x)), rep(1, nbasis(x))
, "Default call: columns are scaled to sum-up to one")
checkIdentical(colSums(scoef(x, 100)), rep(1, nbasis(x))
, "Scale=10: columns are scaled to sum-up to 10")
})
#'
scale.KINOMO <- function(x, center=c('basis', 'coef'), scale=1){
# determine base value
if( missing(center) ) center <- match.arg(center)
base <- center
delta <-
if( is.character(base) ){
base <- match.arg(center)
if( base == 'basis' ) colSums(basis(x))
else{
scale <- 1/scale
1 / rowSums(coef(x))
}
}else if( is.numeric(base) ) base
else stop("Invalid base value: should be a numeric or one of "
, str_out(c('none', 'basis', 'coef')))
# scale
D <- scale/delta
# W <- W * D
basis(x) <- sweep(basis(x), 2L, D, '*')
# H <- D^-1 * H
coef(x) <- sweep(coef(x), 1L, D, '/')
x
}
unit.test("scale", {
r <- 3
x <- rKINOMO(r, 10, 5)
.lcheck <- function(msg, rx, ref, target){
.msg <- function(...) paste(msg, ':', ...)
checkTrue(!identical(basis(x), basis(rx)), .msg("changes basis matrix"))
checkTrue(!identical(coef(x), coef(rx)), .msg("changes coef matrix"))
checkEqualsNumeric(fitted(x), fitted(rx), .msg("fitted target is identical"))
brx <- colSums(basis(rx))
crx <- rowSums(coef(rx))
if( target == 1 ){
checkEquals(brx, ref, .msg("correctly scales basis components"))
checkTrue(!all(crx==ref), .msg("does not force scale on coefficient matrix"))
}else{
checkTrue(!all(brx==ref), .msg("does not force scale on basis matrix"))
checkEquals(crx, ref
, .msg("correctly scales rows of coef matrix"))
}
}
.check <- function(msg, ref, ...){
.lcheck(str_c(msg, " + argument center='basis'")
, scale(x, center='basis', ...), ref, 1)
.lcheck(str_c(msg, " + argument center='coef'")
, scale(x, center='coef', ...), ref, 2)
}
.lcheck("Default call", scale(x), rep(1, r), 1)
.check("Missing argument scale", rep(1, r))
.check("Argument scale=10", rep(10, r), scale=10)
s <- runif(r)
.check("Argument scale=numeric", s, scale=s)
})
#' @family KINOMO-interface
setGeneric('rKINOMO', function(x, target, ...) standardGeneric('rKINOMO') )
# Define the loading namespace
.PKG.NAMESPACE <- packageEnv()
#'
is.KINOMO <- function(x){
# load definition for base class KINOMO
clref <- getClass('KINOMO', .Force=TRUE, where=.PKG.NAMESPACE)
is(x, clref)
}
unit.test(is.KINOMO,{
checkTrue(!is.KINOMO(1:4), "on vector: FALSE")
checkTrue(!is.KINOMO(list(1:4)), "on list: FALSE")
checkTrue(is.KINOMO('KINOMO'), "on 'KINOMO': TRUE")
checkTrue(is.KINOMO('KINOMOstd'), "on 'KINOMOstd': TRUE")
checkTrue( is.KINOMO( KINOMOModel(3) ), "on empty model: TRUE")
checkTrue( is.KINOMO( rKINOMO(3, 20, 10) ), "on random model: TRUE")
checkTrue( is.KINOMO( KINOMO(rmatrix(20,10), 3) ), "on KINOMOfit object: TRUE")
})
isKINOMOclass <- function(x){
if( is.character(x) ){ # test object is a class that extends KINOMO
# load definition for base class KINOMO
clref <- getClass('KINOMO', .Force=TRUE, where=.PKG.NAMESPACE)
cl <- getClass(x, .Force=TRUE, where=.PKG.NAMESPACE)
if( is.null(cl) )
cl <- getClass(x, .Force=TRUE)
extends(cl, clref)
}else
FALSE
}
################################
# Taken from Biobase
selectSome <- function (obj, maxToShow = 5)
{
len <- length(obj)
if (maxToShow < 3)
maxToShow <- 3
if (len > maxToShow) {
maxToShow <- maxToShow - 1
bot <- ceiling(maxToShow/2)
top <- len - (maxToShow - bot - 1)
nms <- obj[c(1:bot, top:len)]
c(as.character(nms[1:bot]), "...", as.character(nms[-c(1:bot)]))
}
else if (is.factor(obj))
as.character(obj)
else obj
}
.showFixedTerms <- function(x, ...){
s <-
sapply(x, function(t){
s <-
if( is.factor(t) ) selectSome(levels(t), ...)
else selectSome(t, ...)
s <- str_out(s, Inf, quote=FALSE)
if( is.factor(t) )
s <- str_c('<', s, ">")
s
})
paste(names(s), '=', s)
}
#' Show method for objects of class \code{KINOMO}
#' @export
setMethod('show', 'KINOMO',
function(object)
{
cat("<Object of class:", class(object), ">\n", sep='')
cat("features:", nrow(object), "\n")
cat("basis/rank:", nbasis(object), "\n")
cat("samples:", ncol(object), "\n")
# show fixed terms
if( (n <- ncterms(object)) ){
cat("fixed coef [", n, "]:\n"
, str_c(' ', .showFixedTerms(cterms(object), 4), collapse="\n")
, "\n", sep='')
}
if( (n <- nbterms(object)) ){
cat("fixed basis [", n, "]:\n"
, str_c(' ', .showFixedTerms(bterms(object), 4), collapse="\n")
, "\n", sep='')
}
# show the miscellaneous model parameters
if( length(object@misc) > 0L ){
cat("miscellaneous:", str_desc(object@misc, exdent=12L), ". (use 'misc(object)')\n")
}
}
)
#'
setMethod('nbasis', signature(x='ANY'),
function(x, ...)
{
if( !is.null(n <- ncol(basis(x, ...))) ) n
else if( is.list(x) && 'nbasis' %in% names(x) ) x[['nbasis']]
else attr(x, 'nbasis')
}
)
#' @export
setMethod('dim', signature(x='KINOMO'),
function(x){
c(nrow(basis(x)), ncol(coef(x)), nbasis(x))
}
)
#'
setGeneric('basisnames', function(x, ...) standardGeneric('basisnames') )
#' @rdname dimnames
setMethod('basisnames', signature(x='ANY'),
function(x)
{
colnames(basis(x))
}
)
#' @export
#' @rdname dimnames
setGeneric('basisnames<-', function(x, ..., value) standardGeneric('basisnames<-') )
#' @rdname dimnames
setReplaceMethod('basisnames', 'ANY',
function(x, ..., value)
{
rownames(.coef(x)) <- value
colnames(.basis(x)) <- value
x
}
)
#' @export
setMethod('dimnames', 'KINOMO',
function(x){
b <- dimnames(basis(x))
if( is.null(b) )
b <- list(NULL, NULL)
c <- dimnames(coef(x))
if( is.null(c) )
c <- list(NULL, NULL)
l <- c(b[1],c[2],b[2])
if( all(sapply(l, is.null)) ) NULL else l
}
)
#' @rdname dimnames
#' @export
setReplaceMethod('dimnames', 'KINOMO',
function(x, value){
if( !is.list(value) && !is.null(value) )
stop("KINOMO::dimnames - Invalid value: must be a list or NULL.")
if( length(value) == 0 )
value <- NULL
else if( length(value) == 1 )
value <- c(value, list(NULL, NULL))
else if( length(value) == 2 ) # if only the two first dimensions reset the third one
value <- c(value, list(NULL))
else if( length(value)!=3 ) # check length of value
stop("KINOMO::dimnames - invalid argument 'value' [a 2 or 3-length list is expected]")
# only set relevant dimensions
if( length(w <- which(dim(x) == 0)) ){
value[w] <- sapply(value[w], function(x) NULL, simplify=FALSE)
}
# set dimnames
dimnames(.basis(x)) <- value[c(1,3)]
dimnames(.coef(x)) <- value[c(3,2)]
# return updated model
x
}
)
#'
setMethod('[', 'KINOMO',
function (x, i, j, ..., drop = FALSE)
{
k <- NULL
mdrop <- missing(drop)
# compute number of arguments: x and drop are always passed
Nargs <- nargs() - !mdrop
single.arg <- FALSE
k.notmissing <- FALSE
if( !missing(i) && Nargs < 3L ){
k <- i
single.arg <- TRUE
}
else if( Nargs > 3L ){
dots <- list(...)
if( length(dots) != 1 )
warning("KINOMO::[ - using only the first extra subset index, the remaining ", length(dots)-1," are discarded.")
k <- dots[[1]]
k.notmissing <- TRUE
}
# no indice was provided => return the object unchanged
if ( missing(i) && missing(j) && !k.notmissing ) {
# check if there is other arguments
if (length(list(...)) != 0)
stop("KINOMO::[] method - please specify which features, samples or basis to subset. See class?KINOMO.")
# otherwise return the untouched object
return(x)
}
# subset the rows of the basis matrix
if ( !missing(i) && !single.arg )
.basis(x) <- basis(x)[i, , drop = FALSE]
# subset the columns of mixture coefficient matrix
if (!missing(j))
.coef(x) <- coef(x)[, j, drop = FALSE]
# subset the basis: columns of basis matrix and row of mixture coefficient matrix
if( single.arg || k.notmissing ){
.basis(x) <- basis(x)[, k, drop = FALSE]
# return basis only single arg and drop=TRUE
if( single.arg && ((mdrop && length(k) == 1L) || drop) ) return( drop(basis(x)) )
.coef(x) <- coef(x)[k, , drop = FALSE]
}
# if drop is TRUE and only one dimension is missing then return affected matrix
if( !single.arg && drop ){
if( missing(i) && !missing(j) )
return( drop(coef(x)) )
else if( missing(j) && !missing(i) )
return( drop(basis(x)) )
}
# return subset object
return(x)
}
)
#' @export
misc <- function(object, ...){
if( !isS4(object) && is.list(object) ) object[['misc']]
else attr(object, 'misc')
}
#' @export
setMethod('$', 'KINOMO',
function(x, name){
x@misc[[name, exact=TRUE]];
}
)
#' @export
setReplaceMethod('$', 'KINOMO',
function(x, name, value) {
x@misc[[name]] <- value
x
}
)
#' @importFrom utils .DollarNames
setGeneric('.DollarNames', package='utils')
#' @method .DollarNames KINOMO
#' @export
.DollarNames.KINOMO <- function(x, pattern = "") grep(pattern, names(misc(x)), value=TRUE)
#' Auto-completion for \code{\linkS4class{KINOMO}} objects
#' @rdname KINOMO-class
#' @export
setMethod('.DollarNames', 'KINOMO', .DollarNames.KINOMO)
is.empty.KINOMO <- function(x, ...){
nrow(x) == 0 && ncol(x) == 0
}
#' \code{hasBasis} tests whether an objects contains a basis matrix -- returned by
#' a suitable method \code{basis} -- with at least one row.
#'
#' @rdname types
#' @export
hasBasis <- function(x) nbasis(x) && nrow(basis(x)) != 0L
#' \code{hasBasis} tests whether an objects contains a coefficient matrix
#' -- returned by a suitable method \code{coef} -- with at least one column.
#'
#' @rdname types
#' @export
hasCoef <- function(x) nbasis(x) && ncol(coef(x)) != 0L
#' \code{is.partial.KINOMO} tests whether an KINOMO model object contains either an empty
#' basis or coefficient matrix.
#' It is a shorcut for \code{!hasCoef(x) || !hasBasis(x)}.
#'
#' @rdname types
#' @export
is.partial.KINOMO <- function(x) !hasCoef(x) || !hasBasis(x)
#'
setMethod('rmatrix', 'KINOMO',
function(x, ...){
a <- fitted(x)
a + rmatrix(a, ...)
}
)
unit.test('rmatrix,KINOMO',{
x <- KINOMOModel(3, 20, 5)
checTrue(is.matrix(y <- rmatrix(x)), "default call: no error")
checkIdentical(dim(y), dim(x)[1:2], "default call: correct dimension")
checkTrue( !any(is.na(basis(y))), 'default call: no NAs in basis anymore')
checkTrue( !any(is.na(coef(y))), 'default call: no NAs in coef anymore')
checkTrue( max( max(abs(basis(y)-basis(x))), max(abs(coef(y)-coef(x))) ) <= 1
, "default call: max difference is <= 1")
set.seed(123)
y <- rmatrix(x)
set.seed(123)
ref <- matrix(runif(nrow(x)*ncol(x)), nrow(x))
checkIdentical(ref, y - fitted(x), "default call: add uniform random noise to fitted matrix")
set.seed(123)
ref <- matrix(rnorm(nrow(x)*ncol(x)), nrow(x))
set.seed(123)
y <- rmatrix(x, rnorm)
checkIdentical(ref, y - fitted(x), "dist is taken into account: add normal random noise to fitted matrix")
set.seed(123)
y <- rmatrix(x, dist=rnorm)
checkIdentical(ref, y - fitted(x), "dist is taken into account: add normal random noise to fitted matrix")
set.seed(123)
checTrue(is.matrix(y <- rmatrix(x, max=10)), "call with arg max=10: no error")
checkTrue( max( max(abs(basis(y)-basis(x))), max(abs(coef(y)-coef(x))) ) <= 10
, "call with arg max=10: max difference is 10")
checkTrue( max( max(abs(basis(y)-basis(x))), max(abs(coef(y)-coef(x))) ) >= 5
, "call with arg max=10: max difference is >= 5")
})
###% Utility function used to sets default elements in a list if they are
###% not already set
###% The default values are given in argument ...
.set.list.defaults <- function(input.list, ...){
expand_list(input.list, ..., .exact=FALSE)
}
###% Partially match arguments for a given function
.match.call.args <- function(x, fun, in.fun=NULL, call=NULL){
stopifnot( is.character(fun) && length(fun) == 1 )
if( length(x) == 0 ) return(x)
x.ind <- charmatch(x, args <- formalArgs(getFunction(fun)))
sapply(seq(length(x)), function(i){
ind <- x.ind[i]
# the argument is not part of the call: keep it unchanged
if( is.na(ind) ) return(x[i])
# multiple matches: error
if( ind == 0 ){
alt <- paste(grep(paste('^', x[i], sep=''), args, value=TRUE), collapse=', ')
stop(if( !is.null(call) ) c(call, ' - '), "Multiple match for argument '", x[i], "' of function '"
, if( is.null(in.fun) ) fun else in.fun, "' [use one of: ", alt, "]"
, call.=FALSE)
}
# return the matched full names
args[ind]
})
}
#'
setGeneric('summary', package='base')
setMethod('summary', signature(object='KINOMO'),
function(object, class, target){
res <- numeric()
## IMPORTANT: if adding a summary measure also add it in the sorting
## schema of method KINOMOList::summary to allow ordering on it
# rank
res <- c(res, rank=nbasis(object))
# compute sparseness
res <- c(res, sparseness=sparseness(object))
# if class is provided: also computes entropy and purity
if( !missing(class) ){
# compute purity
res <- c(res, purity=purity(object, class))
# compute entropy
res <- c(res, entropy=entropy(object, class))
}
# if the target is provided compute the RSS
if( !missing(target) ){
RSS <- rss(object, target)
res <- c(res, rss=RSS)
# explained variance
res <- c(res, evar=evar(object, target))
}
# compute mean silhouette width
siS <- silhouette(object, what = 'samples')
siF <- silhouette(object, what = 'features')
res <- c(res, silhouette.coef = if( !is_NA(siS) ) summary(siS)$avg.width else NA
, silhouette.basis = if( !is_NA(siF) ) summary(siF)$avg.width else NA)
# return result
return(res)
}
)
setGeneric('sparseness', function(x, ...) standardGeneric('sparseness') )
#' Base method that computes the sparseness of a numeric vector.
#'
#' It returns a single numeric value, computed following the definition
#' given in section \emph{Description}.
setMethod('sparseness', signature(x='numeric'),
function(x){
# get length of x
n <- length(x)
# compute and return the sparseness
( sqrt(n) - sum(abs(x)) / sqrt(sum(x^2)) ) / (sqrt(n)-1)
}
)
#' Computes the sparseness of a matrix as the mean sparseness of its column vectors.
#' It returns a single numeric value.
setMethod('sparseness', signature(x='matrix'),
function(x){
# compute the sparseness of each column
s <- apply(x, 2, sparseness)
# return the mean sparseness
mean(s)
}
)
#' Compute the sparseness of an object of class \code{KINOMO}, as the sparseness of
#' the basis and coefficient matrices computed separately.
#'
#' It returns the two values in a numeric vector with names \sQuote{basis} and \sQuote{coef}.
setMethod('sparseness', signature(x='KINOMO'),
function(x){
# return the sparseness of the basis and coef matrix
c(basis=sparseness(basis(x)), coef=sparseness(coef(x)))
}
)
#'
setGeneric('purity', function(x, y, ...) standardGeneric('purity') )
#' Computes the purity directly from the contingency table \code{x}
setMethod('purity', signature(x='table', y='missing'),
function(x, y){
#for each cluster: compute maximum number of samples common to a class
t <- apply(x, 1, max)
# average and return the result
sum(t) / sum(x)
}
)
#' Computes the purity on the contingency table of \code{x} and \code{y}, that is
#' coerced into a factor if necessary.
setMethod('purity', 'factor',
function(x, y, ...){
# coerce `y` into a factor if necessary
if( !is.factor(y) ) y <- as.factor(y)
#compute the purity on the contingency table between clusters and true classes (clusters are in rows)
purity(table(x, y), ...)
}
)
#' Default method that should work for results of clustering algorithms, that have a
#' suitable \code{predict} method that returns the cluster membership vector:
#' the purity is computed between \code{x} and \code{predict{y}}
setMethod('purity', 'ANY',
function(x, y, ...){
# compute the purity for the samples clusters defined by the profiles
purity(predict(x), y, ...)
}
)
#'
setGeneric('entropy', function(x, y, ...) standardGeneric('entropy') )
#' Computes the purity directly from the contingency table \code{x}.
#'
#' This is the workhorse method that is eventually called by all other methods.
setMethod('entropy', signature(x='table', y='missing'),
function(x, y, ...){
#for each cluster: compute the inner sum
t <- apply(x, 1, function(n){ c.size <- sum(n); n %*% ifelse( n!=0, log2(n/c.size), 0)} )
# weight and return the result
- sum(t) / ( sum(x) * log2(ncol(x)) )
}
)
#' Computes the purity on the contingency table of \code{x} and \code{y}, that is
#' coerced into a factor if necessary.
setMethod('entropy', 'factor',
function(x, y, ...){
# coerce `y` into a factor if necessary
if( !is.factor(y) ) y <- as.factor(y)
#copmute entropy on contingency table between clusters and true classes (clusters are in rows)
entropy(table(x, y))
}
)
#' Default method that should work for results of clustering algorithms, that have a
#' suitable \code{predict} method that returns the cluster membership vector:
#' the purity is computed between \code{x} and \code{predict{y}}
setMethod('entropy', 'ANY',
function(x, y, ...){
# compute the entropy for the samples clusters defined by the metagenes expression matrix
entropy(predict(x), y)
}
)
#setGeneric('KINOMOApply', function(object, ...) standardGeneric('KINOMOApply') )
KINOMOApply <- function(X, MARGIN, FUN, ..., simplify = TRUE, USE.NAMES = TRUE){
if( MARGIN == 1L )
apply(basis(X), 1L, FUN, ...)
else if( MARGIN == 4L )
apply(basis(X), 2L, FUN, ...)
else if( MARGIN == 2L )
apply(coef(X), 2L, FUN, ...)
else if( MARGIN == 5L )
apply(coef(X), 1L, FUN, ...)
else if( MARGIN == 3L ){
b <- basis(X)
p <- coef(X)
sapply(setNames(seq(nbasis(X), basisnames(X)))
, function(i, ...) FUN(b[,i], p[i,], ...)
, simplify = simplify, USE.NAMES = USE.NAMES)
}else stop("invalid argument 'MARGIN' (expected values are: 1-basis rows, 2-coef columns, 3-(basis columns, coef rows), or 4-basis columns or 5-coef rows)")
}
###% Utility function to compute the dominant column for each row for a matrix.
.predict.KINOMO <- function(x, prob=FALSE){
if( !is.matrix(x) ) stop('KINOMO:::.predict.KINOMO : only works on matrices')
if( !prob ){
#for each column return the (row) index of the maximum
return( as.factor(apply(x, 1L, function(v) which.max(abs(v)))) )
}
else{
#for each column return the (row) index of the maximum AND the associated probaility
res <- apply(x, 1L,
function(p){
p <- abs(p)
i <- which.max(p)
c(i, p[i]/sum(p))
}
)
# return the result as a list of two elements
return( list(predict=as.factor(res[1,]), prob=res[2,]) )
}
}
setGeneric('predict', package='stats')
setMethod('predict', 'KINOMO',
function(object, what=c('columns', 'rows', 'samples', 'features'), prob=FALSE, dmatrix = FALSE){
# determine which matrix to use for the prediction
what <- match.arg(what)
x <- if( what %in% c('features', 'rows') ) basis(object, all=FALSE) else t(coef(object, all=FALSE))
# compute the indice of the dominant row for each column
res <- .predict.KINOMO(x, prob)
# attach dissimilarity matrix if requested
if( dmatrix ){
attr(res, 'dmatrix') <- 1 - cor(t(x))
}
return( res )
}
)
#'
setGeneric('basiscor', function(x, y, ...) standardGeneric('basiscor') )
#' Computes the correlations between the basis vectors of \code{x} and
#' the columns of \code{y}.
setMethod('basiscor', signature(x='KINOMO', y='matrix'),
function(x, y, ...){
cor(basis(x), y, ...)
}
)
#' Computes the correlations between the columns of \code{x}
#' and the the basis vectors of \code{y}.
setMethod('basiscor', signature(x='matrix', y='KINOMO'),
function(x, y, ...){
cor(x, basis(y), ...)
}
)
#' Computes the correlations between the basis vectors of \code{x} and \code{y}.
setMethod('basiscor', signature(x='KINOMO', y='KINOMO'),
function(x, y, ...){
basiscor(x, basis(y), ...)
}
)
#' Computes the correlations between the basis vectors of \code{x}.
setMethod('basiscor', signature(x='KINOMO', y='missing'),
function(x, y, ...){
basiscor(x, x, ...)
}
)
#'
setGeneric('profcor', function(x, y, ...) standardGeneric('profcor') )
#' Computes the correlations between the basis profiles of \code{x} and
#' the rows of \code{y}.
setMethod('profcor', signature(x='KINOMO', y='matrix'),
function(x, y, ...){
cor(t(coef(x)), t(y), ...)
}
)
#' Computes the correlations between the rows of \code{x} and the basis
#' profiles of \code{y}.
setMethod('profcor', signature(x='matrix', y='KINOMO'),
function(x, y, ...){
cor(t(x), t(coef(y)), ...)
}
)
#' Computes the correlations between the basis profiles of \code{x} and \code{y}.
setMethod('profcor', signature(x='KINOMO', y='KINOMO'),
function(x, y, ...){
profcor(x, coef(y), ...)
}
)
#' Computes the correlations between the basis profiles of \code{x}.
setMethod('profcor', signature(x='KINOMO', y='missing'),
function(x, y, ...){
profcor(x, x, ...)
}
)