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- Bernard Krauth 2012 (24591 bytes)
209: pylab.hist(data,bins=40,normed=True)
258: Energy_hist = int(energy*Nstep+0.5)
263: if Energy == Energy_hist:
270: pylab.hist(data,bins=40,normed=True,facecolor='green')
271: ...tr(N)+", k = "+str(Nstep)+" Energy = "+str(Energy_hist/float(Nstep))) - Levy problem HW01 ICFP 2018.py (676 bytes)
15: pylab.hist(data,bins=100, range=(-1.0, 2.0), normed=True)
16: pylab.title("Histogram of Levy distribution for $ \\alpha $ = " + s... - Bayes tank problem HW02 ICFP 2019.py (910 bytes)
4: histovec = []
6: while (len(histovec) < 1000):
14: histovec.append(N)
16: Nmax = max(histovec)
17: pylab.hist(histovec, range=(0, Nmax), bins=Nmax, normed=True) - Levy problem HW01 ICFP 2017.py (627 bytes)
15: pylab.hist(data,bins=100, range=(-1.0, 2.0), normed=True)
16: pylab.title("Histogram of Levy distribution for $ \\alpha $ = " + s... - CardShuffle.py (535 bytes)
4: HistoData = {}
13: if LL in HistoData: HistoData[LL] += 1
14: else: HistoData[LL] = 1
17: print(HistoData)
18: pylab.hist(data,bins=20,normed=True) - CouplingFromThePast.py (762 bytes)
21: pylab.hist(pos, bins=N, range=(-0.5, N - 0.5), normed=True) - Diffusion CFTP.py (4266 bytes)
33: plt.hist(pos, bins=N, range=(-0.5, N - 0.5), density=True)
41: Here is output of the above Python program. The histogram is absolutely flat, without any corrections.... - Diffusion.py (2640 bytes)
22: plt.hist(data, bins=N, range=(-0.5, N-0.5), density=True)
32: [[Image:Diffusion.png|left|600px|border|Histogram of output after 10 steps, starting from i=0.... - Buggy surface 2d.py (830 bytes)
19: plt.title('buggy_surface_2d.py (histogram of angles)')
21: plt.ylabel('histogram')
22: plt.hist(data, bins=100, density=True) - Naive surface 2d.py (854 bytes)
19: plt.title('naive_surface_2d.py (histogram of angles)')
21: plt.ylabel('histogram')
22: plt.hist(data, bins=100, density=True) - Direct surface 2d.py (819 bytes)
17: plt.title('direct_surface_2d.py (histogram of angles)')
19: plt.ylabel('histogram')
20: plt.hist(data, bins=100, density=True) - Sample transformation exp.py (987 bytes)
22: plt.hist(data, bins=100, density=True,label='data') - Sample transformation power.py (1003 bytes)
23: plt.hist(data, bins=100, density=True,label='data') - Diffusion forward.py (1357 bytes)
21: plt.hist(pos,bins=N,range=(-0.5, N - 0.5), density=True) - Diffusion CFTP coupl pos.py (1094 bytes)
27: plt.hist(pos, bins=N, range=(-0.5, N - 0.5), density=True) - Metropolis X2X4.py (1214 bytes)
26: plt.hist(data, bins=100, density=True,label='data') - Factor Metropolis X2X4.py (1388 bytes)
33: plt.hist(data, bins=100, density=True,label='data') - Lifted Metropolis X2X4.py (1280 bytes)
28: plt.hist(data, bins=100, density=True,label='data') - ZigZag X2X4.py (1419 bytes)
30: plt.hist(data, bins=100, density=True, label='data') - Factor Metropolis X2X4 patch.py (1461 bytes)
34: plt.hist(data, bins=100, density=True,label='data')
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