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Merge pull request #71 from Loop3D/dataprocessor
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Dataprocessor
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@lachlangrose
lachlangrose authored Aug 23, 2021
2 parents bedc7ab + 4ed6fa2 commit 128909f
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Showing 29 changed files with 1,042 additions and 2,102 deletions.
1 change: 1 addition & 0 deletions DockerfileDev
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Expand Up @@ -46,6 +46,7 @@ USER ${NB_USER}
RUN mkdir notebooks
RUN mkdir LoopStructural
RUN mkdir map2loop
RUN mkdir LoopProjectFile

# RUN pip install -e LoopStructural
CMD ["jupyter", "notebook", "--ip='0.0.0.0'", "--NotebookApp.token=''", "--no-browser" ]
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2 changes: 1 addition & 1 deletion LoopStructural/__init__.py
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Expand Up @@ -15,7 +15,7 @@
ch.setFormatter(formatter)
ch.setLevel(logging.WARNING)
loggers = {}
__version__ = '1.1.0'
__version__ = '1.2.0'
from .modelling.core.geological_model import GeologicalModel
from .utils import log_to_console, log_to_file, getLogger
logger = getLogger(__name__)
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1,923 changes: 1 addition & 1,922 deletions LoopStructural/datasets/data/refolded_fold.csv
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96 changes: 55 additions & 41 deletions LoopStructural/interpolators/finite_difference_interpolator.py
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Expand Up @@ -79,58 +79,62 @@ def _setup_interpolator(self, **kwargs):
for key in kwargs:
self.up_to_date = False
if 'regularisation' in kwargs:
self.interpolation_weights['dxy'] = kwargs[
'regularisation'] * 0.7
self.interpolation_weights['dyz'] = kwargs[
'regularisation'] * 0.7
self.interpolation_weights['dxz'] = kwargs[
'regularisation'] * 0.7
self.interpolation_weights['dxx'] = kwargs[
'regularisation'] * 1.
self.interpolation_weights['dyy'] = kwargs[
'regularisation'] * 1.
self.interpolation_weights['dzz'] = kwargs[
'regularisation'] * 1.
self.interpolation_weights['dxy'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights['dyz'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights['dxz'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights['dxx'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights['dyy'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights['dzz'] = 0.1*kwargs[
'regularisation']
self.interpolation_weights[key] = kwargs[key]
# if we want to define the operators manually
if 'operators' in kwargs:
for n, o in kwargs['operators'].items():
self.assemble_inner(o[0], o[1])
# otherwise just use defaults
if 'operators' not in kwargs:

operator = Operator.Dxy_mask

self.assemble_inner(operator, np.sqrt(2 * self.vol) *
self.interpolation_weights['dxy'])
weight = self.interpolation_weights['dxy'] / \
1#(4*self.support.step_vector[0]*self.support.step_vector[1])
self.assemble_inner(operator, weight )
operator = Operator.Dyz_mask
self.assemble_inner(operator, np.sqrt(2 * self.vol) *
self.interpolation_weights['dyz'])
weight = self.interpolation_weights['dyz'] / \
1#(4*self.support.step_vector[1]*self.support.step_vector[2])
self.assemble_inner(operator, weight)
operator = Operator.Dxz_mask
self.assemble_inner(operator, np.sqrt(2 * self.vol) *
self.interpolation_weights['dxz'])
weight = self.interpolation_weights['dxz'] / \
1#(4*self.support.step_vector[0]*self.support.step_vector[2])
self.assemble_inner(operator, weight)
operator = Operator.Dxx_mask
weight = self.interpolation_weights['dxx'] \
/ 1#self.support.step_vector[0]**2
self.assemble_inner(operator,
np.sqrt(self.vol) * self.interpolation_weights[
'dxx'])
weight)
operator = Operator.Dyy_mask
self.assemble_inner(operator,
np.sqrt(self.vol) * self.interpolation_weights[
'dyy'])
weight = self.interpolation_weights['dyy'] / \
1#self.support.step_vector[1]**2
self.assemble_inner(operator,weight)
operator = Operator.Dzz_mask
self.assemble_inner(operator,
np.sqrt(self.vol) * self.interpolation_weights[
'dzz'])
weight = self.interpolation_weights['dzz'] / \
1#self.support.step_vector[2]**2
self.assemble_inner(operator,weight)
self.add_norm_constraint(
np.sqrt(self.vol) * self.interpolation_weights['npw'])
self.interpolation_weights['npw'])
self.add_gradient_constraint(
np.sqrt(self.vol) * self.interpolation_weights['gpw'])
self.interpolation_weights['gpw'])
self.add_vaue_constraint(
np.sqrt(self.vol) * self.interpolation_weights['cpw'])
self.interpolation_weights['cpw'])
self.add_tangent_ctr_pts(
np.sqrt(self.vol) * self.interpolation_weights['tpw']
self.interpolation_weights['tpw']
)
self.add_interface_ctr_pts(
np.sqrt(self.vol)*self.interpolation_weights['ipw']
self.interpolation_weights['ipw']
)

def copy(self):
Expand Down Expand Up @@ -172,7 +176,7 @@ def add_vaue_constraint(self, w=1.):
inside = np.logical_and(~np.any(idc == -1, axis=1), inside)
a = self.support.position_to_dof_coefs(points[inside, :3])
# a*=w

# a/=np.product(self.support.step_vector)
self.add_constraints_to_least_squares(a.T * w,
points[inside, 3] * w,
idc[inside, :],
Expand Down Expand Up @@ -259,6 +263,8 @@ def add_gradient_constraint(self, w=1.):
inside = np.logical_and(~np.any(idc == -1, axis=1), inside)

T = self.support.calcul_T(points[inside, :3])
norm = np.linalg.norm(T,axis=2)
T/=norm[:,:,None]
strike_vector, dip_vector = get_vectors(points[inside, 3:6])
A = np.einsum('ij,ijk->ik', strike_vector.T, T)

Expand All @@ -284,7 +290,6 @@ def add_norm_constraint(self, w=1.):
if points.shape[0] > 0:
# calculate unit vector for orientation data
# points[:,3:]/=np.linalg.norm(points[:,3:],axis=1)[:,None]

node_idx, inside = self.support.position_to_cell_corners(
points[:, :3])
gi = np.zeros(self.support.n_nodes)
Expand All @@ -299,16 +304,17 @@ def add_norm_constraint(self, w=1.):
# this means we are only constraining direction of grad not the
# magnitude
T = self.support.calcul_T(points[inside, :3])

# T*=np.product(self.support.step_vector)
# T/=self.support.step_vector[0]
w /= 3
self.add_constraints_to_least_squares(T[:, 0, :] * w,
points[inside, 3] * w,
points[inside, 3] * w ,
idc[inside, :], name='norm')
self.add_constraints_to_least_squares(T[:, 1, :] * w,
points[inside, 4] * w,
points[inside, 4] * w ,
idc[inside, :], name='norm')
self.add_constraints_to_least_squares(T[:, 2, :] * w,
points[inside, 5] * w,
points[inside, 5] * w ,
idc[inside, :], name='norm')

def add_gradient_orthogonal_constraint(self, points, vector, w=1.0,
Expand Down Expand Up @@ -345,9 +351,15 @@ def add_gradient_orthogonal_constraint(self, points, vector, w=1.0,
idc[inside, :] = gi[node_idx[inside, :]]
inside = np.logical_and(~np.any(idc == -1, axis=1), inside)

#normalise element vector to unit vector for dot product
T = self.support.calcul_T(points[inside, :3])
norm = np.linalg.norm(T,axis=1)
T/=norm[:,None,:]
# normalise vector to unit vector for dot product
vector[inside,:3] /= np.linalg.norm(vector[inside,:3],axis=1)[:,None]
# dot product of vector and element gradient
A = np.einsum('ij,ijk->ik', vector[inside, :3], T)

B = np.zeros(points[inside, :].shape[0])
self.add_constraints_to_least_squares(A * w, B, idc[inside, :], name='gradient orthogonal')

Expand Down Expand Up @@ -390,9 +402,11 @@ def assemble_inner(self, operator, w):
gi[:] = -1
gi[self.region] = np.arange(0, self.nx)
idc = gi[idc]
inside = ~np.any(idc == -1, axis=1)
inside = ~np.any(idc == -1, axis=1)#np.ones(a.shape[0],dtype=bool)#
# a[idc==-1] = 0
# idc[idc==-1] = 0
B = np.zeros(global_indexes.shape[1])
self.add_constraints_to_least_squares(a[inside, :] * w,
self.add_constraints_to_least_squares(a[inside, :] * w ,
B[inside],
idc[inside, :],
name='regularisation'
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2 changes: 1 addition & 1 deletion LoopStructural/interpolators/operator.py
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Expand Up @@ -33,7 +33,7 @@ class Operator(object):
[-0.25, 0, 0.25],
[0, 0, 0],
[0.25, 0, -0.25]
], z])
], z]) / np.sqrt(2)
Dxz_mask = Dxy_mask.swapaxes(0, 1)
Dyz_mask = Dxy_mask.swapaxes(0, 2)

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2 changes: 1 addition & 1 deletion LoopStructural/interpolators/piecewiselinear_interpolator.py
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Expand Up @@ -290,7 +290,7 @@ def add_norm_ctr_pts(self, w=1.0):
# d_t = self.support.get_elements_gradients(e)
norm = np.zeros((element_gradients.shape[0],element_gradients.shape[1]))
norm[inside,:] = np.linalg.norm(element_gradients[inside,:,:], axis=2)
element_gradients /= norm[:, :, None]
# element_gradients /= norm[:, :, None]

d_t = element_gradients
d_t[inside,:,:] *= vol[inside, None, None]
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36 changes: 13 additions & 23 deletions LoopStructural/interpolators/structured_grid.py
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Expand Up @@ -40,19 +40,18 @@ def barycentre(self):


def cell_centres(self, global_index):
"""[summary]
[extended_summary]
"""get the centre of specified cells
Parameters
----------
global_index : [type]
[description]
global_index : array/list
container of integer global indexes to cells
Returns
-------
[type]
[description]
numpy array
Nx3 array of cell centres
"""
ix, iy, iz = self.global_index_to_cell_index(global_index)
x = self.origin[None, 0] + self.step_vector[None, 0] * .5 + \
Expand Down Expand Up @@ -103,15 +102,14 @@ def position_to_local_coordinates(self, pos):
"""
# TODO check if inside mesh
pos = self.rotate(pos)
# pos = self.rotate(pos)
# calculate local coordinates for positions
local_x = ((pos[:, 0] - self.origin[None, 0]) % self.step_vector[
None, 0]) / self.step_vector[None, 0]
local_y = ((pos[:, 1] - self.origin[None, 1]) % self.step_vector[
None, 1]) / self.step_vector[None, 1]
local_z = ((pos[:, 2] - self.origin[None, 2]) % self.step_vector[
None, 2]) / self.step_vector[None, 2]

return local_x, local_y, local_z

def position_to_dof_coefs(self, pos):
Expand Down Expand Up @@ -325,9 +323,8 @@ def calcul_T(self, pos):
# x, y, z = self.node_indexes_to_position(cellx, celly, cellz)
T = np.zeros((pos.shape[0], 3, 8))
x, y, z = self.position_to_local_coordinates(pos)
# div = self.step_vector[0] * self.step_vector[1] * self.step_vector[2]

T[:, 0, 0] = -(1 - y) * (1 - z) # v000

T[:, 0, 0] = (1 - z) * (y- 1) # v000
T[:, 0, 1] = (1 - y) * (1 - z) # (y[:, 3] - pos[:, 1]) / div
T[:, 0, 2] = -y * (1 - z) # (pos[:, 1] - y[:, 0]) / div
T[:, 0, 3] = -(1 - y) * z # (pos[:, 1] - y[:, 1]) / div
Expand All @@ -336,7 +333,7 @@ def calcul_T(self, pos):
T[:, 0, 6] = y * (1 - z)
T[:, 0, 7] = y * z

T[:, 1, 0] = - (1 - x) * (1 - z)
T[:, 1, 0] = (x - 1) * (1 - z)
T[:, 1, 1] = - x * (1 - z)
T[:, 1, 2] = (1 - x) * (1 - z)
T[:, 1, 3] = -(1 - x) * z
Expand All @@ -353,14 +350,7 @@ def calcul_T(self, pos):
T[:, 2, 5] = (1 - x) * y
T[:, 2, 6] = - x * y
T[:, 2, 7] = x * y
return T
T/=self.step_vector[0]

return T

def slice(self, propertyname, isovalue, region):
logger.error("function has been removed, please use the modelviewer class")
return
#
# verts, faces, normals, values = marching_cubes(
# self.properties[propertyname].reshape(self.nsteps, order='F'),
# isovalue,
# spacing=self.step_vector)
# return faces, verts + self.origin[None, :]
5 changes: 4 additions & 1 deletion LoopStructural/interpolators/surfe_wrapper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,4 +115,7 @@ def evaluate_gradient(self, evaluation_points):
if evaluation_points[~mask, :].shape[0] > 0:
evaluated[~mask,:] = self.surfe.EvaluateVectorInterpolantAtPoints(
evaluation_points[~mask])
return evaluated
return
@property
def nx(self):
return self.get_data_locations().shape[0]
1 change: 1 addition & 0 deletions LoopStructural/modelling/__init__.py
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Expand Up @@ -3,3 +3,4 @@
"""

from .input.process_data import ProcessInputData
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