From df99f982a2746f45da005f18581a2da3e9812ffe Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Tue, 1 Mar 2016 10:09:10 +0000 Subject: [PATCH 1/2] [mrd] matplotlib specific fig_kwargs matplotlib specific --- GPy/models/mrd.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/models/mrd.py b/GPy/models/mrd.py index 4e7f2f3b..5b6635a8 100644 --- a/GPy/models/mrd.py +++ b/GPy/models/mrd.py @@ -236,7 +236,7 @@ class MRD(BayesianGPLVMMiniBatch): # sharex=sharex, sharey=sharey) # return fig - def plot_scales(self, titles=None, fig_kwargs=dict(figsize=None, tight_layout=True), **kwargs): + def plot_scales(self, titles=None, fig_kwargs={}, **kwargs): """ Plot input sensitivity for all datasets, to see which input dimensions are significant for which dataset. From 7c173056edf8558ef1b49d2f87ba5347daee8c48 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Tue, 1 Mar 2016 14:42:31 +0000 Subject: [PATCH 2/2] [plotly] fixes for mrd --- GPy/models/mrd.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/GPy/models/mrd.py b/GPy/models/mrd.py index 5b6635a8..547f096f 100644 --- a/GPy/models/mrd.py +++ b/GPy/models/mrd.py @@ -252,12 +252,9 @@ class MRD(BayesianGPLVMMiniBatch): M = len(self.bgplvms) fig = pl().figure(rows=1, cols=M, **fig_kwargs) - plots = {} for c in range(M): canvas = self.bgplvms[c].kern.plot_ARD(title=titles[c], figure=fig, col=c+1, **kwargs) - plots[titles[c]] = canvas - pl().show_canvas(canvas) - return plots + return canvas def plot_latent(self, labels=None, which_indices=None, resolution=60, legend=True,