def read_data_files(pattern): files = glob.glob(pattern) if not files: raise ValueError("cannot find any matching files: " % pattern) keys, times = zip(*[stats.read_raw_data(fname) for fname in files]) validate_keys(keys) means = np.mean(times, axis=0) variances = np.var(times, axis=0) return Data(keys[0], np.array(times), means, variances)
def read_data_files(pattern): files = glob.glob(pattern) # print "processing {} file(s)".format(len(files)) if not files: raise ValueError("cannot find any matching files: %s" % pattern) keys, times = zip(*[stats.read_raw_data(fname) for fname in files]) for idx, i in enumerate(keys): if keys[0] != i: print files[idx] raise ValueError("inconsistent data files") means = np.mean(times, axis=0) variances = np.var(times, axis=0) return Data(keys[0], np.array(times), means, variances)