def plot(pb):
color_f = pb["wells"]["color"]
pb["domain"] = pp.cg.bounding_box(pb["dfn"]["pts"])
pp.plot_fractures(
pb["domain"],
pb["dfn"]["pts"],
pb["dfn"]["edges"],
plot=False,
fig_id=1,
colortag=color_f,
)
pp.plot_wells(
pb["domain"],
pb["wells"]["position"],
plot=False,
fig_id=1,
colortag=pb["wells"]["fracture"],
)
plt.figure(1)
plt.xlabel("x [m]")
plt.ylabel("y [m]")
plt.show()
def main():
# example in 2d
file_name = "network.csv"
write_network(file_name)
# load the network and split it, we assume 2d
domain = {"xmin": 0, "xmax": 1, "ymin": 0, "ymax": 1}
global_network = pp.fracture_importer.network_2d_from_csv(file_name,
domain=domain)
global_network = global_network.split_intersections()
# select a subsample of the fractures
macro_network, micro_network = split_network(global_network,
Criterion.every)
# NOTE: the explicit network is empty so far
# create the macroscopic grid
mesh_size = 2
mesh_kwargs = {
"mesh_size_frac": mesh_size,
"mesh_size_min": mesh_size / 20
}
gb = macro_network.mesh(mesh_kwargs)
# plot the suff
pp.plot_fractures(micro_network.pts, micro_network.edges,
micro_network.domain)
pp.plot_grid(gb, info="c", alpha=0)
# construct the solver
tpfa_dfm = Tpfa_DFM()
# Set data for the upscaling problem
g = gb.grids_of_dimension(gb.dim_max())[0]
d = gb.node_props(g)
# store the
# EK: We probably need to initialize some of the nested dictionaries
d[pp.PARAMETERS][tpfa_dfm.keyword][
tpfa_dfm.network_keyword] = micro_network
# set parameters and discretization variables
# EK: This must be done in this run-script - it is not the responsibility of the
# discretization. We may want to construct a model for this.
# tpfa_dfm.set_parameters(gb)
# tpfa_dfm.set_variables_discretizations(gb)
# discretize with the assembler
assembler = pp.Assembler(gb)
assembler.discretize()
A, b = assembler.assemble_matrix_rhs()
# Solve and distribute
x = spsolve(A, b)
assembler.distribute_variable(x)
def plot(self, **kwargs):
""" Plot the fracture set.
The function passes this fracture set to PorePy plot_fractures
Parameters:
**kwargs: Keyword arguments to be passed on to matplotlib.
"""
pp.plot_fractures(self.domain, self.pts, self.edges, **kwargs)
import numpy as np
import porepy as pp
from examples.papers.flow_upscaling.import_grid import raw_from_csv
from examples.papers.flow_upscaling.frac_gen import fit, generate
if __name__ == "__main__":
file_geo = "algeroyna_1to100.csv"
pts, edges, frac = raw_from_csv(file_geo, {"mesh_size_frac": 10},
{"snap": 1e-3})
domain = {
"xmin": pts[0].min(),
"xmax": pts[0].max(),
"ymin": pts[1].min(),
"ymax": pts[1].max(),
}
pp.plot_fractures(domain, pts, edges)
# we assume only 1 family, need to change the next line instead
family = np.ones(frac.size)
dist_l, dist_a = fit(pts, edges, frac, family)
pts_n, edges_n = generate(pts, edges, frac, dist_l, dist_a)
pp.plot_fractures(domain, pts_n, edges_n)