Searching rectangular tissue samples

This method searches a set of rectangular tissue samples.

Arguments

min_num_of_cells

A named integer vector reporting the minimum number of cells per species or mutant.

num_of_cells

The number of cells in the searched sample.

width

The width of the searched sample.

height

The height of the searched sample.

n_samples

The number of searched samples.

seed

The seed of the random generator the select the samples among those satisfying the constraints (optional).

Value

A vector of n_samples rectangular tissue samples that satisfy the aimed constraints.

Details

The aimed samples mush satisfy the specified number of cells. The sizes of the samples are also provided a parameter of the method. This method takes asymptotic time \(\Theta(|\textrm{tissue width}|*|\textrm{tissue height}|)\).

See also

Simulation

Examples

# set the seed of the random number generator
set.seed(0)

# create a simulation
sim <- SpatialSimulation()
sim$death_activation_level <- 50
sim$add_mutant(name = "A", growth_rate = 0.2, death_rate = 0.01)
sim$place_cell("A", 500, 500)
sim$run_up_to_size(species = "A", num_of_cells = 50)
#> 
 [████████████████████████████████████████] 100% [00m:00s] Saving snapshot                                        


sim$add_mutant(name = "B", growth_rate = 0.3, death_rate = 0.01)
sim$mutate_progeny(sim$choose_cell_in("A"), "B")
sim$run_up_to_size(species = "B", num_of_cells = 40000)
#> 
 [█████████████████████████---------------] 61% [00m:00s] Cells: 59386                                            

 [████████████████████████████████████████] 100% [00m:00s] Saving snapshot                                        


plot <- plot_tissue(sim, num_of_bins = 1000)

# find 3 50x50 samples containing 80 "B" cells and 100 "A" cells
# at least
bboxes <- sim$search_samples(c("A" = 100, "B" = 80), 50, 50,
                             n_samples=3)
bboxes
#> [[1]]
#> TissueRectangle((452,470),(501,519))
#> 
#> [[2]]
#> TissueRectangle((402,520),(451,569))
#> 
#> [[3]]
#> TissueRectangle((452,420),(501,469))
#> 

# plot the bbox of the found samples
for (bbox in bboxes) {
  plot <- plot +
    ggplot2::geom_rect(xmin = bbox$lower_corner[1],
                       xmax = bbox$upper_corner[1],
                       ymin = bbox$lower_corner[2],
                       ymax = bbox$upper_corner[2],
                       fill = NA, color = "black")
}

plot