Merge pull request #55 from Saurabh7/master

Some fixes for GP regression

demos/regression/gp.py

@@ -184,7 +184,10 @@ def _process(feat_train, labels, noise_level, scale, kernel, domain, learn, feat
     n_dimensions = 1
 
     likelihood = sg.GaussianLikelihood()
-    likelihood.set_sigma(noise_level)
+    if learn == 'ML2':
+        likelihood.set_sigma(1)
+    else:
+        likelihood.set_sigma(noise_level)
     covar_parms = np.log([2])
     hyperparams = {'covar': covar_parms, 'lik': np.log([1])}
 
@@ -194,11 +197,17 @@ def _process(feat_train, labels, noise_level, scale, kernel, domain, learn, feat
     zmean = sg.ZeroMean()
     if str(inf_select) == 'ExactInferenceMethod':
         inf = sg.ExactInferenceMethod(SECF, feat_train, zmean, labels, likelihood)
-        inf.set_scale(scale)
+        if learn == 'ML2':
+            inf.set_scale(1)
+        else:
+            inf.set_scale(scale)
     elif str(inf_select) == 'FITCInferenceMethod':
         if feat_induc != None:
             inf = sg.FITCInferenceMethod(SECF, feat_train, zmean, labels, likelihood, feat_induc)
-            inf.set_scale(scale)
+            if learn == 'ML2':
+                inf.set_scale(1)
+            else:
+                inf.set_scale(scale)
         elif feat_induc == None:
             raise ValueError("Argument Error")
 

templates/regression/gaussian_process.html

@@ -15,7 +15,7 @@
         .style("stroke", "lightgrey");
 }
 
-function TrainGP(data)
+function plotMean(data)
 {
     json = $.parseJSON(data);
 
@@ -55,6 +55,12 @@
     $("#TrainGP").attr('disabled', false);
 }
 
+function TrainGP(data)
+{
+    svg.selectAll(".heatmap").remove();
+    plotMean(data)    
+}
+
 function plot_predictive(raw_data)
 {
 
@@ -77,6 +83,8 @@
     var y_scale = result['y_scale'];
     var color_scale = result['color_scale'];
 
+    svg.selectAll(".line").remove();
+
     svg.selectAll(".heatmap").remove();
 
     svg.selectAll(".heatmap")
@@ -107,7 +115,7 @@
         .style("stroke", "grey");
     $('#legend').html("<span id='lower' style='float:left; color:white;'>" + Math.floor(domain[0]) + "</span><span id='upper' style='float:right; color:white;'>" + Math.ceil(domain[1]) + "</span>") ;
 
-    TrainGP(raw_data)
+    plotMean(raw_data)
 
 }