Pre-devel-move check in

GPy/core/symbolic.py

@@ -107,14 +107,14 @@ class Symbolic_core():
 
             # Do symbolic work to compute derivatives.        
             for key, func in self.expressions.items():
-                if func['function'].is_Matrix:
+                # if func['function'].is_Matrix:
-                    rows = func['function'].shape[0]
+                #     rows = func['function'].shape[0]
-                    cols = func['function'].shape[1]
+                #     cols = func['function'].shape[1]
-                    self.expressions[key]['derivative'] = sym.zeros(rows, cols)
+                #     self.expressions[key]['derivative'] = sym.zeros(rows, cols)
-                    for i in xrange(rows):
+                #     for i in xrange(rows):
-                        for j in xrange(cols):
+                #         for j in xrange(cols):
-                            self.expressions[key]['derivative'][i, j] = extract_derivative(func['function'][i, j], derivative_arguments)
+                #             self.expressions[key]['derivative'][i, j] = extract_derivative(func['function'][i, j], derivative_arguments)
-                else:
+                # else:
                     self.expressions[key]['derivative'] = extract_derivative(func['function'], derivative_arguments)
 
     def _set_parameters(self, parameters):

GPy/likelihoods/__init__.py

@@ -6,18 +6,18 @@ from poisson import Poisson
 from student_t import StudentT
 from likelihood import Likelihood
 from mixed_noise import MixedNoise
-# TODO need to fix this in a config file.
+#TODO need to fix this in a config file.
-# TODO need to add the files to the git repo!
+#TODO need to add the files to the git repo!
-#try:
+try:
-    #import sympy as sym
+    import sympy as sym
-    #sympy_available=True
+    sympy_available=True
-#except ImportError:
+except ImportError:
-    #sympy_available=False
+    sympy_available=False
-#if sympy_available:
+if sympy_available:
-    ## These are likelihoods that rely on symbolic.
+    #These are likelihoods that rely on symbolic.
-    #from symbolic import Symbolic
+    from symbolic import Symbolic
-    #from sstudent_t import SstudentT
+    from sstudent_t import SstudentT
-    #from negative_binomial import Negative_binomial
+    from negative_binomial import Negative_binomial
-    ##from skew_normal import Skew_normal
+    from skew_normal import Skew_normal
-    #from skew_exponential import Skew_exponential
+    from skew_exponential import Skew_exponential
-    #from null_category import Null_category
+#    from null_category import Null_category

GPy/util/symbolic.py

@@ -2,15 +2,22 @@ import sys
 import numpy as np
 import sympy as sym
 from sympy import Function, S, oo, I, cos, sin, asin, log, erf, pi, exp, sqrt, sign, gamma, polygamma
-
+from sympy.matrices import Matrix
 ########################################
 ## Try to do some matrix functions: problem, you can't do derivatives
 ## with respect to matrix functions :-(
 
+class GPySymMatrix(Matrix):
+    def __init__(self, indices):
+        Matrix.__init__(self)
+    def atoms(self):
+        return [e2 for e in self for e2 in e.atoms()]
+        
 class selector(Function):
     """A function that returns an element of a Matrix depending on input indices."""
     nargs = 3
-
+    def fdiff(self, argindex=1):
+        return selector(*self.args)
     @classmethod
     def eval(cls, X, i, j):
         if i.is_Number and j.is_Number: