所以,我自己找到了一个有效的解决方案。不确定它是否是最好的解决方案,但它很实用。
要回答我的问题, scipy.optimize.fsolve 需要一个参数 args =(此处为额外参数)。我把预定的参数放在这里。调用该函数时,首先解析 args 并将 3 个预定值放置在适当的位置。
剩余的 6 个变量在列表中传递,并迭代以填补剩余的空白。由于参数没有改变,每个变量总是被放置在矩阵中的相同位置。
使用这种方法,可以预先确定任意 3 个矩阵元素,并且 fsolve 将尝试确定余数。
fsolve 的调用语句如下所示:
paramSolve1, infodict, ier, mesg = scipy.optimize.fsolve(func,(i,i,i,i,i,i),args = (knownVals[0],knownVals[1],knownVals[2]), full_output = True, warning = False)
knwonVals 是预先确定的参数列表,i 是起始猜测(所有 6 个缺失的参数都得到相同的起始猜测)。full_output 允许返回可选输出,warning = False 关闭未找到解决方案时出现的警告消息。有关更多信息,请查看http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fsolve.html
对于那些感兴趣的人,问题的整个代码如下。
import scipy
from scipy.optimize import fsolve
def func(params, *args):
c = propMatrix(createMatrix(args), params)
ans =(scipy.dot(c[:, 0],c[:, 1]), scipy.dot(c[:, 1],c[:, 2]), scipy.dot(c[:, 0],c[:, 2]),scipy.dot(c[:, 0],c[:, 0])-1,scipy.dot(c[:, 1],c[:, 1])-1,scipy.dot(c[:, 2],c[:, 2])-1)
return ans
def createMatrix(knownVals):
c = [['____', '____', '____'],['____', '____', '____'], ['____', '____', '____']]
for element in knownVals:
x, y, val = element
c[y][x] = float(val)
return c
def propMatrix(c, params):
for p in params:
assign = True
for x in range(3):
for y in range(3):
if c[x][y]=='____' and assign:
c[x][y] = float(p)
assign = False
return scipy.array(c)
def test(c):
v1 = c[:, 0]
v2 = c[:, 1]
v3 = c[:, 2]
h1 = c[0, :]
h2 = c[1, :]
h3 = c[2, :]
ans = (scipy.dot(v1,v1)-1, scipy.dot(v1,v2), scipy.dot(v1, v3), scipy.dot(v2, v2)-1, scipy.dot(v2, v3), scipy.dot(v3,v3)-1, scipy.dot(h1,h1)-1, scipy.dot(h1,h2), scipy.dot(h1, h3), scipy.dot(h2, h2)-1, scipy.dot(h2, h3), scipy.dot(h3,h3)-1)
return ans
def getInput():
knownVals = []
print """\n\nThis module analytically solves for the rotation matrix\n
First, enter 3 known values of the matrix:\n
x
1 2 3
1 | c11 c12 c13 |
y 2 | c21 c22 c23 |
3 | c31 c32 c33 |\n\n"""
for i in range(3):
invalid = True
print "Point Number %i:"%(i)
while invalid:
x = int(raw_input("\tx-coordinate:"))-1
if x>2 or x<0:
print "\tInvalid x-coordinate."
else:
invalid = False
invalid = True
while invalid:
y = int(raw_input("\ty-coordinate:"))-1
if y>2 or y<0:
print "\tInvalid y-coordinate."
else:
invalid = False
invalid = True
while invalid:
val = float(raw_input("\tValue:"))
if val>1 or val<-1:
print "\tInvalid value. Must be -1 <= value <= 1"
else:
invalid = False
knownVals.append((x, y, val))
c = createMatrix(knownVals)
print "Input Matrix:\n\n", scipy.array(c)
choice = raw_input("\nIs this correct (y/n)? ")
if choice == "y":
return knownVals
elif choice == "n":
return getInput()
def Main():
solution = False
knownVals = getInput()
for i in (-1,-.5,0,.5,1):
paramSolve1, infodict, ier, mesg = scipy.optimize.fsolve(func,(i,i,i,i,i,i),args = (knownVals[0],knownVals[1],knownVals[2]), full_output = True, warning = False)
if ier == 1:
print "\nInitial value: %r"%(i)
print propMatrix(createMatrix(knownVals),paramSolve1)
solution = True
if not solution:
print "Could not find a valid solution"
scipy.set_printoptions(precision = 4, suppress = True)
Main()