def generate_random_3graph(size_H, K=3):
H = numpy.empty(shape=(size_H, K), dtype=numpy.int32) # Generate H, empty adjacency list matrix
H[:] = -1 # Initialize it with all elements -1
nodes = numpy.arange(0, size_H) # Generate list of nodes from 0 to size_H - 1
randomized_nodes = numpy.random.permutation(nodes) # Randomize their positions so that we construct random K-regular
splits = numpy.array_split(randomized_nodes, 2) # Split the nodes into two halves
first = splits[0] # First half
second = splits[1] # Second half
for i, node1 in enumerate(first):
node1_1 = second[ (i-1) % numpy.size(second) ]
node1_2 = second[ i ]
node1_3 = second[ (i+1) % numpy.size(second) ]
H[node1][0] = node1_1 # Create the edge (node1, node1_1)
H[node1_1][helpers.get_rank(node1_1, H)] = node1 # Create the edge (node1_1, node1)
H[node1][1] = node1_2 # Create the edge (node1, node1_2)
H[node1_2][helpers.get_rank(node1_2, H)] = node1 # Create the edge (node1_2, node1)
H[node1][2] = node1_3 # Create the edge (node1, node1_3)
H[node1_3][helpers.get_rank(node1_3, H)] = node1 # Create the edge (node1_3, node1)
return H
def generate_random_3graph(size_H, K=3):
H = numpy.empty(
shape=(size_H, K),
dtype=numpy.int32) # Generate H, empty adjacency list matrix
H[:] = -1 # Initialize it with all elements -1
nodes = numpy.arange(0,
size_H) # Generate list of nodes from 0 to size_H - 1
randomized_nodes = numpy.random.permutation(
nodes
) # Randomize their positions so that we construct random K-regular
splits = numpy.array_split(randomized_nodes,
2) # Split the nodes into two halves
first = splits[0] # First half
second = splits[1] # Second half
for i, node1 in enumerate(first):
node1_1 = second[(i - 1) % numpy.size(second)]
node1_2 = second[i]
node1_3 = second[(i + 1) % numpy.size(second)]
H[node1][0] = node1_1 # Create the edge (node1, node1_1)
H[node1_1][helpers.get_rank(
node1_1, H)] = node1 # Create the edge (node1_1, node1)
H[node1][1] = node1_2 # Create the edge (node1, node1_2)
H[node1_2][helpers.get_rank(
node1_2, H)] = node1 # Create the edge (node1_2, node1)
H[node1][2] = node1_3 # Create the edge (node1, node1_3)
H[node1_3][helpers.get_rank(
node1_3, H)] = node1 # Create the edge (node1_3, node1)
return H
def info(self):
if dolfin.__version__ >= '1.3.0+':
# I *hate* unannounced and intrusive API changes with no support for a transition.
comm = mpi_comm_world() # self.domain.mesh.mpi_comm() when it works
hmin = MPI.min(comm, self.domain.mesh.hmin())
hmax = MPI.max(comm, self.domain.mesh.hmax())
num_cells = MPI.sum(comm, self.domain.mesh.num_cells())
rank = get_rank()
else:
hmin = MPI.min(self.domain.mesh.hmin())
hmax = MPI.max(self.domain.mesh.hmax())
num_cells = MPI.sum(self.domain.mesh.num_cells())
rank = MPI.process_number()
if rank == 0:
# Physical parameters
print "\n=== Physical parameters ==="
if isinstance(self.params["depth"], float):
print "Water depth: %f m" % self.params["depth"]
print "Gravity constant: %f m/s^2" % self.params["g"]
print "Viscosity constant: %f m^2/s" % self.params["diffusion_coef"]
print "Water density: %f kg/m^3" % self.params["rho"]
if isinstance(self.params["friction"], dolfin.functions.constant.Constant):
print "Bottom friction: %s" % (self.params["friction"](0))
else:
print "Bottom fruction: %f - %f" %\
(self.params["friction"].vector().array().min(),
self.params["friction"].vector().array().max())
print "Advection term: %s" % self.params["include_advection"]
print "Diffusion term: %s" % self.params["include_diffusion"]
print "Steady state: %s" % self.params["steady_state"]
# Turbine settings
print "\n=== Turbine settings ==="
print "Number of turbines: %i" % len(self.params["turbine_pos"])
print "Turbines parametrisation: %s" % self.params["turbine_parametrisation"]
if self.params["turbine_parametrisation"] == "individual":
print "Turbines dimensions: %f x %f" % (self.params["turbine_x"], self.params["turbine_y"])
print "Control parameters: %s" % ', '.join(self.params["controls"])
if len(self.params["turbine_friction"]) > 0:
print "Turbines frictions: %f - %f" % (min(self.params["turbine_friction"]), max(self.params["turbine_friction"]))
# Discretisation settings
print "\n=== Discretisation settings ==="
print "Finite element pair: ", self.finite_element.func_name
print "Steady state: ", self.params["steady_state"]
if not self.params["steady_state"]:
print "Theta: %f" % self.params["theta"]
print "Start time: %f s" % self.params["start_time"]
print "Finish time: %f s" % self.params["finish_time"]
print "Time step: %f s" % self.params["dt"]
print "Number of mesh elements: %i" % num_cells
print "Mesh element size: %f - %f" % (hmin, hmax)
# Optimisation settings
print "\n=== Optimisation settings ==="
print "Automatic functional rescaling: %s" % self.params["automatic_scaling"]
if self.params["automatic_scaling"]:
print "Automatic functional rescaling multiplier: %s" % self.params["automatic_scaling_multiplier"]
print "Automatic checkpoint generation: %s" % self.params["save_checkpoints"]
print ""
# Solver settings
print "\n=== Solver settings ==="
print "Nonlinear solver: %s" % ("Newton" if self.params["newton_solver"] else "Picard")
# Other
print "\n=== Other ==="
print "Dolfin version: %s" % dolfin.__version__
print "Cache forward solution for initial solver guess: %s" % self.params["cache_forward_state"]
print ""
