def test_b(self, theano_f):
"""
Two layers a bit curvy, drift degree 1
"""
data_interp = theano_f[0]
compiled_f = theano_f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_b/test_b_Foliations.csv",
path_i="./GeoModeller/test_b/test_b_Points.csv")
# DEP
# rescaled_data = gempy.rescale_data(geo_data)
#
# data_interp.interpolator._data_scaled = rescaled_data
# data_interp.interpolator._grid_scaled = rescaled_data.grid
# data_interp.interpolator.order_table()
# data_interp.interpolator.set_theano_shared_parameteres()
#
# # Prepare the input data (interfaces, foliations data) to call the theano function.
# # Also set a few theano shared variables with the len of formations series and so on
# input_data_P = data_interp.interpolator.data_prep(u_grade=[3])
#
# sol = compiled_f(input_data_P[0], input_data_P[1], input_data_P[2], input_data_P[3], input_data_P[4],
# input_data_P[5])
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3])
sol = compiled_f(*i)
real_sol = np.load('test_b_sol.npy')
np.testing.assert_array_almost_equal(sol[:, :2, :], real_sol, decimal=3)
def theano_f(self):
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_a/test_a_Foliations.csv",
path_i="./GeoModeller/test_a/test_a_Points.csv")
# data_interp = gempy.set_interpolator(geo_data,
# dtype="float64",
# verbose=['solve_kriging'])
# Set all the theano shared parameters and return the symbolic variables (the input of the theano function)
#input_data_T = data_interp.interpolator.tg.input_parameters_list()
# Prepare the input data (interfaces, foliations data) to call the theano function.
# Also set a few theano shared variables with the len of formations series and so on
# input_data_P = data_interp.interpolator.data_prep(u_grade=[3])
# Compile the theano function.
# compiled_f = theano.function(input_data_T, data_interp.interpolator.tg.whole_block_model(),
# allow_input_downcast=True, profile=True)
data_interp = gempy.InterpolatorInput(geo_data, dtype='float64')
compiled_f = data_interp.compile_th_fn()
return data_interp, compiled_f
def test_a(self, theano_f):
"""
2 Horizontal layers with drift one
"""
data_interp = theano_f[0]
compiled_f = theano_f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_a/test_a_Foliations.csv",
path_i="./GeoModeller/test_a/test_a_Points.csv")
# rescaled_data = gempy.rescale_data(geo_data)
#
# data_interp.interpolator._data_scaled = rescaled_data
# data_interp.interpolator._grid_scaled = rescaled_data.grid
# data_interp.interpolator.order_table()
# data_interp.interpolator.set_theano_shared_parameteres()
#
# # Prepare the input data (interfaces, foliations data) to call the theano function.
# # Also set a few theano shared variables with the len of formations series and so on
# input_data_P = data_interp.interpolator.data_prep(u_grade=[3])
# # Compile the theano function.
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3])
sol = compiled_f(*i)
real_sol = np.load('test_a_sol.npy')
np.testing.assert_array_almost_equal(sol[:, :2, :], real_sol, decimal=3)
gempy.plot_section(geo_data, 25, block=sol[0, 0, :], direction='y', plot_data=True)
gempy.plot_potential_field(geo_data, sol[0, 1, :], 25)
def test_e(self, theano_f_1f):
"""
Two layers a bit curvy, 1 fault
"""
data_interp = theano_f_1f[0]
compiled_f = theano_f_1f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_e/test_e_Foliations.csv",
path_i="./GeoModeller/test_e/test_e_Points.csv")
gempy.set_series(geo_data, {'series': ('A', 'B'),
'fault1': 'f1'}, order_series=['fault1', 'series'])
geo_data.n_faults = 1
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3, 3])
sol = compiled_f(*i)
# print(data_interp.rescale_factor, 'rescale')
real_sol = np.load('test_e_sol.npy')
np.testing.assert_array_almost_equal(sol[:, :2, :], real_sol, decimal=3)
def test_f(self, theano_f_1f):
"""
Two layers a bit curvy, 1 fault
"""
data_interp = theano_f_1f[0]
compiled_f = theano_f_1f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data(
[0, 2000, 0, 2000, -2000, 0], [50, 50, 50],
path_f="./GeoModeller/test_f/test_f_Foliations.csv",
path_i="./GeoModeller/test_f/test_f_Points.csv")
geo_data.set_formation_number(geo_data.formations[[3, 2, 1, 0, 4]])
gempy.set_data_series(geo_data, {
'series':
('Reservoir', 'Seal', 'SecondaryReservoir', 'NonReservoirDeep'),
'fault1':
'MainFault'
},
order_series=['fault1', 'series'])
# rescaled_data = gempy.rescale_data(geo_data)
# # data_interp = gempy.set_interpolator(geo_data, dtype="float64", )
# data_interp.interpolator._data_scaled = rescaled_data
# data_interp.interpolator._grid_scaled = rescaled_data.grid
# data_interp.interpolator.order_table()
# data_interp.interpolator.set_theano_shared_parameteres()
#
# # Prepare the input data (interfaces, foliations data) to call the theano function.
# # Also set a few theano shared variables with the len of formations series and so on
# input_data_P = data_interp.interpolator.data_prep(u_grade=[3, 3])
#
# data_interp.interpolator.get_kriging_parameters()
#
# sol = compiled_f(input_data_P[0], input_data_P[1], input_data_P[2], input_data_P[3], input_data_P[4],
# input_data_P[5])
# # print(data_interp.rescale_factor, 'rescale')
geo_data.n_faults = 1
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3, 3])
sol = compiled_f(*i)
real_sol = np.load('test_f_sol.npy')
# np.testing.assert_array_almost_equal(sol[:, :2, :], real_sol, decimal=2)
mismatch = ~np.isclose(sol[:, :2, :], real_sol,
rtol=0.01).sum() / np.product(sol.shape)
assert mismatch * 100 < 1
GeoMod_sol = geo_data.read_vox('./GeoModeller/test_f/test_f.vox')
similarity = (
(GeoMod_sol - sol[0, 0, :]) != 0).sum() / sol[0, 0].shape[0]
print('The mismatch geomodeller-gempy is ', similarity * 100, '%')
assert similarity < 0.05, 'The mismatch with geomodeller is too high'
def interpolator(self):
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_a/test_a_Foliations.csv",
path_i="./GeoModeller/test_a/test_a_Points.csv")
data_interp = gempy.set_interpolator(geo_data,
dtype="float64",
verbose=['solve_kriging'])
def test_e(self, theano_f_1f):
"""
Two layers a bit curvy, 1 fault
"""
data_interp = theano_f_1f[0]
compiled_f = theano_f_1f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data(
[0, 10, 0, 10, -10, 0], [50, 50, 50],
path_f="./GeoModeller/test_e/test_e_Foliations.csv",
path_i="./GeoModeller/test_e/test_e_Points.csv")
gempy.set_data_series(geo_data, {
'series': ('A', 'B'),
'fault1': 'f1'
},
order_series=['fault1', 'series'])
# rescaled_data = gempy.rescale_data(geo_data)
# # data_interp = gempy.set_interpolator(geo_data, dtype="float64", )
# data_interp.interpolator._data_scaled = rescaled_data
# data_interp.interpolator._grid_scaled = rescaled_data.grid
# data_interp.interpolator.order_table()
# data_interp.interpolator.set_theano_shared_parameteres()
#
# # Prepare the input data (interfaces, foliations data) to call the theano function.
# # Also set a few theano shared variables with the len of formations series and so on
# input_data_P = data_interp.interpolator.data_prep(u_grade=[3, 3])
#
# data_interp.interpolator.get_kriging_parameters()
#
#
#
# sol = compiled_f(input_data_P[0], input_data_P[1], input_data_P[2], input_data_P[3], input_data_P[4],
# input_data_P[5])
geo_data.n_faults = 1
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3, 3])
sol = compiled_f(*i)
# print(data_interp.rescale_factor, 'rescale')
real_sol = np.load('test_e_sol.npy')
np.testing.assert_array_almost_equal(sol[:, :2, :],
real_sol,
decimal=3)
def test_f(self, theano_f_1f):
"""
Two layers a bit curvy, 1 fault
"""
data_interp = theano_f_1f[0]
compiled_f = theano_f_1f[1]
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.import_data([0, 2000, 0, 2000, -2000, 0], [50, 50, 50],
path_f="./GeoModeller/test_f/test_f_Foliations.csv",
path_i="./GeoModeller/test_f/test_f_Points.csv")
geo_data.set_formation_number(geo_data.formations[[3, 2, 1, 0, 4]])
gempy.set_series(geo_data, {'series': ('Reservoir'
, 'Seal',
'SecondaryReservoir',
'NonReservoirDeep'
),
'fault1': 'MainFault'},
order_series=['fault1', 'series'])
geo_data.n_faults = 1
data_interp.set_interpolator(geo_data)
i = data_interp.get_input_data(u_grade=[3, 3])
sol = compiled_f(*i)
real_sol = np.load('test_f_sol.npy')
# np.testing.assert_array_almost_equal(sol[:, :2, :], real_sol, decimal=2)
mismatch = ~np.isclose(sol[:, :2, :], real_sol, rtol=0.01).sum()/np.product(sol.shape)
assert mismatch * 100 < 1
GeoMod_sol = geo_data.read_vox('./GeoModeller/test_f/test_f.vox')
similarity = ((GeoMod_sol - sol[0, 0, :]) != 0).sum() / sol[0, 0].shape[0]
print('The mismatch geomodeller-gempy is ', similarity*100, '%')
assert similarity < 0.05, 'The mismatch with geomodeller is too high'
