v_data[0, :3] += 0.1
data = pd.DataFrame(v_data, columns=["X", "Y", "Z", "val"])
data["feature_name"] = "test"
data["feature_name"] = "test"
data["nx"] = np.nan
data["ny"] = np.nan
data["nz"] = np.nan
data.loc[3, :] = [0, 0, 0, np.nan, "test", v, 0, 0]
# data.loc[3,['nx','ny','nz']]/=np.linalg.norm(data.loc[3,['nx','ny','nz']])
# data.loc[4,:] = [0,0,1,np.nan,'test',1,0,0]
model = GeologicalModel(np.zeros(3), np.ones(3) * 10)
model.data = data
model.create_and_add_foliation("test",
nelements=1e4,
interpolatortype="FDI")
view = LavaVuModelViewer(model)
view.add_isosurface(model["test"], slices=[0, 1], name="test")
view.add_data(model["test"])
view.rotate([-92.68915557861328, 2.879497528076172, 1.5840799808502197])
view.xmin = 0
view.ymin = 0
view.zmin = 0
view.xmax = 10
view.ymax = 10
view.zmax = 10
images[v] = view.image_array()
fig, ax = plt.subplots(1, 3, figsize=(30, 10))
ax[0].imshow(images[1])
ax[1].imshow(images[5])
ax[2].imshow(images[1 / 5])
ax[0].axis("off")
model = GeologicalModel(bb[0,:],bb[1,:])
model.set_model_data(data)
vals = [0,60,250,330,600]
strat_column = {'strati':{}}
for i in range(len(vals)-1):
strat_column['strati']['unit_{}'.format(i)] = {'min':vals[i],'max':vals[i+1],'id':i}
model.set_stratigraphic_column(strat_column)
strati = model.create_and_add_foliation("strati",
interpolatortype="FDI", # try changing this to 'PLI'
nelements=1e4, # try changing between 1e3 and 5e4
buffer=0.3,
solver='pyamg',
damp=True
)
viewer = LavaVuModelViewer(model,background="white")
viewer.add_model_surfaces()
viewer.rotate([-85.18760681152344, 42.93233871459961, 0.8641873002052307])
viewer.display()
#################################################################################################
# Looking at the log file
# ~~~~~~~~~~~~~~~~~~~~~~~
# Here are the first 10 lines of the log file.
# Most operations in loopstructural are recorded and this will allow you to identify whether
# an operation is not occuring as you would expect.
from itertools import islice
# with open('logging_demo_log.log') as inf:
# for line in islice(inf, 0, 11):
# print(line)
def loop2LoopStructural(thickness_file,orientation_file,contacts_file,bbox):
from LoopStructural import GeologicalModel
from LoopStructural.visualisation import LavaVuModelViewer
import lavavu
df = pd.read_csv(thickness_file)
thickness = {}
for f in df['formation'].unique():
thickness[f] = np.mean(df[df['formation']==f]['thickness'])
#display(thickness)
order = ['P__TKa_xs_k','P__TKo_stq','P__TKk_sf','P__TK_s',
'A_HAu_xsl_ci', 'A_HAd_kd', 'A_HAm_cib', 'A_FOj_xs_b',
'A_FO_xo_a', 'A_FO_od', 'A_FOu_bbo',
'A_FOp_bs', 'A_FOo_bbo', 'A_FOh_xs_f', 'A_FOr_b']
strat_val = {}
val = 0
for o in order:
if o in thickness:
strat_val[o] = val
val+=thickness[o]
#display(strat_val)
orientations = pd.read_csv(orientation_file)
contacts = pd.read_csv(contacts_file)
contacts['val'] = np.nan
for o in strat_val:
contacts.loc[contacts['formation']==o,'val'] = strat_val[o]
data = pd.concat([orientations,contacts],sort=False)
data['type'] = np.nan
for o in order:
data.loc[data['formation']==o,'type'] = 's0'
data
boundary_points = np.zeros((2,3))
boundary_points[0,0] = bbox[0]
boundary_points[0,1] = bbox[1]
boundary_points[0,2] = -20000
boundary_points[1,0] = bbox[2]
boundary_points[1,1] = bbox[3]
boundary_points[1,2] = 1200
model = GeologicalModel(boundary_points[0,:],boundary_points[1,:])
model.set_model_data(data)
strati = model.create_and_add_foliation('s0', #identifier in data frame
interpolatortype="FDI", #which interpolator to use
nelements=400000, # how many tetras/voxels
buffer=0.1, # how much to extend nterpolation around box
solver='external',
external=solve_pyamg
)
#viewer = LavaVuModelViewer()
viewer = LavaVuModelViewer(model)
viewer.add_data(strati['feature'])
viewer.add_isosurface(strati['feature'],
# nslices=10,
slices= strat_val.values(),
# voxet={'bounding_box':boundary_points,'nsteps':(100,100,50)},
paint_with=strati['feature'],
cmap='tab20'
)
#viewer.add_scalar_field(model.bounding_box,(100,100,100),
# 'scalar',
## norm=True,
# paint_with=strati['feature'],
# cmap='tab20')
viewer.add_scalar_field(strati['feature'])
viewer.set_viewer_rotation([-53.8190803527832, -17.1993350982666, -2.1576387882232666])
#viewer.save("fdi_surfaces.png")
viewer.interactive()
########################################################################
# Stratigraphic columns
# ~~~~~~~~~~~~~~~~~~~~~~~
# We define the stratigraphic column using a nested dictionary
stratigraphic_column = {}
stratigraphic_column['strati2'] = {}
stratigraphic_column['strati2']['unit1'] = {'min': 1, 'max': 10, 'id': 0}
stratigraphic_column['strati'] = {}
stratigraphic_column['strati']['unit2'] = {'min': -60, 'max': 0, 'id': 1}
stratigraphic_column['strati']['unit3'] = {'min': -250, 'max': -60, 'id': 2}
stratigraphic_column['strati']['unit4'] = {'min': -330, 'max': -250, 'id': 3}
stratigraphic_column['strati']['unit5'] = {
'min': -np.inf,
'max': -330,
'id': 4
}
########################################################
# Adding stratigraphic column to the model
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# The stratigraphic column can be added to the geological model. Allowing
# for the `model.evaluate_model(xyz)` function to be called.
model.set_stratigraphic_column(stratigraphic_column)
viewer = LavaVuModelViewer(model)
viewer.add_model(cmap='tab20')
viewer.rotate([-85.18760681152344, 42.93233871459961, 0.8641873002052307])
viewer.display()
# distance from a reference horizon. It is comparable
# to the relative thickness
#
# * ``nx`` is the x component of the normal vector to the surface gradient
# * ``ny`` is the y component of the normal vector to the surface gradient
# * ``nz`` is the z component of the normal vector to the surface gradeint
# * ``strike`` is the strike angle
# * ``dip`` is the dip angle
#
# Having a look at the data for this example by looking at the top of the
# dataframe and then using a 3D plot
#
data['feature_name'].unique()
viewer = LavaVuModelViewer(background='white')
viewer.add_value_data(data[~np.isnan(data['val'])][['X', 'Y', 'Z']],
data[~np.isnan(data['val'])]['val'],
name='value points')
viewer.add_vector_data(data[~np.isnan(data['nx'])][['X', 'Y', 'Z']],
data[~np.isnan(data['nx'])][['nx', 'ny', 'nz']],
name='orientation points')
viewer.rotate([-85.18760681152344, 42.93233871459961, 0.8641873002052307])
viewer.display()
######################################################################
# The pandas dataframe can be linked to the ``GeologicalModel`` using
# ``.set_model_data(dataframe``
#
model.set_model_data(data)
'nelements': 1e5, # how many tetras/voxels
'buffer': 1.8, # how much to extend nterpolation around box
#'solver':'cg',
'cpw': 10,
'npw': 10
}
model = GeologicalModel.from_map2loop_directory(
proj_path,
# evaluate=False,
fault_params=fault_params,
rescale=False,
foliation_params=foliation_params,
)
#model.to_file(output_path + "/model.pickle")
model.update()
view = LavaVuModelViewer(model, vertical_exaggeration=1)
view.nsteps = np.array([200, 200, 200])
view.nsteps = np.array([50, 50, 50])
for sg in model.feature_name_index:
if ('super' in sg):
view.add_data(model.features[model.feature_name_index[sg]])
view.nelements = 1e5
view.add_model_surfaces(function=function, filename=filename, faults=False)
view.nelements = 1e6
view.add_model_surfaces(function=function,
filename=filename,
strati=False,
displacement_cmap='rainbow')
view.lv.webgl(vtk_path + model_name)
view.nsteps = np.array([200, 200, 200])