Quick answer:
arrays = []
for line in open(your_file): # no need to use readlines if you don't want to store them
# use a list comprehension to build your array on the fly
new_array = np.array((array.float(i) for i in line.split(' ')))
arrays.append(new_array)
If you process often this kind of data, the csv module will help.
import csv
arrays = []
# declare the format of you csv file and Python will turn line into
# lists for you
parser = csv.reader(open(your_file), delimiter=' '))
for l in parser:
arrays.append(np.array((array.float(i) for i in l)))
If you feel wild, you can even make this completly declarative:
import csv
parser = csv.reader(open(your_file), delimiter=' '))
make_array = lambda row : np.array((array.float(i) for i in row))
arrays = [make_array(row) for row in parser]
And if you realy want you colleagues to hate you, you can make a one liner (NOT PYTHONIC AT ALL :-):
arrays = [np.array((array.float(i) for i in r)) for r in csv.reader(open(your_file), delimiter=' '))]
Stripping all the boiler plate and flexibility, you can end up with a clean and quite readable one liner. I wouldn't use it because I like the refatoring potential of using csv
, but it can be good enought. It's a grey zone here, so I wouldn't say it's Pythonic, but it's definitly handy.
arrays = [np.array((array.float(i) for i in l.split())) for l in open(your_file))]
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