Mercurial > repos > eschen42 > w4mkmeans
annotate w4m_general_purpose_routines.R @ 0:6ccbe18131a6 draft
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
author | eschen42 |
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date | Tue, 08 Aug 2017 15:30:38 -0400 |
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children | c415b7dc6f37 |
rev | line source |
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0
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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1 # prepare.data.matrix - Prepare x.datamatrix for multivariate statistical analaysis (MVA) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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2 # - Motivation: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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3 # - Selection: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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4 # - You may want to exclude several samples from your analysis: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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5 # - If so, set the argument 'exclude.samples' to a vector of sample names |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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6 # - You may want to exclude several features or features from your analysis: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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7 # - If so, set the argument 'exclude.features' to a vector of feature names |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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8 # - Renaming samples: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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9 # - You may want to rename several samples from your analysis: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
eschen42
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10 # - If so, set the argument 'sample.rename.function' to a function accepting a vector |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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11 # of sample names and producing a vector of strings of equivalent length |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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12 # - MVA is confounded by missing values. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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13 # - By default, this function imputes missing values as zero. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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14 # - For a different imputation, set the 'data.imputation' argument to a function |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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15 # accepting a single matrix argument and returning a matrix of the same |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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16 # dimensions as the argument. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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17 # - Transformation |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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18 # - It may be desirable to transform the intensity data to reduce the range. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
eschen42
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19 # - By default, this function performs an eigth-root transformation: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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20 # - Any root-tranformation has the advantage of never being negative. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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21 # - Calculation of the eight-root is four times faster in my hands than log10. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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22 # - However, it has the disadvantage that calculation of fold-differences |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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23 # is not additive as with log-transformation. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
eschen42
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24 # - Rather, you must divide the values and raise to the eighth power. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
eschen42
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25 # - For a different transformation, set the 'data.transformation' argument |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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26 # to a function accepting a single matrix argument. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
eschen42
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27 # - The function should be written to return a matrix of the same dimensions |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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28 # as the argument. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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29 # arguments: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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30 # - x.matrix - matrix of intensities (or data.frame of sample metadata) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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31 # - one row per sample |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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32 # - one column per feature or metadata attribute |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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33 # - exclude.samples - vector of labels of matrix rows (samples) to omit from analysis |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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34 # - exclude.features - vector of labels of matrix columnss (features) to omit from analysis |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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35 # - sample.rename.function - function to be used to rename rows if necessary, or NULL |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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36 # - e.g., sample.rename.function = function(x) { |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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37 # sub("(.*)_.*","\\1", row.names(x)) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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38 # } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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39 # - data.imputation - function applied to matrix to impute missing values |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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40 # - e.g., data.imputation = function(m) { |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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41 # m[is.na(m)] <- min(m, na.rm = TRUE) / 100 |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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42 # return (m) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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43 # } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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44 # - data.transformation - function applied to matrix cells |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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45 # - e.g., data.transformation = function(x) { return( log10(x) ) } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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46 # or, data.transformation = log10 |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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47 # result value: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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48 # transformed, imputed x.datamatrix with renamed rows and with neither excluded values nor features |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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49 # |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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50 ################################ |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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51 ## |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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52 ## Notes regarding the effectiveness and performance of the data transformation method. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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53 ## |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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54 ## The two transformations that I tried (log10 and 8th root) required different imputation methods. |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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55 ## |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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56 ## For the LCMS resin data set that I was working with, separation in MVA was nearly equivalent for: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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57 ## data.imputation <- function(x.matrix) { |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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58 ## x.matrix[is.na(x.matrix)] <- 0 |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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59 ## return (x.matrix) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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60 ## } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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61 ## data.transformation <- function(x) { |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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62 ## sqrt( sqrt( sqrt(x) ) ) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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63 ## } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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64 ## and |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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65 ## data.imputation <- function(x.matrix) { |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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66 ## x.matrix[is.na(x.matrix)] <- min(x.matrix, na.rm = TRUE) / 100 |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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67 ## return (x.matrix) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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68 ## } |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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69 ## data.transformation <- function(x) { |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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70 ## log10(x) |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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71 ## } |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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72 ## |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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73 ## Note further that triple application of the square root: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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74 ## - may be four times faster than log10: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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75 ## - may be three times faster than log2: |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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76 ## |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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77 ## system.time( junk <- sqrt( sqrt( sqrt(1:100000000) ) ) ) |
6ccbe18131a6
planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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78 ## user system elapsed |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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79 ## 0.832 0.236 1.069 |
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80 ## system.time( junk <- log10(1:100000000) ) |
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81 ## user system elapsed |
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82 ## 3.936 0.400 4.337 |
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planemo upload for repository https://github.com/HegemanLab/w4mkmeans_galaxy_wrapper/tree/master commit 299e5c7fdb0d6eb0773f3660009f6d63c2082a8d
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83 ## system.time( junk <- log2(1:100000000) ) |
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84 ## user system elapsed |
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85 ## 2.784 0.320 3.101 |
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86 ## |
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87 ################################ |
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88 # |
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89 prepare.data.matrix <- function( |
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90 x.matrix |
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91 , exclude.samples = NULL |
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92 , exclude.features = NULL |
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93 , sample.rename.function = NULL |
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94 , data.imputation = |
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95 function(m) { |
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96 # replace NA values with zero |
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97 m[is.na(m)] <- 0 |
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98 # replace negative values with zero, if applicable (It should never be applicable!) |
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99 if (min(m < 0)) { |
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100 m <- matrix(lapply(X = m, FUN = function(z) {max(z,0)}), nrow = nrow(m) ) |
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101 } |
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102 # return matrix as the result |
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103 return (m) |
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104 } |
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105 , data.transformation = function(x) { |
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106 sqrt( sqrt( sqrt(x) ) ) |
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107 } |
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108 , en = new.env() |
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109 ) { |
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110 # MatVar - Compute variance of rows or columns of a matrix |
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111 # ref: http://stackoverflow.com/a/25100036 |
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112 # For row variance, dim == 1, for col variance, dim == 2 |
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113 MatVar <- function(x, dim = 1) { |
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114 if (dim == 1) { |
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115 dim.x.2 <- dim(x)[2] |
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116 if ( dim.x.2 == 0 ) |
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117 stop("MatVar: there are zero columns") |
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118 if ( dim.x.2 == 1 ) { |
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119 stop("MatVar: a single column is insufficient to calculate a variance") |
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120 # return ( rep.int(x = 0, times = nrow(x)) ) |
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121 } else { |
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122 return ( rowSums( (x - rowMeans(x))^2 ) / ( dim(x)[2] - 1 ) ) |
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123 } |
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124 } else if (dim == 2) { |
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125 dim.x.1 <- dim(x)[1] |
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126 if ( dim.x.1 == 0 ) { |
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127 stop("MatVar: there are zero rows") |
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128 } |
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129 if ( dim.x.1 == 1 ) { |
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130 stop("MatVar: a single row is insufficient to calculate a variance") |
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131 # return ( rep.int(x = 0, times = ncol(x)) ) |
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132 } else { |
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133 return ( rowSums( (t(x) - colMeans(x))^2 ) / ( dim(x)[1] - 1 ) ) |
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134 } |
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135 } else stop("Please enter valid dimension, for rows, dim = 1; for colums, dim = 2") |
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136 } |
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137 |
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138 nonzero.var <- function(x) { |
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139 if (nrow(x) == 0) { |
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140 print(str(x)) |
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141 stop("matrix has no rows") |
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142 } |
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143 if (ncol(x) == 0) { |
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144 print(str(x)) |
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145 stop("matrix has no columns") |
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146 } |
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147 if ( is.numeric(x) ) { |
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148 # exclude any rows with zero variance |
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149 row.vars <- MatVar(x, dim = 1) |
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150 nonzero.row.vars <- row.vars > 0 |
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151 nonzero.rows <- row.vars[nonzero.row.vars] |
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152 if ( length(rownames(x)) != length(rownames(nonzero.rows)) ) { |
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153 row.names <- attr(nonzero.rows,"names") |
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154 x <- x[ row.names, , drop = FALSE ] |
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155 } |
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156 |
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157 # exclude any columns with zero variance |
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158 column.vars <- MatVar(x, dim = 2) |
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159 nonzero.column.vars <- column.vars > 0 |
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160 nonzero.columns <- column.vars[nonzero.column.vars] |
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161 if ( length(colnames(x)) != length(colnames(nonzero.columns)) ) { |
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162 column.names <- attr(nonzero.columns,"names") |
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163 x <- x[ , column.names, drop = FALSE ] |
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164 } |
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165 } |
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166 return (x) |
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167 } |
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168 |
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169 if (is.null(x.matrix)) { |
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170 stop("FATAL ERROR - prepare.data.matrix was called with null x.matrix") |
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171 } |
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172 |
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173 en$xpre <- x <- x.matrix |
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174 |
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175 # exclude any samples as indicated |
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176 if ( !is.null(exclude.features) ) { |
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177 my.colnames <- colnames(x) |
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178 my.col.diff <- setdiff(my.colnames, exclude.features) |
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179 x <- x[ , my.col.diff , drop = FALSE ] |
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180 } |
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181 |
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182 # exclude any features as indicated |
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183 if ( !is.null(exclude.samples) ) { |
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184 my.rownames <- rownames(x) |
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185 my.row.diff <- setdiff(my.rownames, exclude.samples) |
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186 x <- x[ my.row.diff, , drop = FALSE ] |
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187 } |
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188 |
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189 # rename rows if desired |
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190 if ( !is.null(sample.rename.function) ) { |
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191 renamed <- sample.rename.function(x) |
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192 rownames(x) <- renamed |
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193 } |
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194 |
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195 # save redacted x.datamatrix to environment |
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196 en$redacted.data.matrix <- x |
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197 |
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198 # impute values missing from the x.datamatrix |
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199 if ( !is.null(data.imputation) ) { |
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200 x <- data.imputation(x) |
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201 } |
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202 |
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203 # perform transformation if desired |
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204 if ( !is.null(data.transformation) ) { |
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205 x <- data.transformation(x) |
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206 } else { |
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207 x <- x |
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208 } |
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209 |
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210 # purge rows and columns that have zero variance |
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211 if ( is.numeric(x) ) { |
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212 x <- nonzero.var(x) |
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213 } |
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214 |
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215 # save imputed, transformed x.datamatrix to environment |
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216 en$imputed.transformed.data.matrix <- x |
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217 |
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218 return(x) |
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219 } |
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220 |
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221 |
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222 ##----------------------------------------------- |
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223 ## helper functions for error detection/reporting |
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224 ##----------------------------------------------- |
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225 |
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226 # log-printing to stderr |
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227 log_print <- function(x, ...) { |
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228 cat( |
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229 format(Sys.time(), "%Y-%m-%dT%H:%M:%S%z") |
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230 , " " |
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231 , c(x, ...) |
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232 , "\n" |
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233 , sep="" |
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234 , file=stderr() |
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235 ) |
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236 } |
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237 |
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238 # tryCatchFunc produces a list |
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239 # On success of expr(), tryCatchFunc produces |
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240 # list(success TRUE, value = expr(), msg = "") |
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241 # On failure of expr(), tryCatchFunc produces |
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242 # list(success = FALSE, value = NA, msg = "the error message") |
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243 tryCatchFunc <- function(expr) { |
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244 # format error for logging |
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245 format_error <- function(e) { |
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246 paste(c("Error { message:", e$message, ", call:", e$call, "}"), collapse = " ") |
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247 } |
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248 my_expr <- expr |
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249 retval <- NULL |
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250 tryCatch( |
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251 expr = { |
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252 retval <- ( list( success = TRUE, value = my_expr(), msg = "" ) ) |
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253 } |
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254 , error = function(e) { |
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255 retval <<- list( success = FALSE, value = NA, msg = format_error(e) ) |
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256 } |
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257 ) |
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258 return (retval) |
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259 } |
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260 |
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261 # tryCatchProc produces a list |
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262 # On success of expr(), tryCatchProc produces |
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263 # list(success TRUE, msg = "") |
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264 # On failure of expr(), tryCatchProc produces |
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265 # list(success = FALSE, msg = "the error message") |
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266 tryCatchProc <- function(expr) { |
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267 # format error for logging |
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268 format_error <- function(e) { |
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269 paste(c("Error { message:", e$message, ", call:", e$call, "}"), collapse = " ") |
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270 } |
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271 retval <- NULL |
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272 tryCatch( |
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273 expr = { |
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274 expr() |
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275 retval <- ( list( success = TRUE, msg = "" ) ) |
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276 } |
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277 , error = function(e) { |
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278 retval <<- list( success = FALSE, msg = format_error(e) ) |
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279 } |
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280 ) |
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281 return (retval) |
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282 } |
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283 |