Factored out lapack into utils so we can check version and give deprecation warnings

GPy/util/linalg.py

@@ -11,6 +11,12 @@ import types
 import ctypes
 from ctypes import byref, c_char, c_int, c_double # TODO
 # import scipy.lib.lapack
+import scipy
+
+if np.all(np.float64((scipy.__version__).split('.')[:2]) >= np.array([0, 10])):
+    import scipy.linalg.lapack as lapack
+else:
+    import scipy.linalg.lapack.flapack as lapack
 
 try:
     _blaslib = ctypes.cdll.LoadLibrary(np.core._dotblas.__file__) # @UndefinedVariable
@@ -18,6 +24,36 @@ try:
 except:
     _blas_available = False
 
+def dtrtrs(A, B, lower=0, trans=0, unitdiag=0, overwrite_b=0):
+    """Wrapper for lapack dtrtrs function
+
+    :param A: Matrix A
+    :param B: Matrix B
+    :param lower: is matrix lower (true) or upper (false)
+    :returns:
+    """
+    return lapack.dtrtrs(A, B, lower=lower, trans=trans, unitdiag=unitdiag, overwrite_b=overwrite_b)
+
+def dpotrs(A, B, overwrite_b=0, lower=0):
+    """Wrapper for lapack dpotrs function
+
+    :param A: Matrix A
+    :param B: Matrix B
+    :param lower: is matrix lower (true) or upper (false)
+    :returns:
+    """
+    return lapack.dpotrs(A, B, overwrite_b=overwrite_b, lower=lower)
+
+def dpotri(A, B, overwrite_b=0, lower=0):
+    """Wrapper for lapack dpotri function
+
+    :param A: Matrix A
+    :param B: Matrix B
+    :param lower: is matrix lower (true) or upper (false)
+    :returns:
+    """
+    return lapack.dpotri(A, B, overwrite_b=overwrite_b, lower=lower)
+
 def trace_dot(a, b):
     """
     efficiently compute the trace of the matrix product of a and b
@@ -56,7 +92,7 @@ def _mdot_r(a, b):
 
 def jitchol(A, maxtries=5):
     A = np.asfortranarray(A)
-    L, info = linalg.lapack.flapack.dpotrf(A, lower=1)
+    L, info = lapack.dpotrf(A, lower=1)
     if info == 0:
         return L
     else:
@@ -117,7 +153,7 @@ def pdinv(A, *args):
     L = jitchol(A, *args)
     logdet = 2.*np.sum(np.log(np.diag(L)))
     Li = chol_inv(L)
-    Ai, _ = linalg.lapack.flapack.dpotri(L)
+    Ai, _ = lapack.dpotri(L)
     # Ai = np.tril(Ai) + np.tril(Ai,-1).T
     symmetrify(Ai)
 
@@ -133,7 +169,7 @@ def chol_inv(L):
 
     """
 
-    return linalg.lapack.flapack.dtrtri(L, lower=True)[0]
+    return lapack.dtrtri(L, lower=True)[0]
 
 
 def multiple_pdinv(A):
@@ -150,7 +186,7 @@ def multiple_pdinv(A):
     N = A.shape[-1]
     chols = [jitchol(A[:, :, i]) for i in range(N)]
     halflogdets = [np.sum(np.log(np.diag(L[0]))) for L in chols]
-    invs = [linalg.lapack.flapack.dpotri(L[0], True)[0] for L in chols]
+    invs = [lapack.dpotri(L[0], True)[0] for L in chols]
     invs = [np.triu(I) + np.triu(I, 1).T for I in invs]
     return np.dstack(invs), np.array(halflogdets)
 
@@ -351,9 +387,9 @@ def cholupdate(L, x):
 def backsub_both_sides(L, X, transpose='left'):
     """ Return L^-T * X * L^-1, assumuing X is symmetrical and L is lower cholesky"""
     if transpose == 'left':
-        tmp, _ = linalg.lapack.flapack.dtrtrs(L, np.asfortranarray(X), lower=1, trans=1)
-        return linalg.lapack.flapack.dtrtrs(L, np.asfortranarray(tmp.T), lower=1, trans=1)[0].T
+        tmp, _ = lapack.dtrtrs(L, np.asfortranarray(X), lower=1, trans=1)
+        return lapack.dtrtrs(L, np.asfortranarray(tmp.T), lower=1, trans=1)[0].T
     else:
-        tmp, _ = linalg.lapack.flapack.dtrtrs(L, np.asfortranarray(X), lower=1, trans=0)
-        return linalg.lapack.flapack.dtrtrs(L, np.asfortranarray(tmp.T), lower=1, trans=0)[0].T
+        tmp, _ = lapack.dtrtrs(L, np.asfortranarray(X), lower=1, trans=0)
+        return lapack.dtrtrs(L, np.asfortranarray(tmp.T), lower=1, trans=0)[0].T