def test_linear(self):
N = 3000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
new_y = linear(x, y, new_x)
self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
def test_linear(self):
N = 3000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "`linear` is deprecated")
new_y = linear(x, y, new_x)
assert_allclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
def test_linear_interp():
n = 10
x = np.arange(n, dtype=np.float)
y = np.arange(n, dtype=np.float)
new_x = np.arange(n, dtype=np.float) + 0.5
scipy_new_y = linear(x, y, new_x)
np.testing.assert_almost_equal(scipy_new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
for i in range(n - 1):
assert vic_lib.linear_interp(new_x[i], x[i], x[i + 1],
y[i], y[i + 1]) == scipy_new_y[i]
def test_linear(self):
N = 3000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
new_y = linear(x, y, new_x)
self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
def test_linear(self):
N = 3000.
x = arange(N)
y = arange(N)
new_x = arange(N)+0.5
t1 = time.clock()
new_y = linear(x, y, new_x)
t2 = time.clock()
#print "time for linear interpolation with N = %i:" % N, t2 - t1
self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
def test_linear2(self):
N = 3000
x = arange(N, dtype=np.float)
y = ones((100,N)) * arange(N)
new_x = arange(N) + 0.5
new_y = linear(x, y, new_x)
self.assertAllclose(new_y[:5,:5],
[[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5]])
def test_linear2(self):
N = 3000
x = arange(N, dtype=float)
y = ones((100,N)) * arange(N)
new_x = arange(N) + 0.5
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "`linear` is deprecated")
new_y = linear(x, y, new_x)
assert_allclose(new_y[:5,:5],
[[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5]])
def test_linear2(self):
N = 3000
x = arange(N, dtype=float)
y = ones((100,N)) * arange(N)
new_x = arange(N) + 0.5
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "`linear` is deprecated")
new_y = linear(x, y, new_x)
assert_allclose(new_y[:5,:5],
[[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5]])
def test_linear2(self):
N = 3000
x = arange(N, dtype=float)
y = ones((100,N)) * arange(N)
new_x = arange(N) + 0.5
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
new_y = linear(x, y, new_x)
self.assertAllclose(new_y[:5,:5],
[[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5]])
def test_linear2(self):
N = 3000.
x = arange(N)
y = ones((100, N)) * arange(N)
new_x = arange(N) + 0.5
t1 = time.clock()
new_y = linear(x, y, new_x)
t2 = time.clock()
#print "time for 2D linear interpolation with N = %i:" % N, t2 - t1
self.assertAllclose(
new_y[:5, :5],
[[0.5, 1.5, 2.5, 3.5, 4.5], [0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5], [0.5, 1.5, 2.5, 3.5, 4.5],
[0.5, 1.5, 2.5, 3.5, 4.5]])