bug fixes

modules/auxfunc.R

@@ -191,15 +191,12 @@ helpText.server = c(
                            "<li>A column with a time point. Headers of columns with time points need to be numeric</li>"), #2
   'Generate 60 random synthetic time series distributed evenly among 6 groups. Every time series has 60 time points.',             #3
   'Load CSV file with a column of track IDs for removal. IDs should correspond to those used for plotting.',                       #4
-<<<<<<< HEAD
   'Load CSV file with 5 columns: grouping, start and end tpts of stimulation, start and end of y-position, dummy column with ID.', #5
   chBtrajInter = 'Interpolate missing time points and pre-existing NAs. Missing time points are rows entirely missing from the dataset. To interpolate, the interval of the time column must be provided.',                       #6
   'If the track ID is unique only within a group, make it unique globally by combining with grouping columns.',                    #7
-=======
   'Load CSV file with 5 columns: grouping, start and end time points of stimulation, start and end of y-position, dummy column with ID.', #5
   'Interpolate missing time points indicated with NAs. In addition, add NA if a row with a time point is completely missing. The interval of the time column must be provided to know which rows are missing.',                       #6
   'If the track ID is not globally unique, try to make it unique by prepending another column to the track ID (typically the group column).',                    #7
->>>>>>> d154660843617744aa265b8e65e9abb9bbf8b1ce
   'Select columns to group data according to treatment, condition, etc.',                                                          #8
   'Select math operation to perform on a single or two columns,',                                                                  #9
   'Select range of time for further processing.',                                                                                  #10

modules/tabScatter.R

@@ -14,22 +14,14 @@
 # callModule(clustHier, 'TabClustHier', dataMod)
 # where dataMod is the output from a reactive function that returns dataset ready for clustering
 
-<<<<<<< HEAD
-helpText.tabScatter = c(alScatter = "Display measurement values from two different time points as a scatter plot.",
-                        rBfoldChange = 'Y-axis can display a value at a selected time point or a difference between values at two selected time points.', #1
-                  chBregression = 'Add a line with linear regression and regions of 95% confidence interval.', #2
-                  inNeighTpts = 'A number of time points left & right of selected time points; use the mean of values from these time points for the scatterplot.', #3
-                  inPlotHeight = 'Height in pixels of the displayed plot', #4
-                  inPlotNcolFacet = 'Number of facets in a row. Each facet displayes a scatter plot for a single group.' #5
-=======
-helpText.tabScatter = c("Display measurement relationship between two different time points as a scatter plot. Instead of using the exact value of time points, can also use local average values around them with the smoothing option.",
-                  'Y-axis can display a value at a selected time point or a difference between values at two selected time points. The former reports the magnitude of the difference while the former reports the amplitude of the difference between the 2 selected time points.', #1
-                  'Add a line with linear regression and regions of 95% confidence interval.', #2
-                  'Window length for moving average smoothing used before plotting the scatterplot. Useful to avoid artefacts in the scatterplot due to spurious variations at specific time points.', #3
-                  'Height in pixels of the displayed plot', #4
-                  'Number of facets in a row. Each facet displayes a scatter plot for a single group.' #5
->>>>>>> d154660843617744aa265b8e65e9abb9bbf8b1ce
-)
+helpText.tabScatter = c(alScatter = paste0("Display measurement relationship between two different time points as a scatter plot. ",
+                                           "Instead of plotting the exact value of time points, you can also switch on smoothing and use local average values around chosen time points."),
+                        rBfoldChange = paste0("Y-axis can display a value at a selected time point or a difference between values at two selected time points.", 
+                                              "The former reports the magnitude of the difference while the former reports the amplitude of the difference between the 2 selected time points."),
+                        chBregression = 'Add a line with linear regression and regions of 95% confidence interval.', #2
+                        inNeighTpts = 'Window length in time points for smoothing with the average used before plotting the scatterplot. Useful to avoid artefacts in the scatterplot due to spurious variations at specific time points.', #3
+                        inPlotHeight = 'Height in pixels of the displayed plot', #4
+                        inPlotNcolFacet = 'Number of facets in a row. Each facet displayes a scatter plot for a single group.')
 
 # UI ----
 tabScatterPlotUI <- function(id, label = "Comparing t-points") {
@@ -41,34 +33,22 @@ tabScatterPlotUI <- function(id, label = "Comparing t-points") {
     ),
     actionLink(ns("alScatter"), "Learn more"),
     br(),
-    
     fluidRow(
       column(
         4,
         uiOutput(ns('uiSelTptX')),
         uiOutput(ns('uiSelTptY')),
-        bsAlert("alertAnchor2differentTpts"),
-        radioButtons(ns('rBfoldChange'), 'Y-axis', 
-                     choices = c("Y" = "y", "Y-X" = "diff"), 
-                     width = "100px", inline = T),
-        bsTooltip(ns('rBfoldChange'), helpText.tabScatter[["rBfoldChange"]], placement = "top", trigger = "hover", options = NULL)
+        bsAlert("alertAnchor2differentTpts")
       ),
       column(
         4, 
         numericInput(ns('inNeighTpts'), 'Smoothing', value = 0, step = 1, min = 0, width = "120px"),
-<<<<<<< HEAD
         bsTooltip(ns('inNeighTpts'), helpText.tabScatter[["inNeighTpts"]], placement = "top", trigger = "hover", options = NULL),
         checkboxInput(ns('chBregression'), 'Linear regression with 95% CI'),
-        bsTooltip(ns('chBregression'), helpText.tabScatter[["chBregression"]], placement = "top", trigger = "hover", options = NULL)
-=======
-        bsTooltip(ns('inNeighTpts'), helpText.tabScatter[4], placement = "bottom", trigger = "hover", options = NULL),
-
+        bsTooltip(ns('chBregression'), helpText.tabScatter[["chBregression"]], placement = "top", trigger = "hover", options = NULL),
         radioButtons(ns('rBfoldChange'), 'Y-axis', 
                      choices = c("Y" = "y", "Y - X" = "diff"), 
-                     width = "100px", inline = T),
-        bsTooltip(ns('rBfoldChange'), helpText.tabScatter[2], placement = "bottom", trigger = "hover", options = NULL)
-        
->>>>>>> d154660843617744aa265b8e65e9abb9bbf8b1ce
+                     width = "100px", inline = T)
       ),
       column(
         4,

ui.R

@@ -99,13 +99,8 @@ shinyUI(fluidPage(
       uiOutput('uiChBnormGroup'),
 
       tags$hr(),
-<<<<<<< HEAD
-      downloadButton('downloadDataClean', 'Download mod\'d data'),
-      bsTooltip('downloadDataClean', helpText.server[16], placement = "top", trigger = "hover", options = NULL)
-=======
       downloadButton('downloadDataClean', 'Download processed data'),
-      bsTooltip('downloadDataClean', helpText.server[16], placement = "bottom", trigger = "hover", options = NULL)
->>>>>>> d154660843617744aa265b8e65e9abb9bbf8b1ce
+      bsTooltip('downloadDataClean', helpText.server[16], placement = "top", trigger = "hover", options = NULL)
     ),
     
     mainPanel(