inst/doc/neurobase.R

In neurobase: 'Neuroconductor' Base Package with Helper Functions for 'nifti' Objects

## ----setup, include=FALSE-----------------------------------------------------
library(neurobase)
library(oro.nifti)
knitr::opts_chunk$set(echo = TRUE)

## ----nifti_obj----------------------------------------------------------------
library(oro.nifti)
set.seed(20161007)
dims = rep(10, 3)
arr = array(rnorm(10*10*10), dim = dims)
nim = oro.nifti::nifti(arr)
print(nim)
print(class(nim))
oro.nifti::is.nifti(nim)

## ----nifti_slot---------------------------------------------------------------
nim@cal_max
cal_max(nim)
slot(nim, "cal_max")

## ----nifti_data---------------------------------------------------------------
data = slot(nim, ".Data")
class(data)

## ----nifti_data2--------------------------------------------------------------
data = oro.nifti::img_data(nim)
class(data)
dim(data)

## ----nifti_slice--------------------------------------------------------------
slice = data[,,3]
class(slice)

## ----nifti_arr_slice----------------------------------------------------------
slice = data[,,3, drop = FALSE]
class(slice)

## ----slotnames----------------------------------------------------------------
slotNames(nim)

## ----logical------------------------------------------------------------------
above_zero = nim > 0
class(above_zero)
img_data(above_zero)[1]

## ----multi_log----------------------------------------------------------------
class(nim > 0 & nim < 2)

## -----------------------------------------------------------------------------
class(nim * 2)
class(nim + (nim / 4))
class(nim * nim)
class(nim^2)

## ----sum----------------------------------------------------------------------
sum(above_zero)

## ----mean---------------------------------------------------------------------
mean(above_zero)

## ----summs--------------------------------------------------------------------
min(nim)
max(nim)
range(nim)
class(abs(nim))

## ----eve, cache=FALSE---------------------------------------------------------
fname = system.file(
  file.path("nifti", "mniRL.nii.gz"),
  package = "oro.nifti")
eve = readnii(fname)

## ----ortho--------------------------------------------------------------------
oro.nifti::orthographic(eve)

## ----ortho2-------------------------------------------------------------------
neurobase::ortho2(eve)

## ----ortho2_noorient----------------------------------------------------------
neurobase::ortho2(eve, add.orient = FALSE)

## ----ortho_nona---------------------------------------------------------------
orthographic(eve, y = eve > quantile(eve, 0.9))

## ----ortho2_nona--------------------------------------------------------------
ortho2(eve, y = eve > quantile(eve, 0.9))

## ----eve2, cache=FALSE--------------------------------------------------------
eve2 = eve
eve2[which.max(eve)] = eve2[which.max(eve)] * 5

## ----ortho2_large-------------------------------------------------------------
ortho2(eve2)

## ----ortho2_rob---------------------------------------------------------------
ortho2(robust_window(eve2))

## ----ortho2_zlim--------------------------------------------------------------
ortho2(eve2, zlim = quantile(eve2, probs = c(0, 0.999)))

## ----eve_left-----------------------------------------------------------------
flipped_fname = system.file(
  file.path("nifti", "mniLR.nii.gz"),
  package = "oro.nifti")
flipped_eve = readnii(flipped_fname)

## ----double_ortho-------------------------------------------------------------
double_ortho(flipped_eve, eve)

## ----all_slices---------------------------------------------------------------
image(eve, z = 45)

## ----one_slice----------------------------------------------------------------
image(eve, z = 45, plot.type = "single")

## ----two_slice----------------------------------------------------------------
image(eve, z = c(45, 50), plot.type = "single")

## ----one_slice_sag------------------------------------------------------------
image(eve, z = 52, plot.type = "single", plane = "sagittal")

## ----one_slice_overlay--------------------------------------------------------
overlay(eve, y = eve > quantile(eve, 0.9), z = 45, plot.type = "single")

## ----one_slice_overlay_right--------------------------------------------------
mask = eve > quantile(eve, 0.9)
mask[ mask == 0] = NA
overlay(eve, y = mask, z = 45, plot.type = "single")
rm(list = "mask")

## ----dd, cache=FALSE----------------------------------------------------------
reduced = dropEmptyImageDimensions(eve)
dim(eve)
dim(reduced)

## ----plot_red-----------------------------------------------------------------
ortho2(reduced)

## ----plot_full_eve------------------------------------------------------------
ortho2(eve)

## ----replace_empty------------------------------------------------------------
dd = dropEmptyImageDimensions(eve, keep_ind = TRUE)
reduced = dd$outimg
reversed = replace_dropped_dimensions(img = reduced, 
                                      inds = dd$inds,
                                      orig.dim = dd$orig.dim)
all(reversed == eve)

## ----nim, cache = FALSE-------------------------------------------------------
dims = dim(eve)
arr = array(rnorm(prod(dims)), dim = dims)
nim = nifti(arr)
nim

## ----copyniftiheader, cache = FALSE-------------------------------------------
nim = copyNIfTIHeader(img = eve, arr = nim)
nim

## ----zeroes, cache=FALSE------------------------------------------------------
zeroes = niftiarr(eve, 0)

## ----masking------------------------------------------------------------------
eve_masked = mask_img(eve, eve > mean(eve))

## ----plot_mask----------------------------------------------------------------
ortho2(eve_masked)

## ----vec, cache=FALSE---------------------------------------------------------
vals = c(eve)
class(vals)

## ----dens---------------------------------------------------------------------
plot(density(vals))

## ----masking_2, cache=FALSE---------------------------------------------------
vals = eve[ eve > 0 ]
mean(vals)
mean(eve)

## ----na_eve-------------------------------------------------------------------
mask = eve > 0
mask[ mask == 0 ] = NA
eve_masked = mask_img(eve, mask)
mean(eve_masked)
mean(eve_masked, na.rm = TRUE)

## ----masking_3----------------------------------------------------------------
vals = eve[ eve > 0 ]

## ----dens_2-------------------------------------------------------------------
plot(density(vals))

## ----dens_with_mask-----------------------------------------------------------
plot(density(eve, mask = eve > 0))