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tests/testthat/test_peakPantheR_parallelAnnotation.R
In peakPantheR: Peak Picking and Annotation of High Resolution Experiments
context('peakPantheR_parallelAnnotation()')
skip_if_not_installed('faahKO', minimum_version = '1.18.0')
library(faahKO)
## Input and expected data
# 3 files
input_spectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
system.file('cdf/KO/ko16.CDF', package = "faahKO"),
system.file('cdf/KO/ko18.CDF', package = "faahKO"))
## 1 missing file
input_missingSpectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
"aaa/bbb.cdf",
system.file('cdf/KO/ko18.CDF', package = "faahKO"))
# 4 features
input_targetFeatTable <- data.frame(matrix(vector(), 4, 8, dimnames=list(c(), c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax"))),stringsAsFactors=FALSE)
input_targetFeatTable[1,] <- c("ID-1", "Cpd 1", 3310., 3344.888, 3390., 522.194778, 522.2, 522.205222)
input_targetFeatTable[2,] <- c("ID-2", "Cpd 2", 3280., 3385.577, 3440., 496.195038, 496.2, 496.204962)
input_targetFeatTable[3,] <- c("ID-3", "Cpd 3", 3420., 3454.435, 3495., 464.195358, 464.2, 464.204642)
input_targetFeatTable[4,] <- c("ID-4", "Cpd 4", 3670., 3701.697, 3745., 536.194638, 536.2, 536.205362)
input_targetFeatTable[,c(3:8)] <- sapply(input_targetFeatTable[,c(3:8)], as.numeric)
# FIR
input_FIR <- data.frame(matrix(vector(), 4, 4, dimnames=list(c(), c("rtMin", "rtMax", "mzMin", "mzMax"))),stringsAsFactors=FALSE)
input_FIR[1,] <- c(3336.542, 3390.272, 522.1995, 522.2005)
input_FIR[2,] <- c(3378.274, 3426.266, 496.1995, 496.2005)
input_FIR[3,] <- c(3444.524, 3478.431, 464.1995, 464.2005)
input_FIR[4,] <- c(3689.7, 3738.213, 536.1995, 536.2005)
input_FIR[,c(1:4)] <- sapply(input_FIR[,c(1:4)], as.numeric)
# uROI (ROI are wrong, uROI are right)
input_uROI <- input_targetFeatTable[,c("rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax")]
input_badtargetFeatTable <- input_targetFeatTable
input_badtargetFeatTable[1, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[2, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[3, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[4, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
# cpdMetadata
input_cpdMetadata <- data.frame(matrix(data=c('a','b','c','d',1,2,3,4), nrow=4, ncol=2, dimnames=list(c(),c('testcol1','testcol2')), byrow=FALSE), stringsAsFactors=FALSE)
# spectraMetadata
input_spectraMetadata <- data.frame(matrix(data=c('e','f','g',5,6,7), nrow=3, ncol=2, dimnames=list(c(),c('testcol1','testcol2')), byrow=FALSE), stringsAsFactors=FALSE)
# Expected peakTables
peakTable1 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable1[1,] <- c(TRUE, 3309.7589296586070, 3346.8277590361445, 3385.4098874628098, 522.194778, 522.20001220703125, 522.205222, 26133726.6811244078, 889280, 901015.80529226747, FALSE, 0.023376160866574614, 1.93975903614455092, 1.0153573486330891, 1.0268238825675249)
peakTable1[2,] <- c(TRUE, 3345.3766648628907, 3386.5288072289159, 3428.2788374983961, 496.20001220703125, 496.20001220703125, 496.20001220703125, 35472141.3330242932, 1128960, 1113576.69008227298, FALSE, 0.024601030353423384, 0.95180722891564074, 1.0053782620427065, 1.0093180792278085)
peakTable1[3,] <- c(TRUE, 3451.2075903614455, 3451.5072891566265, 3501.6697504924518, 464.195358, 464.20001220703125, 464.204642, 7498427.1583901159, 380736, 389632.13549519412, FALSE, 0.026296922148575364, -2.92771084337346110, 207.6939219686769036, 380.5019028782010082)
peakTable1[4,] <- c(TRUE, 3670.9201232710743, 3704.1427831325304, 3740.0172511251831, 536.20001220703125, 536.20001220703125, 536.20001220703125, 8626279.9788195733, 330176, 326763.87246511364, FALSE, 0.022765817240815486, 2.44578313253032320, 1.0305289730128095, 1.0536948855480386)
peakTable1[,c(1,11)] <- sapply(peakTable1[,c(1,11)], as.logical)
peakTable1[,c(2:10,12:15)] <- sapply(peakTable1[,c(2:10,12:15)], as.numeric)
# 2
peakTable2 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable2[1,] <- c(TRUE, 3326.1063495851854, 3365.102, 3407.2726475892355, 522.194778, 522.20001220703125, 522.205222, 24545301.622835573, 761664, 790802.2209998488, FALSE, 0.023376160866574614, 20.2139999999999, 1.0339153786516375, 1.0630802030537212)
peakTable2[2,] <- c(TRUE, 3365.0238566258713, 3405.791, 3453.4049569205681, 496.195038, 496.20001220703125, 496.204962, 37207579.286265120, 1099264, 1098720.2929832144, FALSE, 0.024601030353423384, 20.2139999999999, 1.0839602450900523, 1.1717845972583161)
peakTable2[3,] <- c(TRUE, 3425.9772908380342, 3466.1733975903617, 3508.0320324994614, 464.195358, 464.20001220703125, 464.204642, 11512269.4488430563, 366720, 365928.64209905855, FALSE, 0.026296922148575364, 11.738397590361728, 1.0157024674594695, 1.0275996777323413)
peakTable2[4,] <- c(TRUE, 3678.1204484629088, 3720.347, 3768.8011145239534, 536.194638, 536.20001220703125, 536.205362, 7983406.0412310315, 220096, 229651.947643013, FALSE, 0.022765817240815486, 18.65, 1.0738577621711971, 1.1514233243540024)
peakTable2[,c(1,11)] <- sapply(peakTable2[,c(1,11)], as.logical)
peakTable2[,c(2:10,12:15)] <- sapply(peakTable2[,c(2:10,12:15)], as.numeric)
# 3
peakTable3 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable3[1,] <- c(TRUE, 3333.8625894557053, 3368.233, 3407.4362838927614, 522.194778, 522.20001220703125, 522.205222, 21447174.404490683, 758336, 765009.9805796633, FALSE, 0.023376160866574614, 23.345000000000255, 1.0609102044546637, 1.1155310457756928)
peakTable3[2,] <- c(TRUE, 3373.3998828113113, 3413.4952530120481, 3454.4490330927388, 496.195038, 496.20001220703125, 496.204962, 35659353.614476241, 1149440, 1145857.7611069249, FALSE, 0.024601030353423384, 27.918253012047899, 1.0081407426394933, 1.0143315197994494)
peakTable3[3,] <- c(FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, NA, NA, NA, NA)
peakTable3[4,] <- c(TRUE, 3672.3110625980275, 3714.088, 3761.43921706666, 536.194638, 536.20001220703125, 536.205362, 6467062.4309558524, 196160, 189416.24807174454, FALSE, 0.022765817240815486, 12.391, 1.0656000616594850, 1.1333185588985102)
peakTable3[,c(1,11)] <- sapply(peakTable3[,c(1,11)], as.logical)
peakTable3[,c(2:10,12:15)] <- sapply(peakTable3[,c(2:10,12:15)], as.numeric)
expected_peakTables <- list(peakTable1, peakTable2, peakTable3)
# Expected peakFit
# 1
cFit1.1 <- list(amplitude=162404.8057918259, center=3341.888, sigma=0.078786133031045896, gamma=0.0018336101984172684, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.1) <- 'peakPantheR_curveFit'
cFit1.2 <- list(amplitude=199249.10572753669, center=3382.577, sigma=0.074904415304607966, gamma=0.0011471899372353885, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.2) <- 'peakPantheR_curveFit'
cFit1.3 <- list(amplitude=31645.961277502651, center=3451.435, sigma=0.064803553287811053, gamma=2.8557893789555022, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.3) <- 'peakPantheR_curveFit'
cFit1.4 <- list(amplitude=59193.591103772116, center=3698.697, sigma=0.082789238806238355, gamma=0.0026044299691057823, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.4) <- 'peakPantheR_curveFit'
# 2
cFit2.1 <- list(amplitude=124090.83425474487, center=3359.102, sigma=0.071061541060964212, gamma=0.0018336072657203239, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.1) <- 'peakPantheR_curveFit'
cFit2.2 <- list(amplitude=151407.23415130575, center=3399.791, sigma=0.063753866057052563, gamma=0.001676782834598999, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.2) <- 'peakPantheR_curveFit'
cFit2.3 <- list(amplitude=60803.292514896151, center=3460.824, sigma=0.072633009809671245, gamma=0.0015588615168115277, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.3) <- 'peakPantheR_curveFit'
cFit2.4 <- list(amplitude=31542.623023583215, center=3714.347, sigma=0.062820857630350654, gamma=0.0015366513073237947, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.4) <- 'peakPantheR_curveFit'
# 3
cFit3.1 <- list(amplitude=122363.51256736703, center=3362.233, sigma=0.075489598945304492, gamma=0.0025160536725299734, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.1) <- 'peakPantheR_curveFit'
cFit3.2 <- list(amplitude=204749.86097918145, center=3409.182, sigma=0.075731781812843249, gamma=0.0013318670577834328, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.2) <- 'peakPantheR_curveFit'
cFit3.3 <- NA
cFit3.4 <- list(amplitude=26628.505498512375, center=3708.088, sigma=0.064131129861254479, gamma=0.0015719426982490699, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.4) <- 'peakPantheR_curveFit'
expected_peakFit <- list(list(cFit1.1, cFit1.2, cFit1.3, cFit1.4), list(cFit2.1, cFit2.2, cFit2.3, cFit2.4), list(cFit3.1, cFit3.2, cFit3.3, cFit3.4))
# Expected dataPoints
tmp_raw_data1 <- MSnbase::readMSData(input_spectraPaths[1], centroided=TRUE, mode='onDisk')
ROIDataPoints1 <- extractSignalRawData(tmp_raw_data1, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
tmp_raw_data2 <- MSnbase::readMSData(input_spectraPaths[2], centroided=TRUE, mode='onDisk')
ROIDataPoints2 <- extractSignalRawData(tmp_raw_data2, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
tmp_raw_data3 <- MSnbase::readMSData(input_spectraPaths[3], centroided=TRUE, mode='onDisk')
ROIDataPoints3 <- extractSignalRawData(tmp_raw_data3, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
expected_dataPoints <- list(ROIDataPoints1, ROIDataPoints2, ROIDataPoints3)
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables
expected_annotation@peakFit <- expected_peakFit
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files (1 missing), 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
expected_annotation@peakTables <- expected_peakTables[c(1,3)]
expected_annotation@peakFit <- expected_peakFit[c(1,3)]
expected_annotation@dataPoints <- expected_dataPoints[c(1,3)]
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 2)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose, modify parameter with ... (cpd #3)', {
# Cpd 3 is now found in 3rd file
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Modify fit of window #3
tmp_params <- list(init_params = list(amplitude=1E5, center=3455., sigma=0.1, gamma=0),
lower_bounds = list(amplitude=0, center=3450., sigma=0, gamma=-0.1),
upper_bounds = list(amplitude=1E9, center=3460., sigma=5, gamma=0.1))
new_params <- list('guess', 'guess', tmp_params, 'guess')
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
# modify peakTable
tmp_peakTable1 <- expected_peakTables[[1]]
tmp_peakTable1[3,c(2:10,12:15)] <- c(3418.0076795585401, 3455.6277710843374, 3495.4734240188186, 464.195358, 464.2000122, 464.204642, 11307215.264967661, 380736, 381327.26552768378, 0.026296922148575364, 1.1927710843374371, 1.0223856861398346, 1.0391667928715738)
tmp_peakTable2 <- expected_peakTables[[2]]
tmp_peakTable2[3,c(2:10,12:15)] <- c(3433.0520428402692, 3464.1974939759039, 3518.3673814020449, 464.195358, 464.2000122, 464.204642, 11632481.39997852, 366720, 370275.43095360085, 0.026296922148575364, 9.762493975903908, 1.3108566292516153, 1.566712445298531)
tmp_peakTable3 <- expected_peakTables[[3]]
tmp_peakTable3[3,c(2:10,12:15)] <- c(3428.5236305028589, 3459.5514216867468, 3510.3107983995801, 464.195358, 464.2000122, 464.204642, 9697604.1795769241, 319488, 321005.94361925457, 0.026296922148575364, 5.1164216867468895, 1.2652077714541707, 1.4814479150398188)
tmp_peakTable3$found[3] <- TRUE
expected_annotation@peakTables <- list(tmp_peakTable1, tmp_peakTable2, tmp_peakTable3)
# modify curveFit
tmp_curveFit1.3 <- list(amplitude=64246.052173667762, center=3450, sigma=0.07533469863886906, gamma=0.0019238229766131536, fitStatus=2, curveModel="skewedGaussian")
class(tmp_curveFit1.3) <- 'peakPantheR_curveFit'
tmp_curveFit2.3 <- list(amplitude=31499.356902732343, center=3454.217764223421, sigma=0.052005180846722628, gamma=0.0030181085286239786, fitStatus=1, curveModel="skewedGaussian")
class(tmp_curveFit2.3) <- 'peakPantheR_curveFit'
tmp_curveFit3.3 <- list(amplitude=29842.598057228814, center=3450, sigma=0.055439446898995937, gamma=0.0031338189157350213, fitStatus=2, curveModel="skewedGaussian")
class(tmp_curveFit3.3) <- 'peakPantheR_curveFit'
expected_annotation@peakFit <- expected_peakFit
expected_annotation@peakFit[[1]][[3]] <- tmp_curveFit1.3
expected_annotation@peakFit[[2]][[3]] <- tmp_curveFit2.3
expected_annotation@peakFit[[3]][[3]] <- tmp_curveFit3.3
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, params=new_params))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose, peaks not found and not replaced (cpd #3)', {
# Cpd #3 will not give results
noMatch_ROI3 <- input_targetFeatTable
noMatch_ROI3[3,6:8] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=noMatch_ROI3, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
tmp_peakTables <- expected_peakTables
tmp_peakTables[[1]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[1]]$found[3] <- FALSE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[2]]$found[3] <- FALSE
tmp_peakTables[[3]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[3]]$found[3] <- FALSE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
tmp_peakFit[[3]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[3]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('3 files, 4 compounds, no uROI, FIR replace peaks not found (cpd #3), no getAcquTime, no verbose', {
# Cpd #3 will not give results, FIR will replace
noMatch_ROI3 <- input_targetFeatTable
noMatch_ROI3[3,6:8] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=noMatch_ROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
tmp_peakTables <- expected_peakTables
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3463.824, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8675223.6101818271, 366720, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$is_filled[3] <- TRUE
tmp_peakTables[[3]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[3]]$found[3] <- TRUE
tmp_peakTables[[3]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
tmp_peakFit[[3]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[3]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files, 4 compounds, uROI, no FIR, no fitGauss, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=input_uROI, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables
expected_annotation@peakFit <- expected_peakFit
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
test_that('serial: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----- ko15 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Fit of ROI #3 is unsuccessful (try error)\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "Error file does not exist: aaa/bbb.cdf\n", "----- ko18 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #2\n", "Fit of ROI #3 is unsuccessful (try error)\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #4\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 40)
expect_equal(result_parallelAnnotation$messages[c(1:7,9,10,13,14,18:22,24:27,30,31,35,36,37,38,40)], expected_message)
})
test_that('parallel (with cluster reset): 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "Running 3 clusters of 1 files over 1 cores:\n", " starting cluster 1/3\n", " starting cluster 2/3\n", " starting cluster 3/3\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=1, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 13)
expect_equal(result_parallelAnnotation$messages[c(1:11,13)], expected_message)
})
test_that('parallel (without cluster reset): 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=0, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 9)
expect_equal(result_parallelAnnotation$messages[c(1:7,9)], expected_message)
})
test_that('serial and parallel (with cluster reset) give the same result: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# results
result_serial <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
result_parallel <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=1, verbose=TRUE))
# Check results
expect_equal(result_serial$result, result_parallel$result, tolerance=1e-6)
})
test_that('serial and parallel (without cluster reset) give the same result: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# results
result_serial <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
result_parallel <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=0, verbose=TRUE))
# Check results
expect_equal(result_serial$result, result_parallel$result, tolerance=1e-6)
})
test_that('change to resetWorkers alters the number of parallel cluster reset', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "Running 2 clusters of 2 files over 1 cores:\n", " starting cluster 1/2\n", " starting cluster 2/2\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=2, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 12)
expect_equal(result_parallelAnnotation$messages[c(1:10,12)], expected_message)
})
test_that('already annotated message in verbose', {
# use "serial: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose"
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, isAnnotated=TRUE, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("!! Data was already annotated, results will be overwritten !!\n", "Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----- ko15 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Fit of ROI #3 is unsuccessful (try error)\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "Error file does not exist: aaa/bbb.cdf\n", "----- ko18 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #2\n", "Fit of ROI #3 is unsuccessful (try error)\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #4\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 41)
expect_equal(result_parallelAnnotation$messages[c(1:8,10,11,14,15,19:23,25:28,31,32,36,37,38,39,41)], expected_message)
})
test_that('catch file that doesnt exist, catch error processing, no file left', {
# Object fully initialised
wrongPaths <- c("aaa/bbb.cdf", system.file("extdata/test_fakemzML.mzML", package = "peakPantheR"))
initAnnotation <- peakPantheRAnnotation(spectraPaths=wrongPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(FALSE, FALSE),]
expected_annotation@isAnnotated <- FALSE
# Expected message
expected_message <- c("Processing 4 compounds in 2 samples:\n", " uROI:\tFALSE\n", " FIR:\tFALSE\n", "Error file does not exist: aaa/bbb.cdf\n", "----- test_fakemzML -----\n", "-----\n", "Error processing file: test_fakemzML\n", "\n-----\n", "----------------\n", "No file left in the object!\n", "Annotation object reordered by sample acquisition date\n", "----------------\n", " 2 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
# cannot check the failure paths
expect_equal(dim(result_parallelAnnotation$result$failures)[1], 2)
expect_equal(dim(result_parallelAnnotation$result$failures)[2], 2)
# Check messages (remove timing and paths in error messages)
expect_equal(length(result_parallelAnnotation$messages), 16)
expect_equal(result_parallelAnnotation$messages[c(1:7, 9, 10, 12, 13, 14, 16)], expected_message)
})
test_that('curveModel emgGaussian: 3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected peakFit
# 1
cFit1.1emg <- list(amplitude=22322950, center=3341.888, sigma=5, gamma=0.09934113, fitStatus=2, curveModel="emgGaussian")
class(cFit1.1emg) <- 'peakPantheR_curveFit'
cFit1.2emg <- list(amplitude=29181384, center=3382.577, sigma=5, gamma=0.08974434, fitStatus=2, curveModel="emgGaussian")
class(cFit1.2emg) <- 'peakPantheR_curveFit'
cFit1.3emg <- list(amplitude=9173607, center=3451.435, sigma=5, gamma=0.1071507, fitStatus=2, curveModel="emgGaussian")
class(cFit1.3emg) <- 'peakPantheR_curveFit'
cFit1.4emg <- list(amplitude=7719709, center=3698.697, sigma=5, gamma=0.1060304, fitStatus=2, curveModel="emgGaussian")
class(cFit1.4emg) <- 'peakPantheR_curveFit'
# 2
cFit2.1emg <- list(amplitude=22094946, center=3359.102, sigma=5, gamma=0.07724317, fitStatus=2, curveModel="emgGaussian")
class(cFit2.1emg) <- 'peakPantheR_curveFit'
cFit2.2emg <- list(amplitude=34397901, center=3399.791, sigma=5, gamma=0.0651969, fitStatus=2, curveModel="emgGaussian")
class(cFit2.2emg) <- 'peakPantheR_curveFit'
cFit2.3emg <- list(amplitude=9671145, center=3460.824, sigma=5, gamma=0.08864798, fitStatus=2, curveModel="emgGaussian")
class(cFit2.3emg) <- 'peakPantheR_curveFit'
cFit2.4emg <- list(amplitude=7296689, center=3714.347, sigma=5, gamma=0.06171862, fitStatus=2, curveModel="emgGaussian")
class(cFit2.4emg) <- 'peakPantheR_curveFit'
# 3
cFit3.1emg <- list(amplitude=20390552, center=3362.233, sigma=5, gamma=0.08186031, fitStatus=2, curveModel="emgGaussian")
class(cFit3.1emg) <- 'peakPantheR_curveFit'
cFit3.2emg <- list(amplitude=29719102, center=3409.182, sigma=5, gamma=0.09218107, fitStatus=2, curveModel="emgGaussian")
class(cFit3.2emg) <- 'peakPantheR_curveFit'
cFit3.3emg <- NA
cFit3.4emg <- list(amplitude=5751872, center=3708.088, sigma=5, gamma=0.06964929, fitStatus=2, curveModel="emgGaussian")
class(cFit3.4emg) <- 'peakPantheR_curveFit'
expected_peakFit_emg <- list(list(cFit1.1emg, cFit1.2emg, cFit1.3emg, cFit1.4emg), list(cFit2.1emg, cFit2.2emg, cFit2.3emg, cFit2.4emg), list(cFit3.1emg, cFit3.2emg, cFit3.3emg, cFit3.4emg))
# Expected peakTables
peakTable1emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable1emg[1,] <- c(TRUE, 3327.999, 3346.996, 3403.919, 522.1948, 522.2, 522.2052, 22261723, 889280, 1057506.5, FALSE, 0.02337616, 2.108434, 1.653451, 2.064384)
peakTable1emg[2,] <- c(TRUE, 3368.739, 3387.926, 3450.433, 496.1950, 496.2, 496.2050, 29098356, 1128960, 1313099.4, FALSE, 0.02460103, 2.349398, 1.745483, 2.219176)
peakTable1emg[3,] <- c(TRUE, 3437.496, 3456.351, 3509.499, 464.1954, 464.2, 464.2046, 9149178, 380736, 450748.4, FALSE, 0.02629692, 1.915663, 1.592171, 1.962157)
peakTable1emg[4,] <- c(TRUE, 3684.765, 3703.637, 3757.294, 536.1946, 536.2, 536.2054, 7699066, 330176, 377425.9, FALSE, 0.02276582, 1.939759, 1.600693, 1.976502)
peakTable1emg[,c(1,11)] <- sapply(peakTable1emg[,c(1,11)], as.logical)
peakTable1emg[,c(2:10,12:15)] <- sapply(peakTable1emg[,c(2:10,12:15)], as.numeric)
# 2
peakTable2emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable2emg[1,] <- c(TRUE, 3345.357, 3364.813, 3436.703, 522.1948, 522.2, 522.2052, 22028618, 761664, 916975.6, FALSE, 0.02337616, 19.92484, 1.898412, 2.477039)
peakTable2emg[2,] <- c(TRUE, 3386.117, 3405.791, 3490.313, 496.1950, 496.2, 496.2050, 34288936, 1099264, 1293794.6, FALSE, 0.02460103, 20.21400, 2.116160, 2.850792)
peakTable2emg[3,] <- c(TRUE, 3447.002, 3466.197, 3529.422, 464.1954, 464.2, 464.2046, 9643477, 366720, 432400.6, FALSE, 0.02629692, 11.76249, 1.757855, 2.240265)
peakTable2emg[4,] <- c(TRUE, 3700.724, 3720.347, 3809.535, 536.1946, 536.2, 536.2054, 7273154, 220096, 265357.4, FALSE, 0.02276582, 18.65000, 2.207992, 3.012906)
peakTable2emg[,c(1,11)] <- sapply(peakTable2emg[,c(1,11)], as.logical)
peakTable2emg[,c(2:10,12:15)] <- sapply(peakTable2emg[,c(2:10,12:15)], as.numeric)
# 3
peakTable3emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable3emg[1,] <- c(TRUE, 3348.458, 3367.799, 3435.888, 522.1948, 522.2, 522.2052, 20330539, 758336, 873749.6, FALSE, 0.02337616, 22.91127, 1.837158, 2.373902)
peakTable3emg[2,] <- c(TRUE, 3395.322, 3414.459, 3475.443, 496.1950, 496.2, 496.2050, 29635397, 1149440, 1355916.7, FALSE, 0.02460103, 28.88211, 1.721309, 2.178978)
peakTable3emg[3,] <- c(FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, NA, NA, NA, NA)
peakTable3emg[4,] <- c(TRUE, 3694.401, 3714.064, 3793.313, 536.1946, 536.2, 536.2054, 5734001, 196160, 225006.2, FALSE, 0.02276582, 12.36690, 2.015364, 2.673714)
peakTable3emg[,c(1,11)] <- sapply(peakTable3emg[,c(1,11)], as.logical)
peakTable3emg[,c(2:10,12:15)] <- sapply(peakTable3emg[,c(2:10,12:15)], as.numeric)
expected_peakTables_emg <- list(peakTable1emg, peakTable2emg, peakTable3emg)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables_emg
expected_annotation@peakFit <- expected_peakFit_emg
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Fit of ROI #3 is unsuccessful (cannot determine rtMin/rtMax)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, curveModel='emgGaussian'))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 4)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('curveModel unknown: 3 failures', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- peakPantheRAnnotation(targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata)
expected_annotation@spectraMetadata <- data.frame(matrix(character(), ncol=2, byrow=FALSE, dimnames=list(c(), c('testcol1', 'testcol2'))), stringsAsFactors=FALSE)
#expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
#expected_annotation@peakTables <- expected_peakTables
#expected_annotation@peakFit <- expected_peakFit
#expected_annotation@dataPoints <- expected_dataPoints
#expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- c('Error: "curveModel" must be one of: skewedGaussian, emgGaussian','Error: "curveModel" must be one of: skewedGaussian, emgGaussian','Error: "curveModel" must be one of: skewedGaussian, emgGaussian')
names(tmp_status) <- input_spectraPaths
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- character(0)
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, curveModel='unknown_curveModel'))
# Check results (all failures)
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no fit, so no message)
expect_equal(length(result_parallelAnnotation$messages), 0)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('raise errors', {
# Object fails validation on input check
wrongInit <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
wrongInit@TIC <- c(1, 2)
msg1 <- paste('invalid class ', dQuote('peakPantheRAnnotation'),' object: TIC has 2 elements (samples). Should be 3', sep='')
expect_error(peakPantheR_parallelAnnotation(wrongInit, ncores=0, getAcquTime=FALSE, verbose=FALSE), msg1, fixed=TRUE)
# resetWorkers is not an integer
initAnnotation2 <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
msg2 <- "Check input, resetWorkers must be an integer"
expect_error(peakPantheR_parallelAnnotation(initAnnotation2, ncores=0, getAcquTime=FALSE, resetWorkers='not an Integer', verbose=FALSE), msg2, fixed=TRUE)
# resetWorkers is < 0
initAnnotation3 <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
msg3 <- "Check input, resetWorkers must be a positive integer"
expect_error(peakPantheR_parallelAnnotation(initAnnotation3, ncores=0, getAcquTime=FALSE, resetWorkers=-10, verbose=FALSE), msg3, fixed=TRUE)
})
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peakPantheR documentation built on Nov. 8, 2020, 6:38 p.m.
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context('peakPantheR_parallelAnnotation()')
skip_if_not_installed('faahKO', minimum_version = '1.18.0')
library(faahKO)
## Input and expected data
# 3 files
input_spectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
system.file('cdf/KO/ko16.CDF', package = "faahKO"),
system.file('cdf/KO/ko18.CDF', package = "faahKO"))
## 1 missing file
input_missingSpectraPaths <- c(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
"aaa/bbb.cdf",
system.file('cdf/KO/ko18.CDF', package = "faahKO"))
# 4 features
input_targetFeatTable <- data.frame(matrix(vector(), 4, 8, dimnames=list(c(), c("cpdID", "cpdName", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax"))),stringsAsFactors=FALSE)
input_targetFeatTable[1,] <- c("ID-1", "Cpd 1", 3310., 3344.888, 3390., 522.194778, 522.2, 522.205222)
input_targetFeatTable[2,] <- c("ID-2", "Cpd 2", 3280., 3385.577, 3440., 496.195038, 496.2, 496.204962)
input_targetFeatTable[3,] <- c("ID-3", "Cpd 3", 3420., 3454.435, 3495., 464.195358, 464.2, 464.204642)
input_targetFeatTable[4,] <- c("ID-4", "Cpd 4", 3670., 3701.697, 3745., 536.194638, 536.2, 536.205362)
input_targetFeatTable[,c(3:8)] <- sapply(input_targetFeatTable[,c(3:8)], as.numeric)
# FIR
input_FIR <- data.frame(matrix(vector(), 4, 4, dimnames=list(c(), c("rtMin", "rtMax", "mzMin", "mzMax"))),stringsAsFactors=FALSE)
input_FIR[1,] <- c(3336.542, 3390.272, 522.1995, 522.2005)
input_FIR[2,] <- c(3378.274, 3426.266, 496.1995, 496.2005)
input_FIR[3,] <- c(3444.524, 3478.431, 464.1995, 464.2005)
input_FIR[4,] <- c(3689.7, 3738.213, 536.1995, 536.2005)
input_FIR[,c(1:4)] <- sapply(input_FIR[,c(1:4)], as.numeric)
# uROI (ROI are wrong, uROI are right)
input_uROI <- input_targetFeatTable[,c("rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax")]
input_badtargetFeatTable <- input_targetFeatTable
input_badtargetFeatTable[1, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[2, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[3, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
input_badtargetFeatTable[4, c("rtMin", "rtMax", "mzMin", "mzMax")] <- c(0,10000, 0,1000)
# cpdMetadata
input_cpdMetadata <- data.frame(matrix(data=c('a','b','c','d',1,2,3,4), nrow=4, ncol=2, dimnames=list(c(),c('testcol1','testcol2')), byrow=FALSE), stringsAsFactors=FALSE)
# spectraMetadata
input_spectraMetadata <- data.frame(matrix(data=c('e','f','g',5,6,7), nrow=3, ncol=2, dimnames=list(c(),c('testcol1','testcol2')), byrow=FALSE), stringsAsFactors=FALSE)
# Expected peakTables
peakTable1 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable1[1,] <- c(TRUE, 3309.7589296586070, 3346.8277590361445, 3385.4098874628098, 522.194778, 522.20001220703125, 522.205222, 26133726.6811244078, 889280, 901015.80529226747, FALSE, 0.023376160866574614, 1.93975903614455092, 1.0153573486330891, 1.0268238825675249)
peakTable1[2,] <- c(TRUE, 3345.3766648628907, 3386.5288072289159, 3428.2788374983961, 496.20001220703125, 496.20001220703125, 496.20001220703125, 35472141.3330242932, 1128960, 1113576.69008227298, FALSE, 0.024601030353423384, 0.95180722891564074, 1.0053782620427065, 1.0093180792278085)
peakTable1[3,] <- c(TRUE, 3451.2075903614455, 3451.5072891566265, 3501.6697504924518, 464.195358, 464.20001220703125, 464.204642, 7498427.1583901159, 380736, 389632.13549519412, FALSE, 0.026296922148575364, -2.92771084337346110, 207.6939219686769036, 380.5019028782010082)
peakTable1[4,] <- c(TRUE, 3670.9201232710743, 3704.1427831325304, 3740.0172511251831, 536.20001220703125, 536.20001220703125, 536.20001220703125, 8626279.9788195733, 330176, 326763.87246511364, FALSE, 0.022765817240815486, 2.44578313253032320, 1.0305289730128095, 1.0536948855480386)
peakTable1[,c(1,11)] <- sapply(peakTable1[,c(1,11)], as.logical)
peakTable1[,c(2:10,12:15)] <- sapply(peakTable1[,c(2:10,12:15)], as.numeric)
# 2
peakTable2 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable2[1,] <- c(TRUE, 3326.1063495851854, 3365.102, 3407.2726475892355, 522.194778, 522.20001220703125, 522.205222, 24545301.622835573, 761664, 790802.2209998488, FALSE, 0.023376160866574614, 20.2139999999999, 1.0339153786516375, 1.0630802030537212)
peakTable2[2,] <- c(TRUE, 3365.0238566258713, 3405.791, 3453.4049569205681, 496.195038, 496.20001220703125, 496.204962, 37207579.286265120, 1099264, 1098720.2929832144, FALSE, 0.024601030353423384, 20.2139999999999, 1.0839602450900523, 1.1717845972583161)
peakTable2[3,] <- c(TRUE, 3425.9772908380342, 3466.1733975903617, 3508.0320324994614, 464.195358, 464.20001220703125, 464.204642, 11512269.4488430563, 366720, 365928.64209905855, FALSE, 0.026296922148575364, 11.738397590361728, 1.0157024674594695, 1.0275996777323413)
peakTable2[4,] <- c(TRUE, 3678.1204484629088, 3720.347, 3768.8011145239534, 536.194638, 536.20001220703125, 536.205362, 7983406.0412310315, 220096, 229651.947643013, FALSE, 0.022765817240815486, 18.65, 1.0738577621711971, 1.1514233243540024)
peakTable2[,c(1,11)] <- sapply(peakTable2[,c(1,11)], as.logical)
peakTable2[,c(2:10,12:15)] <- sapply(peakTable2[,c(2:10,12:15)], as.numeric)
# 3
peakTable3 <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable3[1,] <- c(TRUE, 3333.8625894557053, 3368.233, 3407.4362838927614, 522.194778, 522.20001220703125, 522.205222, 21447174.404490683, 758336, 765009.9805796633, FALSE, 0.023376160866574614, 23.345000000000255, 1.0609102044546637, 1.1155310457756928)
peakTable3[2,] <- c(TRUE, 3373.3998828113113, 3413.4952530120481, 3454.4490330927388, 496.195038, 496.20001220703125, 496.204962, 35659353.614476241, 1149440, 1145857.7611069249, FALSE, 0.024601030353423384, 27.918253012047899, 1.0081407426394933, 1.0143315197994494)
peakTable3[3,] <- c(FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, NA, NA, NA, NA)
peakTable3[4,] <- c(TRUE, 3672.3110625980275, 3714.088, 3761.43921706666, 536.194638, 536.20001220703125, 536.205362, 6467062.4309558524, 196160, 189416.24807174454, FALSE, 0.022765817240815486, 12.391, 1.0656000616594850, 1.1333185588985102)
peakTable3[,c(1,11)] <- sapply(peakTable3[,c(1,11)], as.logical)
peakTable3[,c(2:10,12:15)] <- sapply(peakTable3[,c(2:10,12:15)], as.numeric)
expected_peakTables <- list(peakTable1, peakTable2, peakTable3)
# Expected peakFit
# 1
cFit1.1 <- list(amplitude=162404.8057918259, center=3341.888, sigma=0.078786133031045896, gamma=0.0018336101984172684, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.1) <- 'peakPantheR_curveFit'
cFit1.2 <- list(amplitude=199249.10572753669, center=3382.577, sigma=0.074904415304607966, gamma=0.0011471899372353885, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.2) <- 'peakPantheR_curveFit'
cFit1.3 <- list(amplitude=31645.961277502651, center=3451.435, sigma=0.064803553287811053, gamma=2.8557893789555022, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.3) <- 'peakPantheR_curveFit'
cFit1.4 <- list(amplitude=59193.591103772116, center=3698.697, sigma=0.082789238806238355, gamma=0.0026044299691057823, fitStatus=2, curveModel="skewedGaussian")
class(cFit1.4) <- 'peakPantheR_curveFit'
# 2
cFit2.1 <- list(amplitude=124090.83425474487, center=3359.102, sigma=0.071061541060964212, gamma=0.0018336072657203239, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.1) <- 'peakPantheR_curveFit'
cFit2.2 <- list(amplitude=151407.23415130575, center=3399.791, sigma=0.063753866057052563, gamma=0.001676782834598999, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.2) <- 'peakPantheR_curveFit'
cFit2.3 <- list(amplitude=60803.292514896151, center=3460.824, sigma=0.072633009809671245, gamma=0.0015588615168115277, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.3) <- 'peakPantheR_curveFit'
cFit2.4 <- list(amplitude=31542.623023583215, center=3714.347, sigma=0.062820857630350654, gamma=0.0015366513073237947, fitStatus=2, curveModel="skewedGaussian")
class(cFit2.4) <- 'peakPantheR_curveFit'
# 3
cFit3.1 <- list(amplitude=122363.51256736703, center=3362.233, sigma=0.075489598945304492, gamma=0.0025160536725299734, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.1) <- 'peakPantheR_curveFit'
cFit3.2 <- list(amplitude=204749.86097918145, center=3409.182, sigma=0.075731781812843249, gamma=0.0013318670577834328, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.2) <- 'peakPantheR_curveFit'
cFit3.3 <- NA
cFit3.4 <- list(amplitude=26628.505498512375, center=3708.088, sigma=0.064131129861254479, gamma=0.0015719426982490699, fitStatus=2, curveModel="skewedGaussian")
class(cFit3.4) <- 'peakPantheR_curveFit'
expected_peakFit <- list(list(cFit1.1, cFit1.2, cFit1.3, cFit1.4), list(cFit2.1, cFit2.2, cFit2.3, cFit2.4), list(cFit3.1, cFit3.2, cFit3.3, cFit3.4))
# Expected dataPoints
tmp_raw_data1 <- MSnbase::readMSData(input_spectraPaths[1], centroided=TRUE, mode='onDisk')
ROIDataPoints1 <- extractSignalRawData(tmp_raw_data1, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
tmp_raw_data2 <- MSnbase::readMSData(input_spectraPaths[2], centroided=TRUE, mode='onDisk')
ROIDataPoints2 <- extractSignalRawData(tmp_raw_data2, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
tmp_raw_data3 <- MSnbase::readMSData(input_spectraPaths[3], centroided=TRUE, mode='onDisk')
ROIDataPoints3 <- extractSignalRawData(tmp_raw_data3, rt=input_targetFeatTable[,c('rtMin','rtMax')], mz=input_targetFeatTable[,c('mzMin','mzMax')], verbose=FALSE)
expected_dataPoints <- list(ROIDataPoints1, ROIDataPoints2, ROIDataPoints3)
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables
expected_annotation@peakFit <- expected_peakFit
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files (1 missing), 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
expected_annotation@peakTables <- expected_peakTables[c(1,3)]
expected_annotation@peakFit <- expected_peakFit[c(1,3)]
expected_annotation@dataPoints <- expected_dataPoints[c(1,3)]
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 2)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose, modify parameter with ... (cpd #3)', {
# Cpd 3 is now found in 3rd file
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Modify fit of window #3
tmp_params <- list(init_params = list(amplitude=1E5, center=3455., sigma=0.1, gamma=0),
lower_bounds = list(amplitude=0, center=3450., sigma=0, gamma=-0.1),
upper_bounds = list(amplitude=1E9, center=3460., sigma=5, gamma=0.1))
new_params <- list('guess', 'guess', tmp_params, 'guess')
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
# modify peakTable
tmp_peakTable1 <- expected_peakTables[[1]]
tmp_peakTable1[3,c(2:10,12:15)] <- c(3418.0076795585401, 3455.6277710843374, 3495.4734240188186, 464.195358, 464.2000122, 464.204642, 11307215.264967661, 380736, 381327.26552768378, 0.026296922148575364, 1.1927710843374371, 1.0223856861398346, 1.0391667928715738)
tmp_peakTable2 <- expected_peakTables[[2]]
tmp_peakTable2[3,c(2:10,12:15)] <- c(3433.0520428402692, 3464.1974939759039, 3518.3673814020449, 464.195358, 464.2000122, 464.204642, 11632481.39997852, 366720, 370275.43095360085, 0.026296922148575364, 9.762493975903908, 1.3108566292516153, 1.566712445298531)
tmp_peakTable3 <- expected_peakTables[[3]]
tmp_peakTable3[3,c(2:10,12:15)] <- c(3428.5236305028589, 3459.5514216867468, 3510.3107983995801, 464.195358, 464.2000122, 464.204642, 9697604.1795769241, 319488, 321005.94361925457, 0.026296922148575364, 5.1164216867468895, 1.2652077714541707, 1.4814479150398188)
tmp_peakTable3$found[3] <- TRUE
expected_annotation@peakTables <- list(tmp_peakTable1, tmp_peakTable2, tmp_peakTable3)
# modify curveFit
tmp_curveFit1.3 <- list(amplitude=64246.052173667762, center=3450, sigma=0.07533469863886906, gamma=0.0019238229766131536, fitStatus=2, curveModel="skewedGaussian")
class(tmp_curveFit1.3) <- 'peakPantheR_curveFit'
tmp_curveFit2.3 <- list(amplitude=31499.356902732343, center=3454.217764223421, sigma=0.052005180846722628, gamma=0.0030181085286239786, fitStatus=1, curveModel="skewedGaussian")
class(tmp_curveFit2.3) <- 'peakPantheR_curveFit'
tmp_curveFit3.3 <- list(amplitude=29842.598057228814, center=3450, sigma=0.055439446898995937, gamma=0.0031338189157350213, fitStatus=2, curveModel="skewedGaussian")
class(tmp_curveFit3.3) <- 'peakPantheR_curveFit'
expected_annotation@peakFit <- expected_peakFit
expected_annotation@peakFit[[1]][[3]] <- tmp_curveFit1.3
expected_annotation@peakFit[[2]][[3]] <- tmp_curveFit2.3
expected_annotation@peakFit[[3]][[3]] <- tmp_curveFit3.3
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, params=new_params))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose, peaks not found and not replaced (cpd #3)', {
# Cpd #3 will not give results
noMatch_ROI3 <- input_targetFeatTable
noMatch_ROI3[3,6:8] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=noMatch_ROI3, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
tmp_peakTables <- expected_peakTables
tmp_peakTables[[1]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[1]]$found[3] <- FALSE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[2]]$found[3] <- FALSE
tmp_peakTables[[3]][3,c(2:10,12:15)] <- as.numeric(NA)
tmp_peakTables[[3]]$found[3] <- FALSE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
tmp_peakFit[[3]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[3]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('3 files, 4 compounds, no uROI, FIR replace peaks not found (cpd #3), no getAcquTime, no verbose', {
# Cpd #3 will not give results, FIR will replace
noMatch_ROI3 <- input_targetFeatTable
noMatch_ROI3[3,6:8] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=noMatch_ROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
tmp_peakTables <- expected_peakTables
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3463.824, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8675223.6101818271, 366720, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$is_filled[3] <- TRUE
tmp_peakTables[[3]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[3]]$found[3] <- TRUE
tmp_peakTables[[3]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
tmp_peakFit[[3]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[3]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
if ((.Platform$OS.type != "windows") || (.Machine$sizeof.pointer == 8)) {
test_that('3 files, 4 compounds, uROI, no FIR, no fitGauss, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=input_uROI, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables
expected_annotation@peakFit <- expected_peakFit
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 3)
expect_equal(result_parallelAnnotation$messages, expected_message)
}) }
test_that('serial: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----- ko15 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Fit of ROI #3 is unsuccessful (try error)\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "Error file does not exist: aaa/bbb.cdf\n", "----- ko18 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #2\n", "Fit of ROI #3 is unsuccessful (try error)\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #4\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 40)
expect_equal(result_parallelAnnotation$messages[c(1:7,9,10,13,14,18:22,24:27,30,31,35,36,37,38,40)], expected_message)
})
test_that('parallel (with cluster reset): 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "Running 3 clusters of 1 files over 1 cores:\n", " starting cluster 1/3\n", " starting cluster 2/3\n", " starting cluster 3/3\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=1, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 13)
expect_equal(result_parallelAnnotation$messages[c(1:11,13)], expected_message)
})
test_that('parallel (without cluster reset): 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=0, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 9)
expect_equal(result_parallelAnnotation$messages[c(1:7,9)], expected_message)
})
test_that('serial and parallel (with cluster reset) give the same result: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# results
result_serial <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
result_parallel <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=1, verbose=TRUE))
# Check results
expect_equal(result_serial$result, result_parallel$result, tolerance=1e-6)
})
test_that('serial and parallel (without cluster reset) give the same result: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# results
result_serial <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
result_parallel <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=0, verbose=TRUE))
# Check results
expect_equal(result_serial$result, result_parallel$result, tolerance=1e-6)
})
test_that('change to resetWorkers alters the number of parallel cluster reset', {
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "Running 2 clusters of 2 files over 1 cores:\n", " starting cluster 1/2\n", " starting cluster 2/2\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=1, getAcquTime=TRUE, resetWorkers=2, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 12)
expect_equal(result_parallelAnnotation$messages[c(1:10,12)], expected_message)
})
test_that('already annotated message in verbose', {
# use "serial: 3 files, (1 missing), 4 compounds, uROI, FIR replace peaks not found (cpd #3), getAcquTime, verbose"
# sample 2 is missing
# Cpd #3 will not give results
noMatch_uROI3 <- input_uROI
noMatch_uROI3[3,4:6] <- c(52.194778, 52.2, 52.205222)
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_missingSpectraPaths, targetFeatTable=input_badtargetFeatTable, uROIExist=TRUE, useUROI=TRUE, uROI=noMatch_uROI3, useFIR=TRUE, FIR=input_FIR, isAnnotated=TRUE, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(1,3),]
expected_annotation@TIC <- c(2410533091, 2332817115)
tmp_peakTables <- expected_peakTables[c(1,3)]
tmp_peakTables[[1]][3,c(2:10,12:15)] <- c(3444.524, 3454.435, 3478.431, 464.1995, 464.20001220703125, 464.2005, 8801660.3810909167, 380736, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[1]]$is_filled[3] <- TRUE
tmp_peakTables[[2]][3,c(2:10,12:15)] <- c(3444.524, 3460.696, 3478.431, 464.1995, 464.20001220703125, 464.2005, 6564791.4560000831, 319488, as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA), as.numeric(NA))
tmp_peakTables[[2]]$found[3] <- TRUE
tmp_peakTables[[2]]$is_filled[3] <- TRUE
expected_annotation@peakTables <- tmp_peakTables
tmp_peakFit <- expected_peakFit[c(1,3)]
tmp_peakFit[[1]][[3]] <- NA
tmp_peakFit[[2]][[3]] <- NA
expected_annotation@peakFit <- tmp_peakFit
tmp_dataPoints <- expected_dataPoints[c(1,3)]
tmp_dataPoints[[1]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
tmp_dataPoints[[2]][[3]] <- data.frame(rt=numeric(), mz=numeric(), int=numeric())
expected_annotation@dataPoints <- tmp_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- 'Error file does not exist: aaa/bbb.cdf'
names(tmp_status) <- 'aaa/bbb.cdf'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("!! Data was already annotated, results will be overwritten !!\n", "Processing 4 compounds in 3 samples:\n", " uROI:\tTRUE\n", " FIR:\tTRUE\n", "----- ko15 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Fit of ROI #3 is unsuccessful (try error)\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "Error file does not exist: aaa/bbb.cdf\n", "----- ko18 -----\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Check input, mzMLPath must be a .mzML\n", "Reading data from 4 windows\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #1\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #2\n", "Fit of ROI #3 is unsuccessful (try error)\n", "Warning: rtMin/rtMax outside of ROI; datapoints cannot be used for mzMin/mzMax calculation, approximate mz and returning ROI$mzMin and ROI$mzMax for ROI #4\n", "1 features to integrate with FIR\n", "Reading data from 1 windows\n", "----------------\n", "1 file(s) failed to process:\n file error\n1 aaa/bbb.cdf Error file does not exist: aaa/bbb.cdf\n", "Annotation object cannot be reordered by sample acquisition date\n", "----------------\n", " 1 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=TRUE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no timing)
expect_equal(length(result_parallelAnnotation$messages), 41)
expect_equal(result_parallelAnnotation$messages[c(1:8,10,11,14,15,19:23,25:28,31,32,36,37,38,39,41)], expected_message)
})
test_that('catch file that doesnt exist, catch error processing, no file left', {
# Object fully initialised
wrongPaths <- c("aaa/bbb.cdf", system.file("extdata/test_fakemzML.mzML", package = "peakPantheR"))
initAnnotation <- peakPantheRAnnotation(spectraPaths=wrongPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- initAnnotation[c(FALSE, FALSE),]
expected_annotation@isAnnotated <- FALSE
# Expected message
expected_message <- c("Processing 4 compounds in 2 samples:\n", " uROI:\tFALSE\n", " FIR:\tFALSE\n", "Error file does not exist: aaa/bbb.cdf\n", "----- test_fakemzML -----\n", "-----\n", "Error processing file: test_fakemzML\n", "\n-----\n", "----------------\n", "No file left in the object!\n", "Annotation object reordered by sample acquisition date\n", "----------------\n", " 2 failure(s)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=TRUE))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-6)
# cannot check the failure paths
expect_equal(dim(result_parallelAnnotation$result$failures)[1], 2)
expect_equal(dim(result_parallelAnnotation$result$failures)[2], 2)
# Check messages (remove timing and paths in error messages)
expect_equal(length(result_parallelAnnotation$messages), 16)
expect_equal(result_parallelAnnotation$messages[c(1:7, 9, 10, 12, 13, 14, 16)], expected_message)
})
test_that('curveModel emgGaussian: 3 files, 4 compounds, no uROI, no FIR, no getAcquTime, no verbose', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected peakFit
# 1
cFit1.1emg <- list(amplitude=22322950, center=3341.888, sigma=5, gamma=0.09934113, fitStatus=2, curveModel="emgGaussian")
class(cFit1.1emg) <- 'peakPantheR_curveFit'
cFit1.2emg <- list(amplitude=29181384, center=3382.577, sigma=5, gamma=0.08974434, fitStatus=2, curveModel="emgGaussian")
class(cFit1.2emg) <- 'peakPantheR_curveFit'
cFit1.3emg <- list(amplitude=9173607, center=3451.435, sigma=5, gamma=0.1071507, fitStatus=2, curveModel="emgGaussian")
class(cFit1.3emg) <- 'peakPantheR_curveFit'
cFit1.4emg <- list(amplitude=7719709, center=3698.697, sigma=5, gamma=0.1060304, fitStatus=2, curveModel="emgGaussian")
class(cFit1.4emg) <- 'peakPantheR_curveFit'
# 2
cFit2.1emg <- list(amplitude=22094946, center=3359.102, sigma=5, gamma=0.07724317, fitStatus=2, curveModel="emgGaussian")
class(cFit2.1emg) <- 'peakPantheR_curveFit'
cFit2.2emg <- list(amplitude=34397901, center=3399.791, sigma=5, gamma=0.0651969, fitStatus=2, curveModel="emgGaussian")
class(cFit2.2emg) <- 'peakPantheR_curveFit'
cFit2.3emg <- list(amplitude=9671145, center=3460.824, sigma=5, gamma=0.08864798, fitStatus=2, curveModel="emgGaussian")
class(cFit2.3emg) <- 'peakPantheR_curveFit'
cFit2.4emg <- list(amplitude=7296689, center=3714.347, sigma=5, gamma=0.06171862, fitStatus=2, curveModel="emgGaussian")
class(cFit2.4emg) <- 'peakPantheR_curveFit'
# 3
cFit3.1emg <- list(amplitude=20390552, center=3362.233, sigma=5, gamma=0.08186031, fitStatus=2, curveModel="emgGaussian")
class(cFit3.1emg) <- 'peakPantheR_curveFit'
cFit3.2emg <- list(amplitude=29719102, center=3409.182, sigma=5, gamma=0.09218107, fitStatus=2, curveModel="emgGaussian")
class(cFit3.2emg) <- 'peakPantheR_curveFit'
cFit3.3emg <- NA
cFit3.4emg <- list(amplitude=5751872, center=3708.088, sigma=5, gamma=0.06964929, fitStatus=2, curveModel="emgGaussian")
class(cFit3.4emg) <- 'peakPantheR_curveFit'
expected_peakFit_emg <- list(list(cFit1.1emg, cFit1.2emg, cFit1.3emg, cFit1.4emg), list(cFit2.1emg, cFit2.2emg, cFit2.3emg, cFit2.4emg), list(cFit3.1emg, cFit3.2emg, cFit3.3emg, cFit3.4emg))
# Expected peakTables
peakTable1emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable1emg[1,] <- c(TRUE, 3327.999, 3346.996, 3403.919, 522.1948, 522.2, 522.2052, 22261723, 889280, 1057506.5, FALSE, 0.02337616, 2.108434, 1.653451, 2.064384)
peakTable1emg[2,] <- c(TRUE, 3368.739, 3387.926, 3450.433, 496.1950, 496.2, 496.2050, 29098356, 1128960, 1313099.4, FALSE, 0.02460103, 2.349398, 1.745483, 2.219176)
peakTable1emg[3,] <- c(TRUE, 3437.496, 3456.351, 3509.499, 464.1954, 464.2, 464.2046, 9149178, 380736, 450748.4, FALSE, 0.02629692, 1.915663, 1.592171, 1.962157)
peakTable1emg[4,] <- c(TRUE, 3684.765, 3703.637, 3757.294, 536.1946, 536.2, 536.2054, 7699066, 330176, 377425.9, FALSE, 0.02276582, 1.939759, 1.600693, 1.976502)
peakTable1emg[,c(1,11)] <- sapply(peakTable1emg[,c(1,11)], as.logical)
peakTable1emg[,c(2:10,12:15)] <- sapply(peakTable1emg[,c(2:10,12:15)], as.numeric)
# 2
peakTable2emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable2emg[1,] <- c(TRUE, 3345.357, 3364.813, 3436.703, 522.1948, 522.2, 522.2052, 22028618, 761664, 916975.6, FALSE, 0.02337616, 19.92484, 1.898412, 2.477039)
peakTable2emg[2,] <- c(TRUE, 3386.117, 3405.791, 3490.313, 496.1950, 496.2, 496.2050, 34288936, 1099264, 1293794.6, FALSE, 0.02460103, 20.21400, 2.116160, 2.850792)
peakTable2emg[3,] <- c(TRUE, 3447.002, 3466.197, 3529.422, 464.1954, 464.2, 464.2046, 9643477, 366720, 432400.6, FALSE, 0.02629692, 11.76249, 1.757855, 2.240265)
peakTable2emg[4,] <- c(TRUE, 3700.724, 3720.347, 3809.535, 536.1946, 536.2, 536.2054, 7273154, 220096, 265357.4, FALSE, 0.02276582, 18.65000, 2.207992, 3.012906)
peakTable2emg[,c(1,11)] <- sapply(peakTable2emg[,c(1,11)], as.logical)
peakTable2emg[,c(2:10,12:15)] <- sapply(peakTable2emg[,c(2:10,12:15)], as.numeric)
# 3
peakTable3emg <- data.frame(matrix(vector(), 4, 15, dimnames=list(c(), c("found", "rtMin", "rt", "rtMax", "mzMin", "mz", "mzMax", "peakArea", "maxIntMeasured", "maxIntPredicted", "is_filled", "ppm_error", "rt_dev_sec", "tailingFactor", "asymmetryFactor"))),stringsAsFactors=FALSE)
peakTable3emg[1,] <- c(TRUE, 3348.458, 3367.799, 3435.888, 522.1948, 522.2, 522.2052, 20330539, 758336, 873749.6, FALSE, 0.02337616, 22.91127, 1.837158, 2.373902)
peakTable3emg[2,] <- c(TRUE, 3395.322, 3414.459, 3475.443, 496.1950, 496.2, 496.2050, 29635397, 1149440, 1355916.7, FALSE, 0.02460103, 28.88211, 1.721309, 2.178978)
peakTable3emg[3,] <- c(FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, FALSE, NA, NA, NA, NA)
peakTable3emg[4,] <- c(TRUE, 3694.401, 3714.064, 3793.313, 536.1946, 536.2, 536.2054, 5734001, 196160, 225006.2, FALSE, 0.02276582, 12.36690, 2.015364, 2.673714)
peakTable3emg[,c(1,11)] <- sapply(peakTable3emg[,c(1,11)], as.logical)
peakTable3emg[,c(2:10,12:15)] <- sapply(peakTable3emg[,c(2:10,12:15)], as.numeric)
expected_peakTables_emg <- list(peakTable1emg, peakTable2emg, peakTable3emg)
# Expected annotation
expected_annotation <- initAnnotation
expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
expected_annotation@peakTables <- expected_peakTables_emg
expected_annotation@peakFit <- expected_peakFit_emg
expected_annotation@dataPoints <- expected_dataPoints
expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- NA
names(tmp_status) <- 'test'
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- c("Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Polarity can not be extracted from netCDF files, please set manually the polarity with the 'polarity' method.\n", "Fit of ROI #3 is unsuccessful (cannot determine rtMin/rtMax)\n")
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, curveModel='emgGaussian'))
# Check results
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (centwave output)
expect_equal(length(result_parallelAnnotation$messages), 4)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('curveModel unknown: 3 failures', {
# Object fully initialised
initAnnotation <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata, spectraMetadata=input_spectraMetadata)
# Expected annotation
expected_annotation <- peakPantheRAnnotation(targetFeatTable=input_targetFeatTable, cpdMetadata=input_cpdMetadata)
expected_annotation@spectraMetadata <- data.frame(matrix(character(), ncol=2, byrow=FALSE, dimnames=list(c(), c('testcol1', 'testcol2'))), stringsAsFactors=FALSE)
#expected_annotation@TIC <- c(2410533091, 2524040155, 2332817115)
#expected_annotation@peakTables <- expected_peakTables
#expected_annotation@peakFit <- expected_peakFit
#expected_annotation@dataPoints <- expected_dataPoints
#expected_annotation@isAnnotated <- TRUE
# Expected failures
tmp_status <- c('Error: "curveModel" must be one of: skewedGaussian, emgGaussian','Error: "curveModel" must be one of: skewedGaussian, emgGaussian','Error: "curveModel" must be one of: skewedGaussian, emgGaussian')
names(tmp_status) <- input_spectraPaths
tmp_failures <- !is.na(tmp_status)
names(tmp_failures) <- NULL
expected_failures <- data.frame(matrix(c(names(tmp_status)[tmp_failures], tmp_status[tmp_failures]), ncol=2, byrow=FALSE, dimnames=list(c(), c('file', 'error'))), stringsAsFactors=FALSE)
# Expected message
expected_message <- character(0)
# results (output, warnings and messages)
result_parallelAnnotation <- evaluate_promise(peakPantheR_parallelAnnotation(initAnnotation, ncores=0, getAcquTime=FALSE, verbose=FALSE, curveModel='unknown_curveModel'))
# Check results (all failures)
expect_equal(result_parallelAnnotation$result$annotation, expected_annotation, tolerance=1e-5)
expect_equal(result_parallelAnnotation$result$failures, expected_failures)
# Check messages (no fit, so no message)
expect_equal(length(result_parallelAnnotation$messages), 0)
expect_equal(result_parallelAnnotation$messages, expected_message)
})
test_that('raise errors', {
# Object fails validation on input check
wrongInit <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
wrongInit@TIC <- c(1, 2)
msg1 <- paste('invalid class ', dQuote('peakPantheRAnnotation'),' object: TIC has 2 elements (samples). Should be 3', sep='')
expect_error(peakPantheR_parallelAnnotation(wrongInit, ncores=0, getAcquTime=FALSE, verbose=FALSE), msg1, fixed=TRUE)
# resetWorkers is not an integer
initAnnotation2 <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
msg2 <- "Check input, resetWorkers must be an integer"
expect_error(peakPantheR_parallelAnnotation(initAnnotation2, ncores=0, getAcquTime=FALSE, resetWorkers='not an Integer', verbose=FALSE), msg2, fixed=TRUE)
# resetWorkers is < 0
initAnnotation3 <- peakPantheRAnnotation(spectraPaths=input_spectraPaths, targetFeatTable=input_targetFeatTable)
msg3 <- "Check input, resetWorkers must be a positive integer"
expect_error(peakPantheR_parallelAnnotation(initAnnotation3, ncores=0, getAcquTime=FALSE, resetWorkers=-10, verbose=FALSE), msg3, fixed=TRUE)
})
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