numpy.trapz()
function integrate along the given axis using the composite trapezoidal rule.
Syntax : numpy.trapz(y, x = None, dx = 1.0, axis = -1)
Parameters :
y : [array_like] Input array to integrate.
x : [array_like, optional] The sample points corresponding to the y values. If x is None, the sample points are assumed to be evenly spaced dx apart. The default is None.
dx : [scalar, optional] The spacing between sample points when x is None. The default is 1.
axis : [int, optional] The axis along which to integrate.Return :
trapz: [float] Definite integral as approximated by trapezoidal rule.
Code #1 :
# Python program explaining # numpy.trapz() function # importing numpy as geek import numpy as geek y = [ 1 , 2 , 3 , 4 ] gfg = geek.trapz( y ) print (gfg) |
Output :
7.5
Code #2 :
# Python program explaining # numpy.trapz() function # importing numpy as geek import numpy as geek y = [ 1 , 2 , 3 , 4 ] x = [ 5 , 6 , 7 , 8 ] gfg = geek.trapz(y, x) print (gfg) |
Output :
7.5
Code #3 :
# Python program explaining # numpy.trapz() function # importing numpy as geek import numpy as geek y = [ 1 , 2 , 3 , 4 ] gfg = geek.trapz(y, dx = 2 ) print (gfg) |
Output :
15.0