Next Generation xcms Result Object

The XcmsExperiment is a data container for xcms preprocessing results (i.e. results from chromatographic peak detection, alignment and correspondence analysis).

It provides the same functionality than the XCMSnExp object, but uses the more advanced and modern MS infrastructure provided by the MsExperiment and Spectra Bioconductor packages. With this comes a higher flexibility on how and where to store the data.

Documentation of the various functions for XcmsExperiment objects are grouped by topic and provided in the sections below.

The default xcms workflow is to perform

• chromatographic peak detection using findChromPeaks()

• optionally refine identified chromatographic peaks using refineChromPeaks()

• perform an alignment (retention time adjustment) using adjustRtime(). Depending on the method used this requires to run a correspondence analysis first

• perform a correspondence analysis using the groupChromPeaks() function to group chromatographic peaks across samples to define the LC-MS features.

• optionally perform a gap-filling to rescue signal in samples in which no chromatographic peak was identified and hence a missing value would be reported. This can be performed using the fillChromPeaks() function.

Usage

filterFeatureDefinitions(object, ...)

# S4 method for class 'MsExperiment'
filterRt(object, rt = numeric(), ...)

# S4 method for class 'MsExperiment'
filterMzRange(object, mz = numeric(), msLevel. = uniqueMsLevels(object))

# S4 method for class 'MsExperiment'
filterMz(object, mz = numeric(), msLevel. = uniqueMsLevels(object))

# S4 method for class 'MsExperiment'
filterMsLevel(object, msLevel. = uniqueMsLevels(object))

# S4 method for class 'MsExperiment'
uniqueMsLevels(object)

# S4 method for class 'MsExperiment'
filterFile(object, file = integer(), ...)

# S4 method for class 'MsExperiment'
rtime(object)

# S4 method for class 'MsExperiment'
fromFile(object)

# S4 method for class 'MsExperiment'
fileNames(object)

# S4 method for class 'MsExperiment'
polarity(object)

# S4 method for class 'MsExperiment'
filterIsolationWindow(object, mz = numeric())

# S4 method for class 'MsExperiment'
chromatogram(
  object,
  rt = matrix(nrow = 0, ncol = 2),
  mz = matrix(nrow = 0, ncol = 2),
  aggregationFun = "sum",
  msLevel = 1L,
  isolationWindowTargetMz = NULL,
  chunkSize = 2L,
  return.type = "MChromatograms",
  BPPARAM = bpparam()
)

featureArea(
  object,
  mzmin = min,
  mzmax = max,
  rtmin = min,
  rtmax = max,
  features = character()
)

# S4 method for class 'MsExperiment,missing'
plot(x, y, msLevel = 1L, peakCol = "#ff000060", ...)

# S4 method for class 'XcmsExperiment,ANY,ANY,ANY'
x[i, j, ..., drop = TRUE]

# S4 method for class 'XcmsExperiment'
filterIsolationWindow(object, mz = numeric())

# S4 method for class 'XcmsExperiment'
filterRt(object, rt, msLevel.)

# S4 method for class 'XcmsExperiment'
filterMzRange(object, mz = numeric(), msLevel. = uniqueMsLevels(object))

# S4 method for class 'XcmsExperiment'
filterMsLevel(object, msLevel. = uniqueMsLevels(object))

# S4 method for class 'XcmsExperiment'
hasChromPeaks(object, msLevel = integer())

# S4 method for class 'XcmsExperiment'
dropChromPeaks(object, keepAdjustedRtime = FALSE)

# S4 method for class 'XcmsExperiment'
chromPeaks(object) <- value

# S4 method for class 'XcmsExperiment'
chromPeaks(
  object,
  rt = numeric(),
  mz = numeric(),
  ppm = 0,
  msLevel = integer(),
  type = c("any", "within", "apex_within"),
  isFilledColumn = FALSE
)

# S4 method for class 'XcmsExperiment'
chromPeakData(object) <- value

# S4 method for class 'XcmsExperiment'
chromPeakData(
  object,
  msLevel = integer(),
  return.type = c("DataFrame", "data.frame")
)

# S4 method for class 'XcmsExperiment'
filterChromPeaks(
  object,
  keep = rep(TRUE, nrow(.chromPeaks(object))),
  method = "keep",
  ...
)

# S4 method for class 'XcmsExperiment'
dropAdjustedRtime(object)

# S4 method for class 'MsExperiment'
hasAdjustedRtime(object)

# S4 method for class 'XcmsExperiment'
rtime(object, adjusted = hasAdjustedRtime(object))

# S4 method for class 'XcmsExperiment'
adjustedRtime(object)

# S4 method for class 'XcmsExperiment'
hasFeatures(object, msLevel = integer())

# S4 method for class 'XcmsExperiment'
featureDefinitions(object) <- value

# S4 method for class 'XcmsExperiment'
featureDefinitions(
  object,
  mz = numeric(),
  rt = numeric(),
  ppm = 0,
  type = c("any", "within", "apex_within"),
  msLevel = integer()
)

# S4 method for class 'XcmsExperiment'
dropFeatureDefinitions(object, keepAdjustedRtime = FALSE)

# S4 method for class 'XcmsExperiment'
filterFeatureDefinitions(object, features = integer())

# S4 method for class 'XcmsExperiment'
hasFilledChromPeaks(object)

# S4 method for class 'XcmsExperiment'
dropFilledChromPeaks(object)

# S4 method for class 'XcmsExperiment'
quantify(object, ...)

# S4 method for class 'XcmsExperiment'
featureValues(
  object,
  method = c("medret", "maxint", "sum"),
  value = "into",
  intensity = "into",
  filled = TRUE,
  missing = NA_real_,
  msLevel = integer()
)

# S4 method for class 'XcmsExperiment'
chromatogram(
  object,
  rt = matrix(nrow = 0, ncol = 2),
  mz = matrix(nrow = 0, ncol = 2),
  aggregationFun = "sum",
  msLevel = 1L,
  chunkSize = 2L,
  isolationWindowTargetMz = NULL,
  return.type = c("XChromatograms", "MChromatograms"),
  include = character(),
  chromPeaks = c("apex_within", "any", "none"),
  BPPARAM = bpparam()
)

# S4 method for class 'XcmsExperiment'
processHistory(object, type)

# S4 method for class 'XcmsExperiment'
filterFile(
  object,
  file,
  keepAdjustedRtime = hasAdjustedRtime(object),
  keepFeatures = FALSE,
  ...
)

Arguments

object

An XcmsExperiment object.

...

Additional optional parameters. For quantify: any parameter for the featureValues call used to extract the feature value matrix.

rt

For chromPeaks and featureDefinitions: numeric(2) defining the retention time range for which chromatographic peaks or features should be returned. The full range is used by default. For chromatogram: two column numerical matrix with each row representing the lower and upper retention time window(s) for the chromatograms. If not provided the full retention time range is used.

mz

For chromPeaks and featureDefinitions: numeric(2) optionally defining the m/z range for which chromatographic peaks or feature definitions should be returned. The full m/z range is used by default. For chromatogram: two-column numerical matrix with each row representing m/z range that should be aggregated into a chromatogram. If not provided the full m/z range of the data will be used (and hence a total ion chromatogram will be returned if aggregationFun = "sum" is used). For filterIsolationWindow: numeric(1) defining the m/z that should be contained within the spectra's isolation window.

msLevel.

For filterRt: ignored. filterRt will always filter by retention times on all MS levels regardless of this parameter. For chromatogram: integer with the MS level from which the chromatogram(s) should be extracted. Has to be either of length 1 or length equal to the numer of rows of the parameters mz and rt defining the m/z and rt regions from which the chromatograms should be created. Defaults to msLevel = 1L. for filterMsLevel: integer defining the MS level(s) to which the data should be subset.

file

For filterFile: integer with the indices of the samples (files) to which the data should be subsetted.

aggregationFun

For chromatogram: character(1) defining the function that should be used to aggregate intensities for retention time (i.e. each spectrum) along the specified m/z range (parameter mz). Defaults to aggregationFun = "sum" and hence all intensities will be summed up. Alternatively, use aggregationFun = "max" to use the maximal intensity per m/z range to create a base peak chromatogram (BPC).

msLevel

integer defining the MS level (or multiple MS level if the function supports it).

isolationWindowTargetMz

For chromatogram: numeric (of length equal to the number of rows of rt and mz) with the isolation window target m/z of the MS2 spectra from which the chromatgrom should be generated. For MS1 data (msLevel = 1L, the default), this parameter is ignored. See examples on chromatogram below for further information.

chunkSize

For chromatogram: integer(1) defining the number of files from which the data should be loaded at a time into memory. Defaults to chunkSize = 2L.

return.type

For chromPeakData: character(1) defining the class of the returned object. Can be either "DataFrame" (the default) or "data.frame". For chromatogram: character(1) defining the type of the returned object. Currently only return.type = "MChromatograms" is supported.

BPPARAM

For chromatogram: parallel processing setup. Defaults to BPPARAM = bpparam(). See bpparam() for more information.

mzmin

For featureArea: function to calculate the "mzmin" of a feature based on the "mzmin" values of the individual chromatographic peaks assigned to that feature. Defaults to mzmin = min.

mzmax

For featureArea: function to calculate the "mzmax" of a feature based on the "mzmax" values of the individual chromatographic peaks assigned to that feature. Defaults to mzmax = max.

rtmin

For featureArea: function to calculate the "rtmin" of a feature based on the "rtmin" values of the individual chromatographic peaks assigned to that feature. Defaults to rtmin = min.

rtmax

For featureArea: function to calculate the "rtmax" of a feature based on the "rtmax" values of the individual chromatographic peaks assigned to that feature. Defaults to rtmax = max.

features

For filterFeatureDefinitions and featureArea: logical, integer or character defining the features to keep or from which to extract the feature area, respectively. See function description for more information.

x

An XcmsExperiment object.

y

For plot: should not be defined as it is not supported.

peakCol

For plot: defines the border color of the rectangles indicating the identified chromatographic peaks. Only a single color is supported. Defaults to `peakCol = "#ff000060".

i

For [: integer or logical defining the samples/files to subset.

j

For [: not supported.

drop

For [: ignored.

keepAdjustedRtime

logical(1): whether adjusted retention times (if present) should be retained.

value

For featureValues: character(1) defining which value should be reported for each feature in each sample. Can be any column of the chromPeaks matrix or "index" if simply the index of the assigned peak should be returned. Defaults to value = "into" thus the integrated peak area is reported.

ppm

For chromPeaks and featureDefinitions: optional numeric(1) specifying the ppm by which the m/z range (defined by mz should be extended. For a value of ppm = 10, all peaks within mz[1] - ppm / 1e6 and mz[2] + ppm / 1e6 are returned.

type

For chromPeaks and featureDefinitions and only if either mz and rt are defined too: character(1): defining which peaks (or features) should be returned. For type = "any": returns all chromatographic peaks or features also only partially overlapping any of the provided ranges. For type = "within": returns only peaks or features completely within the region defined by mz and/or rt. For type = "apex_within": returns peaks or features for which the m/z and retention time of the peak's apex is within the region defined by mz and/or rt. For processHistory: restrict returned processing steps to specific types. Use processHistoryTypes() to list all supported values.

isFilledColumn

For chromPeaks: logical(1) whether a column "is_filled" should be included in the returned matrix with the information whether a peak was detected or only filled-in. Note that this information is also provided in the chromPeakData data frame.

keep

For filterChromPeaks: logical, integer or character specifying which chromatographic peaks to keep. If logical the length of keep needs to match the number of rows of chromPeaks. Alternatively, keep allows to specify the index (row) of peaks to keep or their ID (i.e. row name in chromPeaks).

method

For featureValues: character(1) specifying the method to resolve multi-peak mappings within the same sample (correspondence analysis can assign more than one chromatographic peak within a sample to the same feature, e.g. if they are close in retention time). Options: method = "medret": report the value for the chromatographic peak closest to the feature's median retention time. method = "maxint": report the value for the chromatographic peak with the largest signal (parameter intensity allows to select the column in chromPeaks that should be used for signal). method = "sum": sum the value for all chromatographic peaks in a sample assigned to the same feature. The default is method = "medret". For filterChromPeaks: currently only method = "keep" is supported.

adjusted

For rtime,XcmsExperiment: whether adjusted or raw retention times should be returned. The default is to return adjusted retention times, if available.

intensity

For featureValues: character(1) specifying the name of the column in the chromPeaks(objects) matrix containing the intensity value of the peak that should be used for the conflict resolution if method = "maxint".

filled

For featureValues: logical(1) specifying whether values for filled-in peaks should be reported. For filled = TRUE (the default) filled peak values are returned, otherwise NA is reported for the respective features in the samples in which no peak was detected.

missing

For featureValues: default value for missing values. Allows to define the value that should be reported for a missing peak intensity. Defaults to missing = NA_real_.

include

For chromatogram: deprecated; use parameter chromPeaks instead.

chromPeaks

For chromatogram: character(1) defining which chromatographic peaks should be returned. Can be either chromPeaks = "apex_within" (default) to return all chromatographic peaks with the m/z and RT of their apex within the m/z and retention time window, chromPeaks = "any" for all chromatographic peaks that are overlapping with the m/z - retention time window or chromPeaks = "none" to not include any chromatographic peaks. See also parameter type below for additional information.

keepFeatures

for most subsetting functions ([, filterFile): logical(1): wheter eventually present feature definitions should be retained in the returned (filtered) object.

Subsetting and filtering

• [: subset an XcmsExperiment by sample (parameter i). Subsetting will by default drop correspondence results (as subsetting by samples will obviously affect the feature definition) and alignment results (adjusted retention times) while identified chromatographic peaks (for the selected samples) will be retained. Which preprocessing results should be kept or dropped can also be configured with optional parameters keepChromPeaks (by default TRUE), keepAdjustedRtime (by default FALSE) and keepFeatures (by default FALSE).

• filterChromPeaks: filter chromatographic peaks of an XcmsExperiment keeping only those specified with parameter keep. Returns the XcmsExperiment with the filtered data. Chromatographic peaks to retain can be specified either by providing their index in the chromPeaks matrix, their ID (rowname in chromPeaks) or with a logical vector with the same length than number of rows of chromPeaks. Assignment of chromatographic peaks are updated to eventually present feature definitions after filtering.

• filterFeatureDefinitions: filter feature definitions of an XcmsExperiment keeping only those defined with parameter features, which can be a logical of length equal to the number of features, an integer with the index of the features in featureDefinitions(object) to keep or a character with the feature IDs (i.e. row names in featureDefinitions(object)).

• filterFile: filter an XcmsExperiment (or MsExperiment) by file (sample). The index of the samples to which the data should be subsetted can be specified with parameter file. The sole purpose of this function is to provide backward compatibility with the MSnbase package. Wherever possible, the [ function should be used instead for any sample-based subsetting. Parameters keepChromPeaks, keepAdjustedRtime and keepChromPeaks can be passed using .... Note also that in contrast to [, filterFile does not support subsetting in arbitrary order.

• filterIsolationWindow: filter the spectra within an MsExperiment or XcmsExperiment object keeping only those with an isolation window containing the specified m/z (i.e., keeping spectra with an "isolationWindowLowerMz" smaller than the user-provided mz and an "isolationWindowUpperMz" larger than mz). For an XcmsExperiment also all chromatographic peaks (and subsequently also features) are removed for which the range of their "isolationWindowLowerMz" and "isolationWindowUpperMz" (columns in chromPeakData) do not contain the user provided mz.

• filterMsLevel: filter the data of the XcmsExperiment or MsExperiment to keep only data of the MS level(s) specified with parameter msLevel..

• filterMz, filterMzRange: filter the spectra within an XcmsExperiment or MsExperiment to the specified m/z range (parameter mz). For XcmsExperiment also identified chromatographic peaks and features are filtered keeping only those that are within the specified m/z range (i.e. for which the m/z of the peak apex is within the m/z range). Parameter msLevels. allows to restrict the filtering to only specified MS levels. By default data from all MS levels are filtered.

• filterRt: filter an XcmsExperiment keeping only data within the specified retention time range (parameter rt). This function will keep all preprocessing results present within the retention time range: all identified chromatographic peaks with the retention time of the apex position within the retention time range rt are retained along, if present, with the associated features. Parameter msLevel. is currently ignored, i.e. filtering will always performed on all MS levels of the object.

Functionality related to chromatographic peaks

• chromatogram: extract chromatographic data from a data set. Parameters mz and rt allow to define specific m/z - retention time regions to extract the data from (to e.g. for extracted ion chromatograms EICs). Both parameters are expected to be numerical two-column matrices with the first column defining the lower and the second the upper margin. Each row can define a separate m/z - retention time region. Currently the function returns a MChromatograms() object for object being a MsExperiment or, for object being an XcmsExperiment, either a MChromatograms or XChromatograms() depending on parameter return.type (can be either "MChromatograms" or "XChromatograms"). For the latter also chromatographic peaks detected within the provided m/z and retention times are returned. Parameter chromPeaks allows to specify which chromatographic peaks should be reported. See documentation on the chromPeaks parameter for more information. If the XcmsExperiment contains correspondence results, also the associated feature definitions will be included in the returned XChromatograms. By default the function returns chromatograms from MS1 data, but by setting parameter msLevel = 2L it is possible to e.g. extract also MS2 chromatograms. By default, with parameter isolationWindowTargetMz = NULL or isolationWindowTargetMz = NA_real_, data from all MS2 spectra will be considered in the chromatogram extraction. If MS2 data was generated within different m/z isolation windows (such as e.g. with Scies SWATH data), the parameter isolationWindowTargetMz should be used to ensure signal is only extracted from the respective isolation window. The isolationWindowTargetMz() function on the Spectra object can be used to inspect/list available isolation windows of a data set. See also the xcms LC-MS/MS vignette for examples and details.

• chromPeaks: returns a numeric matrix with the identified chromatographic peaks. Each row represents a chromatographic peak identified in one sample (file). The number of columns depends on the peak detection algorithm (see findChromPeaks()) but most methods return the following columns: "mz" (intensity-weighted mean of the m/z values of all mass peaks included in the chromatographic peak), "mzmin" ( smallest m/z value of any mass peak in the chromatographic peak), "mzmax" (largest m/z value of any mass peak in the chromatographic peak), "rt" (retention time of the peak apex), "rtmin" (retention time of the first scan/mass peak of the chromatographic peak), "rtmax" (retention time of the last scan/mass peak of the chromatographic peak), "into" (integrated intensity of the chromatographic peak), "maxo" (maximal intensity of any mass peak of the chromatographic peak), "sample" (index of the sample in object in which the peak was identified). Parameters rt, mz, ppm, msLevel and type allow to extract subsets of identified chromatographic peaks from the object. See parameter description below for details.

• chromPeakData: returns a DataFrame with potential additional annotations for the identified chromatographic peaks. Each row in this DataFrame corresponds to a row (same index and row name) in the chromPeaks matrix. The default annotations are "ms_level" (the MS level in which the peak was identified) and "is_filled" (whether the chromatographic peak was detected (by findChromPeaks) or filled-in (by fillChromPeaks).

• chromPeakSpectra: extract MS spectra for identified chromatographic peaks. This can be either all (full scan) MS1 spectra with retention times between the retention time range of a chromatographic peak, all MS2 spectra (if present) with a retention time within the retention time range of a (MS1) chromatographic peak and a precursor m/z within the m/z range of the chromatographic peak or single, selected spectra depending on their total signal or highest signal. Parameter msLevel allows to define from which MS level spectra should be extracted, parameter method allows to define if all or selected spectra should be returned. See chromPeakSpectra() for details.

• dropChromPeaks: removes (all) chromatographic peak detection results from object. This will also remove any correspondence results (i.e. features) and eventually present adjusted retention times from the object if the alignment was performed after the peak detection. Alignment results (adjusted retention times) can be retained if parameter keepAdjustedRtime is set to TRUE.

• dropFilledChromPeaks: removes chromatographic peaks added by gap filling with fillChromPeaks.

• fillChromPeaks: perform gap filling to integrate signal missing values in samples in which no chromatographic peak was found. This depends on correspondence results, hence groupChromPeaks needs to be called first. For details and options see fillChromPeaks().

• findChromPeaks: perform chromatographic peak detection. See findChromPeaks() for details.

• hasChromPeaks: whether the object contains peak detection results. Parameter msLevel allows to check whether peak detection results are available for the specified MS level(s).

• hasFilledChromPeaks: whether gap-filling results (i.e., filled-in chromatographic peaks) are present.

• manualChromPeaks: manually add chromatographic peaks by defining their m/z and retention time ranges. See manualChromPeaks() for details and examples.

• plotChromPeakImage: show the density of identified chromatographic peaks per file along the retention time. See plotChromPeakImage() for details.

• plotChromPeaks: indicate identified chromatographic peaks from one sample in the RT-m/z space. See plotChromPeaks() for details.

• plotPrecursorIons: general visualization of precursor ions of LC-MS/MS data. See plotPrecursorIons() for details.

• refineChromPeaks: refines identified chromatographic peaks in object. See refineChromPeaks() for details.

Functionality related to alignment

• adjustedRtime: extract adjusted retention times. This is just an alias for rtime(object, adjusted = TRUE).

• adjustRtime: performs retention time adjustment (alignment) of the data. See adjustRtime() for details.

• applyAdjustedRtime: replaces the original (raw) retention times with the adjusted ones. See applyAdjustedRtime() for more information.

• dropAdjustedRtime: drops alignment results (adjusted retention time) from the result object. This also reverts the retention times of identified chromatographic peaks if present in the result object. Note that any results from a correspondence analysis (i.e. feature definitions) will be dropped too (if the correspondence analysis was performed after the alignment). This can be overruled with keepAdjustedRtime = TRUE.

• hasAdjustedRtime: whether alignment was performed on the object (i.e., the object contains alignment results).

• plotAdjustedRtime: plot the alignment results; see plotAdjustedRtime() for more information.

Functionality related to correspondence analysis

• dropFeatureDefinitions: removes any correspondence analysis results from object as well as any filled-in chromatographic peaks. By default (with parameter keepAdjustedRtime = FALSE) also all alignment results will be removed if alignment was performed after the correspondence analysis. This can be overruled with keepAdjustedRtime = TRUE.

• featureArea: returns a matrix with columns "mzmin", "mzmax", "rtmin" and "rtmax" with the m/z and retention time range for each feature (row) in object. By default these represent the minimal m/z and retention times as well as maximal m/z and retention times for all chromatographic peaks assigned to that feature. Parameter features allows to extract these values for selected features only. Parameters mzmin, mzmax, rtmin and rtmax allow to define the function to calculate the reported "mzmin", "mzmax", "rtmin" and "rtmax" values.

• featureChromatograms: extract ion chromatograms (EICs) for each feature in object. See featureChromatograms() for more details.

• featureDefinitions: returns a data.frame with feature definitions or an empty data.frame if no correspondence analysis results are present. Parameters msLevel, mz, ppm and rt allow to define subsets of feature definitions that should be returned with the parameter type defining how these parameters should be used to subset the returned data.frame. See parameter descriptions for details.

• featureSpectra: returns a Spectra() or List of Spectra with (MS1 or MS2) spectra associated to each feature. See featureSpectra() for more details and available parameters.

• featuresSummary: calculate a simple summary on features. See featureSummary() for details.

• groupChromPeaks: performs the correspondence analysis (i.e., grouping of chromatographic peaks into LC-MS features). See groupChromPeaks() for details.

• hasFeatures: whether correspondence analysis results are presentin in object. The optional parameter msLevel allows to define the MS level(s) for which it should be determined if feature definitions are available.

• overlappingFeatures: identify features that overlapping or close in m/z - rt dimension. See overlappingFeatures() for more information.

Extracting data and results from an XcmsExperiment

Preprocessing results can be extracted using the following functions:

• chromPeaks: extract identified chromatographic peaks. See section on chromatographic peak detection for details.

• featureDefinitions: extract the definition of features (chromatographic peaks grouped across samples). See section on correspondence analysis for details.

• featureValues: extract a matrix of values for features from each sample (file). Rows are features, columns samples. Which value should be returned can be defined with parameter value, which can be any column of the chromPeaks matrix. By default (value = "into") the integrated chromatographic peak intensities are returned. With parameter msLevel it is possible to extract values for features from certain MS levels. During correspondence analysis, more than one chromatographic peak per sample can be assigned to the same feature (e.g. if they are very close in retention time). Parameter method allows to define the strategy to deal with such cases: method = "medret": report the value from the chromatographic peak with the apex position closest to the feautre's median retention time. method = "maxint": report the value from the chromatographic peak with the largest signal (parameter intensity allows to define the column in chromPeaks that should be selected; defaults to intensity = "into"). method = "sum"`: sum the values for all chromatographic peaks assigned to the feature in the same sample.

• quantify: extract the correspondence analysis results as a SummarizedExperiment(). The feature values are used as assay in the returned SummarizedExperiment, rowData contains the featureDefinitions (without column "peakidx") and colData the sampleData of object. Additional parameters to the featureValues function (that is used to extract the feature value matrix) can be passed via ....

Visualization

• plot: plot for each file the position of individual peaks in the m/z - retention time space (with color-coded intensity) and a base peak chromatogram. This function should ideally be called only on a data subset (i.e. after using filterRt and filterMz to restrict to a region of interest). Parameter msLevel allows to define from which MS level the plot should be created. If x is a XcmsExperiment with available identified chromatographic peaks, also the region defining the peaks are indicated with a rectangle. Parameter peakCol allows to define the color of the border for these rectangles.

• plotAdjustedRtime: plot the alignment results; see plotAdjustedRtime() for more information.

• plotChromPeakImage: show the density of identified chromatographic peaks per file along the retention time. See plotChromPeakImage() for details.

• plotChromPeaks: indicate identified chromatographic peaks from one sample in the RT-m/z space. See plotChromPeaks() for details.

General functionality and functions for backward compatibility

• uniqueMsLevels: returns the unique MS levels of the spectra in object.

The functions listed below ensure compatibility with the older XCMSnExp() xcms result object.

• fileNames: returns the original data file names for the spectra data. Ideally, the dataOrigin or dataStorage spectra variables from the object's spectra should be used instead.

• fromFile: returns the file (sample) index for each spectrum within object. Generally, subsetting by sample using the [ is the preferred way to get spectra from a specific sample.

• polarity: returns the polarity information for each spectrum in object.

• processHistory: returns a list with ProcessHistory process history objects that contain also the parameter object used for the different processings. Optional parameter type allows to query for specific processing steps.

• rtime: extract retention times of the spectra from the MsExperiment or XcmsExperiment object. It is thus a shortcut for rtime(spectra(object)) which would be the preferred way to extract retention times from an MsExperiment. The rtime method for XcmsExperiment has an additional parameter adjusted which allows to define whether adjusted retention times (if present - adjusted = TRUE) or raw retention times (adjusted = FALSE) should be returned. By default adjusted retention times are returned if available.

Differences compared to the XCMSnExp() object

• Subsetting by [ supports arbitrary ordering.

Author

Johannes Rainer

Examples

## Creating a MsExperiment object representing the data from an LC-MS
## experiment.
library(MsExperiment)

## Defining the raw data files
fls <- 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"))

## Defining a data frame with the sample characterization
df <- data.frame(mzML_file = basename(fls),
                sample = c("ko15", "ko16", "ko18"))
## Importing the data. This will initialize a `Spectra` object representing
## the raw data and assign these to the individual samples.
mse <- readMsExperiment(spectraFiles = fls, sampleData = df)

## Extract a total ion chromatogram and base peak chromatogram
## from the data
bpc <- chromatogram(mse, aggregationFun = "max")
tic <- chromatogram(mse)

## Plot them
par(mfrow = c(2, 1))
plot(bpc, main = "BPC")
plot(tic, main = "TIC")


## Extracting MS2 chromatographic data
##
## To show how MS2 chromatograms can be extracted we first load a DIA
## (SWATH) data set.
mse_dia <- readMsExperiment(system.file("TripleTOF-SWATH",
    "PestMix1_SWATH.mzML", package = "msdata"))

## Extracting MS2 chromatogram requires also to specify the isolation
## window from which to extract the data. Without that chromatograms
## will be empty:
chr_ms2 <- chromatogram(mse_dia, msLevel = 2L)
intensity(chr_ms2[[1L]])
#>    [1]   167.451218   105.432610    48.448413    42.587666    51.141832
#>    [6]    32.010572    39.833950   162.208892   146.962103   116.968997
#>   [11]    47.464513    43.562779    47.522917    32.687743    48.205317
#>   [16]   154.777987   151.650104   114.490964    51.955748    40.298667
#>   [21]    42.889420    26.168091    41.573644   160.917377   155.598118
#>   [26]   115.631891    56.064858    40.531724    51.336031    35.671689
#>   [31]    47.007723   176.209493   150.000631   129.402529    52.351775
#>   [36]    41.211416    45.764487    30.722598    42.549656   162.606472
#>   [41]   159.749701   131.409168    57.591062    40.961098    47.379330
#>   [46]    35.990142    56.194426   176.991264   158.162751   128.185092
#>   [51]    55.115210    38.549212    52.187233    29.735383    42.294920
#>   [56]   168.506534   148.606744   123.903268    50.443994    37.206104
#>   [61]    49.667910    36.124219    45.099398   160.804559   144.212288
#>   [66]   117.309985    57.318721    40.807128    46.997778    31.888547
#>   [71]    44.914434   162.760728   141.112480   116.353180    61.330481
#>   [76]    42.391655    46.165895    36.830656    41.048551   173.389121
#>   [81]   150.354805   121.448249    58.297946    39.415169    48.137585
#>   [86]    33.945039    42.597284   176.705435   152.759067   117.964302
#>   [91]    57.009782    41.762080    49.519787    33.609967    45.789184
#>   [96]   173.561615   131.868021   118.099061    55.553144    39.780311
#>  [101]    46.840269    34.194347    41.879404   157.716579   140.589185
#>  [106]   121.374668    51.687723    40.195854    47.690116    37.602680
#>  [111]    43.965245   156.025829   157.369269   110.587061    52.018941
#>  [116]    39.871676    47.531537    33.916085    39.490682   162.735606
#>  [121]   151.371999   115.130247    52.206799    41.082679    48.981736
#>  [126]    29.885040    50.262584   174.824692   137.808708   118.701492
#>  [131]    52.714717    36.914359    44.841750    35.428872    42.102767
#>  [136]   176.969381   143.918775   122.172542    46.627960    39.409697
#>  [141]    45.892751    32.955673    45.916826   164.074529   110.974725
#>  [146]   121.420453    57.000711    38.071610    43.426923    31.968076
#>  [151]    43.205524   167.359458   136.644147   114.657853    53.570604
#>  [156]    37.251428    48.855616    28.654548    46.821310   159.257533
#>  [161]   136.078653   122.850526    51.119067    36.936050    47.987294
#>  [166]    31.154454    44.033667   187.065329   138.560486   121.384740
#>  [171]    49.859420    41.431116    52.683159    31.240847    41.930264
#>  [176]   166.090714   137.037807   126.818365    55.785933    40.353991
#>  [181]    47.617070    32.448793    46.101182   178.091599   126.628694
#>  [186]   125.285128    53.154098    38.196966    45.725605    33.988735
#>  [191]    47.783238   176.030519   138.156590   121.158414    51.131236
#>  [196]    37.260215    46.927999    32.118103    50.824118   163.126561
#>  [201]   143.490280   119.269498    50.446773    39.403250    45.444075
#>  [206]    31.371791    46.041094   163.995802    98.558906    97.119329
#>  [211]    43.657266    31.607119    40.415288    19.480071    41.681597
#>  [216]   165.475850   101.389368   103.396216    42.729989    20.902430
#>  [221]    48.426218    26.930463    53.396440   187.151969    58.083847
#>  [226]   108.166753    51.910657    24.056782    43.929434    29.711441
#>  [231]    46.996525   143.340123   111.724883   130.201873    46.946882
#>  [236]    30.703287    45.463666    25.532886    53.455083   188.459844
#>  [241]   121.595032   128.265759    48.481593    36.367438    39.432143
#>  [246]    35.110147    45.317950   199.461130   123.822349   124.453397
#>  [251]    51.373002    40.373744    44.575361    34.098693    44.992004
#>  [256]   199.302711   115.622113   115.520087    52.588235    36.559259
#>  [261]    42.863897    19.107814    42.420217   216.812980   145.216247
#>  [266]   118.223439    61.237153    31.971820    45.693190    30.493408
#>  [271]    43.479256   214.007843   137.507353   135.967656    60.011754
#>  [276]    37.082835    39.620731    30.998244    42.027486   232.012743
#>  [281]   118.387136   142.364895    51.672463    38.945555    41.669065
#>  [286]    33.612390    41.247462   196.533657   115.020205   142.988161
#>  [291]    46.530636    36.358999    43.610314    34.859240    41.568579
#>  [296]   199.727458   118.619273   127.635654    47.808546    34.739862
#>  [301]    45.326667    38.867514    43.806293   202.771954   126.833096
#>  [306]   164.186773    52.443501    41.062466    45.812602    36.456879
#>  [311]    41.972819   222.238004   129.047394   146.835109    53.216151
#>  [316]    36.054789    41.644602    41.153462    44.151703   198.428224
#>  [321]   133.110851   127.782179    50.909340    39.017341    43.719600
#>  [326]    42.062764    44.099596   187.029552   123.340463   116.238022
#>  [331]    46.525230    41.095261    49.200918    45.152890    47.486162
#>  [336]   226.301902   134.037386   124.916782    58.381726    40.923225
#>  [341]    49.689228    36.423063    44.652538   161.173165   126.906557
#>  [346]   103.237367    55.496240    42.352044    45.500991    34.862405
#>  [351]    41.926576   163.237384   117.727915   105.705640    49.150506
#>  [356]    38.811569    48.849277    27.522183    44.785886   160.226922
#>  [361]   113.355423   112.975909    50.373055    39.141868    47.454134
#>  [366]    31.329878    46.244481   158.126581   121.931115   118.672109
#>  [371]    56.822938    37.047153    44.821043    35.484114    38.755738
#>  [376]   191.300899   130.326700   117.394953    53.562705    36.812964
#>  [381]    45.737268    31.711265    43.831297   158.679602   128.274776
#>  [386]   111.081271    48.823742    39.079050    45.954053    31.563248
#>  [391]    38.653086   176.238025   128.692405   118.366005    42.698888
#>  [396]    39.021745    46.105397    35.345455    40.248080   175.256934
#>  [401]   139.035411   112.353086    50.371917    37.354196    48.254171
#>  [406]    32.303338    42.679164   171.239180   104.472487   122.455740
#>  [411]    48.074323    38.934960    46.869484    35.927003    45.715158
#>  [416]   228.863116   130.873426   123.462988    56.414827    41.828009
#>  [421]    52.009153    37.171067    46.885994   241.372911   123.043119
#>  [426]   133.669185    61.397251    41.912858    51.326151    34.145175
#>  [431]    43.159684   193.986114   112.600631   120.207558    41.959882
#>  [436]    33.638388    47.956467    32.989986    38.815009   182.225208
#>  [441]   110.543328   126.495590    45.878389    30.322753    40.737404
#>  [446]    27.611870    45.191360   162.945866   108.900070   118.947459
#>  [451]    45.752574    29.518900    43.446930    28.691413    40.876603
#>  [456]   152.296499    97.336724   116.545222    50.060893    34.709605
#>  [461]    41.048271    35.368648    39.523235   152.532517    97.537269
#>  [466]    92.912022    45.620119    29.189715    36.658149    26.662089
#>  [471]    38.752345   128.852280   100.981794   109.578946    48.040893
#>  [476]    34.831760    38.101074    28.549529    41.152690   141.402519
#>  [481]   101.452419   113.073400    50.223908    32.221343    41.203864
#>  [486]    30.189605    41.476329   150.812408   119.987223   126.791050
#>  [491]    56.253979    33.970643    41.440763    28.418729    36.884502
#>  [496]   151.521866   127.808146   107.266956    50.975376    35.513003
#>  [501]    42.469854    30.469824    36.575157   145.856516   112.498257
#>  [506]    97.783282    52.686416    34.647375    40.969349    27.201655
#>  [511]    39.861164   147.592851   125.196846   107.886744    51.600730
#>  [516]    37.969832    37.686576    33.473837    40.492766   138.681531
#>  [521]   115.332075   116.144761    47.054372    33.797785    46.507380
#>  [526]    27.791961    42.171336   140.036967   121.225005   104.036724
#>  [531]    47.233675    38.214997    41.466050    32.206779    42.691704
#>  [536]   139.523492   129.458122   111.883703    45.873956    34.418329
#>  [541]    39.452800    28.672196    44.544770   132.852484   105.496340
#>  [546]    98.788578    49.043451    33.354703    37.570898    28.401155
#>  [551]    46.793168   124.081183   134.779078   111.072208    48.193504
#>  [556]    37.352554    38.492679    30.140132    34.180987   150.349048
#>  [561]   127.751322   109.830612    48.353302    33.361524    38.676967
#>  [566]    27.177009    38.237094   151.832900   119.423590   108.777089
#>  [571]    59.370222    27.981177    41.502313    28.070891    33.805593
#>  [576]   153.805769    66.500519   100.033210    38.243472    21.429552
#>  [581]    35.849464    27.832320    42.276980   141.855202   108.842237
#>  [586]   113.209048    40.932875    31.415275    26.385132    25.796249
#>  [591]    44.596828   136.734716    39.113411    88.657524    43.650184
#>  [596]    30.565965    44.374236    25.166760    39.799153   139.989898
#>  [601]   112.345237   105.048307    47.806467    34.410027    33.377036
#>  [606]    25.100477    33.934663   134.232939   109.667560   108.007680
#>  [611]    46.322747    31.528887    36.890234    28.285215    32.815617
#>  [616]   129.861855   103.835167   105.723162    46.497357    27.632753
#>  [621]    39.557204    28.456075    37.007709   122.480471    91.297184
#>  [626]    99.087357    41.633584    31.281372    38.874662    30.189158
#>  [631]    38.613619   133.617479   102.807951    97.771981    48.130536
#>  [636]    30.429434    35.423973    26.915430    40.223614   139.184034
#>  [641]   106.234774   104.388371    48.370299    31.882032    34.893013
#>  [646]    25.255039    36.265976   129.206981   101.493353    99.002509
#>  [651]    44.346640    32.158756    39.429191    26.705643    37.622683
#>  [656]   132.237249   109.599833    92.242120    46.847184    31.010174
#>  [661]    37.535520    27.512162    41.985617   137.100186   105.086888
#>  [666]    94.188571    43.261979    33.923542    40.955904    24.140754
#>  [671]    49.249031   145.383441   108.475989   102.639441    44.052413
#>  [676]    31.671950    38.316922    26.313719    36.032487   145.339185
#>  [681]   109.010582   111.256913    44.568090    32.622182    43.235431
#>  [686]    28.846874    41.603560   185.257926    90.491924    55.381179
#>  [691]    52.559675    35.404760    39.212934    26.798098    37.332781
#>  [696]   207.062895   113.098940   112.052358    46.283524    25.168956
#>  [701]    36.233487    27.672381    44.556306   179.957265   110.232423
#>  [706]   102.707046    48.953326    36.362766    35.710726    34.303696
#>  [711]    39.764515   188.588142   113.188109   118.948407    48.587346
#>  [716]    33.652624    40.238380    31.320930    29.659764   191.976195
#>  [721]   104.352510   105.337010    47.377342    30.138890    35.353116
#>  [726]    30.443518    38.085864   161.939634    99.286794   113.933793
#>  [731]    47.386050    31.276776    35.586038    28.099018    38.582196
#>  [736]   158.502928   108.189300   108.556956    45.916943    29.664124
#>  [741]    35.072582    29.660793    30.060255   163.596847   104.458447
#>  [746]   111.339333    42.839141    30.381518    32.467032    27.207105
#>  [751]    31.829775   152.395823    92.090382   101.389516    38.136271
#>  [756]    30.162735    34.126044    27.465397    32.316456   159.614114
#>  [761]    97.103220    93.203515    44.641377    27.876265    36.166051
#>  [766]    25.380971    33.702906   155.271182   102.884171    96.148820
#>  [771]    44.848030    30.642579    37.470218    27.501099    30.589302
#>  [776]   163.899956   101.194633    95.039853    45.704995    32.728440
#>  [781]    33.720749    26.186973    36.896967   156.103823   113.336619
#>  [786]    98.596145    48.631773    33.012071    38.892305    28.817390
#>  [791]    39.441818   171.890864   112.334461   107.901088    46.708054
#>  [796]    32.391567    29.360276    26.269499    32.755082   160.337011
#>  [801]   113.112331    96.390912    47.874924    32.144085    34.075555
#>  [806]    32.297730    35.310021   149.723302   104.396845    99.148335
#>  [811]    44.486707    31.296760    33.825723    29.673124    34.026282
#>  [816]   165.011075   109.287485   105.432956    46.554563    31.546334
#>  [821]    34.769495    26.309489    36.822224   170.078539    97.233150
#>  [826]   103.437863    43.135479    28.860388    33.053009    23.208648
#>  [831]    38.422893   159.336934    88.512512   103.206401    47.365989
#>  [836]    31.572353    35.984752    22.722223    33.728057   146.322609
#>  [841]   107.862552   105.438540    47.479481    28.481425    31.647929
#>  [846]    26.164322    30.565289   149.787435   130.332740    98.296281
#>  [851]    41.290008    38.151850    34.086264    29.415540    37.504760
#>  [856]   201.926000   210.496647    93.751699    50.988839    51.721273
#>  [861]    47.046052    29.129116    59.443360   349.692621   411.374657
#>  [866]    85.913687    59.676289    90.024034    67.344532    40.821380
#>  [871]    91.276277   530.047933   697.728942    79.454606    74.053664
#>  [876]   132.664091    82.780161    49.933027   132.319325   649.397279
#>  [881]   841.452977    91.543068    92.976836   168.231806   102.184256
#>  [886]    58.848030   135.167703   733.247639   900.496888    94.106439
#>  [891]    90.594612   144.141867    95.562042    51.211730   137.975992
#>  [896]   645.368867   897.487709    86.226899    88.836395   139.545482
#>  [901]    74.780693    50.911947   104.015507   608.068443   704.566139
#>  [906]    94.131264    68.269341    92.880510    63.487855    35.247855
#>  [911]    72.120525   399.302359   426.784746    87.379760    60.358757
#>  [916]    63.452186    54.776193    29.311635    52.562169   282.731257
#>  [921]   278.563776    96.429320    49.760013    48.450612    38.933191
#>  [926]    25.844857    43.225975   212.039464   160.201024    98.777070
#>  [931]    46.029153    37.862905    37.250173    27.008984    35.842104
#>  [936]   169.997601   156.630668    93.014267    48.222163    35.064183
#>  [941]    35.451472    23.543123    32.686649   171.065548   105.790041
#>  [946]   108.830875    45.272460    31.981356    30.120026    23.585034
#>  [951]    32.319106   159.294988   115.495441   115.896828    47.765108
#>  [956]    29.215978    34.400212    25.209040    35.119547   165.818130
#>  [961]   107.669547   106.891347    46.208358    32.254054    33.814447
#>  [966]    24.801176    35.543628   155.108299   113.496329   110.971571
#>  [971]    44.721446    28.139904    31.768555    25.935012    31.160421
#>  [976]   141.595916   104.123449   109.959406    42.095975    29.355523
#>  [981]    33.334306    28.015602    32.062996   150.583101    90.077886
#>  [986]   105.341658    41.192123    29.251126    29.782968    26.674842
#>  [991]    36.906096   170.581104    97.567593   105.959960    39.480080
#>  [996]    28.286513    28.900908    22.996521    31.173936   142.981469
#> [1001]    93.127804   109.395854    44.881067    30.412322    33.138231
#> [1006]    24.754524    35.953917   140.121663   102.959301   105.862271
#> [1011]    40.174324    29.285178    32.617315    27.309924    38.589327
#> [1016]   166.073498    89.320133   106.740038    46.417630    29.564379
#> [1021]    39.726060    29.746300    34.125606   168.017869    90.316623
#> [1026]   107.312059    42.062266    29.621464    34.036371    26.995349
#> [1031]    34.642726   157.013142    97.627014   114.828925    46.800743
#> [1036]    27.051983    35.225135    28.283421    35.625325   175.540814
#> [1041]   118.424921   107.035100    43.272736    30.311741    34.189589
#> [1046]    27.176501    34.648530   180.816095   107.999549   106.611958
#> [1051]    44.284883    29.429024    34.550493    26.800240    36.931911
#> [1056]   156.397981   102.388683   114.543137    43.335283    29.670092
#> [1061]    36.463383    31.204052    36.964631   152.760545   105.690832
#> [1066]   112.532788    45.675366    31.084984    36.516981    27.889156
#> [1071]    39.951343   160.542475   108.768802   120.086017    44.621606
#> [1076]    29.979912    32.758499    29.640258    35.449074   144.627534
#> [1081]    95.904708    98.581966    29.151899    25.652984    34.015049
#> [1086]    23.739257    33.309044   132.845364   110.519425    97.435606
#> [1091]    36.445994    24.191037    33.755435    25.317860    34.692138
#> [1096]   133.370595    89.432865    78.788986    35.394559    32.745781
#> [1101]    34.401351    21.857643    37.652579   149.387315    92.966335
#> [1106]   117.034547    41.307684    25.799113    35.371046    30.828860
#> [1111]    36.504718   148.164662   173.861551    98.670328    50.817050
#> [1116]    24.953204    36.405526    20.948719    52.882848   151.105567
#> [1121]   391.764819   158.707810    32.949967    33.791382    46.733799
#> [1126]    21.774906    87.747553   160.094614   819.146131   141.687122
#> [1131]    41.526904    44.907794    62.191336    38.025100   108.899176
#> [1136]   242.205228   746.278612   165.371112    43.624310    52.703623
#> [1141]    95.556257    46.402372   204.718860   409.282334  1610.046856
#> [1146]   268.615342    60.597154    55.776300    92.681383    48.520625
#> [1151]   204.365289   371.091568  1585.529313   261.537745    35.539510
#> [1156]    62.214589    96.423575    29.725105   188.243389   314.450925
#> [1161]  1120.563718   255.135276    47.119980    48.516808    89.928485
#> [1166]    37.324552   142.475128   250.435000   566.727559   168.645876
#> [1171]    40.371340    44.392902    66.118259    29.763397    90.735531
#> [1176]   191.261879   789.235621   177.715166    49.942617    39.819652
#> [1181]    46.928773    29.820479    76.079930   172.221738   431.544954
#> [1186]   142.811706    44.438606    33.643979    39.060616    25.329606
#> [1191]    55.605822   151.479111   287.372645   130.826744    39.162669
#> [1196]    31.567921    36.137109    25.640328    36.565181   156.137129
#> [1201]   189.563114   114.160943    48.205198    27.381770    30.582241
#> [1206]    22.257580    40.508673   146.431932   116.312190   100.976158
#> [1211]    36.645808    27.605937    30.085477    26.043214    36.610432
#> [1216]   184.984871   126.509686    90.825038    36.832579    27.637315
#> [1221]    32.743402    25.398717    30.508300   140.194227   118.434799
#> [1226]    95.947858    29.674962    28.870998    33.375377    27.328116
#> [1231]    39.398779   178.195530   105.098561    84.987955    43.518142
#> [1236]    27.896133    36.033127    27.324011    34.533595   153.969597
#> [1241]    85.703834    99.892381    34.242776    26.875551    36.100405
#> [1246]    23.063659    30.791688   165.702633    67.073723   119.794516
#> [1251]    39.406710    22.804362    32.508115    31.149893    38.454433
#> [1256]   139.124003    99.513846    77.327728    43.546272    31.916123
#> [1261]    33.064523    31.806988    37.525104   183.940540   132.497918
#> [1266]    99.188331    47.054355    30.830371    34.161061    27.230252
#> [1271]    39.881592   186.165895    84.479401    96.370104    44.697988
#> [1276]    28.816349    31.995093    32.431530    39.123189   152.214855
#> [1281]    63.328493   124.861869    41.193206    28.866022    40.435678
#> [1286]    25.878933    35.254059   126.227156   110.655427   115.221361
#> [1291]    35.455676    30.530741    37.684927    17.316758    32.490885
#> [1296]   134.756237   105.090005   141.773908    34.771503    30.138122
#> [1301]    29.993710    19.134206    31.945019   174.943336    86.977711
#> [1306]   119.414188    46.054079    27.007063    37.394333    25.526424
#> [1311]    32.350547   176.360991   100.247268    92.214134    42.100218
#> [1316]    26.598997    31.552884    32.203519    33.252210   104.017945
#> [1321]   116.210076    62.106982    49.084530    26.358952    34.067227
#> [1326]    26.564477    36.290081   142.263964    47.620735   112.944846
#> [1331]    34.322501    28.551036    38.993419    22.362873    35.850753
#> [1336]   136.374939    99.798530    92.174216    24.876948    31.416041
#> [1341]    27.977401    22.599160    27.002678   136.757612    85.021712
#> [1346]    66.102933    48.928459    27.674189    31.963448    31.680869
#> [1351]    31.415532   206.067120    79.858983    67.724770    51.565559
#> [1356]    36.770206    33.478235    33.397290    30.300532   185.169355
#> [1361]    59.689057   113.624347    45.834682    35.071004    30.272516
#> [1366]    26.018613    31.311628   137.484421    97.771376    98.282888
#> [1371]    46.533382    32.927842    31.117646    27.572587    33.224553
#> [1376]   150.592315    72.236452    96.214203    52.651345    36.777134
#> [1381]    28.324229    32.304347    38.065710   116.620451    98.368924
#> [1386]   106.193656    54.976777    26.129837    31.190081    29.061710
#> [1391]    33.049347   235.458633    49.644926   105.635875    28.457881
#> [1396]    32.916288    41.376448    28.199523    32.091286   204.683036
#> [1401]    92.369982   117.488798    33.176475    37.188275    36.916034
#> [1406]    24.631105    35.289954   152.838308    74.815710    74.688163
#> [1411]    56.601092    27.957361    35.494486    34.825380    37.205302
#> [1416]   162.042605    49.309894   107.588334    42.188854    29.120570
#> [1421]    35.488853    19.608062    31.033799   186.844817    97.331014
#> [1426]    93.206562    48.051964    37.413884    27.915677    40.912424
#> [1431]    38.188606   119.108399    53.634031   105.031201    43.672971
#> [1436]    21.503384    31.892517    27.013946    45.004002   110.739233
#> [1441]    95.821644    93.103918    58.389068    28.267440    35.444377
#> [1446]    24.704700    36.539813   212.861125   103.871532   129.800170
#> [1451]    40.755682    30.372291    37.629196    28.002186    35.415052
#> [1456]   235.109370    80.404990   123.798571    36.751008    41.045761
#> [1461]    29.878926    24.239642    40.312472   127.568099    57.314662
#> [1466]    97.914116    46.504641    29.215859    38.111446    25.698333
#> [1471]    34.554269   157.990302    84.496738    74.541171    32.664953
#> [1476]    40.293004    28.729528    28.841443    38.652989   144.608685
#> [1481]   103.610632    91.145180    38.251578    32.525705    29.559268
#> [1486]    28.371520    34.002482   139.517177    47.311838   122.164686
#> [1491]    46.971462    28.612430    36.331883    27.220920    31.552084
#> [1496]   207.302292    91.903460   114.640190    30.747115    26.480455
#> [1501]    37.264549    30.834890    32.124568   183.139218    70.849133
#> [1506]   129.735962    40.666440    24.421463    35.638740    17.057095
#> [1511]    35.863203   160.275320    89.107102   123.293859    35.963508
#> [1516]    39.949520    35.584113    20.181869    31.828364   135.130744
#> [1521]   119.125820    96.000743    45.748627    25.493576    37.545546
#> [1526]    21.838315    35.173620   172.009139    70.488143   104.181722
#> [1531]    25.083607    32.690491    41.949165    15.853308    37.556713
#> [1536]   156.180366    89.693465    88.501997    23.182854    33.387140
#> [1541]    39.341711    19.210659    38.406144   160.599245   123.616225
#> [1546]    92.213588    36.325025    32.144818    46.369477    39.971955
#> [1551]    33.936432   195.647481    77.179203   111.316890    33.769247
#> [1556]    26.788419    46.454249    24.763817    39.588913   146.920034
#> [1561]   126.582540   109.726625    40.927068    38.069900    41.180900
#> [1566]    27.001062    34.850588   197.805155    80.765977    97.622657
#> [1571]    26.326894    27.408477    42.529164    21.699734    30.852826
#> [1576]   171.079778    93.319155   103.618405    31.096392    37.420658
#> [1581]    33.034041    21.859346    35.250289   171.183623    87.360047
#> [1586]   100.242504    32.113428    26.525980    42.798271    20.262626
#> [1591]    28.644451   176.150627    69.840818   119.224692    25.607179
#> [1596]    31.822188    35.727435    21.551686    35.178318   156.434354
#> [1601]   104.369524   101.711197    53.031272    29.573143    32.794880
#> [1606]    29.026631    36.193032   154.152449    89.099312    98.262950
#> [1611]    40.983253    24.163189    34.501748    31.976277    35.426385
#> [1616]   148.537631    97.701749   109.391669    46.714138    25.523892
#> [1621]    31.964336    35.362196    33.886820   157.480453    86.366383
#> [1626]    79.107788    38.764546    26.201341    25.624606    28.607790
#> [1631]    33.253877   142.411533    90.983309    93.451915    47.661561
#> [1636]    26.865360    32.096030    31.834129    31.258656   230.045142
#> [1641]    71.557235   132.132516    47.257443    24.495178    37.002452
#> [1646]    20.361930    36.194230   248.565752    64.068487   157.677227
#> [1651]    53.574143    24.249650    37.743398    21.712505    28.686528
#> [1656]   218.324965    66.007129    89.803788    46.140171    23.027989
#> [1661]    29.306930    27.006135    32.963365   187.819705    85.063270
#> [1666]    81.274325    43.366147    28.403436    37.554051    21.598555
#> [1671]    36.212499   158.448519    78.372012    77.477039    29.996444
#> [1676]    32.272852    32.906730    24.015367    33.172171   272.487378
#> [1681]    84.846888    85.014031    29.668608    39.581763    40.042868
#> [1686]    37.099377    36.948299   203.872117    61.969520   146.510894
#> [1691]    38.981498    30.018676    20.476881    36.929195    43.787444
#> [1696]   154.430081    90.605106   146.302234    40.669078    27.420887
#> [1701]    35.429644    57.348454    34.920677   263.241275    71.016427
#> [1706]    79.633341    50.394459    25.392463    40.220837    52.619259
#> [1711]    42.117045   215.196783    58.495471   108.490964    61.623339
#> [1716]    23.415285    38.055228    26.456648    61.001604   266.378869
#> [1721]    93.817655   121.125686    57.490407    37.148676    27.849703
#> [1726]    45.148767    50.306234   197.005061   106.544321   102.487807
#> [1731]    27.663152    38.055031    43.434172    48.045937    40.335960
#> [1736]   191.640031    67.029701   137.051483    65.579437    22.572407
#> [1741]    38.649261    40.508534    57.055165   140.799223   133.669713
#> [1746]    74.303656    56.998198    39.294406    36.815819    25.600391
#> [1751]    54.495908   295.211768   127.769307   109.169560    30.880279
#> [1756]    32.020910    43.418441    48.313316    48.187284   147.377280
#> [1761]    94.739802   119.769936    46.917040    39.250639    41.261021
#> [1766]    28.507046    41.979571   196.337320    81.106436   168.109136
#> [1771]    52.962343    21.686875    30.963254    43.027813    38.210871
#> [1776]   307.503439    80.468017   141.685174    47.534258    29.558209
#> [1781]    37.009343    37.449933    41.153272   166.665936   105.003535
#> [1786]    86.877174    55.994831    38.115102    45.375383    23.711647
#> [1791]    45.017327   195.095036    64.489254   141.102600    58.586026
#> [1796]    24.740041    39.417257    45.935621    44.368479   248.729436
#> [1801]    99.076422   108.528579    57.070673    37.177808    25.617253
#> [1806]    43.001979    56.238403   242.362830    68.406010   149.126453
#> [1811]    26.213064    36.171577    40.075221    32.053932    54.676368
#> [1816]   356.667826    55.901124   155.707960    67.176312    30.555825
#> [1821]    36.290777    51.125159    69.950411   172.199389    84.890150
#> [1826]   155.172876    20.486742    34.701371    45.691073    48.161121
#> [1831]    36.894187   302.110497    93.596723    91.851749    65.116098
#> [1836]    39.147736    36.466925    26.774093    69.335105   296.318700
#> [1841]    90.782109   215.716420    51.973785    27.257805    30.972503
#> [1846]    49.214708    58.873692   155.052388   131.714048   176.217341
#> [1851]    27.778185    31.060168    43.479056    37.612360    33.331283
#> [1856]   271.083706   108.032408   101.957330    52.877356    36.519604
#> [1861]    33.477509    23.041509    56.101345   305.169499   113.602917
#> [1866]   211.426262    53.749557    18.842347    39.586898    44.027395
#> [1871]    43.585771   185.544784    99.435757    98.333853    53.386409
#> [1876]    34.430626    30.946110    25.427338    38.509870   285.530040
#> [1881]    52.472315   198.993257    58.660556    38.832734    37.082364
#> [1886]    44.011392    41.031400   188.437410    87.474563    98.043931
#> [1891]    78.003673    34.698912    41.750663    35.420446    39.510279
#> [1896]   383.074116    98.765139   119.145008    51.552674    33.715571
#> [1901]    34.694111    42.824697    48.457643   296.863562    84.082733
#> [1906]   114.538239    28.738582    42.499469    43.984079    36.904957
#> [1911]    35.895894   325.381169    81.027964   137.467786    38.488739
#> [1916]    27.329626    47.504072    16.035063    58.288272   280.982411
#> [1921]    81.964843   147.251262    41.919116    28.917983    29.126941
#> [1926]    24.707881    54.181098   242.407159   100.310015   137.655731
#> [1931]    41.494815    26.177019    28.914556    26.650264    46.273476
#> [1936]   231.882754    89.895481   112.320566    32.803755    33.588569
#> [1941]    33.033767    26.608555    50.960213   458.659131   107.640478
#> [1946]   150.360576    65.517246    35.414668    38.215521    43.125685
#> [1951]    50.555097   283.978981    97.550146   135.993181    58.664513
#> [1956]    35.917116    36.995451    38.546234    49.043232   325.272207
#> [1961]    98.996154   147.221397    69.319522    35.468042    35.986838
#> [1966]    38.794882    50.329541   335.374756    96.065313   147.845948
#> [1971]    61.414690    35.989945    36.926313    38.591692    51.843903
#> [1976]   324.264422   101.529915   135.551127    65.209398    36.824668
#> [1981]    37.633576    39.007057    46.347952   316.556611    96.712077
#> [1986]   142.219890    66.475186    34.892562    35.069106    41.596664
#> [1991]    52.278679   254.675998   109.176872   154.631251    65.022175
#> [1996]    43.055877    43.341532    49.361935    54.482969   354.457471
#> [2001]    89.377830   160.112253    64.213553    42.558553    39.835207
#> [2006]    59.856009    60.354117   379.372871   109.208437   166.123293
#> [2011]    61.810196    39.636466    40.870663    51.759527    54.428493
#> [2016]   376.155093   103.506800   170.954710    64.387163    40.418625
#> [2021]    39.887188    55.752389    56.483176   362.650536   115.075388
#> [2026]   143.364995    57.492267    38.523954    32.647061    51.301592
#> [2031]    46.871748   384.224012    88.074090   163.403510    47.091308
#> [2036]    38.166879    36.352915    38.096904    53.610835   368.810280
#> [2041]   108.832158   153.158567    67.981493    44.443709    39.159903
#> [2046]    52.367430    53.014402   415.838201   115.424278   153.048996
#> [2051]   120.144144    40.145176    36.078019    44.489095    52.712724
#> [2056]   389.350239   110.070706   146.372008   163.313465    46.588510
#> [2061]    40.543530    47.885738    53.107820   399.845750    96.952821
#> [2066]   155.735393   141.124334    46.514724    44.535562    46.303457
#> [2071]    52.881468   407.918184   114.145907   158.973029   121.196010
#> [2076]    32.334025    36.807087    48.935408    55.988427   400.204529
#> [2081]   122.143079   148.332373   109.835709    40.129369    39.771837
#> [2086]    36.824987    59.225614   334.339159   105.224713   149.474562
#> [2091]    79.284124    46.528001    41.737876    45.739151    70.237961
#> [2096]   403.477595   117.842087   495.825624    74.954894    34.224355
#> [2101]    40.451839    46.355804    62.324136   286.454247    89.056594
#> [2106]  5832.395161    87.522507    51.302731    41.023700    29.757374
#> [2111]    48.602331   235.819508    67.292766 13873.384850   112.370406
#> [2116]    75.664919    37.635591    27.751099    37.371573   267.709799
#> [2121]    52.310421 17165.405181   191.168944    82.199662    32.221482
#> [2126]    24.518181    33.193361   252.173733    49.401413 16437.503614
#> [2131]   159.827322    89.323235    36.391296    22.471497    35.772829
#> [2136]   252.290946    65.733328 13755.012642    97.936771    60.497118
#> [2141]    33.123704    27.679177    34.807008   253.211050    56.774516
#> [2146] 10955.394431    96.865632    51.837906    29.911206    29.050536
#> [2151]    40.047838   234.478684    82.087474  9493.409165    83.231644
#> [2156]    51.672872    35.252748    29.158378    48.748037   365.643260
#> [2161]    90.750294  6442.331874    75.831233    52.951960    38.056488
#> [2166]    33.368845    48.303094   352.849221    91.706198  4600.186775
#> [2171]    69.476735    52.822776    38.611727    44.488193    51.911443
#> [2176]   431.401173   101.796074  2892.800990    66.987991    51.283043
#> [2181]    38.911728    45.438261    47.577080   399.170704   108.112526
#> [2186]  1774.720067    64.928496    46.699510    43.879691    40.686856
#> [2191]    50.936232   445.515064   106.386173  1354.003510    64.540338
#> [2196]    49.147460    35.080291    46.991590    48.374540   428.179441
#> [2201]   103.169871   941.571921    72.048556    53.248166    36.666954
#> [2206]    48.456305    46.269972   422.903522   110.674410   752.972866
#> [2211]    70.220963    49.831384    37.652212    45.846990    49.459702
#> [2216]   447.458198   106.774150   630.149374    69.259278    51.613374
#> [2221]    33.897051    46.393051    46.725414   449.146344    97.630969
#> [2226]   541.745739    75.886827    41.253986    40.926556    45.904882
#> [2231]    45.775102   470.359972    99.460572   494.868960    72.884706
#> [2236]    52.137230    42.584389    46.582839    49.957400   438.727083
#> [2241]   110.900816   455.857940    75.793757    50.861001    43.644965
#> [2246]    48.120407    47.968101   472.913455   113.232404   394.845602
#> [2251]    73.335230    53.254563    39.055537    43.107564    44.777950
#> [2256]   486.724239   112.924868   342.480613    71.166023    52.477110
#> [2261]    43.093652    48.508074    47.582490   473.236068   107.121591
#> [2266]   314.538700    68.552210    49.572075    46.860595    42.282366
#> [2271]    41.354109   435.768428   106.979632   279.561779    63.373882
#> [2276]    53.443520    39.888940    47.507710    46.408509   479.389012
#> [2281]    99.470195   295.953485    70.021186    46.548519    40.014569
#> [2286]    43.371476    40.823099   454.627431   116.416887   241.948283
#> [2291]    65.018561    48.924704    37.893611    42.659015    49.039957
#> [2296]   491.670790    95.426186   237.162205    68.319898    53.581855
#> [2301]    36.353723    44.225962    45.001981   447.547469   109.786524
#> [2306]   237.586439    66.047106    45.552718    36.644631    43.799834
#> [2311]    44.847455   418.299828   122.267204   222.628184    64.904554
#> [2316]    46.077932    36.239206    50.909309    45.872858   475.359280
#> [2321]   121.625129   213.582292    64.780518    46.055814    41.639253
#> [2326]    43.247804    47.021251   482.833683   143.198061   203.076683
#> [2331]    61.808888    44.536787    41.674611    50.834753    49.958632
#> [2336]   462.927389   133.091117   212.156884    65.674832    45.832769
#> [2341]    45.227610    50.943171    45.399300   476.837618   134.462510
#> [2346]   212.997852    83.683738    46.307428    44.114147    49.426245
#> [2351]    46.066511   445.476788   146.815803   205.989675   147.752024
#> [2356]    50.177558    52.419657    55.526217    47.264174   490.760576
#> [2361]   170.817562   214.155841   181.371703    57.437563    52.451408
#> [2366]    60.217505    50.999636   485.747137   160.952902   195.593397
#> [2371]   186.363268    62.290553    47.320707    57.157110    49.019309
#> [2376]   485.676005   143.149765   199.440368   135.085678    76.823418
#> [2381]    45.874357    46.694395    46.705219   472.472557   122.590519
#> [2386]   196.164505   114.501037    81.142977    42.737055    47.379126
#> [2391]    43.960697   469.841693   120.431267   179.920177    88.308295
#> [2396]    75.505423    40.908099    55.427963    50.543494   447.686020
#> [2401]   112.830110   183.489394    70.699660    60.818758    41.392392
#> [2406]    63.049013    48.161211   447.263685   113.098922   186.604226
#> [2411]    70.344673    56.597906    43.191166    63.650399    43.669881
#> [2416]   478.137230   111.280911   183.160843    68.099514    54.380999
#> [2421]    45.587965    63.487612    47.277363   435.605030   113.039216
#> [2426]   163.528049    64.942955    46.626150    40.701930    53.573868
#> [2431]    44.855228   428.627071   111.044178   183.114925    71.578556
#> [2436]    40.439535    44.389309    57.025407    46.306825   438.637845
#> [2441]   106.830294   180.154460    71.048972    44.054351    41.686204
#> [2446]    47.594233    50.640354   477.948657   107.768497   183.448420
#> [2451]    70.589348    41.367258    40.588047    57.552715    43.678015
#> [2456]   505.276160   106.934839   175.443230    64.234972    45.826434
#> [2461]    41.444938    51.237273    49.127882   456.103902   110.304658
#> [2466]   181.128785    64.361756    42.257462    36.234890    56.042026
#> [2471]    46.002784   461.831220   112.112989   177.799746    59.419955
#> [2476]    45.835058    37.143329    57.791545    46.574726   473.481790
#> [2481]   113.347008   187.479618    60.441204    44.384575    36.748130
#> [2486]    58.255789    50.525020   468.894201   112.097804   172.268805
#> [2491]    66.881132    47.767594    35.614725    62.727494    47.721740
#> [2496]   479.832255   115.216485   168.147780    64.495323    48.895200
#> [2501]    40.707435    62.435092    44.537999   477.044890   107.602994
#> [2506]   160.913590    67.899740    48.596475    37.600284    50.072798
#> [2511]    44.891404   446.804062   111.290585   162.397966    61.712172
#> [2516]    41.225893    35.227686    51.303568    45.314574   461.196746
#> [2521]   115.938279   177.651151    67.345495    46.733009    39.527198
#> [2526]    56.816790    52.750451   424.494314   111.871450   163.096121
#> [2531]    80.499247    49.625922    40.675166    50.999692    52.492706
#> [2536]   468.263938   113.744053   176.055005   122.768205    47.463385
#> [2541]    41.041710    53.205646    78.578701   584.468115   115.955268
#> [2546]   191.130047   181.661404    54.624808    37.018977    56.041601
#> [2551]    70.841264   664.795500   124.590019   224.475239   187.583307
#> [2556]    50.438938    40.283084    50.180244    86.135610   570.187038
#> [2561]   134.230020   219.730538   146.569392    50.101408    39.866188
#> [2566]    49.076670    72.141985   521.389886   117.411897   200.841469
#> [2571]   111.737539    50.180836    39.118886    49.177277    63.998615
#> [2576]   466.357814   130.208352   186.026854    90.567113    47.000837
#> [2581]    39.512403    47.244710    59.240777   451.402441   121.219202
#> [2586]   183.565928    85.706048    51.367771    41.658139    46.595095
#> [2591]    62.208513   461.008189   112.948330   208.372259   106.603505
#> [2596]    50.952128    40.728191    55.395050    68.092937   587.144867
#> [2601]   121.209110   245.040250   166.608778    50.820778    46.078316
#> [2606]    54.586626    73.634932   629.747347   106.906315   220.482740
#> [2611]   174.262815    48.301433    46.288178    55.616089    77.046168
#> [2616]   610.995708   103.686176   194.916945   156.926065    48.564475
#> [2621]    44.978622    52.375992    70.770942   566.716943   114.624499
#> [2626]   180.656253   109.721550    47.479018    45.371014    50.931045
#> [2631]    70.955909   522.202017   110.237149   173.128564   100.635447
#> [2636]    45.183336    41.858009    48.651565    64.857451   435.670086
#> [2641]   109.835674   173.932545    76.596251    49.585715    44.332319
#> [2646]    47.835264    54.787442   399.844011   105.368428   158.937927
#> [2651]    71.319149    45.394350    41.681597    52.281926    49.528685
#> [2656]   382.456539   105.509972   162.843921    77.230597    44.006242
#> [2661]    37.321572    83.274316    49.168353   432.168623   105.166536
#> [2666]   154.536989    63.360656    43.257950    38.976037   121.911508
#> [2671]    41.409602   416.626463   104.332561   150.248674    65.020749
#> [2676]    48.399111    35.372174    97.019543    41.577903   386.252188
#> [2681]    99.126223   136.614468    69.607545    41.745846    33.963000
#> [2686]    89.715885    47.772692   373.844217   108.473919   138.761989
#> [2691]   107.148913    45.289243    38.850900    66.693888    47.320003
#> [2696]   374.427710   100.337538   147.019071   108.946940    44.767658
#> [2701]    31.970107    55.714322    40.898479   384.554854   104.902908
#> [2706]   152.970046   102.968200    42.386481    35.469126    46.910892
#> [2711]    39.892412   392.099680   111.670846   158.119160    93.352925
#> [2716]    43.845470    34.770151    43.459377    45.528240   368.951429
#> [2721]   100.894014   141.036437    91.908482    42.468380    35.463312
#> [2726]    43.798070    53.840996   376.266252    99.509117   133.894132
#> [2731]    89.294837    39.262945    37.729908    43.829460   216.280428
#> [2736]   351.838721   101.478866   140.720373    82.380093    40.751900
#> [2741]    37.179003    47.645561   397.230075   362.989834    98.861373
#> [2746]   140.412077    70.692329    50.636567    35.765085    50.151279
#> [2751]   320.469480   356.958652   108.716669   141.060782    78.796086
#> [2756]    43.260207    37.810845    44.797668   278.136920   334.220326
#> [2761]    93.462171   133.870650    69.984913    42.031692    39.729968
#> [2766]    42.617221   203.946074   375.335101    92.918614   150.667486
#> [2771]    66.658469    64.518478    40.465141    37.987780   319.792309
#> [2776]   381.687629    95.203955   158.715536    62.906516   118.817601
#> [2781]    35.928716    44.179380   422.806755   339.826894    96.870755
#> [2786]   170.204776    65.174303   129.831309    39.115973    46.567989
#> [2791]   277.553212   379.195222   100.939231   160.881076    61.380293
#> [2796]   113.236567    30.495809    43.721927   221.316362   331.970851
#> [2801]   101.783902   156.075804    65.746408    94.056235    33.463657
#> [2806]    41.203415   134.397904   335.178189   109.343455   159.628160
#> [2811]    56.701886    75.474413    33.982118    40.438525    92.386664
#> [2816]   413.892579   107.377343   207.107832    58.226374    60.382087
#> [2821]    39.293829    41.553251    67.557693   502.811196   100.060179
#> [2826]   241.096155    63.202887    55.581887    32.281917    48.897676
#> [2831]    54.018214   530.671079    98.657496   250.577511    64.236887
#> [2836]    57.254045    29.696300    53.560764    47.510936   482.104900
#> [2841]    87.972094   243.426023    68.539853    80.170418    33.892214
#> [2846]    60.884106    52.454029   417.665537    95.028840   202.186937
#> [2851]    65.538071    96.851122    35.226911    49.554699    47.346519
#> [2856]   452.073756   105.329216   179.652847    63.027096    89.270784
#> [2861]    32.109190    50.222711    40.365956   390.430038    94.825371
#> [2866]   154.653021    65.312407    74.879131    39.632950    43.034229
#> [2871]    44.376038   364.625164   106.327953   155.579487    56.476849
#> [2876]    68.204701    37.557180    40.732334    51.897565   338.730040
#> [2881]   101.356362   152.716527    56.022610    64.241037    38.503367
#> [2886]    39.174198    48.377148   339.486165   101.688007   149.401876
#> [2891]    84.371173    66.150104    48.432286    44.200528    48.981838
#> [2896]   350.977215   101.010195   155.124837   261.774278    62.327187
#> [2901]    50.881668    41.499536    58.946579   426.405576   137.709243
#> [2906]   154.974981  1044.061565    75.624113    52.398541    56.741179
#> [2911]    90.532370   475.939693   236.967228   139.114540  3432.023477
#> [2916]   110.743161    75.961875    92.011387   166.027562   929.845177
#> [2921]   504.843100   139.855029  6483.536127   197.809790   140.472021
#> [2926]   127.368047   224.242597  1451.459637   717.187880   141.928024
#> [2931]  7367.100911   239.956124   158.085961   124.970249   220.324988
#> [2936]  1630.745826   600.373785   130.757386  6646.782293   195.933957
#> [2941]   165.239449   116.567387   190.198294  1142.097216   483.831937
#> [2946]   129.864168  5204.742301   162.181947   194.907652   100.592671
#> [2951]   155.622761   852.478428   309.304721   137.013250  4042.596232
#> [2956]   117.024751   183.219997    75.718323   108.972406   623.185056
#> [2961]   276.796656   138.015189  2280.942842    83.652375   146.110538
#> [2966]    57.217777    85.910595   426.909449   169.369923   130.765452
#> [2971]  1129.015567    72.541058    98.417314    51.786954    65.490581
#> [2976]   370.740360   137.832735   128.707394   584.099025    70.200104
#> [2981]    78.216922    45.082211    53.395062   396.197642   115.825544
#> [2986]   164.890511   344.759542    67.780839    58.186826    49.007957
#> [2991]    57.555344   377.432551   103.528653   173.131749   304.128630
#> [2996]    82.324333    59.280267    49.017062    58.471389   385.087567
#> [3001]   107.713102   188.159390   256.629299    76.506054   144.285021
#> [3006]    51.495279    51.635400   381.894585   115.585556   176.218209
#> [3011]   207.990364    64.513575   471.014842    48.795036    46.370679
#> [3016]   413.799603   114.708741   170.739805   142.628879    51.914241
#> [3021]   766.677505    46.983835    45.447159   385.264893   105.968021
#> [3026]   157.320836   124.018762    52.331639   727.865570    45.855819
#> [3031]    48.050871   464.501195   108.529287   140.250347   114.867799
#> [3036]    49.210129  1365.406863    50.159966    48.346549   401.379074
#> [3041]    94.303394   127.682224    76.557818    38.802320  8245.265938
#> [3046]    75.312788    41.553529   443.388435    82.071571    97.633059
#> [3051]    55.690245    35.804840 11817.493575    99.572008    41.501168
#> [3056]   446.000312    72.960672    84.298512    48.043065    35.754181
#> [3061] 12414.736519    99.395533    38.658161   397.013831    74.672682
#> [3066]    72.898924    43.723220    44.488826 12981.508815   108.049080
#> [3071]    39.232533   376.557258    79.987398    79.204333    40.242510
#> [3076]    44.137902 13369.054391    87.335052    34.362953   431.964433
#> [3081]    80.404728    81.348712    39.098851    42.970071 12251.031919
#> [3086]    83.383473    40.176316   405.543253    73.572794    92.162209
#> [3091]    47.164285    47.335381 11181.342307    80.073486    33.482190
#> [3096]   381.244893    82.093875   106.339604    55.248650    41.232214
#> [3101] 10035.242946    67.145501    41.769664   351.287240    79.788459
#> [3106]   116.131377    54.850998    41.936423  7552.693637    64.331488
#> [3111]    45.096367   363.235391    88.494106   152.857911    58.406151
#> [3116]    45.085574  5274.329443    54.984343    51.276605   384.683981
#> [3121]    85.207682   170.325455    56.245315    48.942358  3446.959797
#> [3126]    62.191727    72.638760   376.092814    96.718939   207.073727
#> [3131]    51.516924    58.128504  2306.458394   105.223533    90.857087
#> [3136]   437.576096    91.756143   202.965217    50.084695   171.950652
#> [3141]  1713.140865   201.747017   165.403270   574.701225    97.888899
#> [3146]   224.355435    50.426250   643.298990  1559.863603   357.425180
#> [3151]   250.534715  1457.781432    77.966053   327.988844    48.599136
#> [3156]  1830.193673  2340.699961   361.455326   221.523901  3259.837324
#> [3161]    80.292646   667.704245    46.440136  3960.048515  3318.063234
#> [3166]   374.118420   251.656618  4836.139255    75.492559   911.828175
#> [3171]    45.894324  5028.931315  3790.007761   376.525573   204.266086
#> [3176]  6447.558959    81.661543  1083.513819    48.934917  5462.590695
#> [3181]  4040.078162   316.379302   201.778532  5451.933901    77.594644
#> [3186]  1029.314338    50.048455  4427.503115  4019.770812   354.163547
#> [3191]   159.297537  4770.406330    89.531190   681.997054    50.058454
#> [3196]  3735.746069  3014.155752   253.142876   138.573892  3442.385517
#> [3201]   108.520769   567.223315    48.193977  2389.961043  2112.600046
#> [3206]   167.179547   116.898048  2200.591211    90.379031   389.386558
#> [3211]    58.841952  1387.697525  1671.304308   122.009446    91.749983
#> [3216]  1334.821787    86.827529   273.706301    47.739604   682.037909
#> [3221]  2702.578604   116.541629    68.538327  1053.298147    90.165921
#> [3226]   199.887662    48.969506   366.617997  8110.564172   119.166472
#> [3231]    57.492952  1253.169747    79.696759   125.325973    70.386734
#> [3236]   185.103845 17817.324496   154.758688    54.444984  1848.090470
#> [3241]    86.306052   112.925436    69.415037    97.107928 24421.982208
#> [3246]   177.387707    53.053684  2350.667822    68.231133   115.283247
#> [3251]    70.470103    67.408725 24224.176889   199.367430    54.483140
#> [3256]  1851.521975    71.252109   104.026548    73.399323    62.840590
#> [3261] 20173.169426   159.624412    54.335656  1643.522781    75.692504
#> [3266]   112.373523    84.076986    71.224743 15413.772897    94.253645
#> [3271]    46.128246  1353.106928    87.476977   123.569037    76.496362
#> [3276]    83.747586 10410.026459    73.003667    43.600309   914.755517
#> [3281]    86.775649   147.780305    77.343147    80.636035  5586.789067
#> [3286]    59.589081    41.941584   542.935288    94.678388   156.837136
#> [3291]   111.355258    84.365073  2892.251637    49.823283    51.304918
#> [3296]   529.727005   106.611109   202.748799   118.293521   114.514784
#> [3301]  1277.830641    57.576321    46.114399   422.564773   105.676005
#> [3306]   216.152271   131.173524    98.990215   730.104704    56.522926
#> [3311]    53.390978   384.438329    93.755092   285.822187    97.594344
#> [3316]    85.205392   547.206071    46.915710    51.918508   404.797401
#> [3321]    93.750448   295.711001   140.678887    77.257286   421.634536
#> [3326]    46.707930    54.991718   377.567921   100.374922   312.936990
#> [3331]   132.502633    71.580301   274.483526    49.194447    61.477936
#> [3336]   431.160271    88.113807   354.666093   124.343121    70.724463
#> [3341]   237.235026    53.864975    57.278502   386.820263    99.928820
#> [3346]   387.976732   135.955634    88.630018   214.309572    54.529801
#> [3351]    54.718577   337.031514   114.828256   287.822821   156.152333
#> [3356]   119.974355   180.442025    69.066942    51.631361   386.171758
#> [3361]   110.462710   307.941976   156.382602   142.630032   144.549083
#> [3366]    53.404418    50.098636   364.021570   140.529983   246.337782
#> [3371]   215.574043   150.186601   143.793425    44.319647    49.858377
#> [3376]   425.172901   146.985848   220.863097   398.886785   190.947449
#> [3381]   121.991410    53.573488    47.726592   383.298964   129.257191
#> [3386]   217.825355   747.478983   243.704667   125.857035    54.983686
#> [3391]    50.734335   448.644560   128.739227   227.458562  1514.914099
#> [3396]   446.209846   125.520585    50.398286    59.134788   446.003391
#> [3401]   107.173052   231.371720  2620.309723   705.822113   115.209906
#> [3406]    53.223066    70.486035   459.659304   106.569502   337.338604
#> [3411]  4899.363778  1153.960002   134.494480    56.529112    78.164909
#> [3416]   583.802260   104.608224   499.497467  7395.244639  1887.052951
#> [3421]   211.215561    94.945173   103.651928   788.532002   106.056672
#> [3426]   800.572374 10043.866250  2623.693823   240.230819   111.280702
#> [3431]   148.987083   914.847067   109.614644  1249.143255 12097.695780
#> [3436]  3653.450436   277.743610   182.055874   179.234241  1221.271458
#> [3441]   126.401723  1715.142546 14563.587860  5407.566131   264.512774
#> [3446]   210.784998   229.734521  1587.126612   124.967387  2232.878777
#> [3451] 15532.657079  6234.608575   269.324034   208.424586   233.263276
#> [3456]  1552.763248   120.786471  1960.332508 15743.664269  5880.225753
#> [3461]   220.480492   230.471743   231.182513  1374.267268   122.930560
#> [3466]  1785.462605 13040.903736  4625.013483   185.892917   177.027535
#> [3471]   207.044462  1064.031657   129.958451  1151.740920 10275.138221
#> [3476]  3030.566003   134.904623   101.688033   129.392091   737.169609
#> [3481]   110.267769   682.744596  7212.835770  1644.275912    96.058334
#> [3486]    74.493444    88.870497   520.998709    98.802609   438.159170
#> [3491]  3896.246661   903.259424    80.395037    70.742299    64.676344
#> [3496]   463.621414    92.772626   298.435963  2059.432492   466.110953
#> [3501]    74.424627    65.230299    55.563819   424.500233    95.895749
#> [3506]   218.235428  1111.334132   276.446303    70.360008    58.971164
#> [3511]    51.898553   421.426599    94.400382   183.128169   641.387997
#> [3516]   186.855560    64.828225    61.017041    46.322119   405.869448
#> [3521]    96.276210   165.488380   444.988146   134.354429    68.978034
#> [3526]    59.648629    41.928908   390.248778    97.680430   142.669647
#> [3531]   326.401134   100.406484    69.730199    56.872277    47.295864
#> [3536]   410.286925   100.654992   147.297034   253.873683    88.259557
#> [3541]    69.272909    54.819753    53.691147   357.119705    96.424177
#> [3546]   159.983678   197.203818    70.524063    64.887608    59.124792
#> [3551]    55.327900   392.013416   112.728092   166.700046   165.703903
#> [3556]    70.800969    71.877032    53.680604   150.170933   386.079010
#> [3561]   128.308721   142.192752   116.723960    63.349980    94.577026
#> [3566]    52.785717   618.750584   350.651580   115.429550   162.722968
#> [3571]    86.215457    51.653908   203.842317    53.626194  2246.121891
#> [3576]   382.415158   102.911678   134.274657    65.262824    67.883797
#> [3581]   529.226182    68.566852  6140.326677   470.275514    86.503963
#> [3586]   120.076985    52.290525    95.471138  1327.676572   152.403422
#> [3591] 12409.546012   446.365777    81.111320   120.051437    38.316607
#> [3596]   125.396044  2111.053553   192.086990 15265.605845   505.665088
#> [3601]    68.267354   110.300507    42.960764   122.990922  2434.511379
#> [3606]   193.448085 13856.641640   473.746327    61.488787   118.927335
#> [3611]    40.846413    98.481253  2635.015115   145.921496 10782.008108
#> [3616]   514.134987    75.622974   108.849099    43.482325    72.364911
#> [3621]  3990.963925   135.316360  7795.630482   619.633191    76.814228
#> [3626]    96.248114    42.018788    61.545582  5406.427674    89.845524
#> [3631]  4769.421076   970.879131    75.477365    85.024211    40.636458
#> [3636]    56.770813  5599.366446    84.311730  2351.550069  1181.581148
#> [3641]    78.535752    87.937028    51.470706    80.762274  5635.438907
#> [3646]   160.984848  1184.728514  1395.521664   100.176642    86.781772
#> [3651]    73.051767   160.614398  5912.221951   219.380200   738.510947
#> [3656]  1140.732565   145.020645    84.483414    86.219270   289.808744
#> [3661]  4809.441537   317.619402   519.229572   955.273766   138.266457
#> [3666]    86.975240    94.872176   315.805714  4244.719148   287.564623
#> [3671]   385.001572   745.416471   139.109839    94.263892    89.964926
#> [3676]   245.282922  3344.973796   379.042695   285.002069   562.866452
#> [3681]   118.547819    93.237187    90.176100   196.391278  2100.318811
#> [3686]   372.299956   239.873667   524.349564   106.931143   106.563291
#> [3691]    76.841937   139.732984  1207.312222   316.286884   197.681512
#> [3696]   436.388388    91.078274   113.614040    71.921476    96.063303
#> [3701]   652.662973   256.810664   168.067726   441.319650    88.802723
#> [3706]   109.248382    81.351967    73.164431   396.452972   225.406458
#> [3711]   142.344921   374.552271    93.302201   111.343348    67.648089
#> [3716]    70.830980   300.911453   204.240726   133.175767   342.959788
#> [3721]    87.580712   113.913341    69.461376    65.748910   411.875001
#> [3726]   308.109618   129.885858   418.053823    88.435850   126.543285
#> [3731]    58.067230    82.053081  1163.347622   656.206055   142.131827
#> [3736]   483.019800    81.782910   125.925370    55.778440   134.806233
#> [3741]  4152.926938  1369.659515   175.497921  1422.080153    74.546009
#> [3746]   142.809977    57.799691   158.359331 10781.055266  1887.565770
#> [3751]   254.454628  4125.279513    57.171463   159.062548    49.352282
#> [3756]   191.586048 19414.716845  1915.301956   249.685607  9593.457980
#> [3761]    53.229879   179.321117    49.398018   219.538918 25027.612744
#> [3766]  1699.348942   237.978199 12125.899330    47.666146   150.118401
#> [3771]    45.483353   205.384385 24722.054114  1560.084209   187.063079
#> [3776] 10025.053218    47.770314   142.855425    45.881075   160.115075
#> [3781] 22247.285425  1122.209056   179.858794  7811.386646    57.296257
#> [3786]   139.605985    42.877661   120.245360 17227.041343   966.745916
#> [3791]   160.845884  4808.898843    69.792791   125.729821    38.167593
#> [3796]    84.820290 11515.139382   548.766364   115.779634  2597.306317
#> [3801]    74.623623   115.060676    45.678531    75.170218  7086.094049
#> [3806]   378.804598    96.321522  1232.934934    81.323214   120.188202
#> [3811]    56.723953    66.465334  3185.372583   268.484301    82.963581
#> [3816]   687.802587    85.506730   117.224576    64.479412    65.524019
#> [3821]  1814.608266   225.544707    85.407348   542.782638    86.349111
#> [3826]   123.004558    58.317664    66.202576  1100.415739   214.043717
#> [3831]    77.217544   388.616710    81.948864   124.003550    70.615695
#> [3836]    61.841084   667.588209   172.941852    72.987441   404.906494
#> [3841]    91.581221   116.061535    69.550928    61.093073   432.550454
#> [3846]   190.066188    68.221521   423.191811    86.533175   132.812863
#> [3851]    63.531707    67.118890   403.301821   192.687840    73.299575
#> [3856]   444.097988    89.506922   113.664797    60.807217    65.998789
#> [3861]   407.663872   164.538277   124.435118   553.638583    86.238665
#> [3866]   130.324484    70.253929    61.002073   435.633906   152.830988
#> [3871]   391.973385   547.802014    81.861402   112.163967    59.381364
#> [3876]    59.971323   411.557948   135.541161  1744.958889   612.703115
#> [3881]    88.034656   110.804463    61.708663    71.230467   293.507325
#> [3886]   110.757471  6077.740919   862.483115    81.360095   105.068825
#> [3891]    67.573796    81.850953   186.911564   111.805663 13307.111044
#> [3896]  1372.664704    70.698866    88.051398    82.856088   108.482019
#> [3901]   144.194354    85.800517 18869.675912  1635.211647    64.893472
#> [3906]    88.788734   104.189162   113.902982   109.419341    84.412407
#> [3911] 20187.201067  1944.522540    63.006302   102.301590    93.458797
#> [3916]   111.017181    99.386746    89.749888 18506.676232  1730.000063
#> [3921]    62.605072   139.625281    84.196161    92.953162    83.759750
#> [3926]    76.876001 14237.193458  1203.023799    84.155309   189.537974
#> [3931]    77.877443    70.071738    80.401970   103.007223  8360.494762
#> [3936]   828.841696    84.691190   241.267317    65.904531    64.646327
#> [3941]    83.996235   113.440815  4721.723304   635.543387    90.308433
#> [3946]   222.556461    53.405444    55.582060    78.115123   125.319860
#> [3951]  2118.763134   487.729132    93.171913   192.335782    61.750752
#> [3956]    56.489347   108.363090   132.220562   932.305071   423.365816
#> [3961]    91.165989   145.139294    80.454267    51.459135   306.211543
#> [3966]    72.197537   439.134534   393.756957    76.900078   172.189370
#> [3971]   112.221617    34.701941   937.758675    87.240965   236.845782
#> [3976]   579.096423   102.674654   293.163169   327.418643    34.228399
#> [3981]  3036.340119   137.194945   179.647357  1120.911737   109.453593
#> [3986]   971.508357  1178.908284    39.262406  7097.736498   177.924146
#> [3991]   192.667422  2053.846316   278.958163  1660.497186  1904.867305
#> [3996]    47.415967 13612.566461   342.179352   294.165621  3160.448690
#> [4001]   435.425394  2127.446369  2887.688182    42.565342 14766.058057
#> [4006]   345.222552   278.494640  3322.225743   372.767125  2362.250764
#> [4011]  2609.591924    38.852476 12625.212351   309.212933   222.647444
#> [4016]  2664.950264   315.022733  1834.223903  1730.079802    38.026996
#> [4021]  9392.282426   224.407183   190.014574  1941.780229   207.846138
#> [4026]  1009.193277  1040.100975    40.215923  5706.949405   163.142562
#> [4031]   250.473155  1476.288686   148.233481   633.366188   545.469896
#> [4036]    40.898872  3206.350817   153.621670  1082.551877  1200.967449
#> [4041]   119.793940   425.444598   296.827609    42.566649  1538.463505
#> [4046]   268.504453  3411.768063  1179.528350   117.978419   465.694062
#> [4051]   182.231784    59.051107   707.841693   798.219025  5707.023102
#> [4056]  1486.346857   117.639523   831.651246   192.140575    69.683965
#> [4061]   487.604232  1810.516731  5655.658358  1759.984767   138.435596
#> [4066]   908.943295   205.512557    62.792249   586.376364  3350.792698
#> [4071]  3557.345636  2794.186745    96.937053  1355.829542   229.861769
#> [4076]   122.015590  1829.677277  6027.546728  3410.287913  2622.834168
#> [4081]    77.087682  1324.298012   191.503052   163.245090  3664.284597
#> [4086]  5437.512162  1735.487584  2429.998068   108.438155  1178.696880
#> [4091]   162.410241   267.114850  6283.259947  4333.732537  1024.766212
#> [4096]  1805.691424   108.535899   706.189219    91.852790   244.940871
#> [4101]  8028.558449  2034.124100   643.886912  1045.987358    68.133528
#> [4106]   330.332173    52.346737   154.506984  8406.522748  1084.783013
#> [4111]   396.354323   536.963676    54.900689   156.037455    36.911622
#> [4116]   100.574239  8086.313752   465.948604   289.557508   323.240735
#> [4121]    51.519895   121.549670    37.724636    70.075937  7054.943526
#> [4126]   284.338271   164.873854   264.384663    44.183074    94.368913
#> [4131]    33.475381    53.233161  5233.526518   206.557768   148.569036
#> [4136]   229.047964    47.795181   101.349570    35.298529    43.934168
#> [4141]  3946.345265   164.245997   129.941261   229.565143    52.575088
#> [4146]    81.682126    40.134699    42.011162  2149.719056   180.495567
#> [4151]   153.656255   252.291856    51.914673    96.644777    39.215569
#> [4156]    44.699284  1105.301500   170.612759   191.196159   299.601564
#> [4161]    55.762865    89.791462    37.016342    48.470076   631.509387
#> [4166]   142.981072   313.874315   261.312555    54.545496    96.572753
#> [4171]    38.547161    40.580551   403.145616   144.833464   342.246587
#> [4176]   310.954171    64.032320    98.969568    41.323106    47.257789
#> [4181]   320.515738   136.787292   286.709227   266.342598    53.949720
#> [4186]   100.135118    41.356455    43.328885   267.502695   144.459614
#> [4191]   164.988137   328.513179    57.461130    94.882088    40.005957
#> [4196]    39.564587   207.814849   126.104782   119.881971   280.057880
#> [4201]    52.793556    89.049451    35.078434    46.238785   146.926702
#> [4206]   110.740945    84.288822   279.134654    47.290907    94.405094
#> [4211]    37.226860    48.481465   162.433349   106.836158    77.830367
#> [4216]   264.453547    64.449780    88.148473    51.289629    40.248770
#> [4221]   127.812709   104.602114    67.768942   258.024133    61.969323
#> [4226]    82.904072    41.338179    42.952148   110.149472   117.332622
#> [4231]    67.180968   204.606299    56.525766    90.216799    46.333286
#> [4236]    44.435855    99.924897   100.880076    64.386607   258.448507
#> [4241]    66.325437    93.075675    36.416222    40.134242    95.424911
#> [4246]   120.528329    62.859443   261.412888    61.412603    86.133227
#> [4251]    42.906540    39.572776    82.769467   111.134468    51.519102
#> [4256]   286.668917    64.283166    84.813246    40.286968    37.904904
#> [4261]    69.903974   101.585087    56.501014   278.245946    61.309376
#> [4266]    87.758078    39.301138    41.492513    65.751722   104.708166
#> [4271]    52.745788   289.672285    62.170847    84.853457    36.613074
#> [4276]    41.065433    63.258503   105.844881    55.619390   279.935325
#> [4281]    65.660522    80.181659    38.893459    40.557632    57.631244
#> [4286]   128.399536    52.285071   293.503915    56.622564    95.275258
#> [4291]    45.338733    45.787694    54.856984    98.758217    53.656562
#> [4296]   293.183126    46.206202   110.215465    74.328091    56.813193
#> [4301]    66.842069   118.049178    58.332928   357.771687    56.772910
#> [4306]   123.815829    89.686368    71.647151    56.830797   153.497084
#> [4311]    49.366267   331.818114    56.743310   116.216086    76.397035
#> [4316]    59.559612    59.977540   145.390264    49.855219   314.519660
#> [4321]    61.537938   121.968848    67.554024    61.811850    57.497588
#> [4326]   129.414189    49.220161   280.976827    58.198151   109.382159
#> [4331]    58.828400    63.334645    51.710396   158.309001    53.081195
#> [4336]   233.696873    54.915254    99.290802    37.056606    53.601216
#> [4341]    50.327137   161.450047    65.423462   192.412946    50.879132
#> [4346]    92.203203    51.482459    50.083648    51.578465   137.690177
#> [4351]    82.735760   282.085141    49.772270    92.265072    68.277279
#> [4356]    73.567708    58.589771   142.897967    86.865603   321.770474
#> [4361]    56.413381   206.576746   171.211971   131.399072    46.079827
#> [4366]   159.835466   177.649695   363.398232    56.437854   584.305911
#> [4371]   571.609175   323.764918    46.295060   228.783927   426.355290
#> [4376]   542.757191    46.243221  1658.880072  1622.507155   997.029544
#> [4381]    52.807188   531.293593   749.134423   922.991166    39.452485
#> [4386]  2825.488790  2877.784777  1508.763285    65.139674   831.675763
#> [4391]  1141.031608  1391.305612    39.270631  3856.434958  3860.638527
#> [4396]  2222.188867    71.057165  1332.707846  1264.313461  1480.532561
#> [4401]    40.535523  3580.879003  3477.841466  2148.575595    77.281534
#> [4406]  1014.496104  1115.037402  1125.428625    39.748277  2954.830371
#> [4411]  2742.905155  1478.568493    61.673042   600.030137   762.467306
#> [4416]   751.502703    42.944433  2058.174511  1747.792682   818.145429
#> [4421]    47.708205   379.688054   512.696804   591.761472    42.598034
#> [4426]  1085.150648   920.500510   370.857232    43.804657   257.972650
#> [4431]   373.951200   475.887365    55.008088   646.133952   497.478089
#> [4436]   222.843946    41.230330   194.674755   178.710725   371.505328
#> [4441]    57.140406   339.753634   231.120987   134.328742    42.509141
#> [4446]   153.446260   132.452704   337.295803    54.562566   238.367276
#> [4451]   181.902731    99.626090    45.039130   152.466819   123.765795
#> [4456]   319.224321    53.479184   191.147905   133.862770    77.500712
#> [4461]    40.884697   144.562822    89.399850   310.357274    50.228462
#> [4466]   148.823911    97.549715    72.132407    39.522509   130.002939
#> [4471]    77.423112   289.631985    55.407644   142.645613   103.648934
#> [4476]    71.219004    51.694390   139.958523    82.921971   292.494079
#> [4481]    52.205973   181.637192    69.654248    81.094329    68.157062
#> [4486]   169.031478    86.042279   308.772410    53.377927   310.139904
#> [4491]    69.020225    66.398735    76.538431   163.269922    74.792746
#> [4496]   264.083464    48.114779   829.376209    69.830268    66.752727
#> [4501]    76.916664   163.950370    86.172492   276.670364    52.656940
#> [4506]  1914.579471    65.068199    58.827195    81.856336   196.329029
#> [4511]   104.180491   502.488765    53.568452  2747.098598    51.924475
#> [4516]    59.908836    87.904676   202.476039   125.925033  1019.848396
#> [4521]    53.380118  3511.184929    48.108025    56.457501   150.473284
#> [4526]   227.412918   142.088304  2872.239379    56.085864  3064.459565
#> [4531]    70.128100    63.608724   241.978705   214.168285   127.073370
#> [4536]  7327.306561    47.353124  2551.168664    69.940965    78.336143
#> [4541]   241.413151   249.864527   163.291762 11816.092896    44.269472
#> [4546]  1506.343634    55.429840    75.701900   178.393479   213.936204
#> [4551]   149.746016 10828.569943    51.917788   875.938513    50.516516
#> [4556]    91.879225   128.072299   243.998080   124.920143  8187.996344
#> [4561]    52.379129   452.274888    42.016104    67.711327    86.443328
#> [4566]   215.559648   101.002137  4219.553405    51.288061   276.236507
#> [4571]    38.036253    62.686607    70.009414   187.261870    91.053534
#> [4576]  1847.232543    55.696516   199.953871    36.243559    58.281916
#> [4581]    57.880514   191.821269    82.974095   941.544817    50.940288
#> [4586]   163.811216    38.687191    51.246496    49.906409   169.517866
#> [4591]    73.059557   643.602890    55.092397   133.211018    39.873766
#> [4596]    49.214188    48.038795   168.921205    67.181868   493.367367
#> [4601]    50.925881   118.515011    31.855963    52.775020    46.840387
#> [4606]   179.739927    69.377023   411.059316    50.439892   112.860340
#> [4611]    32.885993    50.016701    48.796571   166.045830    63.744490
#> [4616]   379.992069    49.849600   125.535197    36.394381    42.845141
#> [4621]    44.649761   183.210385    67.217464   317.219016    55.596707
#> [4626]    92.889999    34.362905    50.603551    48.219711   200.643150
#> [4631]    58.318596   312.149223    49.672869    92.801931    31.449582
#> [4636]    48.793051    45.627728   183.778058    52.802457   302.197141
#> [4641]    51.193953    80.921134    39.615357    46.794926    47.705001
#> [4646]   180.875624    52.438282   276.114152    50.887574    82.552679
#> [4651]    36.917704    47.417947    40.085574   175.438082    61.262524
#> [4656]   286.949399    53.042678   103.432709    33.243855    53.685708
#> [4661]    49.722538   185.507442    65.283741   287.849976    52.636642
#> [4666]    84.107162    31.474252    63.818638    48.940789   164.824659
#> [4671]    70.795252   264.853286    59.222573    90.152780    27.160904
#> [4676]    89.749870    57.063146   181.639975    66.890297   269.435757
#> [4681]    66.396097    80.147617    28.577496   122.774279    71.885516
#> [4686]   178.217865    59.325944   247.322788    68.980612    85.526426
#> [4691]    30.771644   111.374158    85.778464   230.254863    59.405668
#> [4696]   262.859357    56.453945    80.841921    25.095487   111.384500
#> [4701]   101.615747   292.653718    75.714277   236.219201    62.770011
#> [4706]    76.347353    29.549898    92.813874    94.254533   277.517573
#> [4711]    53.902052   232.997644    59.397059    71.790755    29.417685
#> [4716]    80.426822    88.550111   244.533126    56.060521   237.362021
#> [4721]    55.113275    72.179748    30.059435    68.114589    64.858636
#> [4726]   246.275348    48.147082   231.276261    59.358420    71.755033
#> [4731]    31.014290    61.453193    56.600685   207.804537    44.582336
#> [4736]   216.942810    58.470191    74.902481    29.037620    56.128376
#> [4741]    41.433763   214.985116    47.945246   238.681643    54.878736
#> [4746]    74.306264    28.871119    53.933283    51.477292   240.338017
#> [4751]    45.071880   319.892479    60.243923    71.908718    30.792017
#> [4756]    50.461645    43.276440   228.400380    49.487292   296.458126
#> [4761]    46.205151    72.394365    31.631879    51.444877    44.081211
#> [4766]   264.518612    43.777099   331.151428    52.130969    75.112764
#> [4771]    34.393221    46.578332    42.388637   276.102014    56.115048
#> [4776]   362.837851    58.398589    74.458122    30.720373    45.265009
#> [4781]    44.877775   276.971183    52.895040   349.033458    46.847567
#> [4786]    72.428151    34.847921    63.150338    52.859219   278.265463
#> [4791]    53.059548   396.797879    47.275672    66.330887    29.480862
#> [4796]    71.637194    53.837807   307.917395    56.975557   497.815422
#> [4801]    48.149000    72.074457    30.924934    93.585150    44.845495
#> [4806]   333.082104    64.602899   628.595244    46.241044    68.278919
#> [4811]    40.911953    91.214876    49.440920   293.720754    60.020386
#> [4816]   627.625701    50.614990    69.169435    28.467986    70.115238
#> [4821]    43.505653   309.938003    59.928173   575.279742    47.659137
#> [4826]    71.464793    32.106199    60.286711    49.790274   294.248272
#> [4831]    58.653218   685.388791    46.213836    69.006738    29.242110
#> [4836]    51.410295    45.520157   357.318091    51.821616   703.832977
#> [4841]    47.358509    75.602755    28.371720    51.350037    48.103827
#> [4846]   420.375025    54.557280   660.463500    55.045969    76.902699
#> [4851]    32.517357    51.046595    47.326629   455.927849    46.463520
#> [4856]   652.636737    49.820302    67.005941    32.962791    56.354765
#> [4861]    39.792577   535.631324    50.786102   482.542554    45.937160
#> [4866]    66.954484    27.526334    57.859302    47.467405   676.631754
#> [4871]    47.187554   475.886387    45.488405    68.867610    28.043411
#> [4876]    66.464158    53.735365   990.586320    48.262246   486.732631
#> [4881]    47.613015    64.115459    26.575104    89.239618    78.133335
#> [4886]  2147.019938    60.448976   485.854286    46.575728    66.852067
#> [4891]    25.055291   140.143325   119.297522  4785.156591    79.674124
#> [4896]   468.269479    40.069633    53.752282    21.424326   230.675430
#> [4901]   179.378576  6983.051321   108.451029   604.748155    36.021672
#> [4906]    56.476180    25.989365   277.886080   238.432355  8121.600158
#> [4911]   113.564386   529.230850    34.702434    56.259035    24.925178
#> [4916]   263.869149   208.314547  6791.957569   115.353383   462.317766
#> [4921]    42.774459    62.295376    25.392242   182.715289   113.173815
#> [4926]  4407.928285    90.005843   380.251795    46.900266    55.914632
#> [4931]    27.799285   115.570539    79.058044  2517.681085    67.723625
#> [4936]   365.169886    46.346011    63.736670    26.285887    63.575800
#> [4941]    54.973395  1016.756863    59.035719   314.809195    42.061985
#> [4946]    57.064270    24.355705    49.483228    41.642904   629.549182
#> [4951]    46.952355   299.548207    43.353903    61.252663    28.244145
#> [4956]    44.116027    40.359105   413.014250    42.694832   348.094255
#> [4961]    44.406247    60.548911    23.920501    41.520794    37.626969
#> [4966]   280.745009    44.364923   276.202102    49.087521    69.952603
#> [4971]    29.107688    37.645823    37.956093   187.936462    49.330026
#> [4976]   271.683895    49.996027    72.130079    24.524474    36.834286
#> [4981]    34.680823   173.507615    48.710235   308.370965    49.999272
#> [4986]    65.250505    27.344688    37.068941    29.006739   126.356819
#> [4991]    53.180806   325.906607    45.791061    65.085692    30.906553
#> [4996]    42.035999    33.820820   115.196643    48.461630   282.270670
#> [5001]    47.862877    65.823179    27.003224    36.460184    31.905152
#> [5006]    86.673064    53.963977   334.402929    45.000086    68.865902
#> [5011]    26.074596    33.596923    34.060453    76.903663    56.431894
#> [5016]   328.876977    45.333796    61.137680    25.360921    34.779504
#> [5021]    35.907375    71.257939    54.631313   321.782398    55.947935
#> [5026]    75.419724    26.057713    33.953019    33.511435    62.095741
#> [5031]    48.594550   318.331998    50.517598    62.658040    26.447861
#> [5036]    35.184809    35.683931    49.447750    45.818880   297.853359
#> [5041]    43.528390    64.768476    25.413464    30.008566    33.274146
#> [5046]    54.379836    43.844371   277.684504    47.210207    61.803186
#> [5051]    28.459141    36.008184    32.183616    45.571559    43.043387
#> [5056]   216.424570    47.089564    61.269947    26.100267    31.252960
#> [5061]    30.096715    43.530337    63.426359   240.832936    45.444751
#> [5066]    69.823334    23.452219    34.694233    28.758334    43.586328
#> [5071]   228.805007   271.242768    51.764197    59.215860    25.704444
#> [5076]    35.203498    33.849074    57.042047   883.215340   198.589383
#> [5081]    46.525925    59.050193    25.690238    33.508681    34.143498
#> [5086]   103.191358  3793.034272   237.970979    46.374508    63.158940
#> [5091]    23.593530    34.508682    37.986472   321.577456 10387.647943
#> [5096]   221.502027    46.100283    40.960708    20.854672    40.466064
#> [5101]    48.014631   458.881079 14625.467060   334.037362    33.822183
#> [5106]    49.832747    22.347413    43.504691    51.173487   664.266095
#> [5111] 16593.904326   282.950405    31.236959    43.570580    20.728093
#> [5116]    43.185005    59.566814   676.587390 16188.642222   313.413631
#> [5121]    38.075133    51.941585    14.116758    49.725098    60.537468
#> [5126]   490.664727 12504.341366   332.336475    37.057482    50.585754
#> [5131]    25.794391    34.584245    39.173538   294.094119  9368.650824
#> [5136]   238.538071    39.816894    53.761216    27.356094    42.350012
#> [5141]    32.642037   161.953584  4959.686799   273.161323    41.500725
#> [5146]    72.503669    22.130488    33.884160    28.541240    80.038212
#> [5151]  1901.186338   188.447495    53.187130    69.078084    33.401141
#> [5156]    33.780515    33.022667    61.955306  1182.946692   215.098218
#> [5161]    42.515117    62.778956    26.216766    35.221615    48.032176
#> [5166]    54.959703   825.698900   207.598380    55.643398    71.384935
#> [5171]    31.635770    35.349741    48.964816    50.205919   578.695492
#> [5176]   265.714340    42.320107    61.631955    24.768630    33.323584
#> [5181]    48.746423    39.307374   432.141679   328.384663    49.987269
#> [5186]    60.807526    28.164686    37.712182    35.494426    33.273868
#> [5191]   327.161537   237.954949    51.004126    62.141679    24.341466
#> [5196]    33.163396    32.038287    57.151888   307.955087   293.975123
#> [5201]    45.686545    60.149132    22.322665    32.619832    39.601874
#> [5206]    23.049419   240.837605   186.115206    46.597708    51.809865
#> [5211]    30.635418    21.868757    36.862236    31.747517   177.808305
#> [5216]   258.993183    35.778968    80.982385    17.748673    31.080975
#> [5221]    27.910608    29.008353   152.458723   206.890375    60.902021
#> [5226]    55.154165    30.905965    35.537998    26.481802    36.547885
#> [5231]    71.281653   319.363948    39.509593    54.674671    23.694966
#> [5236]    22.768565    35.902006    15.519170   122.210194   311.873757
#> [5241]    54.575711    52.414871    43.260145    27.726636    26.703534
#> [5246]    29.005692    49.958104   318.460082    32.422931    65.452027
#> [5251]    16.243843    29.931222    67.388561    21.198202   115.150943
#> [5256]   311.011074    49.097036    34.894409    32.663204    26.605071
#> [5261]   143.219070   132.124666    52.465763   726.977373    24.659910
#> [5266]    50.157988     9.839966    34.117595   213.281965   367.988658
#> [5271]    55.975199  1133.979505    35.030130    48.212218    18.222072
#> [5276]    27.248220   749.983686   568.723259    73.905793  1688.907677
#> [5281]    28.385296    40.115522     9.298693    25.190910   284.538703
#> [5286]  1371.456125    51.937697  1970.014395    31.139139    30.812823
#> [5291]    17.957888    20.077910  2250.042225   247.380044   120.841294
#> [5296]   358.835250    29.951044    30.655786    10.936186    22.041673
#> [5301]   842.268770   684.991122    50.578106   751.022704    17.030382
#> [5306]    56.704069     9.993893    26.125907   395.690440   108.014778
#> [5311]    52.044293   173.997155    27.761691    56.691786     8.355937
#> [5316]    25.420549   121.274068   109.111402    40.842086   185.723421
#> [5321]    19.028397    54.993547     8.221156    30.516583    74.598682
#> [5326]    54.938835    47.603433   208.145478    26.427559    48.410746
#> [5331]    11.010037    29.746014    95.137569    31.070524    62.041933
#> [5336]    81.034690    27.960036    50.010338    13.210586    25.622529
#> [5341]    62.798812    34.743141    57.948189    67.948480    29.345248
#> [5346]    43.847262    10.212893    24.417106    37.715088    24.016516
#> [5351]    51.844956    56.948543    23.039180    47.985173    15.485633
#> [5356]    17.196868    28.604007    28.672823    49.094864    85.515405
#> [5361]    20.712237    54.197844     9.996985    24.535078    30.869278
#> [5366]    33.406760    37.092492   108.928467    29.427018    40.057003
#> [5371]    11.233572    25.663400    26.074822    14.684448    44.153481
#> [5376]    79.863051    20.674375    53.945479     8.635538    21.866742
#> [5381]    21.568681    27.295084    37.782676   119.027245    19.828372
#> [5386]    64.745642     6.866438    37.820110    16.976812    31.202158
#> [5391]    28.064303   126.817124    18.990707    62.140496     7.116460
#> [5396]    29.441396    13.949700    37.203920    24.919200   207.062197
#> [5401]    29.096854    47.315740    14.389914    27.333264    21.161312
#> [5406]    22.028162    24.699609   255.689930    37.234862    35.792454
#> [5411]    19.542832    31.829631    31.247314    19.193122    39.076528
#> [5416]   151.820509    35.495920    47.397914    20.446395    31.425314
#> [5421]    34.012810    15.253335    31.759759   121.802695    31.030318
#> [5426]    45.767372    12.877493    24.125255    27.306708    18.044403
#> [5431]    30.132601   109.521549    41.443886    49.541559    14.060000
#> [5436]    19.674713    30.753903    13.244524    32.146125   147.121849
#> [5441]    37.313982    45.717337    20.340095    23.995267    22.475538
#> [5446]    15.280520    30.612373   126.313107    34.105550    45.470899
#> [5451]    13.900067    23.654804    24.500477    16.061011    30.066356
#> [5456]   144.995349    35.720150    52.332116    22.641242    21.791053
#> [5461]    23.008396    17.488522    26.974505   117.847114    30.733337
#> [5466]    40.035589    13.306863    24.808838    22.640671    11.095066
#> [5471]    37.035494   169.536042    34.706612    42.308956    11.265198
#> [5476]    25.540988    17.534398    13.917723    36.879266    95.253177
#> [5481]    28.148921    54.359477    12.156747    23.301489    18.149539
#> [5486]     9.520780    25.295166   108.913805    31.419713    34.356447
#> [5491]    13.770139    23.333087    18.118756     9.574440    29.141270
#> [5496]    95.353999    35.310113    34.061251    13.283332    22.279662
#> [5501]    17.767520    10.718367    28.965177    93.648825    31.672368
#> [5506]    50.220073    13.240031    19.169652    16.961605    10.676379
#> [5511]    27.901531   101.624876    30.922475    30.711283    10.036392
#> [5516]    23.545922    15.679841    23.386392    32.812637    88.778950
#> [5521]    32.032750    38.288512    11.881548    17.974256    16.239587
#> [5526]    11.168106    24.564803   100.224677    27.833303    57.880141
#> [5531]     9.091872    15.109380    14.008010    10.726497    35.164280
#> [5536]    97.430139    27.099293    37.656634    11.423134    19.898495
#> [5541]    19.736534    10.571789    29.370398   124.398256    27.596925
#> [5546]    33.851647    11.234983    16.486515    15.795668    13.592158
#> [5551]    27.078752    93.896182    31.460622    44.212066     9.682059
#> [5556]    19.535536    14.092844     9.353039    32.686904    79.027967
#> [5561]    28.658147    38.346754    12.294601    14.046168    16.102160
#> [5566]    10.279072    34.637368    52.164251    28.343455    34.719642
#> [5571]    12.085510    16.228113    15.652985     9.625466    32.608459
#> [5576]    50.489848    31.156872    33.528733    10.087299    16.134050
#> [5581]    13.856099     7.972964    36.169426    88.756489    28.420947
#> [5586]    34.800597     9.344251    14.378970    15.781564     6.902752
#> [5591]    31.046286    59.280232    22.718516    32.093968     7.078729
#> [5596]    15.966721    14.978711     8.551211    28.791502    61.168031
#> [5601]    28.751535    34.515249    10.039587    15.328628    13.471790
#> [5606]    11.967418    22.615952    59.452777    25.812509    34.832149
#> [5611]    14.232937    18.010681    13.874654    12.665227    25.134650
#> [5616]    81.158182    25.747741    36.183789     9.222818    13.347133
#> [5621]    18.191310     5.800864    23.016008    59.047435    23.624210
#> [5626]    36.489993     8.455181    13.820350    20.218870    14.415679
#> [5631]    21.961414    42.435816    22.019617    24.294659     8.502477
#> [5636]    14.249668    21.836311    11.240619    31.662255    53.946034
#> [5641]    43.582236    29.396582    10.156057    13.793700    14.460816
#> [5646]     6.621688    23.156595    41.370287    23.171764    39.400401
#> [5651]     6.507159    12.296025    14.287846     7.503581    23.035727
#> [5656]    44.507807    21.540643    29.158486     8.421196    14.577786
#> [5661]    16.518687     6.551813    17.652274    40.726932    21.477399
#> [5666]    27.832757     5.174307    17.541639    15.466425     6.045972
#> [5671]    23.942745    42.047886    20.552341    21.297594    11.327878
#> [5676]    14.112659    13.465211     7.561116    20.891421    39.545105
#> [5681]    19.466234    25.902088     6.970867    10.721802    14.237479
#> [5686]     7.934469    18.993176    43.471168    18.829538    28.251999
#> [5691]     6.619835    14.278923    11.615486    10.125237    25.820873
#> [5696]    37.290990    22.039825    45.526493     8.860670    13.170684
#> [5701]    11.965083     5.701149    22.970239    47.536575    17.859171
#> [5706]    27.403849    11.756828    13.365287    11.563088     6.603249
#> [5711]    19.394457    38.509610    19.594411    27.302006     7.978791
#> [5716]    12.335761    13.157835     5.887464    20.281194    50.624110
#> [5721]    18.197701    23.702696    12.613101    13.236488    15.888507
#> [5726]     6.469216    20.713158    33.497166    21.683398    20.855007
#> [5731]     6.527923    14.409809    12.152113     5.829081    21.829375
#> [5736]    42.967839    18.284162    25.953627     7.302648    15.312105
#> [5741]    11.163051     7.059352    22.451720    55.118277    14.706257
#> [5746]    24.231435     6.239305    11.933300    11.482309    13.922378
#> [5751]    23.312185    35.999993    18.468304    22.806715     6.053295
#> [5756]    13.681849    10.199348     6.919740    21.173732    38.787369
#> [5761]    18.394192    24.134528     5.934901    11.611764    11.985345
#> [5766]     6.137566    25.370443    36.355738    30.076121    24.597549
#> [5771]     8.476769    11.829287    12.237094     7.833082    17.024092
#> [5776]    31.942338    17.740252    26.062882     7.070393    13.139167
#> [5781]    10.057769     5.095920    20.020777    40.341561    15.354534
#> [5786]    29.237354     8.457130    10.475425    10.036429    10.087661
#> [5791]    21.093659    47.750642    17.410353    29.669635     6.080444
#> [5796]    12.988895    10.065906     7.317907    19.790424    30.071568
#> [5801]    26.804742    22.730861     6.864117    10.676785    11.237936
#> [5806]     5.643706    21.637751    43.567709    27.582795    24.688186
#> [5811]     6.651049    12.489531    12.305251     5.027223    21.187252
#> [5816]    39.480930    17.954805    21.496859     7.088664    10.972968
#> [5821]    10.433393     7.064342    17.486392    41.079621    12.462918
#> [5826]    22.563665     4.645000    10.210050     9.841871     4.545358
#> [5831]    18.956592    37.958999    17.593745    23.096646     5.675881
#> [5836]    11.308275    11.962768     6.282951    20.170424    47.077768
#> [5841]    15.466341    23.863601     7.573546    11.824666    10.677047
#> [5846]     4.094874    19.369373    48.449219    16.441603    28.571513
#> [5851]     5.143756    13.317933    10.858247     6.331893    21.963200
#> [5856]    36.229585    15.474986    20.541464     7.247845    12.542505
#> [5861]    11.423010     6.824097    15.968173    39.267411    14.246214
#> [5866]    23.859755     4.786252    10.830720     9.510862     4.685188
#> [5871]    17.486187    32.752970    14.303565    21.148966     7.471369
#> [5876]    11.557634     9.989837     5.051698    19.569410    42.029570
#> [5881]    15.710827    20.697971     6.101037    10.979036    12.173694
#> [5886]     5.356524    18.635946    34.636425    16.274177    22.425319
#> [5891]     7.265970    11.199063    11.075436     5.460401    16.274875
#> [5896]    43.487680    16.894735    22.490648     5.658307    11.431265
#> [5901]    12.308903     3.716979    14.761261    30.137723    26.085530
#> [5906]    23.743736     5.511207     9.487293    11.727344     3.946854
#> [5911]    18.358340    30.042680    17.640732    19.396595     5.540704
#> [5916]    12.829256     9.375596     4.478811    20.907189    31.625138
#> [5921]    14.311768    21.888127     6.201748    10.436704    11.062678
#> [5926]     4.800994    22.197087    37.329104    16.905886    21.342389
#> [5931]     4.184414     9.794905    12.300346     6.322615    19.054385
#> [5936]    25.624018    15.559821    21.976108     5.925293    10.548200
#> [5941]    11.061320     3.928094    21.721847    31.082930    15.730390
#> [5946]    22.552142     4.821667    11.816226    11.516344     5.600983
#> [5951]    19.042766    27.369907    13.867009    19.324885     4.316336
#> [5956]    11.744548    10.201385     6.862863    14.868542    25.671994
#> [5961]    21.497115    19.950111     5.227230    12.352900    11.793891
#> [5966]     7.922085    16.467514    29.233923    19.342515    24.204033
#> [5971]     6.817222    11.201137    13.313019     4.572647    24.195375
#> [5976]    31.381669    17.205520    22.203010    11.207973    10.988817
#> [5981]     8.733691     4.249936    22.672829    27.506185    18.057019
#> [5986]    22.534012     5.698990    10.988898    12.000976     5.925525
#> [5991]    17.584087    36.361166    17.059897    19.463759     5.744939
#> [5996]    14.029562    12.062251     6.391228    20.279620    20.916822
#> [6001]    15.465160    21.549043     6.722870    12.028100     9.949838
#> [6006]     6.007326    24.382272    33.732603    18.271602    21.577365
#> [6011]     6.615802    10.172838    10.803664     3.854277    18.433202
#> [6016]    30.541047    18.613627    21.680726     7.294082    11.106864
#> [6021]    12.282757     5.239440    19.904770    28.836984    15.674173
#> [6026]    21.713432    13.651867    11.300693    10.528669     7.567143
#> [6031]    18.464297    29.124795    14.150920    25.964121     5.663315
#> [6036]    11.118359    11.280843     5.713714    17.904503    36.231586
#> [6041]    21.510322    18.696684     5.041147     9.124287    11.431144
#> [6046]     3.798698    18.065674    25.423382    20.677185    20.894602
#> [6051]     5.702843    10.777248    10.712305     5.173653    20.071802
#> [6056]    36.382167    17.871196    22.533954     6.061124    11.017222
#> [6061]     9.661962     5.581918    18.825902    30.713348    22.574746
#> [6066]    21.728186     6.972377    11.105360    13.780225     4.550884
#> [6071]    19.395026    26.880207    14.210696    22.155957     6.797550
#> [6076]    10.275557    12.222819     8.398578    24.344253    34.193368
#> [6081]    15.504388    20.300883     5.677231    10.249366    12.681867
#> [6086]     4.815232    26.414719    32.685804    19.477807    25.813704
#> [6091]     5.742608    10.393623    11.986271     6.906906    16.276390
#> [6096]    26.596281    13.400807    18.981896     4.858285    10.454178
#> [6101]    12.701189     7.966966    20.260167    30.027440    18.859080
#> [6106]    22.618743     5.682270    12.054238    11.638004     5.021385
#> [6111]    15.539340    34.765216    19.191591    15.998954     5.048621
#> [6116]     9.386482    13.078936     5.873381    15.623255    28.514973
#> [6121]    15.029830    19.101041     6.477837    11.175430    12.146461
#> [6126]     5.148064    18.652995    29.943941    18.033890    23.966590
#> [6131]     6.252118     9.911543    11.501488     3.347896    14.578482
#> [6136]    25.920330    16.644279    17.580480     6.416454    10.302214
#> [6141]     9.645012     6.561954    17.809095    26.193635    16.791367
#> [6146]    25.535732     4.844136    11.837402     8.871229     4.757383
#> [6151]    15.651360    26.396547    14.027239    19.791865     9.792290
#> [6156]     8.804900    10.444221     5.243068    19.937082    26.089301
#> [6161]    18.055032    22.551599     6.192553     9.915538     9.173633
#> [6166]     5.868727    15.541182    24.232333    14.435194    23.942167
#> [6171]     5.017874    10.179691    11.269468     4.221513    20.727558
#> [6176]    26.321338    19.164747    18.945027     7.669707    11.056863
#> [6181]    11.127577    12.666749    15.256717    25.997107    17.438546
#> [6186]    19.986527     6.671356    10.993758     9.369533     4.444676
#> [6191]    21.731148    28.489718    13.770881    18.928200     5.659063
#> [6196]    10.686092     9.026780     4.218146    15.360442    32.986778
#> [6201]    14.450117    23.222753     6.086246    10.253449    10.288777
#> [6206]     5.155154    16.632369    24.452634    15.953815    16.944394
#> [6211]     5.786364    10.837662    12.010598     4.611328    19.639332
#> [6216]    23.316960    16.959275    25.506402     4.360476    10.334268
#> [6221]    11.445835     8.239900    14.574909    25.082319    11.856776
#> [6226]    26.322803     4.254589    11.393935     9.486259     4.610584
#> [6231]    15.952926    27.274178    16.735782    21.962689     5.648849
#> [6236]    12.947390    11.642464     4.671631    15.635235    25.916409
#> [6241]    16.055308    18.728775     6.844440     9.780797    10.753023
#> [6246]     6.802180    21.511615    52.861304    13.085859    21.294226
#> [6251]     5.747175     8.597011    10.058490     8.907762    15.482151
#> [6256]    35.679026    16.521257    27.283316     4.951118    10.781809
#> [6261]     9.012623     6.569064    19.638396    29.239237    13.164390
#> [6266]    23.731186     5.510069    10.607306    13.007705     4.549610
#> [6271]    18.385448    33.727136    14.876893    28.768128     6.202144
#> [6276]    11.445276    11.072589     5.572842    20.476118    25.933766
#> [6281]    15.658919    20.068896     5.536041    10.364386    12.191351
#> [6286]     4.242294    18.140369    28.400607    17.945117    23.952858
#> [6291]     5.254488     9.975148    13.029144     4.996982    16.987497
#> [6296]    21.594442    19.360542    18.129262     6.440756     9.416642
#> [6301]     8.879312     3.974525    22.951163    29.104788    17.868570
#> [6306]    20.328365    11.548576    10.085428    10.498596     4.715607
#> [6311]    24.529314    26.396005    21.096141    19.854503     9.045296
#> [6316]    10.613922    12.959016     5.471734    21.122166    30.976210
#> [6321]    17.467314    30.765345     6.214583    10.425230     9.409511
#> [6326]     5.592456    16.731984    23.036097    17.275026    21.311622
#> [6331]     5.486886    10.735616     9.364954     3.541165    20.435235
#> [6336]    23.682017    12.751667    19.746048     7.011281     9.291310
#> [6341]     8.632754     4.888646    22.854153    42.580133    22.856214
#> [6346]    20.414992     6.439880    11.011290    12.585844     4.953826
#> [6351]    24.834518    30.640564    13.469658    30.635091     6.262156
#> [6356]    11.240475    11.193622     4.392331    19.049030    28.331619
#> [6361]    19.054333    33.136650     5.985691    10.087040     9.629414
#> [6366]     4.252129    17.535644    22.333125    15.536449    20.266349
#> [6371]     5.705797    11.686510    12.066039     6.810281    21.422717
#> [6376]    30.576053    15.644490    18.046062     6.146557    11.416335
#> [6381]    11.477552     5.818372    18.691383    21.365292    13.661480
#> [6386]    19.384176     5.654201    11.051018    10.236746     5.007565
#> [6391]    18.888312    25.496562    12.647561    24.443660     7.740616
#> [6396]    11.405505    11.184417    12.563951    20.612560    27.299467
#> [6401]    16.240234    21.575600     6.522759    10.468161    11.962806
#> [6406]     4.640039    12.203463    20.964559    15.498840    19.165081
#> [6411]     4.929392    10.422037    11.032308     7.748884    19.017662
#> [6416]    28.355905    13.492469    20.585249     6.358037    10.892174
#> [6421]    10.782553     6.424071    20.991071    26.787088    36.758570
#> [6426]    21.156857     5.091073    10.649386    10.809779     5.820364
#> [6431]    18.408146    35.748520    25.736241    19.774131     7.259056
#> [6436]    10.382411    10.373931     4.647639    14.995460    22.978675
#> [6441]    19.219628    22.706139     7.141451    11.857613    10.200689
#> [6446]     5.671289    20.476081    25.707751    17.518600    30.063380
#> [6451]     7.862410    11.423195    12.148871     6.945512    16.150527
#> [6456]    24.298117    14.559476    20.360127     4.588653    11.398603
#> [6461]     9.113533     4.713270    16.622362    31.611712    14.491402
#> [6466]    21.475547     6.315935    11.508246    11.642655     5.202209
#> [6471]    20.508794    30.428672    19.069939    21.935285     6.848964
#> [6476]    11.256043    12.959254    11.712290    17.863851    23.550501
#> [6481]    12.352790    26.415876     5.366100    11.636339    11.313623
#> [6486]     4.908458    18.968952    26.960806    18.474412    23.130283
#> [6491]     6.378123    11.770825     9.588354     9.072638    18.655192
#> [6496]    26.455795    21.032671    31.279063     7.377360    12.570899
#> [6501]     9.846947     4.500947    18.131702    24.298941    17.305334
#> [6506]    20.882561     6.153599     9.618351    10.714424    11.896306
#> [6511]    20.155444    29.094227    15.572138    28.487446    10.424288
#> [6516]    11.914281    12.415575     5.900483    19.919316    22.812075
#> [6521]    15.593424    26.030601     7.840797    11.509692    12.017372
#> [6526]     8.057531    22.592977    22.892289    14.215761    20.443693
#> [6531]     5.393908    11.870577    11.834267     6.053441    15.883934
#> [6536]    23.083281    16.238323    22.422582     6.289417    10.830067
#> [6541]    10.223057     7.172563    17.810912    24.632146    13.679702
#> [6546]    20.500806     6.857304    10.062145     9.713911     6.287977
#> [6551]    14.404737    27.440468    17.232877    26.050061    16.110817
#> [6556]     9.997268    11.447893     4.527345    17.506791    27.246427
#> [6561]    15.694653    20.233884     6.666143     8.928364    10.965052
#> [6566]     3.648313    23.213616    33.352166    15.071790    36.678364
#> [6571]     7.022363    11.270742     8.838623    13.090240    19.128171
#> [6576]    35.436642    19.507580    18.148779     4.615980     9.578203
#> [6581]    10.253686     4.703976    20.169298    22.556414    16.640852
#> [6586]    24.354504     5.193703    12.812498    10.455099     4.696572
#> [6591]    22.974636    27.090029    19.984680    25.796121     7.334822
#> [6596]    11.942260    10.560468     5.169543    20.273639    26.778747
#> [6601]    17.712928    47.051205     5.623750    10.359454    10.664079
#> [6606]     4.895109    19.253780    27.860563    17.694158    28.949455
#> [6611]     8.289831    11.102530    11.607740     3.466563    14.714239
#> [6616]    29.265666    14.398066    22.644254     5.936996    10.778961
#> [6621]    11.092141     4.643042    21.476321    27.218363    17.894117
#> [6626]    23.355493     5.036956     9.768475    10.394807     4.895581
#> [6631]    20.026397    29.728378    14.898927    20.384213     5.368960
#> [6636]    10.511783    10.439251     6.390248    22.113762    28.523886
#> [6641]    13.802355    21.631001     9.026024    11.403928     9.918543
#> [6646]     4.623812    15.742373    28.029476    18.554355    22.773872
#> [6651]     5.746443    11.767112    10.083992     4.374796    17.626457
#> [6656]    27.991132    15.331903    23.400512     6.216858    12.313058
#> [6661]    10.803967     5.525187    15.587872    23.094022    15.856851
#> [6666]    18.961042     6.198267    11.592470    10.174680     4.796777
#> [6671]    19.315707    27.416641    15.184901    24.891714     6.427024
#> [6676]    10.255672    11.831430     5.093051    20.173487    27.496317
#> [6681]    20.103094    38.396415     6.865835    11.102031    11.310023
#> [6686]     5.478815    18.663656    24.478150    16.901445    21.618265
#> [6691]     7.999599    10.073415     7.744202     8.749388    19.594045
#> [6696]    26.903182    14.525386    22.084893     5.142531    11.084978
#> [6701]    10.620466     7.738099    18.321208    29.081020    13.301647
#> [6706]    19.992725     5.895386    10.644138    11.859441     7.282677
#> [6711]    18.018021    28.188249    24.760736    22.038372     4.366667
#> [6716]    11.001688    12.499550     5.123093    15.262302    23.756095
#> [6721]    20.720150    30.228790     4.394520    10.028479     9.707609
#> [6726]     4.350069    18.140195    20.009206    17.993648    19.002447
#> [6731]     6.299981    11.473525     9.543563     4.155215    15.328477
#> [6736]    28.991882    17.768750    22.615224     6.139764    11.501982
#> [6741]    13.734892     5.499403    16.914373    28.790825    16.872875
#> [6746]    18.492110     5.583537     8.935665    11.769684     5.286785
#> [6751]    18.034496    32.084175    15.515344    19.329474     8.072934
#> [6756]    11.121037     9.593857     5.412797    19.771129    23.106614
#> [6761]    17.579322    20.187170     5.363943    11.451182    11.587418
#> [6766]     5.364188    16.048256    25.325948    15.721866    18.614385
#> [6771]     6.805010     9.811136    11.751012     3.874564    23.567623
#> [6776]    23.543039    13.171079    27.936709     8.197528    11.255197
#> [6781]     8.107489     7.452791    21.564299    27.342121    12.945750
#> [6786]    25.453192     6.986556     9.905569     9.395154     4.332932
#> [6791]    16.783253    22.894339    24.797071    22.335369     6.891753
#> [6796]    11.678509    10.689191     4.912379    21.466754    23.509351
#> [6801]    13.218125    17.953736     8.571553     9.593539    10.262257
#> [6806]     6.482088    16.753287    34.789242    15.390476    22.116460
#> [6811]     6.477632    10.788972    13.416375     5.291164    21.663222
#> [6816]    32.065756    14.023479    30.832228     5.314142     9.250391
#> [6821]     9.214860     6.348743    18.339258    24.655968    13.249055
#> [6826]    55.532747     6.780604    11.377478    13.323924     6.216104
#> [6831]    14.935224    25.768693    12.909203    22.671930     4.488649
#> [6836]    10.799970    10.937674     5.255813    19.616507    23.172698
#> [6841]    15.823211    21.245194     7.096178     9.550661    11.152417
#> [6846]     8.152236    21.084419    26.770305    14.429645    21.271298
#> [6851]     7.832856    12.056087    11.779300     4.475797    18.643286
#> [6856]    26.387191    14.730316    36.594233     8.089238    11.029222
#> [6861]    10.422804     7.267043    15.095851    26.593623    21.754364
#> [6866]    23.551933     5.089353    10.360865    11.938029     5.753962
#> [6871]    20.659532    24.610320    21.376482    20.406358     5.275592
#> [6876]     9.250746    10.613810     3.960601    17.330385    30.206389
#> [6881]    15.360810    29.016053     5.530230    11.171647     9.412464
#> [6886]     5.113704    21.928675    38.104277    11.901806    21.775210
#> [6891]     5.200633    10.539019    10.844053     6.163663    16.175943
#> [6896]    36.678962    16.282467    38.056857     5.362595    11.323132
#> [6901]    10.703461     5.397676    15.702316    24.359320    15.139917
#> [6906]    18.602421     4.762504    10.856186    14.184799     8.808151
#> [6911]    14.704503    31.305581    11.804618    26.150565     6.763011
#> [6916]     9.497258    11.582165     5.394998    23.759381    20.320550
#> [6921]    15.241552    16.246039     4.684850    10.979298    10.456820
#> [6926]     8.905588    14.781592    27.012876    14.292981    33.032637
#> [6931]     5.100140    10.400169    13.934594     4.795497    17.293917
#> [6936]    20.621456    13.904029    17.864621     5.156797    10.480541
#> [6941]    10.470159     4.898430    14.563778    25.385020    21.642064
#> [6946]    18.811826     4.960947    11.097639    13.182356     5.667703
#> [6951]    18.891917    21.366534    12.954209    22.733060     7.033172
#> [6956]    11.417416     9.605428     5.253914    19.270777    25.843744
#> [6961]    14.485716    25.597451     5.316602    10.640504     9.586580
#> [6966]     5.366495    13.176101    30.195574    18.606871    17.343704
#> [6971]     7.126794     9.636645    12.942500     4.748871    18.303082
#> [6976]    23.545868    16.706177    25.737615     6.227998    11.098120
#> [6981]    10.200699     6.050280    18.225609    27.069885    14.260101
#> [6986]    19.685704     5.140146    12.979811     9.685239     3.892039
#> [6991]    19.996609    28.714788    12.774022    20.914691     5.563148
#> [6996]    11.257266     7.818056     8.191035    19.670319    24.455115
#> [7001]    13.901029    20.666881     5.740455    10.390315    10.540737
#> [7006]     5.239556    18.002698    30.751921    14.245768    22.747782
#> [7011]     6.905547    11.496915    12.349256     6.612709    18.463281
#> [7016]    28.900459    15.671822    19.157494     7.323224    10.722297
#> [7021]    11.034751    10.277040    21.406327    29.377878    14.209451
#> [7026]    20.876081     5.839155    11.080671    10.919747     5.575396
#> [7031]    15.760910    26.419115    13.416710    16.347512     5.374161
#> [7036]     9.481983    12.547474     4.060674    17.018011    30.737735
#> [7041]    13.810171    17.649129     5.622687    10.487182    10.083001
#> [7046]     6.024245    15.634883    30.548391    25.156382    29.441643
#> [7051]     8.865323    12.989413    12.099445     4.575110    15.880972
#> [7056]    28.032077    15.624855    26.689582     7.208590     9.815443
#> [7061]    10.065303     3.596404    18.388266    28.468746    15.937781
#> [7066]    18.162128     6.642714    10.818792    13.257751     3.985955
#> [7071]    15.419146    26.977868    13.988382    17.933015     8.956976
#> [7076]    10.258652    12.037752     3.863613    18.960030    32.534989
#> [7081]    14.185539    16.000703     6.372031    11.121082    12.152146
#> [7086]     5.688608    17.753208    30.389682    15.119966    19.452684
#> [7091]     8.024150    10.194372    10.160811     7.108232    17.640853
#> [7096]    25.193212    13.075439    16.072879     6.290957     9.592162
#> [7101]    12.689229     4.033864    20.406621    23.419240    18.145626
#> [7106]    21.302784     5.481212    11.696416    11.580833     4.831010
#> [7111]    22.675253    32.060353    16.695246    25.414814     6.109536
#> [7116]    11.846644    10.857186     5.205461    16.780919    25.427510
#> [7121]    16.107229    17.122453     5.059080    10.556342    11.822079
#> [7126]     4.515281    14.988842    30.244731    12.690808    19.665574
#> [7131]     6.713899     9.560162     9.421713     5.681562    16.055999
#> [7136]    28.171817    20.712684    20.664815     6.748661    12.571693
#> [7141]     8.823148     5.822341    20.121793    20.979256    18.631864
#> [7146]    21.673262     7.629184    13.502819     9.073333     8.684805
#> [7151]    16.186168    21.464304    15.091964    19.862444     4.927465
#> [7156]    12.930948    14.048988     7.158971    17.242263    23.563460
#> [7161]    15.466045    19.277646     7.587924    10.872017     9.533815
#> [7166]     4.970147    16.913882    24.449818    43.758709    25.863644
#> [7171]     5.232467     9.738889    11.804419     8.489460    16.669560
#> [7176]    26.688257    17.219719    27.996507     5.178023    11.167806
#> [7181]    11.004149     4.800555    19.655563    43.036808    15.986097
#> [7186]    18.054808     5.628900    11.407267    10.183817     4.532392
#> [7191]    20.219760    27.134075    13.048674    21.588818     5.518193
#> [7196]    12.782701     9.393076     5.146381    18.904115    22.286011
#> [7201]    18.671808    24.223806     8.796984    11.846353    13.320911
#> [7206]     6.489286    19.517095    29.724709    10.712072    17.545316
#> [7211]     4.368678     8.627120    10.559412     5.426895    17.799580
#> [7216]    25.874331    17.997040    18.517430     5.618141    11.743682
#> [7221]    11.158027     3.575223    20.657490    32.562441    19.037497
#> [7226]    26.273791     6.283998    12.640235    11.624089     4.913197
#> [7231]    20.571886    30.399636    15.870522    24.490590     6.410994
#> [7236]    13.209832    11.364761     5.087315    16.052558    22.931022
#> [7241]    16.044677    31.339568     6.483887    11.570144    10.642505
#> [7246]    11.810883    20.532468    24.897924    14.516260    19.030195
#> [7251]     5.798249    10.029972     9.873241     3.567322    15.658822
#> [7256]    23.023953    13.123244    23.926514     4.117592    10.599039
#> [7261]    10.300942     3.321613    20.175308    23.785457    14.509117
#> [7266]    19.682312     4.608440    10.591288     9.225198     8.423284
#> [7271]    22.571393    22.472397    14.747287    19.000214     5.375725
#> [7276]    11.626566    13.137880     4.952970    19.718954    26.383357
#> [7281]    15.215226    28.117391     5.542641    12.041772    11.480610
#> [7286]     5.272277    20.217408    34.523173    15.138853    27.339873
#> [7291]     4.612850    11.663930    10.295282     5.648234    16.710742
#> [7296]    26.140353    16.727275    22.147068     5.179146    10.149677
#> [7301]    10.860208     4.961367    18.097953    27.945734    18.120679
#> [7306]    21.437620     6.141739    10.819232     9.853445     5.869381
#> [7311]    15.428073    27.692158    19.264237    27.566039     6.393489
#> [7316]    10.265059    10.295941     3.146296    14.911231    27.209805
#> [7321]    17.108452    22.307817     5.526573    11.341389    10.502163
#> [7326]     5.046900    23.287188    26.458952    18.182431    15.872881
#> [7331]     4.926028    10.896387     9.224376     6.180670    17.732998
#> [7336]    21.434360    18.239937    20.242460     6.465121    12.215855
#> [7341]    10.073714     7.710437    19.436794    34.905662    18.347346
#> [7346]    24.781970     4.619737    10.903837     9.441030     2.893308
#> [7351]    16.659490    39.575581    14.102785    22.814500     5.316469
#> [7356]    13.326233    10.705395     5.415616    20.063398    23.376480
#> [7361]    17.464293    21.574140     4.836159    11.063343     9.073998
#> [7366]     5.139404    20.440055    32.329492    18.073725    24.193438
#> [7371]     5.621191    11.747614    10.044469     4.964368    21.480612
#> [7376]    24.070078    18.499838    25.460212     5.770030    11.065400
#> [7381]    11.097140     5.494908    20.947693    20.181266    14.691009
#> [7386]    18.358518    12.839608    10.779411    11.778241     4.042762
#> [7391]    14.593209    24.424841    18.810647    30.670111     5.781123
#> [7396]    12.204886    12.370435     7.702345    19.604917    27.572259
#> [7401]    14.847023    22.105461     5.941954    11.608932    11.650530
#> [7406]     4.810545    15.205574    27.321689    15.771732    29.597042
#> [7411]     5.330957    10.728306    11.132029    11.893980    19.501164
#> [7416]    25.440793    11.841345    18.703986     5.092588    13.080661
#> [7421]    11.049942    13.596787    16.725051    28.551876    18.751091
#> [7426]    20.968913     5.036960    10.868268    11.691249     5.074553
#> [7431]    19.074393    20.464564    13.393238    22.127389     5.214133
#> [7436]    11.972148    10.633052     5.715829    17.524953    30.918745
#> [7441]    17.044198    20.282594     5.437108    12.423008    11.990285
#> [7446]     4.790931    19.447584    29.974709    19.251738    17.455773
#> [7451]     6.751485    11.323130    10.531420     7.612166    21.257715
#> [7456]    20.800256    13.720112    25.410774     4.919325    10.800045
#> [7461]     9.372462     5.072446    20.185149    38.150772    19.376895
#> [7466]    20.854240     5.337673    11.381572    12.616399     3.990814
#> [7471]    18.291332    25.068256    12.631867    23.330574     6.869057
#> [7476]    12.553170    11.815984     5.021365    20.802859    28.155576
#> [7481]    15.764191    26.821764     6.360442    11.766035    10.782271
#> [7486]     3.896033    17.382828    27.710311    18.100761    17.079317
#> [7491]     7.684174    11.574225    10.768669     8.289828    18.917753
#> [7496]    26.804411    13.688045    21.537911     5.078491    12.180277
#> [7501]    10.125505     5.288098    22.262421    24.846690    21.931702
#> [7506]    23.686373     6.074599    11.436642    10.600646     4.518934
#> [7511]    21.997900    21.524193    23.527411    26.759419     7.094081
#> [7516]    12.090066    10.643323     4.132045    18.537347    19.476560
#> [7521]    25.686040    21.352789     6.128181    12.199460    13.321196
#> [7526]     2.734434    21.206933    23.053278    17.372551    25.798210
#> [7531]     9.698968    14.378929    12.645599     7.810056    20.034915
#> [7536]    32.555793    16.791938    25.004879     5.251820    13.702863
#> [7541]    10.538479     5.009352    22.555193    19.712689    26.936604
#> [7546]    17.422569     6.176965    14.143801    12.003666     3.828041
#> [7551]    17.644515    25.042951    16.887221    30.769232     9.324177
#> [7556]    12.406835    12.606379     5.283516    18.386701    29.474921
#> [7561]    15.251721    19.601222    10.085241     9.814753    10.810465
#> [7566]     4.140590    19.163609    20.468277    14.263511    22.320248
#> [7571]     5.150916    10.569625    11.878047     6.988212    17.878611
#> [7576]    26.540782    15.207089    20.221743    14.457465    11.367417
#> [7581]    11.208363     4.907654    21.556411    30.568173    14.046807
#> [7586]    19.669251     6.402272    13.619962    10.007125     5.780530
#> [7591]    23.186570    27.099030    15.929814    31.258148     7.509852
#> [7596]     9.551942    13.551723     5.922459    16.579424    20.662296
#> [7601]    19.112092    25.091589     4.978148    11.568894    12.625133
#> [7606]     4.354787    23.936968    26.683195    14.458707    21.009509
#> [7611]    12.612336     9.856103    11.225819     8.167260    16.837622
#> [7616]    20.325522    16.058894    20.026479     5.190318    12.508379
#> [7621]    11.215948     4.217643    19.692705    29.805327    15.671152
#> [7626]    18.085552     5.073741    12.106583    11.490157     5.347962
#> [7631]    18.824891    49.726941    14.281069    20.817688     8.415164
#> [7636]     9.796088    10.595431     5.451450    16.636279    31.143978
#> [7641]    19.292997    16.612393     4.891810    11.551406    12.025671
#> [7646]     3.924839    19.266377    22.736391    16.075325    30.839272
#> [7651]     5.590718    13.171760    11.567755     6.094387    16.769438
#> [7656]    28.060955    12.635570    18.827009     4.027460    12.082643
#> [7661]     9.984518     4.672091    24.819565    30.471918    16.111701
#> [7666]    22.382919     4.645265    12.025229    13.000555     5.091949
#> [7671]    26.920995    26.348043    19.936282    24.945016     6.827643
#> [7676]    11.023471    10.900113     8.315678    21.473304    27.530558
#> [7681]    12.454847    21.831697     5.573722    10.601059    11.925730
#> [7686]     5.746961    20.713728    25.798588    16.012434    21.796169
#> [7691]     6.417882    10.700514    10.903377     4.480478    17.149674
#> [7696]    23.878620    18.499575    25.481645     6.656719    13.782775
#> [7701]    12.623189     5.521048    25.624412    31.446268    16.421929
#> [7706]    20.429872     4.733633    10.520906    11.185344     4.420251
#> [7711]    22.497928    36.608600    15.347308    19.480339     7.083301
#> [7716]    10.731928    14.869575     5.547368    18.916802    25.658793
#> [7721]    15.953297    25.185723     7.185226    12.205838    11.457208
#> [7726]     8.220383    17.299302    23.415723    14.061044    20.435312
#> [7731]     7.046283    12.713612     9.526309     7.821084    19.330632
#> [7736]    30.619985    12.920738    25.131478     6.298253    11.351445
#> [7741]    11.885363     4.346974    20.596821    34.553287    15.620047
#> [7746]    18.851762     3.972778    13.309963     7.983911     4.375903
#> [7751]    17.639627    30.102932   111.255685   107.742982    39.323458
#> [7756]    90.245908    41.333908    34.393383    60.231789  1347.062580
#> [7761]   258.993888   149.097302    80.886770   183.057364   380.588923
#> [7766]   221.053078   231.076300  2751.860237   427.376555   220.757567
#> [7771]   181.393390   275.608580   891.967851   372.613964   324.520833
#> [7776]  2654.088363   605.403913   261.982388   205.642529   331.290232
#> [7781]   737.029419   389.073368   315.570563  2277.503047   615.309312
#> [7786]   300.432175   252.564125   404.578241   908.647718   649.023116
#> [7791]   423.792728  1707.197354   827.826970   349.325771   352.824885
#> [7796]   457.667557   702.284586   429.008773   344.530821  2202.876764
#> [7801]   768.317060   465.955844   290.023176   385.290865   623.483698
#> [7806]   402.191514   305.123658  1714.732878   588.782495   461.701825
#> [7811]   247.541897   320.326130   489.561579   343.556420   303.208162
#> [7816]  1539.537585   651.452719   378.687139   248.363507   302.456540
#> [7821]   429.367335   317.360105   250.107659  1538.783435   509.186961
#> [7826]   391.489768   233.971815   260.377352   347.627022   264.328962
#> [7831]   207.426240  1365.394803   523.692695   327.306901   192.844284
#> [7836]   256.843326   362.948637   242.274251   193.427337  1348.491000
#> [7841]   479.303437   285.394727   165.414905   245.095873   336.400719
#> [7846]   217.795558   192.110785  1252.299473   468.573697   439.146607
#> [7851]   186.816167   218.680490   299.378622   222.052751   172.299356
#> [7856]  1210.765626   476.897979   355.980335   183.315618   236.212957
#> [7861]   271.984407   213.512437   180.891237  1179.405691   434.962204
#> [7866]   293.513382   183.294823   251.041310   263.574969   198.637262
#> [7871]   170.918953  1072.756967   440.406159   270.230960   185.138421
#> [7876]   219.393022   234.354640   167.557228   145.656116  1003.720204
#> [7881]   420.371526   280.616540   167.380158   204.790994   212.103685
#> [7886]   159.726511   136.725763   924.848811   454.933102   316.368792
#> [7891]   160.482277   185.209258   230.637496   156.850222   136.952103
#> [7896]   978.977708   408.307152   260.772104   162.477973   180.792609
#> [7901]   185.818480   126.458559   124.354105   924.736240   417.284080
#> [7906]   257.575590   154.447681   168.303761   162.235745   132.724399
#> [7911]   122.158344   858.140658   378.140355   305.451603   135.094730
#> [7916]   161.287850   158.749598   119.737923   117.369899   802.067620
#> [7921]   403.725657   232.105776   126.496602   159.704853   146.799901
#> [7926]   115.072374   103.631570   706.194285   334.775766   261.211185
#> [7931]   128.103187   149.964394   152.966866   117.347215   104.952157
#> [7936]   706.182840   344.046077   269.141127   123.395546   124.171349
#> [7941]   138.099311    82.074642    75.826916   589.043040   223.601279
#> [7946]   175.886064   142.444739   142.247683   111.930238    91.713923
#> [7951]    86.087973   595.800695   369.323350   212.722680   110.991849
#> [7956]   116.459330   129.801881    89.286497    82.584815   543.322802
#> [7961]   315.849776   218.248313   113.947610   121.421001   123.501765
#> [7966]    85.558560    82.558582   641.804290   345.811973   162.071403
#> [7971]    66.968154   141.820448    90.956242    80.273137    68.719788
#> [7976]   414.186888   184.411137   252.840866   110.139158   137.705735
#> [7981]   100.290282    50.685694    89.180058   497.646742   134.601899
#> [7986]   297.016990    85.664223    89.164163    61.245065    95.795605
#> [7991]    82.820765   534.519704   344.328371   196.745896   104.924516
#> [7996]    62.622743   113.532331    85.375663    82.439499   342.765803

## First we list available isolation windows
table(isolationWindowTargetMz(spectra(mse_dia)))
#> 
#> 163.75 208.95 244.05 270.85  299.1  329.8 367.35 601.85 
#>   1000   1000   1000   1000   1000   1000   1000   1000 

## We can then extract the TIC of MS2 data for a specific isolation window
chr_ms2 <- chromatogram(mse_dia, msLevel = 2L,
    isolationWindowTargetMz = 244.05)
plot(chr_ms2)

####
## Chromatographic peak detection

## Perform peak detection on the data using the centWave algorith. Note
## that the parameters are chosen to reduce the run time of the example.
p <- CentWaveParam(noise = 10000, snthresh = 40, prefilter = c(3, 10000))
xmse <- findChromPeaks(mse, param = p)
xmse
#> Object of class XcmsExperiment 
#>  Spectra: MS1 (3834) 
#>  Experiment data: 3 sample(s)
#>  Sample data links:
#>   - spectra: 3 sample(s) to 3834 element(s).
#>  xcms results:
#>   - chromatographic peaks: 248 in MS level(s): 1 

## Have a quick look at the identified chromatographic peaks
head(chromPeaks(xmse))
#>          mz mzmin mzmax       rt    rtmin    rtmax       into       intb   maxo
#> CP001 453.2 453.2 453.2 2506.073 2501.378 2527.982  1007409.0  1007380.8  38152
#> CP002 302.0 302.0 302.0 2617.185 2595.275 2640.659   687146.6   671297.8  30552
#> CP003 344.0 344.0 344.0 2679.783 2646.919 2709.517  5210015.9  5135916.9 152320
#> CP004 430.1 430.1 430.1 2681.348 2639.094 2712.647  2395840.3  2299899.6  65752
#> CP005 366.0 366.0 366.0 2679.783 2642.224 2718.907  3365174.0  3279468.3  79928
#> CP006 343.0 343.0 343.0 2678.218 2637.529 2712.647 24147443.2 23703761.7 672064
#>          sn sample
#> CP001 38151      1
#> CP002    46      1
#> CP003    68      1
#> CP004    42      1
#> CP005    49      1
#> CP006    87      1

## Extract chromatographic peaks identified between 3000 and 3300 seconds
chromPeaks(xmse, rt = c(3000, 3300), type = "within")
#>          mz mzmin mzmax       rt    rtmin    rtmax        into        intb
#> CP021 453.2 453.2 453.2 3063.196 3035.027 3114.840  3001594.78  3001514.97
#> CP030 361.1 361.1 361.1 3147.704 3141.444 3153.964   367361.84   362278.28
#> CP031 340.3 340.3 340.3 3230.646 3225.952 3233.776    68671.25    68664.99
#> CP032 526.2 526.2 526.2 3243.166 3238.471 3246.296   374698.56   374692.30
#> CP033 313.1 313.1 313.1 3276.030 3254.121 3290.115  1199152.63  1162839.05
#> CP034 454.1 454.1 454.1 3276.030 3261.945 3294.809 12283448.95 12024951.77
#> CP108 307.1 307.1 307.1 3143.009 3121.099 3164.918  2191519.65  2063202.03
#> CP109 278.1 278.1 278.1 3196.217 3180.568 3213.432   657840.25   651048.36
#> CP110 526.1 526.1 526.1 3179.003 3150.833 3210.302 21334966.98 21147392.01
#> CP111 380.1 380.1 380.1 3152.398 3132.054 3174.308  2201517.91  2201474.09
#> CP112 380.1 380.1 380.1 3210.302 3210.302 3216.561   187031.44   187023.61
#> CP113 380.1 380.1 380.1 3202.477 3174.308 3216.561  1156780.73  1156736.91
#> CP114 380.1 380.1 380.1 3222.821 3216.561 3240.036   485818.25   485793.21
#> CP115 286.2 286.2 286.2 3258.815 3246.296 3280.725  1264118.64  1247233.70
#> CP116 308.1 308.1 308.1 3261.945 3241.601 3285.419  2066854.37  2025917.82
#> CP204 380.1 380.1 380.1 3150.835 3128.925 3171.179  2036803.99  1937655.24
#> CP205 286.2 286.2 286.2 3250.992 3233.777 3257.252   732016.23   722185.86
#> CP206 568.2 568.2 568.2 3207.173 3185.264 3232.212  3951832.25  3866503.74
#>         maxo    sn sample
#> CP021  53096 53095      1
#> CP030  49240    57      1
#> CP031  11391 11390      1
#> CP032  60800 60799      1
#> CP033  55392    50      1
#> CP034 554112    58      1
#> CP108 101400    43      2
#> CP109  30208    54      2
#> CP110 622144   251      2
#> CP111  95176 95175      2
#> CP112  25144 28791      2
#> CP113  28920 28919      2
#> CP114  23176 23535      2
#> CP115  67600    41      2
#> CP116  96272    78      2
#> CP204  82624    49      3
#> CP205  74824    68      3
#> CP206 164352   113      3

## Extract ion chromatograms (EIC) for the first two chromatographic
## peaks.
chrs <- chromatogram(xmse,
    mz = chromPeaks(xmse)[1:2, c("mzmin", "mzmax")],
    rt = chromPeaks(xmse)[1:2, c("rtmin", "rtmax")])
#> Processing chromatographic peaks

## An EIC for each sample and each of the two regions was extracted.
## Identified chromatographic peaks in the defined regions are extracted
## as well.
chrs
#> XChromatograms with 2 rows and 3 columns
#>                    1               2               3
#>      <XChromatogram> <XChromatogram> <XChromatogram>
#> [1,]        peaks: 1        peaks: 0        peaks: 0
#> [2,]        peaks: 1        peaks: 0        peaks: 0
#> phenoData with 3 variables
#> featureData with 4 variables
#> - - - xcms preprocessing - - -
#> Chromatographic peak detection:
#>  method: centWave 

## Plot the EICs for the second defined region
plot(chrs[2, ])


## Subsetting the data to the results (and data) for the second sample
a <- xmse[2]
nrow(chromPeaks(xmse))
#> [1] 248
nrow(chromPeaks(a))
#> [1] 100

## Filtering the result by retention time: keeping all spectra and
## chromatographic peaks within 3000 and 3500 seconds.
xmse_sub <- filterRt(xmse, rt = c(3000, 3500))
#> Filter spectra
xmse_sub
#> Object of class XcmsExperiment 
#>  Spectra: MS1 (960) 
#>  Experiment data: 3 sample(s)
#>  Sample data links:
#>   - spectra: 3 sample(s) to 960 element(s).
#>  xcms results:
#>   - chromatographic peaks: 79 in MS level(s): 1 
nrow(chromPeaks(xmse_sub))
#> [1] 79

## Perform an initial feature grouping to allow alignment using the
## peak groups method:
pdp <- PeakDensityParam(sampleGroups = rep(1, 3))
xmse <- groupChromPeaks(xmse, param = pdp)

## Perform alignment using the peak groups method.
pgp <- PeakGroupsParam(span = 0.4)
xmse <- adjustRtime(xmse, param = pgp)
#> Performing retention time correction using 19 peak groups.

## Visualizing the alignment results
plotAdjustedRtime(xmse)

## Performing the final correspondence analysis
xmse <- groupChromPeaks(xmse, param = pdp)

## Show the definition of the first 6 features
featureDefinitions(xmse) |> head()
#>      mzmed mzmin mzmax    rtmed    rtmin    rtmax npeaks 1      peakidx
#> FT01 279.0 279.0 279.0 2789.588 2787.430 2791.746      2 2      11, 199
#> FT02 286.2 286.2 286.2 3253.923 3245.811 3262.034      2 2     115, 205
#> FT03 300.2 300.2 300.2 3385.835 3384.068 3390.895      4 3 35, 125,....
#> FT04 301.0 301.0 301.0 2789.066 2787.430 2790.180      3 3  10, 97, 198
#> FT05 305.1 305.1 305.1 2927.922 2922.158 2933.686      2 2      14, 202
#> FT06 305.1 305.1 305.1 3000.543 2991.470 3009.616      2 2      15, 203
#>      ms_level
#> FT01        1
#> FT02        1
#> FT03        1
#> FT04        1
#> FT05        1
#> FT06        1

## Extract the feature values; show the results for the first 6 rows.
featureValues(xmse) |> head()
#>        ko15.CDF ko16.CDF   ko18.CDF
#> FT01 17140627.0       NA 16919266.9
#> FT02         NA  1264119   732016.2
#> FT03  4700903.2  5313736  5169558.2
#> FT04  3051847.8  1964444  2774885.3
#> FT05  1070389.9       NA  1983342.5
#> FT06   847473.1       NA  1003750.6

## The full results can also be extracted as a `SummarizedExperiment`
## that would eventually simplify subsequent analyses with other packages.
## Any additional parameters passed to the function are passed to the
## `featureValues` function that is called to generate the feature value
## matrix.
se <- quantify(xmse, method = "sum")

## EICs for all features can be extracted with the `featureChromatograms`
## function. Note that, depending on the data set, extracting this for
## all features might take some time. Below we extract EICs for the
## first 10 features by providing the feature IDs.
chrs <- featureChromatograms(xmse,
    features = rownames(featureDefinitions(xmse))[1:10])
chrs
#> XChromatograms with 10 rows and 3 columns
#>              ko15.CDF        ko16.CDF        ko18.CDF
#>       <XChromatogram> <XChromatogram> <XChromatogram>
#> [1,]         peaks: 1        peaks: 0        peaks: 1
#> [2,]         peaks: 0        peaks: 1        peaks: 1
#> ...              ...             ...             ... 
#> [9,]         peaks: 1        peaks: 2        peaks: 0
#> [10,]        peaks: 1        peaks: 1        peaks: 1
#> phenoData with 3 variables
#> featureData with 4 variables
#> - - - xcms preprocessing - - -
#> Chromatographic peak detection:
#>  method: centWave 
#> Correspondence:
#>  method: chromatographic peak density 
#>  10 feature(s) identified.

plot(chrs[3, ])