... | ... |
@@ -1,8 +1,8 @@ |
1 | 1 |
Package: OncoSimulR |
2 | 2 |
Type: Package |
3 | 3 |
Title: Forward Genetic Simulation of Cancer Progression with Epistasis |
4 |
-Version: 2.99.5 |
|
5 |
-Date: 2020-12-18 |
|
4 |
+Version: 2.99.6 |
|
5 |
+Date: 2020-12-13 |
|
6 | 6 |
Authors@R: c( |
7 | 7 |
person("Ramon", "Diaz-Uriarte", role = c("aut", "cre"), |
8 | 8 |
email = "rdiaz02@gmail.com"), |
... | ... |
@@ -499,6 +499,8 @@ oncoSimulIndiv <- function(fp, |
499 | 499 |
if(inherits(fp, "fitnessEffects")) { |
500 | 500 |
s <- sh <- NULL ## force it soon! |
501 | 501 |
} |
502 |
+ if(!inherits(fp, "fitnessEffects")) |
|
503 |
+ stop("v.1 functionality has been removed. Please use v.2") |
|
502 | 504 |
|
503 | 505 |
## legacies from poor name choices |
504 | 506 |
typeFitness <- switch(model, |
... | ... |
@@ -549,8 +551,8 @@ oncoSimulIndiv <- function(fp, |
549 | 551 |
stop("Unknown model") |
550 | 552 |
} |
551 | 553 |
|
552 |
- if( (length(mu) > 1) && !inherits(fp, "fitnessEffects")) |
|
553 |
- stop("Per-gene mutation rates cannot be used with the old poset format") |
|
554 |
+ ## if( (length(mu) > 1) && !inherits(fp, "fitnessEffects")) |
|
555 |
+ ## stop("Per-gene mutation rates cannot be used with the old poset format") |
|
554 | 556 |
|
555 | 557 |
if(any(mu < 0)) { |
556 | 558 |
stop("(at least one) mutation rate (mu) is negative") |
... | ... |
@@ -584,83 +586,83 @@ oncoSimulIndiv <- function(fp, |
584 | 586 |
|
585 | 587 |
if(is_null_na(sampleEvery)) stop("sampleEvery cannot be NULL or NA") |
586 | 588 |
|
587 |
- if(!inherits(fp, "fitnessEffects")) { |
|
588 |
- if(any(unlist(lapply(list(fp, |
|
589 |
- numPassengers, |
|
590 |
- s, sh), is.null)))) { |
|
591 |
- m <- paste("You are using the old poset format.", |
|
592 |
- "You must specify all of poset, numPassengers", |
|
593 |
- "s, and sh.") |
|
594 |
- stop(m) |
|
589 |
+ ## if(!inherits(fp, "fitnessEffects")) { |
|
590 |
+ ## if(any(unlist(lapply(list(fp, |
|
591 |
+ ## numPassengers, |
|
592 |
+ ## s, sh), is.null)))) { |
|
593 |
+ ## m <- paste("You are using the old poset format.", |
|
594 |
+ ## "You must specify all of poset, numPassengers", |
|
595 |
+ ## "s, and sh.") |
|
596 |
+ ## stop(m) |
|
595 | 597 |
|
596 |
- } |
|
597 |
- if(AND_DrvProbExit) { |
|
598 |
- stop("The AND_DrvProbExit = TRUE setting is invalid", |
|
599 |
- " with the old poset format.") |
|
600 |
- } |
|
601 |
- if(!is.null(muEF)) |
|
602 |
- stop("Mutator effects cannot be specified with the old poset format.") |
|
603 |
- if( length(initMutant) > 0) |
|
604 |
- warning("With the old poset format you can no longer use initMutant.", |
|
605 |
- " The initMutant you passed will be ignored.") |
|
606 |
- ## stop("With the old poset, initMutant can only take a single value.") |
|
607 |
- if(!is_null_na(fixation)) |
|
608 |
- stop("'fixation' cannot be specified with the old poset format.") |
|
609 |
- ## Seeding C++ is now much better in new version |
|
610 |
- if(is.null(seed) || (seed == "auto")) {## passing a null creates a random seed |
|
611 |
- ## name is a legacy. This is really the seed for the C++ generator. |
|
612 |
- ## Nope, we cannot use 2^32, because as.integer will fail. |
|
613 |
- seed <- as.integer(round(runif(1, min = 0, max = 2^16))) |
|
614 |
- } |
|
615 |
- if(verbosity >= 2) |
|
616 |
- cat(paste("\n Using ", seed, " as seed for C++ generator\n")) |
|
617 |
- |
|
618 |
- if(!is_null_na(detectionProb)) stop("detectionProb cannot be used in v.1 objects") |
|
619 |
- ## if(message.v1) |
|
620 |
- ## message("You are using the old poset format. Consider using the new one.") |
|
598 |
+ ## } |
|
599 |
+ ## if(AND_DrvProbExit) { |
|
600 |
+ ## stop("The AND_DrvProbExit = TRUE setting is invalid", |
|
601 |
+ ## " with the old poset format.") |
|
602 |
+ ## } |
|
603 |
+ ## if(!is.null(muEF)) |
|
604 |
+ ## stop("Mutator effects cannot be specified with the old poset format.") |
|
605 |
+ ## if( length(initMutant) > 0) |
|
606 |
+ ## warning("With the old poset format you can no longer use initMutant.", |
|
607 |
+ ## " The initMutant you passed will be ignored.") |
|
608 |
+ ## ## stop("With the old poset, initMutant can only take a single value.") |
|
609 |
+ ## if(!is_null_na(fixation)) |
|
610 |
+ ## stop("'fixation' cannot be specified with the old poset format.") |
|
611 |
+ ## ## Seeding C++ is now much better in new version |
|
612 |
+ ## if(is.null(seed) || (seed == "auto")) {## passing a null creates a random seed |
|
613 |
+ ## ## name is a legacy. This is really the seed for the C++ generator. |
|
614 |
+ ## ## Nope, we cannot use 2^32, because as.integer will fail. |
|
615 |
+ ## seed <- as.integer(round(runif(1, min = 0, max = 2^16))) |
|
616 |
+ ## } |
|
617 |
+ ## if(verbosity >= 2) |
|
618 |
+ ## cat(paste("\n Using ", seed, " as seed for C++ generator\n")) |
|
619 |
+ |
|
620 |
+ ## if(!is_null_na(detectionProb)) stop("detectionProb cannot be used in v.1 objects") |
|
621 |
+ ## ## if(message.v1) |
|
622 |
+ ## ## message("You are using the old poset format. Consider using the new one.") |
|
621 | 623 |
|
622 | 624 |
|
623 |
- ## A simulation stops if cancer or finalTime appear, the first |
|
624 |
- ## one. But if we set onlyCnacer = FALSE, we also accept simuls |
|
625 |
- ## without cancer (or without anything) |
|
625 |
+ ## ## A simulation stops if cancer or finalTime appear, the first |
|
626 |
+ ## ## one. But if we set onlyCnacer = FALSE, we also accept simuls |
|
627 |
+ ## ## without cancer (or without anything) |
|
626 | 628 |
|
627 |
- op <- try(oncoSimul.internal(poset = fp, ## restrict.table = rt, |
|
628 |
- ## numGenes = numGenes, |
|
629 |
- numPassengers = numPassengers, |
|
630 |
- typeCBN = "CBN", |
|
631 |
- birth = birth, |
|
632 |
- s = s, |
|
633 |
- death = death, |
|
634 |
- mu = mu, |
|
635 |
- initSize = initSize, |
|
636 |
- sampleEvery = sampleEvery, |
|
637 |
- detectionSize = detectionSize, |
|
638 |
- finalTime = finalTime, |
|
639 |
- initSize_species = 2000, |
|
640 |
- initSize_iter = 500, |
|
641 |
- seed = seed, |
|
642 |
- verbosity = verbosity, |
|
643 |
- speciesFS = 10000, |
|
644 |
- ratioForce = 2, |
|
645 |
- typeFitness = typeFitness, |
|
646 |
- max.memory = max.memory, |
|
647 |
- mutationPropGrowth = mutationPropGrowth, |
|
648 |
- initMutant = -1, |
|
649 |
- max.wall.time = max.wall.time, |
|
650 |
- max.num.tries = max.num.tries, |
|
651 |
- keepEvery = keepEvery, |
|
652 |
- ## alpha = 0.0015, |
|
653 |
- sh = sh, |
|
654 |
- K = K, |
|
655 |
- minDetectDrvCloneSz = minDetectDrvCloneSz, |
|
656 |
- extraTime = extraTime, |
|
657 |
- detectionDrivers = detectionDrivers, |
|
658 |
- onlyCancer = onlyCancer, |
|
659 |
- errorHitWallTime = errorHitWallTime, |
|
660 |
- errorHitMaxTries = errorHitMaxTries), |
|
661 |
- silent = !verbosity) |
|
662 |
- objClass <- "oncosimul" |
|
663 |
- } else { |
|
629 |
+ ## op <- try(oncoSimul.internal(poset = fp, ## restrict.table = rt, |
|
630 |
+ ## ## numGenes = numGenes, |
|
631 |
+ ## numPassengers = numPassengers, |
|
632 |
+ ## typeCBN = "CBN", |
|
633 |
+ ## birth = birth, |
|
634 |
+ ## s = s, |
|
635 |
+ ## death = death, |
|
636 |
+ ## mu = mu, |
|
637 |
+ ## initSize = initSize, |
|
638 |
+ ## sampleEvery = sampleEvery, |
|
639 |
+ ## detectionSize = detectionSize, |
|
640 |
+ ## finalTime = finalTime, |
|
641 |
+ ## initSize_species = 2000, |
|
642 |
+ ## initSize_iter = 500, |
|
643 |
+ ## seed = seed, |
|
644 |
+ ## verbosity = verbosity, |
|
645 |
+ ## speciesFS = 10000, |
|
646 |
+ ## ratioForce = 2, |
|
647 |
+ ## typeFitness = typeFitness, |
|
648 |
+ ## max.memory = max.memory, |
|
649 |
+ ## mutationPropGrowth = mutationPropGrowth, |
|
650 |
+ ## initMutant = -1, |
|
651 |
+ ## max.wall.time = max.wall.time, |
|
652 |
+ ## max.num.tries = max.num.tries, |
|
653 |
+ ## keepEvery = keepEvery, |
|
654 |
+ ## ## alpha = 0.0015, |
|
655 |
+ ## sh = sh, |
|
656 |
+ ## K = K, |
|
657 |
+ ## minDetectDrvCloneSz = minDetectDrvCloneSz, |
|
658 |
+ ## extraTime = extraTime, |
|
659 |
+ ## detectionDrivers = detectionDrivers, |
|
660 |
+ ## onlyCancer = onlyCancer, |
|
661 |
+ ## errorHitWallTime = errorHitWallTime, |
|
662 |
+ ## errorHitMaxTries = errorHitMaxTries), |
|
663 |
+ ## silent = !verbosity) |
|
664 |
+ ## objClass <- "oncosimul" |
|
665 |
+ ## } else { |
|
664 | 666 |
s <- sh <- NULL ## force it. |
665 | 667 |
if(numPassengers != 0) |
666 | 668 |
warning(paste("Specifying numPassengers has no effect", |
... | ... |
@@ -728,7 +730,7 @@ oncoSimulIndiv <- function(fp, |
728 | 730 |
fixation = fixation), |
729 | 731 |
silent = !verbosity) |
730 | 732 |
objClass <- c("oncosimul", "oncosimul2") |
731 |
- } |
|
733 |
+ ## } |
|
732 | 734 |
if(inherits(op, "try-error")) { |
733 | 735 |
## if(length(grep("BAIL OUT NOW", op))) |
734 | 736 |
stop(paste("Unrecoverable error:", op )) |
... | ... |
@@ -1763,156 +1765,156 @@ get.mut.vector <- function(x, timeSample, typeSample, |
1763 | 1765 |
|
1764 | 1766 |
|
1765 | 1767 |
|
1766 |
-oncoSimul.internal <- function(poset, ## restrict.table, |
|
1767 |
- numPassengers, |
|
1768 |
- ## numGenes, |
|
1769 |
- typeCBN, |
|
1770 |
- birth, |
|
1771 |
- s, |
|
1772 |
- death, |
|
1773 |
- mu, |
|
1774 |
- initSize, |
|
1775 |
- sampleEvery, |
|
1776 |
- detectionSize, |
|
1777 |
- finalTime, |
|
1778 |
- initSize_species, |
|
1779 |
- initSize_iter, |
|
1780 |
- seed, |
|
1781 |
- verbosity, |
|
1782 |
- speciesFS, |
|
1783 |
- ratioForce, |
|
1784 |
- typeFitness, |
|
1785 |
- max.memory, |
|
1786 |
- mutationPropGrowth, ## make it explicit |
|
1787 |
- initMutant, |
|
1788 |
- max.wall.time, |
|
1789 |
- keepEvery, |
|
1790 |
- alpha, |
|
1791 |
- sh, |
|
1792 |
- K, |
|
1793 |
- ## endTimeEvery, |
|
1794 |
- detectionDrivers, |
|
1795 |
- onlyCancer, |
|
1796 |
- errorHitWallTime, |
|
1797 |
- max.num.tries, |
|
1798 |
- errorHitMaxTries, |
|
1799 |
- minDetectDrvCloneSz, |
|
1800 |
- extraTime) { |
|
1768 |
+## oncoSimul.internal <- function(poset, ## restrict.table, |
|
1769 |
+## numPassengers, |
|
1770 |
+## ## numGenes, |
|
1771 |
+## typeCBN, |
|
1772 |
+## birth, |
|
1773 |
+## s, |
|
1774 |
+## death, |
|
1775 |
+## mu, |
|
1776 |
+## initSize, |
|
1777 |
+## sampleEvery, |
|
1778 |
+## detectionSize, |
|
1779 |
+## finalTime, |
|
1780 |
+## initSize_species, |
|
1781 |
+## initSize_iter, |
|
1782 |
+## seed, |
|
1783 |
+## verbosity, |
|
1784 |
+## speciesFS, |
|
1785 |
+## ratioForce, |
|
1786 |
+## typeFitness, |
|
1787 |
+## max.memory, |
|
1788 |
+## mutationPropGrowth, ## make it explicit |
|
1789 |
+## initMutant, |
|
1790 |
+## max.wall.time, |
|
1791 |
+## keepEvery, |
|
1792 |
+## alpha, |
|
1793 |
+## sh, |
|
1794 |
+## K, |
|
1795 |
+## ## endTimeEvery, |
|
1796 |
+## detectionDrivers, |
|
1797 |
+## onlyCancer, |
|
1798 |
+## errorHitWallTime, |
|
1799 |
+## max.num.tries, |
|
1800 |
+## errorHitMaxTries, |
|
1801 |
+## minDetectDrvCloneSz, |
|
1802 |
+## extraTime) { |
|
1801 | 1803 |
|
1802 |
- ## the value of 20000, in megabytes, for max.memory sets a limit of ~ 20 GB |
|
1804 |
+## ## the value of 20000, in megabytes, for max.memory sets a limit of ~ 20 GB |
|
1803 | 1805 |
|
1804 | 1806 |
|
1805 |
- ## if(keepEvery < sampleEvery) |
|
1806 |
- ## warning("setting keepEvery to sampleEvery") |
|
1807 |
- |
|
1808 |
- ## a backdoor to allow passing restrictionTables directly |
|
1809 |
- if(inherits(poset, "restrictionTable")) |
|
1810 |
- restrict.table <- poset |
|
1811 |
- else |
|
1812 |
- restrict.table <- poset.to.restrictTable(poset) |
|
1813 |
- numDrivers <- nrow(restrict.table) |
|
1814 |
- numGenes <- (numDrivers + numPassengers) |
|
1815 |
- if(numGenes < 2) |
|
1816 |
- stop("There must be at least two genes (loci) in the fitness effects.", |
|
1817 |
- "If you only care about a degenerate case with just one,", |
|
1818 |
- "you can enter a second gene", |
|
1819 |
- "with fitness effect of zero.") |
|
1820 |
- if(numGenes > 64) |
|
1821 |
- stop("Largest possible number of genes (loci) is 64 for version 1.", |
|
1822 |
- "You are strongly encouraged to use the new specification", |
|
1823 |
- "as in version 2.") |
|
1824 |
- |
|
1825 |
- ## These can never be set by the user |
|
1826 |
- ## if(initSize_species < 10) { |
|
1827 |
- ## warning("initSize_species too small?") |
|
1828 |
- ## } |
|
1829 |
- ## if(initSize_iter < 100) { |
|
1830 |
- ## warning("initSize_iter too small?") |
|
1831 |
- ## } |
|
1807 |
+## ## if(keepEvery < sampleEvery) |
|
1808 |
+## ## warning("setting keepEvery to sampleEvery") |
|
1809 |
+ |
|
1810 |
+## ## a backdoor to allow passing restrictionTables directly |
|
1811 |
+## if(inherits(poset, "restrictionTable")) |
|
1812 |
+## restrict.table <- poset |
|
1813 |
+## else |
|
1814 |
+## restrict.table <- poset.to.restrictTable(poset) |
|
1815 |
+## numDrivers <- nrow(restrict.table) |
|
1816 |
+## numGenes <- (numDrivers + numPassengers) |
|
1817 |
+## if(numGenes < 2) |
|
1818 |
+## stop("There must be at least two genes (loci) in the fitness effects.", |
|
1819 |
+## "If you only care about a degenerate case with just one,", |
|
1820 |
+## "you can enter a second gene", |
|
1821 |
+## "with fitness effect of zero.") |
|
1822 |
+## if(numGenes > 64) |
|
1823 |
+## stop("Largest possible number of genes (loci) is 64 for version 1.", |
|
1824 |
+## "You are strongly encouraged to use the new specification", |
|
1825 |
+## "as in version 2.") |
|
1826 |
+ |
|
1827 |
+## ## These can never be set by the user |
|
1828 |
+## ## if(initSize_species < 10) { |
|
1829 |
+## ## warning("initSize_species too small?") |
|
1830 |
+## ## } |
|
1831 |
+## ## if(initSize_iter < 100) { |
|
1832 |
+## ## warning("initSize_iter too small?") |
|
1833 |
+## ## } |
|
1832 | 1834 |
|
1833 |
- ## numDrivers <- nrow(restrict.table) |
|
1834 |
- if(length(unique(restrict.table[, 1])) != numDrivers) |
|
1835 |
- stop("BAIL OUT NOW: length(unique(restrict.table[, 1])) != numDrivers)") |
|
1836 |
- ddr <- restrict.table[, 1] |
|
1837 |
- if(any(diff(ddr) != 1)) |
|
1838 |
- stop("BAIL OUT NOW: any(diff(ddr) != 1") |
|
1839 |
- ## sanity checks |
|
1840 |
- if(max(restrict.table[, 1]) != numDrivers) |
|
1841 |
- stop("BAIL OUT NOW: max(restrict.table[, 1]) != numDrivers") |
|
1842 |
- if(numDrivers > numGenes) |
|
1843 |
- stop("BAIL OUT NOW: numDrivers > numGenes") |
|
1835 |
+## ## numDrivers <- nrow(restrict.table) |
|
1836 |
+## if(length(unique(restrict.table[, 1])) != numDrivers) |
|
1837 |
+## stop("BAIL OUT NOW: length(unique(restrict.table[, 1])) != numDrivers)") |
|
1838 |
+## ddr <- restrict.table[, 1] |
|
1839 |
+## if(any(diff(ddr) != 1)) |
|
1840 |
+## stop("BAIL OUT NOW: any(diff(ddr) != 1") |
|
1841 |
+## ## sanity checks |
|
1842 |
+## if(max(restrict.table[, 1]) != numDrivers) |
|
1843 |
+## stop("BAIL OUT NOW: max(restrict.table[, 1]) != numDrivers") |
|
1844 |
+## if(numDrivers > numGenes) |
|
1845 |
+## stop("BAIL OUT NOW: numDrivers > numGenes") |
|
1844 | 1846 |
|
1845 |
- non.dep.drivers <- restrict.table[which(restrict.table[, 2] == 0), 1] |
|
1847 |
+## non.dep.drivers <- restrict.table[which(restrict.table[, 2] == 0), 1] |
|
1846 | 1848 |
|
1847 | 1849 |
|
1848 | 1850 |
|
1849 | 1851 |
|
1850 |
- ## if( (is.null(endTimeEvery) || (endTimeEvery > 0)) && |
|
1851 |
- ## (typeFitness %in% c("bozic1", "exp") )) { |
|
1852 |
- ## warning(paste("endTimeEvery will take a positive value. ", |
|
1853 |
- ## "This will make simulations not stop until the next ", |
|
1854 |
- ## "endTimeEvery has been reached. Thus, in simulations ", |
|
1855 |
- ## "with very fast growth, simulations can take a long ", |
|
1856 |
- ## "time to finish, or can hit the wall time limit. ")) |
|
1857 |
- ## } |
|
1858 |
- ## if(is.null(endTimeEvery)) |
|
1859 |
- ## endTimeEvery <- keepEvery |
|
1860 |
- ## if( (endTimeEvery > 0) && (endTimeEvery %% keepEvery) ) |
|
1861 |
- ## warning("!(endTimeEvery %% keepEvery)") |
|
1862 |
- ## a sanity check in restricTable, so no neg. indices for the positive deps |
|
1863 |
- neg.deps <- function(x) { |
|
1864 |
- ## checks a row of restrict.table |
|
1865 |
- numdeps <- x[2] |
|
1866 |
- if(numdeps) { |
|
1867 |
- deps <- x[3:(3+numdeps - 1)] |
|
1868 |
- return(any(deps < 0)) |
|
1869 |
- } else FALSE |
|
1870 |
- } |
|
1871 |
- if(any(apply(restrict.table, 1, neg.deps))) |
|
1872 |
- stop("BAIL OUT NOW: Negative dependencies in restriction table") |
|
1852 |
+## ## if( (is.null(endTimeEvery) || (endTimeEvery > 0)) && |
|
1853 |
+## ## (typeFitness %in% c("bozic1", "exp") )) { |
|
1854 |
+## ## warning(paste("endTimeEvery will take a positive value. ", |
|
1855 |
+## ## "This will make simulations not stop until the next ", |
|
1856 |
+## ## "endTimeEvery has been reached. Thus, in simulations ", |
|
1857 |
+## ## "with very fast growth, simulations can take a long ", |
|
1858 |
+## ## "time to finish, or can hit the wall time limit. ")) |
|
1859 |
+## ## } |
|
1860 |
+## ## if(is.null(endTimeEvery)) |
|
1861 |
+## ## endTimeEvery <- keepEvery |
|
1862 |
+## ## if( (endTimeEvery > 0) && (endTimeEvery %% keepEvery) ) |
|
1863 |
+## ## warning("!(endTimeEvery %% keepEvery)") |
|
1864 |
+## ## a sanity check in restricTable, so no neg. indices for the positive deps |
|
1865 |
+## neg.deps <- function(x) { |
|
1866 |
+## ## checks a row of restrict.table |
|
1867 |
+## numdeps <- x[2] |
|
1868 |
+## if(numdeps) { |
|
1869 |
+## deps <- x[3:(3+numdeps - 1)] |
|
1870 |
+## return(any(deps < 0)) |
|
1871 |
+## } else FALSE |
|
1872 |
+## } |
|
1873 |
+## if(any(apply(restrict.table, 1, neg.deps))) |
|
1874 |
+## stop("BAIL OUT NOW: Negative dependencies in restriction table") |
|
1873 | 1875 |
|
1874 |
- ## transpose the table |
|
1875 |
- rtC <- convertRestrictTable(restrict.table) |
|
1876 |
+## ## transpose the table |
|
1877 |
+## rtC <- convertRestrictTable(restrict.table) |
|
1876 | 1878 |
|
1877 | 1879 |
|
1878 |
- return(c( |
|
1879 |
- BNB_Algo5(restrictTable = rtC, |
|
1880 |
- numDrivers = numDrivers, |
|
1881 |
- numGenes = numGenes, |
|
1882 |
- typeCBN_= typeCBN, |
|
1883 |
- s = s, |
|
1884 |
- death = death, |
|
1885 |
- mu = mu, |
|
1886 |
- initSize = initSize, |
|
1887 |
- sampleEvery = sampleEvery, |
|
1888 |
- detectionSize = detectionSize, |
|
1889 |
- finalTime = finalTime, |
|
1890 |
- initSp = initSize_species, |
|
1891 |
- initIt = initSize_iter, |
|
1892 |
- seed = seed, |
|
1893 |
- verbosity = verbosity, |
|
1894 |
- speciesFS = speciesFS, |
|
1895 |
- ratioForce = ratioForce, |
|
1896 |
- typeFitness_ = typeFitness, |
|
1897 |
- maxram = max.memory, |
|
1898 |
- mutationPropGrowth = as.integer(mutationPropGrowth), |
|
1899 |
- initMutant = initMutant, |
|
1900 |
- maxWallTime = max.wall.time, |
|
1901 |
- keepEvery = keepEvery, |
|
1902 |
- sh = sh, |
|
1903 |
- K = K, |
|
1904 |
- detectionDrivers = detectionDrivers, |
|
1905 |
- onlyCancer = onlyCancer, |
|
1906 |
- errorHitWallTime = errorHitWallTime, |
|
1907 |
- maxNumTries = max.num.tries, |
|
1908 |
- errorHitMaxTries = errorHitMaxTries, |
|
1909 |
- minDetectDrvCloneSz = minDetectDrvCloneSz, |
|
1910 |
- extraTime = extraTime |
|
1911 |
- ), |
|
1912 |
- NumDrivers = numDrivers |
|
1913 |
- )) |
|
1880 |
+## return(c( |
|
1881 |
+## BNB_Algo5(restrictTable = rtC, |
|
1882 |
+## numDrivers = numDrivers, |
|
1883 |
+## numGenes = numGenes, |
|
1884 |
+## typeCBN_= typeCBN, |
|
1885 |
+## s = s, |
|
1886 |
+## death = death, |
|
1887 |
+## mu = mu, |
|
1888 |
+## initSize = initSize, |
|
1889 |
+## sampleEvery = sampleEvery, |
|
1890 |
+## detectionSize = detectionSize, |
|
1891 |
+## finalTime = finalTime, |
|
1892 |
+## initSp = initSize_species, |
|
1893 |
+## initIt = initSize_iter, |
|
1894 |
+## seed = seed, |
|
1895 |
+## verbosity = verbosity, |
|
1896 |
+## speciesFS = speciesFS, |
|
1897 |
+## ratioForce = ratioForce, |
|
1898 |
+## typeFitness_ = typeFitness, |
|
1899 |
+## maxram = max.memory, |
|
1900 |
+## mutationPropGrowth = as.integer(mutationPropGrowth), |
|
1901 |
+## initMutant = initMutant, |
|
1902 |
+## maxWallTime = max.wall.time, |
|
1903 |
+## keepEvery = keepEvery, |
|
1904 |
+## sh = sh, |
|
1905 |
+## K = K, |
|
1906 |
+## detectionDrivers = detectionDrivers, |
|
1907 |
+## onlyCancer = onlyCancer, |
|
1908 |
+## errorHitWallTime = errorHitWallTime, |
|
1909 |
+## maxNumTries = max.num.tries, |
|
1910 |
+## errorHitMaxTries = errorHitMaxTries, |
|
1911 |
+## minDetectDrvCloneSz = minDetectDrvCloneSz, |
|
1912 |
+## extraTime = extraTime |
|
1913 |
+## ), |
|
1914 |
+## NumDrivers = numDrivers |
|
1915 |
+## )) |
|
1914 | 1916 |
|
1915 |
-} |
|
1917 |
+## } |
|
1916 | 1918 |
|
1917 | 1919 |
OncoSimulWide2Long <- function(x) { |
1918 | 1920 |
## Put data in long format, for ggplot et al |
... | ... |
@@ -5,10 +5,6 @@ nr_BNB_Algo5 <- function(rFE, mu_, death, initSize_, sampleEvery, detectionSize, |
5 | 5 |
.Call('OncoSimulR_nr_BNB_Algo5', PACKAGE = 'OncoSimulR', rFE, mu_, death, initSize_, sampleEvery, detectionSize, finalTime, initSp, initIt, seed, verbosity, speciesFS, ratioForce, typeFitness_, maxram, mutationPropGrowth, initMutant_, maxWallTime, keepEvery, K, detectionDrivers, onlyCancer, errorHitWallTime, maxNumTries, errorHitMaxTries, minDetectDrvCloneSz, extraTime, keepPhylog, MMUEF, full2mutator_, n2, p2, PDBaseline, cPDetect_i, checkSizePEvery, AND_DrvProbExit, fixation_list) |
6 | 6 |
} |
7 | 7 |
|
8 |
-BNB_Algo5 <- function(restrictTable, numDrivers, numGenes, typeCBN_, s, death, mu, initSize, sampleEvery, detectionSize, finalTime, initSp, initIt, seed, verbosity, speciesFS, ratioForce, typeFitness_, maxram, mutationPropGrowth, initMutant, maxWallTime, keepEvery, sh, K, detectionDrivers, onlyCancer, errorHitWallTime, maxNumTries, errorHitMaxTries, minDetectDrvCloneSz, extraTime) { |
|
9 |
- .Call('OncoSimulR_BNB_Algo5', PACKAGE = 'OncoSimulR', restrictTable, numDrivers, numGenes, typeCBN_, s, death, mu, initSize, sampleEvery, detectionSize, finalTime, initSp, initIt, seed, verbosity, speciesFS, ratioForce, typeFitness_, maxram, mutationPropGrowth, initMutant, maxWallTime, keepEvery, sh, K, detectionDrivers, onlyCancer, errorHitWallTime, maxNumTries, errorHitMaxTries, minDetectDrvCloneSz, extraTime) |
|
10 |
-} |
|
11 |
- |
|
12 | 8 |
evalRGenotype <- function(rG, rFE, spPop, verbose, prodNeg, calledBy_, currentTime) { |
13 | 9 |
.Call('OncoSimulR_evalRGenotype', PACKAGE = 'OncoSimulR', rG, rFE, spPop, verbose, prodNeg, calledBy_, currentTime) |
14 | 10 |
} |
... | ... |
@@ -8,7 +8,7 @@ |
8 | 8 |
} |
9 | 9 |
\description{ |
10 | 10 |
|
11 |
- Conver the \code{pops.by.time} component from its "wide" format (with |
|
11 |
+ Convert the \code{pops.by.time} component from its "wide" format (with |
|
12 | 12 |
one column for time, and as many columns as clones/genotypes) into |
13 | 13 |
"long" format, so that it can be used with other functions, for |
14 | 14 |
instance for plots. |
... | ... |
@@ -43,16 +43,8 @@ OncoSimulWide2Long(x) |
43 | 43 |
} |
44 | 44 |
|
45 | 45 |
\examples{ |
46 |
-data(examplePosets) |
|
47 |
-## An object of class oncosimul |
|
48 |
-p705 <- examplePosets[["p705"]] |
|
49 |
-p1 <- oncoSimulIndiv(p705) |
|
50 |
-class(p1) |
|
51 |
-lp1 <- OncoSimulWide2Long(p1) |
|
52 |
-head(lp1) |
|
53 |
-summary(lp1) |
|
54 |
- |
|
55 |
-## An object of class oncosimul2 |
|
46 |
+ |
|
47 |
+ |
|
56 | 48 |
data(examplesFitnessEffects) |
57 | 49 |
|
58 | 50 |
sm <- oncoSimulIndiv(examplesFitnessEffects$cbn1, |
... | ... |
@@ -867,74 +867,13 @@ of the individual done, and the number of attempts and time used.} |
867 | 867 |
|
868 | 868 |
|
869 | 869 |
\seealso{ |
870 |
- \code{\link{plot.oncosimul}}, \code{\link{examplePosets}}, |
|
870 |
+ \code{\link{plot.oncosimul}}, |
|
871 | 871 |
\code{\link{samplePop}}, \code{\link{allFitnessEffects}} |
872 | 872 |
|
873 | 873 |
|
874 | 874 |
} |
875 | 875 |
\examples{ |
876 | 876 |
|
877 |
-################################# |
|
878 |
-##### |
|
879 |
-##### Examples using v.1 |
|
880 |
-##### |
|
881 |
-################################# |
|
882 |
- |
|
883 |
- |
|
884 |
-## use poset p701 |
|
885 |
-data(examplePosets) |
|
886 |
-p701 <- examplePosets[["p701"]] |
|
887 |
- |
|
888 |
-## Exp Model |
|
889 |
- |
|
890 |
-b1 <- oncoSimulIndiv(p701) |
|
891 |
-summary(b1) |
|
892 |
- |
|
893 |
-plot(b1, addtot = TRUE) |
|
894 |
- |
|
895 |
-## McFarland; use a small sampleEvery, but also a reasonable |
|
896 |
-## keepEvery. |
|
897 |
-## We also modify mutation rate to values similar to those in the |
|
898 |
-## original paper. |
|
899 |
-## Note that detectionSize will play no role |
|
900 |
-## finalTime is large, since this is a slower process |
|
901 |
-## initSize is set to 4000 so the default K is larger and we are likely |
|
902 |
-## to reach cancer. Alternatively, set K = 2000. |
|
903 |
- |
|
904 |
-m1 <- oncoSimulIndiv(p701, |
|
905 |
- model = "McFL", |
|
906 |
- mu = 5e-7, |
|
907 |
- initSize = 4000, |
|
908 |
- sampleEvery = 0.025, |
|
909 |
- finalTime = 15000, |
|
910 |
- keepEvery = 10, |
|
911 |
- onlyCancer = FALSE) |
|
912 |
-plot(m1, addtot = TRUE, log = "") |
|
913 |
- |
|
914 |
- |
|
915 |
- |
|
916 |
- |
|
917 |
-## Simulating 4 individual trajectories |
|
918 |
-## (I set mc.cores = 2 to comply with --as-cran checks, but you |
|
919 |
-## should either use a reasonable number for your hardware or |
|
920 |
-## leave it at its default value). |
|
921 |
- |
|
922 |
- |
|
923 |
-p1 <- oncoSimulPop(4, p701, |
|
924 |
- keepEvery = 10, |
|
925 |
- mc.cores = 2) |
|
926 |
-summary(p1) |
|
927 |
-samplePop(p1) |
|
928 |
- |
|
929 |
-p2 <- oncoSimulSample(4, p701) |
|
930 |
- |
|
931 |
- |
|
932 |
-######################################### |
|
933 |
-###### |
|
934 |
-###### Examples using v.2: |
|
935 |
-###### |
|
936 |
-######################################### |
|
937 |
- |
|
938 | 877 |
|
939 | 878 |
|
940 | 879 |
#### A model similar to the one in McFarland. We use 270 genes. |
... | ... |
@@ -1001,7 +940,7 @@ object.size(oiP1) |
1001 | 940 |
|
1002 | 941 |
|
1003 | 942 |
|
1004 |
-######## Using a poset for pancreatic cancer from Gerstung et al. |
|
943 |
+######## Using an extended poset for pancreatic cancer from Gerstung et al. |
|
1005 | 944 |
### (s and sh are made up for the example; only the structure |
1006 | 945 |
### and names come from Gerstung et al.) |
1007 | 946 |
|
... | ... |
@@ -1042,7 +981,7 @@ femuv <- allFitnessEffects(noIntGenes = ni) |
1042 | 981 |
oncoSimulIndiv(femuv, mu = muv) |
1043 | 982 |
} |
1044 | 983 |
|
1045 |
-#########Frequency dependent fitness examples |
|
984 |
+######### Frequency dependent fitness examples |
|
1046 | 985 |
|
1047 | 986 |
## An example with cooperation. Presence of WT favours all clones |
1048 | 987 |
## and all clones have a positive effect on themselves |
... | ... |
@@ -324,34 +324,6 @@ |
324 | 324 |
\code{\link{oncoSimulIndiv}} |
325 | 325 |
} |
326 | 326 |
\examples{ |
327 |
-\dontrun{ |
|
328 |
-data(examplePosets) |
|
329 |
-p701 <- examplePosets[["p701"]] |
|
330 |
- |
|
331 |
-## Simulate and plot a single individual, including showing |
|
332 |
-## Shannon's diversity index |
|
333 |
-b1 <- oncoSimulIndiv(p701) |
|
334 |
-plot(b1, addtot = TRUE, plotDiversity = TRUE) |
|
335 |
- |
|
336 |
-## A stacked area plot |
|
337 |
-plot(b1, type = "stacked", plotDiversity = TRUE) |
|
338 |
- |
|
339 |
-## And what if I show a stream plot? |
|
340 |
-plot(b1, type = "stream", plotDiversity = TRUE) |
|
341 |
- |
|
342 |
-## Simulate and plot 2 individuals |
|
343 |
-## (I set mc.cores = 2 to comply with --as-cran checks, but you |
|
344 |
-## should either use a reasonable number for your hardware or |
|
345 |
-## leave it at its default value). |
|
346 |
- |
|
347 |
-p1 <- oncoSimulPop(2, p701, mc.cores = 2) |
|
348 |
- |
|
349 |
-par(mfrow = c(1, 2)) |
|
350 |
-plot(p1, ask = FALSE) |
|
351 |
- |
|
352 |
-## Stacked; we cannot log here, and harder to see patterns |
|
353 |
-plot(p1, ask = FALSE, type = "stacked") |
|
354 |
-} |
|
355 | 327 |
|
356 | 328 |
## Show individual genotypes and drivers for an |
357 | 329 |
## epistasis case with at most eight genotypes |
... | ... |
@@ -41,6 +41,10 @@ |
41 | 41 |
This specification of restrictions is for version 1. See |
42 | 42 |
\code{\link{allFitnessEffects}} for a much more flexible one for |
43 | 43 |
version 2. Both can be used with \code{\link{oncoSimulIndiv}}. |
44 |
+ |
|
45 |
+ |
|
46 |
+ Note that simulating using posets directly is no longer |
|
47 |
+ supported. This function is left here only for historical purposes. |
|
44 | 48 |
} |
45 | 49 |
|
46 | 50 |
\references{ |
... | ... |
@@ -168,14 +168,26 @@ sampledGenotypes(y, genes = NULL) |
168 | 168 |
} |
169 | 169 |
|
170 | 170 |
\examples{ |
171 |
-data(examplePosets) |
|
172 |
-p705 <- examplePosets[["p705"]] |
|
171 |
+######## Using an extended poset for pancreatic cancer from Gerstung et al. |
|
172 |
+### (s and sh are made up for the example; only the structure |
|
173 |
+### and names come from Gerstung et al.) |
|
174 |
+ |
|
175 |
+ |
|
176 |
+pancr <- allFitnessEffects(data.frame(parent = c("Root", rep("KRAS", 4), "SMAD4", "CDNK2A", |
|
177 |
+ "TP53", "TP53", "MLL3"), |
|
178 |
+ child = c("KRAS","SMAD4", "CDNK2A", |
|
179 |
+ "TP53", "MLL3", |
|
180 |
+ rep("PXDN", 3), rep("TGFBR2", 2)), |
|
181 |
+ s = 0.15, |
|
182 |
+ sh = -0.3, |
|
183 |
+ typeDep = "MN")) |
|
184 |
+ |
|
173 | 185 |
|
174 | 186 |
## (I set mc.cores = 2 to comply with --as-cran checks, but you |
175 | 187 |
## should either use a reasonable number for your hardware or |
176 | 188 |
## leave it at its default value). |
177 | 189 |
|
178 |
-p1 <- oncoSimulPop(4, p705, mc.cores = 2) |
|
190 |
+p1 <- oncoSimulPop(4, pancr, mc.cores = 2) |
|
179 | 191 |
(sp1 <- samplePop(p1)) |
180 | 192 |
sampledGenotypes(sp1) |
181 | 193 |
|
... | ... |
@@ -190,7 +202,7 @@ sampledGenotypes(sp2) |
190 | 202 |
|
191 | 203 |
## Now single cell sampling |
192 | 204 |
|
193 |
-r1 <- oncoSimulIndiv(p705) |
|
205 |
+r1 <- oncoSimulIndiv(pancr) |
|
194 | 206 |
samplePop(r1, typeSample = "single") |
195 | 207 |
|
196 | 208 |
sampledGenotypes(samplePop(r1, typeSample = "single")) |
197 | 209 |
deleted file mode 100644 |
... | ... |
@@ -1,2314 +0,0 @@ |
1 |
-// Copyright 2013-2021 Ramon Diaz-Uriarte |
|
2 |
- |
|
3 |
-// This program is free software: you can redistribute it and/or modify |
|
4 |
-// it under the terms of the GNU General Public License as published by |
|
5 |
-// the Free Software Foundation, either version 3 of the License, or |
|
6 |
-// (at your option) any later version. |
|
7 |
- |
|
8 |
-// This program is distributed in the hope that it will be useful, |
|
9 |
-// but WITHOUT ANY WARRANTY; without even the implied warranty of |
|
10 |
-// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|
11 |
-// GNU General Public License for more details. |
|
12 |
- |
|
13 |
-// You should have received a copy of the GNU General Public License |
|
14 |
-// along with this program. If not, see <http://www.gnu.org/licenses/>. |
|
15 |
- |
|
16 |
- |
|
17 |
-#include "debug_common.h" |
|
18 |
-#include "common_classes.h" |
|
19 |
-#include "bnb_common.h" |
|
20 |
-#include <cfloat> |
|
21 |
-#include <limits> |
|
22 |
-#include <iostream> |
|
23 |
-#include <random> |
|
24 |
-#include <bitset> |
|
25 |
-#include <set> |
|
26 |
-#include <iterator> |
|
27 |
-#include <map> |
|
28 |
-#include <sstream> |
|
29 |
-#include <string> |
|
30 |
-#include <ctime> |
|
31 |
-#include <sys/time.h> |
|
32 |
- |
|
33 |
-#include <stdexcept> |
|
34 |
- |
|
35 |
-using namespace Rcpp; |
|
36 |
-using std::vector; |
|
37 |
- |
|
38 |
- |
|
39 |
-// To track if mutation is really much smaller than birth/death |
|
40 |
-#define MIN_RATIO_MUTS |
|
41 |
-#ifdef MIN_RATIO_MUTS |
|
42 |
-// There is really no need for these to be globals? |
|
43 |
-// Unless I wanted to use them inside some function. So leave as globals. |
|
44 |
-double g_min_birth_mut_ratio = DBL_MAX; |
|
45 |
-double g_min_death_mut_ratio = DBL_MAX; |
|
46 |
-double g_tmp1 = DBL_MAX; |
|
47 |
-#endif |
|
48 |
- |
|
49 |
- |
|
50 |
-typedef std::bitset<64> Genotype64; |
|
51 |
- |
|
52 |
- |
|
53 |
-// Format of restrictTable |
|
54 |
-// - mutations in columns |
|
55 |
-// - first row, the number |
|
56 |
-// - second row, the number of dependencies |
|
57 |
-// - rest of rows, the id of the dependency |
|
58 |
-// - past number of dependencies: a -9 |
|
59 |
-// In fact, the first row is redundant. Leave it, just in case. |
|
60 |
- |
|
61 |
- |
|
62 |
-// Genotypes: the first (or column 0) genotype is the all ceros. |
|
63 |
-// would not be needed, but makes Algo5 a lot simpler. |
|
64 |
- |
|
65 |
-// But mutatedPos start at 0. |
|
66 |
-// Will need to add 1 when plotting and analyzing with R. |
|
67 |
- |
|
68 |
-// Ojo: typeCBN is going to be an int. |
|
69 |
-// But from R we pass a string, and that determined the integer. |
|
70 |
- |
|
71 |
- |
|
72 |
-static void fitness(spParamsP& tmpP, |
|
73 |
- const spParamsP& parentP, |
|
74 |
- const int& mutatedPos, |
|
75 |
- Rcpp::IntegerMatrix restrictTable, |
|
76 |
- const std::string& typeCBN, |
|
77 |
- const Genotype64& newGenotype, |
|
78 |
- // const double& birthRate, |
|
79 |
- const double& s, |
|
80 |
- // const double& death, |
|
81 |
- const int& numDrivers, |
|
82 |
- const std::string& typeFitness, |
|
83 |
- // const double& genTime, |
|
84 |
- // const double& adjust_fitness_B, |
|
85 |
- const double& sh){ |
|
86 |
- //const double& adjust_fitness_MF) { |
|
87 |
- |
|
88 |
- using namespace Rcpp; |
|
89 |
- // Two pieces: split into two functions?? |
|
90 |
- // - checking restrictions |
|
91 |
- // - returning actual fitness according |
|
92 |
- |
|
93 |
- |
|
94 |
- int numDependencies; |
|
95 |
- int sumDriversMet = 0; |
|
96 |
- int sumDriversNoMet = 0; |
|
97 |
- int sumDependenciesMet = 0; |
|
98 |
- |
|
99 |
- // set appropriate defaults. Change only needed stuff. |
|
100 |
- tmpP.birth = parentP.birth; |
|
101 |
- tmpP.death = parentP.death; |
|
102 |
- tmpP.absfitness = parentP.absfitness; |
|
103 |
- |
|
104 |
- |
|
105 |
- |
|
106 |
- |
|
107 |
- |
|
108 |
- // **** Are driver constraints met? *** |
|
109 |
- |
|
110 |
- |
|
111 |
- // Two cases: same s, sh, sp or different ones. If same, return three |
|
112 |
- // integers: sumDriversMet, sumDriversNoMet, sumPassengers. If |
|
113 |
- // different, return three vectors, filled with the non-zero |
|
114 |
- // entries. These vectors then are combined as dictated by the fintness |
|
115 |
- // functions. |
|
116 |
- |
|
117 |
- // If same single s, sh, sp: function takes three integers. O.w. it |
|
118 |
- // takes three integer vectors. |
|
119 |
- |
|
120 |
- |
|
121 |
- |
|
122 |
- if(mutatedPos >= numDrivers) { //the new mutation is a passenger |
|
123 |
- return; |
|
124 |
- } else { |
|
125 |
- for(int m = 0; m < numDrivers; ++m) { |
|
126 |
- if( newGenotype[m] ) { // this m is mutated |
|
127 |
- const Rcpp::IntegerMatrix::Column thisRestrict = |
|
128 |
- restrictTable(_, m); |
|
129 |
- numDependencies = thisRestrict[1]; |
|
130 |
- if(!numDependencies) { // this driver has no dependencies |
|
131 |
- sumDriversMet++; |
|
132 |
-#ifdef DEBUGZ |
|
133 |
- Rcpp::Rcout << "\n No dependencies: "; |
|
134 |
- DP2(sumDriversMet); |
|
135 |
-#endif |
|
136 |
- |
|
137 |
- } |
|
138 |
- else { |
|
139 |
- sumDependenciesMet = 0; |
|
140 |
- for(int i = 2; i < (2 + numDependencies); i++) { |
|
141 |
- sumDependenciesMet += newGenotype[ thisRestrict[i] ]; |
|
142 |
- } |
|
143 |
- if( ( (typeCBN == "Multiple") && (sumDependenciesMet) ) || |
|
144 |
- ( (typeCBN == "CBN") && (sumDependenciesMet == numDependencies) )) { |
|
145 |
- sumDriversMet++; |
|
146 |
- } else { |
|
147 |
- sumDriversNoMet++; |
|
148 |
- } |
|
149 |
- } |
|
150 |
- } |
|
151 |
- } |
|
152 |
- } |
|
153 |
- |
|
154 |
-#ifdef DEBUGZ |
|
155 |
- DP2(sumDriversMet); |
|
156 |
- DP2(sumDriversNoMet); |
|
157 |
- DP2(sh); |
|
158 |
- DP2(typeFitness); |
|
159 |
-#endif |
|
160 |
- |
|
161 |
- // if sh < 0 : we do not allow any unment dependencies. |
|
162 |
- // if sh = 0: no penalty for unmet dependencies |
|
163 |
- |
|
164 |
- |
|
165 |
- // FIXME: why not just pass the birth and death rates, and combine them |
|
166 |
- // in arbitrary ways? Might even allow to pass on death and birth rates |
|
167 |
- // from R. Only need care when any are density dependent. |
|
168 |
- |
|
169 |
- |
|
170 |
- // Beware: doing it this way with Bozic1 is kind of questionable because |
|
171 |
- // if birth = 1, there is no immediate extinction. In fact, there never |
|
172 |
- // is. |
|
173 |
- if((sh < 0) && sumDriversNoMet) { |
|
174 |
- tmpP.absfitness = 0.0; |
|
175 |
- tmpP.death = 1.0; |
|
176 |
- tmpP.birth = 0.0; // this is what really matters so that |
|
177 |
- // the pop does not get added. |
|
178 |
- // Line with comment "fitness is 0" |
|
179 |
- } else { |
|
180 |
- if(typeFitness == "bozic1") { |
|
181 |
- tmpP.death = pow( 1.0 - s, sumDriversMet) * |
|
182 |
- pow( 1.0 + sh, sumDriversNoMet); |
|
183 |
- tmpP.birth = 1.0; |
|
184 |
- // } else if (typeFitness == "bozic2") { |
|
185 |
- // double pp = pow( 1.0 - s, sumDriversMet) * |
|
186 |
- // pow( 1.0 + sh, sumDriversNoMet); |
|
187 |
- // tmpP.birth = (1.0/genTime) * (1.0 - 0.5 * pp ); |
|
188 |
- // tmpP.death = (0.5/genTime) * pp; |
|
189 |
- // } else if(typeFitness == "beerenwinkel") { |
|
190 |
- // // like Datta et al., 2013 |
|
191 |
- // tmpP.absfitness = pow(1.0 + s, sumDriversMet) * |
|
192 |
- // pow( 1.0 - sh, sumDriversNoMet); |
|
193 |
- // tmpP.birth = adjust_fitness_B * tmpP.absfitness; |
|
194 |
- // } else if(typeFitness == "mcfarland0") { |
|
195 |
- // tmpP.absfitness = pow(1.0 + s, sumDriversMet) / |
|
196 |
- // pow( 1.0 + sh, sumDriversNoMet); |
|
197 |
- // tmpP.birth = adjust_fitness_MF * tmpP.absfitness; |
|
198 |
- // } else if(typeFitness == "mcfarland") { |
|
199 |
- // tmpP.birth = pow(1.0 + s, sumDriversMet) / |
|
200 |
- // pow( 1.0 + sh, sumDriversNoMet); |
|
201 |
- } else if(typeFitness == "mcfarlandlog") { |
|
202 |
- tmpP.birth = pow(1.0 + s, sumDriversMet) / |
|
203 |
- pow( 1.0 + sh, sumDriversNoMet); |
|
204 |
- } else if (typeFitness == "exp") { |
|
205 |
- // Also like Datta et al., 2013 An additional driver gene mutation |
|
206 |
- // increases a cell’s fitness by a factor of (1+sd), whereas an |
|
207 |
- // additional housekeeper gene mutation decreases fitness by a |
|
208 |
- // factor of (1-sh) and the effect of multiple mutations is |
|
209 |
- // multiplicative |
|
210 |
- tmpP.birth = pow(1.0 + s, sumDriversMet) * |
|
211 |
- pow( 1.0 - sh, sumDriversNoMet); |
|
212 |
- |
|
213 |
-#ifdef DEBUGZ |
|
214 |
- double posi = pow(1.0 + s, sumDriversMet); |
|
215 |
- double negi = pow( 1.0 - sh, sumDriversNoMet); |
|
216 |
- DP2(posi); |
|
217 |
- DP2(negi); |
|
218 |
-#endif |
|
219 |
- |
|
220 |
- } // else if (typeFitness == "log") { |
|
221 |
- // tmpP.birth = birthRate+ s * log1p(sumDriversMet) - |
|
222 |
- // sh * log(1 + sumDriversNoMet); |
|
223 |
- // } else { // linear |
|
224 |
- // tmpP.birth = birthRate + s * static_cast<double>(sumDriversMet) - |
|
225 |
- // sh * static_cast<double>(sumDriversNoMet); |
|
226 |
- // } |
|
227 |
- } |
|
228 |
-} |
|
229 |
-// Notice: if restriction is 3 -> 4 -> 5 |
|
230 |
-// and one has 5 and 4, only 4 is unmet. Beware of that. |
|
231 |
-// So we talk about the immediate dependency or restriction. |
|
232 |
-// Not the whole transitive closure. |
|
233 |
- |
|
234 |
-// When birth == 0, popSize should become 0 immediately. |
|
235 |
-// No evaluation through random numbers, etc. |
|
236 |
-// This is how we do it. |
|
237 |
- |
|
238 |
-// How small can they get? |
|
239 |
-// d1 <- function(s, mut) { (1 - s)^mut} |
|
240 |
-// d2 <- function(s, mut) { (0.5/4) * ((1 - s)^mut) } |
|
241 |
- |
|
242 |
- |
|
243 |
-// limited benchmarks suggest the following is slower |
|
244 |
-// static inline void new_sp_bitset2(unsigned int& sp, const Genotype64& newGenotype, |
|
245 |
-// const std::vector<Genotype64>& Genotypes) { |
|
246 |
-// sp = std::distance(Genotypes.begin(), |
|
247 |
-// std::find(Genotypes.begin(), |
|
248 |
-// Genotypes.end(), newGenotype)); |
|
249 |
-// } |
|
250 |
- |
|
251 |
- |
|
252 |
-static inline void new_sp_bitset(unsigned int& sp, const Genotype64& newGenotype, |
|
253 |
- const std::vector<Genotype64>& Genotypes) { |
|
254 |
- sp = 0; |
|
255 |
- |
|
256 |
- for(sp = 0; sp < Genotypes.size(); ++sp) { |
|
257 |
- if( newGenotype == Genotypes[sp] ) |
|
258 |
- break; |
|
259 |
- } |
|
260 |
-} |
|
261 |
- |
|
262 |
- |
|
263 |
- |
|
264 |
-static void getMutatedPos_bitset(int& mutatedPos, int& numMutablePosParent, |
|
265 |
- //gsl_rng *r, |
|
266 |
- std::mt19937& ran_generator, |
|
267 |
- std::vector<int>& mutablePos, |
|
268 |
- const Genotype64& nextMutantGenotype, |
|
269 |
- // const int& nextMutant, |
|
270 |
- // const std::vector<Genotype64>& Genotypes, |
|
271 |
- const int& numGenes) { |
|
272 |
- // We want mutatedPos and numMutablePosParent |
|
273 |
- |
|
274 |
- // Note: impossible to have a second recorded mutation in |
|
275 |
- // the same gene. |
|
276 |
- |
|
277 |
- // Remember numMutablePosParent is the number of mutable positions in |
|
278 |
- // the parent! so after mutation is one less, but we do not decrease it |
|
279 |
- // here. |
|
280 |
- |
|
281 |
- numMutablePosParent = 0; |
|
282 |
- for(int i = 0; i < numGenes; ++i) { |
|
283 |
- if( !nextMutantGenotype.test(i) ) { |
|
284 |
- mutablePos[numMutablePosParent] = i; |
|
285 |
- ++numMutablePosParent; |
|
286 |
- } |
|
287 |
- } |
|
288 |
- |
|
289 |
- if(numMutablePosParent > 1) { |
|
290 |
- std::uniform_int_distribution<int> unif(0, numMutablePosParent - 1); |
|
291 |
- mutatedPos = mutablePos[unif(ran_generator)]; |
|
292 |
- } else { |
|
293 |
- mutatedPos = mutablePos[0]; |
|
294 |
- } |
|
295 |
- |
|
296 |
- // if(numMutablePosParent > 1) { |
|
297 |
- // mutatedPos = mutablePos[gsl_rng_uniform_int(r, numMutablePosParent)]; |
|
298 |
- // } else { |
|
299 |
- // mutatedPos = mutablePos[0]; |
|
300 |
- // } |
|
301 |
- |
|
302 |
- |
|
303 |
-#ifdef DEBUGV |
|
304 |
- Rcpp::Rcout << "\n numMutablePosParent = " << numMutablePosParent; |
|
305 |
- Rcpp::Rcout << "\n mutatedPos = " << mutatedPos << "\n"; |
|
306 |
- |
|
307 |
-#endif |
|
308 |
- |
|
309 |
- // if(numMutablePos > 1) { |
|
310 |
- // mutatedPos = mutablePos[gsl_rng_uniform_int(r, numMutablePos)]; |
|
311 |
- // } else if (numMutablePos == 1) { |
|
312 |
- // mutatedPos = mutablePos[0]; |
|
313 |
- // } else { |
|
314 |
- // // Should never happen, as mutation = 0 if no mutable positions. |
|
315 |
- // throw std::out_of_range("Algo5: run out of mutable places!!??"); |
|
316 |
- // } |
|
317 |
- |
|
318 |
-} |
|
319 |
- |
|
320 |
- |
|
321 |
-static void remove_zero_sp_v7(std::vector<int>& sp_to_remove, |
|
322 |
- std::vector<Genotype64>& Genotypes, |
|
323 |
- std::vector<spParamsP>& popParams, |
|
324 |
- std::multimap<double, int>& mapTimes) { |
|
325 |
- // here("entering remove_zero_sp_v7"); |
|
326 |
- std::vector<spParamsP>::iterator popParams_begin = popParams.begin(); |
|
327 |
- std::vector<Genotype64>::iterator Genotypes_begin = Genotypes.begin(); |
|
328 |
- std::vector<int>::reverse_iterator r = sp_to_remove.rbegin(); |
|
329 |
- int remove_this; |
|
330 |
- // for(r = sp_to_remove.rbegin(); r != sp_to_remove.rend(); ++r) { |
|
331 |
- while(r != sp_to_remove.rend() ) { |
|
332 |
- remove_this = *r; |
|
333 |
- mapTimes.erase(popParams[remove_this].pv); |
|
334 |
- popParams.erase(popParams_begin + remove_this); |
|
335 |
- Genotypes.erase(Genotypes_begin + remove_this); |
|
336 |
- ++r; |
|
337 |
- } |
|
338 |
- // here("exiting remove_zero_sp_v7"); |
|
339 |
- |
|
340 |
-} |
|
341 |
- |
|
342 |
-static inline int count_NDrivers(const Genotype64& Genotype, |
|
343 |
- const int& NumDrivers) { |
|
344 |
- int totalDr = 0; |
|
345 |
- for(int i = 0; i < NumDrivers; ++i) |
|
346 |
- totalDr += Genotype[i]; |
|
347 |
- return totalDr; |
|
348 |
-} |
|
349 |
- |
|
350 |
-static void totPopSize_and_fill_out_crude_P(int& outNS_i, |
|
351 |
- double& totPopSize, |
|
352 |
- double& lastStoredSample, |
|
353 |
- std::vector<Genotype64>& genot_out, |
|
354 |
- //std::vector<unsigned long long>& sp_id_out, |
|
355 |
- std::vector<double>& popSizes_out, |
|
356 |
- std::vector<int>& index_out, |
|
357 |
- std::vector<double>& time_out, |
|
358 |
- std::vector<double>& sampleTotPopSize, |
|
359 |
- std::vector<double>& sampleLargestPopSize, |
|
360 |
- std::vector<int>& sampleMaxNDr, |
|
361 |
- std::vector<int>& sampleNDrLargestPop, |
|
362 |
- bool& simulsDone, |
|
363 |
- bool& reachDetection, |
|
364 |
- int& lastMaxDr, |
|
365 |
- double& done_at, |
|
366 |
- const std::vector<Genotype64>& Genotypes, |
|
367 |
- const std::vector<spParamsP>& popParams, |
|
368 |
- const double& currentTime, |
|
369 |
- const int& NumDrivers, |
|
370 |
- const double& keepEvery, |
|
371 |
- const double& detectionSize, |
|
372 |
- const double& finalTime, |
|
373 |
- // const double& endTimeEvery, |
|
374 |
- const int& detectionDrivers, |
|
375 |
- const int& verbosity, |
|
376 |
- const double& minDetectDrvCloneSz, |
|
377 |
- const double& extraTime, |
|
378 |
- const double& fatalPopSize = 1e15) { |
|
379 |
- // Fill out, but also compute totPopSize |
|
380 |
- // and return sample summaries for popsize, drivers. |
|
381 |
- |
|
382 |
- // This determines if we are done or not by checking popSize, number of |
|
383 |
- // drivers, etc |
|
384 |
- |
|
385 |
- // static int lastMaxDr = 0; // preserves value across calls to Algo5 from R. |
|
386 |
- // so can not use it. |
|
387 |
- bool storeThis = false; |
|
388 |
- totPopSize = 0.0; |
|
389 |
- |
|
390 |
- // DP2(lastMaxDr); |
|
391 |
- // DP2(detectionDrivers); |
|
392 |
- // DP2(currentTime); |
|
393 |
- // DP2((lastStoredSample + endTimeEvery)); |
|
394 |
- // DP2(detectionSize); |
|
395 |
- |
|
396 |
- // this could all be part of popSize_over_m_dr, with a better name |
|
397 |
- int tmp_ndr = 0; |
|
398 |
- int max_ndr = 0; |
|
399 |
- double popSizeOverDDr = 0.0; |
|
400 |
- |
|
401 |
- for(size_t i = 0; i < popParams.size(); ++i) { |
|
402 |
- totPopSize += popParams[i].popSize; |
|
403 |
- tmp_ndr = count_NDrivers(Genotypes[i], NumDrivers); |
|
404 |
- if(tmp_ndr > max_ndr) max_ndr = tmp_ndr; |
|
405 |
- if(tmp_ndr >= detectionDrivers) popSizeOverDDr += popParams[i].popSize; |
|
406 |
- } |
|
407 |
- lastMaxDr = max_ndr; |
|
408 |
- |
|
409 |
- |
|
410 |
- if (keepEvery < 0) { |
|
411 |
- storeThis = false; |
|
412 |
- } else if( currentTime >= (lastStoredSample + keepEvery) ) { |
|
413 |
- storeThis = true; |
|
414 |
- } |
|
415 |
- |
|
416 |
- if( (totPopSize <= 0.0) || (currentTime >= finalTime) ) { |
|
417 |
- simulsDone = true; |
|
418 |
- } |
|
419 |
- |
|
420 |
- |
|
421 |
- // if( (totPopSize >= detectionSize) || |
|
422 |
- // ( (lastMaxDr >= detectionDrivers) && |
|
423 |
- // (popSizeOverDDr >= minDetectDrvCloneSz) ) ) { |
|
424 |
- // simulsDone = true; |
|
425 |
- // reachDetection = true; |
|
426 |
- // } |
|
427 |
- |
|
428 |
- if(extraTime > 0) { |
|
429 |
- if(done_at < 0) { |
|
430 |
- if( (totPopSize >= detectionSize) || |
|
431 |
- ( (lastMaxDr >= detectionDrivers) && |
|
432 |
- (popSizeOverDDr >= minDetectDrvCloneSz) ) ) { |
|
433 |
- done_at = currentTime + extraTime; |
|
434 |
- } |
|
435 |
- } else if (currentTime >= done_at) { |
|
436 |
- simulsDone = true; |
|
437 |
- reachDetection = true; |
|
438 |
- } |
|
439 |
- } else if( (totPopSize >= detectionSize) || |
|
440 |
- ( (lastMaxDr >= detectionDrivers) && |
|
441 |
- (popSizeOverDDr >= minDetectDrvCloneSz) ) ) { |
|
442 |
- simulsDone = true; |
|
443 |
- reachDetection = true; |
|
444 |
- } |
|
445 |
- |
|
446 |
- |
|
447 |
- |
|
448 |
- |
|
449 |
- // This is no longer used. |
|
450 |
- // // Beware: this can lead to never stopping if |
|
451 |
- // // decreases in popSize or drivers |
|
452 |
- |
|
453 |
- // // Logic: if a period k you meet any condition, recheck again at k + |
|
454 |
- // // endTimeEvery, and if conditions met exit. Prevents exiting if you |
|
455 |
- // // reach the cancer state almost by chance. But this is way too |
|
456 |
- // // paranoid. The idea is of application mainly for McF and Beeren |
|
457 |
- // // models, so we do not bail out as soon as just a single cell with one |
|
458 |
- // // new driver. But this makes things very slow. |
|
459 |
- |
|
460 |
- // // Thus, never pass an endTimeEvery > 0, but use detectionDrivers = 1 + |
|
461 |
- // // intended final Drivers. |
|
462 |
- |
|
463 |
- // // FIXME |
|
464 |
- // // Ideally, we would check, for McFL, that popsize of the pop with |
|
465 |
- // // required number of drivers is at least, say, > initSize. |
|
466 |
- // // But that is not trivial, as requires more accounting. Do later. |
|
467 |
- |
|
468 |
- |
|
469 |
- // if(endTimeEvery > 0) { |
|
470 |
- // if(done_at <= 0 ) { |
|
471 |
- // if( (totPopSize >= detectionSize) || |
|
472 |
- // (lastMaxDr >= detectionDrivers) ) |
|
473 |
- // done_at = currentTime + endTimeEvery; |
|
474 |
- // } else if (currentTime >= done_at) { |
|
475 |
- // if( (totPopSize >= detectionSize) || |
|
476 |
- // (lastMaxDr >= detectionDrivers) ) { |
|
477 |
- // simulsDone = true; |
|
478 |
- // reachDetection = true; |
|
479 |
- // } |
|
480 |
- // else |
|
481 |
- // done_at = -9; |
|
482 |
- // } |
|
483 |
- // } else if( (totPopSize >= detectionSize) || |
|
484 |
- // (lastMaxDr >= detectionDrivers) ) { |
|
485 |
- |
|
486 |
- // simulsDone = true; |
|
487 |
- // reachDetection = true; |
|
488 |
- // } |
|
489 |
- |
|
490 |
- |
|
491 |
- if(totPopSize >= fatalPopSize) { |
|
492 |
- Rcpp::Rcout << "\n\totPopSize > " << fatalPopSize |
|
493 |
- <<". You are likely to loose precision and run into numerical issues\n"; |
|
494 |
- } |
|
495 |
- |
|
496 |
- if(simulsDone) |
|
497 |
- storeThis = true; |
|
498 |
- |
|
499 |
- |
|
500 |
- if( storeThis ) { |
|
501 |
- lastStoredSample = currentTime; |
|
502 |
- outNS_i++; |
|
503 |
- int ndr_lp = 0; |
|
504 |
- double l_pop_s = 0.0; |
|
505 |
- |
|
506 |
- time_out.push_back(currentTime); |
|
507 |
- |
|
508 |
- for(size_t i = 0; i < popParams.size(); ++i) { |
|
509 |
- genot_out.push_back(Genotypes[i]); |
|
510 |
- popSizes_out.push_back(popParams[i].popSize); |
|
511 |
- index_out.push_back(outNS_i); |
|
512 |
- |
|
513 |
- if(popParams[i].popSize > l_pop_s) { |
|
514 |
- l_pop_s = popParams[i].popSize; |
|
515 |
- ndr_lp = count_NDrivers(Genotypes[i], NumDrivers); |
|
516 |
- } |
|
517 |
- } |
|
518 |
- sampleTotPopSize.push_back(totPopSize); |
|
519 |
- sampleLargestPopSize.push_back(l_pop_s); |
|
520 |
- sampleMaxNDr.push_back(max_ndr); |
|
521 |
- sampleNDrLargestPop.push_back(ndr_lp); |
|
522 |
- } |
|
523 |
- |
|
524 |
- |
|
525 |
- |
|
526 |
- // if( storeThis ) { |
|
527 |
- // lastStoredSample = currentTime; |
|
528 |
- // outNS_i++; |
|
529 |
- // int tmp_ndr = 0; |
|
530 |
- // int max_ndr = 0; |
|
531 |
- // int ndr_lp = 0; |
|
532 |
- // double l_pop_s = 0.0; |
|
533 |
- |
|
534 |
- // time_out.push_back(currentTime); |
|
535 |
- |
|
536 |
- // for(size_t i = 0; i < popParams.size(); ++i) { |
|
537 |
- // genot_out.push_back(Genotypes[i]); |
|
538 |
- // popSizes_out.push_back(popParams[i].popSize); |
|
539 |
- // index_out.push_back(outNS_i); |
|
540 |
- // // I have to repeat the counting of drivers here. |
|
541 |
- // tmp_ndr = count_NDrivers(Genotypes[i], NumDrivers); |
|
542 |
- // if(tmp_ndr > max_ndr) max_ndr = tmp_ndr; |
|
543 |
- // if(popParams[i].popSize > l_pop_s) { |
|
544 |
- // l_pop_s = popParams[i].popSize; |
|
545 |
- // ndr_lp = tmp_ndr; |
|
546 |
- // // ndr_lp = count_NDrivers(Genotypes[i], NumDrivers); |
|
547 |
- // } |
|
548 |
- // // lastMaxDr = max_ndr; // and this should have been out of the |
|
549 |
- // // popParams.size() loop |
|
550 |
- // } |
|
551 |
- // // lastMaxDr = max_ndr; |
|
552 |
- // sampleTotPopSize.push_back(totPopSize); |
|
553 |
- // sampleLargestPopSize.push_back(l_pop_s); |
|
554 |
- // sampleMaxNDr.push_back(max_ndr); |
|
555 |
- // sampleNDrLargestPop.push_back(ndr_lp); |
|
556 |
- // }// else if (keepEvery < 0) { |
|
557 |
- // // FIXME keepEvery |
|
558 |
- // // must keep track of results to bail out |
|
559 |
- |
|
560 |
- // // FIXME counting max drivers should be done always, like counting |
|
561 |
- // // totPopSize. |
|
562 |
- |
|
563 |
- // int tmp_ndr = 0; |
|
564 |
- // int max_ndr = 0; |
|
565 |
- |
|
566 |
- // for(size_t i = 0; i < popParams.size(); ++i) { |
|
567 |
- // tmp_ndr = count_NDrivers(Genotypes[i], NumDrivers); |
|
568 |
- // if(tmp_ndr > max_ndr) max_ndr = tmp_ndr; |
|
569 |
- // // lastMaxDr = max_ndr; |
|
570 |
- // } |
|
571 |
- // lastMaxDr = max_ndr; |
|
572 |
- // } |
|
573 |
- |
|
574 |
- |
|
575 |
- |
|
576 |
- |
|
577 |
- if( !std::isfinite(totPopSize) ) { |
|
578 |
- throw std::range_error("totPopSize not finite"); |
|
579 |
- } |
|
580 |
- if( std::isnan(totPopSize) ) { |
|
581 |
- throw std::range_error("totPopSize is NaN"); |
|
582 |
- } |
|
583 |
- |
|
584 |
- if(totPopSize > (4.0 * 1e15)) { |
|
585 |
- if(verbosity > 0) |
|
586 |
- Rcpp::Rcout << "\nWARNING: popSize > 4e15. Likely loss of precission\n"; |
|
587 |
- } |
|
588 |
-} |
|
589 |
- |
|
590 |
-// FIXME: I might want to return the actual drivers in each period |
|
591 |
-// and the actual drivers in the population with largest popsize |
|
592 |
-// Something like what we do now with whichDrivers |
|
593 |
-// and count_NumDrivers |
|
594 |
- |
|
595 |
- |
|
596 |
-// static inline void fill_SStats(Rcpp::NumericMatrix& perSampleStats, |
|
597 |
-// const std::vector<double>& sampleTotPopSize, |
|
598 |
-// const std::vector<double>& sampleLargestPopSize, |
|
599 |
-// const std::vector<double>& sampleLargestPopProp, |
|
600 |
-// const std::vector<int>& sampleMaxNDr, |
|
601 |
-// const std::vector<int>& sampleNDrLargestPop){ |
|
602 |
- |
|
603 |
-// for(size_t i = 0; i < sampleTotPopSize.size(); ++i) { |
|
604 |
-// perSampleStats(i, 0) = sampleTotPopSize[i]; |
|
605 |
-// perSampleStats(i, 1) = sampleLargestPopSize[i]; // Never used in R FIXME: remove!! |
|
606 |
-// perSampleStats(i, 2) = sampleLargestPopProp[i]; // Never used in R |
|
607 |
-// perSampleStats(i, 3) = static_cast<double>(sampleMaxNDr[i]); |
|
608 |
-// perSampleStats(i, 4) = static_cast<double>(sampleNDrLargestPop[i]); |
|
609 |
-// } |
|
610 |
-// } |
|
611 |
- |
|
612 |
-inline void reshape_to_outNS(Rcpp::NumericMatrix& outNS, |
|
613 |
- const std::vector<unsigned long long>& uniqueGenotV, |
|
614 |
- const std::vector<unsigned long long>& genot_out_ul, |
|
615 |
- const std::vector<double>& popSizes_out, |
|
616 |
- const std::vector<int>& index_out, |
|
617 |
- const std::vector<double>& time_out){ |
|
618 |
- |
|
619 |
- std::vector<unsigned long long>::const_iterator fbeg = uniqueGenotV.begin(); |
|
620 |
- std::vector<unsigned long long>::const_iterator fend = uniqueGenotV.end(); |
|
621 |
- |
|
622 |
- int column; |
|
623 |
- |
|
624 |
- for(size_t i = 0; i < genot_out_ul.size(); ++i) { |
|
625 |
- column = std::distance(fbeg, lower_bound(fbeg, fend, genot_out_ul[i]) ); |
|
626 |
- // here(" looping over i "); |
|
627 |
- outNS(index_out[i], column + 1) = popSizes_out[i]; |
|
628 |
- } |
|
629 |
- |
|
630 |
- for(size_t j = 0; j < time_out.size(); ++j) |
|
631 |
- outNS(j, 0) = time_out[j]; |
|
632 |
-} |
|
633 |
- |
|
634 |
-static inline void find_unique_genotypes(std::set<unsigned long long>& uniqueGenotypes, |
|
635 |
- const std::vector<unsigned long long>& genot_out_l) { |
|
636 |
- for(size_t i = 0; i < genot_out_l.size(); ++i) |
|
637 |
- uniqueGenotypes.insert( genot_out_l[i] ); |
|
638 |
-} |
|
639 |
- |
|
640 |
-static inline void genot_out_to_ullong(std::vector<unsigned long long>& go_l, |
|
641 |
- const std::vector<Genotype64>& go) { |
|
642 |
- for(size_t i = 0; i < go.size(); ++i) |
|
643 |
- go_l[i] = go[i].to_ullong(); |
|
644 |
-} |
|
645 |
- |
|
646 |
- |
|
647 |
-static inline void uniqueGenotypes_to_vector(std::vector<unsigned long long>& ugV, |
|
648 |
- const std::set<unsigned long long>& uniqueGenotypes) { |
|
649 |
- ugV.assign(uniqueGenotypes.begin(), uniqueGenotypes.end() ); |
|
650 |
-} |
|
651 |
- |
|
652 |
- |
|
653 |
-static inline void create_returnGenotypes(Rcpp::IntegerMatrix& returnGenotypes, |
|
654 |
- const int& numGenes, |
|
655 |
- const std::vector<unsigned long long>& uniqueGenotypesV){ |
|
656 |
- // In C++, as the original were bitsets, pos 0 is at the right |
|
657 |
- // In R, pos 0 is at the left |
|
658 |
- |
|
659 |
- for(size_t i = 0; i < uniqueGenotypesV.size(); ++i) { |
|
660 |
- Genotype64 tmpbs(uniqueGenotypesV[i]); |
|
661 |
- for(int j = 0; j < numGenes; ++j) { |
|
662 |
- returnGenotypes(j, i) = tmpbs[j]; |
|
663 |
- } |
|
664 |
- } |
|
665 |
-} |
|
666 |
- |
|
667 |
-// FIXME: change this, now that we keep a count of drivers? |
|
668 |
-static inline void count_NumDrivers(int& maxNumDrivers, |
|
669 |
- std::vector<int>& countByDriver, |
|
670 |
- Rcpp::IntegerMatrix& returnGenotypes, |
|
671 |