Description Usage Arguments Details Value Examples

View source: R/volumetric.R View source: R/plot.R

The function plots ‘embryo2d’ object in different ways: (1) 2d color levelplot of intesities, (2) 3d plot of intensities and (3) 1d plots of sections along coordinate (AP or DV) directions.

1 2 3 4 5 |

`x` |
object of class ‘embryo2d’ |

`type` |
plot type (see Details) |

`...` |
further arguments passed to plotting function |

A lot of drawing methods, 1d, 2d, 3d, for regular grid and for orginal nuclear centers. Type variants:

- nuclei-2d
is 2d nuclei plot. One point for one nucleus. Also one can pass the following arguments:

`voronoi`

— logical whether plot Voronoi diagram for nuclei, 'TRUE' by default;`col`

— argument for`colorRampPalette`

, this pallete used for Voronoi diagram, color intensity corresponds to nuclei intensity value, greyscale pallete by default- field-2d
is Lattice levelplot for intensity regularization. Argument

`col`

defines color palette (see previous item)- field-section
is Lattice xyplot for of section for intensities in regular grid. Additional arguments:

`at`

,`units`

— units for`at`

('percent' or 'original'),`coord`

— 'x' or 'y', 'y' by default- nuclei-section
is Lattice xyplot of section for intensities in nucleus. Additional arguments:

`at`

,`units`

,`coord`

— see previous item,`tolerance`

— is the half-width of the strip around the section position- field-3d
is 3d rgl plot, nuclei are depicted by colored spheres, color intensity corresponds to nuclei intensity value. Additional argument

`col`

— character vector of two values, denotes colors for the lowest and the highest intensities correspondingly- nuclei-3d
is 3d rgl surface plot, values in regular grid are depicted, color intensity corresponds to nuclei intensity value. Additional argument

`col`

— see previous item

Other parameters are passed to plot functions.

‘trellis’ object (see lattice) for 2d plots, a vector of object IDs for 3d plots.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | ```
xlim <- c(22, 88)
ylim <- c(32, 68)
L <- c(15, 15)
good <- 3
file <- system.file("extdata/data", "ab16.txt", package = "BioSSA")
df <- read.emb.data(file)
bss <- BioSSA(cad ~ AP + DV, data = df,
L = L,
step = 0.5,
xlim = xlim, ylim = ylim)
# Reconstruction of elementary components
rec.elem <- reconstruct(bss, groups = 1:6)
plot(plot(rec.elem))
# Sections for testing the reconstruction quality
rec <- reconstruct(bss, groups = list(good = 1:good))
p.ny <- plot(attr(rec, "series"), type = "nuclei-section", at = 50, coord = "y", tol = 5)
p.fy2 <- plot(rec$good, type = "field-section", at = 50, coord = "y")
# y-sections
pls <- list()
pls[[1]] <- p.ny + p.fy2
pls[[2]] <- plot(residuals(bss, 1:good), type = "nuclei-section",
at = 50, coord = "y", tol = 5,
ref = TRUE, col = "blue")
print(pls[[1]], split = c(1, 1, 2, 1), more = TRUE)
print(pls[[2]], split = c(2, 1, 2, 1))
# Dependence of noise on trend
plot(bss, type = "residuals", model = "multiplicative", groups = 1:good)
# 3d-figure of reconstruction
plot(rec$good, type = "nuclei-3d", col = c("blue", "red"))
# 2d-figures with triangulation
plot(rec$good, type = "nuclei-2d")
``` |

BioSSA/BioSSA documentation built on Dec. 28, 2017, 9:27 p.m.

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