Merge branch 'devel' of github.com:SheffieldML/GPy into devel

Conflicts:
	GPy/examples/regression.py
	GPy/kern/constructors.py
	GPy/testing/kernel_tests.py
	GPy/util/multioutput.py

GPy/util/multioutput.py

@@ -0,0 +1,35 @@
+import numpy as np
+import warnings
+from .. import kern
+
+def build_lcm(input_dim, num_outputs, CK = [], NC = [], W_columns=1,W=None,kappa=None):
+    #TODO build_icm or build_lcm
+    """
+    Builds a kernel for a linear coregionalization model
+
+    :input_dim: Input dimensionality
+    :num_outputs: Number of outputs
+    :param CK: List of coregionalized kernels (i.e., this will be multiplied by a coregionalize kernel).
+    :param K: List of kernels that will be added up together with CK, but won't be multiplied by a coregionalize kernel
+    :param W_columns: number tuples of the corregionalization parameters 'coregion_W'
+    :type W_columns: integer
+    """
+
+    for k in CK:
+        if k.input_dim <> input_dim:
+            k.input_dim = input_dim
+            warnings.warn("kernel's input dimension overwritten to fit input_dim parameter.")
+
+    for k in NC:
+        if k.input_dim <> input_dim + 1:
+            k.input_dim = input_dim + 1
+            warnings.warn("kernel's input dimension overwritten to fit input_dim parameter.")
+
+    kernel = CK[0].prod(kern.coregionalize(num_outputs,W_columns,W,kappa),tensor=True)
+    for k in CK[1:]:
+        k_coreg = kern.coregionalize(num_outputs,W_columns,W,kappa)
+        kernel += k.prod(k_coreg,tensor=True)
+    for k in NC:
+        kernel += k
+
+    return kernel