def construct_eos_for_material(material_tag,units=None,etamin=0.94,etamax=100.0): """Return a spheral EOS object for a material identified by tag. construct_eos_for_material(mtag,units) calls the appropriate spheral eos constructor for the material identified by mtag, which must be one of the keys defined in the global shelpers.material_dictionary. This dictionary also includes additional arguments to be passed to the constructor, when necessary. The etamin and etamax optional arguments have slightly different meaning depending on which EOS constructor is actually used. Currently implemented constructors are: Tillotson : the value of etamin is passed to the etamin_solid parameter of the constructor. This is used to limit tensional pressure when the material is no longer solid. (Note that the spheral constructor also has an etamin parameter, which is used to prevent underflows in the pressure computation.) ANEOS : Not yet implemented. All pcs runs should use this method to create equations of state, instead of calling the spheral constructors directly, in order to allow automatic record keeping of what material was used in a given run. This also allows reusing "pre cooked" node lists in new runs. The file <pcs>/MATERIALS.md should contain a table of available material tags. See also: material_dictionary """ # Make sure we are not wasting our time. assert isinstance(material_tag,str) assert material_tag.lower() in material_dictionary.keys() if units is None: units = sph.PhysicalConstants(1,1,1) assert isinstance(units,sph.PhysicalConstants) assert isinstance(etamin,float) assert isinstance(etamax,float) # Build eos using our internal dictionary mat_dict = material_dictionary[material_tag.lower()] eos_constructor = mat_dict['eos_constructor'] eos_arguments = mat_dict['eos_arguments'] eos = None if mat_dict['eos_type'] == 'Tillotson': eos = eos_constructor(eos_arguments['materialName'], 1e-20, 1e20, units, etamin_solid=etamin) eos.uid = mat_dict['eos_id'] # Fix for LLNL ignoring the min eta requirement of Tillotson eos.minimumPressure = eos.pressure( eos.etamin_solid*eos.referenceDensity, 0) eos.minimumPressureType = 1 # 0: floor 1: zero pass else: print "EOS type {} not yet implemented".format(mat_dict['eos_type']) pass # And Bob's our uncle return eos
def pflatten_node_list(nl,filename,do_header=True,nl_id=0,silent=False): """Flatten physical field values from a node list to a rectangular ascii file. pflatten_node_list(nl,filename) extracts field variables from all nodes of nl, which must be a valid node list, and writes them as a rectangular table into the text file filename. (A short header is also written, using the # comment character so the resulting file can be easily read with numpy.loadtext.) The file will be overwritten if it exists. If filename has the .gz extension it will be compressed using gzip. pflatten_node_list(...,do_header=False) omits the header and appends the flattened nl to the end of the file if one exists. pflatten_node_list(...,nl_id=id) places the integer id in the first column of every node (row) in the node list. This can be used when appending multiple lists to the same file, providing a convenient way to distinguish nodes from different lists when the file is later read. The default id (for single node list files) is 0. The format of the output table is (one line per node): id eos_id x y z vx vy vz m rho p T U hmin hmax The p in pflatten is for 'parallel', a reminder that all nodes will be processed in their local rank, without ever being communicated or collected in a single process. Each mpi rank will wait its turn to access the output file, so the writing is in fact serial, but avoids bandwidth and memory waste and is thus suitable for large node lists from high-res runs. See also: spickle_node_list """ # Make sure we are not wasting our time. assert isinstance(nl,(sph.Spheral.NodeSpace.FluidNodeList3d, sph.Spheral.SolidMaterial.SolidNodeList3d) ), "argument 1 must be a node list" assert isinstance(filename, str), "argument 2 must be a simple string" assert isinstance(do_header, bool), "true or false" assert isinstance(silent, bool), "true or false" assert isinstance(nl_id, int), "int only idents" assert not isinstance(nl_id, bool), "int only idents" # Determine if file should be compressed. if os.path.splitext(filename)[1] == '.gz': import gzip open = gzip.open else: import __builtin__ open = __builtin__.open # Write the header. if do_header: nbGlobalNodes = mpi.allreduce(nl.numInternalNodes, mpi.SUM) header = header_template.format(nbGlobalNodes) if mpi.rank == 0: fid = open(filename,'w') fid.write(header) fid.close() pass pass # Start collecting data. if not silent: sys.stdout.write('Flattening ' + nl.label() + ' ' + nl.name + '........') # Get values of field variables stored in internal nodes. xloc = nl.positions().internalValues() vloc = nl.velocity().internalValues() mloc = nl.mass().internalValues() rloc = nl.massDensity().internalValues() uloc = nl.specificThermalEnergy().internalValues() Hloc = nl.Hfield().internalValues() #(pressure and temperature are stored in the eos object.) eos = nl.equationOfState() ploc = sph.ScalarField('ploc',nl) Tloc = sph.ScalarField('loc',nl) rref = nl.massDensity() uref = nl.specificThermalEnergy() eos.setPressure(ploc,rref,uref) eos.setTemperature(Tloc,rref,uref) # Procs take turns writing internal node values to file. for proc in range(mpi.procs): if proc == mpi.rank: fid = open(filename,'a') for nk in range(nl.numInternalNodes): line = "{:2d} ".format(nl_id) line += "{:2d} ".format(getattr(nl,'eos_id',-1)) line += "{0.x:+12.5e} {0.y:+12.5e} {0.z:+12.5e} ".format(xloc[nk]) line += "{0.x:+12.5e} {0.y:+12.5e} {0.z:+12.5e} ".format(vloc[nk]) line += "{0:+12.5e} ".format(mloc[nk]) line += "{0:+12.5e} ".format(rloc[nk]) line += "{0:+12.5e} ".format(ploc[nk]) line += "{0:+12.5e} ".format(Tloc[nk]) line += "{0:+12.5e} ".format(uloc[nk]) line += "{0:+12.5e} ".format(Hloc[nk].Inverse().eigenValues().minElement()) line += "{0:+12.5e} ".format(Hloc[nk].Inverse().eigenValues().maxElement()) line += "\n" fid.write(line) pass fid.close() pass mpi.barrier() pass # And Bob's our uncle. if not silent: print "Done."
def __init__(self, R, eos, rho0=None, rmin=0, units=None, nbins=100): """Class constructor for quasi-incompressible density profile. Assuming a barely compressible, one-layer planet, a pressure profile in hydrostatic equilibrium can be found by integrating the hydrostatic equation with constant density. The equation of state can then be inverted to provide a density profile consistent with this pressure profile. Although the resulting pressure/density state is not strictly self consistent, it may be used as a good approximation for small planets that are not expected to be highly compressed. This class generates, in the constructor, a density profile: a vector of radii and a vector of corresponding densities. The __call__ method is used to extract a density for an arbitrary radius by interpolation. This is to provide the interface used by some of the existing node generators in SPHERAL. Parameters ---------- R : float > 0 Radius of uncompressed planet. eos : SolidSpheral3d.EquationOfState3d Equation-of-state of planet material. rho0 : float > 0, optional Guess for density at surface. If not provided eos.referenceDensity will be used. rMin : float >=0, optional Bottom of profile to be computed. Default is 0. units : SolidSpheral3d.PhysicalConstants, optional Units object if arguments are not in MKS. Must match constants member of eos. Default is SolidSpheral3d.PhysicalConstants(1,1,1). nbins : int >= 10, optional Number of interpolation points in [rMin,R]. """ # Minimal input checking assert np.isreal(R) and R > 0 assert np.isreal(rmin) and rmin < R assert isinstance(eos, sph.EquationOfState3d) assert type(nbins) is type(1) and nbins >= 10 if rho0 is None: rho0 = eos.referenceDensity assert type(rho0) is type(1.0) and rho0 > 0 if units is None: units = sph.PhysicalConstants(1,1,1) assert isinstance(units, sph.PhysicalConstants) assert units.G == eos.constants.G # Local variables rvec = np.linspace(rmin, R, num=nbins) dvec = np.ones(rvec.size)*np.NaN pvec = np.ones(rvec.size)*np.NaN # Step one - calculate pressure profile G = units.G for k in range(rvec.size): pvec[k] = 2*np.pi/3*G*rho0**2*(R**2 - rvec[k]**2) assert np.all(np.isfinite(pvec)) # Step two - lion hunt to invert eos and get a density def f(x): return pressure(eos,x,0) - p_hs for k in range(pvec.size): p_hs = pvec[k] x_hi = eos.referenceDensity*2 x_lo = eos.referenceDensity/2 while (x_hi - x_lo) > 1e-12*eos.referenceDensity: x_hs = (x_lo + x_hi)/2 if f(x_hs) > 0: x_hi = x_hs else: x_lo = x_hs pass pass dvec[k] = x_hs assert np.all(np.isfinite(dvec)) # Store object data self.rvec = rvec self.dvec = dvec self.pvec = pvec self.units = units # And Bob's our uncle. return
def spickle_node_list(nl,filename=None,silent=False): """Pack physical field variables from a node list in a dict and pickle. (Note: This is not a true pickler class.) spickle_node_list(nl,filename) extracts field variables from all nodes of nl, which must be a valid node list, and packs them in a dict that is returned to the caller. If the optional argument filename is a string then dict will also be pickled to a file of that name. The file will be overwritten if it exists. The s in spickle is for 'serial', a reminder that this method collects all nodes of the node list (from all ranks) in a single process. Thus this method is mainly useful for interactive work with small node lists. It is the user's responsibility to make sure her process has enough memory to hold the returned dict. See also: pflatten_node_list """ # Make sure we are not wasting our time. assert isinstance(nl,(sph.Spheral.NodeSpace.FluidNodeList3d, sph.Spheral.SolidMaterial.SolidNodeList3d) ), "argument 1 must be a node list" assert isinstance(silent, bool), "true or false" # Start collecting data. if not silent: sys.stdout.write('Pickling ' + nl.label() + ' ' + nl.name + '........') # Get values of field variables stored in internal nodes. xloc = nl.positions().internalValues() vloc = nl.velocity().internalValues() mloc = nl.mass().internalValues() rloc = nl.massDensity().internalValues() uloc = nl.specificThermalEnergy().internalValues() Hloc = nl.Hfield().internalValues() #(pressure and temperature are stored in the eos object.) eos = nl.equationOfState() ploc = sph.ScalarField('ploc',nl) Tloc = sph.ScalarField('loc',nl) rref = nl.massDensity() uref = nl.specificThermalEnergy() eos.setPressure(ploc,rref,uref) eos.setTemperature(Tloc,rref,uref) # Zip fields so that we have all fields for each node in the same tuple. # We do this so we can concatenate everything in a single reduction operation, # to ensure that all fields in one record in the final list belong to the # same node. localFields = zip(xloc, vloc, mloc, rloc, uloc, ploc, Tloc, Hloc) # Do a SUM reduction on all ranks. # This works because the + operator for python lists is a concatenation! globalFields = mpi.allreduce(localFields, mpi.SUM) # Create a dictionary to hold field variables. nlFieldDict = dict(name=nl.name, x=[], # position vector v=[], # velocity vector m=[], # mass rho=[], # mass density p=[], # pressure h=[], # smoothing ellipsoid axes T=[], # temperature U=[], # specific thermal energy ) # Loop over nodes to fill field values. nbGlobalNodes = mpi.allreduce(nl.numInternalNodes, mpi.SUM) for k in range(nbGlobalNodes): nlFieldDict[ 'x'].append((globalFields[k][0].x, globalFields[k][0].y, globalFields[k][0].z)) nlFieldDict[ 'v'].append((globalFields[k][1].x, globalFields[k][1].y, globalFields[k][1].z)) nlFieldDict[ 'm'].append( globalFields[k][2]) nlFieldDict['rho'].append( globalFields[k][3]) nlFieldDict[ 'U'].append( globalFields[k][4]) nlFieldDict[ 'p'].append( globalFields[k][5]) nlFieldDict[ 'T'].append( globalFields[k][6]) nlFieldDict[ 'h'].append((globalFields[k][7].Inverse().eigenValues().x, globalFields[k][7].Inverse().eigenValues().y, globalFields[k][7].Inverse().eigenValues().z, )) # Optionally, pickle the dict to a file. if mpi.rank == 0: if filename is not None: if isinstance(filename, str): with open(filename, 'wb') as fid: pickle.dump(nlFieldDict, fid) pass pass else: msg = "Dict NOT pickled to file because " + \ "argument 2 is {} instead of {}".format(type(filename), type('x')) sys.stderr.write(msg+'\n') pass pass pass # And Bob's our uncle. if not silent: print "Done." return nlFieldDict
def __init__(self, R, rCore, eosMantle, eosCore, nbins = 100, units=None): """Class constructor for quasi-incompressible two-layer density profile.""" # Minimal input checking assert True if units is None: units = sph.PhysicalConstants(1,1,1) assert isinstance(units, sph.PhysicalConstants) assert units.G == eosMantle.constants.G == eosCore.constants.G # Local variables rvec = np.linspace(0, R, num=nbins) dvec = np.ones(rvec.size)*np.NaN pvec = np.ones(rvec.size)*np.NaN rc = rCore rhoc = eosCore.referenceDensity rhom = eosMantle.referenceDensity assert 0 < rc < R assert rhom <= rhoc r_inner = rvec[rvec <= rc] r_outer = rvec[rvec > rc] # Step one - calculate pressure profile G = units.G c2 = 4*np.pi/3*G*(0.5*rhom**2*R**2 - rhom*(rhoc - rhom)*rc**3/R) c1 = 4*np.pi/3*G*(0.5*rhoc**2 - 1.5*rhom**2 + rhoc*rhom)*rc**2 + c2 p_inner = np.ones(r_inner.size)*np.NaN p_outer = np.ones(r_outer.size)*np.NaN for k in range(r_inner.size): p_inner[k] = c1 - 4*np.pi/3*G*0.5*rhoc**2*r_inner[k]**2 for k in range(r_outer.size): p_outer[k] = c2 - 4*np.pi/3*G*(0.5*rhom**2*r_outer[k]**2 - rhom*(rhoc - rhom)*rc**3/r_outer[k]) assert np.all(np.isfinite(p_inner)) assert np.all(np.isfinite(p_outer)) pvec = np.concatenate((p_inner, p_outer)) # Step two - lion hunt to invert eos and get a density def f(x): return pressure(eos,x,0) - p_hs for k in range(rvec.size): p_hs = pvec[k] if rvec[k] <= rc: eos = eosCore else: eos = eosMantle x_hi = eos.referenceDensity*2 x_lo = eos.referenceDensity/2 while (x_hi - x_lo) > 1e-12*eos.referenceDensity: x_hs = (x_lo + x_hi)/2 if f(x_hs) > 0: x_hi = x_hs else: x_lo = x_hs pass pass dvec[k] = x_hs assert np.all(np.isfinite(dvec)) # Store object data self.rvec = rvec self.dvec = dvec self.pvec = pvec self.units = units # And Bob's our uncle. return
assert isinstance(eos, sph.EquationOfState3d) #assert np.isscalar(rho) #assert np.isscalar(eps) #assert np.isreal(rho) #assert np.isreal(eps) # Assign thermo values to fields and calculate pressure pressure.rhof[0] = rho pressure.epsf[0] = eps eos.setPressure(pressure.peef, pressure.rhof, pressure.epsf) # Extract pressure from field and return return pressure.peef[0] # End function pressure # Static fake node list and thermo fields for function pressure pressure.nodes = sph.makeVoidNodeList('fakenodes',1) pressure.rhof = sph.ScalarField('rho',pressure.nodes) pressure.epsf = sph.ScalarField('eps',pressure.nodes) pressure.peef = sph.ScalarField('pee',pressure.nodes) class HydrostaticQIC1LayerDensityProfile(): """Callable hydrostatic quasi-incompressible density profile.""" #--------------------------------------------------------------------------- # The constructor #--------------------------------------------------------------------------- def __init__(self, R, eos, rho0=None, rmin=0, units=None, nbins=100): """Class constructor for quasi-incompressible density profile. Assuming a barely compressible, one-layer planet, a pressure profile in hydrostatic equilibrium can be found by integrating the hydrostatic
# currently used by pcs into the global workspace. There you can interactively # call the EOS methods and compare different materials. This script can also be # used to extract the code snippets needed to create EOS objects in spheral runs. #------------------------------------------------------------------------------- import sys, os import SolidSpheral3d as sph # The top-level spheral module importer #------------------------------------------------------------------------------- # Setup #------------------------------------------------------------------------------- # Show signs of life. print "Loading spheral equations of state..." # EOS constructors take a units object. I usually work in MKS. units = sph.PhysicalConstants(1.0, # Unit length in meters 1.0, # Unit mass in kg 1.0) # Unit time in seconds #------------------------------------------------------------------------------- # Tillotson EOS for common materials #------------------------------------------------------------------------------- mats = ['Granite', 'Basalt', 'Nylon', 'Pure Ice', '30% Silicate Ice', 'Water'] etamin, etamax = 0.94, 10.0 pext, pmin, pmax = 0.0, -1e200, 1e200 # these are actually the defaults EOSes = [sph.TillotsonEquationOfState(mat, 1e-20, 1e20, units, etamin_solid = etamin, externalPressure = pext, minimumPressure = pmin, maximumPressure = pmax) for mat in mats] granite = EOSes[0] basalt = EOSes[1] nylon = EOSes[2]
import mpi # Mike's simplified mpi wrapper import SolidSpheral3d as sph # The top-level spheral module importer from GenerateNodeDistribution3d import GenerateNodeDistribution3d # basic nl-gens from VoronoiDistributeNodes import distributeNodes3d # the load distributer pcsbase = '' # Edit this with full path to <pcs> if you see an ImportError. sys.path += ['..', pcsbase, os.getenv('PCSBASE', '')] import shelpers # My module of some helper functions #------------------------------------------------------------------------------- # Construct a minimal spheral simulation structure, consisting of a node list, a # node lists generator, a node list distributer, a physics package, an integrator, # and a controller. #------------------------------------------------------------------------------- # First, create an equation of state. units = sph.PhysicalConstants(1.0, 1.0, 1.0) eos = shelpers.construct_eos_for_material('h2oice', units) # Create an empty node list. nodes = sph.makeFluidNodeList('nodelist', eos) # Create a stock generator. generator = GenerateNodeDistribution3d(2, 2, 2, eos.referenceDensity, distributionType='lattice') # Distribute nodes to ranks (suppress with any cl arg to speed things up). if len(sys.argv) == 1: distributeNodes3d((nodes, generator))
pcsbase = '' # Edit this with full path to <pcs> if you see an ImportError. sys.path += ['..',pcsbase,os.getenv('PCSBASE','')] import shelpers # My module of some helper functions #------------------------------------------------------------------------------- # Construct a minimal spheral simulation structure, consisting of a node list, a # node lists generator, a node list distributer, a physics package, an integrator, # and a controller. #------------------------------------------------------------------------------- # First, create an equation of state. units = sph.PhysicalConstants(1.0,1.0,1.0) eos = shelpers.construct_eos_for_material('h2oice',units) # Create an empty node list. nodes = sph.makeFluidNodeList('nodelist', eos) # Create a stock generator. generator = GenerateNodeDistribution3d(2, 2, 2, eos.referenceDensity, distributionType = 'lattice') # Distribute nodes to ranks (suppress with any cl arg to speed things up). if len(sys.argv) == 1: distributeNodes3d((nodes, generator)) # Create a DataBase object to hold the node lists. db = sph.DataBase() db.appendNodeList(nodes) # Create the kernel function for SPH.