Relocated and renamed

GPy/plotting/matplot_dep/base_plots.py

@@ -0,0 +1,135 @@
+# #Copyright (c) 2012, GPy authors (see AUTHORS.txt).
+# Licensed under the BSD 3-clause license (see LICENSE.txt)
+
+
+import Tango
+import pylab as pb
+import numpy as np
+
+def gpplot(x,mu,lower,upper,edgecol=Tango.colorsHex['darkBlue'],fillcol=Tango.colorsHex['lightBlue'],axes=None,**kwargs):
+    if axes is None:
+        axes = pb.gca()
+    mu = mu.flatten()
+    x = x.flatten()
+    lower = lower.flatten()
+    upper = upper.flatten()
+
+    #here's the mean
+    axes.plot(x,mu,color=edgecol,linewidth=2)
+
+    #here's the box
+    kwargs['linewidth']=0.5
+    if not 'alpha' in kwargs.keys():
+        kwargs['alpha'] = 0.3
+    axes.fill(np.hstack((x,x[::-1])),np.hstack((upper,lower[::-1])),color=fillcol,**kwargs)
+
+    #this is the edge:
+    axes.plot(x,upper,color=edgecol,linewidth=0.2)
+    axes.plot(x,lower,color=edgecol,linewidth=0.2)
+
+def removeRightTicks(ax=None):
+    ax = ax or pb.gca()
+    for i, line in enumerate(ax.get_yticklines()):
+        if i%2 == 1:   # odd indices
+            line.set_visible(False)
+def removeUpperTicks(ax=None):
+    ax = ax or pb.gca()
+    for i, line in enumerate(ax.get_xticklines()):
+        if i%2 == 1:   # odd indices
+            line.set_visible(False)
+def fewerXticks(ax=None,divideby=2):
+    ax = ax or pb.gca()
+    ax.set_xticks(ax.get_xticks()[::divideby])
+
+def align_subplots(N,M,xlim=None, ylim=None):
+    """make all of the subplots have the same limits, turn off unnecessary ticks"""
+    #find sensible xlim,ylim
+    if xlim is None:
+        xlim = [np.inf,-np.inf]
+        for i in range(N*M):
+            pb.subplot(N,M,i+1)
+            xlim[0] = min(xlim[0],pb.xlim()[0])
+            xlim[1] = max(xlim[1],pb.xlim()[1])
+    if ylim is None:
+        ylim = [np.inf,-np.inf]
+        for i in range(N*M):
+            pb.subplot(N,M,i+1)
+            ylim[0] = min(ylim[0],pb.ylim()[0])
+            ylim[1] = max(ylim[1],pb.ylim()[1])
+
+    for i in range(N*M):
+        pb.subplot(N,M,i+1)
+        pb.xlim(xlim)
+        pb.ylim(ylim)
+        if (i)%M:
+            pb.yticks([])
+        else:
+            removeRightTicks()
+        if i<(M*(N-1)):
+            pb.xticks([])
+        else:
+            removeUpperTicks()
+
+def align_subplot_array(axes,xlim=None, ylim=None):
+    """make all of the axes in the array hae the same limits, turn off unnecessary ticks
+    
+    use pb.subplots() to get an array of axes
+    """
+    #find sensible xlim,ylim
+    if xlim is None:
+        xlim = [np.inf,-np.inf]
+        for ax in axes.flatten():
+            xlim[0] = min(xlim[0],ax.get_xlim()[0])
+            xlim[1] = max(xlim[1],ax.get_xlim()[1])
+    if ylim is None:
+        ylim = [np.inf,-np.inf]
+        for ax in axes.flatten():
+            ylim[0] = min(ylim[0],ax.get_ylim()[0])
+            ylim[1] = max(ylim[1],ax.get_ylim()[1])
+
+    N,M = axes.shape
+    for i,ax in enumerate(axes.flatten()):
+        ax.set_xlim(xlim)
+        ax.set_ylim(ylim)
+        if (i)%M:
+            ax.set_yticks([])
+        else:
+            removeRightTicks(ax)
+        if i<(M*(N-1)):
+            ax.set_xticks([])
+        else:
+            removeUpperTicks(ax)
+
+def x_frame1D(X,plot_limits=None,resolution=None):
+    """
+    Internal helper function for making plots, returns a set of input values to plot as well as lower and upper limits
+    """
+    assert X.shape[1] ==1, "x_frame1D is defined for one-dimensional inputs"
+    if plot_limits is None:
+        xmin,xmax = X.min(0),X.max(0)
+        xmin, xmax = xmin-0.2*(xmax-xmin), xmax+0.2*(xmax-xmin)
+    elif len(plot_limits)==2:
+        xmin, xmax = plot_limits
+    else:
+        raise ValueError, "Bad limits for plotting"
+
+    Xnew = np.linspace(xmin,xmax,resolution or 200)[:,None]
+    return Xnew, xmin, xmax
+
+def x_frame2D(X,plot_limits=None,resolution=None):
+    """
+    Internal helper function for making plots, returns a set of input values to plot as well as lower and upper limits
+    """
+    assert X.shape[1] ==2, "x_frame2D is defined for two-dimensional inputs"
+    if plot_limits is None:
+        xmin,xmax = X.min(0),X.max(0)
+        xmin, xmax = xmin-0.2*(xmax-xmin), xmax+0.2*(xmax-xmin)
+    elif len(plot_limits)==2:
+        xmin, xmax = plot_limits
+    else:
+        raise ValueError, "Bad limits for plotting"
+
+    resolution = resolution or 50
+    xx,yy = np.mgrid[xmin[0]:xmax[0]:1j*resolution,xmin[1]:xmax[1]:1j*resolution]
+    Xnew = np.vstack((xx.flatten(),yy.flatten())).T
+    return Xnew, xx, yy, xmin, xmax