From 062071b20d1d40c64bb619931bd11bd28e780485 Mon Sep 17 00:00:00 2001 From: Rémi Flamary Date: Fri, 1 Sep 2017 15:31:44 +0200 Subject: update example with rst titles --- docs/source/auto_examples/plot_OTDA_classes.rst | 190 ------------------------ 1 file changed, 190 deletions(-) delete mode 100644 docs/source/auto_examples/plot_OTDA_classes.rst (limited to 'docs/source/auto_examples/plot_OTDA_classes.rst') diff --git a/docs/source/auto_examples/plot_OTDA_classes.rst b/docs/source/auto_examples/plot_OTDA_classes.rst deleted file mode 100644 index 097e9fc..0000000 --- a/docs/source/auto_examples/plot_OTDA_classes.rst +++ /dev/null @@ -1,190 +0,0 @@ - - -.. _sphx_glr_auto_examples_plot_OTDA_classes.py: - - -======================== -OT for domain adaptation -======================== - - - - - -.. rst-class:: sphx-glr-horizontal - - - * - - .. image:: /auto_examples/images/sphx_glr_plot_OTDA_classes_001.png - :scale: 47 - - * - - .. image:: /auto_examples/images/sphx_glr_plot_OTDA_classes_004.png - :scale: 47 - - -.. rst-class:: sphx-glr-script-out - - Out:: - - It. |Loss |Delta loss - -------------------------------- - 0|9.171271e+00|0.000000e+00 - 1|2.133783e+00|-3.298127e+00 - 2|1.895941e+00|-1.254484e-01 - 3|1.844628e+00|-2.781709e-02 - 4|1.824983e+00|-1.076467e-02 - 5|1.815453e+00|-5.249337e-03 - 6|1.808104e+00|-4.064733e-03 - 7|1.803558e+00|-2.520475e-03 - 8|1.801061e+00|-1.386155e-03 - 9|1.799391e+00|-9.279565e-04 - 10|1.797176e+00|-1.232778e-03 - 11|1.795465e+00|-9.529479e-04 - 12|1.795316e+00|-8.322362e-05 - 13|1.794523e+00|-4.418932e-04 - 14|1.794444e+00|-4.390599e-05 - 15|1.794395e+00|-2.710318e-05 - 16|1.793713e+00|-3.804028e-04 - 17|1.793110e+00|-3.359479e-04 - 18|1.792829e+00|-1.569563e-04 - 19|1.792621e+00|-1.159469e-04 - It. |Loss |Delta loss - -------------------------------- - 20|1.791334e+00|-7.187689e-04 - - - - -| - - -.. code-block:: python - - - import matplotlib.pylab as pl - import ot - - - - - #%% parameters - - n=150 # nb samples in source and target datasets - - xs,ys=ot.datasets.get_data_classif('3gauss',n) - xt,yt=ot.datasets.get_data_classif('3gauss2',n) - - - - - #%% plot samples - - pl.figure(1) - - pl.subplot(2,2,1) - pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples') - pl.legend(loc=0) - pl.title('Source distributions') - - pl.subplot(2,2,2) - pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples') - pl.legend(loc=0) - pl.title('target distributions') - - - #%% OT estimation - - # LP problem - da_emd=ot.da.OTDA() # init class - da_emd.fit(xs,xt) # fit distributions - xst0=da_emd.interp() # interpolation of source samples - - - # sinkhorn regularization - lambd=1e-1 - da_entrop=ot.da.OTDA_sinkhorn() - da_entrop.fit(xs,xt,reg=lambd) - xsts=da_entrop.interp() - - # non-convex Group lasso regularization - reg=1e-1 - eta=1e0 - da_lpl1=ot.da.OTDA_lpl1() - da_lpl1.fit(xs,ys,xt,reg=reg,eta=eta) - xstg=da_lpl1.interp() - - - # True Group lasso regularization - reg=1e-1 - eta=2e0 - da_l1l2=ot.da.OTDA_l1l2() - da_l1l2.fit(xs,ys,xt,reg=reg,eta=eta,numItermax=20,verbose=True) - xstgl=da_l1l2.interp() - - - #%% plot interpolated source samples - pl.figure(4,(15,8)) - - param_img={'interpolation':'nearest','cmap':'jet'} - - pl.subplot(2,4,1) - pl.imshow(da_emd.G,**param_img) - pl.title('OT matrix') - - - pl.subplot(2,4,2) - pl.imshow(da_entrop.G,**param_img) - pl.title('OT matrix sinkhorn') - - pl.subplot(2,4,3) - pl.imshow(da_lpl1.G,**param_img) - pl.title('OT matrix non-convex Group Lasso') - - pl.subplot(2,4,4) - pl.imshow(da_l1l2.G,**param_img) - pl.title('OT matrix Group Lasso') - - - pl.subplot(2,4,5) - pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3) - pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30) - pl.title('Interp samples') - pl.legend(loc=0) - - pl.subplot(2,4,6) - pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3) - pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30) - pl.title('Interp samples Sinkhorn') - - pl.subplot(2,4,7) - pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3) - pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30) - pl.title('Interp samples non-convex Group Lasso') - - pl.subplot(2,4,8) - pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.3) - pl.scatter(xstgl[:,0],xstgl[:,1],c=ys,marker='+',label='Transp samples',s=30) - pl.title('Interp samples Group Lasso') -**Total running time of the script:** ( 0 minutes 2.225 seconds) - - - -.. container:: sphx-glr-footer - - - .. container:: sphx-glr-download - - :download:`Download Python source code: plot_OTDA_classes.py ` - - - - .. container:: sphx-glr-download - - :download:`Download Jupyter notebook: plot_OTDA_classes.ipynb ` - -.. rst-class:: sphx-glr-signature - - `Generated by Sphinx-Gallery `_ -- cgit v1.2.3