visumot_frame: visumot_frame
In grrchrr/VisumotR: Visualizing Motility on Images

Description Usage Arguments Details Value Examples

View source: R/visumot_frame.R

With visumot_frame, continous and discrete parameters can be mapped individually on color, shape and size for one timepoint.

1	visumot_frame(df, ...)

`df`	dataframe of the form: `df(track, time, X, Y, (Z,) mapping_parameters, ...)`
`image`	`character`: filename of image
`stack`	`logical`: default: `FALSE`, single image file provided if time-resolved imagestack is used, set: `TRUE`
`image.depth`	`numeric`: set image bit-depth; just important if Z-projections are calculated
`image.normalize`	`logical`: normalize image
`frame`	`integer`: frame to be mapped
`tracks`	`vector`: defining tracks to be displayed
`par.map`	`character`: specifying parameter in `df` to be visualized by color
`par.shape`	`character`: specifying parameter in `df` to be mapped on shape
`par.display`	display option for mapping; default: `TRUE`, mapping is disable with: `FALSE`
`par.max`	`numeric`: defining upper range of color mapping
`par.min`	`numeric`: defining lower range of color mapping
`par.unit`	`character`: unit of the numeric mapped parameter
`crop`	`logical`: option for cropping images; default: `FALSE`
`sub.img`	`logical`: option for creating sub-images from specified `tracks` or pre-filtered `df`; default: `FALSE`
`sub.window`	`numeric`: size of the sub-images in pixels
`sub.col`	`numeric`: number of columns in which sub-images are arranged
`tracks.size`	`numeric`: size of tracks
`tracks.alpha`	`numeric`: transparency of tracks
`tracks.length`	`numeric`: length of tracks (in frames)
`tracks.label`	`logical`: when sub.img is used, display or hide track label
`tracks.label.x`	`numeric`: when sub.img is used, set x-position of label
`tracks.label.y`	`numeric`: when sub.img is used, set y-position of label
`points.size`	`numeric`: size of points
`points.alpha`	`numeric`: transparency of points
`points.stat`	`character`: display statistic; default: `'echo'`, for blurring; without blurring `'identity'`
`points.shape`	`numeric`: set shape from ggplot2 shape palette
`axis.tick`	`numeric`: axis ticks in px
`axis.display`	`logical`: display axis
`axis.labs`	`logical`: display labs
`unit`	`character`: setting name of unit; default: `'px'`
`scaling`	`numeric`: scaling factor for unit; default: `1`
`dimensions`	`numeric`: specify whether the images are 2D or 3D. If 3D is selected the data is assumed to be in the form: `df(track, time, X, Y, Z, mapping paramters, ...)`
`manual.z`	`numerice`: specify Z-plane to be visualized if no projection or sub windows are used
`scale.bar`	`logical`: show scalebar; default: `FALSE`
`scale.width`	`numeric`: width of scalebar; default: `40`
`scale.height`	`numeric`: height of scalebar; default: `10`
`scale.x`	`numeric`: distance from left border of the image towards scalebar
`scale.y`	`numeric`: distance from bottom border of the image towards scalebar
`scale.color`	`character`: specify color from R-color palette or hexcode
`interactive`	`logical`: return the plot as an interactive plotly object. Not supported when using sub.img or crop modes.

To be written...

returns a ggplot2 plot-object which can be further modified

# import tracking data
df <- read.csv('hiv_tracking.csv')
# get image files
images <- list.files(pattern='.tif')
# run visumot_frame with default settings
visumot_frame(df, image=images[1], frame=1) 
# run visumot_frame with specified settings
visumot_frame(df,
 image= images[1],
 frame = 1,
 tracks = c(34, 125, 199, 205),
 scale.bar = TRUE, 
 scale.bar.color = 'red',
 par.map='speed',
 par.shape='contact'
 )