dis_voronoi_example.py

# ---
# jupyter:
#   jupytext:
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#   metadata:
#     section: dis
#     authors:
#       - name: Christian Langevin
# ---

# # Voronoi Grid and MODFLOW 6 Flow and Transport Example
#
# First set the path and import the required packages. The flopy path doesn't have to be set if you install flopy from a binary installer. If you want to run this notebook, you have to set the path to your own flopy path.

# +
import os
import sys
from pathlib import Path
from pprint import pformat
from tempfile import TemporaryDirectory

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from shapely.geometry import LineString, Point

import flopy
from flopy.discretization import VertexGrid
from flopy.utils.triangle import Triangle as Triangle
from flopy.utils.voronoi import VoronoiGrid

temp_dir = TemporaryDirectory()
workspace = Path(temp_dir.name)

print(sys.version)
print(f"numpy version: {np.__version__}")
print(f"matplotlib version: {mpl.__version__}")
print(f"flopy version: {flopy.__version__}")
# -

# ### Use Triangle to Generate Points for Voronoi Grid

# +
# set domain extents
xmin = 0.0
xmax = 2000.0
ymin = 0.0
ymax = 1000.0

# set minimum angle
angle_min = 30

# set maximum area
area_max = 1000.0

delr = area_max**0.5
ncol = xmax / delr
nrow = ymax / delr
nodes = ncol * nrow
print("equivalent delr: ", delr)
print("equivalent nodes, ncol, nrow: ", int(nodes), ncol, nrow)

# +
tri = Triangle(maximum_area=area_max, angle=angle_min, model_ws=workspace)
poly = np.array(((xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)))
tri.add_polygon(poly)
tri.build(verbose=False)

fig = plt.figure(figsize=(10, 10))
ax = plt.subplot(1, 1, 1, aspect="equal")
pc = tri.plot(ax=ax)
# -

# ### Create and Plot FloPy Voronoi Grid
#
# The Flopy VoronoiGrid class can be used to generate voronoi grids using the scipy.spatial.Voronoi class.  The VoronoiGrid class is a thin wrapper that makes sure edge cells are closed and provides methods for obtaining the information needed to make FloPy MODFLOW models.  It works by passing in the flopy Triangle object generated in the previous cell.

voronoi_grid = VoronoiGrid(tri)
fig = plt.figure(figsize=(10, 10))
ax = plt.subplot(1, 1, 1, aspect="equal")
voronoi_grid.plot(ax=ax, facecolor="none")

# ### Use the VertexGrid Representation to Identify Boundary Cells

# +
gridprops = voronoi_grid.get_gridprops_vertexgrid()
vgrid = flopy.discretization.VertexGrid(**gridprops, nlay=1)
ibd = np.zeros(vgrid.ncpl, dtype=int)
gi = flopy.utils.GridIntersect(vgrid)

# identify cells on left edge
line = LineString([(xmin, ymin), (xmin, ymax)])
cells0 = gi.intersect(line)["cellids"]
cells0 = np.array(list(cells0))
ibd[cells0] = 1

# identify cells on right edge
line = LineString([(xmax, ymin), (xmax, ymax)])
cells1 = gi.intersect(line)["cellids"]
cells1 = np.array(list(cells1))
ibd[cells1] = 2

# identify cell for a constant concentration condition
point = Point((500, 500))
cells2 = gi.intersect(point)["cellids"]
cells2 = np.array(list(cells2))
ibd[cells2] = 3

if True:
    fig = plt.figure(figsize=(10, 10))
    ax = plt.subplot(1, 1, 1, aspect="equal")
    pmv = flopy.plot.PlotMapView(modelgrid=vgrid)
    pmv.plot_array(ibd)
# -

# ### Create Run and Post Process a MODFLOW 6 Flow Model

# +
name = "mf"
sim_ws = os.path.join(workspace, "flow")
sim = flopy.mf6.MFSimulation(
    sim_name=name, version="mf6", exe_name="mf6", sim_ws=sim_ws
)
tdis = flopy.mf6.ModflowTdis(
    sim, time_units="DAYS", perioddata=[[1.0, 1, 1.0]]
)
gwf = flopy.mf6.ModflowGwf(sim, modelname=name, save_flows=True)
ims = flopy.mf6.ModflowIms(
    sim,
    print_option="SUMMARY",
    complexity="complex",
    outer_dvclose=1.0e-8,
    inner_dvclose=1.0e-8,
)
disv_gridprops = voronoi_grid.get_disv_gridprops()
nlay = 1
top = 1.0
botm = [0.0]
disv = flopy.mf6.ModflowGwfdisv(
    gwf, nlay=nlay, **disv_gridprops, top=top, botm=botm
)
npf = flopy.mf6.ModflowGwfnpf(
    gwf,
    xt3doptions=[(True)],
    k=10.0,
    save_saturation=True,
    save_specific_discharge=True,
)
ic = flopy.mf6.ModflowGwfic(gwf)

chdlist = []
for icpl in cells0:
    chdlist.append([(0, icpl), 1.0])
for icpl in cells1:
    chdlist.append([(0, icpl), 0.0])
chd = flopy.mf6.ModflowGwfchd(gwf, stress_period_data=chdlist)
oc = flopy.mf6.ModflowGwfoc(
    gwf,
    budget_filerecord=f"{name}.bud",
    head_filerecord=f"{name}.hds",
    saverecord=[("HEAD", "ALL"), ("BUDGET", "ALL")],
    printrecord=[("HEAD", "LAST"), ("BUDGET", "LAST")],
)
sim.write_simulation()
success, buff = sim.run_simulation(report=True, silent=True)
assert success, pformat(buff)

head = gwf.output.head().get_data()
bdobj = gwf.output.budget()
spdis = bdobj.get_data(text="DATA-SPDIS")[0]

fig = plt.figure(figsize=(15, 15))
ax = plt.subplot(1, 1, 1, aspect="equal")
pmv = flopy.plot.PlotMapView(gwf)
pmv.plot_array(head, cmap="jet", alpha=0.5)
pmv.plot_vector(spdis["qx"], spdis["qy"], alpha=0.25)
# -

# ### Create Run and Post Process a MODFLOW 6 Transport Model

# +
name = "mf"
sim_ws = os.path.join(workspace, "transport")
sim = flopy.mf6.MFSimulation(
    sim_name=name, version="mf6", exe_name="mf6", sim_ws=sim_ws
)
tdis = flopy.mf6.ModflowTdis(
    sim, time_units="DAYS", perioddata=[[100 * 365.0, 100, 1.0]]
)
gwt = flopy.mf6.ModflowGwt(sim, modelname=name, save_flows=True)
ims = flopy.mf6.ModflowIms(
    sim,
    print_option="SUMMARY",
    complexity="simple",
    linear_acceleration="bicgstab",
    outer_dvclose=1.0e-6,
    inner_dvclose=1.0e-6,
)
disv_gridprops = voronoi_grid.get_disv_gridprops()
nlay = 1
top = 1.0
botm = [0.0]
disv = flopy.mf6.ModflowGwtdisv(
    gwt, nlay=nlay, **disv_gridprops, top=top, botm=botm
)
ic = flopy.mf6.ModflowGwtic(gwt, strt=0.0)
sto = flopy.mf6.ModflowGwtmst(gwt, porosity=0.2)
adv = flopy.mf6.ModflowGwtadv(gwt, scheme="TVD")
dsp = flopy.mf6.ModflowGwtdsp(gwt, alh=5.0, ath1=0.5)
sourcerecarray = [()]
ssm = flopy.mf6.ModflowGwtssm(gwt, sources=sourcerecarray)
cnclist = [
    [(0, cells2[0]), 1.0],
]
cnc = flopy.mf6.ModflowGwtcnc(
    gwt, maxbound=len(cnclist), stress_period_data=cnclist, pname="CNC-1"
)
pd = [
    ("GWFHEAD", "../flow/mf.hds"),
    ("GWFBUDGET", "../flow/mf.bud"),
]
fmi = flopy.mf6.ModflowGwtfmi(gwt, packagedata=pd)
oc = flopy.mf6.ModflowGwtoc(
    gwt,
    budget_filerecord=f"{name}.cbc",
    concentration_filerecord=f"{name}.ucn",
    saverecord=[("CONCENTRATION", "ALL"), ("BUDGET", "ALL")],
)

sim.write_simulation()
success, buff = sim.run_simulation(report=True, silent=True)
assert success, pformat(buff)

conc = gwt.output.concentration().get_data()

fig = plt.figure(figsize=(10, 10))
ax = plt.subplot(1, 1, 1, aspect="equal")
pmv = flopy.plot.PlotMapView(gwf)
c = pmv.plot_array(conc, cmap="jet")
pmv.contour_array(conc, levels=(0.0001, 0.001, 0.01, 0.1), colors="y")
plt.colorbar(c, shrink=0.5)
# -

# ## Building Voronoi Grid Examples

# ### Irregular Domain Boundary

# +
domain = [
    [1831.381546, 6335.543757],
    [4337.733475, 6851.136153],
    [6428.747084, 6707.916043],
    [8662.980804, 6493.085878],
    [9350.437333, 5891.561415],
    [9235.861245, 4717.156511],
    [8963.743036, 3685.971717],
    [8691.624826, 2783.685023],
    [8047.13433, 2038.94045],
    [7416.965845, 578.0953252],
    [6414.425073, 105.4689614],
    [5354.596258, 205.7230386],
    [4624.173696, 363.2651598],
    [3363.836725, 563.7733141],
    [1330.11116, 1809.788273],
    [399.1804436, 2998.515188],
    [914.7728404, 5132.494831],
]
area_max = 100.0**2
tri = Triangle(maximum_area=area_max, angle=30, model_ws=workspace)
poly = np.array(domain)
tri.add_polygon(poly)
tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

# ### Simple Rectangular Domain

# +
xmin = 0.0
xmax = 2.0
ymin = 0.0
ymax = 1.0
area_max = 0.001
tri = Triangle(maximum_area=area_max, angle=30, model_ws=workspace)
poly = np.array(((xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)))
tri.add_polygon(poly)
tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

# ### Circular Grid

# +
theta = np.arange(0.0, 2 * np.pi, 0.2)
radius = 100.0
x = radius * np.cos(theta)
y = radius * np.sin(theta)
circle_poly = [(x, y) for x, y in zip(x, y)]
tri = Triangle(maximum_area=5, angle=30, model_ws=workspace)
tri.add_polygon(circle_poly)
tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

# ### Circular Grid with Hole

# +
theta = np.arange(0.0, 2 * np.pi, 0.2)
radius = 30.0
x = radius * np.cos(theta) + 25.0
y = radius * np.sin(theta) + 25.0
inner_circle_poly = [(x, y) for x, y in zip(x, y)]

tri = Triangle(maximum_area=10, angle=30, model_ws=workspace)
tri.add_polygon(circle_poly)
tri.add_polygon(inner_circle_poly)
tri.add_hole((25, 25))
tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

# ### Regions with Different Refinement

# +
active_domain = [(0, 0), (100, 0), (100, 100), (0, 100)]
area1 = [(10, 10), (40, 10), (40, 40), (10, 40)]
area2 = [(60, 60), (80, 60), (80, 80), (60, 80)]
tri = Triangle(angle=30, model_ws=workspace)
tri.add_polygon(active_domain)
tri.add_polygon(area1)
tri.add_polygon(area2)
tri.add_region((1, 1), 0, maximum_area=100)  # point inside active domain
tri.add_region((11, 11), 1, maximum_area=10)  # point inside area1
tri.add_region((61, 61), 2, maximum_area=3)  # point inside area2
tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

# ### Regions with Different Refinement and Hole

# +
active_domain = [(0, 0), (100, 0), (100, 100), (0, 100)]
area1 = [(10, 10), (40, 10), (40, 40), (10, 40)]
area2 = [(70, 70), (90, 70), (90, 90), (70, 90)]

tri = Triangle(angle=30, model_ws=workspace)

# requirement that active_domain is first polygon to be added
tri.add_polygon(active_domain)

# requirement that any holes be added next
theta = np.arange(0.0, 2 * np.pi, 0.2)
radius = 10.0
x = radius * np.cos(theta) + 50.0
y = radius * np.sin(theta) + 70.0
circle_poly0 = [(x, y) for x, y in zip(x, y)]
tri.add_polygon(circle_poly0)
tri.add_hole((50, 70))

# Add a polygon to force cells to conform to it
theta = np.arange(0.0, 2 * np.pi, 0.2)
radius = 10.0
x = radius * np.cos(theta) + 70.0
y = radius * np.sin(theta) + 20.0
circle_poly1 = [(x, y) for x, y in zip(x, y)]
tri.add_polygon(circle_poly1)
# tri.add_hole((70, 20))

# add line through domain to force conforming cells
line = [(x, x) for x in np.linspace(11, 89, 100)]
tri.add_polygon(line)


# then regions and other polygons should follow
tri.add_polygon(area1)
tri.add_polygon(area2)
tri.add_region((1, 1), 0, maximum_area=100)  # point inside active domain
tri.add_region((11, 11), 1, maximum_area=10)  # point inside area1
tri.add_region((70, 70), 2, maximum_area=1)  # point inside area2

tri.build(verbose=False)

vor = VoronoiGrid(tri)
gridprops = vor.get_gridprops_vertexgrid()
voronoi_grid = VertexGrid(**gridprops, nlay=1)

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot()
ax.set_aspect("equal")
voronoi_grid.plot(ax=ax)
# -

try:
    # ignore PermissionError on Windows
    temp_dir.cleanup()
except:
    pass