diff options
Diffstat (limited to 'examples/plot_optim_OTreg.py')
-rw-r--r-- | examples/plot_optim_OTreg.py | 75 |
1 files changed, 46 insertions, 29 deletions
diff --git a/examples/plot_optim_OTreg.py b/examples/plot_optim_OTreg.py index 8abb426..276b250 100644 --- a/examples/plot_optim_OTreg.py +++ b/examples/plot_optim_OTreg.py @@ -12,63 +12,80 @@ 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') +pl.figure(3, figsize=(5, 5)) +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 -reg=1e-1 +def f(G): + return 0.5 * np.sum(G**2) + + +def df(G): + return G -Gl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True) + +reg = 1e-1 + +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)) + -Ge=ot.optim.cg(a,b,M,reg,f,df,verbose=True) +def df(G): + return np.log(G) + 1. -pl.figure(4) -ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg') + +reg = 1e-3 + +Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True) + +pl.figure(4, figsize=(5, 5)) +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 +pl.figure(5, figsize=(5, 5)) +ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg') +pl.show() |