import openpnm as op
from openpnm.models.physics import source_terms
from openpnm.models import collections
import matplotlib.pyplot as plt


op.visualization.set_mpl_style()
ws = op.Workspace()
ws.settings["default_solver"] = "ScipySpsolve"
ws.clear()

pn = op.network.Cubic(shape=[25, 25, 1], spacing=1e-4)

# Create domain
Ps = pn.coords[:, 0] < 13e-4
Ts = pn.find_neighbor_throats(pores=Ps, asmask=True)
pn["pore.domain1"] = Ps
pn["throat.domain1"] = Ts

# Create domain2
Ps = pn.coords[:, 0] >= 13e-4
Ts = pn.find_neighbor_throats(pores=Ps, mode="xnor", asmask=True)
pn["pore.domain2"] = Ps
pn["throat.domain2"] = Ts

# Add network/geometry models to both domains
pn.add_model_collection(collections.geometry.cones_and_cylinders, domain="domain1")
pn.add_model_collection(collections.geometry.pyramids_and_cuboids, domain="domain2")

# FIXME: Must regenerate network models, otherwise, phase models will complain
pn.regenerate_models()

# Create phase and add phase/physics models
air = op.phase.Air(network=pn, name="air")
air.add_model_collection(collections.physics.standard)
air.regenerate_models()

# Add a nonlinear reaction
air["pore.reaction_sites"] = False
air["pore.reaction_sites"][[310, 212, 113]] = True
air.add_model(
    propname="pore.reaction1",
    model=source_terms.power_law,
    X="pore.concentration",
    A1=-1,
    A2=2,
    A3=0,
    domain="reaction_sites",
    regen_mode="deferred",
)
air.add_model(
    propname="pore.reaction2",
    model=source_terms.power_law,
    X="pore.concentration",
    A1=-1,
    A2=2,
    A3=0,
    domain="reaction_sites",
    regen_mode="deferred",
)

# Run Fickian diffusion with reaction
rxn = op.algorithms.FickianDiffusion(network=pn, phase=air)
rxn.set_value_BC(pores=pn.pores("left"), values=1)
rxn.set_source(pores=air.pores("reaction_sites"), propname="pore.reaction1")
rxn.run()

# Run Fickian diffusion with reaction
rxn2 = op.algorithms.FickianDiffusion(network=pn, phase=air)
rxn2.set_value_BC(pores=pn.pores("left"), values=1)
rxn2.set_source(pores=air.pores("reaction_sites"), propname="pore.reaction2")
rxn2.run()

# Plot concentration profile
fig, ax = plt.subplots()
ax = op.visualization.plot_coordinates(
    network=pn,
    ax=ax,
    color_by=rxn2['pore.concentration'],
    size_by=pn['pore.diameter'],
    s=75,
    ec='k',
    linewidth=0.5,
)
ax = op.visualization.plot_connections(
    network=pn,
    ax=ax,
    zorder=0,
    color_by=pn['throat.diameter'],
    linewidth=1.5,
    alpha=0.5,
)
ax.axis(False)
fig.colorbar(ax.collections[0], label='pore.concentration')
fig.colorbar(ax.collections[1], label='throat.diameter')