#!/usr/bin/env python
#
# Ising2D model using PyOpenCL 
#
# CC BY-NC-SA 2011 : <emmanuel.quemener@ens-lyon.fr> 
#
# Thanks to Andreas Klockner for PyOpenCL:
# http://mathema.tician.de/software/pyopencl
# 
# Interesting links:
# http://viennacl.sourceforge.net/viennacl-documentation.html
# http://enja.org/2011/02/22/adventures-in-pyopencl-part-1-getting-started-with-python/

import pyopencl as cl
import numpy
from PIL import Image
import time,string
from numpy.random import randint as nprnd
import sys
import getopt
import matplotlib.pyplot as plt

# Size of micro blocks
BSZ=16

# 2097152 on HD5850 (with 1GB of RAM)
#  262144 on GT218
#STEP=262144
#STEP=1048576
#STEP=2097152
#STEP=4194304
#STEP=8388608
STEP=16777216
#STEP=268435456

# Flag to define LAPIMAGE between iteration on OpenCL kernel calls
#LAPIMAGE=True
LAPIMAGE=False

# Version 2 of kernel : much optimize one
# a string template is used to replace BSZ (named $block_size) by its value 
KERNEL_CODE_ORIG=string.Template("""
#define BSZ $block_size

/* Marsaglia RNG very simple implementation */
#define znew (z=36969*(z&65535)+(z>>16))
#define wnew (w=18000*(w&65535)+(w>>16))
#define MWC ((znew<<16)+wnew )
#define MWCfp (float)(MWC * 2.328306435454494e-10f)

__kernel void MainLoop(__global int *s,float J,float B,float T,uint size,
                       uint iterations,uint seed_w,uint seed_z)
{
   uint base_idx=(uint)(BSZ*get_global_id(0));
   uint base_idy=(uint)(BSZ*get_global_id(1));
   uint base_id=base_idx+base_idy*size;

   uint z=seed_z+(uint)get_global_id(0);
   uint w=seed_w+(uint)get_global_id(1);

   for (uint i=0;i<iterations;i++)
   {
      uint x=(uint)(MWC%BSZ);
      uint y=(uint)(MWC%BSZ);

      int p=s[base_id+x+size*y];

      int u=s[((base_idx+x)%size)+size*((base_idy+y-1)%size)];
      int d=s[((base_idx+x)%size)+size*((base_idy+y+1)%size)];
      int l=s[((base_idx+x-1)%size)+size*((base_idy+y)%size)];
      int r=s[((base_idx+x+1)%size)+size*((base_idy+y)%size)];

      float DeltaE=p*(2.0f*J*(float)(u+d+l+r)+B);

      float factor= ((DeltaE < 0.0f) || (MWCfp < exp(-DeltaE/T))) ? -1:1;

      s[base_id+x+size*y]= factor*p; 
   }
 
}
""")

# Version 2 of kernel : much optimize one
# a string template is used to replace BSZ (named $block_size) by its value 
KERNEL_CODE=string.Template("""

/* Marsaglia RNG very simple implementation */
#define znew (z=36969*(z&65535)+(z>>16))
#define wnew (w=18000*(w&65535)+(w>>16))
#define MWC ((znew<<16)+wnew )
#define MWCfp (float)(MWC * 2.328306435454494e-10f)

__kernel void MainLoop(__global int *s,float J,float B,float T,uint size,
                       uint iterations,uint seed_w,uint seed_z)
{
   uint z=seed_z+(uint)get_global_id(0);
   uint w=seed_w+(uint)get_global_id(1);

   int xo,yo,xe,ye,base,OddSize;
   int p,u,d,l,r,factor;
   float DeltaE;

   OddSize=(size%2==0)?1:0;

   base=2*get_global_id(0);
   yo=base/size;
   xo=(yo%2==0) ? base%size:(base%size+OddSize)%size ;
   ye=yo;
   xe=(xo+1)%size;

   for (uint i=0;i<iterations;i++)
   {
      // Odd pixel
      p=s[yo*size+xo];

      u= (yo==     0) ? s[xo+size*(size-1)]:s[xo+size*(yo-1)];
      d= (yo==size-1) ? s[xo]:s[xo+size*(yo+1)];
      l= (xo==     0) ? s[yo*size+size-1]:s[xo-1+size*yo];
      r= (xo==size-1) ? s[yo*size]:s[xo+1+yo*size];

      DeltaE=(float)p*(2.e0f*J*(float)(u+d+l+r)+B);

      factor= ((DeltaE < 0.e0f) || (MWCfp < (float)exp(-DeltaE/T))) ? -1:1;

      s[yo*size+xo]= factor*p;

      // Even pixel

      p=s[ye*size+xe];
      u= (ye==     0) ? s[xe+size*(size-1)]:s[xe+size*(ye-1)];
      d= (ye==size-1) ? s[xe]:s[xe+size*(ye+1)];
      l= (xe==     0) ? s[ye*size+size-1]:s[xe-1+size*ye];
      r= (xe==size-1) ? s[ye*size]:s[xe+1+ye*size];

      DeltaE=(float)p*(2.e0f*J*(float)(u+d+l+r)+B);

      factor= ((DeltaE < 0.e0f) || (MWCfp < (float)exp(-DeltaE/T))) ? -1:1;

      s[ye*size+xe]= factor*p; 
      barrier(CLK_LOCAL_MEM_FENCE);
   }

 
}
""")

def ImageOutput(sigma,prefix):
    Max=sigma.max()
    Min=sigma.min()
    
    # Normalize value as 8bits Integer
    SigmaInt=(255*(sigma-Min)/(Max-Min)).astype('uint8')
    image = Image.fromarray(SigmaInt)
    image.save("%s.jpg" % prefix)
    
def CheckLattice(sigma):

    over=sigma[sigma>1]
    under=sigma[sigma<-1]
    
    if  (over.size+under.size) > 0:
	print "Problem on Lattice on %i spin(s)." % (over.size+under.size)
    else:
	print "No problem on Lattice"

def Metropolis(sigma,J,B,T,iterations,Device,Divider):

    kernel_params = {}

    print iterations,Divider
    
    # Je detecte un peripherique GPU dans la liste des peripheriques
    Id=1
    HasXPU=False
    for platform in cl.get_platforms():
        for device in platform.get_devices():
            if Id==Device:
                XPU=device
                print "CPU/GPU selected: ",device.name.lstrip()
                HasXPU=True
            Id+=1

    if HasXPU==False:
        print "No XPU #%i found in all of %i devices, sorry..." % (Device,Id-1)
        sys.exit()		
	
    ctx = cl.Context([XPU])
    queue = cl.CommandQueue(ctx,
			    properties=cl.command_queue_properties.PROFILING_ENABLE)

    MetropolisCL = cl.Program(ctx,KERNEL_CODE.substitute(kernel_params)).build()
    
    # Je recupere les flag possibles pour les buffers
    mf = cl.mem_flags

    # Program based on Kernel2
    sigmaCL = cl.Buffer(ctx, mf.WRITE_ONLY | mf.COPY_HOST_PTR, hostbuf=sigma)
    #sigmaCL = cl.Buffer(ctx, mf.READ_WRITE, sigma.nbytes)
    #cl.enqueue_copy(queue,sigmaCL,sigma).wait();
    
    i=0
    duration=0.
    if iterations%Divider == 0:
        steps=iterations/Divider;
    else:
        steps=iterations/Divider+1;

    step=0
    while (step*steps < iterations):
    
        # Call OpenCL kernel
        # sigmaCL is lattice translated in CL format
        # step is number of iterations
        
        start_time=time.time() 

        CLLaunch=MetropolisCL.MainLoop(queue,
                                       (int(sigma.shape[0]*sigma.shape[1]/2),1),None,
                                       sigmaCL,
                                       numpy.float32(J),numpy.float32(B),
                                       numpy.float32(T),
                                       numpy.uint32(sigma.shape[0]),
                                       numpy.uint32(steps),
                                       numpy.uint32(2008),
                                       numpy.uint32(1010))
                                     
        CLLaunch.wait()
	    # elapsed = 1e-9*(CLLaunch.profile.end - CLLaunch.profile.start)
        elapsed = time.time()-start_time
        print "Iteration %i with T=%f and %i iterations in %f: " % (step,T,steps,elapsed)
        if LAPIMAGE:
	        cl.enqueue_copy(queue, sigma, sigmaCL).wait()
	        checkLattice(sigma)
	        ImageOutput(sigma,"Ising2D_GPU_OddEven_%i_%1.1f_%.3i_Lap" % (SIZE,T,i))
        step=step+1
        duration=duration+elapsed

    cl.enqueue_copy(queue,sigma,sigmaCL).wait()
    CheckLattice(sigma)
    sigmaCL.release()
    
    return(duration)

def Magnetization(sigma,M):
    return(numpy.sum(sigma)/(sigma.shape[0]*sigma.shape[1]*1.0))

def Energy(sigma,J,B):
    # Copy & Cast values
    E=numpy.copy(sigma).astype(numpy.float32)
    
    # Slice call to estimate Energy
    E[1:-1,1:-1]=E[1:-1,1:-1]*(2.0*J*(E[:-2,1:-1]+E[2:,1:-1]+
	                                  E[1:-1,:-2]+E[1:-1,2:])+B)
    
    # Clean perimeter
    E[:,0]=0
    E[:,-1]=0
    E[0,:]=0
    E[-1,:]=0
    
    Energy=numpy.sum(E)

    return(Energy/(E.shape[0]*E.shape[1]*1.0))

def CriticalT(T,E):

    Epoly=numpy.poly1d(numpy.polyfit(T,E,T.size/3))
    dEpoly=numpy.diff(Epoly(T))
    dEpoly=numpy.insert(dEpoly,0,0)
    return(T[numpy.argmin(dEpoly)])

def PolyFitE(T,E):

    Epoly=numpy.poly1d(numpy.polyfit(T,E,T.size/3))
    return(Epoly(T))

def DisplayCurves(T,E,M,J,B):

    plt.xlabel("Temperature")
    plt.ylabel("Energy")

    Experience,=plt.plot(T,E,label="Energy") 

    plt.legend()
    plt.show()

if __name__=='__main__':
	
    # Set defaults values
    # Coupling factor
    J=1.
    # External Magnetic Field is null
    B=0.
    # Size of Lattice
    Size=256
    # Default Temperatures (start, end, step)
    Tmin=0.1
    Tmax=5
    Tstep=0.1
    # Default Number of Iterations
    Iterations=Size*Size
    # Default Device is first one
    Device=1
    # Default Divider
    Divider=1

    # Curves is True to print the curves
    Curves=False

    OCL_vendor={}
    OCL_type={}
    OCL_description={}

    try:
        import pyopencl as cl
 
        print "\nHere are available OpenCL devices:"
        Id=1
        for platform in cl.get_platforms():
            for device in platform.get_devices():
                OCL_vendor[Id]=platform.vendor.lstrip().rstrip()
                #OCL_type[Id]=cl.device_type.to_string(device.type)
                OCL_type[Id]="xPU"
                OCL_description[Id]=device.name.lstrip().rstrip()
                print "* Device #%i from %s of type %s : %s" % (Id,OCL_vendor[Id],OCL_type[Id],OCL_description[Id])
                Id=Id+1
        OCL_MaxDevice=Id-1
        print
        
    except ImportError:
        print "Your platform does not seem to support OpenCL"
        sys.exit(0)   
    
    try:
        opts, args = getopt.getopt(sys.argv[1:],"hcj:b:z:i:s:e:p:d:v:",["coupling=","magneticfield=","size=","iterations=","tempstart=","tempend=","tempstep=","units",'device='])
    except getopt.GetoptError:
        print '%s -d <Device Id> -j <Coupling Factor> -b <Magnetic Field> -z <Size of Square Lattice> -i <Iterations> -s <Minimum Temperature> -e <Maximum Temperature> -p <steP Temperature> -v <diVider> -c (Print Curves)' % sys.argv[0]
        sys.exit(2)
    
    for opt, arg in opts:
        if opt == '-h':
            print '%s -d <Device Id> -j <Coupling Factor> -b <Magnetic Field> -z <Size of Square Lattice> -i <Iterations> -s <Minimum Temperature> -e <Maximum Temperature> -p <steP Temperature> -v <diVider> -c (Print Curves)' % sys.argv[0]
            sys.exit()
        elif opt == '-c':
            Curves=True
        elif opt in ("-d", "--device"):
            Device = int(arg)
            if Device>OCL_MaxDevice:
                "Device #%s seems not to be available !"
                sys.exit()
        elif opt in ("-j", "--coupling"):
            J = float(arg)
        elif opt in ("-b", "--magneticfield"):
            B = float(arg)
        elif opt in ("-s", "--tempmin"):
            Tmin = float(arg)
        elif opt in ("-e", "--tempmax"):
            Tmax = float(arg)
        elif opt in ("-p", "--tempstep"):
            Tstep = float(arg)
        elif opt in ("-i", "--iterations"):
            Iterations = int(arg)
        elif opt in ("-z", "--size"):
            Size = int(arg)
        elif opt in ("-v", "--divider"):
            Divider = int(arg)
            
    print "Here are parameters of simulation:"
    print "* Device selected #%s: %s of type %s from %s" % (Device,OCL_description[Device],OCL_type[Device],OCL_vendor[Device])
    print "* Coupling Factor J : %s" % J
    print "* Magnetic Field B :  %s" % B
    print "* Size of lattice : %sx%s" % (Size,Size)
    print "* Divider inside loop : %s" % Divider
    print "* Iterations : %s" % Iterations
    print "* Temperatures from %s to %s by %s" % (Tmin,Tmax,Tstep)

    LAPIMAGE=False
	
    if Iterations<STEP:
        STEP=Iterations

    numpy.random.seed(20081010)
    sigmaIn=numpy.where(numpy.random.randn(Size,Size)>0,1,-1).astype(numpy.int32)
	
    ImageOutput(sigmaIn,"Ising2D_GPU_Local_%i_Initial" % (Size))

	
    Trange=numpy.arange(Tmin,Tmax+Tstep,Tstep)
    
    E=[]
    M=[]
	
    for T in Trange:
        sigma=numpy.copy(sigmaIn)
        duration=Metropolis(sigma,J,B,T,Iterations,Device,Divider)
        E=numpy.append(E,Energy(sigma,J,B))
        M=numpy.append(M,Magnetization(sigma,B))
        ImageOutput(sigma,"Ising2D_GPU_OddEven_%i_%1.1f_Final" % (Size,T))
        print "GPU/CPU Time : %f" % (duration)
        print "Total Energy at Temperature %f : %f" % (T,E[-1])
        print "Total Magnetization at Temperature %f : %f" % (T,M[-1])
		
    # Save output
    numpy.savez("Ising2D_GPU_Global_%i_%.8i" % (Size,Iterations),(Trange,E,M))
    
    # Estimate Critical temperature
    print "The critical temperature on %ix%i lattice with J=%f, B=%f is %f " % (Size,Size,J,B,CriticalT(Trange,E))

    if Curves:
        DisplayCurves(Trange,E,M,J,B)