"""
Finite-volume computations of the shallow water wave equation.

Title: ANGUA shallow_water_domain - 2D triangular domains for finite-volume
       computations of the shallow water wave equation.


Author: Ole Nielsen, Ole.Nielsen@ga.gov.au
        Stephen Roberts, Stephen.Roberts@anu.edu.au
        Duncan Gray, Duncan.Gray@ga.gov.au
        Gareth Davies, gareth.davies.ga.code@gmail.com

CreationDate: 2004

Description:
    This module contains a specialisation of class Generic_Domain from
    module generic_domain.py consisting of methods specific to the
    Shallow Water Wave Equation

    U_t + E_x + G_y = S

    where

    U = [w, uh, vh]
    E = [uh, u^2h + gh^2/2, uvh]
    G = [vh, uvh, v^2h + gh^2/2]
    S represents source terms forcing the system
    (e.g. gravity, friction, wind stress, ...)

    and _t, _x, _y denote the derivative with respect to t, x and y
    respectively.


    The quantities are

    symbol    variable name    explanation
    x         x                horizontal distance from origin [m]
    y         y                vertical distance from origin [m]
    z         elevation        elevation of bed on which flow is modelled [m]
    h         height           water height above z [m]
    w         stage            absolute water level, w = z+h [m]
    u                          speed in the x direction [m/s]
    v                          speed in the y direction [m/s]
    uh        xmomentum        momentum in the x direction [m^2/s]
    vh        ymomentum        momentum in the y direction [m^2/s]

    eta                        mannings friction coefficient [to appear]
    nu                         wind stress coefficient [to appear]

    The conserved quantities are w, uh, vh

Reference:
    Catastrophic Collapse of Water Supply Reservoirs in Urban Areas,
    Christopher Zoppou and Stephen Roberts,
    Journal of Hydraulic Engineering, vol. 127, No. 7 July 1999

    Hydrodynamic modelling of coastal inundation.
    Nielsen, O., S. Roberts, D. Gray, A. McPherson and A. Hitchman
    In Zerger, A. and Argent, R.M. (eds) MODSIM 2005 International Congress on
    Modelling and Simulation. Modelling and Simulation Society of Australia and
    New Zealand, December 2005, pp. 518-523. ISBN: 0-9758400-2-9.
    http://www.mssanz.org.au/modsim05/papers/nielsen.pdf

    See also: https://anuga.anu.edu.au and https://en.wikipedia.org/wiki/ANUGA_Hydro


Constraints: See GPL license in the user guide
"""
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division

# Decorator added for profiling
#------------------------------

#rom past.builtins import str
from builtins import range
from past.utils import old_div
from future.utils import raise_
def profileit(name):
    def inner(func):
        def wrapper(*args, **kwargs):
            prof = cProfile.Profile()
            retval = prof.runcall(func, *args, **kwargs)
            # Note use of name from outer scope
            print(str(args[1])+"_"+name)
            prof.dump_stats(str(args[1])+"_"+name)
            return retval
        return wrapper
    return inner
#-----------------------------

import numpy as num
import sys
import os
import time

try:
    import dill as pickle
except:
    import pickle

from anuga.abstract_2d_finite_volumes.generic_domain \
                    import Generic_Domain

from anuga.shallow_water.forcing import Cross_section
from anuga.utilities.numerical_tools import mean
from anuga.file.sww import SWW_file

import anuga.utilities.log as log

from anuga.utilities.parallel_abstraction import size, rank, get_processor_name
from anuga.utilities.parallel_abstraction import finalize, send, receive
from anuga.utilities.parallel_abstraction import pypar_available, barrier


#from pypar import size, rank, send, receive, barrier

class Domain(Generic_Domain):
    """
    This class is a specialization of class Generic_Domain from
    module generic_domain.py consisting of methods specific to the
    Shallow Water Wave Equation

    U_t + E_x + G_y = S

    where

    U = [w, uh, vh]
    E = [uh, u^2h + gh^2/2, uvh]
    G = [vh, uvh, v^2h + gh^2/2]

    S represents source terms forcing the system
    (e.g. gravity, friction, wind stress, ...)

    and _t, _x, _y denote the derivative with respect to t, x and y
    respectively.

    The quantities are

    symbol    variable name    explanation
        x         x                horizontal distance from origin [m]
        y         y                vertical distance from origin [m]
        z         elevation        elevation of bed on which flow is modelled [m]
        h         height           water height above z [m]
        w         stage            absolute water level, w = z+h [m]
        u                          speed in the x direction [m/s]
        v                          speed in the y direction [m/s]
        uh        xmomentum        momentum in the x direction [m^2/s]
        vh        ymomentum        momentum in the y direction [m^2/s]

        eta                        mannings friction coefficient [to appear]
        nu                         wind stress coefficient [to appear]

    The conserved quantities are w, uh, vh
    """

    def __init__(self,
                 coordinates=None,
                 vertices=None,
                 boundary=None,
                 tagged_elements=None,
                 geo_reference=None,
                 use_inscribed_circle=False,
                 mesh_filename=None,
                 use_cache=False,
                 verbose=False,
                 conserved_quantities = None,
                 evolved_quantities = None,
                 other_quantities = None,
                 full_send_dict=None,
                 ghost_recv_dict=None,
                 starttime=0,
                 processor=0,
                 numproc=1,
                 number_of_full_nodes=None,
                 number_of_full_triangles=None,
                 ghost_layer_width=2,
                 **kwargs):

        """
        Instantiate a shallow water domain.

        @param coordinates: vertex locations for the mesh
        @param vertices: vertex indices for the mesh
        @param boundary: boundaries of the mesh
        """

        # Define quantities for the shallow_water domain
        if conserved_quantities is None:
            conserved_quantities = ['stage', 'xmomentum', 'ymomentum']

        if evolved_quantities is None:
            evolved_quantities =  ['stage', 'xmomentum', 'ymomentum']

        if other_quantities is None:
            other_quantities = ['elevation', 'friction', 'height',
                                'xvelocity', 'yvelocity', 'x', 'y']





        Generic_Domain.__init__(self,
                            coordinates,
                            vertices,
                            boundary,
                            conserved_quantities,
                            evolved_quantities,
                            other_quantities,
                            tagged_elements,
                            geo_reference,
                            use_inscribed_circle,
                            mesh_filename,
                            use_cache,
                            verbose,
                            full_send_dict,
                            ghost_recv_dict,
                            starttime,
                            processor,
                            numproc,
                            number_of_full_nodes=number_of_full_nodes,
                            number_of_full_triangles=number_of_full_triangles,
                            ghost_layer_width=ghost_layer_width)

        #-------------------------------
        # Operator Data Structures
        #-------------------------------
        self.fractional_step_operators = []
        self.kv_operator = None



        #-------------------------------
        # Set flow defaults
        #-------------------------------
        self.set_flow_algorithm()


        #-------------------------------
        # Forcing Terms
        #
        # Gravity is now incorporated in
        # compute_fluxes routine
        #-------------------------------
        self.forcing_terms.append(manning_friction_implicit)


        #-------------------------------
        # Stored output
        #-------------------------------
        self.set_store(True)
        self.set_store_centroids(True)
        self.set_store_vertices_uniquely(False)
        self.quantities_to_be_stored = {'elevation': 1,
                                        'friction':1,
                                        'stage': 2,
                                        'xmomentum': 2,
                                        'ymomentum': 2}

        #-------------------------------
        # Set up check pointing every n
        # yieldsteps
        #-------------------------------
        self.checkpoint = False
        self.yieldstep_counter = 0
        self.checkpoint_step = 10

        #-------------------------------
        # Useful auxiliary quantity
        #-------------------------------
        n = self.number_of_elements
        self.quantities['x'].set_values(self.vertex_coordinates[:,0].reshape(n,3))
        self.quantities['x'].set_boundary_values_from_edges()

        self.quantities['y'].set_values(self.vertex_coordinates[:,1].reshape(n,3))
        self.quantities['y'].set_boundary_values_from_edges()

        # For riverwalls, we need to know the 'edge_flux_type' for each edge
        # Edge-flux-type of 0 == Normal edge, with shallow water flux
        #                   1 == riverwall
        #                   2 == ?
        #                   etc
        self.edge_flux_type=num.zeros(len(self.edge_coordinates[:,0])).astype(int)

        # Riverwalls -- initialise with dummy values
        # Presently only works with DE algorithms, will fail otherwise
        import anuga.structures.riverwall
        self.riverwallData=anuga.structures.riverwall.RiverWall(self)

        ## Keep track of the fluxes through the boundaries
        ## Only works for DE algorithms at present
        max_time_substeps=3 # Maximum number of substeps supported by any timestepping method
        # boundary_flux_sum holds boundary fluxes on each sub-step [unused substeps = 0.]
        self.boundary_flux_sum=num.array([0.]*max_time_substeps)
        from anuga.operators.boundary_flux_integral_operator import boundary_flux_integral_operator
        self.boundary_flux_integral=boundary_flux_integral_operator(self)
        # Make an integer counting how many times we call compute_fluxes_central -- so we know which substep we are on
        #self.call=1

        # List to store the volumes we computed before
        self.volume_history=[]

        # Work arrays [avoid allocate statements in compute_fluxes or extrapolate_second_order]
        self.edge_flux_work=num.zeros(len(self.edge_coordinates[:,0])*3) # Advective fluxes
        self.pressuregrad_work=num.zeros(len(self.edge_coordinates[:,0])) # Gravity related terms
        self.x_centroid_work=num.zeros(old_div(len(self.edge_coordinates[:,0]),3))
        self.y_centroid_work=num.zeros(old_div(len(self.edge_coordinates[:,0]),3))

        ############################################################################
        ## Local-timestepping information
        #
        # Fluxes can be updated every 1, 2, 4, 8, .. max_flux_update_frequency timesteps
        # The global timestep is not allowed to increase except when
        # number_of_timesteps%max_flux_update_frequency==0
        self.max_flux_update_frequency=2**0 # Must be a power of 2.

        # flux_update_frequency. The edge flux terms are re-computed only when
        #    number_of_timesteps%flux_update_frequency[myEdge]==0
        self.flux_update_frequency=num.zeros(len(self.edge_coordinates[:,0])).astype(int)+1
        # Flag: should we update the flux on the next compute fluxes call?
        self.update_next_flux=num.zeros(len(self.edge_coordinates[:,0])).astype(int)+1
        # Flag: should we update the extrapolation on the next extrapolation call?
        # (Only do this if one or more of the fluxes on that triangle will be computed on
        # the next timestep, assuming only the flux computation uses edge/vertex values)
        self.update_extrapolation=num.zeros(old_div(len(self.edge_coordinates[:,0]),3)).astype(int)+1

        # edge_timestep [wavespeed/radius] -- not updated every timestep
        self.edge_timestep=num.zeros(len(self.edge_coordinates[:,0]))+1.0e+100

        # Do we allow the timestep to increase (not every time if local
        # extrapolation/flux updating is used)
        self.allow_timestep_increase=num.zeros(1).astype(int)+1

    def _set_config_defaults(self):
        """Set the default values in this routine. That way we can inherit class
        and just redefine the defaults for the new class
        """

        from anuga.config import minimum_storable_height
        from anuga.config import minimum_allowed_height, maximum_allowed_speed
        from anuga.config import g
        from anuga.config import tight_slope_limiters
        from anuga.config import extrapolate_velocity_second_order
        from anuga.config import alpha_balance
        from anuga.config import optimise_dry_cells
        from anuga.config import optimised_gradient_limiter
        from anuga.config import use_edge_limiter
        from anuga.config import use_centroid_velocities
        from anuga.config import compute_fluxes_method
        from anuga.config import distribute_to_vertices_and_edges_method
        from anuga.config import sloped_mannings_function
        from anuga.config import low_froude


        # Early algorithms need elevation to remain continuous
        self.set_using_discontinuous_elevation(False)

        self.set_minimum_allowed_height(minimum_allowed_height)
        self.maximum_allowed_speed = maximum_allowed_speed



        self.minimum_storable_height = minimum_storable_height
        self.g = g

        self.alpha_balance = alpha_balance
        self.tight_slope_limiters = tight_slope_limiters

        self.set_low_froude(low_froude)

        self.set_use_optimise_dry_cells(optimise_dry_cells)
        self.set_extrapolate_velocity(extrapolate_velocity_second_order)

        self.set_use_edge_limiter(use_edge_limiter)
        self.optimised_gradient_limiter = optimised_gradient_limiter
        self.use_centroid_velocities = use_centroid_velocities

        self.set_sloped_mannings_function(sloped_mannings_function)
        self.set_compute_fluxes_method(compute_fluxes_method)

        self.set_distribute_to_vertices_and_edges_method(distribute_to_vertices_and_edges_method)

        self.set_store_centroids(False)

    def get_algorithm_parameters(self):
        """
        Get the standard parameter that are currently set (as a dictionary)
        """

        parameters = {}

        parameters['minimum_allowed_height']  = self.minimum_allowed_height
        parameters['maximum_allowed_speed']   = self.maximum_allowed_speed
        parameters['minimum_storable_height'] = self.minimum_storable_height
        parameters['g']                       = self.g
        parameters['alpha_balance']           = self.alpha_balance
        parameters['tight_slope_limiters']    = self.tight_slope_limiters
        parameters['optimise_dry_cells']      = self.optimise_dry_cells
        parameters['use_edge_limiter']        = self.use_edge_limiter
        parameters['low_froude']              = self.low_froude
        parameters['use_centroid_velocities'] = self.use_centroid_velocities
        parameters['use_sloped_mannings']     = self.use_sloped_mannings
        parameters['compute_fluxes_method']   = self.get_compute_fluxes_method()
        parameters['distribute_to_vertices_and_edges_method'] = \
                         self.get_distribute_to_vertices_and_edges_method()
        parameters['flow_algorithm']          = self.get_flow_algorithm()
        parameters['CFL']                     = self.get_CFL()
        parameters['timestepping_method']     = self.get_timestepping_method()

        parameters['optimised_gradient_limiter']        = self.optimised_gradient_limiter
        parameters['extrapolate_velocity_second_order'] = self.extrapolate_velocity_second_order



        return parameters

    def print_algorithm_parameters(self):
        """
        Print the standard parameters that are curently set (as a dictionary)
        """

        print('#============================')
        print('# Domain Algorithm Parameters ')
        print('#============================')
        from pprint import pprint
        pprint(self.get_algorithm_parameters(),indent=4)

        print('#----------------------------')


    def _set_tsunami_defaults(self):
        """Set up the defaults for running the flow_algorithm "tsunami"
        """

        self._set_config_defaults()

        self.set_CFL(1.0)
        #self.set_use_kinematic_viscosity(False)

        self.set_timestepping_method(2)
        self.set_default_order(2)
        self.set_compute_fluxes_method('tsunami')
        self.set_extrapolate_velocity()
        self.set_distribute_to_vertices_and_edges_method('tsunami')
        self.use_edge_limiter=True

        # The following allows storage of the negative depths associated with this method
        self.minimum_storable_height=-99999999999.0


        # Note that the extrapolation method used in quantity_ext.c (e.g.
        # extrapolate_second_order_and_limit_by_edge) uses a constant value for
        # all the betas.
        self.beta_w=1.0
        self.beta_w_dry=1.0
        self.beta_uh=1.0
        self.beta_uh_dry=1.0
        self.beta_vh=1.0
        self.beta_vh_dry=1.0

        #self.optimise_dry_cells=True
        # "self.optimise_dry_cells=False" presently ensures that the stage is
        # always >= minimum_bed_edge value.  Actually, we should only need to
        # apply 'False' on the very first time step (to deal with stage values
        # that were initialised below the bed by the user). After this, the
        # algorithm should take care of itself, and 'True' should be okay.
        self.optimise_dry_cells=False

        # Because gravity is treated within the flux function,
        # we remove it from the forcing terms.
        #self.forcing_terms.remove(gravity)

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        ## (OLD) We demand that vertex values are stored uniquely
        ##self.set_store_vertices_smoothly(False)
        # Now we can just store centroids directly
        self.set_store_centroids(True)

        self.maximum_allowed_speed=0.0
        #self.minimum_allowed_height=0.01

        #self.forcing_terms.append(manning_friction_explicit)
        #self.forcing_terms.remove(manning_friction_implicit)
        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print("#")
            print("# Here are some tips on using the 'tsunami' solver")
            print("#")
            print("# 1) When plotting outputs, I strongly suggest you examine centroid values, not vertex values")
            print("# , as the latter can be completely misleading near strong gradients in the flow. ")
            print("# There is a plot_util.py script in anuga_core/utilities/ which might help you extract")
            print("# quantities at centroid values from sww files.")
            print("# Note that to accuractely compute centroid values from sww files, the files need to store ")
            print("# vertices uniquely. This makes for large sww files (3x), but is the price to pay for the right answer")
            print("# (unless we alter IO to allow centroids to be written to sww files, which would then affect")
            print("# ANUGA viewer as well -- I expect this would be lots of work)")
            print("#")
            print("# 2) In field scale applications (where the depth is typically > 1m), I suggest you set")
            print("# domain.minimum_allowed_height=0.01 (the default is 1.0e-3). ")
            print("#")
            print("# 3) This solver is not expected to perform well in problems with very")
            print("# shallow water flowing down steep slopes (such that the stage_centroid_value ")
            print("# is less than the maximum bed_edge_value on a given triangle). However, analytical tests")
            print("# suggest it can do typical wetting/drying situations very well (parabolic oscillations test case) ")
            print("#")
            print("# 4) This solver allows the stage_centroid_value to drop to slightly below the minimum bed_vertex_value")
            print("# on it's triangle. In other ANUGA versions (e.g. 1.2.1), the limit would be the")
            print("# bed_centroid_value. This means that triangles store slightly more water than they are")
            print("# typically interpreted to store, which might have significance in some applications.")
            print("#")
            print("# You will probably be able to tell this is causing you problems by convergence testing")
            print("#")
            print('# 5) Note that many options in config.py have been overridden by the solver -- we have ')
            print('# deliberately attempted to get the solver to perform well with consistent values of ')
            print('# these parameters -- so I advise against changing them unless you at least check that ')
            print('# it really does improve things')
            print('#')
            print('##########################################################################')



    def _set_1_0_defaults(self):
        """Set up the defaults for running the flow_algorithm "1_0"
           so that users can revert back to old default algorithm
        """


        self._set_config_defaults()

        self.set_timestepping_method(1)
        self.set_default_order(1)
        self.set_CFL(1.0)


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 1_0')
            print('#')
            print('# Uses diffusive first order spatial, first order timestepping')
            print('#')
            print('##########################################################################')



    def _set_1_5_defaults(self):
        """Set up the defaults for running the flow_algorithm "1_5"
           so that users can revert back to old default algorithm
        """

        self._set_config_defaults()

        self.set_timestepping_method(1)
        self.set_default_order(2)
        beta_w      = 1.0
        beta_w_dry  = 0.2
        beta_uh     = 1.0
        beta_uh_dry = 0.2
        beta_vh     = 1.0
        beta_vh_dry = 0.2
        self.set_betas(beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry)
        self.set_CFL(1.0)
        self.set_compute_fluxes_method('wb_2')
        self.set_extrapolate_velocity()


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 1_5')
            print('#')
            print('# Uses diffusive second order spatial, first order timestepping')
            print('#')
            print('##########################################################################')


    def _set_1_75_defaults(self):
        """Set up the defaults for running the flow_algorithm "1_75"
           so that users can revert back to old default algorithm
        """


        self._set_config_defaults()

        self.set_timestepping_method(1)
        self.set_default_order(2)
        beta_w      = 1.5
        beta_w_dry  = 0.2
        beta_uh     = 1.5
        beta_uh_dry = 0.2
        beta_vh     = 1.5
        beta_vh_dry = 0.2
        self.set_betas(beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry)
        self.set_CFL(0.75)
        self.set_compute_fluxes_method('wb_2')
        self.set_extrapolate_velocity()


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 1_75')
            print('#')
            print('# Uses less diffusive second order spatial, first order timestepping')
            print('#')
            print('##########################################################################')

    def _set_2_0_limited_defaults(self):
        """Set up the defaults for running the flow_algorithm "2_limited"
           so that users can revert back to old default algorithm
        """

        self._set_config_defaults()

        self.set_timestepping_method(2)
        self.set_default_order(2)
        beta_w      = 1.5
        beta_w_dry  = 0.2
        beta_uh     = 1.5
        beta_uh_dry = 0.2
        beta_vh     = 1.5
        beta_vh_dry = 0.2
        self.set_betas(beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry)
        self.set_CFL(1.0)
        self.set_compute_fluxes_method('wb_2')
        self.set_extrapolate_velocity()


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 2_0_limited')
            print('#')
            print('# Uses diffusive second order spatial, second order timestepping')
            print('#')
            print('##########################################################################')


    def _set_2_0_defaults(self):
        """Set up the defaults for running the flow_algorithm "2_0"
           so that users can revert back to old default algorithm
        """

        self._set_config_defaults()

        self.set_timestepping_method(2)
        self.set_default_order(2)
        beta_w      = 1.9
        beta_w_dry  = 0.2
        beta_uh     = 1.9
        beta_uh_dry = 0.2
        beta_vh     = 1.9
        beta_vh_dry = 0.2
        self.set_betas(beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry)
        self.set_CFL(1.0)
        self.set_compute_fluxes_method('wb_2')
        self.set_extrapolate_velocity()

        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 2_0')
            print('#')
            print('# Uses second order spatial, second order timestepping')
            print('#')
            print('##########################################################################')

    def _set_2_5_defaults(self):
        """Set up the defaults for running the flow_algorithm "2_0"
           so that users can revert back to old default algorithm
        """

        self._set_config_defaults()

        self.set_timestepping_method(3)
        self.set_default_order(2)
        beta_w      = 1.9
        beta_w_dry  = 0.2
        beta_uh     = 1.9
        beta_uh_dry = 0.2
        beta_vh     = 1.9
        beta_vh_dry = 0.2
        self.set_betas(beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry)
        self.set_CFL(1.0)
        self.set_compute_fluxes_method('wb_2')
        self.set_extrapolate_velocity()


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using continuous elevation solver 2_5')
            print('#')
            print('# Uses second order spatial, third order timestepping')
            print('#')
            print('##########################################################################')

    def _set_DE0_defaults(self):
        """Set up the defaults for running the flow_algorithm "DE0"
           A 'discontinuous elevation' method
        """

        self._set_config_defaults()

        self.set_CFL(0.9)
        self.set_use_kinematic_viscosity(False)
        #self.timestepping_method='rk2'#'rk3'#'euler'#'rk2'
        self.set_timestepping_method('euler')

        self.set_using_discontinuous_elevation(True)
        self.set_compute_fluxes_method('DE')
        self.set_distribute_to_vertices_and_edges_method('DE')

        # Don't place any restriction on the minimum storable height
        #self.minimum_storable_height=-99999999999.0
        self.minimum_allowed_height=1.0e-12

        self.use_edge_limiter=True
        self.set_default_order(2)
        self.set_extrapolate_velocity()

        self.beta_w=0.5
        self.beta_w_dry=0.0
        self.beta_uh=0.5
        self.beta_uh_dry=0.0
        self.beta_vh=0.5
        self.beta_vh_dry=0.0


        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 2, 'height':2})
        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 1})
        self.set_store_centroids(True)

        self.optimise_dry_cells=False

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        # By default vertex values are NOT stored uniquely
        # for storage efficiency. We may override this (but not so important since
        # centroids are stored anyway
        # self.set_store_vertices_smoothly(False)

        self.maximum_allowed_speed=0.0

        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using discontinuous elevation solver DE0')
            print('#')
            print('# First order timestepping')
            print('#')
            print('# Make sure you use centroid values when reporting on important output quantities')
            print('#')
            print('##########################################################################')


    def _set_DE1_defaults(self):
        """Set up the defaults for running the flow_algorithm "DE1"
           A 'discontinuous elevation' method
        """

        self._set_config_defaults()

        self.set_CFL(1.0)
        self.set_use_kinematic_viscosity(False)
        #self.timestepping_method='rk2'#'rk3'#'euler'#'rk2'
        self.set_timestepping_method(2)

        self.set_using_discontinuous_elevation(True)
        self.set_compute_fluxes_method('DE')
        self.set_distribute_to_vertices_and_edges_method('DE')

        # Don't place any restriction on the minimum storable height
        #self.minimum_storable_height=-99999999999.0
        self.minimum_allowed_height=1.0e-5

        self.use_edge_limiter=True
        self.set_default_order(2)
        self.set_extrapolate_velocity()

        self.beta_w=1.0
        self.beta_w_dry=0.0
        self.beta_uh=1.0
        self.beta_uh_dry=0.0
        self.beta_vh=1.0
        self.beta_vh_dry=0.0


        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 2, 'height':2})
        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 1})
        self.set_store_centroids(True)

        self.optimise_dry_cells=False

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        # By default vertex values are NOT stored uniquely
        # for storage efficiency. We may override this (but not so important since
        # centroids are stored anyway
        # self.set_store_vertices_smoothly(False)

        self.maximum_allowed_speed=0.0


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using discontinuous elevation solver DE1 ')
            print('#')
            print('# Uses rk2 timestepping')
            print('#')
            print('# Make sure you use centroid values when reporting on important output quantities')
            print('#')
            print('##########################################################################')

    def _set_DE2_defaults(self):
        """Set up the defaults for running the flow_algorithm "DE2"
           A 'discontinuous elevation' method
        """

        self._set_config_defaults()

        self.set_CFL(1.0)
        self.set_use_kinematic_viscosity(False)
        #self.timestepping_method='rk2'#'rk3'#'euler'#'rk2'
        self.set_timestepping_method(3)

        self.set_using_discontinuous_elevation(True)
        self.set_compute_fluxes_method('DE')
        self.set_distribute_to_vertices_and_edges_method('DE')

        # Don't place any restriction on the minimum storable height
        #self.minimum_storable_height=-99999999999.0
        self.minimum_allowed_height=1.0e-5

        self.use_edge_limiter=True
        self.set_default_order(2)
        self.set_extrapolate_velocity()

        self.beta_w=1.0
        self.beta_w_dry=0.0
        self.beta_uh=1.0
        self.beta_uh_dry=0.0
        self.beta_vh=1.0
        self.beta_vh_dry=0.0


        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 2, 'height':2})
        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 1})
        self.set_store_centroids(True)

        self.optimise_dry_cells=False

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        # By default vertex values are NOT stored uniquely
        # for storage efficiency. We may override this (but not so important since
        # centroids are stored anyway
        # self.set_store_vertices_smoothly(False)

        self.maximum_allowed_speed=0.0


        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using discontinuous elevation solver DE2')
            print('#')
            print('# Using rk3 timestepping')
            print('#')
            print('# Make sure you use centroid values when reporting on important output quantities')
            print('#')
            print('##########################################################################')

    def _set_DE1_7_defaults(self):
        """Set up the defaults for running the flow_algorithm "DE0_7"
           A 'discontinuous elevation' method
        """

        self._set_config_defaults()

        self.set_CFL(1.0)
        self.set_use_kinematic_viscosity(False)
        #self.timestepping_method='rk2'#'rk3'#'euler'#'rk2'
        self.set_timestepping_method(2)

        self.set_using_discontinuous_elevation(True)
        self.set_compute_fluxes_method('DE')
        self.set_distribute_to_vertices_and_edges_method('DE')

        # Don't place any restriction on the minimum storable height
        #self.minimum_storable_height=-99999999999.0
        self.minimum_allowed_height=1.0e-12

        self.use_edge_limiter=True
        self.set_default_order(2)
        self.set_extrapolate_velocity()

        self.beta_w=0.75
        self.beta_w_dry=0.1
        self.beta_uh=0.75
        self.beta_uh_dry=0.1
        self.beta_vh=0.75
        self.beta_vh_dry=0.1


        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 2, 'height':2})
        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 1})
        self.set_store_centroids(True)

        self.optimise_dry_cells=False

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        # By default vertex values are NOT stored uniquely
        # for storage efficiency. We may override this (but not so important since
        # centroids are stored anyway
        # self.set_store_vertices_smoothly(False)

        self.maximum_allowed_speed=0.0

        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using discontinuous elevation solver DE1_7 ')
            print('#')
            print('# A slightly more diffusive version of DE1, does use rk2 timestepping')
            print('#')
            print('# Make sure you use centroid values when reporting on important output quantities')
            print('#')
            print('##########################################################################')


    def _set_DE0_7_defaults(self):
        """Set up the defaults for running the flow_algorithm "DE3"
           A 'discontinuous elevation' method
        """

        self._set_config_defaults()

        self.set_CFL(0.9)
        self.set_use_kinematic_viscosity(False)
        #self.timestepping_method='rk2'#'rk3'#'euler'#'rk2'
        self.set_timestepping_method(1)

        self.set_using_discontinuous_elevation(True)
        self.set_compute_fluxes_method('DE')
        self.set_distribute_to_vertices_and_edges_method('DE')

        # Don't place any restriction on the minimum storable height
        #self.minimum_storable_height=-99999999999.0
        self.minimum_allowed_height=1.0e-12

        self.use_edge_limiter=True
        self.set_default_order(2)
        self.set_extrapolate_velocity()

        self.beta_w=0.7
        self.beta_w_dry=0.1
        self.beta_uh=0.7
        self.beta_uh_dry=0.1
        self.beta_vh=0.7
        self.beta_vh_dry=0.1


        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 2, 'height':2})
        #self.set_quantities_to_be_stored({'stage': 2, 'xmomentum': 2,
        #         'ymomentum': 2, 'elevation': 1})
        self.set_store_centroids(True)

        self.optimise_dry_cells=False

        # We need the edge_coordinates for the extrapolation
        self.edge_coordinates=self.get_edge_midpoint_coordinates()

        # By default vertex values are NOT stored uniquely
        # for storage efficiency. We may override this (but not so important since
        # centroids are stored anyway
        # self.set_store_vertices_smoothly(False)

        self.maximum_allowed_speed=0.0

        if self.processor == 0 and self.verbose:
            print('##########################################################################')
            print('#')
            print('# Using discontinuous elevation solver DE0_7')
            print('#')
            print('# A slightly less diffusive version than DE0, uses euler timestepping')
            print('#')
            print('# Make sure you use centroid values when reporting on important output quantities')
            print('#')
            print('##########################################################################')



    def update_special_conditions(self):

        my_update_special_conditions(self)

    # Note Padarn 06/12/12: The following line decorates
    # the set_quantity function to be profiled individually.
    # Need to uncomment the decorator at top of file.
    #@profileit("set_quantity.profile")
    def set_quantity(self, name, *args, **kwargs):
        """Set values for named quantity

        We have to do something special for 'elevation'
        otherwise pass through to generic set_quantity
        """

#        if name == 'elevation':
#            stage_c = self.get_quantity('stage').centroid_values
#            elev_c =  self.get_quantity('elevation').centroid_values
#            height_c = stage_c - elev_c
#            Generic_Domain.set_quantity(self, name, *args, **kwargs)
#            stage_c[:] = elev_c + height_c
#        else:
#            Generic_Domain.set_quantity(self, name, *args, **kwargs)

        Generic_Domain.set_quantity(self, name, *args, **kwargs)


    def set_store(self, flag=True):
        """Set whether data saved to sww file.
        """

        self.store = flag

    def get_store(self):
        """Get whether data saved to sww file.
        """

        return self.store


    def set_store_centroids(self, flag=True):
        """Set whether centroid data is saved to sww file.
        """

        self.store_centroids = flag

    def get_store_centroids(self):
        """Get whether data saved to sww file.
        """

        return self.store_centroids

    def set_checkpointing(self, checkpoint= True, checkpoint_dir = 'CHECKPOINTS', checkpoint_step=10, checkpoint_time = None):
        """
        Set up checkpointing.

        @param checkpoint: Default = True. Set to False will tur off checkpointing
        @param checkpoint_dir: Where to store checkpointing files
        @param checkpoint_step: Save checkpoint files after this many yieldsteps
        @param checkpoint_time: If set, over-rides checkpoint_step. save checkpoint files
                        after this amount of walltime
        """



        if checkpoint:
            # create checkpoint directory if necessary
            if not os.path.exists(checkpoint_dir):
                os.mkdir(checkpoint_dir)

            assert os.path.exists(checkpoint_dir)
            self.checkpoint_dir = checkpoint_dir
            if checkpoint_time is not None:
                #import time
                self.walltime_prev = time.time()
                self.checkpoint_time = checkpoint_time
                self.checkpoint_step = 0
            else:
                self.checkpoint_step = checkpoint_step
            self.checkpoint = True
            #print(self.checkpoint_dir, self.checkpoint_step)
        else:
            self.checkpoint = False

    def set_sloped_mannings_function(self, flag=True):
        """Set mannings friction function to use the sloped
        wetted area.

        The flag is tested in the python wrapper
        mannings_friction_implicit
        """
        if flag:
            self.use_sloped_mannings = True
        else:
            self.use_sloped_mannings = False


    def set_compute_fluxes_method(self, flag='original'):
        """Set method for computing fluxes.

        Currently
           original
           wb_1
           wb_2
           wb_3
           tsunami
           DE
        """
        compute_fluxes_methods = ['original', 'wb_1', 'wb_2', 'wb_3', 'tsunami', 'DE']

        if flag in compute_fluxes_methods:
            self.compute_fluxes_method = flag
        else:
            msg = 'Unknown compute_fluxes_method. \nPossible choices are:\n'+ \
            ', '.join(compute_fluxes_methods)+'.'
            raise Exception(msg)


    def set_local_extrapolation_and_flux_updating(self,nlevels=8):
        """
            Use local flux and extrapolation updating

            nlevels == number of flux_update_frequency levels > 1

                   For example, to allow flux updating every 1,2,4,8
                   timesteps, do:

                    domain.set_local_extrapolation_and_flux_updating(nlevels=3)

                   (since 2**3==8)
        """

        self.max_flux_update_frequency=2**nlevels

        if(self.max_flux_update_frequency != 1):
            if self.timestepping_method != 'euler':
                raise Exception('Local extrapolation and flux updating only supported with euler timestepping')
            if self.compute_fluxes_method != 'DE':
                raise Exception('Local extrapolation and flux updating only supported for discontinuous flow algorithms')


    def get_compute_fluxes_method(self):
        """Get method for computing fluxes.

        See set_compute_fluxes_method for possible choices.
        """

        return self.compute_fluxes_method



    def set_distribute_to_vertices_and_edges_method(self, flag='original'):
        """Set method for computing fluxes.

        Currently
           original
           tsunami
        """
        distribute_to_vertices_and_edges_methods = ['original',  'tsunami', 'DE']

        if flag in distribute_to_vertices_and_edges_methods:
            self.distribute_to_vertices_and_edges_method = flag
        else:
            msg = 'Unknown distribute_to_vertices_and_edges_method. \nPossible choices are:\n'+ \
            ', '.join(distribute_to_vertices_and_edges_methods)+'.'
            raise Exception(msg)





    def get_distribute_to_vertices_and_edges_method(self):
        """Get method for distribute_to_vertices_and_edges.

        See set_distribute_to_vertices_and_edges_method for possible choices.
        """

        return self.distribute_to_vertices_and_edges_method





    def set_flow_algorithm(self, flag='DE0'):
        """Set combination of slope limiting and time stepping

        Currently
           1
           1.5
           2
           2.5
           tsunami
           DE0
           DE1
           DE2
           DE0_7
           DE1_7
        """

        # FIXME(Ole): flag should be called algorithm ;-)
        flag = str(flag)

        # Replace any dots with dashes
        flag = flag.replace(".","_")


        flow_algorithms = ['1_0', '1_5', '1_75', '2_0', '2_0_limited', '2_5', \
                           'tsunami', 'yusuke', 'DE0', 'DE1', 'DE2', \
                           'DE0_7', "DE1_7"]

        if flag in flow_algorithms:
            self.flow_algorithm = flag
        else:
            msg = 'Unknown flow_algorithm. \nPossible choices are:\n'+ \
            ', '.join(flow_algorithms)+'.'
            raise Exception(msg)

        if self.flow_algorithm == '1_0':
            self._set_1_0_defaults()

        if self.flow_algorithm == '1_5':
            self._set_1_5_defaults()

        if self.flow_algorithm == '1_75':
            self._set_1_75_defaults()

        if self.flow_algorithm == '2_0_limited':
            self._set_2_0_limited_defaults()


        if self.flow_algorithm == '2_0':
            self._set_2_0_defaults()


        if self.flow_algorithm == '2_5':
            self._set_2_5_defaults()


        if self.flow_algorithm == 'tsunami':
            self._set_tsunami_defaults()


        if self.flow_algorithm == 'yusuke':
            # To speed up calculation we also turn off
            # the update of other quantities

            self._set_tsunami_defaults()




        if self.flow_algorithm == 'DE0':
            self._set_DE0_defaults()

        if self.flow_algorithm == 'DE1':
            self._set_DE1_defaults()

        if self.flow_algorithm == 'DE2':
            self._set_DE2_defaults()

        if self.flow_algorithm == 'DE0_7':
            self._set_DE0_7_defaults()

        if self.flow_algorithm == 'DE1_7':
            self._set_DE1_7_defaults()


    def get_flow_algorithm(self):
        """
        Get method used for timestepping and spatial discretisation

        """

        return self.flow_algorithm


    def set_gravity_method(self):
        """Gravity method is determined by the compute_fluxes_method
        This is now not used, as gravity is combine in the compute_fluxes method
        """

        if  self.get_compute_fluxes_method() == 'original':
            self.forcing_terms[0] = gravity

        elif self.get_compute_fluxes_method() == 'wb_1':
            self.forcing_terms[0] = gravity_wb

        elif self.get_compute_fluxes_method() == 'wb_2':
            self.forcing_terms[0] = gravity

        else:
            raise Exception('undefined compute_fluxes method')

    def set_extrapolate_velocity(self, flag=True):
        """ Extrapolation routine uses momentum by default,
        can change to velocity extrapolation which
        seems to work better.
        """

        if flag is True:
            self.extrapolate_velocity_second_order = True
        elif flag is False:
            self.extrapolate_velocity_second_order = False

    def set_use_edge_limiter(self, flag=True):
        """ Extrapolation routine uses vertex values by default,
        for limiting, can change to edge limiting which
        seems to work better in some cases.
        """

        if flag is True:
            self.use_edge_limiter = True
        elif flag is False:
            self.use_edge_limiter = False

    def set_low_froude(self, low_froude=0):
        """ For low Froude problems the standard flux calculations
        can lead to excessive damping. Set low_froude to 1 or 2 for
        flux calculations which minimize the damping in this case.
        """

        assert low_froude in [0,1,2]

        self.low_froude = low_froude

    def set_use_optimise_dry_cells(self, flag=True):
        """ Try to optimize calculations where region is dry
        """

        if flag is True:
            self.optimise_dry_cells = int(True)
        elif flag is False:
            self.optimise_dry_cells = int(False)




    def set_use_kinematic_viscosity(self, flag=True):

        from anuga.operators.kinematic_viscosity_operator import Kinematic_viscosity_operator

        if flag :
            # Create Operator if necessary
            if self.kv_operator is None:
                self.kv_operator = Kinematic_viscosity_operator(self)
        else:
            if self.kv_operator is None:
                return
            else:
                # Remove operator from fractional_step_operators
                self.fractional_step_operators.remove(self.kv_operator)
                self.kv_operator = None





    def set_beta(self, beta):
        """Shorthand to assign one constant value [0,2] to all limiters.
        0 Corresponds to first order, where as larger values make use of
        the second order scheme.
        """

        self.beta_w = beta
        self.beta_w_dry = beta
        self.quantities['stage'].beta = beta

        self.beta_uh = beta
        self.beta_uh_dry = beta
        self.quantities['xmomentum'].beta = beta

        self.beta_vh = beta
        self.beta_vh_dry = beta
        self.quantities['ymomentum'].beta = beta


    def set_betas(self, beta_w, beta_w_dry, beta_uh, beta_uh_dry, beta_vh, beta_vh_dry):
        """Assign beta values in the range  [0,2] to all limiters.
        0 Corresponds to first order, where as larger values make use of
        the second order scheme.
        """

        self.beta_w = beta_w
        self.beta_w_dry = beta_w_dry
        self.quantities['stage'].beta = beta_w

        self.beta_uh = beta_uh
        self.beta_uh_dry = beta_uh_dry
        self.quantities['xmomentum'].beta = beta_uh

        self.beta_vh = beta_vh
        self.beta_vh_dry = beta_vh_dry
        self.quantities['ymomentum'].beta = beta_vh




    def set_store_vertices_uniquely(self, flag=True, reduction=None):
        """Decide whether vertex values should be stored uniquely as
        computed in the model (True) or whether they should be reduced to one
        value per vertex using self.reduction (False).
        """

        # FIXME (Ole): how about using the word "continuous vertex values" or
        # "continuous stage surface"
        self.smooth = not flag

        # Reduction operation for get_vertex_values
        if reduction is None:
            self.reduction = mean
            #self.reduction = min  #Looks better near steep slopes

    def set_store_vertices_smoothly(self, flag=True, reduction=None):
        """Decide whether vertex values should be stored smoothly (one value per vertex)
        or uniquely as
        computed in the model (False).
        """

        # FIXME (Ole): how about using the word "continuous vertex values" or
        # "continuous stage surface"
        self.smooth = flag

        # Reduction operation for get_vertex_values
        if reduction is None:
            self.reduction = mean
            #self.reduction = min  #Looks better near steep slopes

    def set_minimum_storable_height(self, minimum_storable_height):
        """Set the minimum depth that will be written to an SWW file.

        minimum_storable_height  minimum allowed SWW depth is in meters

        This is useful for removing thin water layers that seems to be caused
        by friction creep.
        """

        self.minimum_storable_height = minimum_storable_height


    def get_minimum_storable_height(self):

        return self.minimum_storable_height


    def set_minimum_allowed_height(self, minimum_allowed_height):
        """Set minimum depth that will be recognised in the numerical scheme.

        minimum_allowed_height  minimum allowed depth in meters

        The parameter H0 (Minimal height for flux computation) is also set by
        this function.
        """

        #FIXME (Ole): rename H0 to minimum_allowed_height_in_flux_computation

        #FIXME (Ole): Maybe use histogram to identify isolated extreme speeds
        #and deal with them adaptively similarly to how we used to use 1 order
        #steps to recover.

        self.minimum_allowed_height = minimum_allowed_height
        self.H0 = minimum_allowed_height



    def get_minimum_allowed_height(self):

        return self.minimum_allowed_height

    def set_maximum_allowed_speed(self, maximum_allowed_speed):
        """Set the maximum particle speed that is allowed in water shallower
        than minimum_allowed_height.

        maximum_allowed_speed

        This is useful for controlling speeds in very thin layers of water and
        at the same time allow some movement avoiding pooling of water.
        """

        self.maximum_allowed_speed = maximum_allowed_speed

    def set_points_file_block_line_size(self, points_file_block_line_size):
        """
        """

        self.points_file_block_line_size = points_file_block_line_size


    # FIXME: Probably obsolete in its curren form
    def set_quantities_to_be_stored(self, q):
        """Specify which quantities will be stored in the SWW file.

        q must be either:
          - a dictionary with quantity names
          - a list of quantity names (for backwards compatibility)
          - None

        The format of the dictionary is as follows

        quantity_name: flag where flag must be either 1 or 2.
        If flag is 1, the quantity is considered static and will be
        stored once at the beginning of the simulation in a 1D array.

        If flag is 2, the quantity is considered time dependent and
        it will be stored at each yieldstep by appending it to the
        appropriate 2D array in the sww file.

        If q is None, storage will be switched off altogether.

        Once the simulation has started and thw sww file opened,
        this function will have no effect.

        The format, where q is a list of names is for backwards compatibility
        only.
        It will take the specified quantities to be time dependent and assume
        'elevation' to be static regardless.
        """

        if q is None:
            self.quantities_to_be_stored = {}
            self.store = False
            return

        # Check correctness
        for quantity_name in q:
            msg = ('Quantity %s is not a valid conserved quantity'
                   % quantity_name)
            assert quantity_name in self.quantities, msg

        assert isinstance(q, dict)
        self.quantities_to_be_stored = q

    def get_wet_elements(self, indices=None, minimum_height=None):
        """Return indices for elements where h > minimum_allowed_height

        Optional argument:
            indices is the set of element ids that the operation applies to.

        Usage:
            indices = get_wet_elements()

        Note, centroid values are used for this operation
        """

        # Water depth below which it is considered to be 0 in the model
        # FIXME (Ole): Allow this to be specified as a keyword argument as well
        from anuga.config import minimum_allowed_height

        if minimum_height is None:
            minimum_height = minimum_allowed_height

        elevation = self.get_quantity('elevation').\
                        get_values(location='centroids', indices=indices)
        stage = self.get_quantity('stage').\
                    get_values(location='centroids', indices=indices)
        depth = stage - elevation

        # Select indices for which depth > 0
        wet_indices = num.compress(depth > minimum_height,
                                   num.arange(len(depth)))
        return wet_indices

    def get_maximum_inundation_elevation(self, indices=None, minimum_height=None):
        """Return highest elevation where h > 0

        Optional argument:
            indices is the set of element ids that the operation applies to.
            minimum_height for testing h > minimum_height
        Usage:
            q = get_maximum_inundation_elevation()

        Note, centroid values are used for this operation
        """

        wet_elements = self.get_wet_elements(indices, minimum_height)
        return self.get_quantity('elevation').\
                   get_maximum_value(indices=wet_elements)

    def get_maximum_inundation_location(self, indices=None):
        """Return location of highest elevation where h > 0

        Optional argument:
            indices is the set of element ids that the operation applies to.

        Usage:
            q = get_maximum_inundation_location()

        Note, centroid values are used for this operation
        """

        wet_elements = self.get_wet_elements(indices)
        return self.get_quantity('elevation').\
                   get_maximum_location(indices=wet_elements)


    def get_water_volume(self):

        from anuga import numprocs

        #print self.evolved_called

        if not self.evolved_called:
            Stage = self.quantities['stage']
            Elev =  self.quantities['elevation']
            h_c = Stage.centroid_values - Elev.centroid_values
            #print h_c
            from anuga import Quantity
            Height = Quantity(self)
            Height.set_values(h_c, location='centroids')
            #print Height.centroid_values
            volume = Height.get_integral()
        elif self.get_using_discontinuous_elevation():
            Height = self.quantities['height']
            volume = Height.get_integral()
        else:
            Stage = self.quantities['stage']
            Elev =  self.quantities['elevation']
            Height = Stage-Elev
            volume = Height.get_integral()

        if numprocs == 1:
            self.volume_history.append(volume)
            return volume

        # isolated parallel code
        from anuga import myid, send, receive, barrier

        if myid == 0:
            water_volume = volume
            for i in range(1,numprocs):
                remote_volume = receive(i)
                water_volume = water_volume + remote_volume
        else:
            send(volume,0)

        #barrier()

        if myid == 0:
            for i in range(1,numprocs):
                send(water_volume,i)
        else:
            water_volume = receive(0)

        self.volume_history.append(water_volume)
        return water_volume

    def get_boundary_flux_integral(self):
        """
            Compute the boundary flux integral.
            Should work in parallel
        """

        from anuga import numprocs

        if not self.compute_fluxes_method=='DE':
            msg='Boundary flux integral only supported for DE fluxes '+\
                '(because computation of boundary_flux_sum is only implemented there)'
            raise_(Exception, msg)

        flux_integral = self.boundary_flux_integral.boundary_flux_integral[0]

        if numprocs == 1:
            return flux_integral

        # isolate parallel code
        from anuga import myid, send, receive, barrier

        if myid == 0:
            for i in range(1,numprocs):
                remote_flux_integral = receive(i)
                flux_integral = flux_integral + remote_flux_integral
        else:
            send(flux_integral,0)

        #barrier()

        if myid == 0:
            for i in range(1,numprocs):
                send(flux_integral,i)
        else:
            flux_integral = receive(0)

        return flux_integral

    def get_fractional_step_volume_integral(self):
        """
            Compute the integrated flows from fractional steps
            This requires that the fractional step operators
              update the fractional_step_volume_integral
            Should work in parallel
        """

        from anuga import numprocs

        flux_integral = self.fractional_step_volume_integral

        if numprocs == 1:
            return flux_integral

        # isolate parallel code
        from anuga import myid, send, receive, barrier

        if myid == 0:
            for i in range(1,numprocs):
                remote_flux_integral = receive(i)
                flux_integral = flux_integral + remote_flux_integral
        else:
            send(flux_integral,0)

        #barrier()

        if myid == 0:
            for i in range(1,numprocs):
                send(flux_integral,i)
        else:
            flux_integral = receive(0)

        return flux_integral

    def get_flow_through_cross_section(self, polyline, verbose=False):
        """Get the total flow through an arbitrary poly line.

        This is a run-time equivalent of the function with same name
        in sww_interrogate.py

        Input:
            polyline: Representation of desired cross section - it may contain
                      multiple sections allowing for complex shapes. Assume
                      absolute UTM coordinates.
                      Format [[x0, y0], [x1, y1], ...]

        Output:
            Q: Total flow [m^3/s] across given segments.
        """


        cross_section = Cross_section(self, polyline, verbose)

        return cross_section.get_flow_through_cross_section()


    def get_energy_through_cross_section(self, polyline,
                                         kind='total',
                                         verbose=False):
        """Obtain average energy head [m] across specified cross section.

        Inputs:
            polyline: Representation of desired cross section - it may contain
                      multiple sections allowing for complex shapes. Assume
                      absolute UTM coordinates.
                      Format [[x0, y0], [x1, y1], ...]
            kind:     Select which energy to compute.
                      Options are 'specific' and 'total' (default)

        Output:
            E: Average energy [m] across given segments for all stored times.

        The average velocity is computed for each triangle intersected by
        the polyline and averaged weighted by segment lengths.

        The typical usage of this function would be to get average energy of
        flow in a channel, and the polyline would then be a cross section
        perpendicular to the flow.

        #FIXME (Ole) - need name for this energy reflecting that its dimension
        is [m].
        """



        cross_section = Cross_section(self, polyline, verbose)

        return cross_section.get_energy_through_cross_section(kind)


    def check_integrity(self):
        """ Run integrity checks on shallow water domain. """
        Generic_Domain.check_integrity(self)

        #Check that we are solving the shallow water wave equation
        msg = 'First conserved quantity must be "stage"'
        assert self.conserved_quantities[0] == 'stage', msg
        msg = 'Second conserved quantity must be "xmomentum"'
        assert self.conserved_quantities[1] == 'xmomentum', msg
        msg = 'Third conserved quantity must be "ymomentum"'
        assert self.conserved_quantities[2] == 'ymomentum', msg


    #@profile
    def extrapolate_second_order_sw(self):
        """Fast version of extrapolation from centroids to edges"""

        from .shallow_water_ext import extrapolate_second_order_sw as extrapol2
        extrapol2(self)

    #@profile
    def compute_fluxes(self):
        """Compute fluxes and timestep suitable for all volumes in domain.

        Compute total flux for each conserved quantity using "flux_function"

        Fluxes across each edge are scaled by edgelengths and summed up
        Resulting flux is then scaled by area and stored in
        explicit_update for each of the three conserved quantities
        stage, xmomentum and ymomentum

        The maximal allowable speed computed by the flux_function for each volume
        is converted to a timestep that must not be exceeded. The minimum of
        those is computed as the next overall timestep.

        Post conditions:
          domain.explicit_update is reset to computed flux values
          domain.flux_timestep is set to the largest step satisfying all volumes.

        This wrapper calls the underlying C version of compute fluxes
        """

        if self.compute_fluxes_method == 'original':
            from .shallow_water_ext import compute_fluxes_ext_central_structure
            from .shallow_water_ext import gravity as gravity_c

            self.flux_timestep = compute_fluxes_ext_central_structure(self)
            gravity_c(self)

        elif self.compute_fluxes_method == 'wb_1':
            # Calc pressure terms using Simpson rule in flux
            # computations. Then they match up exactly with
            # standard gravity term - g h grad(z)
            from .shallow_water_ext import compute_fluxes_ext_wb
            from .shallow_water_ext import gravity as gravity_c

            self.flux_timestep = compute_fluxes_ext_wb(self)
            gravity_c(self)

        elif self.compute_fluxes_method == 'wb_2':
            # Use standard flux calculation, but calc gravity
            # as -g h grad(w) - sum midpoint edge pressure terms

            from .shallow_water_ext import compute_fluxes_ext_central_structure
            from .shallow_water_ext import gravity_wb as gravity_wb_c

            self.flux_timestep = compute_fluxes_ext_central_structure(self)
            gravity_wb_c(self)


        elif self.compute_fluxes_method == 'wb_3':
            # Calculate pure flux terms with simpsons rule, and
            # gravity flux and gravity forcing via
            # as -g h grad(w) - sum midpoint edge pressure terms
            from .shallow_water_ext import compute_fluxes_ext_wb_3
            from .shallow_water_ext import gravity_wb as gravity_wb_c

            self.flux_timestep = compute_fluxes_ext_wb_3(self)
            gravity_wb_c(self)

        elif self.compute_fluxes_method == 'tsunami':
            # Using Gareth Davies well balanced scheme
            # Flux calculation and gravity incorporated in same
            # procedure
            #
            # FIXME SR: This needs cleaning up, should just be passing through
            # the domain as in other compute flux calls

            from .swb2_domain_ext import compute_fluxes_ext_central \
                                      as compute_fluxes_ext

            # Shortcuts
            Stage = self.quantities['stage']
            Xmom = self.quantities['xmomentum']
            Ymom = self.quantities['ymomentum']
            Bed = self.quantities['elevation']

            timestep = self.evolve_max_timestep

            self.flux_timestep = compute_fluxes_ext(timestep,
                                           self.epsilon,
                                           self.H0,
                                           self.g,
                                           self.neighbours,
                                           self.neighbour_edges,
                                           self.normals,
                                           self.edgelengths,
                                           self.radii,
                                           self.areas,
                                           self.tri_full_flag,
                                           Stage.edge_values,
                                           Xmom.edge_values,
                                           Ymom.edge_values,
                                           Bed.edge_values,
                                           Stage.boundary_values,
                                           Xmom.boundary_values,
                                           Ymom.boundary_values,
                                           self.boundary_flux_type,
                                           Stage.explicit_update,
                                           Xmom.explicit_update,
                                           Ymom.explicit_update,
                                           self.already_computed_flux,
                                           self.max_speed,
                                           int(self.optimise_dry_cells),
                                           Stage.centroid_values,
                                           Bed.centroid_values,
                                           Bed.vertex_values)

        elif self.compute_fluxes_method == 'DE':
            # Using Gareth Davies discontinuous elevation scheme
            # Flux calculation and gravity incorporated in same
            # procedure

            from .swDE1_domain_ext import compute_fluxes_ext_central \
                                      as compute_fluxes_ext

            timestep = self.evolve_max_timestep

            flux_timestep = compute_fluxes_ext(self, timestep)

            self.flux_timestep = flux_timestep

        else:
            raise Exception('unknown compute_fluxes_method')

            # TODO (SR)
            # Should implement wb_4 as simpsons rule on both pure
            # flux and pressure flux terms, ie a combination of wb_1
            # and wb_3
            # Mabe should come up with better names!




    def distribute_to_vertices_and_edges(self):
        """ Call correct module function """



        if self.compute_fluxes_method == 'tsunami':


            # FIXME SR: Clean up code to just take self (domain) as
            # input argument
            from .swb2_domain_ext import protect

            # shortcuts
            wc = self.quantities['stage'].centroid_values
            wv = self.quantities['stage'].vertex_values
            zc = self.quantities['elevation'].centroid_values
            zv = self.quantities['elevation'].vertex_values
            xmomc = self.quantities['xmomentum'].centroid_values
            ymomc = self.quantities['ymomentum'].centroid_values
            areas = self.areas

            mass_error = protect(self.minimum_allowed_height, self.maximum_allowed_speed,
                self.epsilon, wc, wv, zc,zv, xmomc, ymomc, areas)

            if mass_error > 0.0 and self.verbose :
                print('Cumulative mass protection: %g m^3 '% mass_error)


            from .swb2_domain_ext import extrapolate_second_order_edge_sw as extrapol2_ext

            # Shortcuts
            Stage = self.quantities['stage']
            Xmom = self.quantities['xmomentum']
            Ymom = self.quantities['ymomentum']
            Elevation = self.quantities['elevation']

            extrapol2_ext(self,
                  self.surrogate_neighbours,
                  self.number_of_boundaries,
                  self.centroid_coordinates,
                  Stage.centroid_values,
                  Xmom.centroid_values,
                  Ymom.centroid_values,
                  Elevation.centroid_values,
                  self.edge_coordinates,
                  Stage.edge_values,
                  Xmom.edge_values,
                  Ymom.edge_values,
                  Elevation.edge_values,
                  Stage.vertex_values,
                  Xmom.vertex_values,
                  Ymom.vertex_values,
                  Elevation.vertex_values,
                  int(self.optimise_dry_cells),
                  int(self.extrapolate_velocity_second_order))

        elif self.compute_fluxes_method=='DE':

            # Do protection step
            self.protect_against_infinitesimal_and_negative_heights()
            # Do extrapolation step
            from .swDE1_domain_ext import extrapolate_second_order_edge_sw as extrapol2
            extrapol2(self)

        else:
            # Code for original method
            if self.use_edge_limiter:
                self.distribute_using_edge_limiter()
            else:
                self.distribute_using_vertex_limiter()



    def distribute_using_edge_limiter(self):
        """Distribution from centroids to edges specific to the SWW eqn.

        It will ensure that h (w-z) is always non-negative even in the
        presence of steep bed-slopes by taking a weighted average between shallow
        and deep cases.

        In addition, all conserved quantities get distributed as per either a
        constant (order==1) or a piecewise linear function (order==2).


        Precondition:
          All quantities defined at centroids and bed elevation defined at
          vertices.

        Postcondition
          Conserved quantities defined at vertices
        """

        # Remove very thin layers of water
        self.protect_against_infinitesimal_and_negative_heights()

        for name in self.conserved_quantities:
            Q = self.quantities[name]
            if self._order_ == 1:
                Q.extrapolate_first_order()
            elif self._order_ == 2:
                Q.extrapolate_second_order_and_limit_by_edge()
            else:
                raise Exception('Unknown order')

        self.balance_deep_and_shallow()

        # Compute edge values by interpolation
        for name in self.conserved_quantities:
            Q = self.quantities[name]
            Q.interpolate_from_vertices_to_edges()

    def distribute_using_vertex_limiter(self):
        """Distribution from centroids to vertices specific to the SWW equation.

        It will ensure that h (w-z) is always non-negative even in the
        presence of steep bed-slopes by taking a weighted average between shallow
        and deep cases.

        In addition, all conserved quantities get distributed as per either a
        constant (order==1) or a piecewise linear function (order==2).

        FIXME: more explanation about removal of artificial variability etc

        Precondition:
          All quantities defined at centroids and bed elevation defined at
          vertices.

        Postcondition
          Conserved quantities defined at vertices
        """

        # Remove very thin layers of water
        self.protect_against_infinitesimal_and_negative_heights()

        # Extrapolate all conserved quantities
        if self.optimised_gradient_limiter:
            # MH090605 if second order,
            # perform the extrapolation and limiting on
            # all of the conserved quantities

            if (self._order_ == 1):
                for name in self.conserved_quantities:
                    Q = self.quantities[name]
                    Q.extrapolate_first_order()
            elif self._order_ == 2:
                self.extrapolate_second_order_sw()
            else:
                raise Exception('Unknown order')
        else:
            # Old code:
            for name in domain.conserved_quantities:
                Q = self.quantities[name]

                if self._order_ == 1:
                    Q.extrapolate_first_order()
                elif self._order_ == 2:
                    Q.extrapolate_second_order_and_limit_by_vertex()
                else:
                    raise Exception('Unknown order')

        # Take bed elevation into account when water heights are small
        self.balance_deep_and_shallow()

        # Compute edge values by interpolation
        for name in self.conserved_quantities:
            Q = self.quantities[name]
            Q.interpolate_from_vertices_to_edges()


    def protect_against_infinitesimal_and_negative_heights(self):
        """ Clean up the stage and momentum values to ensure non-negative heights
        """

        if self.flow_algorithm == 'tsunami':

            from .swb2_domain_ext import protect

            # shortcuts
            wc = self.quantities['stage'].centroid_values
            wv = self.quantities['stage'].vertex_values
            zc = self.quantities['elevation'].centroid_values
            zv = self.quantities['elevation'].vertex_values
            xmomc = self.quantities['xmomentum'].centroid_values
            ymomc = self.quantities['ymomentum'].centroid_values
            areas = self.areas

            mass_error = protect(self.minimum_allowed_height, self.maximum_allowed_speed,
                self.epsilon, wc, wv, zc,zv, xmomc, ymomc, areas)

            if mass_error > 0.0 and self.verbose :
                print('Cumulative mass protection: '+str(mass_error)+' m^3 ')

        elif self.compute_fluxes_method == 'DE':

            from .swDE1_domain_ext import protect_new


            mass_error = protect_new(self)

#             # shortcuts
#             wc = self.quantities['stage'].centroid_values
#             wv = self.quantities['stage'].vertex_values
#             zc = self.quantities['elevation'].centroid_values
#             zv = self.quantities['elevation'].vertex_values
#             xmomc = self.quantities['xmomentum'].centroid_values
#             ymomc = self.quantities['ymomentum'].centroid_values
#             areas = self.areas
#             xc = self.centroid_coordinates[:,0]
#             yc = self.centroid_coordinates[:,1]

            #mass_error = protect(self.minimum_allowed_height, self.maximum_allowed_speed,
            #       self.epsilon, wc, wv, zc,zv, xmomc, ymomc, areas, xc, yc)
#
            if mass_error > 0.0 and self.verbose :
                #print('Cumulative mass protection: ' + str(mass_error) + ' m^3 ')
                # From https://stackoverflow.com/questions/22397261/cant-convert-float-object-to-str-implicitly
                print('Cumulative mass protection: {0} m^3'.format(mass_error))

        else:
            from .shallow_water_ext import protect

            # Shortcuts
            wc = self.quantities['stage'].centroid_values
            zc = self.quantities['elevation'].centroid_values
            xmomc = self.quantities['xmomentum'].centroid_values
            ymomc = self.quantities['ymomentum'].centroid_values

            protect(self.minimum_allowed_height, self.maximum_allowed_speed,
                    self.epsilon, wc, zc, xmomc, ymomc)


    def balance_deep_and_shallow(self):
        """Compute linear combination between stage as computed by
        gradient-limiters limiting using w, and stage computed by
        gradient-limiters limiting using h (h-limiter).

        The former takes precedence when heights are large compared to the
        bed slope while the latter takes precedence when heights are
        relatively small.  Anything in between is computed as a balanced
        linear combination in order to avoid numerical disturbances which
        would otherwise appear as a result of hard switching between
        modes.

        Wrapper for C implementation
        """

        from .shallow_water_ext import balance_deep_and_shallow \
                                      as balance_deep_and_shallow_ext

        # Shortcuts
        wc = self.quantities['stage'].centroid_values
        zc = self.quantities['elevation'].centroid_values
        wv = self.quantities['stage'].vertex_values
        zv = self.quantities['elevation'].vertex_values

        # Momentums at centroids
        xmomc = self.quantities['xmomentum'].centroid_values
        ymomc = self.quantities['ymomentum'].centroid_values

        # Momentums at vertices
        xmomv = self.quantities['xmomentum'].vertex_values
        ymomv = self.quantities['ymomentum'].vertex_values

        balance_deep_and_shallow_ext(self,
                                   wc, zc, wv, zv, wc,
                                   xmomc, ymomc, xmomv, ymomv)


    def update_conserved_quantities(self):
        """Update vectors of conserved quantities using previously
        computed fluxes and specified forcing functions.
        """


        timestep = self.timestep


        # Update conserved_quantities
        #for name in self.conserved_quantities:
        #    Q = self.quantities[name]
        #    Q.update(timestep)

        #print 'shallow water update conserved quantties'

        Elev = self.quantities['elevation']
        Stage = self.quantities['stage']
        Xmom = self.quantities['xmomentum']
        Ymom = self.quantities['ymomentum']

        Stage.update(timestep)
        Xmom.update(timestep)
        Ymom.update(timestep)

        if self.get_using_discontinuous_elevation():

            tff = self.tri_full_flag

            negative_ids = num.where( num.logical_and((Stage.centroid_values - Elev.centroid_values) < 0.0 , tff > 0) )[0]

            if len(negative_ids) > 0:
                # FIXME: This only warns the first time -- maybe we should warn whenever loss occurs?
                import warnings
                msg = 'Negative cells being set to zero depth, possible loss of conservation. \n' +\
                      'Consider using domain.report_water_volume_statistics() to check the extent of the problem'
                warnings.warn(msg)

                Stage.centroid_values[negative_ids] = Elev.centroid_values[negative_ids]
                Xmom.centroid_values[negative_ids] = 0.0
                Ymom.centroid_values[negative_ids] = 0.0




    def update_other_quantities(self):
        """ There may be a need to calculates some of the other quantities
        based on the new values of conserved quantities
        """

        return

        """
        if self.flow_algorithm == 'yusuke':
            return


        # The centroid values of height and x and y velocity
        # might not have been setup

        self.update_centroids_of_velocities_and_height()


        # At present just use piecewise constants for these "other' quantities
        for name in ['height', 'xvelocity', 'yvelocity']:
            Q = self.quantities[name]
            Q.extrapolate_first_order()

#        for name in ['height', 'xvelocity', 'yvelocity']:
#            Q = self.quantities[name]
#            if self._order_ == 1:
#                Q.extrapolate_first_order()
#            elif self._order_ == 2:
#                if self.use_edge_limiter:
#                    Q.extrapolate_second_order_and_limit_by_edge()
#                else:
#                    Q.extrapolate_second_order_and_limit_by_vertex()
#            else:
#                raise Exception('Unknown order')

        """

    def update_centroids_of_velocities_and_height(self):
        """Calculate the centroid values of velocities and height based
        on the values of the quantities stage and x and y momentum

        Assumes that stage and momentum are up to date

        Useful for kinematic viscosity calculations
        """

        # For shallow water we need to update height xvelocity and yvelocity

        #Shortcuts
        W  = self.quantities['stage']
        UH = self.quantities['xmomentum']
        VH = self.quantities['ymomentum']
        H  = self.quantities['height']
        Z  = self.quantities['elevation']
        U  = self.quantities['xvelocity']
        V  = self.quantities['yvelocity']

        #print num.min(W.centroid_values)

        # Make sure boundary values of conserved quantites
        # are consistent with value of functions at centroids
        #self.distribute_to_vertices_and_edges()
        Z.set_boundary_values_from_edges()

        #W.set_boundary_values_from_edges()
        #UH.set_boundary_values_from_edges()
        #VH.set_boundary_values_from_edges()


        #Aliases
        w_C   = W.centroid_values
        z_C   = Z.centroid_values
        uh_C  = UH.centroid_values
        vh_C  = VH.centroid_values
        u_C   = U.centroid_values
        v_C   = V.centroid_values
        h_C   = H.centroid_values

        w_B   = W.boundary_values
        z_B   = Z.boundary_values
        uh_B  = UH.boundary_values
        vh_B  = VH.boundary_values
        u_B   = U.boundary_values
        v_B   = V.boundary_values
        h_B   = H.boundary_values

        h_C[:] = w_C-z_C
        h_C[:] = num.where(h_C >= 0, h_C , 0.0)

        h_B[:] = w_B-z_B
        h_B[:] = num.where(h_B >=0, h_B, 0.0)

        # Update height values
        #H.set_values( num.where(W.centroid_values-Z.centroid_values>=0,
        #                        W.centroid_values-Z.centroid_values, 0.0), location='centroids')
        #H.set_boundary_values( num.where(W.boundary_values-Z.boundary_values>=0,
        #                                 W.boundary_values-Z.boundary_values, 0.0))



        #assert num.min(h_C) >= 0
        #assert num.min(h_B) >= 0


        H0 = 1.0e-8

        #U.set_values(uh_C/(h_C + H0/h_C), location='centroids')
        #V.set_values(vh_C/(h_C + H0/h_C), location='centroids')

        factor = old_div(h_C,(h_C*h_C + H0))
        u_C[:]  = uh_C*factor
        v_C[:]  = vh_C*factor

        #U.set_boundary_values(uh_B/(h_B + H0/h_B))
        #V.set_boundary_values(vh_B/(h_B + H0/h_B))

        factor = old_div(h_B,(h_B*h_B + H0))
        u_B[:]  = uh_B*factor
        v_B[:]  = vh_B*factor



    def update_centroids_of_momentum_from_velocity(self):
        """Calculate the centroid value of x and y momentum from height and velocities

        Assumes centroids of height and velocities are up to date

        Useful for kinematic viscosity calculations
        """

        # For shallow water we need to update height xvelocity and yvelocity

        #Shortcuts
        UH = self.quantities['xmomentum']
        VH = self.quantities['ymomentum']
        H  = self.quantities['height']
        Z  = self.quantities['elevation']
        U  = self.quantities['xvelocity']
        V  = self.quantities['yvelocity']


        #Arrays
        u_C  = U.centroid_values
        v_C  = V.centroid_values
        uh_C = UH.centroid_values
        vh_C = VH.centroid_values
        h_C  = H.centroid_values

        u_B  = U.boundary_values
        v_B  = V.boundary_values
        uh_B = UH.boundary_values
        vh_B = VH.boundary_values
        h_B  = H.boundary_values

        uh_C[:] = u_C*h_C
        vh_C[:] = v_C*h_C
        #UH.set_values(u_C*h_C , location='centroids')
        #VH.set_values(v_C*h_C , location='centroids')

        self.distribute_to_vertices_and_edges()



    def evolve(self,
               yieldstep=None,
               outputstep=None,
               finaltime=None,
               duration=None,
               skip_initial_step=False):
        """Specialisation of basic evolve method from parent class.

            Evolve the model up to time finaltime or for a duraton of time duration. 

            yield every yieldstep period
            output to sww file every outputstep period

            outputstep should be an integer multiple of yieldstep. 

            If outputstep is None, the output to sww sile every yieldstep. 
            If yieldstep is None then simply evolve to finaltime or for a duration.
        """

        # Call check integrity here rather than from user scripts
        # self.check_integrity()

        if outputstep is None:
            outputstep = yieldstep

        if yieldstep is None:
            output_frequency = 1
        else:
            msg = f'outputstep ({outputstep}) should be an integer multiple of yieldstep ({yieldstep})'
            output_frequency = outputstep/yieldstep
            assert float(output_frequency).is_integer(), msg

        msg = 'Attribute self.beta_w must be in the interval [0, 2]'
        assert 0 <= self.beta_w <= 2.0, msg

        # Initial update of vertex and edge values before any STORAGE
        # and or visualisation.
        # This is done again in the initialisation of the Generic_Domain
        # evolve loop but we do it here to ensure the values are ok for storage.
        self.distribute_to_vertices_and_edges()

        if self.store is True and (self.get_relative_time() == 0.0 or self.evolved_called is False):
            self.initialise_storage()

        # Call basic machinery from parent class
        for t in self._evolve_base(yieldstep=yieldstep,
                                   finaltime=finaltime, duration=duration,
                                   skip_initial_step=skip_initial_step):


            walltime = time.time()

            #print t , self.get_time()
            # Store model data, e.g. for subsequent visualisation
            if self.store:
                if self.yieldstep_counter%output_frequency == 0:
                    self.store_timestep()

            if self.checkpoint:
                save_checkpoint=False
                if self.checkpoint_step == 0:
                    if rank() == 0:
                        if walltime - self.walltime_prev > self.checkpoint_time:

                            save_checkpoint = True
                        for cpu in range(size()):
                            if cpu != rank():
                                send(save_checkpoint, cpu)
                    else:
                        save_checkpoint = receive(0)

                elif self.yieldstep_counter%self.checkpoint_step == 0:
                        save_checkpoint = True

                if save_checkpoint:
                    pickle_name = os.path.join(self.checkpoint_dir,self.get_name())+'_'+str(self.get_time())+'.pickle'
                    pickle.dump(self, open(pickle_name, 'wb'))

                    barrier()
                    self.walltime_prev = time.time()

                    #print 'Stored Checkpoint File '+pickle_name

            # Pass control on to outer loop for more specific actions
            yield(t)

            self.yieldstep_counter += 1

    def initialise_storage(self):
        """Create and initialise self.writer object for storing data.
        Also, save x,y and bed elevation
        """

        # Initialise writer
        self.writer = SWW_file(self)

        # Store vertices and connectivity
        self.writer.store_connectivity()


    def store_timestep(self):
        """Store time dependent quantities and time.

        Precondition:
           self.writer has been initialised
        """

        self.writer.store_timestep()


    def sww_merge(self,  *args, **kwargs):

        pass

    def timestepping_statistics(self,
                                track_speeds=False,
                                triangle_id=None,
                                relative_time=False,
                                time_unit='sec'):
        """Return string with time stepping statistics for printing or logging

        Optional boolean keyword track_speeds decides whether to report
        location of smallest timestep as well as a histogram and percentile
        report.
        """

        from anuga.config import epsilon, g

        # Call basic machinery from parent class
        msg = Generic_Domain.timestepping_statistics(self,
                                                     track_speeds=track_speeds,
                                                     triangle_id=triangle_id,
                                                     relative_time=relative_time,
                                                     time_unit=time_unit)

        if track_speeds is True:
            # qwidth determines the text field used for quantities
            qwidth = self.qwidth

            # Selected triangle
            k = self.k

            # Report some derived quantities at vertices, edges and centroid
            # specific to the shallow water wave equation
            z = self.quantities['elevation']
            w = self.quantities['stage']

            Vw = w.get_values(location='vertices', indices=[k])[0]
            Ew = w.get_values(location='edges', indices=[k])[0]
            Cw = w.get_values(location='centroids', indices=[k])

            Vz = z.get_values(location='vertices', indices=[k])[0]
            Ez = z.get_values(location='edges', indices=[k])[0]
            Cz = z.get_values(location='centroids', indices=[k])

            name = 'depth'
            Vh = Vw-Vz
            Eh = Ew-Ez
            Ch = Cw-Cz

            message  = '    %s: vertex_values =  %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Vh[0], Vh[1], Vh[2])

            message += '    %s: edge_values =    %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Eh[0], Eh[1], Eh[2])

            message += '    %s: centroid_value = %.4f\n'\
                 % (name.ljust(qwidth), Ch[0])

            msg += message

            uh = self.quantities['xmomentum']
            vh = self.quantities['ymomentum']

            Vuh = uh.get_values(location='vertices', indices=[k])[0]
            Euh = uh.get_values(location='edges', indices=[k])[0]
            Cuh = uh.get_values(location='centroids', indices=[k])

            Vvh = vh.get_values(location='vertices', indices=[k])[0]
            Evh = vh.get_values(location='edges', indices=[k])[0]
            Cvh = vh.get_values(location='centroids', indices=[k])

            # Speeds in each direction
            Vu = old_div(Vuh,(Vh + epsilon))
            Eu = old_div(Euh,(Eh + epsilon))
            Cu = old_div(Cuh,(Ch + epsilon))
            name = 'U'
            message  = '    %s: vertex_values =  %.4f,\t %.4f,\t %.4f\n' \
                 % (name.ljust(qwidth), Vu[0], Vu[1], Vu[2])

            message += '    %s: edge_values =    %.4f,\t %.4f,\t %.4f\n' \
                 % (name.ljust(qwidth), Eu[0], Eu[1], Eu[2])

            message += '    %s: centroid_value = %.4f\n' \
                 % (name.ljust(qwidth), Cu[0])

            msg += message

            Vv = old_div(Vvh,(Vh + epsilon))
            Ev = old_div(Evh,(Eh + epsilon))
            Cv = old_div(Cvh,(Ch + epsilon))
            name = 'V'
            message  = '    %s: vertex_values =  %.4f,\t %.4f,\t %.4f\n' \
                 % (name.ljust(qwidth), Vv[0], Vv[1], Vv[2])

            message += '    %s: edge_values =    %.4f,\t %.4f,\t %.4f\n' \
                 % (name.ljust(qwidth), Ev[0], Ev[1], Ev[2])

            message += '    %s: centroid_value = %.4f\n'\
                 %(name.ljust(qwidth), Cv[0])

            msg += message

            # Froude number in each direction
            name = 'Froude (x)'
            Vfx = old_div(Vu,(num.sqrt(g*Vh) + epsilon))
            Efx = old_div(Eu,(num.sqrt(g*Eh) + epsilon))
            Cfx = old_div(Cu,(num.sqrt(g*Ch) + epsilon))

            message  = '    %s: vertex_values =  %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Vfx[0], Vfx[1], Vfx[2])

            message += '    %s: edge_values =    %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Efx[0], Efx[1], Efx[2])

            message += '    %s: centroid_value = %.4f\n'\
                 % (name.ljust(qwidth), Cfx[0])

            msg += message

            name = 'Froude (y)'
            Vfy = old_div(Vv,(num.sqrt(g*Vh) + epsilon))
            Efy = old_div(Ev,(num.sqrt(g*Eh) + epsilon))
            Cfy = old_div(Cv,(num.sqrt(g*Ch) + epsilon))

            message  = '    %s: vertex_values =  %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Vfy[0], Vfy[1], Vfy[2])

            message += '    %s: edge_values =    %.4f,\t %.4f,\t %.4f\n'\
                 % (name.ljust(qwidth), Efy[0], Efy[1], Efy[2])

            message += '    %s: centroid_value = %.4f\n'\
                 % (name.ljust(qwidth), Cfy[0])

            msg += message

        return msg

    def print_timestepping_statistics(self, *args, **kwargs):

        msg = self.timestepping_statistics(*args, **kwargs)

        print(msg)


    def compute_boundary_flows(self):
        """Compute boundary flows at current timestep.

        Quantities computed are:
           Total inflow across boundary
           Total outflow across boundary
           Flow across each tagged boundary segment

        These calculations are only approximate since they don't use the
        flux calculation used in evolve

        See get_boundary_flux_integral for an exact computation
        """

        # Run through boundary array and compute for each segment
        # the normal momentum ((uh, vh) dot normal) times segment length.
        # Based on sign accumulate this into boundary_inflow and
        # boundary_outflow.

        # Compute flows along boundary

        uh = self.get_quantity('xmomentum').get_values(location='edges')
        vh = self.get_quantity('ymomentum').get_values(location='edges')

        # Loop through edges that lie on the boundary and calculate
        # flows
        boundary_flows = {}
        total_boundary_inflow = 0.0
        total_boundary_outflow = 0.0
        for vol_id, edge_id in self.boundary:
            # Compute normal flow across edge. Since normal vector points
            # away from triangle, a positive sign means that water
            # flows *out* from this triangle.

            momentum = [uh[vol_id, edge_id], vh[vol_id, edge_id]]
            normal = self.mesh.get_normal(vol_id, edge_id)
            length = self.mesh.get_edgelength(vol_id, edge_id)
            normal_flow = num.dot(momentum, normal)*length

            # Reverse sign so that + is taken to mean inflow
            # and - means outflow. This is more intuitive.
            edge_flow = -normal_flow

            # Tally up inflows and outflows separately
            if edge_flow > 0:
                # Flow is inflow
                total_boundary_inflow += edge_flow
            else:
                # Flow is outflow
                total_boundary_outflow += edge_flow

            # Tally up flows by boundary tag
            tag = self.boundary[(vol_id, edge_id)]

            if tag not in boundary_flows:
                boundary_flows[tag] = 0.0
            boundary_flows[tag] += edge_flow


        return boundary_flows, total_boundary_inflow, total_boundary_outflow


    def compute_forcing_flows(self):
        """
        Compute flows in and out of domain due to forcing terms.

        Quantities computed are:

           Total inflow through forcing terms
           Total outflow through forcing terms
           Current total volume in domain

        """

        #FIXME(Ole): We need to separate what part of explicit_update was
        # due to the normal flux calculations and what is due to forcing terms.

        pass


    def compute_total_volume(self):
        """
        Compute total volume (m^3) of water in entire domain

        """

        return self.get_water_volume()


    def volumetric_balance_statistics(self):
        """Create volumetric balance report suitable for printing or logging.
        """

        (boundary_flows, total_boundary_inflow,
         total_boundary_outflow) = self.compute_boundary_flows()

        message = '---------------------------\n'
        message += 'Volumetric balance report:\n'
        message += 'Note: Boundary fluxes are not exact\n'
        message += 'See get_boundary_flux_integral for exact computation\n'
        message += '--------------------------\n'
        message += 'Total boundary inflow [m^3/s]: %.2f\n' % total_boundary_inflow
        message += 'Total boundary outflow [m^3/s]: %.2f\n' % total_boundary_outflow
        message += 'Net boundary flow by tags [m^3/s]\n'
        for tag in boundary_flows:
            message += '    %s [m^3/s]: %.2f\n' % (tag, boundary_flows[tag])

        message += 'Total net boundary flow [m^3/s]: %.2f\n' % \
                    (total_boundary_inflow + total_boundary_outflow)
        message += 'Total volume in domain [m^3]: %.2f\n' % \
                    self.compute_total_volume()

        # The go through explicit forcing update and record the rate of change
        # for stage and
        # record into forcing_inflow and forcing_outflow. Finally compute
        # integral of depth to obtain total volume of domain.

        # FIXME(Ole): This part is not yet done.

        return message

    def print_volumetric_balance_statistics(self):

        print (self.volumetric_balance_statistics())

    def compute_flux_update_frequency(self):
        """
            Update the 'flux_update_frequency' and 'update_extrapolate' variables
            Used to control updating of fluxes / extrapolation for 'local-time-stepping'
        """
        from .swDE1_domain_ext import compute_flux_update_frequency \
                                  as compute_flux_update_frequency_ext

        compute_flux_update_frequency_ext(self, self.timestep)

    def report_water_volume_statistics(self, verbose=True, returnStats=False):
        """
        Compute the volume, boundary flux integral, fractional step volume integral, and their difference

        If verbose, print a summary
        If returnStats, return a list with the volume statistics
        """
        from anuga import myid

        if(self.compute_fluxes_method != 'DE'):
            if(myid==0):
                print('Water_volume_statistics only supported for DE algorithm ')
            return

        # Compute the volume
        Vol=self.get_water_volume()
        # Compute the boundary flux integral
        fluxIntegral=self.get_boundary_flux_integral()
        fracIntegral=self.get_fractional_step_volume_integral()

        if(verbose and myid==0):
            print(' ')
            print('    Volume V is:', Vol)
            print('    Boundary Flux integral BF: ', fluxIntegral)
            print('    (rate + inlet) Fractional Step volume integral FS: ', fracIntegral)
            print('    V - BF - FS - InitialVolume :',  Vol- fluxIntegral -fracIntegral - self.volume_history[0])
            print(' ')

        if(returnStats):
            return [Vol, fluxIntegral, fracIntegral]
        else:
            return

    def report_cells_with_small_local_timestep(self, threshold_depth=None):
        """
        Convenience function to print the locations of cells
        with a small local timestep.

        Computations are at cell centroids

        Useful in models
        with complex meshes, to find ways to speed up the model
        """
        from anuga.parallel import myid, numprocs
        from anuga.config import g, epsilon

        if(threshold_depth is None):
            threshold_depth=self.minimum_allowed_height

        uh = self.quantities['xmomentum'].centroid_values
        vh = self.quantities['ymomentum'].centroid_values
        d =  self.quantities['stage'].centroid_values - self.quantities['elevation'].centroid_values
        d = num.maximum(d, threshold_depth)
        v = old_div(( (uh)**2 + (vh)**2)**0.5,d)
        v = v*(d>threshold_depth)

        for i in range(numprocs):
            if(myid==i):
                print('    Processor ', myid)
                gravSpeed=(g*d)**0.5
                waveSpeed = abs(v)+gravSpeed
                localTS=old_div(self.radii,num.maximum(waveSpeed, epsilon))
                controlling_pt_ind=localTS.argmin()
                print('    * Smallest LocalTS is: ', localTS[controlling_pt_ind])
                print('     -- Location: ', round(self.centroid_coordinates[controlling_pt_ind,0]+self.geo_reference.xllcorner,2),\
                                        round(self.centroid_coordinates[controlling_pt_ind,1]+self.geo_reference.yllcorner,2))
                print('     -+ Speed: ', v[controlling_pt_ind])
                print('     -* Gravity_wave_speed', gravSpeed[controlling_pt_ind])
                print(' ')

            barrier()
        return

# =======================================================================
# PETE: NEW METHODS FOR FOR PARALLEL STRUCTURES. Note that we assume the
# first "number_of_full_[nodes|triangles]" are full [nodes|triangles]
# For full triangles it is possible to enquire self.tri_full_flag == True
# =======================================================================

    def get_number_of_full_triangles(self, *args, **kwargs):
        return self.number_of_full_triangles

    def get_full_centroid_coordinates(self, *args, **kwargs):
        C = self.mesh.get_centroid_coordinates(*args, **kwargs)
        return C[:self.number_of_full_triangles, :]

    def get_full_vertex_coordinates(self, *args, **kwargs):
        V = self.mesh.get_vertex_coordinates(*args, **kwargs)
        return V[:3*self.number_of_full_triangles,:]

    def get_full_triangles(self, *args, **kwargs):
        T = self.mesh.get_triangles(*args, **kwargs)
        return T[:self.number_of_full_triangles,:]

    def get_full_nodes(self, *args, **kwargs):
        N = self.mesh.get_nodes(*args, **kwargs)
        return N[:self.number_of_full_nodes,:]

    def get_tri_map(self):
        return self.tri_map

    def get_inv_tri_map(self):
        return self.inv_tri_map

################################################################################
# End of class Shallow Water Domain
################################################################################

#-----------------
# Flux computation
#-----------------

#def compute_fluxes(domain):
#    """Compute fluxes and timestep suitable for all volumes in domain.
#
#    Compute total flux for each conserved quantity using "flux_function"
#
#    Fluxes across each edge are scaled by edgelengths and summed up
#    Resulting flux is then scaled by area and stored in
#    explicit_update for each of the three conserved quantities
#    stage, xmomentum and ymomentum
#
#    The maximal allowable speed computed by the flux_function for each volume
#    is converted to a timestep that must not be exceeded. The minimum of
#    those is computed as the next overall timestep.
#
#    Post conditions:
#      domain.explicit_update is reset to computed flux values
#      domain.timestep is set to the largest step satisfying all volumes.
#
#    This wrapper calls the underlying C version of compute fluxes
#    """
#
#    import sys
#    from shallow_water_ext import compute_fluxes_ext_central \
#                                  as compute_fluxes_ext
#
#    # Shortcuts
#    Stage = domain.quantities['stage']
#    Xmom = domain.quantities['xmomentum']
#    Ymom = domain.quantities['ymomentum']
#    Bed = domain.quantities['elevation']
#
#
#
#    timestep = float(sys.maxint)
#
#    flux_timestep = compute_fluxes_ext(timestep,
#                                       domain.epsilon,
#                                       domain.H0,
#                                       domain.g,
#                                       domain.neighbours,
#                                       domain.neighbour_edges,
#                                       domain.normals,
#                                       domain.edgelengths,
#                                       domain.radii,
#                                       domain.areas,
#                                       domain.tri_full_flag,
#                                       Stage.edge_values,
#                                       Xmom.edge_values,
#                                       Ymom.edge_values,
#                                       Bed.edge_values,
#                                       Stage.boundary_values,
#                                       Xmom.boundary_values,
#                                       Ymom.boundary_values,
#                                       Stage.explicit_update,
#                                       Xmom.explicit_update,
#                                       Ymom.explicit_update,
#                                       domain.already_computed_flux,
#                                       domain.max_speed,
#                                       domain.optimise_dry_cells)
#
#    domain.flux_timestep = flux_timestep
#
#
#
#def compute_fluxes_structure(domain):
#    """Compute fluxes and timestep suitable for all volumes in domain.
#
#    Compute total flux for each conserved quantity using "flux_function"
#
#    Fluxes across each edge are scaled by edgelengths and summed up
#    Resulting flux is then scaled by area and stored in
#    explicit_update for each of the three conserved quantities
#    stage, xmomentum and ymomentum
#
#    The maximal allowable speed computed by the flux_function for each volume
#    is converted to a timestep that must not be exceeded. The minimum of
#    those is computed as the next overall timestep.
#
#    Post conditions:
#      domain.explicit_update is reset to computed flux values
#      domain.flux_timestep is set to the largest step satisfying all volumes.
#
#    This wrapper calls the underlying C version of compute fluxes
#    """
#
#
#    from shallow_water_ext import compute_fluxes_ext_central_structure
#
#
#    domain.flux_timestep = compute_fluxes_ext_central_structure(domain)
#


################################################################################
# Module functions for gradient limiting
################################################################################

def extrapolate_second_order_sw_old(domain):
    """Wrapper calling C version of extrapolate_second_order_sw.

    domain  the domain to operate on

    Note MH090605: The following method belongs to the shallow_water domain
    class, see comments in the corresponding method in shallow_water_ext.c
    """

    from .shallow_water_ext import extrapolate_second_order_sw_old as extrapol2

    # Shortcuts
    Stage = domain.quantities['stage']
    Xmom = domain.quantities['xmomentum']
    Ymom = domain.quantities['ymomentum']
    Elevation = domain.quantities['elevation']

    extrapol2(domain,
              domain.surrogate_neighbours,
              domain.number_of_boundaries,
              domain.centroid_coordinates,
              Stage.centroid_values,
              Xmom.centroid_values,
              Ymom.centroid_values,
              Elevation.centroid_values,
              domain.vertex_coordinates,
              Stage.vertex_values,
              Xmom.vertex_values,
              Ymom.vertex_values,
              Elevation.vertex_values,
              int(domain.optimise_dry_cells),
              int(domain.extrapolate_velocity_second_order))


#def extrapolate_second_order_sw(domain):
#    """Wrapper calling C version of extrapolate_second_order_sw.
#
#    domain  the domain to operate on
#
#    Note MH090605: The following method belongs to the shallow_water domain
#    class, see comments in the corresponding method in shallow_water_ext.c
#    """
#
#    from shallow_water_ext import extrapolate_second_order_sw as extrapol2
#    extrapol2(domain)


def distribute_using_vertex_limiter(domain):
    """Distribution from centroids to vertices specific to the SWW equation.

    It will ensure that h (w-z) is always non-negative even in the
    presence of steep bed-slopes by taking a weighted average between shallow
    and deep cases.

    In addition, all conserved quantities get distributed as per either a
    constant (order==1) or a piecewise linear function (order==2).

    FIXME: more explanation about removal of artificial variability etc

    Precondition:
      All quantities defined at centroids and bed elevation defined at
      vertices.

    Postcondition
      Conserved quantities defined at vertices
    """

    # Remove very thin layers of water
    domain.protect_against_infinitesimal_and_negative_heights()

    # Extrapolate all conserved quantities
    if domain.optimised_gradient_limiter:
        # MH090605 if second order,
        # perform the extrapolation and limiting on
        # all of the conserved quantities

        if (domain._order_ == 1):
            for name in domain.conserved_quantities:
                Q = domain.quantities[name]
                Q.extrapolate_first_order()
        elif domain._order_ == 2:
            domain.extrapolate_second_order_sw()
        else:
            raise Exception('Unknown order')
    else:
        # Old code:
        for name in domain.conserved_quantities:
            Q = domain.quantities[name]

            if domain._order_ == 1:
                Q.extrapolate_first_order()
            elif domain._order_ == 2:
                Q.extrapolate_second_order_and_limit_by_vertex()
            else:
                raise Exception('Unknown order')

    # Take bed elevation into account when water heights are small
    balance_deep_and_shallow(domain)

    # Compute edge values by interpolation
    for name in domain.conserved_quantities:
        Q = domain.quantities[name]
        Q.interpolate_from_vertices_to_edges()

#def distribute_using_edge_limiter(domain):
#    """Distribution from centroids to edges specific to the SWW eqn.
#
#    It will ensure that h (w-z) is always non-negative even in the
#    presence of steep bed-slopes by taking a weighted average between shallow
#    and deep cases.
#
#    In addition, all conserved quantities get distributed as per either a
#    constant (order==1) or a piecewise linear function (order==2).
#
#
#    Precondition:
#      All quantities defined at centroids and bed elevation defined at
#      vertices.
#
#    Postcondition
#      Conserved quantities defined at vertices
#    """
#
#    # Remove very thin layers of water
#    domain.protect_against_infinitesimal_and_negative_heights()
#
#    for name in domain.conserved_quantities:
#        Q = domain.quantities[name]
#        if domain._order_ == 1:
#            Q.extrapolate_first_order()
#        elif domain._order_ == 2:
#            Q.extrapolate_second_order_and_limit_by_edge()
#        else:
#            raise Exception('Unknown order')
#
#    balance_deep_and_shallow(domain)
#
#    # Compute edge values by interpolation
#    for name in domain.conserved_quantities:
#        Q = domain.quantities[name]
#        Q.interpolate_from_vertices_to_edges()
#
##def protect_against_infinitesimal_and_negative_heights(domain):
##    """Protect against infinitesimal heights and associated high velocities"""
##
##    from shallow_water_ext import protect
##
##    # Shortcuts
##    wc = domain.quantities['stage'].centroid_values
##    zc = domain.quantities['elevation'].centroid_values
##    xmomc = domain.quantities['xmomentum'].centroid_values
##    ymomc = domain.quantities['ymomentum'].centroid_values
##
##    protect(domain.minimum_allowed_height, domain.maximum_allowed_speed,
##            domain.epsilon, wc, zc, xmomc, ymomc)





################################################################################
# Standard forcing terms
################################################################################


def manning_friction_implicit(domain):
    """Apply (Manning) friction to water momentum
    Wrapper for c version
    """

    from .shallow_water_ext import manning_friction_flat
    from .shallow_water_ext import manning_friction_sloped

    xmom = domain.quantities['xmomentum']
    ymom = domain.quantities['ymomentum']

    x = domain.get_vertex_coordinates()

    w = domain.quantities['stage'].centroid_values
    z = domain.quantities['elevation'].vertex_values

    uh = xmom.centroid_values
    vh = ymom.centroid_values
    eta = domain.quantities['friction'].centroid_values

    xmom_update = xmom.semi_implicit_update
    ymom_update = ymom.semi_implicit_update

    eps = domain.minimum_allowed_height
    g = domain.g

    if domain.use_sloped_mannings:
        manning_friction_sloped(g, eps, x, w, uh, vh, z, eta, xmom_update, \
                                ymom_update)
    else:
        manning_friction_flat(g, eps, w, uh, vh, z, eta, xmom_update, \
                                ymom_update)


def manning_friction_explicit(domain):
    """Apply (Manning) friction to water momentum
    Wrapper for c version
    """

    from .shallow_water_ext import manning_friction_flat
    from .shallow_water_ext import manning_friction_sloped

    xmom = domain.quantities['xmomentum']
    ymom = domain.quantities['ymomentum']

    x = domain.get_vertex_coordinates()

    w = domain.quantities['stage'].centroid_values
    z = domain.quantities['elevation'].vertex_values

    uh = xmom.centroid_values
    vh = ymom.centroid_values
    eta = domain.quantities['friction'].centroid_values

    xmom_update = xmom.explicit_update
    ymom_update = ymom.explicit_update

    eps = domain.minimum_allowed_height

    if domain.use_sloped_mannings:
        manning_friction_sloped(domain.g, eps, x, w, uh, vh, z, eta, xmom_update, \
                            ymom_update)
    else:
        manning_friction_flat(domain.g, eps, w, uh, vh, z, eta, xmom_update, \
                            ymom_update)



# FIXME (Ole): This was implemented for use with one of the analytical solutions
def linear_friction(domain):
    """Apply linear friction to water momentum

    Assumes quantity: 'linear_friction' to be present
    """

    w = domain.quantities['stage'].centroid_values
    z = domain.quantities['elevation'].centroid_values
    h = w-z

    uh = domain.quantities['xmomentum'].centroid_values
    vh = domain.quantities['ymomentum'].centroid_values
    tau = domain.quantities['linear_friction'].centroid_values

    xmom_update = domain.quantities['xmomentum'].semi_implicit_update
    ymom_update = domain.quantities['ymomentum'].semi_implicit_update

    num_tris = len(domain)
    eps = domain.minimum_allowed_height

    for k in range(num_tris):
        if tau[k] >= eps:
            if h[k] >= eps:
                S = old_div(-tau[k],h[k])

                #Update momentum
                xmom_update[k] += S*uh[k]
                ymom_update[k] += S*vh[k]

def depth_dependent_friction(domain, default_friction,
                             surface_roughness_data,
                             verbose=False):
    """Returns an array of friction values for each wet element adjusted for
            depth.

    Inputs:
        domain - computational domain object
        default_friction - depth independent bottom friction
        surface_roughness_data - N x 5 array of n0, d1, n1, d2, n2 values
        for each friction region.

    Outputs:
        wet_friction - Array that can be used directly to update friction as
                        follows:
                       domain.set_quantity('friction', wet_friction)



    """

    default_n0 = 0  # James - this was missing, don't know what it should be

    # Create a temp array to store updated depth dependent
    # friction for wet elements
    # EHR this is outwardly inneficient but not obvious how to avoid
    # recreating each call??????

    wet_friction    = num.zeros(len(domain), float)
    wet_friction[:] = default_n0  # Initially assign default_n0 to all array so
                                  # sure have no zeros values

    # create depth instance for this timestep
    depth = domain.create_quantity_from_expression('stage - elevation')
    # Recompute depth as vector
    d_vals = depth.get_values(location='centroids')

    # rebuild the 'friction' values adjusted for depth at this instant
    # loop for each wet element in domain

    for i in domain.get_wet_elements():
        # Get roughness data for each element
        d1 = float(surface_roughness_data[i, 1])
        n1 = float(surface_roughness_data[i, 2])
        d2 = float(surface_roughness_data[i, 3])
        n2 = float(surface_roughness_data[i, 4])


        # Recompute friction values from depth for this element

        if d_vals[i]   <= d1:
            ddf = n1
        elif d_vals[i] >= d2:
            ddf = n2
        else:
            ddf = n1 + (old_div((n2-n1),(d2-d1)))*(d_vals[i]-d1)

        # check sanity of result
        if (ddf  < 0.010 or \
                            ddf > 9999.0) :
            log.critical('>>>> WARNING: computed depth_dependent friction '
                         'out of range, ddf%f, n1=%f, n2=%f'
                         % (ddf, n1, n2))

        # update depth dependent friction  for that wet element
        wet_friction[i] = ddf

    # EHR add code to show range of 'friction across domain at this instant as
    # sanity check?????????

    if verbose :
        # return array of domain nvals
        nvals = domain.get_quantity('friction').get_values(location='centroids')
        n_min = min(nvals)
        n_max = max(nvals)

        log.critical('         ++++ calculate_depth_dependent_friction - '
                     'Updated friction - range  %7.3f to %7.3f'
                     % (n_min, n_max))

    return wet_friction

def my_update_special_conditions(domain):

    pass


################################################################################
# Initialise module
################################################################################

#def _raise_compile_exception():
#    """ Raise exception if compiler not available. """
#    msg = 'C implementations could not be accessed by %s.\n ' % __file__
#    msg += 'Make sure compile_all.py has been run as described in '
#    msg += 'the ANUGA installation guide.'
#    raise Exception(msg)
#
#from anuga.utilities import compile
#if not compile.can_use_C_extension('shallow_water_ext.c'):
#    _raise_compile_exception()

if __name__ == "__main__":
    pass
