From fef377f47494012c4156ba7fb63621c631523c24 Mon Sep 17 00:00:00 2001 From: Tiago Freitas Pereira <tiagofrepereira@gmail.com> Date: Wed, 30 Mar 2022 15:52:42 +0200 Subject: [PATCH] Added plotting mechanism --- doc/plot/plot_ISV.py | 4 ++++ doc/plot/plot_JFA.py | 3 +++ 2 files changed, 7 insertions(+) diff --git a/doc/plot/plot_ISV.py b/doc/plot/plot_ISV.py index 91b9ff6..fc3f9c1 100644 --- a/doc/plot/plot_ISV.py +++ b/doc/plot/plot_ISV.py @@ -57,6 +57,10 @@ ubm = bob.learn.em.GMMMachine(n_gaussians).fit(X) gmm_stats = [ubm.acc_statistics(x[np.newaxis]) for x in X] isv_machine = bob.learn.em.ISVMachine(ubm, r_U).fit(gmm_stats, y) +# gmm_stats = [ubm.acc_statistics(x) for x in [setosa, versicolor, virginica]] +# isv_machine = bob.learn.em.ISVMachine(ubm, r_U).fit(gmm_stats, [0, 1, 2]) + + # isvbase = isv_train([setosa, versicolor, virginica], ubm) # Variability direction diff --git a/doc/plot/plot_JFA.py b/doc/plot/plot_JFA.py index f77e677..cae3e31 100644 --- a/doc/plot/plot_JFA.py +++ b/doc/plot/plot_JFA.py @@ -58,6 +58,9 @@ ubm = bob.learn.em.GMMMachine(n_gaussians).fit(X) gmm_stats = [ubm.acc_statistics(x[np.newaxis]) for x in X] jfa_machine = bob.learn.em.JFAMachine(ubm, r_U, r_V).fit(gmm_stats, y) +# gmm_stats = [ubm.acc_statistics(x) for x in [setosa, versicolor, virginica]] +# jfa_machine = bob.learn.em.JFAMachine(ubm, r_U, r_V).fit(gmm_stats, [0, 1, 2]) + # Variability direction U u0 = jfa_machine.U[0:2, 0] / np.linalg.norm(jfa_machine.U[0:2, 0]) -- GitLab