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-rw-r--r--scipy/corelib/mtrand/mtrand.c2
-rw-r--r--scipy/corelib/mtrand/mtrand.pyx2
2 files changed, 2 insertions, 2 deletions
diff --git a/scipy/corelib/mtrand/mtrand.c b/scipy/corelib/mtrand/mtrand.c
index 327bd7fa3..3d565eee4 100644
--- a/scipy/corelib/mtrand/mtrand.c
+++ b/scipy/corelib/mtrand/mtrand.c
@@ -3847,7 +3847,7 @@ static __Pyx_InternTabEntry __pyx_intern_tab[] = {
{&__pyx_n_Float64, "Float64"},
{&__pyx_n_Int, "Int"},
{&__pyx_n_MT19937, "MT19937"},
- {&__pyx_n_Numeric, "Numeric"},
+ {&__pyx_n_Numeric, "scipy"},
{&__pyx_n_ValueError, "ValueError"},
{&__pyx_n___RandomState_ctor, "__RandomState_ctor"},
{&__pyx_n__rand, "_rand"},
diff --git a/scipy/corelib/mtrand/mtrand.pyx b/scipy/corelib/mtrand/mtrand.pyx
index d1fb6d183..640134ea0 100644
--- a/scipy/corelib/mtrand/mtrand.pyx
+++ b/scipy/corelib/mtrand/mtrand.pyx
@@ -670,7 +670,7 @@ cdef class RandomState:
# covariance. Note that sqrt(s)*v where (u,s,v) is the singular value
# decomposition of cov is such an A.
(u,s,v) = scipy.linalg.singular_value_decomposition(cov)
- x = scipy.matrixmultiply(x*Numeric.sqrt(s),v)
+ x = scipy.matrixmultiply(x*scipy.sqrt(s),v)
# The rows of x now have the correct covariance but mean 0. Add
# mean to each row. Then each row will have mean mean.
scipy.add(mean,x,x)