本文整理汇总了Python中scipy.interpolate.PPoly.from_spline方法的典型用法代码示例。如果您正苦于以下问题：Python PPoly.from_spline方法的具体用法？Python PPoly.from_spline怎么用？Python PPoly.from_spline使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.interpolate.PPoly的用法示例。
在下文中一共展示了PPoly.from_spline方法的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_ppoly
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_ppoly(self):
b = _make_random_spline()
t, c, k = b.tck
pp = PPoly.from_spline((t, c, k))
xx = np.linspace(t[k], t[-k], 100)
assert_allclose(b(xx), pp(xx), atol=1e-14, rtol=1e-14)示例2: test_integrate_ppoly
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_integrate_ppoly(self):
# test .integrate method to be consistent with PPoly.integrate
x = [0, 1, 2, 3, 4]
b = make_interp_spline(x, x)
b.extrapolate = 'periodic'
p = PPoly.from_spline(b)
for x0, x1 in [(-5, 0.5), (0.5, 5), (-4, 13)]:
assert_allclose(b.integrate(x0, x1),
p.integrate(x0, x1))示例3: test_from_spline
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_from_spline(self):
np.random.seed(1234)
x = np.sort(np.r_[0, np.random.rand(11), 1])
y = np.random.rand(len(x))
spl = splrep(x, y, s=0)
pp = PPoly.from_spline(spl)
xi = np.linspace(0, 1, 200)
assert_allclose(pp(xi), splev(xi, spl))示例4: test_roots
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_roots(self):
x = np.linspace(0, 1, 31)**2
y = np.sin(30*x)
spl = splrep(x, y, s=0, k=3)
pp = PPoly.from_spline(spl)
r = pp.roots()
r = r[(r >= 0) & (r <= 1)]
assert_allclose(r, sproot(spl), atol=1e-15)示例5: test_derivative_eval
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_derivative_eval(self):
np.random.seed(1234)
x = np.sort(np.r_[0, np.random.rand(11), 1])
y = np.random.rand(len(x))
spl = splrep(x, y, s=0)
pp = PPoly.from_spline(spl)
xi = np.linspace(0, 1, 200)
for dx in range(0, 3):
assert_allclose(pp(xi, dx), splev(xi, spl, dx))示例6: test_derivative
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_derivative(self):
np.random.seed(1234)
x = np.sort(np.r_[0, np.random.rand(11), 1])
y = np.random.rand(len(x))
spl = splrep(x, y, s=0, k=5)
pp = PPoly.from_spline(spl)
xi = np.linspace(0, 1, 200)
for dx in range(0, 10):
assert_allclose(pp(xi, dx), pp.derivative(dx)(xi),
err_msg="dx=%d" % (dx,))示例7: test_antiderivative_vs_spline
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_antiderivative_vs_spline(self):
np.random.seed(1234)
x = np.sort(np.r_[0, np.random.rand(11), 1])
y = np.random.rand(len(x))
spl = splrep(x, y, s=0, k=5)
pp = PPoly.from_spline(spl)
for dx in range(0, 10):
pp2 = pp.antiderivative(dx)
spl2 = splantider(spl, dx)
xi = np.linspace(0, 1, 200)
assert_allclose(pp2(xi), splev(xi, spl2),
rtol=1e-7)示例8: test_integrate
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_integrate(self):
np.random.seed(1234)
x = np.sort(np.r_[0, np.random.rand(11), 1])
y = np.random.rand(len(x))
spl = splrep(x, y, s=0, k=5)
pp = PPoly.from_spline(spl)
a, b = 0.3, 0.9
ig = pp.integrate(a, b)
ipp = pp.antiderivative()
assert_allclose(ig, ipp(b) - ipp(a))
assert_allclose(ig, splint(a, b, spl))
a, b = -0.3, 0.9
ig = pp.integrate(a, b, extrapolate=True)
assert_allclose(ig, ipp(b) - ipp(a))
assert_(np.isnan(pp.integrate(a, b, extrapolate=False)).all())示例9: test_antiderivative_vs_derivative
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
def test_antiderivative_vs_derivative(self):
np.random.seed(1234)
x = np.linspace(0, 1, 30)**2
y = np.random.rand(len(x))
spl = splrep(x, y, s=0, k=5)
pp = PPoly.from_spline(spl)
for dx in range(0, 10):
ipp = pp.antiderivative(dx)
# check that derivative is inverse op
pp2 = ipp.derivative(dx)
assert_allclose(pp.c, pp2.c)
# check continuity
for k in range(dx):
pp2 = ipp.derivative(k)
r = 1e-13
endpoint = r*pp2.x[:-1] + (1 - r)*pp2.x[1:]
assert_allclose(pp2(pp2.x[1:]), pp2(endpoint),
rtol=1e-7, err_msg="dx=%d k=%d" % (dx, k))示例10: splrep
# 需要导入模块: from scipy.interpolate import PPoly [as 别名]
# 或者: from scipy.interpolate.PPoly import from_spline [as 别名]
from scipy.interpolate import PPoly
from scipy.interpolate import splev, splrep
W = np.array([-2.0, -2.5, -3.7538003, -5.00760061, -5.50760061])
tvec = np.linspace(0, 1, W.shape[0])
W = np.hstack((W[0], W[0], W[:], W[-1] - 0.1, W[-1] - 0.2))
tvec = np.hstack((-0.1, -0.05, tvec, 1.05, 1.1))
tck = splrep(tvec, W, s=0, k=3)
x2 = np.linspace(0, 1, 100)
# x2 = np.linspace(tvec[0], tvec[-1], 100)
y2 = splev(x2, tck)
print splev(0, tck)
print splev(0, tck, der=1)
print splev(1, tck, der=1)
poly = PPoly.from_spline(tck)
dpoly = poly.derivative(1)
ddpoly = poly.derivative(2)
[B, idx] = np.unique(poly.x, return_index=True)
coeff = poly.c[:, idx]
plt.plot(tvec, W, "o", x2, y2)
plt.show()