Initial import

scripts/lpls/plots_lpls.py

@@ -0,0 +1,38 @@
+import pylab
+import matplotlib
+
+def plot_corrloads(R, pc1=0,pc2=1,s=20, c='b', zorder=5,expvar=None,ax=None,drawback=True, labels=None):
+    """ Correlation loading plot."""
+
+    # backgorund
+    if ax==None or drawback==True:
+        radius = 1
+        center = (0,0)
+        c100 = matplotlib.patches.Circle(center,radius=radius,
+                                         facecolor='gray',
+                                         alpha=.1,
+                                         zorder=1)
+        c50 = matplotlib.patches.Circle(center, radius=radius/2.0,
+                                        facecolor='gray',
+                                        alpha=.1,
+                                        zorder=2)
+        ax = pylab.gca()
+        ax.add_patch(c100)
+        ax.add_patch(c50)
+        ax.axhline(lw=1.5,color='k')
+        ax.axvline(lw=1.5,color='k')
+
+    # corrloads
+    ax.scatter(R[:,pc1], R[:,pc2], s=s, c=c,zorder=zorder)
+    ax.set_xlim([-1,1])
+    ax.set_ylim([-1,1])
+    if expvar!=None:
+        xstring = "Comp: %d   expl.var:  %.1f " %(pc1+1, expvar[pc1])
+        pylab.xlabel(xstring)
+        ystring = "Comp: %d   expl.var.:  %.1f " %(pc2+1, expvar[pc2])
+        pylab.ylabel(ystring)
+    if labels:
+        assert(len(labels)==R.shape[0])
+        for name, r in zip(labels, R):
+            ax.text(r[pc1], r[pc2], "  " + name)
+    #pylab.show()