Commit 7e9e5719 authored by dmattek's avatar dmattek

bug fixes

parent 40c81676
......@@ -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
......
......@@ -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,
......
......@@ -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(
......
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