runBatch: Batch analysis

Description

runBatch analyzes all image sequences in a specified directory. Use this function when settings have been optimized previously on a single or selection of movies/image sequences.

Usage

runBatch(
  path,
  settings = NULL,
  dirnames = NULL,
  nImages = 1:30,
  pixelRange = NULL,
  threshold = -0.1,
  qthreshold = NULL,
  select = "dark",
  nn = NULL,
  incThres = NULL,
  plotOutput = FALSE,
  plotType = "trajectories",
  L = 20,
  R = 2,
  weight = c(1, 1, 1),
  autoThres = FALSE,
  perFrame = FALSE,
  methodBg = "mean",
  frames = NULL,
  saveAll = FALSE
)

Value

Dataframe with estimated population size for each image sequence.

Arguments

path: A character vector of path name that contains all directories with image sequences.
settings: Object of class 'tracked' containing all optimized settings in attributes, as obtained from trackParticles. Alternatively, settings can be specified using arguments described below.
dirnames: If not all image sequences should be analyzed, specify which files to use as a character string.
nImages: See loadImages
pixelRange: See identifyParticles
threshold: See identifyParticles
qthreshold: See identifyParticles
select: See identifyParticles
nn: Name of artificial neural net if apply it to images. Default is NULL, resulting in no neural net being applied.
incThres: Minimum number of frames that a particle must be present. By default, automated estimate is used.
plotOutput: Default is FALSE. Set TRUE to plot results.
plotType: Default is 'trajectories'. Other options are 'sizes' and 'animation'.
L: See trackParticles
R: See trackParticles
weight: See trackParticles
autoThres: See identifyParticles
perFrame: See identifyParticles
methodBg: See createBackground
frames: See identifyParticles
saveAll: Logical. Set TRUE to save for each image sequence the full object obtained from loadImages. Default is FALSE.

Author

Marjolein Bruijning, Caspar A. Hallmann & Marco D. Visser

Examples

Run this code

if (FALSE) {
## Simulate 3 image sequences
wd <- getwd()
folders <- paste0(rep("images",3),1:3)
populations <- c(15,25,50)
dir.create("./batchTest")
setwd("./batchTest")
for(i in 1:length(folders)){
  dir.create(folders[i])
  traj <- simulTrajec(path=folders[i],
                      nframes=30,nIndividuals=populations[i],
                      h=0.01,rho=0.9,
                      sizes=runif(populations[i],0.004,0.006))
}
setwd(wd)
batchpath <- "./batchTest"
results <- runBatch(path=batchpath,
                    nImages=1:30,threshold=-0.1,select='dark',
                    pixelRange=c(1,100),L=50,R=3,
                    incThres=10)
results
}