more fix to complex type cast and better test.

theano/scalar/basic.py

@@ -175,11 +175,6 @@ class Scalar(Type):
          """
         # todo: use C templating
         return template % dict(nbits = 64, half_nbits = 32, upcast="") + template % dict(nbits = 128, half_nbits = 64, upcast="""
-        complex_type& operator =(npy_float32 y) {
-            this->real=y;
-            this->imag=0;
-            return *this;
-            }
         complex_type& operator =(theano_complex64 y) {
             this->real=y.real;
             this->imag=y.imag;

theano/tensor/tests/test_basic.py

@@ -1921,8 +1921,8 @@ def test_sum_overflow():
     assert f([1]*300) == 300
 
 def test_convert_to_complex():
-    a = value(numpy.ones(3, dtype='complex64'))#+0.5j)
-    b = value(numpy.ones(3, dtype='complex128'))#+0.5j)
+    a = value(numpy.ones(3, dtype='complex64')+0.5j)
+    b = value(numpy.ones(3, dtype='complex128')+0.5j)
 
     f = function([a],basic.convert_to_complex128(a))
 #we need to compare with the same type.
@@ -1935,22 +1935,15 @@ def test_convert_to_complex():
     assert a.type.values_eq_approx(a.data, f(a.data))
 
     #down cast don,t work for now
-#    f = function([b],basic.convert_to_complex64(b))
-#    assert b.type.values_eq_approx(b.data, f(b.data))
+    #f = function([b],basic.convert_to_complex64(b))
+    #assert b.type.values_eq_approx(b.data, f(b.data))
 
     for nbits in (64, 128):
         for t in ['int8','int16','int32','int64','float32','float64']:
             a = value(numpy.ones(3, dtype=t))
-            b = value(numpy.ones(3, dtype=t))
+            b = value(numpy.ones(3, dtype='complex128'))
             f = function([a],basic.convert_to_complex128(a))
-            self.failUnless(a.type.values_eq_approx(a.data, f(a.data)))
-            self.failUnless(b.type.values_eq_approx(b.data, f(b.data)))
-    
-            x=Scalar(t)
-            y=basic.convert_to_complex128(v0)
-            f = function([x],y)
-            assert f(0)==0
-            assert f(1)==1
+            assert a.type.values_eq_approx(b.data, f(a.data))
     
 def test_bug_complext_10_august_09():
     v0 = dmatrix()