from sigvisa.learn.train_coda_models import get_shape_training_data
import numpy as np

X, y, evids = get_shape_training_data(runid=4, site="AS12", chan="SHZ", band="freq_2.0_3.0", phases=["P",], target="amp_transfer", max_acost=np.float("inf"), min_amp=-2)
np.savetxt("X.txt", X)
np.savetxt("y.txt", y)
np.savetxt("evids.txt", evids)

[((258, 280), 'numpy.savetxt', 'np.savetxt', (['"""X.txt"""', 'X'], {}), "('X.txt', X)\n", (268, 280), True, 'import numpy as np\n'), ((281, 303), 'numpy.savetxt', 'np.savetxt', (['"""y.txt"""', 'y'], {}), "('y.txt', y)\n", (291, 303), True, 'import numpy as np\n'), ((304, 334), 'numpy.savetxt', 'np.savetxt', (['"""evids.txt"""', 'evids'], {}), "('evids.txt', evids)\n", (314, 334), True, 'import numpy as np\n'), ((229, 244), 'numpy.float', 'np.float', (['"""inf"""'], {}), "('inf')\n", (237, 244), True, 'import numpy as np\n')]