Numpy数值积分的实现

x = np.arange(10)
print(np.sum(x))    # 返回45
print(np.prod(x))   # 返回0

x += 1
x.sum()     # 返回55
x.prod()    # 返回3628800

x = np.arange(10)/np.arange(10)
print(x)
# [nan  1.  1.  1.  1.  1.  1.  1.  1.  1.]

>>> x.sum()
nan
>>> x.prod()
nan

>>> np.nansum(x)
9.0
>>> np.nanprod(x)
1.0

from matplotlib.pyplot as plt
xs = np.arange(100)/10
ys = np.sin(xs)
ys1 = np.cumsum(ys)/10
plt.plot(xs, ys)
plt.plot(xs, ys1)
plt.show()

x = np.arange(1, 10)
print(np.cumprod(x))
# [     1      2      6     24    120    720   5040  40320 362880]

>>> x = np.arange(10)/np.arange(10)
<stdin>:1: RuntimeWarning: invalid value encountered in true_divide
>>> np.cumsum(x)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan])
>>> np.nancumsum(x)
array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])
>>> np.nancumprod(x)
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])

>>> x = np.arange(5)
>>> y = np.cumsum(x)
>>> print(x)
array([0, 1, 2, 3, 4])
>>> print(y)
array([ 0,  1,  3,  6, 10])

>>> np.trapz(x)
8.0

from matplotlib.pyplot as plt
xs = np.arange(100)/10
ys = np.sin(xs)
y1 = np.cumsum(ys)/10
y2 = [np.trapz(ys[:i+1], dx=0.1) for i in range(100)]
plt.plot(xs, y1)
plt.plot(xs, y2)
plt.show()