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author | Alexandre Gramfort <alexandre.gramfort@m4x.org> | 2017-07-12 22:17:52 +0200 |
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committer | Alexandre Gramfort <alexandre.gramfort@m4x.org> | 2017-07-20 14:05:12 +0200 |
commit | c5a72cc1ff6a1f5462fdca6ced837180820fe19b (patch) | |
tree | e78e4b55a5ae805c3124c7ccd7a24910aaf729b7 | |
parent | de5903618d2d525e48e3f5ffc205c3f566f0095d (diff) |
do plot_optim_OTreg.py
-rw-r--r-- | examples/plot_optim_OTreg.py | 65 |
1 files changed, 39 insertions, 26 deletions
diff --git a/examples/plot_optim_OTreg.py b/examples/plot_optim_OTreg.py index 8abb426..0041770 100644 --- a/examples/plot_optim_OTreg.py +++ b/examples/plot_optim_OTreg.py @@ -12,63 +12,76 @@ import matplotlib.pylab as pl import ot - #%% parameters -n=100 # nb bins +n = 100 # nb bins # bin positions -x=np.arange(n,dtype=np.float64) +x = np.arange(n, dtype=np.float64) # Gaussian distributions -a=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std -b=ot.datasets.get_1D_gauss(n,m=60,s=10) +a = ot.datasets.get_1D_gauss(n, m=20, s=5) # m= mean, s= std +b = ot.datasets.get_1D_gauss(n, m=60, s=10) # loss matrix -M=ot.dist(x.reshape((n,1)),x.reshape((n,1))) -M/=M.max() +M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1))) +M /= M.max() #%% EMD -G0=ot.emd(a,b,M) +G0 = ot.emd(a, b, M) pl.figure(3) -ot.plot.plot1D_mat(a,b,G0,'OT matrix G0') +ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0') #%% Example with Frobenius norm regularization -def f(G): return 0.5*np.sum(G**2) -def df(G): return G +def f(G): + return 0.5 * np.sum(G**2) + + +def df(G): + return G -reg=1e-1 +reg = 1e-1 -Gl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True) +Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True) pl.figure(3) -ot.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg') +ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg') #%% Example with entropic regularization -def f(G): return np.sum(G*np.log(G)) -def df(G): return np.log(G)+1 -reg=1e-3 +def f(G): + return np.sum(G * np.log(G)) + + +def df(G): + return np.log(G) + 1. -Ge=ot.optim.cg(a,b,M,reg,f,df,verbose=True) +reg = 1e-3 + +Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True) pl.figure(4) -ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg') +ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg') #%% Example with Frobenius norm + entropic regularization with gcg -def f(G): return 0.5*np.sum(G**2) -def df(G): return G -reg1=1e-3 -reg2=1e-1 +def f(G): + return 0.5 * np.sum(G**2) + + +def df(G): + return G + +reg1 = 1e-3 +reg2 = 1e-1 -Gel2=ot.optim.gcg(a,b,M,reg1,reg2,f,df,verbose=True) +Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True) pl.figure(5) -ot.plot.plot1D_mat(a,b,Gel2,'OT entropic + matrix Frob. reg') -pl.show()
\ No newline at end of file +ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg') +pl.show() |