[added testing and plotting] restructuring the plotting library

GPy/plotting/gpy_plot/data_plots.py

@@ -0,0 +1,104 @@
+#===============================================================================
+# Copyright (c) 2012-2015, GPy authors (see AUTHORS.txt).
+# All rights reserved.
+# 
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+# 
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+# 
+# * Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+# 
+# * Neither the name of GPy nor the names of its
+#   contributors may be used to endorse or promote products derived from
+#   this software without specific prior written permission.
+# 
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#===============================================================================
+from . import pl
+from . import update_not_existing_kwargs
+from . import defaults
+
+from functools import wraps
+import numpy as np
+
+def _plot_data(self, canvas, which_data_rows='all',
+        which_data_ycols='all', visible_dims=None,
+        error_kwargs=None, **plot_kwargs):
+    """
+    Plot the training data
+      - For higher dimensions than two, use fixed_inputs to plot the data points with some of the inputs fixed.
+
+    Can plot only part of the data
+    using which_data_rows and which_data_ycols.
+
+    :param which_data_rows: which of the training data to plot (default all)
+    :type which_data_rows: 'all' or a slice object to slice self.X, self.Y
+    :param which_data_ycols: when the data has several columns (independant outputs), only plot these
+    :type which_data_rows: 'all' or a list of integers
+    :param visible_dims: an array specifying the input dimensions to plot (maximum two)
+    :type visible_dims: a numpy array
+    :param dict error_kwargs: kwargs for the error plot for the plotting library you are using
+    :param kwargs plot_kwargs: kwargs for the data plot for the plotting library you are using
+    """
+    #deal with optional arguments
+    if which_data_rows == 'all':
+        which_data_rows = slice(None)
+    if which_data_ycols == 'all':
+        which_data_ycols = np.arange(self.output_dim)
+    if error_kwargs is None:
+        error_kwargs = {}
+
+    if hasattr(self, 'has_uncertain_inputs') and self.has_uncertain_inputs():
+        X = self.X.mean
+        X_variance = self.X.variance
+    else:
+        X = self.X
+        X_variance = None
+    Y = self.Y
+
+    #work out what the inputs are for plotting (1D or 2D)
+    if visible_dims is None:
+        visible_dims = np.arange(self.input_dim)
+    assert visible_dims.size <= 2, "Visible inputs cannot be larger than two"
+    free_dims = visible_dims
+    
+    #one dimensional plotting
+    if len(free_dims) == 1:
+        for d in which_data_ycols:
+            update_not_existing_kwargs(plot_kwargs, defaults.data_1d)
+            canvas.append(pl.scatter(canvas, X[which_data_rows, free_dims], Y[which_data_rows, d], **plot_kwargs))
+            if X_variance is not None:
+                update_not_existing_kwargs(error_kwargs, defaults.xerrorbar)
+                canvas.append(pl.xerrorbar(canvas, X[which_data_rows, free_dims].flatten(), Y[which_data_rows, d].flatten(),
+                            2 * np.sqrt(X_variance[which_data_rows, free_dims].flatten()),
+                            **error_kwargs))
+    #2D plotting
+    elif len(free_dims) == 2:
+        for d in which_data_ycols:
+            update_not_existing_kwargs(plot_kwargs, defaults.data_2d)
+            canvas = pl.scatter(canvas, X[which_data_rows, free_dims[0]], X[which_data_rows, free_dims[1]], 
+                                           c=Y[which_data_rows, d], vmin=Y.min(), vmax=Y.max(), **plot_kwargs)
+    else:
+        raise NotImplementedError("Cannot plot in more then two dimensions")
+    return canvas
+
+@wraps(_plot_data)
+def plot_data(self, which_data_rows='all',
+        which_data_ycols='all', visible_dims=None,
+        error_kwargs=None, **plot_kwargs):
+    canvas, kwargs = pl.get_new_canvas(plot_kwargs)
+    _plot_data(self, canvas, which_data_rows, which_data_ycols, visible_dims, error_kwargs, **kwargs)
+    return pl.show_canvas(canvas)