diff --git a/atom_decompose/AtomicDecomp.py b/atom_decompose/AtomicDecomp.py deleted file mode 100644 index 6eeee98..0000000 --- a/atom_decompose/AtomicDecomp.py +++ /dev/null @@ -1,49 +0,0 @@ -import numpy as np -import numba -from numba.experimental import jitclass -from numba import float64 -from numba.typed import Dict -from numba.core import types -import os -import pandas as pd -import copy -from utils import SpatialDomainData as spd - -def cell_to_dict_atom(info,ncore): - cell_lists = Dict.empty(key_type=types.int64, value_type=float_array) - for i in range(1,ncore+1): - cell_lists[i] = np.zeros((1,9)) - for i in range(info.shape[0]): - # atomic coordinates, velocity and acceleration - atom = info[i,0:9].reshape(1,9) - atomID = int(np.floor(i*ncore/info.shape[0])) + 1 - cell_lists[atomID] = np.append(cell_lists[atomID],atom,axis=0) - # for i in range(1,ncore): - # cell_lists[i] = cell_lists[i][1:,:] - return cell_lists - -def cell_to_obj_atom(info,ncore): - cell_lists = cell_to_dict_atom(info,ncore) - new_cell_list = {} - for i in range(1, ncore+1): - if cell_lists[i].shape[0]!=0: - pos = cell_lists[i][:,0:3] # position - vel = cell_lists[i][:,3:6] # velocity - acc = cell_lists[i][:,6:9] # acceleration - spatial_domain_data = spd(pos, vel, acc) - new_cell_list[i] = spatial_domain_data - else: - new_cell_list[i] = spd(np.empty((0,3)),np.empty((0,3)),np.empty((0,3))) - return new_cell_list - -def separate_points_atom(infodict,my_rank): - # since we are using atom-wise decomposition, each processor must know every atomic position - neighbor_spd = None - for i, spd in infodict.items(): - if i!=my_rank: - if neighbor_spd is None: - neighbor_spd = copy.deepcopy(spd) - else: - neighbor_spd.concat(spd) - return infodict[my_rank], neighbor_spd - diff --git a/atom_decompose/LJ_AtomicDecomp.py b/atom_decompose/LJ_AtomicDecomp.py new file mode 100644 index 0000000..11f88ed --- /dev/null +++ b/atom_decompose/LJ_AtomicDecomp.py @@ -0,0 +1,51 @@ +from mpi4py import MPI +import numpy as np +import utils_spatial_decompose as ut +import utils_parallel as utp +def LJ_MD(subdiv,position_init,dt,stop_step,accel_init,r_cut,L,T_eq,e_scale,sig, comm): + rank = comm.Get_rank() + #initialization + if rank == 0: + k_B=1.38064852*10**(-23) + size_sim=position_init.shape[0] + x_dot_init=ut.random_vel_generator(size_sim,T_eq,e_scale) + #initialize PE, KE, T_insta, P_insta, Momentum + PE=np.zeros((stop_step+1,1)) + KE=np.zeros((stop_step+1,1)) + T_insta=np.zeros((stop_step+1,1)) + P_insta=np.zeros((stop_step+1,1)) + #initialize the info matrix + info=np.zeros((stop_step+1,size_sim,9)) + info[0,:,:]=np.concatenate((position_init,x_dot_init,accel_init),axis=1) + infotodic=ut.cell_to_obj((info[0,:,:]),subdiv[0],subdiv[1],subdiv[2],L) + #zero step value + PE[0,:]=ut.LJ_potent_nondimen(info[0,:,0:3],r_cut=r_cut,L=L) + KE[0,:]=ut.Kin_Eng(info[0,:,3:6]) + T_insta[0,:]=2*KE[0,:]*e_scale/(3*(size_sim-1)*k_B) #k + P_insta[0,:]=ut.insta_pressure(L,T_insta[0],info[0,:,0:3],r_cut,e_scale) #unitless + + + else: + infotodic=None + comm.barrier() + infotodic=comm.bcast(infotodic,root=0) + for step in range(stop_step): + if rank!=0: + #call the vel_verlet parallel function + utp.par_worker_vel_ver_pre(infotodic,dt,r_cut,L) + else: + info_temp=utp.vel_Ver(infodict=infotodic,dt=dt,r_limit=r_cut,L=L) + print(info_temp) + tmp=ut.concatDict(info_temp) + info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) + #UPDATE CUBES MAKE SURE ATOMS ARE IN RIGHT CUBES + infotodic=ut.cell_to_obj(info[step+1,:,:],subdiv[0],subdiv[1],subdiv[2],L) + #calculate and store PE, KE, T_insta, P_insta + PE[step+1,:]=ut.LJ_potent_nondimen(info[step+1,:,0:3],r_cut=r_cut,L=L) + KE[step+1,:]=ut.Kin_Eng(info[step+1,:,3:6]) + T_insta[step+1,:]=2*KE[step+1,:]*e_scale/(3*(size_sim-1)*k_B) #k + P_insta[step+1,:]=ut.insta_pressure(L,T_insta[step+1],info[step+1,:,0:3],r_cut,e_scale) #unitless + comm.barrier() + infotodic=comm.bcast(infotodic,root=0) + if rank==0: + return info,PE,KE,T_insta,P_insta diff --git a/atom_decompose/MDargon_atomic.py b/atom_decompose/MDargon_atomic.py new file mode 100644 index 0000000..6dff803 --- /dev/null +++ b/atom_decompose/MDargon_atomic.py @@ -0,0 +1,113 @@ +import numpy as np +import time +import copy +from LJ_SpatialDecomp import * +import utils_spatial_decompose as ut +from mpi4py import MPI + +# run params +stop_step=1000 +k_B=1.38064852*10**(-23) +dt=0.002 +file_name='../data/initial_position_LJ_argon256.txt' +info_init=np.loadtxt(file_name) +num_atoms=info_init.shape[0] + +a_init=np.zeros((num_atoms,3)) +r_c=2.5 +L0=6.8 +#cube division +subdiv=np.array([2,2,1]) +energy_scale=1.66*10**(-21)#unit: J, Argon +sigma=3.4 #unit: Ang, Argon +T_dimensional_equal=300#unit K +T_equal=T_dimensional_equal*k_B/energy_scale +part_type='LJ' +name='argon256' + +comm = MPI.COMM_WORLD +rank = comm.Get_rank() +size = comm.Get_size() +print(rank,size) +comm.barrier() + +if rank==0: + start_time = time.time() + # # initialize + k_B=1.38064852*10**(-23) + size_sim=info_init.shape[0] + # x_dot_init=ut.random_vel_generator(size_sim,T_equal,energy_scale) + #initialize PE, KE, T_insta, P_insta, Momentum + PE=np.zeros((stop_step+1,1)) + KE=np.zeros((stop_step+1,1)) + T_insta=np.zeros((stop_step+1,1)) + P_insta=np.zeros((stop_step+1,1)) + #initialize the info matrix + info=np.zeros((stop_step+1,size_sim,9)) + # info[0,:,:]=np.concatenate((position_init,x_dot_init,a_init),axis=1) + info[0,:,:] = info_init + # np.savetxt('../data/init.txt',info[0,:,:],fmt='%.6f') + infotodic=ut.cell_to_obj((info[0,:,:]),subdiv[0],subdiv[1],subdiv[2],L0) + #zero step value + PE[0,:]=ut.LJ_potent_nondimen(info[0,:,0:3],r_cut=r_c,L=L0) + KE[0,:]=ut.Kin_Eng(info[0,:,3:6]) + T_insta[0,:]=2*KE[0,:]*energy_scale/(3*(size_sim-1)*k_B) #k + P_insta[0,:]=ut.insta_pressure(L0,T_insta[0],info[0,:,0:3],r_c,energy_scale) #unitless +else: + infotodic = None + # info = None +comm.barrier() +infotodic = comm.bcast(infotodic, root = 0) + +# Run MD +for step in range(stop_step): + my_spd_send=utp.vel_Ver( + comm = comm, + infodict=infotodic, + dt=dt, + r_limit=r_c, + L=L0, + my_rank=rank + ) + temp_infodict=comm.gather(my_spd_send,root=0) + if rank == 0: + if step%10==0: + print('current time step is ', step) + temp_infodict=list(filter(None, temp_infodict)) + info_temp=dict(temp_infodict) + tmp=ut.concatDict(info_temp) + info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) + #UPDATE CUBES MAKE SURE ATOMS ARE IN RIGHT CUBES + infotodic=ut.cell_to_obj(info[step+1,:,:],subdiv[0],subdiv[1],subdiv[2],L0) + #calculate and store PE, KE, T_insta, P_insta + PE[step+1,:]=ut.LJ_potent_nondimen(info[step+1,:,0:3],r_cut=r_c,L=L0) + KE[step+1,:]=ut.Kin_Eng(info[step+1,:,3:6]) + T_insta[step+1,:]=2*KE[step+1,:]*energy_scale/(3*(size_sim-1)*k_B) #k + P_insta[step+1,:]=ut.insta_pressure(L0,T_insta[step+1],info[step+1,:,0:3],r_c,energy_scale) #unitless + comm.barrier() + infotodic=comm.bcast(infotodic,root=0) + +if rank == 0: + end_time = time.time() + period = end_time-start_time + print(f'Run time is {period:.3f} seconds') + ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, stop_step, False) +comm.barrier() + +# if rank==0: +# start_time=time.time() +# info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, +# position_init=position_init, +# dt=dt, +# stop_step=stop_step, +# accel_init=a_init, +# r_cut=2.8, +# L=L0, +# T_eq=T_equal, +# e_scale=energy_scale, +# sig=sigma) +# end_time=time.time() +# period = end_time-start_time +# print("For this {} steps operation (dt={}) with r_cut = {} and L = {}, it took:".format(stop_step,dt,r_c,L0),end_time-start_time,'s') +# ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, 1000, False) +# else: diff --git a/atom_decompose/utils_atomic_decompose.py b/atom_decompose/utils_atomic_decompose.py new file mode 100644 index 0000000..c59dd5d --- /dev/null +++ b/atom_decompose/utils_atomic_decompose.py @@ -0,0 +1,215 @@ +import numpy as np +import numba +from numba.experimental import jitclass +from numba import float64 +from numba.typed import Dict +from numba.core import types +import os +import pandas as pd +import copy +from utils import SpatialDomainData as spd + +class SpatialDomainData: + #This class creates objects for storing position, velocity and acceleration information + ##This class contain three functions: + ###__init__ (description) + ###__repr__ (description) + ###concat(description) + def __init__(self, position=np.array([]), velocity=np.array([]), acceleration=np.array([])): + self.P = position + self.V = velocity + self.A = acceleration + + def __repr__(self): + return "(P:{}, V:{}, A:{})".format(self.P, self.V, self.A) + + def concat(self, other): + self.P = np.concatenate((self.P, other.P), 0) + self.V = np.concatenate((self.V, other.V), 0) + self.A = np.concatenate((self.A, other.A), 0) + +# @numba.njit +def pbc1(position,L): + ##This function perform the first rule of periodic boundary condition + #Input: position -- the position before PBC1 + # L -- the simulation cell size + #Ouput: x_new -- the updated position after PBC1 + position_new=np.zeros((position.shape[0],3)) + for i in range(position.shape[0]): + position_ind=position[i,:] + position_empty=np.zeros((1,3)) + for j in range(3): + # position_axis=numba.float64(position_ind[j]) + position_axis = position_ind[j] + if position_axis < 0: + position_axis_new=position_axis+L + elif position_axis > L: + position_axis_new=position_axis-L + else: + position_axis_new=position_axis + position_empty[:,j]=position_axis_new + position_new[i,:]=position_empty + return position_new + +# @numba.njit +def pbc2(separation,L): + ##This function perform the second rule of periodic boundary condition + #Input: separation -- separation before PBC2 + # L -- the simulation cell size + #Ouput: separation_new -- the updated separation after PBC2 + separation_new=np.zeros((separation.shape[0],3)) + for i in range(separation.shape[0]): + separation_ind=separation[i,:] + separation_empty=np.zeros((1,3)) + for j in range(3): + # separation_axis=numba.float64(separation_ind[j]) + separation_axis = separation_ind[j] + if separation_axis < -L/2: + separation_axis_new=separation_axis+L + elif separation_axis > L/2: + separation_axis_new=separation_axis-L + else: + separation_axis_new=separation_axis + separation_empty[:,j]=separation_axis_new + separation_new[i,:]=separation_empty + return separation_new + +# @numba.njit +def random_vel_generator(n,T_equal,e_scale): + ##This function generate random initial velocity at the desired temperature + #Input: n -- number of atoms + # T_equal -- the temperature of interests + # e_scale -- the energy scale of the particle of interests + #Ouput: vel_per_particle -- the velocity matrix assigned to all particles + total_k=3*T_equal*(n-1)/2 + vel_per_particle=np.zeros((n,3)) + for axis in range(3): + vel_per_particle[:,axis]=np.random.randn(n,)-0.5 + Mom_x_total=np.sum(vel_per_particle[:,0]) + Mom_y_total=np.sum(vel_per_particle[:,1]) + Mom_z_total=np.sum(vel_per_particle[:,2]) + Mom_x_avg=Mom_x_total/n + Mom_y_avg=Mom_y_total/n + Mom_z_avg=Mom_z_total/n + vel_per_particle=vel_per_particle-np.array([Mom_x_avg,Mom_y_avg,Mom_z_avg]).reshape(1,3) + k_avg_init=0.5*(1/n)*np.sum(np.sum(vel_per_particle**2,axis=1),axis=0) + k_avg_T_eq=total_k/n + scaling_ratio=np.sqrt(k_avg_T_eq/k_avg_init) + vel_per_particle=vel_per_particle*scaling_ratio + return vel_per_particle + +# @numba.njit +def Kin_Eng(velocity): + ##This function compute the average kinetic energy of the system at given the velocity + #Input: velocity -- the velocities of all the particles + #Output: Kinetic_sum -- the average kinetic energy of the system + num=velocity.shape[0] + Kinetic_per=0.5*np.sum(velocity**2,axis=1) + Kinetic_avg=np.sum(Kinetic_per,axis=0) + return Kinetic_avg + +# @numba.njit +def LJ_potent_nondimen(position,r_cut,L): + ##This function compute the nondimensional potential energy of the system at the given position + #Input: position -- the position of all the particles at this instance + # r_cut -- the cutoff for the short-range force field + # L -- the size of the simulation cell + #Output: np.sum(update_LJ) -- the potential energy of the system at this instance + num=position.shape[0] + update_LJ=np.zeros((num-1,1)) + #fix value for a certain r_limit + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + U_rcut=4*(r_cut**(-12)-r_cut**(-6)) + for atom in range(num-1): + position_relevent=position[atom:,:] + position_other=position_relevent[1:,:] + #pbc rule2 + separation=position_relevent[0,:]-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + LJ=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut: + LJ_num=4*r0**(-12)-4*r0**(-6)-U_rcut-(r0-r_cut)*dU_drcut + LJ.append(LJ_num) + update_LJ[atom,:]=np.sum(np.array(LJ),axis=0) + return np.sum(update_LJ) + +# @numba.njit +def insta_pressure(L,T,position,r_cut,e_scale): + ##This function computes the dimensionless pressure + #Inputs: L -- The size of the simulation cell + # T -- The simulation temperature + # position -- The position of all the particles at this time step + # e_scale -- The energy scale of this particles + #Ouputs: pres_insta -- The instant pressure at this moment + num=position.shape[0] + k_B=1.38064852*10**(-23) + V=L**3 + pres_ideal=num*T*(k_B/e_scale)/V + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + pres_virial=np.zeros((num-1,1)) + for atom in range(num-1): + position_relevent=position[atom:,:] + position_other=position_relevent[1:,:] + position_atom=position_relevent[0,:] + #pbc rule 2 + separation=position_atom-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + force=[] + active_r_relat=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut: + #active_r_relat.append(r0) + force_num=-(24*r0**(-7)-48*r0**(-13))+dU_drcut + force.append(force_num) + active_r_relat.append(r0) + #get out the particles inside the r_cut + active_amount=np.array(active_r_relat).shape[0] + rijFij=np.array(active_r_relat).reshape(1,active_amount)@np.array(force).reshape(active_amount,1) + pres_virial[atom,:]=rijFij + pres_insta=pres_ideal+np.sum(pres_virial,axis=0)/(3*V) + return pres_insta + +def cell_to_dict(info,ncore): + # cell_lists = Dict.empty(key_type=types.int64, value_type=float_array) + cell_lists = {} + for i in range(ncore): + cell_lists[i] = np.zeros((1,9)) + for i in range(info.shape[0]): + # atomic coordinates, velocity and acceleration + atom = info[i,0:9].reshape(1,9) + atomID = int(np.floor(i*ncore/info.shape[0])) + 1 + cell_lists[atomID] = np.append(cell_lists[atomID],atom,axis=0) + for i in range(1,ncore): + cell_lists[i] = cell_lists[i][1:,:] + return cell_lists + +def cell_to_obj(info,ncore): + cell_lists = cell_to_dict(info,ncore) + new_cell_list = {} + for i in range(ncore): + if cell_lists[i].shape[0]!=0: + pos = cell_lists[i][:,0:3] # position + vel = cell_lists[i][:,3:6] # velocity + acc = cell_lists[i][:,6:9] # acceleration + spatial_domain_data = spd(pos, vel, acc) + new_cell_list[i] = spatial_domain_data + else: + new_cell_list[i] = spd(np.empty((0,3)),np.empty((0,3)),np.empty((0,3))) + return new_cell_list + +def separate_points_atom(infodict,my_rank): + # since we are using atom-wise decomposition, each processor must know every atomic position + neighbor_spd = None + for i, spd in infodict.items(): + if i!=my_rank: + if neighbor_spd is None: + neighbor_spd = copy.deepcopy(spd) + else: + neighbor_spd.concat(spd) + return infodict[my_rank], neighbor_spd + diff --git a/atom_decompose/utils_parallel.py b/atom_decompose/utils_parallel.py new file mode 100644 index 0000000..e768af6 --- /dev/null +++ b/atom_decompose/utils_parallel.py @@ -0,0 +1,36 @@ +from mpi4py import MPI +# import numba +import utils_spatial_decompose as ut +import numpy as np +import functools +import operator +#@numba.njit() ##This might not be needed +def par_worker_vel_ver_pre(comm,infodict,dt,r_limit,L,my_rank): + vel_Ver(comm,infodict,dt,r_limit,L,my_rank) + +#@numba.njit() +def vel_Ver(comm,infodict,dt,r_limit=2.5,L=6.8,my_rank=0): + # rank = comm.Get_rank() + rank = my_rank + size = comm.Get_size() + ## Get the data for the current spatial domain + my_spd, neighs_spd=ut.separate_points(infodict, rank, size) + # LEAP FROG METHOD + #acceleration at 0 + my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L) + #velocity at dt/2 + my_spd.V=my_spd.V+my_spd.A*(dt/2) + #position at dt + my_spd.P=my_spd.P+my_spd.V*dt + #PBC rule 1 + my_spd.P=ut.pbc1(position=my_spd.P,L=L) + my_spd_send=(rank,my_spd) + comm.barrier() + temp_infodict=comm.allgather(my_spd_send) + # acceleration at dt + my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L) + # velocity at dt + my_spd.V=my_spd.V+my_spd.A*(dt/2) + my_spd_send=(rank,my_spd) + comm.barrier() + return my_spd_send diff --git a/data/initial_position_LJ_argon256.txt b/data/initial_position_LJ_argon256.txt index 8be0137..56a6f4b 100644 --- a/data/initial_position_LJ_argon256.txt +++ b/data/initial_position_LJ_argon256.txt @@ -1,256 +1,256 @@ -0.0 0.0 0.0 -0.0 0.7735294117647059 0.7735294117647059 -0.7735294117647059 0.0 0.7735294117647059 -0.7735294117647059 0.7735294117647059 0.0 -0.0 0.0 1.5470588235294118 -0.0 0.7735294117647059 2.320588235294118 -0.7735294117647059 0.0 2.320588235294118 -0.7735294117647059 0.7735294117647059 1.5470588235294118 -0.0 0.0 3.0941176470588236 -0.0 0.7735294117647059 3.8676470588235294 -0.7735294117647059 0.0 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-0.392743 -0.097274 0.000000 0.000000 0.000000 +4.641176 4.641176 4.641176 1.288781 -0.856180 -0.104208 0.000000 0.000000 0.000000 +4.641176 5.414706 5.414706 -0.461187 -1.266372 -1.465924 0.000000 0.000000 0.000000 +5.414706 4.641176 5.414706 0.455246 0.265014 -0.371489 0.000000 0.000000 0.000000 +5.414706 5.414706 4.641176 -0.372931 -0.082130 -0.277764 0.000000 0.000000 0.000000 diff --git a/init.txt b/init.txt new file mode 100644 index 0000000..e69de29 diff --git a/spatial_decompose/LJ_SpatialDecomp.py b/spatial_decompose/LJ_SpatialDecomp.py index 5eb4089..11f88ed 100644 --- a/spatial_decompose/LJ_SpatialDecomp.py +++ b/spatial_decompose/LJ_SpatialDecomp.py @@ -2,8 +2,7 @@ import numpy as np import utils_spatial_decompose as ut import utils_parallel as utp -def LJ_MD(subdiv,position_init,dt,stop_step,accel_init,r_cut,L,T_eq,e_scale,sig): - comm = MPI.COMM_WORLD +def LJ_MD(subdiv,position_init,dt,stop_step,accel_init,r_cut,L,T_eq,e_scale,sig, comm): rank = comm.Get_rank() #initialization if rank == 0: diff --git a/spatial_decompose/MDargon_serial.py b/spatial_decompose/MDargon_serial.py new file mode 100644 index 0000000..cfcd702 --- /dev/null +++ b/spatial_decompose/MDargon_serial.py @@ -0,0 +1,150 @@ +import numpy as np +import time +import copy +from LJ_SpatialDecomp import * +# import utils_spatial_decompose as ut +import utils as ut +import utils_spatial_decompose +from mpi4py import MPI + + +def LJ_acc(position,r_cut,L, rank): + subcube_atoms=position.shape[0] + #careful kind of confusing + num=position.shape[0] + update_accel=np.zeros((subcube_atoms,3)) + dU_drcut=48*r_cut**(-13)-24*r_cut**(-7) + #for loop is only of subcube we are interested in but we have to account for ALL distance! + for atom in range(subcube_atoms): + position_other=np.concatenate((position[0:atom,:],position[atom+1:num+1,:]),axis=0) + position_atom=position[atom] + separation=position_atom-position_other + separation_new=ut.pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)) + #get out the particles inside the r_cut + accel=np.zeros((r_relat.shape[0],3)) + flag = 0 + for i, r0 in enumerate(r_relat): + if r0 <= r_cut and r0!=0: + separation_active_num=separation_new[i,:] + vector_part=separation_active_num*(1/r0) + scalar_part=48*r0**(-13)-24*r0**(-7)-dU_drcut + accel_num=vector_part*scalar_part + accel[i,:]=accel_num + # if np.abs(position_atom[0]-4.641496)<0.001 and np.abs(position_atom[1]-3.092705)<0.001 and np.abs(position_atom[2]-3.090466)<0.001: + # flag = 1 + # print(position_atom, accel_num, r0) + update_accel[atom,:]=np.sum(accel,axis=0) + # if np.abs(update_accel[atom,:][0]+6.2848242)<1e-4: + # print('update accel',update_accel[atom,:]) + # print(accel[accel.any(axis=1)],r_relat[a + return update_accel.reshape(subcube_atoms,3) + +# # MPI initialize +# comm = MPI.COMM_WORLD +# rank = comm.Get_rank() +# size = comm.Get_size() +# print(rank,size) +# comm.barrier() +rank = 0 +size = 1 + +# run params +stop_step=1000 +k_B=1.38064852*10**(-23) +dt=0.002 +file_name='../data/initial_position_LJ_argon256.txt' +info_init=np.loadtxt(file_name) +num_atoms=info_init.shape[0] + +a_init=np.zeros((num_atoms,3)) +r_c=1.6 +L0=6.8 +#cube division +subdiv=np.array([int(np.sqrt(size)),int(np.sqrt(size)),1]) +energy_scale=1.66*10**(-21)#unit: J, Argon +sigma=3.4 #unit: Ang, Argon +T_dimensional_equal=300#unit K +T_equal=T_dimensional_equal*k_B/energy_scale +part_type='LJ' +name='argon256' + +#initialize PE, KE, T_insta, P_insta, Momentum +PE=np.zeros((stop_step+1,1)) +KE=np.zeros((stop_step+1,1)) +T_insta=np.zeros((stop_step+1,1)) +P_insta=np.zeros((stop_step+1,1)) + +# if rank==0: + +# # initialize +k_B=1.38064852*10**(-23) +size_sim=info_init.shape[0] +# x_dot_init=ut.random_vel_generator(size_sim,T_equal,energy_scale) +#initialize the info matrix +info=np.zeros((stop_step+1,size_sim,9)) +# info[0,:,:]=np.concatenate((position_init,x_dot_init,a_init),axis=1) +start_time = time.time() +info[0,:,:] = info_init +# np.savetxt('../data/init.txt',info[0,:,:],fmt='%.6f') +# infotodic=ut.cell_to_obj((info[0,:,:]),subdiv[0],subdiv[1],subdiv[2],L0) +my_spd = ut.SpatialDomainData(info[0,:,0:3],info[0,:,3:6],info[0,:,6:9]) +#zero step value +PE[0,:]=ut.LJ_potent_nondimen(info[0,:,0:3],r_cut=r_c,L=L0)/2 +KE[0,:]=ut.Kin_Eng(info[0,:,3:6]) +T_insta[0,:]=2*KE[0,:]*energy_scale/(3*(size_sim-1)*k_B) #k +P_insta[0,:]=ut.insta_pressure(L0,T_insta[0],info[0,:,0:3],r_c,energy_scale)/2 #unitless + +# Run MD +for step in range(stop_step): + my_spd.A = LJ_acc(position=my_spd.P,r_cut=r_c,L=L0,rank=0) + my_spd.V=my_spd.V+my_spd.A*(dt) + my_spd.P=my_spd.P+my_spd.V*dt + my_spd.P=ut.pbc1(position=my_spd.P,L=L0) + if step%20==0: + print('current time step is ', step) + # temp_infodict = (0,my_spd) + # temp_infodict=list(filter(None, temp_infodict)) + temp_infodict = [(0,my_spd)] + info_temp=dict(temp_infodict) + # print(info_temp) + tmp=ut.concatDict(info_temp) + info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) + # info[step+1,:,:] = np.round(info[step+1,:,:],4) + info[step+1,:,0:3] = ut.pbc1(info[step+1,:,0:3],L=L0) + #UPDATE CUBES MAKE SURE ATOMS ARE IN RIGHT CUBES + # infotodic=ut.cell_to_obj(info[step+1,:,:],subdiv[0],subdiv[1],subdiv[2],L0) + + #calculate and store PE, KE, T_insta, P_insta in parallel + PE[step+1,:]=ut.LJ_potent_nondimen(info[step+1,:,0:3],r_cut=r_c,L=L0) + KE[step+1,:]=ut.Kin_Eng(info[step+1,:,3:6]) + T_insta[step+1,:]=2*KE[step+1,:]*energy_scale/(3*(size_sim-1)*k_B) #k + P_insta[step+1,:]=ut.insta_pressure(L0,T_insta[step+1],info[step+1,:,0:3],r_c,energy_scale) #unitless + + +end_time = time.time() +period = end_time-start_time +print(f'Run time is {period:.3f} seconds') +PE = np.round(PE,4) +KE = np.round(KE,4) +T_insta = np.round(T_insta,4) +P_insta = np.round(P_insta,4) +utils_spatial_decompose.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, size, False) + +# if rank==0: +# start_time=time.time() +# info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, +# position_init=position_init, +# dt=dt, +# stop_step=stop_step, +# accel_init=a_init, +# r_cut=2.8, +# L=L0, +# T_eq=T_equal, +# e_scale=energy_scale, +# sig=sigma) +# end_time=time.time() +# period = end_time-start_time +# print("For this {} steps operation (dt={}) with r_cut = {} and L = {}, it took:".format(stop_step,dt,r_c,L0),end_time-start_time,'s') +# ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, 1000, False) +# else: diff --git a/spatial_decompose/MDargon_spatial.py b/spatial_decompose/MDargon_spatial.py index 936447d..52ad443 100644 --- a/spatial_decompose/MDargon_spatial.py +++ b/spatial_decompose/MDargon_spatial.py @@ -2,60 +2,443 @@ import time import copy from LJ_SpatialDecomp import * -import utils_spatial_decompose as ut +# import utils_spatial_decompose as ut +from utils_spatial_decompose import data_saver from mpi4py import MPI +class SpatialDomainData: + #This class creates objects for storing position, velocity and acceleration information + ##This class contain three functions: + ###__init__ (description) + ###__repr__ (description) + ###concat(description) + def __init__(self, position=np.array([]), velocity=np.array([]), acceleration=np.array([])): + self.P = position + self.V = velocity + self.A = acceleration + + def __repr__(self): + return "(P:{}, V:{}, A:{})".format(self.P, self.V, self.A) + + def concat(self, other): + self.P = np.concatenate((self.P, other.P), 0) + self.V = np.concatenate((self.V, other.V), 0) + self.A = np.concatenate((self.A, other.A), 0) + +def LJ_acc(position,neighb_x_0,r_cut,L, rank): + subcube_atoms=position.shape[0] + #careful kind of confusing + position=np.concatenate((position,neighb_x_0),0) + num=position.shape[0] + update_accel=np.zeros((subcube_atoms,3)) + dU_drcut=48*r_cut**(-13)-24*r_cut**(-7) + #for loop is only of subcube we are interested in but we have to account for ALL distance! + for atom in range(subcube_atoms): + position_other=np.concatenate((position[0:atom,:],position[atom+1:num+1,:]),axis=0) + position_atom=position[atom] + separation=position_atom-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)) + #get out the particles inside the r_cut + accel=np.zeros((r_relat.shape[0],3)) + flag = 0 + for i, r0 in enumerate(r_relat): + if r0 <= r_cut and r0!=0: + separation_active_num=separation_new[i,:] + vector_part=separation_active_num*(1/r0) + scalar_part=48*r0**(-13)-24*r0**(-7)-dU_drcut + accel_num=vector_part*scalar_part + accel[i,:]=accel_num + # if np.abs(position_atom[0]-4.641496)<0.001 and np.abs(position_atom[1]-3.092705)<0.001 and np.abs(position_atom[2]-3.090466)<0.001: + # flag = 1 + # print(position_atom, accel_num, r0) + update_accel[atom,:]=np.sum(accel,axis=0) + # if np.abs(update_accel[atom,:][0]+6.2848242)<1e-4: + # print('update accel',update_accel[atom,:]) + # print(accel[accel.any(axis=1)],r_relat[accel.any(axis=1)]) + return update_accel.reshape(subcube_atoms,3) + +def pbc1(position,L): + ##This function perform the first rule of periodic boundary condition + #Input: position -- the position before PBC1 + # L -- the simulation cell size + #Ouput: x_new -- the updated position after PBC1 + position_new=np.zeros((position.shape[0],3)) + for i in range(position.shape[0]): + position_ind=position[i,:] + position_empty=np.zeros((1,3)) + for j in range(3): + # position_axis=numba.float64(position_ind[j]) + position_axis = position_ind[j] + if position_axis < 0: + position_axis_new=position_axis+L + elif position_axis >= L: + position_axis_new=position_axis-L + else: + position_axis_new=position_axis + position_empty[:,j]=position_axis_new + position_new[i,:]=position_empty + return position_new + +# @numba.njit +def pbc2(separation,L): + ##This function perform the second rule of periodic boundary condition + #Input: separation -- separation before PBC2 + # L -- the simulation cell size + #Ouput: separation_new -- the updated separation after PBC2 + separation_new=np.zeros((separation.shape[0],3)) + for i in range(separation.shape[0]): + separation_ind=separation[i,:] + separation_empty=np.zeros((1,3)) + for j in range(3): + # separation_axis=numba.float64(separation_ind[j]) + separation_axis = separation_ind[j] + if separation_axis < -L/2: + separation_axis_new=separation_axis+L + elif separation_axis >= L/2: + separation_axis_new=separation_axis-L + else: + separation_axis_new=separation_axis + separation_empty[:,j]=separation_axis_new + separation_new[i,:]=separation_empty + return separation_new + +def separate_points(infodict, my_rank, nproc): + neighb_spd = None + # Processor matrix n*n*1 (for comparison with force decomposition) + axis = np.sqrt(nproc) + # Here we need to be careful about only copying the neighboring subcube + x,y,z = my_rank % axis, my_rank / axis, 0 + x,y,z = int(np.floor(x)), int(np.floor(y)), int(np.floor(z)) + x_mesh,y_mesh = np.meshgrid(np.linspace(x-1,x+1,3),np.linspace(y-1,y+1,3)) + neighbor_xy = np.column_stack((x_mesh.ravel(),y_mesh.ravel())) + # neighbor_rank = np.array([[i-5,i-4,i-3],[i-1,i,i+1],[i+3,i+4,i+5]]) + # for row in neighbor_rank: + # for col in row: + # if np.floor(col / world) != np.floor(row[1] / world): + # col = np.floor(col / world) * world + world + if axis<=3: + neighbor_rank = np.arange(0,nproc,1) + else: + neighbor_rank = np.zeros(9) + for t,xy in enumerate(neighbor_xy): + xy_old = xy.copy() + if xy[0]<0: + xy[0] = xy[0] + axis + if xy[0]==axis: + xy[0] = xy[0] - axis + # elif xy[0]==axis and xy[1]=axis-1: + # xy[0] = xy[0] - axis + # xy[1] = 0 + if xy[1]<0: + xy[1] = xy[1] + axis + if xy[1] == axis: + xy[1] = xy[1] - axis + # xy[0] = xy[0] + # print(xy_old,xy) + # for i in xy: + # if i<0: + # i = i + axis + # elif i == axis: + # i = i - axis + neighbor_rank[t] = (xy[0] + xy[1]*axis) + # print('neighboring ',my_rank, (x,y), neighbor_rank) + + # copy the info in neighboring ranks + for i, spd in infodict.items(): + if i!=my_rank and i in neighbor_rank: + if neighb_spd is None: + neighb_spd = copy.deepcopy(spd) + else: + neighb_spd.concat(spd) + return infodict[my_rank], neighb_spd + +def cell_to_dict(info,nx,ny,nz,L): + ##This is the helper function to create dictionary containing matrix for cell_to_obj + #Inpust: info -- the position + velocity + acceleration of the patricles at the + # cell_dict = Dict.empty(key_type=types.int64, value_type=float_array) + cell_dict = {} + xinterval=L/nx + yinterval=L/ny + zinterval=L/nz + # print('interval ', xinterval, yinterval) + #cell_lists={} + for i in range(nx*ny*nz): + cell_dict[i]= np.zeros((1,9)) + for i in range(info.shape[0]): + atom=info[i,0:9].reshape(1,9) + #check extra one!!! + #if statements !!!!!!! + #check later + # atomID=int(((np.floor(atom[:,0]/xinterval)+(np.floor(atom[:,1]/yinterval))*ny)+(np.floor(atom[:,2]/zinterval))*(nx*ny))[0]) + atomID=int(((np.floor(atom[:,0]/xinterval)+(np.floor(atom[:,1]/yinterval))*ny))[0]) + cell_dict[atomID]=np.append(cell_dict[atomID],atom,axis=0) + for i in range(nx*ny*nz): + cell_dict[i]=cell_dict[i][1:,:] + return cell_dict + +def cell_to_obj(positions,nx,ny,nz,L): + cell_lists=cell_to_dict(positions,nx,ny,nz,L) + new_cell_list={} + for i in range(nx*ny*nz): + # I think this works but we should think more about what an "empty" shape means + # currently when a key points to an empty cube the cube has a position vector of dimensions [0,3] + if cell_lists[i].shape[0]!=0: + temp_reshaped=cell_lists[i] + temp_position = temp_reshaped[:,0:3] + assert(temp_position.shape[1] == 3) + temp_velocity = temp_reshaped[:,3:6] + temp_acceleration = temp_reshaped[:,6:9] + spatial_domain_data = SpatialDomainData(temp_position, + temp_velocity, + temp_acceleration) + new_cell_list[i] = spatial_domain_data + else: + new_cell_list[i] = SpatialDomainData(np.empty((0,3)), + np.empty((0,3)), + np.empty((0,3))) + return new_cell_list + +def Kin_Eng(velocity): + ##This function compute the average kinetic energy of the system at given the velocity + #Input: velocity -- the velocities of all the particles + #Output: Kinetic_sum -- the average kinetic energy of the system + num=velocity.shape[0] + Kinetic_per=0.5*np.sum(velocity**2,axis=1) + Kinetic_avg=np.sum(Kinetic_per,axis=0) + return Kinetic_avg + +def LJ_potent_nondimen(position,position_neighbor,r_cut,L): + ##This function compute the nondimensional potential energy of the system at the given position + #Input: position -- the position of all the particles at this instance + # r_cut -- the cutoff for the short-range force field + # L -- the size of the simulation cell + #Output: np.sum(update_LJ) -- the potential energy of the system at this instance + num=position.shape[0] + position = np.concatenate((position, position_neighbor),0) + update_LJ=np.zeros((num,1)) + #fix value for a certain r_limit + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + U_rcut=4*(r_cut**(-12)-r_cut**(-6)) + for atom in range(num): + # position_relevent=position[atom:,:] + # position_other=position_relevent[1:,:] + position_atom = position[atom,:] + position_other=np.concatenate((position[0:atom,:],position[atom+1:,:]),axis=0) + #pbc rule2 + # separation=position_relevent[0,:]-position_other + separation = position_atom - position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + LJ=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut and r0!=0: + LJ_num=4*r0**(-12)-4*r0**(-6)-U_rcut-(r0-r_cut)*dU_drcut + LJ.append(LJ_num) + update_LJ[atom,:]=np.sum(np.array(LJ),axis=0) + return np.sum(update_LJ)/2 + +def insta_pressure(L,T,position,position_neighbor,r_cut,e_scale): + ##This function computes the dimensionless pressure + #Inputs: L -- The size of the simulation cell + # T -- The simulation temperature + # position -- The position of all the particles at this time step + # e_scale -- The energy scale of this particles + #Ouputs: pres_insta -- The instant pressure at this moment + num=position.shape[0] + k_B=1.38064852*10**(-23) + V=L**3 + pres_ideal=num*T*(k_B/e_scale)/V + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + pres_virial=np.zeros((num,1)) + position = np.concatenate((position,position_neighbor),0) + for atom in range(num): + # position_relevent=position[atom:,:] + # position_other=position_relevent[1:,:] + # position_atom=position_relevent[0,:] + position_atom = position[atom,:] + position_other = np.concatenate((position[0:atom,:],position[atom+1:,:]),axis=0) + #pbc rule 2 + separation=position_atom-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + force=[] + active_r_relat=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut and r0!=0: + #active_r_relat.append(r0) + force_num=-(24*r0**(-7)-48*r0**(-13))+dU_drcut + force.append(force_num) + active_r_relat.append(r0) + #get out the particles inside the r_cut + active_amount=np.array(active_r_relat).shape[0] + rijFij=np.array(active_r_relat).reshape(1,active_amount)@np.array(force).reshape(active_amount,1) + pres_virial[atom,:]=rijFij + pres_insta=pres_ideal+np.sum(pres_virial,axis=0)/(3*V)/2 + return pres_insta + +def concatDict(infodict): + wholeDict=None + for i,spd in infodict.items(): + if(wholeDict is None): + wholeDict = copy.deepcopy(spd) + else: + wholeDict.concat(spd) + return wholeDict + +# MPI initialize comm = MPI.COMM_WORLD rank = comm.Get_rank() size = comm.Get_size() -print('initial rank', rank) +print(rank,size) +comm.barrier() -stop_step=1 +# run params +stop_step=1000 k_B=1.38064852*10**(-23) dt=0.002 file_name='../data/initial_position_LJ_argon256.txt' -position_init=np.loadtxt(file_name) -num_atoms=position_init.shape[0] +info_init=np.loadtxt(file_name) +num_atoms=info_init.shape[0] a_init=np.zeros((num_atoms,3)) -r_c=2.5 +r_c=1.6 L0=6.8 #cube division -subdiv=np.array([2,2,1]) +subdiv=np.array([int(np.sqrt(size)),int(np.sqrt(size)),1]) energy_scale=1.66*10**(-21)#unit: J, Argon sigma=3.4 #unit: Ang, Argon -T_dimensional_equal=123#unit K +T_dimensional_equal=300#unit K T_equal=T_dimensional_equal*k_B/energy_scale part_type='LJ' name='argon256' +#initialize PE, KE, T_insta, P_insta, Momentum +PE=np.zeros((stop_step+1,1)) +KE=np.zeros((stop_step+1,1)) +T_insta=np.zeros((stop_step+1,1)) +P_insta=np.zeros((stop_step+1,1)) + +if rank==0: + start_time = time.time() + # # initialize + k_B=1.38064852*10**(-23) + size_sim=info_init.shape[0] + # x_dot_init=ut.random_vel_generator(size_sim,T_equal,energy_scale) + #initialize the info matrix + info=np.zeros((stop_step+1,size_sim,9)) + # info[0,:,:]=np.concatenate((position_init,x_dot_init,a_init),axis=1) + info[0,:,:] = info_init + # np.savetxt('../data/init.txt',info[0,:,:],fmt='%.6f') + infotodic=cell_to_obj((info[0,:,:]),subdiv[0],subdiv[1],subdiv[2],L0) + KE[0,:] = Kin_Eng(info[0,:,3:6]) + T_insta[0,:]=2*KE[0,:]*energy_scale/(3*(size_sim-1)*k_B) #k + print(T_insta[0,:][0]) +else: + infotodic = None +comm.barrier() +infotodic = comm.bcast(infotodic, root = 0) +T_single = comm.bcast(T_insta[0,:][0], root=0) + +my_spd, neighs_spd = separate_points(infotodic, my_rank = rank, nproc = size) +#zero step value +PE_single=LJ_potent_nondimen(my_spd.P,neighs_spd.P,r_cut=r_c,L=L0) +P_single=insta_pressure(L0,T_single,my_spd.P,neighs_spd.P,r_c,energy_scale) #unitless +PE_all = comm.reduce(PE_single,op=MPI.SUM,root=0) +P_all = comm.reduce(P_single,op=MPI.SUM,root=0) + if rank==0: - start_time=time.time() - print(rank, start_time) -comm.barrier() -info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, - position_init=position_init, - dt=dt, - stop_step=stop_step, - accel_init=a_init, - r_cut=2.8, - L=L0, - T_eq=T_equal, - e_scale=energy_scale, - sig=sigma) -if rank == 0: - end_time=time.time() + PE[0,:] = PE_all + P_insta[0,:] = P_all + +# Run MD +for step in range(stop_step): + my_spd, neighs_spd=separate_points(infotodic, rank, size) + my_spd.A = LJ_acc(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_c,L=L0,rank=rank) + my_spd.V = my_spd.V + my_spd.A*(dt) + my_spd.P = my_spd.P + my_spd.V * dt + my_spd.P = pbc1(position=my_spd.P,L=L0) + # my_spd_send=utp.vel_Ver( + # comm = comm, + # infodict=infotodic, + # dt=dt, + # r_limit=r_c, + # L=L0, + # my_rank=rank + # ) + my_spd_send = (rank,my_spd) + # apply periodic boundary condition + # my_spd_send[1].P = ut.pbc1(my_spd_send[1].P,L=L0) + #calculate and store KE in parallel + KE_single = Kin_Eng(my_spd_send[1].V) + + # gather + temp_infodict=comm.gather(my_spd_send,root=0) + KE_all = comm.reduce(KE_single,op=MPI.SUM,root=0) + # T_all = comm.reduce(T_single,op=MPI.SUM,root=0) + # P_all = comm.reduce(P_single, op=MPI.SUM, root=0) + + if rank == 0: + if step%20==0: + print('current time step is ', step) + temp_infodict=list(filter(None, temp_infodict)) + info_temp=dict(temp_infodict) + tmp = concatDict(info_temp) + info[step+1,:,:] = np.concatenate((tmp.P,tmp.V,tmp.A),1) + # info[step+1,:,:] = np.round(info[step+1,:,:],4) + # info[step+1,:,0:3] = ut.pbc1(info[step+1,:,0:3],L=L0) + #UPDATE CUBES MAKE SURE ATOMS ARE IN RIGHT CUBES + infotodic = cell_to_obj(info[step+1,:,:],subdiv[0],subdiv[1],subdiv[2],L0) + # gather KE and T + KE[step+1,:]=KE_all + T_insta[step+1,:]=2*KE_all*energy_scale/(3*(size_sim-1)*k_B) #k + comm.barrier() + infotodic = comm.bcast(infotodic, root = 0) + T_single = comm.bcast(T_insta[step+1,:][0], root = 0) + # calculate PE,P in parallel + my_spd, neighs_spd = separate_points(infotodic, my_rank = rank, nproc = size) + PE_single = LJ_potent_nondimen(position = my_spd.P, position_neighbor = neighs_spd.P, r_cut = r_c, L=L0) + P_single = insta_pressure(L0,T_single,my_spd.P,neighs_spd.P,r_c,energy_scale) + # gather back to 0 + PE_all = comm.reduce(PE_single,op=MPI.SUM,root=0) + P_all = comm.reduce(P_single,op=MPI.SUM,root=0) + if rank==0: + #calculate and store PE, P_insta + PE[step+1,:]=PE_all + P_insta[step+1,:]=P_all + # comm.barrier() + # infotodic=comm.bcast(infotodic,root=0) + +if rank == 0: + end_time = time.time() period = end_time-start_time - print("For this {} steps operation (dt={}) with r_cut = {} and L = {}, it took:".format(stop_step,dt,r_c,L0),end_time-start_time,'s') - ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, 1000, False) + print(f'Run time is {period:.3f} seconds') + PE = np.round(PE,4) + KE = np.round(KE,4) + T_insta = np.round(T_insta,4) + P_insta = np.round(P_insta,4) + data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, size, False) +comm.barrier() + +# if rank==0: +# start_time=time.time() +# info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, +# position_init=position_init, +# dt=dt, +# stop_step=stop_step, +# accel_init=a_init, +# r_cut=2.8, +# L=L0, +# T_eq=T_equal, +# e_scale=energy_scale, +# sig=sigma) +# end_time=time.time() +# period = end_time-start_time +# print("For this {} steps operation (dt={}) with r_cut = {} and L = {}, it took:".format(stop_step,dt,r_c,L0),end_time-start_time,'s') +# ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, 1000, False) # else: -# LJ_MD(subdiv=subdiv, -# position_init=position_init, -# dt=dt, -# stop_step=stop_step, -# accel_init=a_init, -# r_cut=2.8, -# L=L0, -# T_eq=T_equal, -# e_scale=energy_scale, -# sig=sigma) diff --git a/spatial_decompose/__pycache__/LJ_SpatialDecomp.cpython-310.pyc b/spatial_decompose/__pycache__/LJ_SpatialDecomp.cpython-310.pyc index 46e8e23..1721536 100644 Binary files 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IMPORTANT: You may need to close and restart your shell after running 'conda init'. -------------------------------------------------------------------------------- -There are messages associated with the following module(s): -------------------------------------------------------------------------------- - -cuda/11.1.1: - Warning - This module has been deprecated and is scheduled for removal. - Please transition to a module from the production pool instead. - -------------------------------------------------------------------------------- - -Traceback (most recent call last): - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/MDargon_spatial.py", line 36, in - info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/LJ_SpatialDecomp.py", line 41, in LJ_MD - info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) -AttributeError: 'NoneType' object has no attribute 'P' -Traceback (most recent call last): - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/MDargon_spatial.py", line 36, in - info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/LJ_SpatialDecomp.py", line 41, in LJ_MD - info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) -AttributeError: 'NoneType' object has no attribute 'P' -Traceback (most recent call last): - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/MDargon_spatial.py", line 36, in - info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/LJ_SpatialDecomp.py", line 41, in LJ_MD - info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) -AttributeError: 'NoneType' object has no attribute 'P' -Traceback (most recent call last): - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/MDargon_spatial.py", line 36, in - info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, - File "/ocean/projects/cts180021p/hzhao3/ParallelComputing/EECS587Project/spatial_decompose/LJ_SpatialDecomp.py", line 41, in LJ_MD - info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) -AttributeError: 'NoneType' object has no attribute 'P' --------------------------------------------------------------------------- -Primary job terminated normally, but 1 process returned -a non-zero exit code. Per user-direction, the job has been aborted. --------------------------------------------------------------------------- --------------------------------------------------------------------------- -mpirun detected that one or more processes exited with non-zero status, thus causing -the job to be terminated. The first process to do so was: - - Process name: [[18937,1],3] - Exit code: 1 --------------------------------------------------------------------------- diff --git a/spatial_decompose/job.out b/spatial_decompose/job.out index 069f2b8..0438a86 100644 --- a/spatial_decompose/job.out +++ b/spatial_decompose/job.out @@ -1,18 +1,62 @@ -/opt/packages/openmpi/gcc/4.1.1-gcc8.3.1-cpu/bin/mpiexec -/opt/packages/openmpi/gcc/4.1.1-gcc8.3.1-cpu/bin/mpirun -MPI startup(): PMI server not found. Please set I_MPI_PMI_LIBRARY variable if it is not a singleton case. -MPI startup(): PMI server not found. Please set I_MPI_PMI_LIBRARY variable if it is not a singleton case. -MPI startup(): PMI server not found. Please set I_MPI_PMI_LIBRARY variable if it is not a singleton case. -MPI startup(): PMI server not found. Please set I_MPI_PMI_LIBRARY variable if it is not a singleton case. -initial rank 0 -0 1704156354.2576318 -initial rank 0 -initial rank 0 -0 1704156354.2602494 -0 1704156354.2602494 -initial rank 0 -0 1704156354.2819088 -{} -{} -{} -{} +/opt/intel/oneapi/intelpython/latest/bin/mpirun +6 9 +1 9 +3 9 +4 9 +7 9 +2 9 +5 9 +8 9 +0 9 +123.00000045477438 +current time step is 0 +current time step is 20 +current time step is 40 +current time step is 60 +current time step is 80 +current time step is 100 +current time step is 120 +current time step is 140 +current time step is 160 +current time step is 180 +current time step is 200 +current time step is 220 +current time step is 240 +current time step is 260 +current time step is 280 +current time step is 300 +current time step is 320 +current time step is 340 +current time step is 360 +current time step is 380 +current time step is 400 +current time step is 420 +current time step is 440 +current time step is 460 +current time step is 480 +current time step is 500 +current time step is 520 +current time step is 540 +current time step is 560 +current time step is 580 +current time step is 600 +current time step is 620 +current time step is 640 +current time step is 660 +current time step is 680 +current time step is 700 +current time step is 720 +current time step is 740 +current time step is 760 +current time step is 780 +current time step is 800 +current time step is 820 +current time step is 840 +current time step is 860 +current time step is 880 +current time step is 900 +current time step is 920 +current time step is 940 +current time step is 960 +current time step is 980 +Run time is 180.458 seconds diff --git a/spatial_decompose/job.sh b/spatial_decompose/job.sh index a1622bf..cb916f8 100644 --- a/spatial_decompose/job.sh +++ b/spatial_decompose/job.sh @@ -1,14 +1,15 @@ #!/bin/bash #SBATCH -N 1 -#SBATCH -n 4 +#SBATCH -n 9 #SBATCH -p RM-small #SBATCH --mem-per-cpu=2000M #SBATCH -e job.err #SBATCH -o job.out -#SBATCH -t 00:05:00 +#SBATCH -t 01:00:00 -conda activate deepmd-gpu -module load openmpi -echo $(which mpiexec) +conda activate dpgpu +# module load openmpi/4.0.5-gcc10.2.0 echo $(which mpirun) -mpirun -n 4 python MDargon_spatial.py \ No newline at end of file +~/.conda/envs/dpgpu/bin/mpirun -np $SLURM_NTASKS python MDargon_spatial.py +# ~/.conda/envs/dpgpu/bin/mpirun -np $SLURM_NTASKS python MDargon_serial.py +# python MDargon_serial.py \ No newline at end of file diff --git a/spatial_decompose/results/argon256_Energy_Temp_Pres16core.csv b/spatial_decompose/results/argon256_Energy_Temp_Pres16core.csv new file mode 100644 index 0000000..49ad0d8 --- /dev/null +++ b/spatial_decompose/results/argon256_Energy_Temp_Pres16core.csv @@ -0,0 +1,1002 @@ +step,KE,PE,T_insta,P_insta +0,391.3016,-413.596,123.0,4.6302 +1,391.1757,-413.0689,122.9604,4.6414 +2,390.2474,-411.739,122.6686,4.664 +3,388.517,-409.6077,122.1247,4.6978 +4,385.9866,-406.6782,121.3293,4.7423 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-0.246290 6.490144 6.232884 +5.416601 4.642234 5.413294 0.480245 0.264217 -0.346864 6.383357 -0.219777 6.196216 +5.413289 5.414452 4.640064 -0.347893 -0.056889 -0.277999 6.402456 6.503995 0.061454 diff --git a/spatial_decompose/results/argon256iter2core1_summary.txt b/spatial_decompose/results/argon256iter2core1_summary.txt new file mode 100644 index 0000000..42f511b --- /dev/null +++ b/spatial_decompose/results/argon256iter2core1_summary.txt @@ -0,0 +1,6 @@ +Simulation Cell Size(unitless): 6.8 +Simulation Particles Amount: 256 +File Name: argon256 +Simulation Time: 4.452249526977539 +Simulation Step: 2 +Force Cut-off: 1.6 diff --git a/spatial_decompose/results/argon256position_last1stps.xyz b/spatial_decompose/results/argon256position_last1stps.xyz new file mode 100644 index 0000000..a5d266e --- /dev/null +++ b/spatial_decompose/results/argon256position_last1stps.xyz @@ -0,0 +1,258 @@ +256 +This is the position of the system during the last 1 steps +LJ 6.79914686e+00 6.79293414e+00 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4.63685834 4.64140176 6.7995932 +LJ 4.63362969 5.41969627 0.7678424 +LJ 5.41854893 4.64767823 0.7784051 +LJ 5.41376288e+00 5.41841132e+00 3.18544164e-0 +LJ 4.64608865 4.64496737 1.5450503 +LJ 4.63751001 5.41741332 2.3241625 +LJ 5.41703856 4.63454681 2.3259166 +LJ 5.41720527 5.4123228 1.5526452 +LJ 4.63232657 4.63347795 3.0884249 +LJ 4.64332578 5.40854564 3.8673383 +LJ 5.42156812 4.64835398 3.8696404 +LJ 5.41159285 5.41320785 3.0937280 +LJ 4.64632379 4.63774988 4.6407581 +LJ 4.63932884 5.4097154 5.4089161 +LJ 5.41660145 4.64223375 5.4132937 +LJ 5.41328882 5.41445243 4.6400637 diff --git a/spatial_decompose/results_before_PE_parallel/MDargon.py b/spatial_decompose/results_before_PE_parallel/MDargon.py new file mode 100644 index 0000000..2093e2d --- /dev/null +++ b/spatial_decompose/results_before_PE_parallel/MDargon.py @@ -0,0 +1,122 @@ +import numpy as np +import time +import copy +from LJ_SpatialDecomp import * +import utils_spatial_decompose as ut +from mpi4py import MPI + +# MPI initialize +comm = MPI.COMM_WORLD +rank = comm.Get_rank() +size = comm.Get_size() +print(rank,size) +comm.barrier() + +# run params +stop_step=1000 +k_B=1.38064852*10**(-23) +dt=0.002 +file_name='../data/initial_position_LJ_argon256.txt' +info_init=np.loadtxt(file_name) +num_atoms=info_init.shape[0] + +a_init=np.zeros((num_atoms,3)) +r_c=1.6 +L0=6.8 +#cube division +subdiv=np.array([int(np.sqrt(size)),int(np.sqrt(size)),1]) +energy_scale=1.66*10**(-21)#unit: J, Argon +sigma=3.4 #unit: Ang, Argon +T_dimensional_equal=300#unit K +T_equal=T_dimensional_equal*k_B/energy_scale +part_type='LJ' +name='argon256' + + + +if rank==0: + start_time = time.time() + # # initialize + k_B=1.38064852*10**(-23) + size_sim=info_init.shape[0] + # x_dot_init=ut.random_vel_generator(size_sim,T_equal,energy_scale) + #initialize PE, KE, T_insta, P_insta, Momentum + PE=np.zeros((stop_step+1,1)) + KE=np.zeros((stop_step+1,1)) + T_insta=np.zeros((stop_step+1,1)) + P_insta=np.zeros((stop_step+1,1)) + #initialize the info matrix + info=np.zeros((stop_step+1,size_sim,9)) + # info[0,:,:]=np.concatenate((position_init,x_dot_init,a_init),axis=1) + info[0,:,:] = info_init + # np.savetxt('../data/init.txt',info[0,:,:],fmt='%.6f') + infotodic=ut.cell_to_obj((info[0,:,:]),subdiv[0],subdiv[1],subdiv[2],L0) + #zero step value + PE[0,:]=ut.LJ_potent_nondimen(info[0,:,0:3],r_cut=r_c,L=L0) + KE[0,:]=ut.Kin_Eng(info[0,:,3:6]) + T_insta[0,:]=2*KE[0,:]*energy_scale/(3*(size_sim-1)*k_B) #k + P_insta[0,:]=ut.insta_pressure(L0,T_insta[0],info[0,:,0:3],r_c,energy_scale) #unitless +else: + infotodic = None + # info = None +comm.barrier() +infotodic = comm.bcast(infotodic, root = 0) + +# Run MD +for step in range(stop_step): + my_spd_send=utp.vel_Ver( + comm = comm, + infodict=infotodic, + dt=dt, + r_limit=r_c, + L=L0, + my_rank=rank + ) + temp_infodict=comm.gather(my_spd_send,root=0) + if rank == 0: + if step%20==0: + print('current time step is ', step) + temp_infodict=list(filter(None, temp_infodict)) + info_temp=dict(temp_infodict) + tmp=ut.concatDict(info_temp) + info[step+1,:,:]=np.concatenate((tmp.P,tmp.V,tmp.A),1) + # info[step+1,:,:] = np.round(info[step+1,:,:],4) + info[step+1,:,0:3] = ut.pbc1(info[step+1,:,0:3],L=L0) + #UPDATE CUBES MAKE SURE ATOMS ARE IN RIGHT CUBES + infotodic=ut.cell_to_obj(info[step+1,:,:],subdiv[0],subdiv[1],subdiv[2],L0) + #calculate and store PE, KE, T_insta, P_insta + PE[step+1,:]=ut.LJ_potent_nondimen(info[step+1,:,0:3],r_cut=r_c,L=L0) + KE[step+1,:]=ut.Kin_Eng(info[step+1,:,3:6]) + T_insta[step+1,:]=2*KE[step+1,:]*energy_scale/(3*(size_sim-1)*k_B) #k + P_insta[step+1,:]=ut.insta_pressure(L0,T_insta[step+1],info[step+1,:,0:3],r_c,energy_scale) #unitless + comm.barrier() + infotodic=comm.bcast(infotodic,root=0) + +if rank == 0: + end_time = time.time() + period = end_time-start_time + print(f'Run time is {period:.3f} seconds') + PE = np.round(PE,4) + KE = np.round(KE,4) + T_insta = np.round(T_insta,4) + P_insta = np.round(P_insta,4) + ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, size, False) +comm.barrier() + +# if rank==0: +# start_time=time.time() +# info,PE,KE,T_insta,P_insta=LJ_MD(subdiv=subdiv, +# position_init=position_init, +# dt=dt, +# stop_step=stop_step, +# accel_init=a_init, +# r_cut=2.8, +# L=L0, +# T_eq=T_equal, +# e_scale=energy_scale, +# sig=sigma) +# end_time=time.time() +# period = end_time-start_time +# print("For this {} steps operation (dt={}) with r_cut = {} and L = {}, it took:".format(stop_step,dt,r_c,L0),end_time-start_time,'s') +# ut.data_saver(info, PE, KE, T_insta, P_insta, L0, num_atoms,part_type,name,period, stop_step, r_c, 1000, False) +# else: \ No newline at end of file diff --git a/spatial_decompose/results_before_PE_parallel/argon256_Energy_Temp_Pres.csv b/spatial_decompose/results_before_PE_parallel/argon256_Energy_Temp_Pres.csv new file mode 100644 index 0000000..7d0ecea --- /dev/null +++ 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b/spatial_decompose/results_before_PE_parallel/argon256_summary.txt @@ -0,0 +1,6 @@ +Simulation Cell Size(unitless): 6.8 +Simulation Particles Amount: 256 +File Name: argon256 +Simulation Time: 729.4726428985596 +Simulation Step: 1000 +Force Cut-off: 2.5 diff --git a/spatial_decompose/results_before_PE_parallel/argon256core16_summary.txt b/spatial_decompose/results_before_PE_parallel/argon256core16_summary.txt new file mode 100644 index 0000000..6cdd2cb --- /dev/null +++ b/spatial_decompose/results_before_PE_parallel/argon256core16_summary.txt @@ -0,0 +1,6 @@ +Simulation Cell Size(unitless): 6.8 +Simulation Particles Amount: 256 +File Name: argon256 +Simulation Time: 5.574477910995483 +Simulation Step: 10 +Force Cut-off: 1.6 diff --git a/spatial_decompose/results_before_PE_parallel/argon256iter1.txt b/spatial_decompose/results_before_PE_parallel/argon256iter1.txt new file mode 100644 index 0000000..aecd965 --- /dev/null +++ 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0.590900 -1.656700 1.331700 7.786500 0.603900 -0.505200 +5.417200 5.412300 1.552700 0.630500 -0.589400 1.396500 5.771700 6.403900 -0.031400 +4.632400 4.633500 3.088500 -2.211800 -1.924100 -1.422300 0.581800 0.325300 1.014400 +4.643400 5.408500 3.867300 0.536500 -1.532100 -0.077200 -0.960100 8.008600 0.020600 +5.421500 4.648400 3.869600 1.723400 1.793200 0.497700 7.784800 -1.247100 -0.670800 +5.411600 5.413200 3.093700 -0.772200 -0.368500 -0.097700 6.026200 5.988500 -0.206900 +4.646400 4.637800 4.640800 1.285400 -0.856500 -0.104400 -1.486300 -0.011500 0.091900 +4.639400 5.409700 5.408900 -0.462000 -1.241100 -1.441200 -0.253400 6.494800 6.236400 +5.416600 4.642200 5.413300 0.480300 0.264300 -0.346900 6.395300 -0.220200 6.194800 +5.413300 5.414500 4.640000 -0.347900 -0.056900 -0.278000 6.407600 6.501500 0.065700 diff --git a/spatial_decompose/temp.txt b/spatial_decompose/temp.txt new file mode 100644 index 0000000..b618e9a --- /dev/null +++ b/spatial_decompose/temp.txt @@ -0,0 +1,20 @@ +4core +update accel [-8.45424897 0.44704291 -0.33678861] +[[-1.45904247e-02 -2.29175846e+00 2.27839159e+00] + [-1.86997900e-02 2.35280556e+00 2.36481349e+00] + [-2.12388218e+00 2.09121071e+00 1.86267859e-03] + [-2.68427912e-02 2.63770860e+00 -2.64739033e+00] + [-2.10905225e+00 -1.22518734e-02 2.09175120e+00] + [-2.13116430e+00 -1.42712217e-02 -2.11631902e+00] + [-2.01381352e+00 -2.00512265e+00 -6.49800616e-03] + [-1.62037165e-02 -2.31127776e+00 -2.30340022e+00]] [1.09461502 1.09352185 1.09733541 1.08949982 1.09744812 1.09708215 + 1.09889725 1.0942828 ] + + +16core +update accel [-6.2848242 -6.63468197 -0.05607445] +[[-0.01459042 -2.29175846 2.27839159] + [-2.10905225 -0.01225187 2.0917512 ] + [-2.1311643 -0.01427122 -2.11631902] + [-2.01381352 -2.00512265 -0.00649801] + [-0.01620372 -2.31127776 -2.30340022]] [1.09461502 1.09744812 1.09708215 1.09889725 1.0942828 ] \ No newline at end of file diff --git a/spatial_decompose/utils.py b/spatial_decompose/utils.py new file mode 100644 index 0000000..ad6595b --- /dev/null +++ b/spatial_decompose/utils.py @@ -0,0 +1,341 @@ +import numpy as np +# import numba +# from numba.experimental import jitclass +# from numba import float64 +# from numba.typed import Dict +# from numba.core import types +import os +import pandas as pd +import copy +#first the dtypes of the input matrices need to be explicitly clarified +class SpatialDomainData: + #This class creates objects for storing position, velocity and acceleration information + ##This class contain three functions: + ###__init__ (description) + ###__repr__ (description) + ###concat(description) + def __init__(self, position=np.array([]), velocity=np.array([]), acceleration=np.array([])): + self.P = position + self.V = velocity + self.A = acceleration + + def __repr__(self): + return "(P:{}, V:{}, A:{})".format(self.P, self.V, self.A) + + def concat(self, other): + self.P = np.concatenate((self.P, other.P), 0) + self.V = np.concatenate((self.V, other.V), 0) + self.A = np.concatenate((self.A, other.A), 0) + +# @numba.njit +def pbc1(position,L): + ##This function perform the first rule of periodic boundary condition + #Input: position -- the position before PBC1 + # L -- the simulation cell size + #Ouput: x_new -- the updated position after PBC1 + position_new=np.zeros((position.shape[0],3)) + for i in range(position.shape[0]): + position_ind=position[i,:] + position_empty=np.zeros((1,3)) + for j in range(3): + # position_axis=numba.float64(position_ind[j]) + position_axis = position_ind[j] + if position_axis < 0: + position_axis_new=position_axis+L + elif position_axis > L: + position_axis_new=position_axis-L + else: + position_axis_new=position_axis + position_empty[:,j]=position_axis_new + position_new[i,:]=position_empty + return position_new + +# @numba.njit +def pbc2(separation,L): + ##This function perform the second rule of periodic boundary condition + #Input: separation -- separation before PBC2 + # L -- the simulation cell size + #Ouput: separation_new -- the updated separation after PBC2 + separation_new=np.zeros((separation.shape[0],3)) + for i in range(separation.shape[0]): + separation_ind=separation[i,:] + separation_empty=np.zeros((1,3)) + for j in range(3): + # separation_axis=numba.float64(separation_ind[j]) + separation_axis = separation_ind[j] + if separation_axis < -L/2: + separation_axis_new=separation_axis+L + elif separation_axis > L/2: + separation_axis_new=separation_axis-L + else: + separation_axis_new=separation_axis + separation_empty[:,j]=separation_axis_new + separation_new[i,:]=separation_empty + return separation_new + +# @numba.njit +def random_vel_generator(n,T_equal,e_scale): + ##This function generate random initial velocity at the desired temperature + #Input: n -- number of atoms + # T_equal -- the temperature of interests + # e_scale -- the energy scale of the particle of interests + #Ouput: vel_per_particle -- the velocity matrix assigned to all particles + total_k=3*T_equal*(n-1)/2 + vel_per_particle=np.zeros((n,3)) + for axis in range(3): + vel_per_particle[:,axis]=np.random.randn(n,)-0.5 + Mom_x_total=np.sum(vel_per_particle[:,0]) + Mom_y_total=np.sum(vel_per_particle[:,1]) + Mom_z_total=np.sum(vel_per_particle[:,2]) + Mom_x_avg=Mom_x_total/n + Mom_y_avg=Mom_y_total/n + Mom_z_avg=Mom_z_total/n + vel_per_particle=vel_per_particle-np.array([Mom_x_avg,Mom_y_avg,Mom_z_avg]).reshape(1,3) + k_avg_init=0.5*(1/n)*np.sum(np.sum(vel_per_particle**2,axis=1),axis=0) + k_avg_T_eq=total_k/n + scaling_ratio=np.sqrt(k_avg_T_eq/k_avg_init) + vel_per_particle=vel_per_particle*scaling_ratio + return vel_per_particle + +# @numba.njit +def Kin_Eng(velocity): + ##This function compute the average kinetic energy of the system at given the velocity + #Input: velocity -- the velocities of all the particles + #Output: Kinetic_sum -- the average kinetic energy of the system + num=velocity.shape[0] + Kinetic_per=0.5*np.sum(velocity**2,axis=1) + Kinetic_avg=np.sum(Kinetic_per,axis=0) + return Kinetic_avg + +# @numba.njit +def LJ_potent_nondimen(position,r_cut,L): + ##This function compute the nondimensional potential energy of the system at the given position + #Input: position -- the position of all the particles at this instance + # r_cut -- the cutoff for the short-range force field + # L -- the size of the simulation cell + #Output: np.sum(update_LJ) -- the potential energy of the system at this instance + num=position.shape[0] + update_LJ=np.zeros((num-1,1)) + #fix value for a certain r_limit + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + U_rcut=4*(r_cut**(-12)-r_cut**(-6)) + for atom in range(num-1): + position_relevent=position[atom:,:] + position_other=position_relevent[1:,:] + #pbc rule2 + separation=position_relevent[0,:]-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + LJ=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut: + LJ_num=4*r0**(-12)-4*r0**(-6)-U_rcut-(r0-r_cut)*dU_drcut + LJ.append(LJ_num) + update_LJ[atom,:]=np.sum(np.array(LJ),axis=0) + return np.sum(update_LJ) + +# @numba.njit +def insta_pressure(L,T,position,r_cut,e_scale): + ##This function computes the dimensionless pressure + #Inputs: L -- The size of the simulation cell + # T -- The simulation temperature + # position -- The position of all the particles at this time step + # e_scale -- The energy scale of this particles + #Ouputs: pres_insta -- The instant pressure at this moment + num=position.shape[0] + k_B=1.38064852*10**(-23) + V=L**3 + pres_ideal=num*T*(k_B/e_scale)/V + dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) + pres_virial=np.zeros((num-1,1)) + for atom in range(num-1): + position_relevent=position[atom:,:] + position_other=position_relevent[1:,:] + position_atom=position_relevent[0,:] + #pbc rule 2 + separation=position_atom-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) + force=[] + active_r_relat=[] + #get out the particles inside the r_limit + for r0 in r_relat: + if r0 <= r_cut: + #active_r_relat.append(r0) + force_num=-(24*r0**(-7)-48*r0**(-13))+dU_drcut + force.append(force_num) + active_r_relat.append(r0) + #get out the particles inside the r_cut + active_amount=np.array(active_r_relat).shape[0] + rijFij=np.array(active_r_relat).reshape(1,active_amount)@np.array(force).reshape(active_amount,1) + pres_virial[atom,:]=rijFij + pres_insta=pres_ideal+np.sum(pres_virial,axis=0)/(3*V) + return pres_insta + +#need to initialize the type before calling the function +# float_array = types.float64[:,:] +# @numba.njit() +def cell_to_dict(info,nx,ny,nz,L): + ##This is the helper function to create dictionary containing matrix for cell_to_obj + #Inpust: info -- the position + velocity + acceleration of the patricles at the + # cell_dict = Dict.empty(key_type=types.int64, value_type=float_array) + cell_dict = {} + xinterval=L/nx + yinterval=L/ny + zinterval=L/nz + #cell_lists={} + for i in range(1,nx*ny*nz+1): + cell_dict[i]= np.zeros((1,9)) + for i in range(info.shape[0]): + atom=info[i,0:9].reshape(1,9) + #check extra one!!! + #if statements !!!!!!! + #check later + atomID=int(((np.floor(atom[:,0]/xinterval)+1+(np.floor(atom[:,1]/yinterval))*ny)+(np.floor(atom[:,2]/zinterval))*(nx*ny))[0]) + cell_dict[atomID]=np.append(cell_dict[atomID],atom,axis=0) + for i in range(1,nx*ny*nz+1): + cell_lists[i]=cell_lists[i][1:,:] + return cell_lists + +def cell_to_obj(positions,nx,ny,nz,L): + cell_lists=cell_to_dict(positions,nx,ny,nz,L) + new_cell_list={} + for i in range(1,nx*ny*nz+1): + # I think this works but we should think more about what an "empty" shape means + # currently when a key points to an empty cube the cube has a position vector of dimensions [0,3] + if cell_lists[i].shape[0]!=0: + temp_reshaped=cell_lists[i] + temp_position = temp_reshaped[:,0:3] + assert(temp_position.shape[1] == 3) + temp_velocity = temp_reshaped[:,3:6] + temp_acceleration = temp_reshaped[:,6:9] + spatial_domain_data = SpatialDomainData(temp_position, + temp_velocity, + temp_acceleration) + new_cell_list[i] = spatial_domain_data + else: + new_cell_list[i] = SpatialDomainData(np.empty((0,3)), + np.empty((0,3)), + np.empty((0,3))) + return new_cell_list + +#@numba.njit() +def separate_points(infodict, my_i): + neighb_spd=None + for i,spd in infodict.items(): + if i!=my_i: + if (neighb_spd is None): + neighb_spd = copy.deepcopy(spd) + else: + neighb_spd.concat(spd) + return infodict[my_i], neighb_spd + +#@numba.njit +def concatDict(infodict): + wholeDict=None + for i,spd in infodict.items(): + if(wholeDict is None): + wholeDict = copy.deepcopy(spd) + else: + wholeDict.concat(spd) + return wholeDict + +#@numba.njit() +def LJ_accel(position,neighb_x_0,r_cut,L): + subcube_atoms=position.shape[0] + #careful kind of confusing + position=np.concatenate((position,neighb_x_0),0) + num=position.shape[0] + update_accel=np.zeros((subcube_atoms,3)) + dU_drcut=48*r_cut**(-13)-24*r_cut**(-7) + #for loop is only of subcube we are interested in but we have to account for ALL distance! + for atom in range(subcube_atoms): + position_other=np.concatenate((position[0:atom,:],position[atom+1:num+1,:]),axis=0) + position_atom=position[atom] + separation=position_atom-position_other + separation_new=pbc2(separation=separation,L=L) + r_relat=np.sqrt(np.sum(separation_new**2,axis=1)) + #get out the particles inside the r_cut + accel=np.zeros((r_relat.shape[0],3)) + for i, r0 in enumerate(r_relat): + if r0 <= r_cut: + separation_active_num=separation_new[i,:] + vector_part=separation_active_num*(1/r0) + scalar_part=48*r0**(-13)-24*r0**(-7)-dU_drcut + accel_num=vector_part*scalar_part + accel[i,:]=accel_num + update_accel[atom,:]=np.sum(accel,axis=0) + return update_accel.reshape(subcube_atoms,3) + +def data_saver(info, PE, KE, T_insta, P_insta, L, num_atoms,part_type,name,period,stop_step, r_c, iterations_int=1000, make_directory=True): + iterations=str(iterations_int) + if make_directory == True: + os.mkdir('results') + path_to_file_xyz="results/"+name+"position_last"+iterations+"stps"+".xyz" + path_to_file_other = "results/"+name+"_Energy_Temp_Pres"+".csv" + path_to_file_summary = "results/"+name+"_summary"+".txt" + p= open(path_to_file_xyz,"w") + s= open(path_to_file_summary,'w') + + #writing xyz file + comment = 'This is the position of the system during the last '+iterations+' steps' + for atoms in info[-int(iterations):,:,0:3]: + p.write("%s\n" % str(num_atoms)) + p.write("%s\n" % comment) + for atom in atoms: + p.write(part_type) + p.write("\t%s\n" % str(atom)[1:-2]) + + #writing other file + other_dict={} + other_dict['KE']=KE.reshape(KE.shape[0],) + other_dict['PE']=PE.reshape(PE.shape[0],) + other_dict['T_insta']=T_insta.reshape(T_insta.shape[0],) + other_dict['P_insta']=P_insta.reshape(P_insta.shape[0],) + other_df=pd.DataFrame.from_dict(other_dict) + other_df.to_csv(path_to_file_other,index_label='step') + + #writing summary file + s.write("Simulation Cell Size(unitless): "+str(L)+"\n") + s.write("Simulation Particles Amount: "+str(num_atoms)+"\n") + s.write("File Name: "+str(name)+"\n") + s.write("Simulation Time: "+ str(period)+"\n") + s.write("Simulation Step: "+str(stop_step)+"\n") + s.write("Force Cut-off: "+str(r_c)+"\n") + p.close() + s.close() + else: + path_to_file_xyz="results/"+name+"position_last"+iterations+"stps"+".xyz" + path_to_file_other = "results/"+name+"_Energy_Temp_Pres"+".csv" + path_to_file_summary = "results/"+name+"_summary"+".txt" + p= open(path_to_file_xyz,"w") + s= open(path_to_file_summary,'w') + + #writing xyz file + comment = 'This is the position of the system during the last '+iterations+' steps' + for atoms in info[-int(iterations):,:,0:3]: + p.write("%s\n" % str(num_atoms)) + p.write("%s\n" % comment) + for atom in atoms: + p.write(part_type) + p.write("\t%s\n" % str(atom)[1:-2]) + + #writing other file + other_dict={} + other_dict['KE']=KE.reshape(KE.shape[0],) + other_dict['PE']=PE.reshape(PE.shape[0],) + other_dict['T_insta']=T_insta.reshape(T_insta.shape[0],) + other_dict['P_insta']=P_insta.reshape(P_insta.shape[0],) + other_df=pd.DataFrame.from_dict(other_dict) + other_df.to_csv(path_to_file_other,index_label='step') + + #writing summary file + s.write("Simulation Cell Size(unitless): "+str(L)+"\n") + s.write("Simulation Particles Amount: "+str(num_atoms)+"\n") + s.write("File Name: "+str(name)+"\n") + s.write("Simulation Time: "+ str(period)+"\n") + s.write("Simulation Step: "+str(stop_step)+"\n") + s.write("Force Cut-off: "+str(r_c)+"\n") + p.close() + s.close() diff --git a/spatial_decompose/utils_parallel.py b/spatial_decompose/utils_parallel.py index b4cbefa..d222460 100644 --- a/spatial_decompose/utils_parallel.py +++ b/spatial_decompose/utils_parallel.py @@ -5,44 +5,33 @@ import functools import operator #@numba.njit() ##This might not be needed -def par_worker_vel_ver_pre(infodict,dt,r_limit,L): - vel_Ver(infodict,dt,r_limit,L) +def par_worker_vel_ver_pre(comm,infodict,dt,r_limit,L,my_rank): + vel_Ver(comm,infodict,dt,r_limit,L,my_rank) #@numba.njit() -def vel_Ver(infodict,dt,r_limit=2.5,L=6.8): - comm = MPI.COMM_WORLD - rank = comm.Get_rank() - size = comm.Get_size() - if rank!=0: - ## Get the data for the current spatial domain - my_spd, neighs_spd=ut.separate_points(infodict, rank) - #acceleration at 0 - my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L) - #velocity at dt/2 - my_spd.V=my_spd.V+my_spd.A*(dt/2) - #position at dt - my_spd.P=my_spd.P+my_spd.V*dt - #PBC rule 1 - my_spd.P=ut.pbc1(position=my_spd.P,L=L) - my_spd_send=(rank,my_spd) - else: - my_spd_send=None - comm.barrier() - temp_infodict=comm.allgather(my_spd_send) - if rank!=0: - temp_infodict=list(filter(None, temp_infodict)) - infodict=dict(temp_infodict) - my_spd, neighs_spd=ut.separate_points(infodict, rank) - #acceleration at dt - my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L) - #velocity at dt - my_spd.V=my_spd.V+my_spd.A*(dt/2) - my_spd_send=(rank,my_spd) - else: - my_spd_send=None - comm.barrier() - temp_infodict=comm.gather(my_spd_send,root=0) - if rank==0: - temp_infodict=list(filter(None, temp_infodict)) - infodict=dict(temp_infodict) - return infodict +def vel_Ver(comm,infodict,dt,r_limit=2.5,L=6.8,my_rank=0): + # rank = comm.Get_rank() + rank = my_rank + size = comm.Get_size() + ## Get the data for the current spatial domain + my_spd, neighs_spd=ut.separate_points(infodict, rank, size) + # LEAP FROG METHOD + #acceleration at 0 + my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L,rank=my_rank) + #velocity at dt/2 + # my_spd.V=my_spd.V+my_spd.A*(dt/2) + my_spd.V=my_spd.V+my_spd.A*(dt) + #position at dt + my_spd.P=my_spd.P+my_spd.V*dt + #PBC rule 1 + my_spd.P=ut.pbc1(position=my_spd.P,L=L) + my_spd_send=(rank,my_spd) + comm.barrier() + # temp_infodict=comm.allgather(my_spd_send) + # # acceleration at dt + # my_spd.A=ut.LJ_accel(position=my_spd.P,neighb_x_0=neighs_spd.P,r_cut=r_limit,L=L,rank=my_rank) + # # velocity at dt + # my_spd.V=my_spd.V+my_spd.A*(dt/2) + # my_spd_send=(rank,my_spd) + # comm.barrier() + return my_spd_send diff --git a/spatial_decompose/utils_spatial_decompose.py b/spatial_decompose/utils_spatial_decompose.py index 65f07d3..218148e 100644 --- a/spatial_decompose/utils_spatial_decompose.py +++ b/spatial_decompose/utils_spatial_decompose.py @@ -42,7 +42,7 @@ def pbc1(position,L): position_axis = position_ind[j] if position_axis < 0: position_axis_new=position_axis+L - elif position_axis > L: + elif position_axis >= L: position_axis_new=position_axis-L else: position_axis_new=position_axis @@ -65,7 +65,7 @@ def pbc2(separation,L): separation_axis = separation_ind[j] if separation_axis < -L/2: separation_axis_new=separation_axis+L - elif separation_axis > L/2: + elif separation_axis >= L/2: separation_axis_new=separation_axis-L else: separation_axis_new=separation_axis @@ -108,35 +108,39 @@ def Kin_Eng(velocity): return Kinetic_avg # @numba.njit -def LJ_potent_nondimen(position,r_cut,L): +def LJ_potent_nondimen(position,position_neighbor,r_cut,L): ##This function compute the nondimensional potential energy of the system at the given position #Input: position -- the position of all the particles at this instance # r_cut -- the cutoff for the short-range force field # L -- the size of the simulation cell #Output: np.sum(update_LJ) -- the potential energy of the system at this instance num=position.shape[0] - update_LJ=np.zeros((num-1,1)) + position = np.concatenate((position, position_neighbor),0) + update_LJ=np.zeros((num,1)) #fix value for a certain r_limit dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) U_rcut=4*(r_cut**(-12)-r_cut**(-6)) - for atom in range(num-1): - position_relevent=position[atom:,:] - position_other=position_relevent[1:,:] + for atom in range(num): + # position_relevent=position[atom:,:] + # position_other=position_relevent[1:,:] + position_atom = position[atom,:] + position_other=np.concatenate((position[0:atom,:],position[atom+1:,:]),axis=0) #pbc rule2 - separation=position_relevent[0,:]-position_other + # separation=position_relevent[0,:]-position_other + separation = position_atom - position_other separation_new=pbc2(separation=separation,L=L) r_relat=np.sqrt(np.sum(separation_new**2,axis=1)).reshape(separation_new.shape[0],) LJ=[] #get out the particles inside the r_limit for r0 in r_relat: - if r0 <= r_cut: + if r0 <= r_cut and r0!=0: LJ_num=4*r0**(-12)-4*r0**(-6)-U_rcut-(r0-r_cut)*dU_drcut LJ.append(LJ_num) update_LJ[atom,:]=np.sum(np.array(LJ),axis=0) - return np.sum(update_LJ) + return np.sum(update_LJ)/2 # @numba.njit -def insta_pressure(L,T,position,r_cut,e_scale): +def insta_pressure(L,T,position,position_neighbor,r_cut,e_scale): ##This function computes the dimensionless pressure #Inputs: L -- The size of the simulation cell # T -- The simulation temperature @@ -148,11 +152,14 @@ def insta_pressure(L,T,position,r_cut,e_scale): V=L**3 pres_ideal=num*T*(k_B/e_scale)/V dU_drcut=24*r_cut**(-7)-48*r_cut**(-13) - pres_virial=np.zeros((num-1,1)) - for atom in range(num-1): - position_relevent=position[atom:,:] - position_other=position_relevent[1:,:] - position_atom=position_relevent[0,:] + pres_virial=np.zeros((num,1)) + position = np.concatenate((position,position_neighbor),0) + for atom in range(num): + # position_relevent=position[atom:,:] + # position_other=position_relevent[1:,:] + # position_atom=position_relevent[0,:] + position_atom = position[atom,:] + position_other = np.concatenate((position[0:atom,:],position[atom+1:,:]),axis=0) #pbc rule 2 separation=position_atom-position_other separation_new=pbc2(separation=separation,L=L) @@ -161,7 +168,7 @@ def insta_pressure(L,T,position,r_cut,e_scale): active_r_relat=[] #get out the particles inside the r_limit for r0 in r_relat: - if r0 <= r_cut: + if r0 <= r_cut and r0!=0: #active_r_relat.append(r0) force_num=-(24*r0**(-7)-48*r0**(-13))+dU_drcut force.append(force_num) @@ -170,7 +177,7 @@ def insta_pressure(L,T,position,r_cut,e_scale): active_amount=np.array(active_r_relat).shape[0] rijFij=np.array(active_r_relat).reshape(1,active_amount)@np.array(force).reshape(active_amount,1) pres_virial[atom,:]=rijFij - pres_insta=pres_ideal+np.sum(pres_virial,axis=0)/(3*V) + pres_insta=pres_ideal+np.sum(pres_virial,axis=0)/(3*V)/2 return pres_insta #need to initialize the type before calling the function @@ -184,24 +191,26 @@ def cell_to_dict(info,nx,ny,nz,L): xinterval=L/nx yinterval=L/ny zinterval=L/nz + # print('interval ', xinterval, yinterval) #cell_lists={} - for i in range(1,nx*ny*nz+1): + for i in range(nx*ny*nz): cell_dict[i]= np.zeros((1,9)) for i in range(info.shape[0]): atom=info[i,0:9].reshape(1,9) #check extra one!!! #if statements !!!!!!! #check later - atomID=int(((np.floor(atom[:,0]/xinterval)+1+(np.floor(atom[:,1]/yinterval))*ny)+(np.floor(atom[:,2]/zinterval))*(nx*ny))[0]) + # atomID=int(((np.floor(atom[:,0]/xinterval)+(np.floor(atom[:,1]/yinterval))*ny)+(np.floor(atom[:,2]/zinterval))*(nx*ny))[0]) + atomID=int(((np.floor(atom[:,0]/xinterval)+(np.floor(atom[:,1]/yinterval))*ny))[0]) cell_dict[atomID]=np.append(cell_dict[atomID],atom,axis=0) - for i in range(1,nx*ny*nz+1): + for i in range(nx*ny*nz): cell_dict[i]=cell_dict[i][1:,:] return cell_dict def cell_to_obj(positions,nx,ny,nz,L): cell_lists=cell_to_dict(positions,nx,ny,nz,L) new_cell_list={} - for i in range(1,nx*ny*nz+1): + for i in range(nx*ny*nz): # I think this works but we should think more about what an "empty" shape means # currently when a key points to an empty cube the cube has a position vector of dimensions [0,3] if cell_lists[i].shape[0]!=0: @@ -222,11 +231,11 @@ def cell_to_obj(positions,nx,ny,nz,L): #@numba.njit() def separate_points(infodict, my_rank, nproc): - neighbor_spd = None + neighb_spd = None # Processor matrix n*n*1 (for comparison with force decomposition) axis = np.sqrt(nproc) # Here we need to be careful about only copying the neighboring subcube - x,y,z = my_rank / axis, my_rank % axis, 0 + x,y,z = my_rank % axis, my_rank / axis, 0 x,y,z = int(np.floor(x)), int(np.floor(y)), int(np.floor(z)) x_mesh,y_mesh = np.meshgrid(np.linspace(x-1,x+1,3),np.linspace(y-1,y+1,3)) neighbor_xy = np.column_stack((x_mesh.ravel(),y_mesh.ravel())) @@ -240,12 +249,30 @@ def separate_points(infodict, my_rank, nproc): else: neighbor_rank = np.zeros(9) for t,xy in enumerate(neighbor_xy): - for i in xy: - if i<0: - i = i + axis - elif i == axis: - i = i - axis + xy_old = xy.copy() + if xy[0]<0: + xy[0] = xy[0] + axis + if xy[0]==axis: + xy[0] = xy[0] - axis + # elif xy[0]==axis and xy[1]=axis-1: + # xy[0] = xy[0] - axis + # xy[1] = 0 + if xy[1]<0: + xy[1] = xy[1] + axis + if xy[1] == axis: + xy[1] = xy[1] - axis + # xy[0] = xy[0] + # print(xy_old,xy) + # for i in xy: + # if i<0: + # i = i + axis + # elif i == axis: + # i = i - axis neighbor_rank[t] = (xy[0] + xy[1]*axis) + # print('neighboring ',my_rank, (x,y), neighbor_rank) # copy the info in neighboring ranks for i, spd in infodict.items(): @@ -267,7 +294,7 @@ def concatDict(infodict): return wholeDict #@numba.njit() -def LJ_accel(position,neighb_x_0,r_cut,L): +def LJ_accel(position,neighb_x_0,r_cut,L, rank): subcube_atoms=position.shape[0] #careful kind of confusing position=np.concatenate((position,neighb_x_0),0) @@ -283,94 +310,71 @@ def LJ_accel(position,neighb_x_0,r_cut,L): r_relat=np.sqrt(np.sum(separation_new**2,axis=1)) #get out the particles inside the r_cut accel=np.zeros((r_relat.shape[0],3)) + flag = 0 for i, r0 in enumerate(r_relat): - if r0 <= r_cut: + if r0 <= r_cut and r0!=0: separation_active_num=separation_new[i,:] vector_part=separation_active_num*(1/r0) scalar_part=48*r0**(-13)-24*r0**(-7)-dU_drcut accel_num=vector_part*scalar_part accel[i,:]=accel_num + # if np.abs(position_atom[0]-4.641496)<0.001 and np.abs(position_atom[1]-3.092705)<0.001 and np.abs(position_atom[2]-3.090466)<0.001: + # flag = 1 + # print(position_atom, accel_num, r0) update_accel[atom,:]=np.sum(accel,axis=0) + # if np.abs(update_accel[atom,:][0]+6.2848242)<1e-4: + # print('update accel',update_accel[atom,:]) + # print(accel[accel.any(axis=1)],r_relat[accel.any(axis=1)]) return update_accel.reshape(subcube_atoms,3) -def data_saver(info, PE, KE, T_insta, P_insta, L, num_atoms,part_type,name,period,stop_step, r_c, iterations_int=1000, make_directory=True): - iterations=str(iterations_int) +def data_saver(info, PE, KE, T_insta, P_insta, L, num_atoms,part_type,name,period,stop_step, r_c, ncore = 8, make_directory=True): + iterations=str(stop_step) if make_directory == True: os.mkdir('results') - # path_to_file_xyz="results/"+name+"position_last"+iterations+"stps"+".xyz" - path_to_file_xyz = "results/"+name+"iter"+iterations+'.txt' - path_to_file_other = "results/"+name+"_Energy_Temp_Pres"+".csv" - path_to_file_summary = "results/"+name+"_summary"+".txt" - p= open(path_to_file_xyz,"w") - s= open(path_to_file_summary,'w') + # path_to_file_xyz="results/"+name+"position_last"+iterations+"stps"+".xyz" + path_to_file_xyz = "results/"+name+"iter"+iterations+'core'+str(ncore)+'.txt' + path_to_file_other = "results/"+name+"_Energy_Temp_Pres"+str(ncore)+'core'+".csv" + path_to_file_summary = "results/"+name+"iter"+iterations+'core'+str(ncore)+"_summary"+".txt" + p= open(path_to_file_xyz,"w") + s= open(path_to_file_summary,'w') - # #writing xyz file - # comment = 'This is the position of the system during the last '+iterations+' steps' - # # for atoms in info[-int(iterations):,:,:]: - # p.write("%s\n" % str(num_atoms)) - # p.write("%s\n" % comment) - # for atom in atoms: - # # p.write(part_type) - # p.write("\t%s\n" % str(atom)[1:-2]) + # #writing xyz file + # comment = 'This is the position of the system during the last '+iterations+' steps' + # # for atoms in info[-int(iterations):,:,:]: + # p.write("%s\n" % str(num_atoms)) + # p.write("%s\n" % comment) + # for atom in atoms: + # # p.write(part_type) + # p.write("\t%s\n" % str(atom)[1:-2]) - #writing xyz file - comment = 'This is the position of the system of the final step' - # for atoms in info[-int(iterations):,:,:]: - # p.write("%s\n" % str(num_atoms)) - # p.write("%s\n" % comment) - # for i in range(num_atoms): - # p.write("\t%s\n" % str(info[:])) - np.savetxt(path_to_file_xyz,info[-1,:,:]) + #writing xyz file + comment = 'This is the position of the system of the final step' + # print(path_to_file_xyz) + # for atoms in info[-int(iterations):,:,:]: + # p.write("%s\n" % str(num_atoms)) + # p.write("%s\n" % comment) + # for i in range(num_atoms): + # p.write("\t%s\n" % str(info[:])) + # output = info[-1,:,:][np.argsort(info[-1,:,0])] + output = info[-1,:,:] + np.savetxt(path_to_file_xyz,output,fmt='%.6f') - #writing other file - other_dict={} - other_dict['KE']=KE.reshape(KE.shape[0],) - other_dict['PE']=PE.reshape(PE.shape[0],) - other_dict['T_insta']=T_insta.reshape(T_insta.shape[0],) - other_dict['P_insta']=P_insta.reshape(P_insta.shape[0],) - other_df=pd.DataFrame.from_dict(other_dict) - other_df.to_csv(path_to_file_other,index_label='step') + #writing other file + other_dict={} + other_dict['KE']=KE.reshape(KE.shape[0],) + other_dict['PE']=PE.reshape(PE.shape[0],) + other_dict['T_insta']=T_insta.reshape(T_insta.shape[0],) + other_dict['P_insta']=P_insta.reshape(P_insta.shape[0],) + other_df=pd.DataFrame.from_dict(other_dict) + other_df.to_csv(path_to_file_other,index_label='step') - #writing summary file - s.write("Simulation Cell Size(unitless): "+str(L)+"\n") - s.write("Simulation Particles Amount: "+str(num_atoms)+"\n") - s.write("File Name: "+str(name)+"\n") - s.write("Simulation Time: "+ str(period)+"\n") - s.write("Simulation Step: "+str(stop_step)+"\n") - s.write("Force Cut-off: "+str(r_c)+"\n") - p.close() - s.close() - else: - path_to_file_xyz="results/"+name+"position_last"+iterations+"stps"+".xyz" - path_to_file_other = "results/"+name+"_Energy_Temp_Pres"+".csv" - path_to_file_summary = "results/"+name+"_summary"+".txt" - p= open(path_to_file_xyz,"w") - s= open(path_to_file_summary,'w') - - #writing xyz file - comment = 'This is the position of the system during the last '+iterations+' steps' - for atoms in info[-int(iterations):,:,0:3]: - p.write("%s\n" % str(num_atoms)) - p.write("%s\n" % comment) - for atom in atoms: - p.write(part_type) - p.write("\t%s\n" % str(atom)[1:-2]) - - #writing other file - other_dict={} - other_dict['KE']=KE.reshape(KE.shape[0],) - other_dict['PE']=PE.reshape(PE.shape[0],) - other_dict['T_insta']=T_insta.reshape(T_insta.shape[0],) - other_dict['P_insta']=P_insta.reshape(P_insta.shape[0],) - other_df=pd.DataFrame.from_dict(other_dict) - other_df.to_csv(path_to_file_other,index_label='step') + #writing summary file + s.write("Simulation Cell Size(unitless): "+str(L)+"\n") + s.write("Simulation Particles Amount: "+str(num_atoms)+"\n") + s.write("File Name: "+str(name)+"\n") + s.write("Simulation Time: "+ str(period)+"\n") + s.write("Simulation Step: "+str(stop_step)+"\n") + s.write("Force Cut-off: "+str(r_c)+"\n") + p.close() + s.close() - #writing summary file - s.write("Simulation Cell Size(unitless): "+str(L)+"\n") - s.write("Simulation Particles Amount: "+str(num_atoms)+"\n") - s.write("File Name: "+str(name)+"\n") - s.write("Simulation Time: "+ str(period)+"\n") - s.write("Simulation Step: "+str(stop_step)+"\n") - s.write("Force Cut-off: "+str(r_c)+"\n") - p.close() - s.close()