@@ -39,6 +39,12 @@ paths <- kwb.utils::resolve(PATHS, desktop = kwb.utils::desktop())
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dir_config <- file.path(kwb.utils::desktop(), "R_Development/RScripts/Flusshygiene/config")
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paths_read <- kwb.utils::readDictionary(file.path(dir_config, "pathDictionary.txt"))
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paths_read <- kwb.utils::resolve(paths_read)
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+ paths_read$dir.data <- ifelse(dir.exists(paths_read$dir.data),
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+ paths_read$dir.data,
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+ "<path_dir.data>")
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+ paths_read$dir.corr <- ifelse(dir.exists(paths_read$dir.corr),
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+ paths_read$dir.corr,
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+ "<path_dir.corr>")
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```
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This document explains the rain data validation procedure as we started to apply
@@ -78,18 +84,18 @@ The task to be performed during "rain data validation" is to
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We follow a semi-automatic approach in which we use
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- - the script `` r windowsPath(PATHS$script_1) `` to read, reformat and merge rain
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+ - the script `` r kwb.utils:: windowsPath(PATHS$script_1) `` to read, reformat and merge rain
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data and correction data and to save the result to RData files and
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- - the script `` r windowsPath(PATHS$script_2) `` to read rain data and correction
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+ - the script `` r kwb.utils:: windowsPath(PATHS$script_2) `` to read rain data and correction
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data from the RData files and prepare csv files in which the time intervals
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that most probably contain rain heights that need correction are indicated.
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The first script reads
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- - rain data files from `` r windowsPath(paths_read$dir.data) `` and
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+ - rain data files from `` r kwb.utils:: windowsPath(paths_read$dir.data) `` and
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- - correction files from `` r windowsPath(paths_read$dir.corr) `` .
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+ - correction files from `` r kwb.utils:: windowsPath(paths_read$dir.corr) `` .
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The user can then check the CSV files created by the second script, edit them
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appropriately and save them under a different name (` userdiff_*.csv ` in the
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