本文整理汇总了Python中scipy.interpolate.fitpack2.UnivariateSpline类的典型用法代码示例。如果您正苦于以下问题：Python UnivariateSpline类的具体用法？Python UnivariateSpline怎么用？Python UnivariateSpline使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了UnivariateSpline类的4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_nan
def test_nan(self):
# bail out early if the input data contains nans
x = np.arange(10, dtype=float)
y = x**3
w = np.ones_like(x)
# also test LSQUnivariateSpline [which needs explicit knots]
spl = UnivariateSpline(x, y, check_finite=True)
t = spl.get_knots()[3:4] # interior knots w/ default k=3
y_end = y[-1]
for z in [np.nan, np.inf, -np.inf]:
y[-1] = z
assert_raises(ValueError, UnivariateSpline,
**dict(x=x, y=y, check_finite=True))
assert_raises(ValueError, InterpolatedUnivariateSpline,
**dict(x=x, y=y, check_finite=True))
assert_raises(ValueError, LSQUnivariateSpline,
**dict(x=x, y=y, t=t, check_finite=True))
y[-1] = y_end # check valid y but invalid w
w[-1] = z
assert_raises(ValueError, UnivariateSpline,
**dict(x=x, y=y, w=w, check_finite=True))
assert_raises(ValueError, InterpolatedUnivariateSpline,
**dict(x=x, y=y, w=w, check_finite=True))
assert_raises(ValueError, LSQUnivariateSpline,
**dict(x=x, y=y, t=t, w=w, check_finite=True))示例2: test_linear_1d
def test_linear_1d(self):
x = [1,2,3]
y = [0,2,4]
lut = UnivariateSpline(x,y,k=1)
assert_array_almost_equal(lut.get_knots(),[1,3])
assert_array_almost_equal(lut.get_coeffs(),[0,4])
assert_almost_equal(lut.get_residual(),0.0)
assert_array_almost_equal(lut([1,1.5,2]),[0,1,2])示例3: test_derivative_and_antiderivative
def test_derivative_and_antiderivative(self):
# Thin wrappers to splder/splantider, so light smoke test only.
x = np.linspace(0, 1, 70) ** 3
y = np.cos(x)
spl = UnivariateSpline(x, y, s=0)
spl2 = spl.antiderivative(2).derivative(2)
assert_allclose(spl(0.3), spl2(0.3))
spl2 = spl.antiderivative(1)
assert_allclose(spl2(0.6) - spl2(0.2), spl.integral(0.2, 0.6))示例4: test_increasing_x
def test_increasing_x(self):
xx = np.arange(10, dtype=float)
yy = xx**3
x = np.arange(10, dtype=float)
x[1] = x[0]
y = x**3
w = np.ones_like(x)
# also test LSQUnivariateSpline [which needs explicit knots]
spl = UnivariateSpline(xx, yy, check_finite=True)
t = spl.get_knots()[3:4] # interior knots w/ default k=3
assert_raises(ValueError, UnivariateSpline,
**dict(x=x, y=y, check_finite=True))
assert_raises(ValueError, InterpolatedUnivariateSpline,
**dict(x=x, y=y, check_finite=True))
assert_raises(ValueError, LSQUnivariateSpline,
**dict(x=x, y=y, t=t, w=w, check_finite=True))