我只是想看看这段代码需要多长时间才能执行。这里还有一个类似的问题：
Python 中的 timeit 模块无法识别 numpy 模块
我明白他们在说什么，但我不明白这些代码行应该放在哪里。这是我所拥有的。我知道滚动浏览有点长，但你可以看到我在开头和结尾放置了 timeit 命令的位置。这是行不通的，我猜这是因为我错误地放置了这些代码行。如果我删除 timeit 的东西，代码会起作用。
谢谢
import timeit
u = timeit.Timer("np.arange(1000)", setup = 'import numpy as np')
#set up variables
m = 4.54
g = 9.81
GR = 8
r_pulley = .1
th1=np.pi/4 #based on motor 1 encoder counts. Number of degrees rotated from + x-axis of base frame 0
th2=np.pi/4 #based on motor 2 encoder counts. Number of degrees rotated from + x-axis of m1 frame 1
th3_motor = np.pi/4*12
th3_pulley = th3_motor/GR
#required forces in x,y,z at end effector
fx = 1
fy = 1
fz = m*g #need to figure this out
l1=6
l2=5
l3=th3_pulley*r_pulley
#Build Homogeneous Tranforms Matrices
H1_0 = np.array(([np.cos(th1),-np.sin(th1),0,0],[np.sin(th1),np.cos(th1),0,0],[0,0,1,l3],[0,0,0,1]))
H2_1 = np.array(([np.cos(th2),-np.sin(th2),0,l1],[np.sin(th2),np.cos(th2),0,0],[0,0,1,0],[0,0,0,1]))
H3_2 = np.array(([1,0,0,l2],[0,1,0,0],[0,0,1,0],[0,0,0,1]))
H2_0 = np.dot(H1_0,H2_1)
H3_0 = np.dot(H2_0,H3_2)
print(np.matrix(H3_0))
#These HTMs are using the way I derived them, not the "correct" way.
#The answers are the same, but I think the processing time will be the same.
#This is because either way the two matrices with all the sines and cosines...
#will be the same. Only difference is in one method the ones and zeroes...
#matrix is the first HTM, in the other method it is the last HTM. So its the...
#same number of matrices with the same information, just being dot-producted...
#in a different order.
#Build Jacobian
#np.cross(x, y)
d10 = H1_0[0:3, 3]
d20 = H2_0[0:3, 3]
d30 = H3_0[0:3, 3]
print(d30)
subt1 = d30-d10
subt2 = d30-d20
#tsubt1 = subt1.transpose()
#tsubt2 = subt2.transpose()
#print(tsubt1)
zeroes = np.array(([0,0,1]))
print(subt1)
print(subt2)
cross1 = np.cross(zeroes, subt1)
cross2 = np.cross(zeroes, subt2)
cross1
cross2
#These cross products are correct but need to be tranposed into columns, right now they are a single row.
#tcross1=cross1.reshape(-1,1)
#tcross2=cross2.reshape(-1,1)
#dont actually need these transposes but I didnt want to forget the command.
# build jacobian (J)
#J = np.zeros((6,2))
#J[0:3,0] = cross1
#J[0:3,1] = cross2
#J[3:6,0] = zeroes
#J[3:6,1] = zeroes
#J
#find torques
J_force = np.zeros((2,3))
J_force[0,:]=cross1
J_force[1,:]=cross2
J_force
#build force matrix
forces = np.array(([fx],[fy],[fz]))
forces
torques = np.dot(J_force,forces)
torques #top number is theta 1 (M1) and bottom number is theta 2 (M2)
#need to add z axis?
print(u.timeit())
# u is a timer eval np.arange(1000)
u = timeit.Timer("np.arange(1000)", setup = 'import numpy as np')
# print how many seconds needed to run np.arange(1000) 1000000 times
# 1000000 is the default value, you can set by passing a int here.
print(u.timeit())
所以以下是你想要的。
import timeit
def main():
#set up variables
m = 4.54
g = 9.81
GR = 8
r_pulley = .1
th1=np.pi/4 #based on motor 1 encoder counts. Number of degrees rotated from + x-axis of base frame 0
th2=np.pi/4 #based on motor 2 encoder counts. Number of degrees rotated from + x-axis of m1 frame 1
th3_motor = np.pi/4*12
th3_pulley = th3_motor/GR
#required forces in x,y,z at end effector
fx = 1
fy = 1
fz = m*g #need to figure this out
l1=6
l2=5
l3=th3_pulley*r_pulley
#Build Homogeneous Tranforms Matrices
H1_0 = np.array(([np.cos(th1),-np.sin(th1),0,0],[np.sin(th1),np.cos(th1),0,0],[0,0,1,l3],[0,0,0,1]))
H2_1 = np.array(([np.cos(th2),-np.sin(th2),0,l1],[np.sin(th2),np.cos(th2),0,0],[0,0,1,0],[0,0,0,1]))
H3_2 = np.array(([1,0,0,l2],[0,1,0,0],[0,0,1,0],[0,0,0,1]))
H2_0 = np.dot(H1_0,H2_1)
H3_0 = np.dot(H2_0,H3_2)
print(np.matrix(H3_0))
#These HTMs are using the way I derived them, not the "correct" way.
#The answers are the same, but I think the processing time will be the same.
#This is because either way the two matrices with all the sines and cosines...
#will be the same. Only difference is in one method the ones and zeroes...
#matrix is the first HTM, in the other method it is the last HTM. So its the...
#same number of matrices with the same information, just being dot-producted...
#in a different order.
#Build Jacobian
#np.cross(x, y)
d10 = H1_0[0:3, 3]
d20 = H2_0[0:3, 3]
d30 = H3_0[0:3, 3]
print(d30)
subt1 = d30-d10
subt2 = d30-d20
#tsubt1 = subt1.transpose()
#tsubt2 = subt2.transpose()
#print(tsubt1)
zeroes = np.array(([0,0,1]))
print(subt1)
print(subt2)
cross1 = np.cross(zeroes, subt1)
cross2 = np.cross(zeroes, subt2)
cross1
cross2
#These cross products are correct but need to be tranposed into columns, right now they are a single row.
#tcross1=cross1.reshape(-1,1)
#tcross2=cross2.reshape(-1,1)
#dont actually need these transposes but I didnt want to forget the command.
# build jacobian (J)
#J = np.zeros((6,2))
#J[0:3,0] = cross1
#J[0:3,1] = cross2
#J[3:6,0] = zeroes
#J[3:6,1] = zeroes
#J
#find torques
J_force = np.zeros((2,3))
J_force[0,:]=cross1
J_force[1,:]=cross2
J_force
#build force matrix
forces = np.array(([fx],[fy],[fz]))
forces
torques = np.dot(J_force,forces)
torques #top number is theta 1 (M1) and bottom number is theta 2 (M2)
#need to add z axis?
u = timeit.Timer(main)
print(u.timeit(5))