root / Ising / Numpy-C / Ising2D.py @ 98
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1 | 18 | equemene | #!/usr/bin/env python
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2 | 18 | equemene | #
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3 | 18 | equemene | # Ising2D model in serial mode using external C library
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4 | 18 | equemene | #
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5 | 18 | equemene | # CC BY-NC-SA 2011 : <emmanuel.quemener@ens-lyon.fr>
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6 | 18 | equemene | |
7 | 18 | equemene | import sys |
8 | 18 | equemene | import numpy |
9 | 18 | equemene | from PIL import Image |
10 | 18 | equemene | from math import exp |
11 | 18 | equemene | from random import random |
12 | 18 | equemene | import time |
13 | 18 | equemene | import getopt |
14 | 18 | equemene | import matplotlib.pyplot as plt |
15 | 18 | equemene | import array_module_np |
16 | 18 | equemene | from numpy.random import randint as nprnd |
17 | 18 | equemene | |
18 | 18 | equemene | def ImageOutput(sigma,prefix): |
19 | 18 | equemene | Max=sigma.max() |
20 | 18 | equemene | Min=sigma.min() |
21 | 18 | equemene | |
22 | 18 | equemene | # Normalize value as 8bits Integer
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23 | 18 | equemene | SigmaInt=(255*(sigma-Min)/(Max-Min)).astype('uint8') |
24 | 18 | equemene | image = Image.fromarray(SigmaInt) |
25 | 18 | equemene | image.save("%s.jpg" % prefix)
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26 | 18 | equemene | |
27 | 18 | equemene | def Metropolis(sigma,J,B,T,iterations): |
28 | 18 | equemene | start=time.time() |
29 | 18 | equemene | |
30 | 18 | equemene | SizeX,SizeY=sigma.shape |
31 | 18 | equemene | |
32 | 18 | equemene | for p in xrange(0,iterations): |
33 | 18 | equemene | # Random access coordonate
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34 | 18 | equemene | X,Y=numpy.random.randint(SizeX),numpy.random.randint(SizeY) |
35 | 18 | equemene | |
36 | 18 | equemene | DeltaE=J*sigma[X,Y]*(2*(sigma[X,(Y+1)%SizeY]+ |
37 | 18 | equemene | sigma[X,(Y-1)%SizeY]+
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38 | 18 | equemene | sigma[(X-1)%SizeX,Y]+
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39 | 18 | equemene | sigma[(X+1)%SizeX,Y])+B)
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40 | 18 | equemene | |
41 | 18 | equemene | if DeltaE < 0. or random() < exp(-DeltaE/T): |
42 | 18 | equemene | sigma[X,Y]=-sigma[X,Y] |
43 | 18 | equemene | duration=time.time()-start |
44 | 18 | equemene | return(duration)
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45 | 18 | equemene | |
46 | 18 | equemene | def Magnetization(sigma,M): |
47 | 18 | equemene | return(numpy.sum(sigma)/(sigma.shape[0]*sigma.shape[1]*1.0)) |
48 | 18 | equemene | |
49 | 18 | equemene | def Energy(sigma,J): |
50 | 18 | equemene | # Copier et caster
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51 | 18 | equemene | E=numpy.copy(sigma).astype(numpy.float32) |
52 | 18 | equemene | |
53 | 18 | equemene | # Appel par slice
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54 | 18 | equemene | E[1:-1,1:-1]=-J*E[1:-1,1:-1]*(E[:-2,1:-1]+E[2:,1:-1]+ |
55 | 18 | equemene | E[1:-1,:-2]+E[1:-1,2:]) |
56 | 18 | equemene | |
57 | 18 | equemene | # Bien nettoyer la peripherie
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58 | 18 | equemene | E[:,0]=0 |
59 | 18 | equemene | E[:,-1]=0 |
60 | 18 | equemene | E[0,:]=0 |
61 | 18 | equemene | E[-1,:]=0 |
62 | 18 | equemene | |
63 | 18 | equemene | Energy=numpy.sum(E) |
64 | 18 | equemene | |
65 | 18 | equemene | return(Energy/(E.shape[0]*E.shape[1]*1.0)) |
66 | 18 | equemene | |
67 | 18 | equemene | def DisplayCurves(T,E,M,J,B): |
68 | 18 | equemene | |
69 | 18 | equemene | plt.xlabel("Temperature")
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70 | 18 | equemene | plt.ylabel("Energy")
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71 | 18 | equemene | |
72 | 18 | equemene | Experience,=plt.plot(T,E,label="Energy")
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73 | 18 | equemene | |
74 | 18 | equemene | plt.legend() |
75 | 18 | equemene | plt.show() |
76 | 18 | equemene | |
77 | 18 | equemene | |
78 | 18 | equemene | if __name__=='__main__': |
79 | 18 | equemene | |
80 | 18 | equemene | # Set defaults values
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81 | 18 | equemene | # Coupling factor
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82 | 18 | equemene | J=1.
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83 | 18 | equemene | # Magnetic Field
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84 | 18 | equemene | B=0.
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85 | 18 | equemene | # Size of Lattice
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86 | 18 | equemene | Size=256
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87 | 18 | equemene | # Default Temperatures (start, end, step)
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88 | 18 | equemene | Tmin=0.1
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89 | 18 | equemene | Tmax=5
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90 | 18 | equemene | Tstep=0.1
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91 | 18 | equemene | # Default Number of Iterations
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92 | 18 | equemene | Iterations=Size*Size |
93 | 18 | equemene | |
94 | 18 | equemene | # Curves is True to print the curves
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95 | 18 | equemene | Curves=False
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96 | 18 | equemene | |
97 | 18 | equemene | try:
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98 | 18 | equemene | opts, args = getopt.getopt(sys.argv[1:],"hcj:b:z:i:s:e:p:",["coupling=","magneticfield=","size=","iterations=","tempstart=","tempend=","tempstep="]) |
99 | 18 | equemene | except getopt.GetoptError:
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100 | 18 | equemene | print '%s -j <Coupling Factor> -b <Magnetic Field> -z <Size of Lattice> -i <Iterations> -s <Minimum Temperature> -e <Maximum Temperature> -p <steP Temperature> -c (Print Curves)' % sys.argv[0] |
101 | 18 | equemene | sys.exit(2)
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102 | 18 | equemene | |
103 | 18 | equemene | |
104 | 18 | equemene | for opt, arg in opts: |
105 | 18 | equemene | if opt == '-h': |
106 | 18 | equemene | print '%s -j <Coupling Factor> -b <Magnetic Field> -z <Size of Lattice> -i <Iterations> -s <Minimum Temperature> -e <Maximum Temperature> -p <steP Temperature> -c (Print Curves)' % sys.argv[0] |
107 | 18 | equemene | sys.exit() |
108 | 18 | equemene | elif opt == '-c': |
109 | 18 | equemene | Curves=True
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110 | 18 | equemene | elif opt in ("-j", "--coupling"): |
111 | 18 | equemene | J = float(arg)
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112 | 18 | equemene | elif opt in ("-b", "--magneticfield"): |
113 | 18 | equemene | B = float(arg)
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114 | 18 | equemene | elif opt in ("-s", "--tempmin"): |
115 | 18 | equemene | Tmin = float(arg)
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116 | 18 | equemene | elif opt in ("-e", "--tempmax"): |
117 | 18 | equemene | Tmax = float(arg)
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118 | 18 | equemene | elif opt in ("-p", "--tempstep"): |
119 | 18 | equemene | Tstep = float(arg)
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120 | 18 | equemene | elif opt in ("-i", "--iterations"): |
121 | 18 | equemene | Iterations = int(arg)
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122 | 18 | equemene | elif opt in ("-z", "--size"): |
123 | 18 | equemene | Size = int(arg)
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124 | 18 | equemene | |
125 | 18 | equemene | print "Coupling Factor J : %s" % J |
126 | 18 | equemene | print "Magnetic Field B : %s" % B |
127 | 18 | equemene | print "Size of lattice : %s" % Size |
128 | 18 | equemene | print "Iterations : %s" % Iterations |
129 | 18 | equemene | print "Temperature on start : %s" % Tmin |
130 | 18 | equemene | print "Temperature on end : %s" % Tmax |
131 | 18 | equemene | print "Temperature step : %s" % Tstep |
132 | 18 | equemene | Trange=numpy.arange(Tmin,Tmax+Tstep,Tstep) |
133 | 18 | equemene | print "Temperatures explored : %s" % Trange |
134 | 18 | equemene | |
135 | 18 | equemene | LAPIMAGE=False
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136 | 18 | equemene | |
137 | 18 | equemene | sigmaIn=numpy.where(numpy.random.randn(Size,Size)>0,1,-1).astype(numpy.int32) |
138 | 18 | equemene | |
139 | 18 | equemene | ImageOutput(sigmaIn,"Ising2D_Serial_%i_Initial" % (Size))
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140 | 18 | equemene | |
141 | 18 | equemene | |
142 | 18 | equemene | E=[] |
143 | 18 | equemene | M=[] |
144 | 18 | equemene | |
145 | 18 | equemene | for T in Trange: |
146 | 18 | equemene | # Indispensable d'utiliser copy : [:] ne fonctionne pas avec numpy !
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147 | 18 | equemene | sigma=numpy.copy(sigmaIn) |
148 | 18 | equemene | # duration=Metropolis(sigma,J,B,T,Iterations)
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149 | 18 | equemene | SeedW,SeedZ=numpy.int32(nprnd(2**31-1)),numpy.int32(nprnd(2**31-1)) |
150 | 18 | equemene | start=time.time() |
151 | 18 | equemene | array_module_np.array_metropolis_np(sigma,J,B,T,Iterations,SeedW,SeedZ) |
152 | 18 | equemene | duration=time.time()-start |
153 | 18 | equemene | E=numpy.append(E,Energy(sigma,J)) |
154 | 18 | equemene | M=numpy.append(M,Magnetization(sigma,B)) |
155 | 18 | equemene | ImageOutput(sigma,"Ising2D_Serial_%i_%1.1f_Final" % (Size,T))
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156 | 18 | equemene | |
157 | 18 | equemene | print "CPU Time : %f" % (duration) |
158 | 18 | equemene | print "Total Energy at Temperature %f : %f" % (T,E[-1]) |
159 | 18 | equemene | print "Total Magnetization at Temperature %f : %f" % (T,M[-1]) |
160 | 18 | equemene | |
161 | 18 | equemene | if Curves:
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162 | 18 | equemene | DisplayCurves(Trange,E,M,J,B) |
163 | 18 | equemene | |
164 | 18 | equemene | # Save output
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165 | 18 | equemene | numpy.savez("Ising2D_Serial_%i_%.8i" % (Size,Iterations),(Trange,E,M))
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