def test_add_multiple_ndarrays():
a = symbol("a", "5 * 4 * int64")
b = symbol("b", "5 * 4 * float32")
x = np.arange(9, dtype="int64").reshape(3, 3)
y = (x + 1).astype("float32")
expr = sin(a) + 2 * b
scope = {a: x, b: y}
expected = sin(x) + 2 * y
# check that we cast correctly
assert expr.dshape == dshape("5 * 4 * float64")
np.testing.assert_array_equal(compute(expr, scope), expected)
np.testing.assert_array_equal(compute(expr, scope, optimize=False), expected)
def test_add_multiple_ndarrays():
a = symbol('a', '5 * 4 * int64')
b = symbol('b', '5 * 4 * float32')
x = np.arange(9, dtype='int64').reshape(3, 3)
y = (x + 1).astype('float32')
expr = sin(a) + 2 * b
scope = {a: x, b: y}
expected = sin(x) + 2 * y
# check that we cast correctly
assert expr.dshape == dshape('5 * 4 * float64')
np.testing.assert_array_equal(compute(expr, scope), expected)
np.testing.assert_array_equal(compute(expr, scope, optimize=False),
expected)
def test_compound(self):
s = t.amount.mean()
r = compute(s, data)
assert isinstance(r, float)
expr = cos(s) ** 2 + sin(s) ** 2
result = compute(expr, data)
expected = math.cos(r) ** 2 + math.sin(r) ** 2
assert result == expected
def test_compound(self):
s = t.amount.mean()
r = compute(s, data)
assert isinstance(r, float)
expr = cos(s)**2 + sin(s)**2
result = compute(expr, data)
expected = math.cos(r)**2 + math.sin(r)**2
assert result == expected
def test_scalar_arithmetic():
x = symbol('x', 'real')
y = symbol('y', 'real')
assert compute(x + y, {x: 2, y: 3}) == 5
assert compute_up(x + y, 2, 3) == 5
assert compute_up(x * y, 2, 3) == 6
assert compute_up(x / y, 6, 3) == 2
assert compute_up(x % y, 4, 3) == 1
assert compute_up(x ** y, 4, 3) == 64
assert compute(x + 1, {x: 2}) == 3
assert compute(x * 2, {x: 2}) == 4
assert compute(1 + x, {x: 2}) == 3
assert compute(2 * x, {x: 2}) == 4
assert compute_up(-x, 1) == -1
assert compute_up(blaze.sin(x), 1) == math.sin(1)
def test_scalar_arithmetic():
x = Symbol('x', 'real')
y = Symbol('y', 'real')
assert compute(x + y, {x: 2, y: 3}) == 5
assert compute_up(x + y, 2, 3) == 5
assert compute_up(x * y, 2, 3) == 6
assert compute_up(x / y, 6, 3) == 2
assert compute_up(x % y, 4, 3) == 1
assert compute_up(x**y, 4, 3) == 64
assert compute(x + 1, {x: 2}) == 3
assert compute(x * 2, {x: 2}) == 4
assert compute(1 + x, {x: 2}) == 3
assert compute(2 * x, {x: 2}) == 4
assert compute_up(-x, 1) == -1
assert compute_up(blaze.sin(x), 1) == math.sin(1)
def distance(lat1, lon1, lat2, lon2, R=3959):
# http://andrew.hedges.name/experiments/haversine/
dlon = radians(lon2 - lon1)
dlat = radians(lat2 - lat1)
a = sin(dlat / 2.0) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2.0) ** 2
return R * 2 * atan2(sqrt(a), sqrt(1 - a))
def distance(lat1, lon1, lat2, lon2, R=3959):
# http://andrew.hedges.name/experiments/haversine/
dlon = radians(lon2 - lon1)
dlat = radians(lat2 - lat1)
a = sin(dlat / 2.0) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2.0) ** 2
return R * 2 * atan2(sqrt(a), sqrt(1 - a))
def myfunc(x):
return myother((cos(x) + sin(x)) ** 2 / math.pi)
def myfunc(x):
return (cos(x) + sin(x)) ** 2 / math.pi
def myfunc(x):
return myother((cos(x) + sin(x))**2 / math.pi)
def myfunc(x):
return (cos(x) + sin(x))**2 / math.pi
def test_sin(self):
a = blaze.array([0, math.pi/6, math.pi/3, 0.5*math.pi,
math.pi, 1.5*math.pi, 2*math.pi])
b = blaze.array([0, 0.5, 0.5*blaze.sqrt(3), 1, 0, -1, 0])
assert_allclose(blaze.sin(a), b, rtol=1e-15, atol=1e-15)
assert_allclose(blaze.sin(-a), -b, rtol=1e-15, atol=1e-15)