The ipyrad plotting library has a number of basic function written with the Python module Toyplot. For each of these I will demonstrate a simple usage of the available function, as well as how to access the raw data in case you want to create your own plotting functions using Python or R. An important note about using the ipyrad plotting functions is that they have to be loaded from a separate module, like below.
## import ipyrad and the ipyrad plotting library
import ipyrad as ip
import ipyrad.plotting as ippSequencing depth varies greatly among RAD-seq data sets depending on the library construction method and the sequencing effort, and it can vary across samples as well. Any Samples that have completed step 3 of an ipyrad assembly will have depth information available which we can access through the API to analyze and visualize.
depthplot
describe the positional arguments to depthplot here...
## load the assembly that is passed step 3
data1 = ip.load_json("tests/data1.json")
## this example has 12 Samples
data1.samples
## let's look at the depth data for Sample '1A_0'
data1.samples["1A_0"].depths
## the data are stored as a numpy array, so there are many
## different operations you can perform to analyze it.
data1.samples["1A_0"].depths.mean()
## using these data you can a create plots using any plotting library.
## We provide a simple create a plot, see cookbook for further options to depthplot
canvas = ipp.depthplot(data1, ...)
## save the plot as a pdf
canvas.render_pdf("depthfig.pdf")