Package 'funkyheatmap' reference manual

Title:	Generating Funky Heatmaps for Data Frames
Description:	Allows generating heatmap-like visualisations for benchmark data frames. Funky heatmaps can be fine-tuned by providing annotations of the columns and rows, which allows assigning multiple palettes or geometries or grouping rows and columns together in categories. Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.
Authors:	Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter), Louise Deconinck [ctb] (<https://orcid.org/0000-0001-8100-6823>, LouiseDck), Artuur Couckuyt [ctb] , Nick Markov [ctb] (<https://orcid.org/0000-0002-3659-4387>, mxposed), Luke Zappia [ctb] (<https://orcid.org/0000-0001-7744-8565>, lazappi)
Maintainer:	Robrecht Cannoodt <[email protected]>
License:	MIT + file LICENSE
Version:	0.6.0
Built:	2024-11-13 22:21:06 UTC
Source:	https://github.com/funkyheatmap/funkyheatmap

The results data frame from dynbenchmark.

Description

This data was generated by running the data-raw/dynbenchmark_data.R script. It is used in the vignette named "vignette("dynbenchmark")" to regenerate the results figures in Saelens et al. 2019.

Usage

dynbenchmark_data
dynbenchmark_data

Format

An object of class list of length 6.

References

Saelens W, Cannoodt R, Todorov H, Saeys Y (2019). “A comparison of single-cell trajectory inference methods.” Nature Biotechnology. doi:10.1038/s41587-019-0071-9.

Generate a funky heatmaps for benchmarks

Description

Allows generating heatmap-like visualisations for benchmark data frames. Funky heatmaps can be fine-tuned by providing annotations of the columns and rows, which allows assigning multiple palettes or geometries or grouping rows and columns together in categories.

Usage

funky_heatmap(
  data,
  column_info = NULL,
  row_info = NULL,
  column_groups = NULL,
  row_groups = NULL,
  palettes = NULL,
  legends = NULL,
  position_args = position_arguments(),
  scale_column = TRUE,
  add_abc = TRUE,
  col_annot_offset,
  col_annot_angle,
  expand
)
funky_heatmap(
  data,
  column_info = NULL,
  row_info = NULL,
  column_groups = NULL,
  row_groups = NULL,
  palettes = NULL,
  legends = NULL,
  position_args = position_arguments(),
  scale_column = TRUE,
  add_abc = TRUE,
  col_annot_offset,
  col_annot_angle,
  expand
)

Arguments

`data`	A data frame with items by row and features in the columns. Must contain one column named `"id"`.
`column_info`	A data frame describing which columns in `data` to plot. This data frame should contain the following columns: `id` (`character`, required): A column name in `data` to plot. Determines the size of the resulting geoms, and also the color unless `color` is specified. `id_color` (`character`): A column name in `data` to use for the color of the resulting geoms. If `NA`, the `id` column will be used. `id_size` (`character`): A column name in `data` to use for the size of the resulting geoms. If `NA`, the `id` column will be used. `name` (`character`): A label for the column. If `NA` or `""`, no label will be plotted. If this column is missing, `id` will be used to generate the `name` column. `geom` (`character`): The geom of the column. Must be one of: `"funkyrect"`, `"circle"`, `"rect"`, `"bar"`, `"pie"`, `"text"` or `"image"`. For `"text"`, the corresponding column in `data` must be a `character`. For `"pie"`, the column must be a list of named numeric vectors. For all other geoms, the column must be a `numeric`. `group` (`character`): The grouping id of each column, must match with `column_groups$group`. If this column is missing or all values are `NA`, columns are assumed not to be grouped. `palette` (`character`): Which palette to colour the geom by. Each value should have a matching value in `palettes$palette`. `width`: Custom width for this column (default: 1). `overlay`: Whether to overlay this column over the previous column. If so, the width of that column will be inherited. `legend`: Whether or not to add a legend for this column. `hjust`: Horizontal alignment of the bar, must be between [0,1] (only for `geom = "bar"`). `vjust`: Vertical alignment of the label, must be between [0,1] (only for `geom = "text"`). `size`: Size of the label, must be a numeric value (only for `geom = "text"`). `label`: Which column to use as a label (only for `geom = "text"`). `directory`: Which directory to use to find the images (only for `geom = "image"`). `extension`: The extension of the images (only for `geom = "image"`). `draw_outline`: Whether or not to draw bounding guides (only for `geom == "bar"`). Default: `TRUE`. `options` (`list` or `json`): Any of the options above. Any values in this column will be spread across the other columns. This is useful for not having to provide a data frame with 1000s of columns. This column can be a json string.
`row_info`	A data frame describing the rows of `data`. This data should contain two columns: `id` (`character`): Corresponds to the column `data$id`. `group` (`character`): The group of the row. If all are `NA`, the rows will not be split up into groups.
`column_groups`	A data frame describing of how to group the columns in `column_info`. Can consist of the following columns: `group` (`character`): The corresponding group in `column_info$group`. `palette` (`character`, optional): The palette used to colour the column group backgrounds. `level1` (`character`): The label at the highest level. `level2` (`character`, optional): The label at the middle level. `level3` (`character`, optional): The label at the lowest level (not recommended).
`row_groups`	A data frame describing of how to group the rows in `row_info`. Can consist of the following columns: `group` (`character`): The corresponding group in `row_info$group`. `level1` (`character`): The label at the highest level. `level2` (`character`, optional): The label at the middle level. `level3` (`character`, optional): The label at the lowest level (not recommended).
`palettes`	A named list of palettes. Each entry in `column_info$palette` should have an entry in this object. If an entry is missing, the type of the column will be inferred (categorical or numerical) and one of the default palettes will be applied. Alternatively, the name of one of the standard palette names can be used: `numerical`: `"Greys"`, `"Blues"`, `"Reds"`, `"YlOrBr"`, `"Greens"` `categorical`: `"Set3"`, `"Set1"`, `"Set2"`, `"Dark2"`
`legends`	A list of legends to add to the plot. Each entry in `column_info$legend` should have a corresponding entry in this object. Each entry should be a list with the following names: `palette` (`character`): The palette to use for the legend. Must be a value in `palettes`. `geom` (`character`): The geom of the legend. Must be one of: `"funkyrect"`, `"circle"`, `"rect"`, `"bar"`, `"pie"`, `"text"`, `"image"`. `title` (`character`, optional): The title of the legend. Defaults to the palette name. `enabled` (`logical`, optional): Whether or not to add the legend. Defaults to `TRUE`. `labels` (`character`, optional): The labels to use for the legend. The defaults depend on the selected geom. `size` (`numeric`, optional): The size of the listed geoms. The defaults depend on the selected geom. `color` (`character`, optional): The color of the listed geoms. The defaults depend on the selected geom. `values` (optional): Used as values for the text and image geoms. `label_width` (`numeric`, optional): The width of the labels (only when geom is `text` or `pie`). Defaults to `1` for text and `2` for images. `value_width` (`numeric`, optional): The width of the values (only for `geom = "text"`). Defaults to `2`. `label_hjust` (`numeric`, optional): The horizontal alignment of the labels (only when geom is `circle`, `rect` or `funkyrect`). Defaults to `0.5`.
`position_args`	Sets parameters that affect positioning within a plot, such as row and column dimensions, annotation details, and the expansion directions of the plot. See `position_arguments()` for more information.
`scale_column`	Whether or not to apply min-max scaling to each numerical column.
`add_abc`	Whether or not to add subfigure labels to the different columns groups.
`col_annot_offset`	DEPRECATED: use `position_args = position_arguments(col_annot_offset = ...)` instead.
`col_annot_angle`	DEPRECATED: use `position_args = position_arguments(col_annot_angle = ...)` instead.
`expand`	DEPRECATED: use `⁠position_args = position_arguments(expand_* = ...)⁠` instead.

Value

A ggplot. .$width and .$height are suggested dimensions for storing the plot with ggplot2::ggsave().

Examples

library(tibble, warn.conflicts = FALSE)

data("mtcars")

data <- rownames_to_column(mtcars, "id")

funky_heatmap(data)
library(tibble, warn.conflicts = FALSE)

data("mtcars")

data <- rownames_to_column(mtcars, "id")

funky_heatmap(data)

Rounded rectangles

Description

Does what ggplot2::geom_rect() does, only curvier. Use the radius aesthetic to change the corner radius.

Usage

geom_rounded_rect(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_rounded_rect(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`stat`	The statistical transformation to use on the data for this layer. When using a `⁠geom_*()⁠` function to construct a layer, the `stat` argument can be used the override the default coupling between geoms and stats. The `stat` argument accepts the following: A `Stat` ggproto subclass, for example `StatCount`. A string naming the stat. To give the stat as a string, strip the function name of the `stat_` prefix. For example, to use `stat_count()`, give the stat as `"count"`. For more information and other ways to specify the stat, see the layer stat documentation.
`position`	A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The `position` argument accepts the following: The result of calling a position function, such as `position_jitter()`. This method allows for passing extra arguments to the position. A string naming the position adjustment. To give the position as a string, strip the function name of the `position_` prefix. For example, to use `position_jitter()`, give the position as `"jitter"`. For more information and other ways to specify the position, see the layer position documentation.
`...`	Other arguments passed on to `layer()`'s `params` argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the `position` argument, or aesthetics that are required can not be passed through `...`. Unknown arguments that are not part of the 4 categories below are ignored. Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, `colour = "red"` or `linewidth = 3`. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the `params`. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data. When constructing a layer using a `⁠stat_()⁠` function, the `...` argument can be used to pass on parameters to the `geom` part of the layer. An example of this is `stat_density(geom = "area", outline.type = "both")`. The geom's documentation lists which parameters it can accept. Inversely, when constructing a layer using a `⁠geom_()⁠` function, the `...` argument can be used to pass on parameters to the `stat` part of the layer. An example of this is `geom_area(stat = "density", adjust = 0.5)`. The stat's documentation lists which parameters it can accept. The `key_glyph` argument of `layer()` may also be passed on through `...`. This can be one of the functions described as key glyphs, to change the display of the layer in the legend.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.

Details

geom_rect() and geom_tile()'s respond differently to scale transformations due to their parameterisation. In geom_rect(), the scale transformation is applied to the corners of the rectangles. In geom_tile(), the transformation is applied only to the centres and its size is determined after transformation.

Aesthetics

geom_tile() understands the following aesthetics (required aesthetics are in bold):

x
y
alpha
colour
fill
group
height
linetype
linewidth
width

Note that geom_raster() ignores colour.

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Examples

library(ggplot2)

df <- data.frame(
  x = rep(c(2, 5, 7, 9, 12), 2),
  y = rep(c(1, 2), each = 5),
  z = factor(rep(1:5, each = 2)),
  w = rep(diff(c(0, 4, 6, 8, 10, 14)), 2)
)

ggplot(df) +
  geom_rounded_rect(
    aes(
      xmin = x - w / 2,
      xmax = x + w / 2,
      ymin = y,
      ymax = y + 1,
      radius = .5,
      fill = z
    ),
    colour = "white"
  )
library(ggplot2)

df <- data.frame(
  x = rep(c(2, 5, 7, 9, 12), 2),
  y = rep(c(1, 2), each = 5),
  z = factor(rep(1:5, each = 2)),
  w = rep(diff(c(0, 4, 6, 8, 10, 14)), 2)
)

ggplot(df) +
  geom_rounded_rect(
    aes(
      xmin = x - w / 2,
      xmax = x + w / 2,
      ymin = y,
      ymax = y + 1,
      radius = .5,
      fill = z
    ),
    colour = "white"
  )

Defines parameters for positioning in a plot.

Description

This function sets parameters that affect positioning within a plot, such as row and column dimensions, annotation details, and the expansion directions of the plot.

Usage

position_arguments(
  row_height = 1,
  row_space = 0.1,
  row_bigspace = 1.2,
  col_width = 1,
  col_space = 0.1,
  col_bigspace = 0.5,
  col_annot_offset = 3,
  col_annot_angle = 30,
  expand_xmin = 0,
  expand_xmax = 2,
  expand_ymin = 0,
  expand_ymax = 0
)
position_arguments(
  row_height = 1,
  row_space = 0.1,
  row_bigspace = 1.2,
  col_width = 1,
  col_space = 0.1,
  col_bigspace = 0.5,
  col_annot_offset = 3,
  col_annot_angle = 30,
  expand_xmin = 0,
  expand_xmax = 2,
  expand_ymin = 0,
  expand_ymax = 0
)

Arguments

`row_height`	The height of the rows.
`row_space`	The space between rows.
`row_bigspace`	The large space between row groups.
`col_width`	The width of the columns.
`col_space`	The space between columns.
`col_bigspace`	The large space between column groups.
`col_annot_offset`	How much the column annotation will be offset by.
`col_annot_angle`	The angle of the column annotation labels.
`expand_xmin`	The minimum expansion of the plot in the x direction.
`expand_xmax`	The maximum expansion of the plot in the x direction.
`expand_ymin`	The minimum expansion of the plot in the y direction.
`expand_ymax`	The maximum expansion of the plot in the y direction.

Value

A list of plot positioning parameters.

Examples

position_arguments(row_height = 1.2, col_width = 1.5, expand_xmax = 3)
position_arguments(row_height = 1.2, col_width = 1.5, expand_xmax = 3)

Scale a vector to the range [0, 1]

Description

Scale a vector to the range [0, 1]

Usage

scale_minmax(x)
scale_minmax(x)

Arguments

`x`	A numeric vector

Value

A numeric vector scaled to the range [0, 1]

Examples

scale_minmax(c(1, 2, 3))
scale_minmax(c(1, 2, 3))

Summary results from the scIB project

Description

This dataset was generated by running the data-raw/scib_summary.R script. This script downloads data for the RNA tasks from the scIB reproducibility repository and summarises it similarly (but not exactly like) what was done in the original paper to give a final ranking of the top performing methods. It is used in the scIB vignette (vignette("scIB")) to reproduce the overall summary figure in Luecken et al. 2021.

Usage

scib_summary
scib_summary

Format

An object of class tbl_df (inherits from tbl, data.frame) with 20 rows and 27 columns.

References

Luecken MD, Büttner M, Chaichoompu K, Danese A, Interlandi M, Mueller MF, Strobl DC, Zappia L, Dugas M, Colomé-Tatché M, Theis FJ (2021). “Benchmarking atlas-level data integration in single-cell genomics.” Nature methods. doi:10.1038/s41592-021-01336-8.

Verify the integrity of the column groups object

Description

Verify the integrity of the column groups object

Usage

verify_column_groups(column_groups, column_info)
verify_column_groups(column_groups, column_info)

Arguments

column_groups

A data frame describing of how to group the columns in column_info. Can consist of the following columns:

group (character): The corresponding group in column_info$group.
palette (character, optional): The palette used to colour the column group backgrounds.
level1 (character): The label at the highest level.
level2 (character, optional): The label at the middle level.
level3 (character, optional): The label at the lowest level (not recommended).

column_info

A data frame describing which columns in data to plot. This data frame should contain the following columns:

id (character, required): A column name in data to plot. Determines the size of the resulting geoms, and also the color unless color is specified.
id_color (character): A column name in data to use for the color of the resulting geoms. If NA, the id column will be used.
id_size (character): A column name in data to use for the size of the resulting geoms. If NA, the id column will be used.
name (character): A label for the column. If NA or "", no label will be plotted. If this column is missing, id will be used to generate the name column.
geom (character): The geom of the column. Must be one of: "funkyrect", "circle", "rect", "bar", "pie", "text" or "image". For "text", the corresponding column in data must be a character. For "pie", the column must be a list of named numeric vectors. For all other geoms, the column must be a numeric.
group (character): The grouping id of each column, must match with column_groups$group. If this column is missing or all values are NA, columns are assumed not to be grouped.
palette (character): Which palette to colour the geom by. Each value should have a matching value in palettes$palette.
width: Custom width for this column (default: 1).
overlay: Whether to overlay this column over the previous column. If so, the width of that column will be inherited.
legend: Whether or not to add a legend for this column.
hjust: Horizontal alignment of the bar, must be between [0,1] (only for geom = "bar").
vjust: Vertical alignment of the label, must be between [0,1] (only for geom = "text").
size: Size of the label, must be a numeric value (only for geom = "text").
label: Which column to use as a label (only for geom = "text").
directory: Which directory to use to find the images (only for geom = "image").
extension: The extension of the images (only for geom = "image").
draw_outline: Whether or not to draw bounding guides (only for geom == "bar"). Default: TRUE.
options (list or json): Any of the options above. Any values in this column will be spread across the other columns. This is useful for not having to provide a data frame with 1000s of columns. This column can be a json string.

Value

The column groups object with all expected columns.

Examples

library(tibble)
column_groups <- tribble(
  ~group, ~level1,
  "foo", "Foo",
  "bar", "Bar"
)
column_info <- tribble(
  ~id, ~geom, ~group,
  "name", "text", NA_character_,
  "foo1", "funkyrect", "foo",
  "foo2", "funkyrect", "foo",
  "bar1", "funkyrect", "bar",
  "bar2", "funkyrect", "bar"
)
verify_column_groups(column_groups, column_info)
library(tibble)
column_groups <- tribble(
  ~group, ~level1,
  "foo", "Foo",
  "bar", "Bar"
)
column_info <- tribble(
  ~id, ~geom, ~group,
  "name", "text", NA_character_,
  "foo1", "funkyrect", "foo",
  "foo2", "funkyrect", "foo",
  "bar1", "funkyrect", "bar",
  "bar2", "funkyrect", "bar"
)
verify_column_groups(column_groups, column_info)

Verify the integrity of the column info object

Description

Verify the integrity of the column info object

Usage

verify_column_info(column_info, data)
verify_column_info(column_info, data)

Arguments

column_info

A data frame describing which columns in data to plot. This data frame should contain the following columns:

id (character, required): A column name in data to plot. Determines the size of the resulting geoms, and also the color unless color is specified.
id_color (character): A column name in data to use for the color of the resulting geoms. If NA, the id column will be used.
id_size (character): A column name in data to use for the size of the resulting geoms. If NA, the id column will be used.
name (character): A label for the column. If NA or "", no label will be plotted. If this column is missing, id will be used to generate the name column.
geom (character): The geom of the column. Must be one of: "funkyrect", "circle", "rect", "bar", "pie", "text" or "image". For "text", the corresponding column in data must be a character. For "pie", the column must be a list of named numeric vectors. For all other geoms, the column must be a numeric.
group (character): The grouping id of each column, must match with column_groups$group. If this column is missing or all values are NA, columns are assumed not to be grouped.
palette (character): Which palette to colour the geom by. Each value should have a matching value in palettes$palette.
width: Custom width for this column (default: 1).
overlay: Whether to overlay this column over the previous column. If so, the width of that column will be inherited.
legend: Whether or not to add a legend for this column.
hjust: Horizontal alignment of the bar, must be between [0,1] (only for geom = "bar").
vjust: Vertical alignment of the label, must be between [0,1] (only for geom = "text").
size: Size of the label, must be a numeric value (only for geom = "text").
label: Which column to use as a label (only for geom = "text").
directory: Which directory to use to find the images (only for geom = "image").
extension: The extension of the images (only for geom = "image").
draw_outline: Whether or not to draw bounding guides (only for geom == "bar"). Default: TRUE.
options (list or json): Any of the options above. Any values in this column will be spread across the other columns. This is useful for not having to provide a data frame with 1000s of columns. This column can be a json string.

data

A data frame with items by row and features in the columns. Must contain one column named "id".

Value

The column info object with all expected columns.

Examples

library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom,
  "name", "text",
  "x", "funkyrect",
  "y", "funkyrect"
)
verify_column_info(column_info, data)
library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom,
  "name", "text",
  "x", "funkyrect",
  "y", "funkyrect"
)
verify_column_info(column_info, data)

Verify the integrity of the data object

Description

Verify the integrity of the data object

Usage

verify_data(data)
verify_data(data)

Arguments

data

A data frame with items by row and features in the columns. Must contain one column named "id".

Value

A verified data object

Examples

library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
verify_data(data)
library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
verify_data(data)

Verify the integrity of the legends object

Description

Verify the integrity of the legends object

Usage

verify_legends(legends, palettes, column_info, data)
verify_legends(legends, palettes, column_info, data)

Arguments

`legends`	A list of legends to add to the plot. Each entry in `column_info$legend` should have a corresponding entry in this object. Each entry should be a list with the following names: `palette` (`character`): The palette to use for the legend. Must be a value in `palettes`. `geom` (`character`): The geom of the legend. Must be one of: `"funkyrect"`, `"circle"`, `"rect"`, `"bar"`, `"pie"`, `"text"`, `"image"`. `title` (`character`, optional): The title of the legend. Defaults to the palette name. `enabled` (`logical`, optional): Whether or not to add the legend. Defaults to `TRUE`. `labels` (`character`, optional): The labels to use for the legend. The defaults depend on the selected geom. `size` (`numeric`, optional): The size of the listed geoms. The defaults depend on the selected geom. `color` (`character`, optional): The color of the listed geoms. The defaults depend on the selected geom. `values` (optional): Used as values for the text and image geoms. `label_width` (`numeric`, optional): The width of the labels (only when geom is `text` or `pie`). Defaults to `1` for text and `2` for images. `value_width` (`numeric`, optional): The width of the values (only for `geom = "text"`). Defaults to `2`. `label_hjust` (`numeric`, optional): The horizontal alignment of the labels (only when geom is `circle`, `rect` or `funkyrect`). Defaults to `0.5`.
`palettes`	A named list of palettes. Each entry in `column_info$palette` should have an entry in this object. If an entry is missing, the type of the column will be inferred (categorical or numerical) and one of the default palettes will be applied. Alternatively, the name of one of the standard palette names can be used: `numerical`: `"Greys"`, `"Blues"`, `"Reds"`, `"YlOrBr"`, `"Greens"` `categorical`: `"Set3"`, `"Set1"`, `"Set2"`, `"Dark2"`
`column_info`	A data frame describing which columns in `data` to plot. This data frame should contain the following columns: `id` (`character`, required): A column name in `data` to plot. Determines the size of the resulting geoms, and also the color unless `color` is specified. `id_color` (`character`): A column name in `data` to use for the color of the resulting geoms. If `NA`, the `id` column will be used. `id_size` (`character`): A column name in `data` to use for the size of the resulting geoms. If `NA`, the `id` column will be used. `name` (`character`): A label for the column. If `NA` or `""`, no label will be plotted. If this column is missing, `id` will be used to generate the `name` column. `geom` (`character`): The geom of the column. Must be one of: `"funkyrect"`, `"circle"`, `"rect"`, `"bar"`, `"pie"`, `"text"` or `"image"`. For `"text"`, the corresponding column in `data` must be a `character`. For `"pie"`, the column must be a list of named numeric vectors. For all other geoms, the column must be a `numeric`. `group` (`character`): The grouping id of each column, must match with `column_groups$group`. If this column is missing or all values are `NA`, columns are assumed not to be grouped. `palette` (`character`): Which palette to colour the geom by. Each value should have a matching value in `palettes$palette`. `width`: Custom width for this column (default: 1). `overlay`: Whether to overlay this column over the previous column. If so, the width of that column will be inherited. `legend`: Whether or not to add a legend for this column. `hjust`: Horizontal alignment of the bar, must be between [0,1] (only for `geom = "bar"`). `vjust`: Vertical alignment of the label, must be between [0,1] (only for `geom = "text"`). `size`: Size of the label, must be a numeric value (only for `geom = "text"`). `label`: Which column to use as a label (only for `geom = "text"`). `directory`: Which directory to use to find the images (only for `geom = "image"`). `extension`: The extension of the images (only for `geom = "image"`). `draw_outline`: Whether or not to draw bounding guides (only for `geom == "bar"`). Default: `TRUE`. `options` (`list` or `json`): Any of the options above. Any values in this column will be spread across the other columns. This is useful for not having to provide a data frame with 1000s of columns. This column can be a json string.
`data`	A data frame with items by row and features in the columns. Must contain one column named `"id"`.

Value

The legends object in the expected format.

Examples

library(tibble)
library(grDevices)
library(RColorBrewer)

# explicit form
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom, ~palette,
  "name", "text", NA,
  "foo", "funkyrect", "pal1",
  "bar", "funkyrect", "pal2"
)
palettes <- list(
  pal1 = rev(brewer.pal(9, "Greys")[-1]),
  pal2 = rev(brewer.pal(9, "Reds")[-8:-9])
)
legends <- list()
verify_legends(legends, palettes, column_info, data)
library(tibble)
library(grDevices)
library(RColorBrewer)

# explicit form
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom, ~palette,
  "name", "text", NA,
  "foo", "funkyrect", "pal1",
  "bar", "funkyrect", "pal2"
)
palettes <- list(
  pal1 = rev(brewer.pal(9, "Greys")[-1]),
  pal2 = rev(brewer.pal(9, "Reds")[-8:-9])
)
legends <- list()
verify_legends(legends, palettes, column_info, data)

Verify the integrity of the palettes object

Description

Verify the integrity of the palettes object

Usage

verify_palettes(palettes, column_info, data)
verify_palettes(palettes, column_info, data)

Arguments

palettes

A named list of palettes. Each entry in column_info$palette should have an entry in this object. If an entry is missing, the type of the column will be inferred (categorical or numerical) and one of the default palettes will be applied. Alternatively, the name of one of the standard palette names can be used:

numerical: "Greys", "Blues", "Reds", "YlOrBr", "Greens"
categorical: "Set3", "Set1", "Set2", "Dark2"

column_info

A data frame describing which columns in data to plot. This data frame should contain the following columns:

id (character, required): A column name in data to plot. Determines the size of the resulting geoms, and also the color unless color is specified.
id_color (character): A column name in data to use for the color of the resulting geoms. If NA, the id column will be used.
id_size (character): A column name in data to use for the size of the resulting geoms. If NA, the id column will be used.
name (character): A label for the column. If NA or "", no label will be plotted. If this column is missing, id will be used to generate the name column.
geom (character): The geom of the column. Must be one of: "funkyrect", "circle", "rect", "bar", "pie", "text" or "image". For "text", the corresponding column in data must be a character. For "pie", the column must be a list of named numeric vectors. For all other geoms, the column must be a numeric.
group (character): The grouping id of each column, must match with column_groups$group. If this column is missing or all values are NA, columns are assumed not to be grouped.
palette (character): Which palette to colour the geom by. Each value should have a matching value in palettes$palette.
width: Custom width for this column (default: 1).
overlay: Whether to overlay this column over the previous column. If so, the width of that column will be inherited.
legend: Whether or not to add a legend for this column.
hjust: Horizontal alignment of the bar, must be between [0,1] (only for geom = "bar").
vjust: Vertical alignment of the label, must be between [0,1] (only for geom = "text").
size: Size of the label, must be a numeric value (only for geom = "text").
label: Which column to use as a label (only for geom = "text").
directory: Which directory to use to find the images (only for geom = "image").
extension: The extension of the images (only for geom = "image").
draw_outline: Whether or not to draw bounding guides (only for geom == "bar"). Default: TRUE.
options (list or json): Any of the options above. Any values in this column will be spread across the other columns. This is useful for not having to provide a data frame with 1000s of columns. This column can be a json string.

data

A data frame with items by row and features in the columns. Must contain one column named "id".

Value

The palettes object with all expected columns.

Examples

library(tibble)
library(grDevices)
library(RColorBrewer)

# explicit form
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom, ~palette,
  "name", "text", NA,
  "foo", "funkyrect", "pal1",
  "bar", "funkyrect", "pal2"
)
palettes <- list(
  pal1 = rev(brewer.pal(9, "Greys")[-1]),
  pal2 = rev(brewer.pal(9, "Reds")[-8:-9])
)
verify_palettes(palettes, column_info, data)

# implicit palettes
palettes <- list(
  pal1 = "Greys",
  pal2 = "Reds"
)
verify_palettes(palettes, column_info, data)

# passing a tibble should also work (for backwards compatibility)
palettes <- tribble(
  ~palette, ~colours,
  "pal1", rev(brewer.pal(9, "Greys")[-1]),
  "pal2", rev(brewer.pal(9, "Reds")[-8:-9])
)
verify_palettes(palettes, column_info, data)
library(tibble)
library(grDevices)
library(RColorBrewer)

# explicit form
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo", "Foo", 0.5, 0.7,
  "bar", "Bar", 1.0, 0.1
)
column_info <- tribble(
  ~id, ~geom, ~palette,
  "name", "text", NA,
  "foo", "funkyrect", "pal1",
  "bar", "funkyrect", "pal2"
)
palettes <- list(
  pal1 = rev(brewer.pal(9, "Greys")[-1]),
  pal2 = rev(brewer.pal(9, "Reds")[-8:-9])
)
verify_palettes(palettes, column_info, data)

# implicit palettes
palettes <- list(
  pal1 = "Greys",
  pal2 = "Reds"
)
verify_palettes(palettes, column_info, data)

# passing a tibble should also work (for backwards compatibility)
palettes <- tribble(
  ~palette, ~colours,
  "pal1", rev(brewer.pal(9, "Greys")[-1]),
  "pal2", rev(brewer.pal(9, "Reds")[-8:-9])
)
verify_palettes(palettes, column_info, data)

Verify the integrity of the row groups object

Description

Verify the integrity of the row groups object

Usage

verify_row_groups(row_groups, row_info)
verify_row_groups(row_groups, row_info)

Arguments

row_groups

A data frame describing of how to group the rows in row_info. Can consist of the following columns:

group (character): The corresponding group in row_info$group.
level1 (character): The label at the highest level.
level2 (character, optional): The label at the middle level.
level3 (character, optional): The label at the lowest level (not recommended).

row_info

A data frame describing the rows of data. This data should contain two columns:

id (character): Corresponds to the column data$id.
group (character): The group of the row. If all are NA, the rows will not be split up into groups.

Value

The row groups object with all expected rows.

Examples

library(tibble)
row_groups <- tribble(
  ~group, ~level1,
  "foo", "Foo",
  "bar", "Bar"
)
row_info <- tribble(
  ~id, ~group,
  "name", NA_character_,
  "foo1", "foo",
  "foo2", "foo",
  "bar1", "bar",
  "bar2", "bar"
)
verify_row_groups(row_groups, row_info)
library(tibble)
row_groups <- tribble(
  ~group, ~level1,
  "foo", "Foo",
  "bar", "Bar"
)
row_info <- tribble(
  ~id, ~group,
  "name", NA_character_,
  "foo1", "foo",
  "foo2", "foo",
  "bar1", "bar",
  "bar2", "bar"
)
verify_row_groups(row_groups, row_info)

Verify the integrity of the row info object

Description

Verify the integrity of the row info object

Usage

verify_row_info(row_info, data)
verify_row_info(row_info, data)

Arguments

row_info

A data frame describing the rows of data. This data should contain two columns:

id (character): Corresponds to the column data$id.
group (character): The group of the row. If all are NA, the rows will not be split up into groups.

data

A data frame with items by row and features in the columns. Must contain one column named "id".

Value

The row info object with all expected columns.

Examples

library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo1", "Foo1", 0.5, 0.7,
  "foo2", "Foo2", 0.5, 0.8,
  "bar1", "Bar1", 1.0, 0.2,
  "bar2", "Bar2", 1.0, 0.1
)
row_info <- tribble(
  ~id, ~group,
  "foo1", "foo",
  "foo2", "foo",
  "bar1", "bar",
  "bar2", "bar"
)
verify_row_info(row_info, data)
library(tibble)
data <- tribble(
  ~id, ~name, ~x, ~y,
  "foo1", "Foo1", 0.5, 0.7,
  "foo2", "Foo2", 0.5, 0.8,
  "bar1", "Bar1", 1.0, 0.2,
  "bar2", "Bar2", 1.0, 0.1
)
row_info <- tribble(
  ~id, ~group,
  "foo1", "foo",
  "foo2", "foo",
  "bar1", "bar",
  "bar2", "bar"
)
verify_row_info(row_info, data)

Package 'funkyheatmap'

Help Index

The results data frame from dynbenchmark.

Description

Usage

Format

References

Generate a funky heatmaps for benchmarks

Description

Usage

Arguments

Value

Examples

Rounded rectangles

Description

Usage

Arguments

Details

Aesthetics

Examples

Defines parameters for positioning in a plot.

Description

Usage

Arguments

Value

Examples

Scale a vector to the range [0, 1]

Description

Usage

Arguments

Value

Examples

Summary results from the scIB project

Description

Usage

Format

References

Verify the integrity of the column groups object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the column info object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the data object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the legends object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the palettes object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the row groups object

Description

Usage

Arguments

Value

Examples

Verify the integrity of the row info object

Description

Usage

Arguments

Value

Examples