ENH: linalg: use signature= for internal casting rather than astype in linalg ufuncs

1 files changed, 23 insertions, 12 deletions

diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index b0d43a531..ae0da3685 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -158,6 +158,7 @@ def _commonType(*arrays):
         t = double
     return t, result_type
 
+
 # _fastCopyAndTranpose assumes the input is 2D (as all the calls in here are).
 
 _fastCT = fastCopyAndTranspose
@@ -359,8 +360,9 @@ def solve(a, b):
     else:
         gufunc = _umath_linalg.solve
 
+    signature = 'DD->D' if isComplexType(t) else 'dd->d'
     extobj = get_linalg_error_extobj(_raise_linalgerror_singular)
-    r = gufunc(a.astype(t), b.astype(t), extobj=extobj)
+    r = gufunc(a, b, signature=signature, extobj=extobj)
 
     return wrap(r.astype(result_t))
 
@@ -493,8 +495,9 @@ def inv(a):
     _assertRankAtLeast2(a)
     _assertNdSquareness(a)
     t, result_t = _commonType(a)
+    signature = 'D->D' if isComplexType(t) else 'd->d'
     extobj = get_linalg_error_extobj(_raise_linalgerror_singular)
-    ainv = _umath_linalg.inv(a.astype(t), extobj=extobj)
+    ainv = _umath_linalg.inv(a, signature=signature, extobj=extobj)
     return wrap(ainv.astype(result_t))
 
 
@@ -576,7 +579,8 @@ def cholesky(a):
     _assertRankAtLeast2(a)
     _assertNdSquareness(a)
     t, result_t = _commonType(a)
-    return wrap(gufunc(a.astype(t), extobj=extobj).astype(result_t))
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    return wrap(gufunc(a, signature=signature, extobj=extobj).astype(result_t))
 
 # QR decompostion
 
@@ -866,8 +870,8 @@ def eigvals(a):
 
     extobj = get_linalg_error_extobj(
         _raise_linalgerror_eigenvalues_nonconvergence)
-
-    w = _umath_linalg.eigvals(a.astype(t), extobj=extobj)
+    signature = 'D->D' if isComplexType(t) else 'd->D'
+    w = _umath_linalg.eigvals(a, signature=signature, extobj=extobj)
 
     if not isComplexType(t):
         if all(w.imag == 0):
@@ -939,7 +943,8 @@ def eigvalsh(a, UPLO='L'):
     _assertRankAtLeast2(a)
     _assertNdSquareness(a)
     t, result_t = _commonType(a)
-    w = gufunc(a.astype(t), extobj=extobj)
+    signature = 'D->d' if isComplexType(t) else 'd->d'
+    w = gufunc(a, signature=signature, extobj=extobj)
     return w.astype(result_t)
 
 def _convertarray(a):
@@ -1071,7 +1076,8 @@ def eig(a):
 
     extobj = get_linalg_error_extobj(
         _raise_linalgerror_eigenvalues_nonconvergence)
-    w, vt = _umath_linalg.eig(a.astype(t), extobj=extobj)
+    signature = 'D->DD' if isComplexType(t) else 'd->DD'
+    w, vt = _umath_linalg.eig(a, signature=signature, extobj=extobj)
 
     if not isComplexType(t) and all(w.imag == 0.0):
         w = w.real
@@ -1182,7 +1188,8 @@ def eigh(a, UPLO='L'):
     else:
         gufunc = _umath_linalg.eigh_up
 
-    w, vt = gufunc(a.astype(t), extobj=extobj)
+    signature = 'D->dD' if isComplexType(t) else 'd->dd'
+    w, vt = gufunc(a, signature=signature, extobj=extobj)
     w = w.astype(_realType(result_t))
     vt = vt.astype(result_t)
     return w, wrap(vt)
@@ -1291,7 +1298,8 @@ def svd(a, full_matrices=1, compute_uv=1):
             else:
                 gufunc = _umath_linalg.svd_n_s
 
-        u, s, vt = gufunc(a.astype(t), extobj=extobj)
+        signature = 'D->DdD' if isComplexType(t) else 'd->ddd'
+        u, s, vt = gufunc(a, signature=signature, extobj=extobj)
         u = u.astype(result_t)
         s = s.astype(_realType(result_t))
         vt = vt.astype(result_t)
@@ -1302,7 +1310,8 @@ def svd(a, full_matrices=1, compute_uv=1):
         else:
             gufunc = _umath_linalg.svd_n
 
-        s = gufunc(a.astype(t), extobj=extobj)
+        signature = 'D->d' if isComplexType(t) else 'd->d'
+        s = gufunc(a, signature=signature, extobj=extobj)
         s = s.astype(_realType(result_t))
         return s
 
@@ -1638,7 +1647,8 @@ def slogdet(a):
     _assertNdSquareness(a)
     t, result_t = _commonType(a)
     real_t = _realType(result_t)
-    sign, logdet = _umath_linalg.slogdet(a.astype(t))
+    signature = 'D->Dd' if isComplexType(t) else 'd->dd'
+    sign, logdet = _umath_linalg.slogdet(a, signature=signature)
     return sign.astype(result_t), logdet.astype(real_t)
 
 def det(a):
@@ -1690,7 +1700,8 @@ def det(a):
     _assertRankAtLeast2(a)
     _assertNdSquareness(a)
     t, result_t = _commonType(a)
-    return _umath_linalg.det(a.astype(t)).astype(result_t)
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    return _umath_linalg.det(a, signature=signature).astype(result_t)
 
 # Linear Least Squares