break.clust: Manually select point clusters from breakage data
In breakage: SICM pipette tip geometry estimation

Description Usage Arguments Details Value Author(s) References See Also Examples

Plots the supplied position-resistance data and allows individual clusters to be selected graphically. A data frame of the median breakage distances and resistances for the selected clusters is returned.

1	break.clust(data, zero.invert = TRUE)

`data`	A data frame including `Z` and `Mohm` columns, as returned by `breakage.plot`.
`zero.invert`	Whether to convert to the `Z` positional data to breakage distance. See Details for more information.

Point clusters are chosen using the Imap select.pts function. A cluster is selected by clicking points around it to draw a polygon. Right-click to close the polygon and define the cluster. To finish selecting, draw a polygon that encloses no points.

The recorded positional information is typically in terms of the piezo used to position the pipette. Model fitting, on the other hand, is done in terms of the breakage distance, i.e. measuring away from the unbroken pipette tip. We can convert from one to the other by taking the most extended surface position as that corresponding to the unbroken tip and substracting subsequent surface positions to determine the length of the broken off region, and this is done by default.

Where data have been collected in more than one pass, with possible positional changes in between, the results from each pass must be aligned together. It may be more convenient to do this in the context of the full position, and then convert to breakage distance afterward.

`Z`	The median position for each cluster, in microns. Values are optionally offset from the maximum tip position, as described above.
`Mohm`	The median resistance for each cluster, in megohms.

Matthew Caldwell

Caldwell, M., Del Linz, S. J. L., Smart, T. G. S. and Moss, G. W. J. 2012 Method for estimating the tip geometry of scanning ion conductance microscope pipets. Anal. Chem. 84(21):8980–8984

breakage.plot, fit.breakage

# load the example data set
data("break.data")

# get the bottom points
raw.points <- breakage.plot( break.data, mV=100 )
## Not run: 
# select the clusters
clustered <- break.clust( raw.points )

## End(Not run)