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Fixes #383 histogram can plot bars as frequency #384

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Oct 6, 2022
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Fixes #383 histogram can plot bars as frequency #384

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3d57cf9
Fixes #383 histogram can plot bars as frequency
pchelle Sep 23, 2022
1c20f7f
Update documentation about default values of histogram
pchelle Oct 6, 2022
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8 changes: 7 additions & 1 deletion R/histogram-datamapping.R
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,8 @@ HistogramDataMapping <- R6::R6Class(
"HistogramDataMapping",
inherit = XYGDataMapping,
public = list(
#' @field frequency logical defining if histogram displays a frequency in y axis
frequency = NULL,
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shouldn't it be frequency = FALSE, instead of NULL?

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Here, both work as the actual value is defined during the initialization by frequency=FALSE.
Unless unlock_object=TRUE, a field named frequency has to be available before the initialization of the object no matter its value.

#' @field stack logical defining if histogram bars should be stacked
stack = NULL,
#' @field bins number of bins or binning values/methods passed on `ggplot2::geom_histogram`
Expand All @@ -17,22 +19,26 @@ HistogramDataMapping <- R6::R6Class(
distribution = NULL,

#' @description Create a new `HistogramDataMapping` object
#' @param frequency logical defining if histogram displays a frequency in y axis
#' @param stack logical defining if histogram bars should be stacked
#' @param bins argument passed on `ggplot2::geom_histogram`
#' @param binwidth width of bins passed on `ggplot2::geom_histogram`. Overwrites `bins`
#' @param distribution Name of distribution to fit to the data.
#' Only 2 distributions are currently available: `"normal"` and `"logNormal"`
#' @param ... parameters inherited from `XYGDataMapping`
#' @return A new `HistogramDataMapping` object
initialize = function(stack = FALSE,
initialize = function(frequency = FALSE,
stack = FALSE,
bins = NULL,
binwidth = NULL,
distribution = NULL,
...) {
super$initialize(...)
validateIsLogical(frequency)
validateIsLogical(stack)
validateIsIncluded(distribution, c("none", "normal", "logNormal"), nullAllowed = TRUE)

self$frequency <- frequency
self$stack <- stack
self$bins <- bins %||% tlfEnv$defaultAggregation$bins
self$binwidth <- binwidth
Expand Down
44 changes: 42 additions & 2 deletions R/plot-histogram.R
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Expand Up @@ -3,15 +3,21 @@
#' Producing Histograms
#'
#' @inheritParams addScatter
#' @param frequency logical defining if histogram displays a frequency in y axis
#' @param bins Number or edges of bins.
#' If `bins` is provided as a single numeric values, `bin` corresponds to number of bins.
#' The bin edges are then equally spaced within the range of data.
#' If `bins` is provided as an array of numeric values, `bin` corresponds to their edges.
#' Default value, `bins=NULL`, uses the value defined by `dataMapping`
#' @param binwidth Numerical value of defining the width of each bin.
#' If defined, `binwidth` can overwrite `bins` if `bins` was not provided or simply provided as a single value.
#' Default value, `binwidth=NULL`, uses the value defined by `dataMapping`
#' @param stack Logical defining for multiple histograms if their bars are stacked
#' Default value, `stack=NULL`, uses the value defined by `dataMapping`
#' @param distribution Name of distribution to fit to the data.
#' Only 2 distributions are currently available: `"normal"` and `"logNormal"`
#' Use `distribution="none"` to prevent fit of distribution
#' Default value, `distribution=NULL`, uses the value defined by `dataMapping`
#' @param dataMapping
#' A `HistogramDataMapping` object mapping `x` and aesthetic groups to their variable names of `data`.
#' @param plotConfiguration
Expand All @@ -27,6 +33,9 @@
#' # Produce histogram of normally distributed data
#' plotHistogram(x = rnorm(100))
#'
#' # Produce histogram of normally distributed data normalized in y axis
#' plotHistogram(x = rnorm(100), frequency = TRUE)
#'
#' # Produce histogram of normally distributed data with many bins
#' plotHistogram(x = rlnorm(100), bins = 21)
#'
Expand All @@ -37,6 +46,7 @@ plotHistogram <- function(data = NULL,
metaData = NULL,
x = NULL,
dataMapping = NULL,
frequency = NULL,
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same

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In plot functions, I had made the choice of leaving NULL as the default value for optional arguments.
So that they won't overwrite the values created by dataMapping and plotConfiguration.
This aims at making it easier to centralize and modify the default frequency, bins, distribution, etc. as it is managed only by the HistogramDataMapping object.
I can change it if it makes it clearer for the users.

bins = NULL,
binwidth = NULL,
stack = NULL,
Expand All @@ -61,16 +71,26 @@ plotHistogram <- function(data = NULL,
validateIsNumeric(binwidth, nullAllowed = TRUE)
validateIsLogical(stack, nullAllowed = TRUE)
validateIsIncluded(distribution, c("normal", "logNormal", "none"), nullAllowed = TRUE)
validateIsLogical(frequency, nullAllowed = TRUE)

dataMapping$frequency <- frequency %||% dataMapping$frequency
dataMapping$stack <- stack %||% dataMapping$stack
dataMapping$distribution <- distribution %||% dataMapping$distribution
dataMapping$bins <- bins %||% dataMapping$bins
dataMapping$binwidth <- binwidth %||% dataMapping$binwidth

# Check for default labeling to update plotConfiguration after using .setPlotConfiguration
ylabel <- NULL
if (isEmpty(plotConfiguration)) {
ylabel <- ifelse(dataMapping$frequency, "Relative frequency", "Count")
}

plotConfiguration <- .setPlotConfiguration(
plotConfiguration, HistogramPlotConfiguration,
data, metaData, dataMapping
)
# Update default ylabel based on frequency
plotConfiguration$labels$ylabel <- ylabel %||% plotConfiguration$labels$ylabel
plotObject <- .setPlotObject(plotObject, plotConfiguration)

mapData <- dataMapping$checkMapData(data)
Expand All @@ -89,6 +109,23 @@ plotHistogram <- function(data = NULL,
if (length(dataMapping$bins) > 1) {
edges <- dataMapping$bins
}
# Manage ggplot aes_string property depending on stack and frequency options
# geom_histogram can use computed variables defined between two dots
# see https://ggplot2.tidyverse.org/reference/geom_histogram.html for more info
yAes <- "..count.."

if (dataMapping$frequency) {
# If histogram bars are not stacked, calculate frequency within each data groups
# Since there is no direct computed variable
# ncount variable is scaled by binwidth*dnorm(0) to get an area of ~1
yAes <- paste0("..ncount..*max(..width..)*", stats::dnorm(0))
if (dataMapping$stack) {
# If histogram bars are stacked,
# Calculate overall frequency as count per bin / total
# This results in same histogram shapes no matter the data groups
yAes <- "..count../sum(..count..)"
}
}

aestheticValues <- .getAestheticValuesFromConfiguration(
n = 1,
Expand All @@ -101,6 +138,7 @@ plotHistogram <- function(data = NULL,
data = mapData,
mapping = ggplot2::aes_string(
x = mapLabels$x,
y = yAes,
fill = mapLabels$fill
),
position = position,
Expand Down Expand Up @@ -202,9 +240,10 @@ plotHistogram <- function(data = NULL,
binwidth <- dataMapping$binwidth %||% binwidth

if (dataMapping$stack) {
yScaling <- binwidth * ifelse(dataMapping$frequency, 1, length(x))
dataFit <- data.frame(
x = xFit,
y = length(x) * binwidth * switch(dataMapping$distribution,
y = yScaling * switch(dataMapping$distribution,
"normal" = stats::dnorm(xFit, mean = mean(x, na.rm = TRUE), sd = stats::sd(x, na.rm = TRUE)),
"logNormal" = stats::dlnorm(xFit, meanlog = mean(log(x), na.rm = TRUE), sdlog = stats::sd(log(x), na.rm = TRUE))
),
Expand All @@ -216,11 +255,12 @@ plotHistogram <- function(data = NULL,
dataFit <- NULL
for (groupLevel in levels(data$legendLabels)) {
selectedGroup <- data$legendLabels %in% groupLevel
yScaling <- binwidth * ifelse(dataMapping$frequency, 1, length(x[selectedGroup]))
dataFit <- rbind.data.frame(
dataFit,
data.frame(
x = xFit,
y = length(x[selectedGroup]) * binwidth * switch(dataMapping$distribution,
y = yScaling * switch(dataMapping$distribution,
"normal" = stats::dnorm(
xFit,
mean = mean(x[selectedGroup], na.rm = TRUE),
Expand Down
11 changes: 1 addition & 10 deletions R/plotconfiguration-sub-classes.R
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Expand Up @@ -76,16 +76,7 @@ ResVsTimePlotConfiguration <- R6::R6Class(
#' @family PlotConfiguration classes
HistogramPlotConfiguration <- R6::R6Class(
"HistogramPlotConfiguration",
inherit = PlotConfiguration,
public = list(
#' @description Create a new `HistogramPlotConfiguration` object
#' @param ylabel Histograms default display is "Count"
#' @param ... parameters inherited from `PlotConfiguration`
#' @return A new `HistogramPlotConfiguration` object
initialize = function(ylabel = "Count", ...) {
super$initialize(ylabel = ylabel, ...)
}
)
inherit = PlotConfiguration
)

#' @title QQPlotConfiguration
Expand Down
5 changes: 5 additions & 0 deletions man/HistogramDataMapping.Rd
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30 changes: 7 additions & 23 deletions man/HistogramPlotConfiguration.Rd
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19 changes: 15 additions & 4 deletions man/plotHistogram.Rd
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