x3p_elemAverage | R Documentation |
x3p_elemAverage() calculate the element-wise average between two surface matrices (of the same dimensions)
x3p_sd() Calculate the standard deviation of x3p surface values
x3p_filter() replace values of a surface matrix based on an element-wise conditional function
x3p_cropWS() Crop rows/columns of missing values around an x3p
x3p_to_dataFrame() Convert an x3p object to a data frame
x3p_delete() replace values in a surface matrix with NA depending on an associated mask.
x3p_elemAverage(x3p1, x3p2)
x3p_sd(..., na.rm = TRUE)
x3p_filter(x3p, cond, replacement = NA, ...)
x3p_cropWS(x3p, croppingThresh = 1)
x3p_to_dataFrame(x3p, preserveResolution = FALSE)
x3p_delete(x3p, mask_vals)
x3p1 |
an x3p object |
x3p2 |
another x3p object |
... |
one or more x3p objects |
na.rm |
logical. Should missing values be removed? |
x3p |
an x3p object |
cond |
a Boolean function whose first argument is 'x'. |
replacement |
value to replace each element for which cond returns FALSE |
croppingThresh |
minimum number of non-NA pixels that need to be in a row/column for it to not be cropped out of the surface matrix |
preserveResolution |
a Boolean dictating whether the scan resolution is preserved in the returned data frame. If FALSE, then the x,y data frame columns will be integer-valued. Otherwise, the difference between consecutive x,y values will be equal to the scan resolution. |
mask_vals |
a hexidecimal color value that corresponds to indices in a mask whose indices are to be replaced in the associated surface |
Transform the values of a x3p surface matrix
data("K013sA1","K013sA2")
# calculates the sd for a single x3p's surface values
x3p_sd(K013sA1)
# calculates the sd for the joint surface values for two x3ps
x3p_sd(K013sA1,K013sA2)
# calculate optimal alignment between the two x3ps
K013sA2_aligned <- cmcR::comparison_allTogether(K013sA1,K013sA2,theta = -3,
returnX3Ps = TRUE,numCells = c(1,1),
maxMissingProp = .99)$alignedTargetCell[[1]]
averaged <- x3p_elemAverage(K013sA1,K013sA2_aligned)
# this will replace values that are larger (in magnitude) than one standard
# deviation of the input x3p's surface values with NA:
filtered1 <- x3p_filter(K013sA1,
cond = function(x,thresh) x < thresh,
thresh = x3p_sd(K013sA1))
# this will replace all surface matrix values between -1 and 1 with 0
filtered2 <- x3p_filter(K013sA1,cond = function(x) abs(x) < 1,replacement = 0)
# exaggerated cropping for the sake of an example
cropped <- x3p_cropWS(K013sA1,croppingThresh = 100)
x3pPlot(K013sA1,K013sA2_aligned,averaged,filtered1,filtered2,cropped,
x3pNames = c("K01sA1","K013sA2 Aligned","Averaged","Filtered1","Filtered2","Cropped"))
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