			# Pizza.py toolkit, www.cs.sandia.gov/~sjplimp/pizza.html
			# Steve Plimpton, sjplimp@sandia.gov, Sandia National Laboratories
			#
			# Copyright (2005) Sandia Corporation. Under the terms of Contract
			# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
			# certain rights in this software. This software is distributed under
			# the GNU General Public License.

			# dump tool

			oneline = "Read, write, manipulate dump files and particle attributes"

			docstr = """
			d = dump("dump.one") read in one or more dump files
			d = dump("dump.1 dump.2.gz") can be gzipped
			d = dump("dump.*") wildcard expands to multiple files
			d = dump("dump.*",0) two args = store filenames, but don't read

			incomplete and duplicate snapshots are deleted
			if atoms have 5 or 8 columns, assign id,type,x,y,z (ix,iy,iz)
			atoms will be unscaled if stored in files as scaled

			time = d.next() read next snapshot from dump files

			used with 2-argument constructor to allow reading snapshots one-at-a-time
			snapshot will be skipped only if another snapshot has same time stamp
			return time stamp of snapshot read
			return -1 if no snapshots left or last snapshot is incomplete
			no column name assignment or unscaling is performed

			d.map(1,"id",3,"x") assign names to atom columns (1-N)

			not needed if dump file is self-describing

			d.tselect.all() select all timesteps
			d.tselect.one(N) select only timestep N
			d.tselect.none() deselect all timesteps
			d.tselect.skip(M) select every Mth step
			d.tselect.test("$t >= 100 and $t < 10000") select matching timesteps
			d.delete() delete non-selected timesteps

			selecting a timestep also selects all atoms in the timestep
			skip() and test() only select from currently selected timesteps
			test() uses a Python Boolean expression with $t for timestep value
			Python comparison syntax: == != < > <= >= and or

			d.aselect.all() select all atoms in all steps
			d.aselect.all(N) select all atoms in one step
			d.aselect.test("$id > 100 and $type == 2") select match atoms in all steps
			d.aselect.test("$id > 100 and $type == 2",N) select matching atoms in one step

			all() with no args selects atoms from currently selected timesteps
			test() with one arg selects atoms from currently selected timesteps
			test() sub-selects from currently selected atoms
			test() uses a Python Boolean expression with $ for atom attributes
			Python comparison syntax: == != < > <= >= and or
			$name must end with a space

			d.write("file") write selected steps/atoms to dump file
			d.write("file",head,app) write selected steps/atoms to dump file
			d.scatter("tmp") write selected steps/atoms to multiple files

			write() can be specified with 2 additional flags
			headd = 0/1 for no/yes snapshot header, app = 0/1 for write vs append
			scatter() files are given timestep suffix: e.g. tmp.0, tmp.100, etc

			d.scale() scale x,y,z to 0-1 for all timesteps
			d.scale(100) scale atom coords for timestep N
			d.unscale() unscale x,y,z to box size to all timesteps
			d.unscale(1000) unscale atom coords for timestep N
			d.wrap() wrap x,y,z into periodic box via ix,iy,iz
			d.unwrap() unwrap x,y,z out of box via ix,iy,iz
			d.owrap("other") wrap x,y,z to same image as another atom
			d.sort() sort atoms by atom ID in all selected steps
			d.sort("x") sort atoms by column value in all steps
			d.sort(1000) sort atoms in timestep N

			scale(), unscale(), wrap(), unwrap(), owrap() operate on all steps and atoms
			wrap(), unwrap(), owrap() require ix,iy,iz be defined
			owrap() requires a column be defined which contains an atom ID
			name of that column is the argument to owrap()
			x,y,z for each atom is wrapped to same image as the associated atom ID
			useful for wrapping all molecule's atoms the same so it is contiguous

			m1,m2 = d.minmax("type") find min/max values for a column
			d.set("$ke = $vx * $vx + $vy * $vy") set a column to a computed value
			d.setv("type",vector) set a column to a vector of values
			d.spread("ke",N,"color") 2nd col = N ints spread over 1st col
			d.clone(1000,"color") clone timestep N values to other steps

			minmax() operates on selected timesteps and atoms
			set() operates on selected timesteps and atoms
			left hand side column is created if necessary
			left-hand side column is unset or unchanged for non-selected atoms
			equation is in Python syntax
			use $ for column names, $name must end with a space
			setv() operates on selected timesteps and atoms
			if column label does not exist, column is created
			values in vector are assigned sequentially to atoms, so may want to sort()
			length of vector must match # of selected atoms
			spread() operates on selected timesteps and atoms
			min and max are found for 1st specified column across all selected atoms
			atom's value is linear mapping (1-N) between min and max
			that is stored in 2nd column (created if needed)
			useful for creating a color map
			clone() operates on selected timesteps and atoms
			values at every timestep are set to value at timestep N for that atom ID
			useful for propagating a color map

			t = d.time() return vector of selected timestep values
			fx,fy,... = d.atom(100,"fx","fy",...) return vector(s) for atom ID N
			fx,fy,... = d.vecs(1000,"fx","fy",...) return vector(s) for timestep N

			atom() returns vectors with one value for each selected timestep
			vecs() returns vectors with one value for each selected atom in the timestep

			index,time,flag = d.iterator(0/1) loop over dump snapshots
			time,box,atoms,bonds,tris = d.viz(index) return list of viz objects
			d.atype = "color" set column returned as "type" by viz
			d.extra("dump.bond") read bond list from dump file
			d.extra(data) extract bond/tri/line list from data

			iterator() loops over selected timesteps
			iterator() called with arg = 0 first time, with arg = 1 on subsequent calls
			index = index within dump object (0 to # of snapshots)
			time = timestep value
			flag = -1 when iteration is done, 1 otherwise
			viz() returns info for selected atoms for specified timestep index
			time = timestep value
			box = [xlo,ylo,zlo,xhi,yhi,zhi]
			atoms = id,type,x,y,z for each atom as 2d array
			bonds = id,type,x1,y1,z1,x2,y2,z2,t1,t2 for each bond as 2d array
			if bonds() was used to define bonds, else empty list
			tris = id,type,x1,y1,z1,x2,y2,z2,x3,y3,z3,nx,ny,nz for each tri as 2d array
			if extra() was used to define tris, else empty list
			lines = id,type,x1,y1,z1,x2,y2,z2 for each line as 2d array
			if extra() was used to define lines, else empty list
			atype is column name viz() will return as atom type (def = "type")
			extra() stores list of bonds/tris/lines to return each time viz() is called
			"""

			# History
			# 8/05, Steve Plimpton (SNL): original version
			# 12/09, David Hart (SNL): allow use of NumPy or Numeric

			# ToDo list
			# try to optimize this line in read_snap: words += f.readline().split()
			# allow $name in aselect.test() and set() to end with non-space
			# should next() snapshot be auto-unscaled ?

			# Variables
			# flist = list of dump file names
			# increment = 1 if reading snapshots one-at-a-time
			# nextfile = which file to read from via next()
			# eof = ptr into current file for where to read via next()
			# nsnaps = # of snapshots
			# nselect = # of selected snapshots
			# snaps = list of snapshots
			# names = dictionary of column names:
			# key = "id", value = column # (0 to M-1)
			# tselect = class for time selection
			# aselect = class for atom selection
			# atype = name of vector used as atom type by viz extract
			# bondflag = 0 if no bonds, 1 if they are defined statically
			# bondlist = static list of bonds to viz() return for all snapshots
			# only a list of atom pairs, coords have to be created for each snapshot
			# triflag = 0 if no tris, 1 if they are defined statically, 2 if dynamic
			# trilist = static list of tris to return via viz() for all snapshots
			# lineflag = 0 if no lines, 1 if they are defined statically
			# linelist = static list of lines to return via viz() for all snapshots
			# Snap = one snapshot
			# time = time stamp
			# tselect = 0/1 if this snapshot selected
			# natoms = # of atoms
			# nselect = # of selected atoms in this snapshot
			# aselect[i] = 0/1 for each atom
			# xlo,xhi,ylo,yhi,zlo,zhi = box bounds (float)
			# atoms[i][j] = 2d array of floats, i = 0 to natoms-1, j = 0 to ncols-1

			# Imports and external programs

			import sys, commands, re, glob, types
			from os import popen
			from math import * # any function could be used by set()

			try:
			import numpy as np
			oldnumeric = False
			except:
			import Numeric as np
			oldnumeric = True

			try: from DEFAULTS import PIZZA_GUNZIP
			except: PIZZA_GUNZIP = "gunzip"

			# Class definition

			class dump:

			# --------------------------------------------------------------------

			def __init__(self,*list):
			self.snaps = []
			self.nsnaps = self.nselect = 0
			self.names = {}
			self.tselect = tselect(self)
			self.aselect = aselect(self)
			self.atype = "type"
			self.bondflag = 0
			self.bondlist = []
			self.triflag = 0
			self.trilist = []
			self.triobj = 0
			self.lineflag = 0
			self.linelist = []

			# flist = list of all dump file names

			words = list[0].split()
			self.flist = []
			for word in words: self.flist += glob.glob(word)
			if len(self.flist) == 0 and len(list) == 1:
			raise StandardError,"no dump file specified"

			if len(list) == 1:
			self.increment = 0
			self.read_all()
			else:
			self.increment = 1
			self.nextfile = 0
			self.eof = 0

			# --------------------------------------------------------------------

			def read_all(self):

			# read all snapshots from each file
			# test for gzipped files

			for file in self.flist:
			if file[-3:] == ".gz":
			f = popen("%s -c %s" % (PIZZA_GUNZIP,file),'r')
			else: f = open(file)

			snap = self.read_snapshot(f)
			while snap:
			self.snaps.append(snap)
			print snap.time,
			sys.stdout.flush()
			snap = self.read_snapshot(f)

			f.close()
			print

			# sort entries by timestep, cull duplicates

			self.snaps.sort(self.compare_time)
			self.cull()
			self.nsnaps = len(self.snaps)
			print "read %d snapshots" % self.nsnaps

			# select all timesteps and atoms

			self.tselect.all()

			# set default names for atom columns if file wasn't self-describing

			if len(self.snaps) == 0:
			print "no column assignments made"
			elif len(self.names):
			print "assigned columns:",self.names2str()
			elif self.snaps[0].atoms == None:
			print "no column assignments made"
			elif len(self.snaps[0].atoms[0]) == 5:
			self.map(1,"id",2,"type",3,"x",4,"y",5,"z")
			print "assigned columns:",self.names2str()
			elif len(self.snaps[0].atoms[0]) == 8:
			self.map(1,"id",2,"type",3,"x",4,"y",5,"z",6,"ix",7,"iy",8,"iz")
			print "assigned columns:",self.names2str()
			else:
			print "no column assignments made"

			# if snapshots are scaled, unscale them

			if (not self.names.has_key("x")) or \
			(not self.names.has_key("y")) or \
			(not self.names.has_key("z")):
			print "no unscaling could be performed"
			elif self.nsnaps > 0:
			if self.scaled(self.nsnaps-1): self.unscale()
			else: print "dump is already unscaled"

			# --------------------------------------------------------------------
			# read next snapshot from list of files

			def next(self):

			if not self.increment: raise StandardError,"cannot read incrementally"

			# read next snapshot in current file using eof as pointer
			# if fail, try next file
			# if new snapshot time stamp already exists, read next snapshot

			while 1:
			f = open(self.flist[self.nextfile],'rb')
			f.seek(self.eof)
			snap = self.read_snapshot(f)
			if not snap:
			self.nextfile += 1
			if self.nextfile == len(self.flist): return -1
			f.close()
			self.eof = 0
			continue
			self.eof = f.tell()
			f.close()
			try:
			self.findtime(snap.time)
			continue
			except: break

			# select the new snapshot with all its atoms

			self.snaps.append(snap)
			snap = self.snaps[self.nsnaps]
			snap.tselect = 1
			snap.nselect = snap.natoms
			for i in xrange(snap.natoms): snap.aselect[i] = 1
			self.nsnaps += 1
			self.nselect += 1

			return snap.time

			# --------------------------------------------------------------------
			# read a single snapshot from file f
			# return snapshot or 0 if failed
			# assign column names if not already done and file is self-describing
			# convert xs,xu to x

			def read_snapshot(self,f):
			try:
			snap = Snap()
			item = f.readline()
			snap.time = int(f.readline().split()[0]) # just grab 1st field
			item = f.readline()
			snap.natoms = int(f.readline())

			snap.aselect = np.zeros(snap.natoms)

			item = f.readline()
			words = f.readline().split()
			snap.xlo,snap.xhi = float(words[0]),float(words[1])
			words = f.readline().split()
			snap.ylo,snap.yhi = float(words[0]),float(words[1])
			words = f.readline().split()
			snap.zlo,snap.zhi = float(words[0]),float(words[1])

			item = f.readline()
			if len(self.names) == 0:
			words = item.split()[2:]
			if len(words):
			for i in range(len(words)):
			if words[i] == "xs" or words[i] == "xu":
			self.names["x"] = i
			elif words[i] == "ys" or words[i] == "yu":
			self.names["y"] = i
			elif words[i] == "zs" or words[i] == "zu":
			self.names["z"] = i
			else: self.names[words[i]] = i

			if snap.natoms:
			words = f.readline().split()
			ncol = len(words)
			for i in xrange(1,snap.natoms):
			words += f.readline().split()
			floats = map(float,words)
			if oldnumeric: atoms = np.zeros((snap.natoms,ncol),np.Float)
			else: atoms = np.zeros((snap.natoms,ncol),np.float)
			start = 0
			stop = ncol
			for i in xrange(snap.natoms):
			atoms[i] = floats[start:stop]
			start = stop
			stop += ncol
			else: atoms = None
			snap.atoms = atoms
			return snap
			except:
			return 0

			# --------------------------------------------------------------------
			# decide if snapshot i is scaled/unscaled from coords of first and last atom

			def scaled(self,i):
			ix = self.names["x"]
			iy = self.names["y"]
			iz = self.names["z"]
			natoms = self.snaps[i].natoms
			if natoms == 0: return 0
			x1 = self.snaps[i].atoms[0][ix]
			y1 = self.snaps[i].atoms[0][iy]
			z1 = self.snaps[i].atoms[0][iz]
			x2 = self.snaps[i].atoms[natoms-1][ix]
			y2 = self.snaps[i].atoms[natoms-1][iy]
			z2 = self.snaps[i].atoms[natoms-1][iz]
			if x1 >= -0.1 and x1 <= 1.1 and y1 >= -0.1 and y1 <= 1.1 and \
			z1 >= -0.1 and z1 <= 1.1 and x2 >= -0.1 and x2 <= 1.1 and \
			y2 >= -0.1 and y2 <= 1.1 and z2 >= -0.1 and z2 <= 1.1:
			return 1
			else: return 0

			# --------------------------------------------------------------------
			# map atom column names

			def map(self,*pairs):
			if len(pairs) % 2 != 0:
			raise StandardError, "dump map() requires pairs of mappings"
			for i in range(0,len(pairs),2):
			j = i + 1
			self.names[pairs[j]] = pairs[i]-1

			# delete unselected snapshots

			# --------------------------------------------------------------------

			def delete(self):
			ndel = i = 0
			while i < self.nsnaps:
			if not self.snaps[i].tselect:
			del self.snaps[i]
			self.nsnaps -= 1
			ndel += 1
			else: i += 1
			print "%d snapshots deleted" % ndel
			print "%d snapshots remaining" % self.nsnaps

			# --------------------------------------------------------------------
			# scale coords to 0-1 for all snapshots or just one

			def scale(self,*list):
			if len(list) == 0:
			print "Scaling dump ..."
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			for snap in self.snaps: self.scale_one(snap,x,y,z)
			else:
			i = self.findtime(list[0])
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			self.scale_one(self.snaps[i],x,y,z)

			# --------------------------------------------------------------------

			def scale_one(self,snap,x,y,z):
			xprdinv = 1.0 / (snap.xhi - snap.xlo)
			yprdinv = 1.0 / (snap.yhi - snap.ylo)
			zprdinv = 1.0 / (snap.zhi - snap.zlo)
			atoms = snap.atoms
			atoms[:,x] = (atoms[:,x] - snap.xlo) * xprdinv
			atoms[:,y] = (atoms[:,y] - snap.ylo) * yprdinv
			atoms[:,z] = (atoms[:,z] - snap.zlo) * zprdinv

			# --------------------------------------------------------------------
			# unscale coords from 0-1 to box size for all snapshots or just one

			def unscale(self,*list):
			if len(list) == 0:
			print "Unscaling dump ..."
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			for snap in self.snaps: self.unscale_one(snap,x,y,z)
			else:
			i = self.findtime(list[0])
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			self.unscale_one(self.snaps[i],x,y,z)

			# --------------------------------------------------------------------

			def unscale_one(self,snap,x,y,z):
			xprd = snap.xhi - snap.xlo
			yprd = snap.yhi - snap.ylo
			zprd = snap.zhi - snap.zlo
			atoms = snap.atoms
			atoms[:,x] = snap.xlo + atoms[:,x]*xprd
			atoms[:,y] = snap.ylo + atoms[:,y]*yprd
			atoms[:,z] = snap.zlo + atoms[:,z]*zprd

			# --------------------------------------------------------------------
			# wrap coords from outside box to inside

			def wrap(self):
			print "Wrapping dump ..."

			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			ix = self.names["ix"]
			iy = self.names["iy"]
			iz = self.names["iz"]

			for snap in self.snaps:
			xprd = snap.xhi - snap.xlo
			yprd = snap.yhi - snap.ylo
			zprd = snap.zhi - snap.zlo
			atoms = snap.atoms
			atoms[:,x] -= atoms[:,ix]*xprd
			atoms[:,y] -= atoms[:,iy]*yprd
			atoms[:,z] -= atoms[:,iz]*zprd

			# --------------------------------------------------------------------
			# unwrap coords from inside box to outside

			def unwrap(self):
			print "Unwrapping dump ..."

			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			ix = self.names["ix"]
			iy = self.names["iy"]
			iz = self.names["iz"]

			for snap in self.snaps:
			xprd = snap.xhi - snap.xlo
			yprd = snap.yhi - snap.ylo
			zprd = snap.zhi - snap.zlo
			atoms = snap.atoms
			atoms[:,x] += atoms[:,ix]*xprd
			atoms[:,y] += atoms[:,iy]*yprd
			atoms[:,z] += atoms[:,iz]*zprd

			# --------------------------------------------------------------------
			# wrap coords to same image as atom ID stored in "other" column

			def owrap(self,other):
			print "Wrapping to other ..."

			id = self.names["id"]
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]
			ix = self.names["ix"]
			iy = self.names["iy"]
			iz = self.names["iz"]
			iother = self.names[other]

			for snap in self.snaps:
			xprd = snap.xhi - snap.xlo
			yprd = snap.yhi - snap.ylo
			zprd = snap.zhi - snap.zlo
			atoms = snap.atoms
			ids = {}
			for i in xrange(snap.natoms):
			ids[atoms[i][id]] = i
			for i in xrange(snap.natoms):
			j = ids[atoms[i][iother]]
			atoms[i][x] += (atoms[i][ix]-atoms[j][ix])*xprd
			atoms[i][y] += (atoms[i][iy]-atoms[j][iy])*yprd
			atoms[i][z] += (atoms[i][iz]-atoms[j][iz])*zprd

			# --------------------------------------------------------------------
			# convert column names assignment to a string, in column order

			def names2str(self):
			ncol = len(self.snaps[0].atoms[0])
			pairs = self.names.items()
			values = self.names.values()
			str = ""
			for i in xrange(ncol):
			if i in values: str += pairs[values.index(i)][0] + ' '
			return str

			# --------------------------------------------------------------------
			# sort atoms by atom ID in all selected timesteps by default
			# if arg = string, sort all steps by that column
			# if arg = numeric, sort atoms in single step

			def sort(self,*list):
			if len(list) == 0:
			print "Sorting selected snapshots ..."
			id = self.names["id"]
			for snap in self.snaps:
			if snap.tselect: self.sort_one(snap,id)
			elif type(list[0]) is types.StringType:
			print "Sorting selected snapshots by %s ..." % list[0]
			id = self.names[list[0]]
			for snap in self.snaps:
			if snap.tselect: self.sort_one(snap,id)
			else:
			i = self.findtime(list[0])
			id = self.names["id"]
			self.sort_one(self.snaps[i],id)

			# --------------------------------------------------------------------
			# sort a single snapshot by ID column

			def sort_one(self,snap,id):
			atoms = snap.atoms
			ids = atoms[:,id]
			ordering = np.argsort(ids)
			for i in xrange(len(atoms[0])):
			atoms[:,i] = np.take(atoms[:,i],ordering)

			# --------------------------------------------------------------------
			# write a single dump file from current selection

			def write(self,file,header=1,append=0):
			if len(self.snaps): namestr = self.names2str()
			if not append: f = open(file,"w")
			else: f = open(file,"a")
			for snap in self.snaps:
			if not snap.tselect: continue
			print snap.time,
			sys.stdout.flush()

			if header:
			print >>f,"ITEM: TIMESTEP"
			print >>f,snap.time
			print >>f,"ITEM: NUMBER OF ATOMS"
			print >>f,snap.nselect
			print >>f,"ITEM: BOX BOUNDS"
			print >>f,snap.xlo,snap.xhi
			print >>f,snap.ylo,snap.yhi
			print >>f,snap.zlo,snap.zhi
			print >>f,"ITEM: ATOMS",namestr

			atoms = snap.atoms
			nvalues = len(atoms[0])
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			line = ""
			for j in xrange(nvalues):
			if (j < 2):
			line += str(int(atoms[i][j])) + " "
			else:
			line += str(atoms[i][j]) + " "
			print >>f,line
			f.close()
			print "\n%d snapshots" % self.nselect

			# --------------------------------------------------------------------
			# write one dump file per snapshot from current selection

			def scatter(self,root):
			if len(self.snaps): namestr = self.names2str()
			for snap in self.snaps:
			if not snap.tselect: continue
			print snap.time,
			sys.stdout.flush()

			file = root + "." + str(snap.time)
			f = open(file,"w")
			print >>f,"ITEM: TIMESTEP"
			print >>f,snap.time
			print >>f,"ITEM: NUMBER OF ATOMS"
			print >>f,snap.nselect
			print >>f,"ITEM: BOX BOUNDS"
			print >>f,snap.xlo,snap.xhi
			print >>f,snap.ylo,snap.yhi
			print >>f,snap.zlo,snap.zhi
			print >>f,"ITEM: ATOMS",namestr

			atoms = snap.atoms
			nvalues = len(atoms[0])
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			line = ""
			for j in xrange(nvalues):
			if (j < 2):
			line += str(int(atoms[i][j])) + " "
			else:
			line += str(atoms[i][j]) + " "
			print >>f,line
			f.close()
			print "\n%d snapshots" % self.nselect

			# --------------------------------------------------------------------
			# find min/max across all selected snapshots/atoms for a particular column

			def minmax(self,colname):
			icol = self.names[colname]
			min = 1.0e20
			max = -min
			for snap in self.snaps:
			if not snap.tselect: continue
			atoms = snap.atoms
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			if atoms[i][icol] < min: min = atoms[i][icol]
			if atoms[i][icol] > max: max = atoms[i][icol]
			return (min,max)

			# --------------------------------------------------------------------
			# set a column value via an equation for all selected snapshots

			def set(self,eq):
			print "Setting ..."
			pattern = "\$\w*"
			list = re.findall(pattern,eq)

			lhs = list[0][1:]
			if not self.names.has_key(lhs):
			self.newcolumn(lhs)

			for item in list:
			name = item[1:]
			column = self.names[name]
			insert = "snap.atoms[i][%d]" % (column)
			eq = eq.replace(item,insert)
			ceq = compile(eq,'','single')

			for snap in self.snaps:
			if not snap.tselect: continue
			for i in xrange(snap.natoms):
			if snap.aselect[i]: exec ceq

			# --------------------------------------------------------------------
			# set a column value via an input vec for all selected snapshots/atoms

			def setv(self,colname,vec):
			print "Setting ..."
			if not self.names.has_key(colname):
			self.newcolumn(colname)
			icol = self.names[colname]

			for snap in self.snaps:
			if not snap.tselect: continue
			if snap.nselect != len(vec):
			raise StandardError,"vec length does not match # of selected atoms"
			atoms = snap.atoms
			m = 0
			for i in xrange(snap.natoms):
			if snap.aselect[i]:
			atoms[i][icol] = vec[m]
			m += 1

			# --------------------------------------------------------------------
			# clone value in col across selected timesteps for atoms with same ID

			def clone(self,nstep,col):
			istep = self.findtime(nstep)
			icol = self.names[col]
			id = self.names["id"]
			ids = {}
			for i in xrange(self.snaps[istep].natoms):
			ids[self.snaps[istep].atoms[i][id]] = i
			for snap in self.snaps:
			if not snap.tselect: continue
			atoms = snap.atoms
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			j = ids[atoms[i][id]]
			atoms[i][icol] = self.snaps[istep].atoms[j][icol]

			# --------------------------------------------------------------------
			# values in old column are spread as ints from 1-N and assigned to new column

			def spread(self,old,n,new):
			iold = self.names[old]
			if not self.names.has_key(new): self.newcolumn(new)
			inew = self.names[new]

			min,max = self.minmax(old)
			print "min/max = ",min,max

			gap = max - min
			invdelta = n/gap
			for snap in self.snaps:
			if not snap.tselect: continue
			atoms = snap.atoms
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			ivalue = int((atoms[i][iold] - min) * invdelta) + 1
			if ivalue > n: ivalue = n
			if ivalue < 1: ivalue = 1
			atoms[i][inew] = ivalue

			# --------------------------------------------------------------------
			# return vector of selected snapshot time stamps

			def time(self):
			vec = self.nselect * [0]
			i = 0
			for snap in self.snaps:
			if not snap.tselect: continue
			vec[i] = snap.time
			i += 1
			return vec

			# --------------------------------------------------------------------
			# extract vector(s) of values for atom ID n at each selected timestep

			def atom(self,n,*list):
			if len(list) == 0:
			raise StandardError, "no columns specified"
			columns = []
			values = []
			for name in list:
			columns.append(self.names[name])
			values.append(self.nselect * [0])
			ncol = len(columns)

			id = self.names["id"]
			m = 0
			for snap in self.snaps:
			if not snap.tselect: continue
			atoms = snap.atoms
			for i in xrange(snap.natoms):
			if atoms[i][id] == n: break
			if atoms[i][id] != n:
			raise StandardError, "could not find atom ID in snapshot"
			for j in xrange(ncol):
			values[j][m] = atoms[i][columns[j]]
			m += 1

			if len(list) == 1: return values[0]
			else: return values

			# --------------------------------------------------------------------
			# extract vector(s) of values for selected atoms at chosen timestep

			def vecs(self,n,*list):
			snap = self.snaps[self.findtime(n)]

			if len(list) == 0:
			raise StandardError, "no columns specified"
			columns = []
			values = []
			for name in list:
			columns.append(self.names[name])
			values.append(snap.nselect * [0])
			ncol = len(columns)

			m = 0
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			for j in xrange(ncol):
			values[j][m] = snap.atoms[i][columns[j]]
			m += 1

			if len(list) == 1: return values[0]
			else: return values

			# --------------------------------------------------------------------
			# add a new column to every snapshot and set value to 0
			# set the name of the column to str

			def newcolumn(self,str):
			ncol = len(self.snaps[0].atoms[0])
			self.map(ncol+1,str)
			for snap in self.snaps:
			atoms = snap.atoms
			if oldnumeric: newatoms = np.zeros((snap.natoms,ncol+1),np.Float)
			else: newatoms = np.zeros((snap.natoms,ncol+1),np.float)
			newatoms[:,0:ncol] = snap.atoms
			snap.atoms = newatoms

			# --------------------------------------------------------------------
			# sort snapshots on time stamp

			def compare_time(self,a,b):
			if a.time < b.time:
			return -1
			elif a.time > b.time:
			return 1
			else:
			return 0

			# --------------------------------------------------------------------
			# delete successive snapshots with duplicate time stamp

			def cull(self):
			i = 1
			while i < len(self.snaps):
			if self.snaps[i].time == self.snaps[i-1].time:
			del self.snaps[i]
			else:
			i += 1

			# --------------------------------------------------------------------
			# iterate over selected snapshots

			def iterator(self,flag):
			start = 0
			if flag: start = self.iterate + 1
			for i in xrange(start,self.nsnaps):
			if self.snaps[i].tselect:
			self.iterate = i
			return i,self.snaps[i].time,1
			return 0,0,-1

			# --------------------------------------------------------------------
			# return list of atoms to viz for snapshot isnap
			# augment with bonds, tris, lines if extra() was invoked

			def viz(self,isnap):
			snap = self.snaps[isnap]

			time = snap.time
			box = [snap.xlo,snap.ylo,snap.zlo,snap.xhi,snap.yhi,snap.zhi]
			id = self.names["id"]
			type = self.names[self.atype]
			x = self.names["x"]
			y = self.names["y"]
			z = self.names["z"]

			# create atom list needed by viz from id,type,x,y,z
			# need Numeric/Numpy mode here

			atoms = []
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			atom = snap.atoms[i]
			atoms.append([atom[id],atom[type],atom[x],atom[y],atom[z]])

			# create list of current bond coords from static bondlist
			# alist = dictionary of atom IDs for atoms list
			# lookup bond atom IDs in alist and grab their coords
			# try is used since some atoms may be unselected
			# any bond with unselected atom is not returned to viz caller
			# need Numeric/Numpy mode here

			bonds = []
			if self.bondflag:
			alist = {}
			for i in xrange(len(atoms)): alist[int(atoms[i][0])] = i
			for bond in self.bondlist:
			try:
			i = alist[bond[2]]
			j = alist[bond[3]]
			atom1 = atoms[i]
			atom2 = atoms[j]
			bonds.append([bond[0],bond[1],atom1[2],atom1[3],atom1[4],
			atom2[2],atom2[3],atom2[4],atom1[1],atom2[1]])
			except: continue

			tris = []
			if self.triflag:
			if self.triflag == 1: tris = self.trilist
			elif self.triflag == 2:
			timetmp,boxtmp,atomstmp,bondstmp, \
			tris,linestmp = self.triobj.viz(time,1)

			lines = []
			if self.lineflag: lines = self.linelist

			return time,box,atoms,bonds,tris,lines

			# --------------------------------------------------------------------

			def findtime(self,n):
			for i in xrange(self.nsnaps):
			if self.snaps[i].time == n: return i
			raise StandardError, "no step %d exists" % n

			# --------------------------------------------------------------------
			# return maximum box size across all selected snapshots

			def maxbox(self):
			xlo = ylo = zlo = None
			xhi = yhi = zhi = None
			for snap in self.snaps:
			if not snap.tselect: continue
			if xlo == None or snap.xlo < xlo: xlo = snap.xlo
			if xhi == None or snap.xhi > xhi: xhi = snap.xhi
			if ylo == None or snap.ylo < ylo: ylo = snap.ylo
			if yhi == None or snap.yhi > yhi: yhi = snap.yhi
			if zlo == None or snap.zlo < zlo: zlo = snap.zlo
			if zhi == None or snap.zhi > zhi: zhi = snap.zhi
			return [xlo,ylo,zlo,xhi,yhi,zhi]

			# --------------------------------------------------------------------
			# return maximum atom type across all selected snapshots and atoms

			def maxtype(self):
			icol = self.names["type"]
			max = 0
			for snap in self.snaps:
			if not snap.tselect: continue
			atoms = snap.atoms
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			if atoms[i][icol] > max: max = atoms[i][icol]
			return int(max)

			# --------------------------------------------------------------------
			# grab bonds/tris/lines from another object

			def extra(self,arg):

			# read bonds from bond dump file

			if type(arg) is types.StringType:
			try:
			f = open(arg,'r')

			item = f.readline()
			time = int(f.readline())
			item = f.readline()
			nbonds = int(f.readline())
			item = f.readline()
			if not re.search("BONDS",item):
			raise StandardError, "could not read bonds from dump file"

			words = f.readline().split()
			ncol = len(words)
			for i in xrange(1,nbonds):
			words += f.readline().split()
			f.close()

			# convert values to int and absolute value since can be negative types

			if oldnumeric: bondlist = np.zeros((nbonds,4),np.Int)
			else: bondlist = np.zeros((nbonds,4),np.int)
			ints = [abs(int(value)) for value in words]
			start = 0
			stop = 4
			for i in xrange(nbonds):
			bondlist[i] = ints[start:stop]
			start += ncol
			stop += ncol
			if bondlist:
			self.bondflag = 1
			self.bondlist = bondlist
			except:
			raise StandardError,"could not read from bond dump file"

			# request bonds from data object

			elif type(arg) is types.InstanceType and ".data" in str(arg.__class__):
			try:
			bondlist = []
			bondlines = arg.sections["Bonds"]
			for line in bondlines:
			words = line.split()
			bondlist.append([int(words[0]),int(words[1]),
			int(words[2]),int(words[3])])
			if bondlist:
			self.bondflag = 1
			self.bondlist = bondlist
			except:
			raise StandardError,"could not extract bonds from data object"

			# request tris/lines from cdata object

			elif type(arg) is types.InstanceType and ".cdata" in str(arg.__class__):
			try:
			tmp,tmp,tmp,tmp,tris,lines = arg.viz(0)
			if tris:
			self.triflag = 1
			self.trilist = tris
			if lines:
			self.lineflag = 1
			self.linelist = lines
			except:
			raise StandardError,"could not extract tris/lines from cdata object"

			# request tris from mdump object

			elif type(arg) is types.InstanceType and ".mdump" in str(arg.__class__):
			try:
			self.triflag = 2
			self.triobj = arg
			except:
			raise StandardError,"could not extract tris from mdump object"

			else:
			raise StandardError,"unrecognized argument to dump.extra()"

			# --------------------------------------------------------------------

			def compare_atom(self,a,b):
			if a[0] < b[0]:
			return -1
			elif a[0] > b[0]:
			return 1
			else:
			return 0

			# --------------------------------------------------------------------
			# one snapshot

			class Snap:
			pass

			# --------------------------------------------------------------------
			# time selection class

			class tselect:

			def __init__(self,data):
			self.data = data

			# --------------------------------------------------------------------

			def all(self):
			data = self.data
			for snap in data.snaps:
			snap.tselect = 1
			data.nselect = len(data.snaps)
			data.aselect.all()
			print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps)

			# --------------------------------------------------------------------

			def one(self,n):
			data = self.data
			for snap in data.snaps:
			snap.tselect = 0
			i = data.findtime(n)
			data.snaps[i].tselect = 1
			data.nselect = 1
			data.aselect.all()
			print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps)

			# --------------------------------------------------------------------

			def none(self):
			data = self.data
			for snap in data.snaps:
			snap.tselect = 0
			data.nselect = 0
			print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps)

			# --------------------------------------------------------------------

			def skip(self,n):
			data = self.data
			count = n-1
			for snap in data.snaps:
			if not snap.tselect: continue
			count += 1
			if count == n:
			count = 0
			continue
			snap.tselect = 0
			data.nselect -= 1
			data.aselect.all()
			print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps)

			# --------------------------------------------------------------------

			def test(self,teststr):
			data = self.data
			snaps = data.snaps
			cmd = "flag = " + teststr.replace("$t","snaps[i].time")
			ccmd = compile(cmd,'','single')
			for i in xrange(data.nsnaps):
			if not snaps[i].tselect: continue
			exec ccmd
			if not flag:
			snaps[i].tselect = 0
			data.nselect -= 1
			data.aselect.all()
			print "%d snapshots selected out of %d" % (data.nselect,data.nsnaps)

			# --------------------------------------------------------------------
			# atom selection class

			class aselect:

			def __init__(self,data):
			self.data = data

			# --------------------------------------------------------------------

			def all(self,*args):
			data = self.data
			if len(args) == 0: # all selected timesteps
			for snap in data.snaps:
			if not snap.tselect: continue
			for i in xrange(snap.natoms): snap.aselect[i] = 1
			snap.nselect = snap.natoms
			else: # one timestep
			n = data.findtime(args[0])
			snap = data.snaps[n]
			for i in xrange(snap.natoms): snap.aselect[i] = 1
			snap.nselect = snap.natoms

			# --------------------------------------------------------------------

			def test(self,teststr,*args):
			data = self.data

			# replace all $var with snap.atoms references and compile test string

			pattern = "\$\w*"
			list = re.findall(pattern,teststr)
			for item in list:
			name = item[1:]
			column = data.names[name]
			insert = "snap.atoms[i][%d]" % column
			teststr = teststr.replace(item,insert)
			cmd = "flag = " + teststr
			ccmd = compile(cmd,'','single')

			if len(args) == 0: # all selected timesteps
			for snap in data.snaps:
			if not snap.tselect: continue
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			exec ccmd
			if not flag:
			snap.aselect[i] = 0
			snap.nselect -= 1
			for i in xrange(data.nsnaps):
			if data.snaps[i].tselect:
			print "%d atoms of %d selected in first step %d" % \
			(data.snaps[i].nselect,data.snaps[i].natoms,data.snaps[i].time)
			break
			for i in xrange(data.nsnaps-1,-1,-1):
			if data.snaps[i].tselect:
			print "%d atoms of %d selected in last step %d" % \
			(data.snaps[i].nselect,data.snaps[i].natoms,data.snaps[i].time)
			break

			else: # one timestep
			n = data.findtime(args[0])
			snap = data.snaps[n]
			for i in xrange(snap.natoms):
			if not snap.aselect[i]: continue
			exec ccmd
			if not flag:
			snap.aselect[i] = 0
			snap.nselect -= 1

lammps/python/examples/pizza/dump.py
9e0598d91891efficient_neuronet

dump.py
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lammps/python/examples/pizza/dump.py9e0598d91891efficient_neuronet

dump.pyView Options

lammps/python/examples/pizza/dump.py
9e0598d91891efficient_neuronet

dump.py
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