import numpy as np
from scipy.ndimage import label


def generate_test_vecs(infile, strelfile, resultfile):
    "test label with different structuring element neighborhoods"
    def bitimage(l):
        return np.array([[c for c in s] for s in l]) == '1'
    data = [np.ones((7, 7)),
            bitimage(["1110111",
                      "1100011",
                      "1010101",
                      "0001000",
                      "1010101",
                      "1100011",
                      "1110111"]),
            bitimage(["1011101",
                      "0001000",
                      "1001001",
                      "1111111",
                      "1001001",
                      "0001000",
                      "1011101"])]
    strels = [np.ones((3, 3)),
              np.zeros((3, 3)),
              bitimage(["010", "111", "010"]),
              bitimage(["101", "010", "101"]),
              bitimage(["100", "010", "001"]),
              bitimage(["000", "111", "000"]),
              bitimage(["110", "010", "011"]),
              bitimage(["110", "111", "011"])]
    strels = strels + [np.flipud(s) for s in strels]
    strels = strels + [np.rot90(s) for s in strels]
    strels = [np.fromstring(s, dtype=np.int).reshape((3, 3))
              for s in set(t.astype(np.int).tostring() for t in strels)]
    inputs = np.vstack(data)
    results = np.vstack([label(d, s)[0] for d in data for s in strels])
    strels = np.vstack(strels)
    np.savetxt(infile, inputs, fmt="%d")
    np.savetxt(strelfile, strels, fmt="%d")
    np.savetxt(resultfile, results, fmt="%d")

generate_test_vecs("label_inputs.txt", "label_strels.txt", "label_results.txt")
