def preprocess(no_wells_marmousi, no_wells_seam):
"""Function initializes data, performs standardization, and train test split
Parameters:
----------
no_wells_marmousi : int,
number of evenly spaced wells and seismic samples to be evenly sampled
from marmousi section.
no_wells_seam : int
number of evenly spaced wells and seismic samples to be evenly sampled from SEAM
Returns
-------
seismic_marmousi : array_like, shape(num_traces, depth samples)
2-D array containing seismic section for marmousi
seismic_seam : array_like, shape(num_traces, depth samples)
2-D array containing seismic section for SEAM
model_marmousi : array_like, shape(num_wells, depth samples)
2-D array containing model section from marmousi 2
model_seam : array_like, shape(num_wells, depth samples)
2-D array containing model section from SEAM
"""
# get project root directory
project_root = os.getcwd()
if ~os.path.isdir(
'data'): # if data directory does not exists then extract
extract('data.zip', project_root)
# Load data
seismic_marmousi = np.load(join(
'data', 'marmousi_synthetic_seismic.npy')).squeeze()
seismic_seam = np.load(join('data',
'poststack_seam_seismic.npy')).squeeze()[:,
50:]
seismic_seam = seismic_seam[::2, :]
# Load targets and standardize data
model_marmousi = np.load(join('data',
'marmousi_Ip_model.npy')).squeeze()[::5, ::4]
model_seam = np.load(join('data',
'seam_elastic_model.npy'))[::3, :, ::2][:, :,
50:]
model_seam = model_seam[:, 0, :] * model_seam[:, 2, :]
# standardize
seismic_marmousi, model_marmousi = standardize(seismic_marmousi,
model_marmousi,
no_wells_marmousi)
seismic_seam, model_seam = standardize(seismic_seam, model_seam,
no_wells_seam)
return seismic_marmousi, seismic_seam, model_marmousi, model_seam
def preprocess(no_wells, data_flag='seam'):
"""Function initializes data, performs standardization, and train test split
Parameters:
----------
no_wells : int,
number of evenly spaced wells and seismic samples to be evenly sampled
from seismic section.
Returns
-------
seismic : array_like, shape(num_traces, depth samples)
2-D array containing seismic section
model : array_like, shape(num_wells, depth samples)
2-D array containing model section
"""
# get project root directory
project_root = os.getcwd()
if ~os.path.isdir(
'data'): # if data directory does not exists then extract
extract('data.zip', project_root)
if data_flag == 'seam':
# Load data
seismic = np.load(join('data',
'poststack_seam_seismic.npy')).squeeze()[:, 50:]
seismic = seismic[::2, :]
# Load targets and standardize data
model = np.load(join('data',
'seam_elastic_model.npy'))[::3, :, ::2][:, :, 50:]
model = model[:, 0, :] * model[:, 2, :]
else:
# Load data
seismic = np.load(join('data',
'marmousi_synthetic_seismic.npy')).squeeze()
model = np.load(join('data',
'marmousi_Ip_model.npy')).squeeze()[::5, ::4]
# standardize
seismic, model = standardize(seismic, model, no_wells)
return seismic, model