1

我正在尝试将数组的行连接nxm到单个组件中的数组，或者将1xm数组的切片n连接到单个组件中的1xn*m数组。然后将原始或数组用作优化参数。问题是当我这样做时，程序集似乎有一些严重的问题。我要么得到明显错误的答案，要么得到尺寸不匹配的错误。1xmnnxm1xn*m

我已经能够通过使用 传入n 1xm数组来使程序集工作exec()，但我更喜欢前面解释的方法。如果有人能告诉我如何以适当的方式完成这项工作，我将不胜感激。

我提供了一个简化的代码示例，说明什么是有效的，什么是我想做的。首先显示我想使用的方法，然后显示我已经开始工作但严重不喜欢的方法。

我想做的事

    from openmdao.main.api import Assembly, Component
    from openmdao.lib.datatypes.api import Float, Array, List
    from openmdao.lib.drivers.api import DOEdriver, SLSQPdriver, COBYLAdriver, CaseIteratorDriver
    from pyopt_driver.pyopt_driver import pyOptDriver

    import numpy as np


    class component1(Component):

        x = Float(iotype='in')
        y = Float(iotype='in')
        term1 = Float(iotype='out')
        a = Float(iotype='in', default_value=1)
        def execute(self):
            x = self.x
            a = self.a

            term1 = a*x**2
            self.term1 = term1

            print "In comp1", self.name, self.a, self.x, self.term1

        def list_deriv_vars(self):
            return ('x',), ('term1',)

        def provideJ(self):

            x = self.x
            a = self.a
            dterm1_dx = 2.*a*x

            J = np.array([[dterm1_dx]])
            print 'In comp1, J = %s' % J

            return J


    class component2(Component):

        x = Float(iotype='in')
        y = Float(iotype='in')
        term1 = Float(iotype='in')
        f = Float(iotype='out')
        q = Array(np.zeros(2), iotype='in', dtype='float')

        def execute(self):

            y = self.y + self.q[0]
            x = self.x + self.q[1]
            term1 = self.term1
            f = term1 + x + y**2
            print 'q = %s' % self.q
            self.f = f
            print "In comp2", self.name, self.x, self.y, self.term1, self.f



    class summer(Component):


        total = Float(iotype='out', desc='sum of all f values')

        def __init__(self, size):
            super(summer, self).__init__()
            self.size = size

            self.add('fs', Array(np.zeros(size), iotype='in', desc='f values from all cases'))

        def execute(self):
            self.total = sum(self.fs)
            print 'In summer, fs = %s and total = %s' % (self.fs, self.total)


    class assembly(Assembly):

        x = Float(iotype='in')
        y = Float(iotype='in')
        total = Float(iotype='out')

        def __init__(self, size):

            super(assembly, self).__init__()

            self.size = size

            self.add('a_vals', Array(np.zeros(size), iotype='in', dtype='float'))
            self.add('q', Array(np.zeros((size, 2)), iotype='in', dtype='float'))
            self.add('fs', Array(np.zeros(size), iotype='out', dtype='float'))

            print 'in init a_vals = %s, fs = %s' % (self.a_vals, self.fs)


        def configure(self):

            self.add('driver', SLSQPdriver())
            # self.add('driver', pyOptDriver())
            # self.driver.optimizer = 'SNOPT'
            # self.driver.pyopt_diff = True

            #create this first, so we can connect to it
            self.add('summer', summer(size=len(self.a_vals)))
            self.connect('summer.total', 'total')

            print 'in configure a_vals = %s' % self.a_vals

            # create instances of components
            for i in range(0, self.size):
                c1 = self.add('comp1_%d' % i, component1())
                c1.missing_deriv_policy = 'assume_zero'

                c2 = self.add('comp2_%d'%i, component2())
                self.connect('a_vals[%d]' % i, 'comp1_%d.a' % i)
                self.connect('x', ['comp1_%d.x' % i, 'comp2_%d.x' % i])
                self.connect('y', ['comp1_%d.y' % i, 'comp2_%d.y' % i])
                self.connect('comp1_%d.term1' % i, 'comp2_%d.term1' % i)
                self.connect('q[%d, :]' % i, 'comp2_%d.q' % i)
                self.connect('comp2_%d.f' % i, 'summer.fs[%d]' % i)

                self.driver.workflow.add(['comp1_%d' % i, 'comp2_%d' % i])

            # self.connect('summer.fs[:]', 'fs[:]')
            self.driver.workflow.add(['summer'])

            # set up main driver (optimizer)
            self.driver.iprint = 1
            self.driver.maxiter = 100
            self.driver.accuracy = 1.0e-6
            self.driver.add_parameter('x', low=-5., high=5.)
            self.driver.add_parameter('y', low=-5., high=5.)
            self.driver.add_parameter('q', low=0., high=5.)
            self.driver.add_objective('summer.total')


    if __name__ == "__main__":
        """ the result should be -1 at (x, y) = (-0.5, 0) """

        import time
        from openmdao.main.api import set_as_top
        a_vals = np.array([1., 1., 1., 1.])
        test = set_as_top(assembly(size=len(a_vals)))
        test.a_vals = a_vals
        print 'in main, test.a_vals = %s, test.fs = %s' % (test.a_vals, test.fs)
        test.x = 2.
        test.y = -5
        test.q = np.tile(np.arange(0., 2.), (4, 1))
        print test.q

        tt = time.time()
        test.run()

        print "Elapsed time: ", time.time()-tt, "seconds"

        print 'result = ', test.summer.total
        print '(x, y) = (%s, %s)' % (test.x, test.y)
        print 'fs = %s' % test.fs
        print test.fs

----------

什么有效

from openmdao.main.api import Assembly, Component
from openmdao.lib.datatypes.api import Float, Array, List
from openmdao.lib.drivers.api import DOEdriver, SLSQPdriver, COBYLAdriver, CaseIteratorDriver
from pyopt_driver.pyopt_driver import pyOptDriver

import numpy as np


class component1(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='out')
    a = Float(iotype='in', default_value=1)

    def execute(self):
        x = self.x
        a = self.a

        term1 = a*x**2
        self.term1 = term1

        print "In comp1", self.name, self.a, self.x, self.term1

    def list_deriv_vars(self):
        return ('x',), ('term1',)

    def provideJ(self):

        x = self.x
        a = self.a
        dterm1_dx = 2.*a*x

        J = np.array([[dterm1_dx]])
        # print 'In comp1, J = %s' % J

        return J


class component2(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='in')
    f = Float(iotype='out')
    q = Array(np.zeros(2), iotype='in', dtype='float')

    def execute(self):

        y = self.y + self.q[0]
        x = self.x + self.q[1]
        term1 = self.term1
        f = term1 + x + y**2
        print 'in comp2 q = %s' % self.q
        self.f = f
        print "In comp2", self.name, self.x, self.y, self.term1, self.f



class summer(Component):


    total = Float(iotype='out', desc='sum of all f values')

    def __init__(self, size):
        super(summer, self).__init__()
        self.size = size

        self.add('fs', Array(np.zeros(size), iotype='in', desc='f values from all cases'))

    def execute(self):
        self.total = sum(self.fs)
        print 'In summer, fs = %s and total = %s' % (self.fs, self.total)


class assembly(Assembly):

    x = Float(iotype='in')
    y = Float(iotype='in')
    total = Float(iotype='out')

    def __init__(self, size):

        super(assembly, self).__init__()

        self.size = size

        self.add('a_vals', Array(np.zeros(size), iotype='in', dtype='float'))

        self.add('fs', Array(np.zeros(size), iotype='out', dtype='float'))

        for i in range(0, size):
            self.add('q_%d' % i, Array(np.zeros(2), iotype='in', dtype='float'))

        print 'in init a_vals = %s, fs = %s' % (self.a_vals, self.fs)

    def configure(self):

        # self.add('driver', SLSQPdriver())
        self.add('driver', pyOptDriver())
        self.driver.optimizer = 'SNOPT'
        # self.driver.pyopt_diff = True

        #create this first, so we can connect to it
        self.add('summer', summer(size=len(self.a_vals)))
        self.connect('summer.total', 'total')

        print 'in configure a_vals = %s' % self.a_vals
        # print 'in configure q = %s' % self.q


        # create instances of components
        for i in range(0, self.size):
            c1 = self.add('comp1_%d' % i, component1())
            c1.missing_deriv_policy = 'assume_zero'

            c2 = self.add('comp2_%d'%i, component2())
            self.connect('a_vals[%d]' % i, 'comp1_%d.a' % i)
            self.connect('x', ['comp1_%d.x' % i, 'comp2_%d.x' % i])
            self.connect('y', ['comp1_%d.y' % i, 'comp2_%d.y' % i])
            self.connect('comp1_%d.term1' % i, 'comp2_%d.term1' % i)
            self.connect('q_%d' % i, 'comp2_%d.q' % i)

            self.connect('comp2_%d.f' % i, 'summer.fs[%d]' % i)

            self.driver.workflow.add(['comp1_%d' % i, 'comp2_%d' % i])

        # self.connect('summer.fs[:]', 'fs[:]')
        self.driver.workflow.add(['summer'])

        # set up main driver (optimizer)
        self.driver.iprint = 1
        self.driver.maxiter = 100
        self.driver.accuracy = 1.0e-6
        self.driver.add_parameter('x', low=-5., high=5.)
        self.driver.add_parameter('y', low=0., high=5.)
        for i in range(0, self.size):
            self.driver.add_parameter('q_%d' % i, low=0., high=5.)
        self.driver.add_objective('summer.total')


if __name__ == "__main__":
    """ the result should be -1 at (x, y) = (-0.5, 0) """

    import time
    from openmdao.main.api import set_as_top
    a_vals = np.array([1., 1., 1., 1.])
    test = set_as_top(assembly(size=len(a_vals)))
    test.a_vals = a_vals
    print 'in main, test.a_vals = %s, test.fs = %s' % (test.a_vals, test.fs)
    test.x = 2.
    test.y = -5
    q = np.tile(np.arange(1., 3.), (4, 1))
    for i in range(0, len(a_vals)):
        exec('test.q_%d = q[%d]' % (i, i))
        exec('print test.q_%d' % i)
        print test.q_0, test.q_1, test.q_2, test.q_3

    tt = time.time()
    test.run()

    print "Elapsed time: ", time.time()-tt, "seconds"

    print 'result = ', test.summer.total
    print '(x, y) = (%s, %s)' % (test.x, test.y)
    print 'fs = %s' % test.fs
    print test.fs
    for i in range(0, len(a_vals)):
        exec('print test.q_%d' % i)
4

2 回答 2

1

我可以通过对 q 到 comp2_.q 的连接进行小的更改来克服设置错误。

我来自：

self.connect('q[%d, :]' % i, 'comp2_%d.q' % i)

到：

self.connect('q[%d]' % i, 'comp2_%d.q' % i)

然后问题贯穿其第一次评估。不幸的是，它在导数计算中的某个地方。即使我打开 SNOPT 并使用 pyopt_diff=True，也会发生这种情况。所以这个玩具问题中的其他东西是不对的。但是删除额外的:内容可以让您摆脱连接错误。

于 2015-08-08T12:40:26.933 回答
1

所以，我也看了你的模型，你肯定没有做错什么。在为顶级优化问题组装网络图时，模型设置中存在错误。它似乎q从输入中丢失了变量，并且从未在用于求解总导数的向量中为其分配空间。我认为它很困惑，q因为它与任何东西都没有直接的完全连接，只是将连接切片到编号的comp2s.

您的第一个解决方法可能是最好的解决方法。不过，我也找到了另一个。我创建了一个名为fakefake; q这个组件除了让你直接将完整的向量连接到某个东西之外什么都不做。然后，我获取了它的输出fakefake.out并在约束中使用它。由于该输出永远不会改变，因此始终满足约束。此解决方法有效，因为完整q连接可防止在修剪期间将输入错误地从图中删除。

通过这些更改，我能够让它运行。我不确定答案是否正确，因为我不知道它们应该是什么。我在下面包含了我的代码。请注意，我还添加了component2和的导数summer。

from openmdao.main.api import Assembly, Component
from openmdao.lib.datatypes.api import Float, Array, List
from openmdao.lib.drivers.api import DOEdriver, SLSQPdriver, COBYLAdriver, CaseIteratorDriver
from pyopt_driver.pyopt_driver import pyOptDriver

import numpy as np


class component1(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='out')
    a = Float(iotype='in', default_value=1)
    def execute(self):
        x = self.x
        a = self.a

        term1 = a*x**2
        self.term1 = term1

        print "In comp1", self.name, self.a, self.x, self.term1

    def list_deriv_vars(self):
        return ('x',), ('term1',)

    def provideJ(self):

        x = self.x
        a = self.a
        dterm1_dx = 2.*a*x

        J = np.array([[dterm1_dx]])
        print 'In comp1, J = %s' % J

        return J


class component2(Component):

    x = Float(iotype='in')
    y = Float(iotype='in')
    term1 = Float(iotype='in')
    q = Array(np.zeros(2), iotype='in', dtype='float')

    f = Float(iotype='out')

    def execute(self):

        y = self.y + self.q[0]
        x = self.x + self.q[1]
        term1 = self.term1
        f = term1 + x + y**2
        print 'q = %s' % self.q
        self.f = f
        print "In comp2", self.name, self.x, self.y, self.term1, self.f

    def list_deriv_vars(self):
        return ('x', 'y', 'term1', 'q'), ('f',)

    def provideJ(self):
        # f = (y+q0)**2 + x + q1 + term1

        df_dx = 1.0
        df_dy = 2.0*self.y + 2.0*self.q[0]
        df_dterm1 = 1.0
        df_dq = np.array([2.0*self.q[0] + 2.0*self.y, 1.0])

        J = np.array([[df_dx, df_dy, df_dterm1, df_dq[0], df_dq[1]]])
        return J

class summer(Component):


    total = Float(iotype='out', desc='sum of all f values')

    def __init__(self, size):
        super(summer, self).__init__()
        self.size = size

        self.add('fs', Array(np.zeros(size), iotype='in', desc='f values from all cases'))

    def execute(self):
        self.total = sum(self.fs)
        print 'In summer, fs = %s and total = %s' % (self.fs, self.total)

    def list_deriv_vars(self):
        return ('fs',), ('total',)

    def provideJ(self):
        J = np.ones((1.0, len(self.fs)))
        return J

class fakefake(Component):

    out = Float(0.0, iotype='out')

    def __init__(self, size):
        super(fakefake, self).__init__()

        self.size = size
        self.add('q', Array(np.zeros(size), iotype='in', dtype='float'))

    def execute(self):
        pass

    def list_deriv_vars(self):
        return ('q',), ('out',)

    def provideJ(self):
        J = np.zeros((1.0, 2.0*len(self.q)))
        return J

class assembly(Assembly):

    x = Float(iotype='in')
    y = Float(iotype='in')
    total = Float(iotype='out')

    def __init__(self, size):

        super(assembly, self).__init__()

        self.size = size

        self.add('a_vals', Array(np.zeros(size), iotype='in', dtype='float'))
        self.add('q', Array(np.zeros((size, 2)), iotype='in', dtype='float'))
        self.add('fs', Array(np.zeros(size), iotype='out', dtype='float'))

        print 'in init a_vals = %s, fs = %s' % (self.a_vals, self.fs)


    def configure(self):

        self.add('driver', SLSQPdriver())
        # self.add('driver', pyOptDriver())
        # self.driver.optimizer = 'SNOPT'
        # self.driver.pyopt_diff = True

        #create this first, so we can connect to it
        self.add('summer', summer(size=len(self.a_vals)))
        self.connect('summer.total', 'total')

        # Trying something...
        self.add('fakefake', fakefake(self.size))
        self.connect('q', 'fakefake.q')

        print 'in configure a_vals = %s' % self.a_vals

        # create instances of components

        for i in range(0, self.size):
            c1 = self.add('comp1_%d' % i, component1())
            c1.missing_deriv_policy = 'assume_zero'

            c2 = self.add('comp2_%d'%i, component2())
            self.connect('a_vals[%d]' % i, 'comp1_%d.a' % i)
            self.connect('x', ['comp1_%d.x' % i, 'comp2_%d.x' % i])
            self.connect('y', ['comp1_%d.y' % i, 'comp2_%d.y' % i])
            self.connect('comp1_%d.term1' % i, 'comp2_%d.term1' % i)
            #self.connect('q[%d, :]' % i, 'comp2_%d.q' % i)
            #self.connect('q[%d]' % i, 'comp2_%d.q' % i)
            self.connect('comp2_%d.f' % i, 'summer.fs[%d]' % i)

            self.driver.workflow.add(['comp1_%d' % i, 'comp2_%d' % i])

        # self.connect('summer.fs[:]', 'fs[:]')
        self.driver.workflow.add(['summer'])

        # set up main driver (optimizer)
        self.driver.iprint = 1
        self.driver.maxiter = 100
        self.driver.accuracy = 1.0e-6
        self.driver.add_parameter('x', low=-5., high=5.)
        self.driver.add_parameter('y', low=-5., high=5.)
        self.driver.add_parameter('q', low=0., high=5.)
        #for i in range(0, self.size):
        #    self.driver.add_parameter('comp2_%d.q' % i, low=0., high=5.)
        self.driver.add_objective('summer.total')
        self.driver.add_constraint('fakefake.out < 1000')


if __name__ == "__main__":
    """ the result should be -1 at (x, y) = (-0.5, 0) """

    import time
    from openmdao.main.api import set_as_top
    a_vals = np.array([1., 1., 1., 1.])
    test = set_as_top(assembly(size=len(a_vals)))
    test.a_vals = a_vals
    print 'in main, test.a_vals = %s, test.fs = %s' % (test.a_vals, test.fs)
    test.x = 2.
    test.y = -5
    test.q = np.tile(np.arange(0., 2.), (4, 1))
    print test.q

    tt = time.time()
    test.run()

    print "Elapsed time: ", time.time()-tt, "seconds"

    print 'result = ', test.summer.total
    print '(x, y) = (%s, %s)' % (test.x, test.y)
    print 'fs = %s' % test.fs
    print test.fs
于 2015-08-12T17:16:33.020 回答