Description Usage Arguments Details Value See Also
The cc_number_ts_img
and cc_brightness_ts_img
classes are designed to
hold objects which are images calculated from the cross-correlated number
and brightness technique.
1 2 3 | cc_number_ts_img(img, frames_per_set, overlapped, thresh, swaps, filt)
cc_brightness_ts_img(img, frames_per_set, overlapped, thresh, swaps, filt)
|
img |
The calculated cross-correlated number or brightness time series image series. |
frames_per_set |
The number of frames used in the calculation of each point in the cross-correlated number or brightness time series. |
overlapped |
A boolean. |
thresh |
A positive integer, possibly an object of class autothresholdr::th. If the different channels of the image had different thresholds, this argument may be specified as a vector or list (of positive integers, possibly objects of class autothresholdr::th), one element for each channel. |
swaps |
A non-negative integer with an attribute |
filt |
A string, the filtering method used. Must be either |
An object of class cc_number_ts_img
or cc_brightness_ts_img
is a
4-dimensional array of real numbers in the mould of an
ijtiff_img with 3 attributes:
thresh
A positive integer, possibly an object of class autothresholdr::th detailing which threshold and thresholding method was used in preprocessing (in the multi-channel case, one threshold per channel is given).
swaps
A non-negative integer indicating the parameter
used for Robin Hood detrending with an attribute auto
which is a logical
indicating whether or not the parameter was chosen automatically (in the
multi-channel case, one swaps
per channel is given).
frames_per_set
A positive integer detailing how many frames were used in the calculation of each point in the number or brightness time series.
overlapped
A boolean. TRUE
indicates that the windows
used to calculate consecutive brightnesses over time were overlapped, FALSE
indicates that they were not.
An object of class cc_number_ts_img
or cc_brightness_ts_img
.
cc_number_timeseries()
, cc_brightness_timeseries()
.
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