lb.append(x)
del buf
return lb
outputs = ['ex1', 'ex1a', 'ex2', 'ex3', 'ex4', 'ex5', 'ex6']
# load data
fnms = ['neg.csv', 'pos.csv']
for dirnm in outputs:
read = []
path = "./" + dirnm + "/"
for x in fnms:
read.append( lcsv(path + x, delim = ',', quote = '"', blank_str = 'Blank', qc_str = None, sample_str = 'Sample') )
neg = read[0]
pos = read[1]
lab = load_labels(path + 'labels.dat')
np.savez_compressed(path+dirnm, negmz = neg[0], posmz = pos[0],
negrt = neg[1], posrt = pos[1],
negbl = neg[2], posbl = pos[2],
negsp = neg[4], possp = pos[4],
label = lab)
exit()
# construct appropriate input
mza = 100.
rootdir = "./data/peak_tables/"
dirnms = [x[0] for x in os.walk(rootdir)]
dirnms = filter(lambda x: "batch" in x, dirnms)
dirnms.sort()
read = []
for curdir in dirnms:
fnms = os.listdir(curdir)
fnms.sort()
fnms = filter(lambda x: x.endswith(".csv"), fnms)
fnms = filter(lambda x: x != "sample_batch.csv", fnms)
part_read = []
for x in fnms:
part_read.append(lcsv(curdir + "/" + x))
print x
read.append(part_read)
# construct appropriate input
exp_file = "./data/sample_batch.csv"
# meaningful_interval =
# 1 26
# 1 26
# blank, flav, trial = loadpar(exp_file)
# exit()