8000 TST: Add some specific desirable type-promotion use cases to the tests · numpy/numpy@cc55973 · GitHub
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TST: Add some specific desirable type-promotion use cases to the tests
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‎numpy/core/tests/test_numeric.py

Lines changed: 50 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -405,6 +405,10 @@ def check_promotion_cases(self, promote_func):
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assert_equal(promote_func(cld,f64), np.dtype(clongdouble))
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# coercion between scalars and 1-D arrays
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assert_equal(promote_func(array([b]),i8), np.dtype(int8))
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assert_equal(promote_func(array([b]),u8), np.dtype(uint8))
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assert_equal(promote_func(array([b]),i32), np.dtype(int32))
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assert_equal(promote_func(array([b]),u32), np.dtype(uint32))
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assert_equal(promote_func(array([i8]),i64), np.dtype(int8))
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assert_equal(promote_func(u64,array([i32])), np.dtype(int32))
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assert_equal(promote_func(i64,array([u32])), np.dtype(uint32))
@@ -429,7 +433,7 @@ def check_promotion_cases(self, promote_func):
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assert_equal(promote_func(array([u16]), i32), np.dtype(uint16))
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# float and complex are treated as the same "kind" for
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# the purposes of array-scalar promotion, so that you can do
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# (1j * float32array) to get a complex64 array instead of
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# (0j + float32array) to get a complex64 array instead of
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# a complex128 array.
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assert_equal(promote_func(array([f32]),c128), np.dtype(complex64))
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@@ -438,6 +442,51 @@ def res_type(a, b):
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return np.add(a, b).dtype
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self.check_promotion_cases(res_type)
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# Use-case: float/complex scalar * bool/int8 array
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# shouldn't narrow the float/complex type
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for a in [np.array([True,False]), np.array([-3,12], dtype=np.int8)]:
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b = 1.234 * a
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assert_equal(b.dtype, np.dtype('f8'), "array type %s" % a.dtype)
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b = np.longdouble(1.234) * a
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assert_equal(b.dtype, np.dtype(np.longdouble),
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"array type %s" % a.dtype)
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b = np.float64(1.234) * a
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assert_equal(b.dtype, np.dtype('f8'), "array type %s" % a.dtype)
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b = np.float32(1.234) * a
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assert_equal(b.dtype, np.dtype('f4'), "array type %s" % a.dtype)
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b = np.float16(1.234) * a
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assert_equal(b.dtype, np.dtype('f2'), "array type %s" % a.dtype)
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b = 1.234j * a
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assert_equal(b.dtype, np.dtype('c16'), "array type %s" % a.dtype)
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b = np.clongdouble(1.234j) * a
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assert_equal(b.dtype, np.dtype(np.clongdouble),
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"array type %s" % a.dtype)
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b = np.complex128(1.234j) * a
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assert_equal(b.dtype, np.dtype('c16'), "array type %s" % a.dtype)
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b = np.complex64(1.234j) * a
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assert_equal(b.dtype, np.dtype('c8'), "array type %s" % a.dtype)
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# The following use-case is problematic, and to resolve its
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# tricky side-effects requires more changes.
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#
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## Use-case: (1-t)*a, where 't' is a boolean array and 'a' is
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## a float32, shouldn't promote to float64
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#a = np.array([1.0, 1.5], dtype=np.float32)
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#t = np.array([True, False])
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#b = t*a
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#assert_equal(b, [1.0, 0.0])
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#assert_equal(b.dtype, np.dtype('f4'))
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#b = (1-t)*a
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#assert_equal(b, [0.0, 1.5])
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#assert_equal(b.dtype, np.dtype('f4'))
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## Probably ~t (bitwise negation) is more proper to use here,
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## but this is arguably less intuitive to understand at a glance, and
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## would fail if 't' is actually an integer array instead of boolean:
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#b = (~t)*a
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#assert_equal(b, [0.0, 1.5])
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#assert_equal(b.dtype, np.dtype('f4'))
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def test_result_type(self):
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self.check_promotion_cases(np.result_type)
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