valid_roket_files.py

import h5py
import numpy as np
import glob
 
 
def validfile(filename):
    f = h5py.File(filename)
    if (list(f.attrs.keys()).count("target.Lambda")):
        Lambda = f.attrs["target.Lambda"][0]
    else:
        Lambda = 1.65
    nactus = f["noise"][:].shape[0]
    niter = f["noise"][:].shape[1]
    P = f["P"][:]
    nmodes = P.shape[0]
    data = np.zeros((nmodes, niter))
    error_list = [
            "noise", "aliasing", "tomography", "filtered modes", "bandwidth",
            "non linearity"
    ]
 
    for i in error_list:
        data += np.dot(P, f[i][:])
 
    data = np.var(data, axis=1)
    data = np.sum(data)
    data = np.exp(-data * (2 * np.pi / Lambda)**2)
    data *= np.exp(-f["fitting"].value)
 
    SR2 = f["SR2"].value
    SR = f["SR"].value
 
    if (np.abs(data - SR) < 0.05 or np.abs(data - SR2) < 0.05):
        f.attrs["validity"] = True
 
 
datapath = "/home/fferreira/Data/correlation/"
filenames = glob.glob(datapath + "roket_8m*.h5")
l = len(filenames)
ind = 0
for f in filenames:
    validfile(f)
    ind += 1
    print(" reading : %d/%d\r" % (ind, l), end=' ')
print("read")