import NamedMatrix

import NamedMatrixHDF5

import sys

import numpy as np

import snpdecomp as snp

from rpy2.robjects import r

import rpy2.robjects as ro

import rpy2.robjects.numpy2ri

import rpy2.rpy_classic as rpy

import h5py

try:

filename = sys.argv[1]

projectname = sys.argv[2]

except Exception:

print "USAGE:\npython rundecomp.py matrixfile projectname"

print "Filename: " + filename + "\nProject: " + projectname

mat = NamedMatrix.readfromfile(filename,nullvalue="-1",header=True, rownames=True,separator='\t',skip=0)

NamedMatrixHDF5.writeNamedMatrix(mat, projectname, "/freqs",overwrite=True)

sigfn = lambda x: str(",".join(map(lambda y: str(y), (x != float('inf'))*1)))

setnames = np.apply_along_axis(sigfn,1,mat.matrix)

unq_subs = np.unique(setnames)

colfn = lambda x: np.array(map(lambda y: y!=str(0), x.split(",")))

cols = map(colfn,unq_subs)

h5 = h5py.File(projectname)

h5.create_group("subsets")

hndl = h5["/subsets"]

hndl.create_dataset("names",data=unq_subs)

hndl.create_dataset("columns",data=cols)

r('''

runPCA_sub <- function(sname, matr, setnames) {

subs = which(setnames==sname)

submat = matr[subs,]

if (length(subs)==1){

return(0)

}

cols = which(is.finite(submat[1,]))

submat = submat[,cols]

pcs = prcomp(t(submat))

pctile = apply(pcs$rotation,2,function(x){rank(abs(x),ties.method="first")})/length(subs)

scaled = t(apply(pctile,1,function(x){x*pcs$sdev}))

sdevscore = apply(pcs$rotation,1,sd)

pcs[["rankscore"]]=scaled

pcs[["sdevscore"]]=sdevscore

pcs[["rownums"]]=subs

return(pcs)

}

''')

runpcasub = r['runPCA_sub']

h5.create_group("pca")

hndl = h5["/pca"]

for i,s in enumerate(unq_subs):

if np.sum(cols[i])<=1:

print "unsavory: " + s

continue

pca = runpcasub(s, mat.matrix, setnames)

if pca[0] == 0:

print "useless: " + s

continue

try:

hndl.create_group(s)

shndl=hndl[s]

shndl.create_dataset("sdev",data=pca[0])

shndl.create_dataset("loadings",data=pca[1])

shndl.create_dataset("center",data=pca[2])

shndl.create_dataset("scale",data=pca[3])

shndl.create_dataset("components",data=pca[4])

shndl.create_dataset("rankscore",data=pca[5])

shndl.create_dataset("sdevscore",data=pca[6])

shndl.create_dataset("rownums",data=pca[7])

except:

print pca

print s

h5.close()