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def test_add(self):
uval = np.random.random()
u = NullVector(self.n, uval, dtype=np.float)
w = u + self.v
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(self.val) + np.float(uval))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: y + self.v, u)
w = u + 2
assert(isinstance(w, NullVector))
assert(w.value == uval + 2)
u += 2
assert(u.value == np.float(uval) + 2)
def test_div(self):
uval = np.random.random() + 1 # Ensure nonzero.
u = NullVector(self.n, uval, dtype=np.float)
w = self.v / u
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(self.val) / np.float(uval))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: self.v / y, u)
w = u / 2
assert(isinstance(w, NullVector))
assert(w.value == uval / 2)
u /= 2
assert(u.value == np.float(uval) / 2)
def test_sub(self):
uval = np.random.random()
u = NullVector(self.n, uval, dtype=np.float)
w = u - self.v
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(uval) - np.float(self.val))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: y - self.v, u)
w = u - 2
assert(isinstance(w, NullVector))
assert(w.value == uval - 2)
u -= 2
assert(u.value == np.float(uval) - 2)
z = np.random.random(self.n)
w = z - self.v
assert(isinstance(w, np.ndarray))
assert(len(w) == self.n)
for i in range(self.n):
assert(w[i] == z[i] - self.val)
def test_order(self):
u = NullVector(self.n, self.val, dtype=np.float)
assert_equal(u == self.v, range(self.n))
u = NullVector(self.n, self.val + 1, dtype=np.float)
assert_equal(u == self.v, [])
u = NullVector(self.n + 1, self.val, dtype=np.float)
assert_equal(u == self.v, [])
def test_sub(self):
uval = np.random.random()
u = NullVector(self.n, uval, dtype=np.float)
w = u - self.v
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(uval) - np.float(self.val))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: y - self.v, u)
w = u - 2
assert(isinstance(w, NullVector))
assert(w.value == uval - 2)
u -= 2
assert(u.value == np.float(uval) - 2)
def test_order(self):
u = NullVector(self.n, self.val, dtype=np.float)
assert_equal(u == self.v, range(self.n))
u = NullVector(self.n, self.val + 1, dtype=np.float)
assert_equal(u == self.v, [])
u = NullVector(self.n + 1, self.val, dtype=np.float)
assert_equal(u == self.v, [])
def setUp(self):
self.n = 10
self.val = np.random.random()
self.v = NullVector(self.n, self.val, dtype=np.float)
def test_mul(self):
uval = np.random.random()
u = NullVector(self.n, uval, dtype=np.float)
w = u * self.v
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(self.val) * np.float(uval))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: y * self.v, u)
w = u * 2
assert(isinstance(w, NullVector))
assert(w.value == uval * 2)
u *= 2
assert(u.value == np.float(uval) * 2)
def test_mul(self):
uval = np.random.random()
u = NullVector(self.n, uval, dtype=np.float)
w = u * self.v
assert(isinstance(w, NullVector))
assert(len(w) == self.n)
assert(w.value == np.float(self.val) * np.float(uval))
assert(w.dtype == np.result_type(self.v.dtype, u.dtype))
u = NullVector(self.n + 1, uval, dtype=np.float)
assert_raises(ValueError, lambda y: y * self.v, u)
w = u * 2
assert(isinstance(w, NullVector))
assert(w.value == uval * 2)
u *= 2
assert(u.value == np.float(uval) * 2)
z = np.random.random(self.n)
w = z * self.v
assert(isinstance(w, np.ndarray))
assert(len(w) == self.n)
for i in range(self.n):
assert(w[i] == z[i] * self.val)