Contingency matrix with columns of only 0s

[Jorge-C]

Current CCA code fails if the contingency matrix has any column with no observations, but vegan's R doesn't.

However, in R both sol and sol2 have the same results (Yval has a few columns with no observations):

library(vegan)
X <- read.table('Xval')
Y <- read.table('Yval')

nonzero <- apply(Y, 2, sum) != 0

sol <- cca(Y[, nonzero], X)
sol2 <- cca(Y, X)

and they match the current python implementation

from ordination import CCA
import numpy as np

X = np.loadtxt('Xval')
Y = np.loadtxt('Yval')

nonzero = Y.sum(axis=0) != 0

sol = CCA(Y[:, nonzero], X)

Maybe we can just remove those columns in __init__ and be careful with names (warning the user "hey, {n_cols} of the contingency matrix had no observations, they were dropped in the analysis.")

[Jorge-C]

Also, test what happens in RDA/CA with same kind of data, and compare to vegan.