Mercurial > repos > george-weingart > maaslin
view src/lib/Constants.R @ 8:e9677425c6c3 default tip
Updated the structure of the libraries
author | george.weingart@gmail.com |
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date | Mon, 09 Feb 2015 12:17:40 -0500 |
parents | e0b5980139d9 |
children |
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##################################################################################### #Copyright (C) <2012> # #Permission is hereby granted, free of charge, to any person obtaining a copy of #this software and associated documentation files (the "Software"), to deal in the #Software without restriction, including without limitation the rights to use, copy, #modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, #and to permit persons to whom the Software is furnished to do so, subject to #the following conditions: # #The above copyright notice and this permission notice shall be included in all copies #or substantial portions of the Software. # #THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, #INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A #PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT #HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION #OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE #SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # # This file is a component of the MaAsLin (Multivariate Associations Using Linear Models), # authored by the Huttenhower lab at the Harvard School of Public Health # (contact Timothy Tickle, ttickle@hsph.harvard.edu). ##################################################################################### inlinedocs <- function( ##author<< Curtis Huttenhower <chuttenh@hsph.harvard.edu> and Timothy Tickle <ttickle@hsph.harvard.edu> ##description<< Global project constants. ) { return( pArgs ) } #General c_COMMA = "," c_DASH = "-" #For reading IO c_MATRIX_NAME = "Matrix:" c_FILE_NAME = "File:" c_DELIMITER = "Delimiter:" c_ID_ROW = "Name_Row_Number:" c_ID_COLUMN = "Name_Column_Number:" c_ROWS = "Read_Rows:" c_PCLROWS = "Read_PCL_Rows:" c_TSVROWS = "Read_TSV_Rows:" c_COLUMNS = "Read_Columns:" c_PCLCOLUMNS = "Read_PCL_Columns:" c_TSVCOLUMNS = "Read_TSV_Columns:" c_CHARACTER_DATA_TYPE = "DT_Character:" c_FACTOR_DATA_TYPE = "DT_Factor:" c_INTEGER_DATA_TYPE = "DT_Integer:" c_LOGICAL_DATA_TYPE = "DT_Logical:" c_NUMERIC_DATA_TYPE = "DT_Numeric:" c_ORDEREDFACTOR_DATA_TYPE = "DT_Ordered_Factor:" ### The name of the data matrix read in using a read.config file c_strMatrixData <- "Abundance" ### The name of the metadata matrix read in using a read.config file c_strMatrixMetadata <- "Metadata" # Settings for MFA visualization/ordination c_iMFA <- 30 c_dHeight <- 9 c_dDefaultScale = 0.5 # The column that is used to determine if information meets a certain significance threshold (dSignificanceLevel) to include in the Summary text file) c_strKeywordEvaluatedForInclusion <- "Q.value" #The name of the custom process function c_strCustomProcessFunction = "processFunction" #Delimiters #Feature name delimiter c_cFeatureDelim = "|" c_cFeatureDelimRex = "\\|" #The word used for unclassified c_strUnclassified = "unclassified" #Maaslincore settings #If a metadata does not have more than count of unique values, it is changed to factor data mode. c_iNonFactorLevelThreshold = 3 #Extensions c_sDetailFileSuffix = ".txt" c_sSummaryFileSuffix = ".txt" c_sLogFileSuffix = "_log" #Delimiter for output tables c_cTableDelimiter="\t" #Testing Related c_strTestingDirectory = "testing" c_strCorrectAnswers = "answers" c_strTemporaryFiles = "tmp" c_strTestingInput = "input" #Reading matrix defaults c_strDefaultMatrixDelimiter = "\t" c_strDefaultMatrixRowID = "1" c_strDefaultMatrixColID = "1" c_strDefaultReadRows = "-" c_strDefaultReadCols = "-" #Separator used when collapsing factor names c_sFactorNameSep = "" #Separator used by the mfa c_sMFANameSep1 = "_" c_sMFANameSep2 = "." #Analysis Module list positioning c_iSelection = 1 c_iTransform = 2 c_iAnalysis = 3 c_iResults = 4 c_iUnTransform = 5 c_iIsUnivariate = 6 #Count based models c_vCountBasedModels = c("neg_binomial","quasi") # Na action in anaylsis, placed here to standardize c_strNA_Action = "na.omit"