コード例 #1
0
ファイル: probe.py プロジェクト: reedessick/nmodelte
        print "decomposing network into generations"
    gens, coups = network.gens()

    # =================================================
    ### define subsets of modes
    # =================================================

    ### pull apart by number of couplings
    if opts.verbose:
        print "separating modes by num_k:"
    num_k_modeNos = {}
    for num_k in opts.num_k:
        if opts.verbose:
            print "\tnum_k:", num_k
        num_k_modeNos[num_k] = [
            [network.modeNoD[nlms] for nlms in _] for _ in pn.downselect_num_k(num_k, network, mode_nums=None)
        ]

        ### pull apart by Ethr
    if opts.verbose:
        print "separating modes by Ethr:"
    ethr_modeNos = {}
    for ethr in opts.Ethr:
        if opts.verbose:
            print "\tEthr:", ethr
        ethr_modeNos[ethr] = [
            [network.modeNoD[nlms] for nlms in _] for _ in pn.downselect_Ethr(ethr, system, freqs=None, mode_nums=None)
        ]

        ### pull apart by collE
    if opts.verbose:
コード例 #2
0
ファイル: nmode_b.py プロジェクト: reedessick/nmodelte
def new_parent_selection(config, system, q=False, verbose=False):
  """
  takes the config file and selects new parents based on the criteria therein
  returns [(O,mode), ...]
  """
#  selection = dict( config.items("parents") )
  selection = dict( [(key.lower(),value) for key, value in config.items("parents")] )
  network = system.network
  freqs = system.compute_3mode_freqs()

  if verbose: print "selection : ", selection

  ### modeNos
  if selection.has_key("modeNos".lower()):
    if verbose: print "selecting parents based on modeNo"
    modeNos = [int(l) for l in selection["modeNos".lower()].strip().split()]
  else:
    modeNos = range(len(network))

  ### genNos
  if selection.has_key("genNos".lower()):
    _modeNos = []
    if verbose: print "selecting parents based on genNo"
    gens,_ = network.gens()
    for genNo in [int(l) for l in selection['genNos'.lower()].split()]:
      for modeNo in gens[genNo]:
        if modeNo in modeNos:
          _modeNos.append( modeNo )
    modeNos = _modeNos

  ### l
  has_min = selection.has_key("min_l".lower())
  has_max = selection.has_key("max_l".lower())
  if has_min or has_max:
    if verbose: print "selecting parents based on l"
    _modeNos = []
    for modeNo in modeNos:
      l = network.modes[modeNo].l
      if (not has_min) or (has_min and (l >= int(selection["min_l".lower()]))):
        if (not has_max) or (has_max and (l <= int(selection["max_l".lower()]))):
          _modeNos.append( modeNo )
    modeNos = _modeNos

  ### frac_Oorb
  has_min = selection.has_key("min_frac_Oorb".lower())
  has_max = selection.has_key("max_frac_Oorb".lower())
  if has_min or has_max:
    if verbose: print "selecting parents based on frac_Oorb"
    _modeNos = []
    for modeNo in modeNos:
      absO_Oorb = abs(freqs[modeNo]/system.Oorb)
      if (not has_min) or (has_min and (absO_Oorb >= float(selection["min_frac_Oorb".lower()]))):
        if (not has_max) or (has_max and (absO_Oorb <= float(selection["max_frac_Oorb".lower()]))):
          _modeNos.append( modeNo )
    modeNos = _modeNos

  ### Amean
  if selection.has_key("min_Amean".lower()):
    if verbose: print "selecting parents based on min_Amean"
    keep, _ = pn.downselect_Amean(q, float(selection["min_Amean".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_Amean"):
    if verbose: print "selecting parents based on max_Amean"
    _, keep = pn.downselect_Amean(q, float(selection["max_Amean".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
    
  ### Alast
  if selection.has_key("min_Alast".lower()):
    if verbose: print "selecting parents based on min_Alast"
    keep, _ = pn.downselect_Alast(q, float(selection["min_Alast".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_Alast"):
    if verbose: print "selecting parents based on max_Alast"
    _, keep = pn.downselect_Alast(q, float(selection["max_Alast".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  ### Afit
  if selection.has_key("min_Afit".lower()):
    if verbose: print "selecting parents based on min_Afit"
    keep, _ = pn.downselect_Afit(q, float(selection["min_Afit".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_Afit"):
    if verbose: print "selecting parents based on max_Afit"
    _, keep = pn.downselect_Afit(q, float(selection["max_Afit".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  ### num_k
  if selection.has_key("min_num_k".lower()):
    if verbose: print "selecting parents based on min_num_k"
    keep, _ = pn.downselect_num_k(q, float(selection["min_num_k".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_num_k"):
    if verbose: print "selecting parents based on max_num_k"
    _, keep = pn.downselect_num_k(q, float(selection["max_num_k".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  ### min_heuristic
  if selection.has_key("min_heuristic".lower()):
    if verbose: print "selecting parents based on min_heuristic"
    keep, _ = pn.downselect_min_heuristic(q, float(selection["min_heuristic".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_heuristic"):
    if verbose: print "selecting parents based on max_heuristic"
    _, keep = pn.downselect_min_heuristic(q, float(selection["max_heuristic".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  ### min_Ethr
  if selection.has_key("min_Ethr".lower()):
    if verbose: print "selecting parents based on min_Ethr"
    keep, _ = pn.downselect_min_Ethr(q, float(selection["min_Ethr".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_Ethr"):
    if verbose: print "selecting parents based on max_Ethr"
    _, keep = pn.downselect_min_Ethr(q, float(selection["max_Ethr".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  ### collE
  if selection.has_key("min_collE".lower()):
    if verbose: print "selecting parents based on min_collE"
    keep, _ = pn.downselect_collE(q, float(selection["min_collE".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]
  if selection.has_key("max_collE"):
    if verbose: print "selecting parents based on max_collE"
    _, keep = pn.downselect_collE(q, float(selection["max_collE".lower()]), network, mode_nums=modeNos)
    modeNos = [network.modeNoD[nlms] for nlms in keep]

  return [(freqs[modeNo], network.modes[modeNo]) for modeNo in sorted(modeNos)]