def test_wrapper(self):
P = KroghInterpolator(self.xs, self.ys)
assert_almost_equal(P(self.test_xs), krogh_interpolate(self.xs, self.ys, self.test_xs))
assert_almost_equal(P.derivative(self.test_xs, 2), krogh_interpolate(self.xs, self.ys, self.test_xs, der=2))
assert_almost_equal(
P.derivatives(self.test_xs, 2), krogh_interpolate(self.xs, self.ys, self.test_xs, der=[0, 1])
)
def test_wrapper(self):
P = KroghInterpolator(self.xs, self.ys)
ki = krogh_interpolate
assert_almost_equal(P(self.test_xs), ki(self.xs, self.ys, self.test_xs))
assert_almost_equal(P.derivative(self.test_xs, 2),
ki(self.xs, self.ys, self.test_xs, der=2))
assert_almost_equal(P.derivatives(self.test_xs, 2),
ki(self.xs, self.ys, self.test_xs, der=[0, 1]))
def test_int_inputs(self):
# Check input args are cast correctly to floats, gh-3669
x = [0, 234,468,702,936,1170,1404,2340,3744,6084,8424,13104,60000]
offset_cdf = np.array([-0.95, -0.86114777, -0.8147762, -0.64072425, -0.48002351,
-0.34925329, -0.26503107, -0.13148093, -0.12988833, -0.12979296,
-0.12973574, -0.08582937, 0.05])
f = KroghInterpolator(x, offset_cdf)
assert_allclose(abs((f(x) - offset_cdf) / f.derivative(x, 1)), 0, atol=1e-10)
def test_int_inputs(self):
# Check input args are cast correctly to floats, gh-3669
x = [0, 234,468,702,936,1170,1404,2340,3744,6084,8424,13104,60000]
offset_cdf = np.array([-0.95, -0.86114777, -0.8147762, -0.64072425, -0.48002351,
-0.34925329, -0.26503107, -0.13148093, -0.12988833, -0.12979296,
-0.12973574, -0.08582937, 0.05])
f = KroghInterpolator(x, offset_cdf)
assert_allclose(abs((f(x) - offset_cdf) / f.derivative(x, 1)), 0, atol=1e-10)
def test_high_derivative(self):
P = KroghInterpolator(self.xs,self.ys)
for i in xrange(len(self.xs),2*len(self.xs)):
assert_almost_equal(P.derivative(self.test_xs,i),
np.zeros(len(self.test_xs)))
def test_derivative(self):
P = KroghInterpolator(self.xs,self.ys)
m = 10
r = P.derivatives(self.test_xs,m)
for i in xrange(m):
assert_almost_equal(P.derivative(self.test_xs,i),r[i])
def test_high_derivative(self):
P = KroghInterpolator(self.xs, self.ys)
for i in range(len(self.xs), 2 * len(self.xs)):
assert_almost_equal(P.derivative(self.test_xs, i),
np.zeros(len(self.test_xs)))
def test_derivative(self):
P = KroghInterpolator(self.xs, self.ys)
m = 10
r = P.derivatives(self.test_xs, m)
for i in range(m):
assert_almost_equal(P.derivative(self.test_xs, i), r[i])
