Commit 483b6be2 authored by majpark21's avatar majpark21

Various tooltip updates

parent 7f1ffe11
.Rproj.user
.Rhistory
.RData
.Ruserdata
......@@ -181,16 +181,16 @@ helpText.server = c(
'Long format: a row is a single data point. Wide format: a row is a time series with columns as time points.', #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
'Load CSV file with 5 columns: grouping, start and end tpts of stimulation, start and end of y-position, dummy column with ID.', #5
'Interpolate missing time points and pre-existing NAs. 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
'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
'Divide measurments by the mean/median or calculate z-score with respect to selected time span.', #11
'Divide measurements by the mean/median or calculate z-score with respect to selected time span.', #11
'Fold-change or z-score with respect to selected time span.', #12
'Normalise with respect to this time span.', #13
'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and sd.', #14
'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and standard deviation.', #14
'Normalise to mean/median of selected time calculated globally, per group, or for individual time series.', #15
'Download time series after modification in this section.' #16
)
......
......@@ -35,7 +35,7 @@ clustHierUI <- function(id, label = "Hierarchical CLustering") {
"Ward D2" = 6,
"McQuitty" = 7
),
selected = 5
selected = 2
)
),
column(4,
......@@ -149,9 +149,9 @@ clustHierUI <- function(id, label = "Hierarchical CLustering") {
)
),
withSpinner(plotOutput(ns('outPlotHier'))),
actionButton(ns('butPlotHierHeatMap'), 'Plot!'),
downPlotUI(ns('downPlotHier'), "Download PNG")
downPlotUI(ns('downPlotHier'), "Download PNG"),
withSpinner(plotOutput(ns('outPlotHier')))
),
tabPanel('Averages',
......
......@@ -34,7 +34,7 @@ clustHierSparUI <- function(id, label = "Sparse Hierarchical CLustering") {
"Single" = 3,
"Centroid" = 4
),
selected = 1
selected = 2
)
),
......
......@@ -14,10 +14,10 @@
# callModule(clustHier, 'TabClustHier', dataMod)
# where dataMod is the output from a reactive function that returns dataset ready for clustering
helpText.tabScatter = c("Display measurement values from two different time points as a scatter plot.",
'Y-axis can display a value at a selected time point or a difference between values at two selected time points.', #1
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
'A number of time points left & right of selected time points; use the mean of values from these time points for the scatterplot.', #3
'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
)
......@@ -48,7 +48,7 @@ tabScatterPlotUI <- function(id, label = "Comparing t-points") {
bsTooltip(ns('inNeighTpts'), helpText.tabScatter[4], placement = "bottom", trigger = "hover", options = NULL),
radioButtons(ns('rBfoldChange'), 'Y-axis',
choices = c("Y" = "y", "Y-X" = "diff"),
choices = c("Y" = "y", "Y - X" = "diff"),
width = "100px", inline = T),
bsTooltip(ns('rBfoldChange'), helpText.tabScatter[2], placement = "bottom", trigger = "hover", options = NULL)
......@@ -79,7 +79,7 @@ tabScatterPlotUI <- function(id, label = "Comparing t-points") {
br(),
checkboxInput(ns('plotInt'),
'Interactive Plot?',
'Interactive Plot',
value = FALSE),
actionButton(ns('butGoScatter'), 'Plot!'),
uiOutput(ns("plotInt_ui")),
......
......@@ -170,7 +170,7 @@ modTrajPlot = function(input, output, session,
ns('inSetYboundsLow'),
label = 'Lower',
step = 0.1,
value = floor(min(loc.dt[[COLY]], na.rm = T))
value = min(loc.dt[[COLY]], na.rm = T)
)
}
})
......@@ -192,7 +192,7 @@ modTrajPlot = function(input, output, session,
ns('inSetYboundsHigh'),
label = 'Upper',
step = 0.1,
value = ceil(max(loc.dt[[COLY]], na.rm = T))
value = max(loc.dt[[COLY]], na.rm = T)
)
}
})
......
......@@ -146,7 +146,7 @@ modTrajRibbonPlot = function(input, output, session,
ns('inSetYboundsLow'),
label = 'Lower',
step = 0.1,
value = floor(min(loc.dt[[COLY]], na.rm = T))
value = min(loc.dt[[COLY]], na.rm = T)
)
}
})
......@@ -168,7 +168,7 @@ modTrajRibbonPlot = function(input, output, session,
ns('inSetYboundsHigh'),
label = 'Upper',
step = 0.1,
value = ceil(max(loc.dt[[COLY]], na.rm = T))
value = max(loc.dt[[COLY]], na.rm = T)
)
}
})
......
......@@ -235,7 +235,7 @@ shinyServer(function(input, output, session) {
#cat('UI varSelGroup::locColSel ', locColSel, '\n')
selectInput(
'inSelGroup',
'Select:',
'Group column:',
locCols,
width = '100%',
selected = locColSel,
......
......@@ -100,7 +100,7 @@ shinyUI(fluidPage(
uiOutput('uiChBnormGroup'),
tags$hr(),
downloadButton('downloadDataClean', 'Download mod\'d data'),
downloadButton('downloadDataClean', 'Download processed data'),
bsTooltip('downloadDataClean', helpText.server[16], placement = "bottom", trigger = "hover", options = NULL)
),
......
Markdown is supported
0%
or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment