`Coulter.CoulterCounterRun`

— TypeA simplified representation of a coulter counter run

`Coulter._find_peaks`

— Method`_find_peaks(xs, ys; minx, miny)`

Finds prominent peaks in `ys`

and returns the values from `xs`

corresponding to the location of these peaks. `minx`

and `miny`

can be used to exclude peaks that are too small in `x`

or `y`

.

`Coulter.diameter`

— Method`diameter(volume)`

Given the `volume`

of a sphere, compute its diameter

`Coulter.extract_peak_interval`

— Method`extract_peak_interval(run; α, n)`

Takes a CoulterCounterRun `run`

and fits a kernel density estimate to smooth out binning effects by the machine and then finds the largest peak. It returns the diameter corresponding to the location of this peak as well as the max and min diameters of the confidence interval defined by `α`

. This interval is generated on the empirically by bootstrapping the data `n`

times.

`Coulter.loadZ2`

— MethodloadZ2(filename, sample)

Loads `filename`

and assigns it to a `sample`

group, returns a `CoulterCounterRun`

object

`Coulter.load_folder`

— Method`load_folder(folder)`

Loads all coulter runs in a folder into a dictionary where the keys are the first parts of the filenames separated by an underscore.

`Coulter.repvec`

— Method`repvec(orig, reps)`

Repeats the items in the first vector by the corresponding number of times in the second vector. Essentially the inverse operation of `hist`

`Coulter.volume`

— Method`volume(diameter)`

Given the `diameter`

of a sphere, return its volume