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次の JModelica スクリプトを実行しています。

#!/usr/local/jmodelica/bin/jm_python.sh
import pyjmi
op = pyjmi.transfer_optimization_problem("BatchReactor", "model.mop")

opt_opts                                 = op.optimize_options()
opt_opts['n_e']                          = 40 # Number of elements
opt_opts['IPOPT_options']['tol']         = 1e-10
opt_opts['IPOPT_options']['print_level'] = 8
opt_opts['IPOPT_options']['output_file'] = '/z/out'

res = op.optimize(options=opt_opts)

結果 (たとえば、時間、x1、x2 など) がファイルに出力されることを期待していました/z/out。ただし、ファイルには IPOPT の詳細なデバッグ/ステータス情報のみが含まれています。

保存される情報をresファイルに直接出力する方法はありますか? どういうわけかres自体を書くか、できればIPOPT/JModelicaにPythonを使わずに結果を書き込んでもらいますか?

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2 に答える 2

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result_file_nameここで別の回答ごとに使用すると、出力ファイルがわかりにくくなることがあります。

以下は、より適切な形式を生成します。

import StringIO
import numpy as np

def PrintResToFile(filename,result):
  def StripMX(x):
    return str(x).replace('MX(','').replace(')','')

  varstr = '#Variable Name={name: <10}, Unit={unit: <7}, Val={val: <10}, Col={col:< 5}, Comment="{comment}"\n'

  with open(filename,'w') as fout:
    #Print all variables at the top of the file, along with relevant information
    #about them.
    for var in result.model.getAllVariables():
      if not result.is_variable(var.getName()):
        val = result.initial(var.getName())
        col = -1
      else:
        val = "Varies"
        col = result.get_column(var.getName())

      unit = StripMX(var.getUnit())
      if not unit:
        unit = "X"

      fout.write(varstr.format(
        name    = var.getName(),
        unit    = unit,
        val     = val,
        col     = col,
        comment = StripMX(var.getAttribute('comment'))
      ))

    #Ensure that time variable is printed
    fout.write(varstr.format(
      name    = 'time',
      unit    = 's',
      val     = 'Varies',
      col     = 0,
      comment = 'None'
    ))

    #The data matrix contains only time-varying variables. So fetch all of
    #these, couple them in tuples with their column number, sort by column
    #number, and then extract the name of the variable again. This results in a
    #list of variable names which are guaranteed to be in the same order as the
    #data matrix.
    vkeys_in_order = map(lambda x: x[1], sorted([(result.get_column(x),x) for x in result.keys() if result.is_variable(x)]))

    for vk in vkeys_in_order:
      fout.write("{0:>13},".format(vk))
    fout.write("\n")

    sio = StringIO.StringIO()
    np.savetxt(sio, result.data_matrix, delimiter=',', fmt='%13.5f')
    fout.write(sio.getvalue())

次のようになります。

#Variable Name=S0        , Unit=kg     , Val=2.0       , Col=-1   , Comment="Solid Mass"
#Variable Name=F0        , Unit=kg     , Val=0.0       , Col=-1   , Comment="Fluid Mass"
#Variable Name=a         , Unit=Hz     , Val=0.2       , Col=-1   , Comment="None"
#Variable Name=b         , Unit=kg/s   , Val=1.0       , Col=-1   , Comment="None"
#Variable Name=f         , Unit=kg/s   , Val=0.05      , Col=-1   , Comment="None"
#Variable Name=h         , Unit=1/g    , Val=0.05      , Col=-1   , Comment="None"
#Variable Name=der(F)    , Unit=X      , Val=Varies    , Col= 1   , Comment="None"
#Variable Name=F         , Unit=kg     , Val=Varies    , Col= 3   , Comment="None"
#Variable Name=der(S)    , Unit=X      , Val=Varies    , Col= 2   , Comment="None"
#Variable Name=S         , Unit=kg     , Val=Varies    , Col= 4   , Comment="None"
#Variable Name=u         , Unit=X      , Val=Varies    , Col= 5   , Comment="None"
#Variable Name=startTime , Unit=X      , Val=0.0       , Col=-1   , Comment="None"
#Variable Name=finalTime , Unit=X      , Val=100.0     , Col=-1   , Comment="None"
#Variable Name=time      , Unit=s      , Val=Varies    , Col= 0   , Comment="None"
         time,       der(F),       der(S),            F,            S,            u,
      0.00000,      0.97097,     -0.97097,      0.00000,      2.00000,      0.97097
      0.38763,      1.07704,     -1.05814,      0.38519,      1.61698,      1.00000
      1.61237,      0.88350,     -0.80485,      1.70714,      0.35885,      0.65862
      2.50000,      0.00000,      0.09688,      2.14545,      0.00000,      0.00000
      2.88763,      0.09842,     -0.00000,      2.18330,      0.00000,      0.06851
      4.11237,      0.10342,      0.00000,      2.30688,      0.00000,      0.07077
      5.00000,      0.10716,      0.00000,      2.40033,      0.00000,      0.07240
      5.38763,      0.10882,     -0.00000,      2.44219,      0.00000,      0.07311
      6.61237,      0.11421,      0.00000,      2.57875,      0.00000,      0.07535
于 2015-08-16T00:11:20.287 に答える