comparison main_macros.xml @ 11:e4ab6b0bdf37 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit b1e5fa3170484d2cc3396f2abe99bb8cfcfa9c65

10:38df89cbed19

  )
  y=y.ravel()
  return X, y
  </token>

  <token name="@GET_SEARCH_PARAMS_FUNCTION@">
def get_search_params(params_builder):
  search_params = {}

  def safe_eval(literal):

    FROM_SCIPY_STATS = [  'bernoulli', 'binom', 'boltzmann', 'dlaplace', 'geom', 'hypergeom',
                          'logser', 'nbinom', 'planck', 'poisson', 'randint', 'skellam', 'zipf' ]

    FROM_NUMPY_RANDOM = [ 'beta', 'binomial', 'bytes', 'chisquare', 'choice', 'dirichlet', 'division',
                          'exponential', 'f', 'gamma', 'geometric', 'gumbel', 'hypergeometric',
                          'laplace', 'logistic', 'lognormal', 'logseries', 'mtrand', 'multinomial',
                          'multivariate_normal', 'negative_binomial', 'noncentral_chisquare', 'noncentral_f',
                          'normal', 'pareto', 'permutation', 'poisson', 'power', 'rand', 'randint',
                          'randn', 'random', 'random_integers', 'random_sample', 'ranf', 'rayleigh',
                          'sample', 'seed', 'set_state', 'shuffle', 'standard_cauchy', 'standard_exponential',
                          'standard_gamma', 'standard_normal', 'standard_t', 'triangular', 'uniform',
                          'vonmises', 'wald', 'weibull', 'zipf' ]

    # File opening and other unneeded functions could be dropped
    UNWANTED = ['open', 'type', 'dir', 'id', 'str', 'repr']

    # Allowed symbol table. Add more if needed.
    new_syms = {
      'np_arange': getattr(np, 'arange'),
      'ensemble_ExtraTreesClassifier': getattr(ensemble, 'ExtraTreesClassifier')
    }

    syms = make_symbol_table(use_numpy=False, **new_syms)

    for method in FROM_SCIPY_STATS:
      syms['scipy_stats_' + method] = getattr(scipy.stats, method)

    for func in FROM_NUMPY_RANDOM:
      syms['np_random_' + func] = getattr(np.random, func)

    for key in UNWANTED:
      syms.pop(key, None)

    aeval = Interpreter(symtable=syms, use_numpy=False, minimal=False,
                      no_if=True, no_for=True, no_while=True, no_try=True,
                      no_functiondef=True, no_ifexp=True, no_listcomp=False,
                      no_augassign=False, no_assert=True, no_delete=True,
                      no_raise=True, no_print=True)

    return aeval(literal)

  for p in params_builder['param_set']:
    search_p = p['search_param_selector']['search_p']
    if search_p.strip() == '':
      continue

    except ValueError:
      sys.exit("Unsupported parameter input: `%s`" %estimator_params)
    estimator.set_params(**params)

  return estimator
  </token>

  <xml name="python_requirements">
      <requirements>
          <requirement type="package" version="2.7">python</requirement>

      </when>
    </conditional>
  </xml>

  <xml name="model_validation_common_options">
    <param argument="cv" type="integer" value="" optional="true" label="cv" help="The number of folds in a (Stratified)KFold" />
    <expand macro="n_jobs"/>
    <expand macro="verbose"/>
    <yield/>
  </xml>

11:e4ab6b0bdf37

  )
  y=y.ravel()
  return X, y
  </token>

  <token name="@SAFE_EVAL_FUNCTION@">
def safe_eval(literal):

  FROM_SCIPY_STATS = [  'bernoulli', 'binom', 'boltzmann', 'dlaplace', 'geom', 'hypergeom',
                        'logser', 'nbinom', 'planck', 'poisson', 'randint', 'skellam', 'zipf' ]

  FROM_NUMPY_RANDOM = [ 'beta', 'binomial', 'bytes', 'chisquare', 'choice', 'dirichlet', 'division',
                        'exponential', 'f', 'gamma', 'geometric', 'gumbel', 'hypergeometric',
                        'laplace', 'logistic', 'lognormal', 'logseries', 'mtrand', 'multinomial',
                        'multivariate_normal', 'negative_binomial', 'noncentral_chisquare', 'noncentral_f',
                        'normal', 'pareto', 'permutation', 'poisson', 'power', 'rand', 'randint',
                        'randn', 'random', 'random_integers', 'random_sample', 'ranf', 'rayleigh',
                        'sample', 'seed', 'set_state', 'shuffle', 'standard_cauchy', 'standard_exponential',
                        'standard_gamma', 'standard_normal', 'standard_t', 'triangular', 'uniform',
                        'vonmises', 'wald', 'weibull', 'zipf' ]

  # File opening and other unneeded functions could be dropped
  UNWANTED = ['open', 'type', 'dir', 'id', 'str', 'repr']

  # Allowed symbol table. Add more if needed.
  new_syms = {
    'np_arange': getattr(np, 'arange'),
    'ensemble_ExtraTreesClassifier': getattr(ensemble, 'ExtraTreesClassifier')
  }

  syms = make_symbol_table(use_numpy=False, **new_syms)

  for method in FROM_SCIPY_STATS:
    syms['scipy_stats_' + method] = getattr(scipy.stats, method)

  for func in FROM_NUMPY_RANDOM:
    syms['np_random_' + func] = getattr(np.random, func)

  for key in UNWANTED:
    syms.pop(key, None)

  aeval = Interpreter(symtable=syms, use_numpy=False, minimal=False,
                    no_if=True, no_for=True, no_while=True, no_try=True,
                    no_functiondef=True, no_ifexp=True, no_listcomp=False,
                    no_augassign=False, no_assert=True, no_delete=True,
                    no_raise=True, no_print=True)

  return aeval(literal)
  </token>

  <token name="@GET_SEARCH_PARAMS_FUNCTION@">
def get_search_params(params_builder):
  search_params = {}

  for p in params_builder['param_set']:
    search_p = p['search_param_selector']['search_p']
    if search_p.strip() == '':
      continue

    except ValueError:
      sys.exit("Unsupported parameter input: `%s`" %estimator_params)
    estimator.set_params(**params)

  return estimator
  </token>

  <token name="@GET_CV_FUNCTION@">
def get_cv(literal):
  if literal == "":
    return None
  if re.match(r'^\d+$', literal):
    return int(literal)
  m = re.match(r'^(?P&lt;method&gt;\w+)\((?P&lt;args&gt;.*)\)$', literal)
  if m:
    my_class = getattr( model_selection, m.group('method') )
    args = safe_eval( 'dict('+ m.group('args') + ')' )
    return my_class( **args )
  sys.exit("Unsupported CV input: %s" %literal)
  </token>

  <xml name="python_requirements">
      <requirements>
          <requirement type="package" version="2.7">python</requirement>

      </when>
    </conditional>
  </xml>

  <xml name="model_validation_common_options">
    <param argument="cv" type="text" value="" size="50" optional="true" label="cv" help="Optional. Integer or evalable splitter object, e.g., StratifiedKFold(n_splits=3, shuffle=True, random_state=10). Leave blank for default." />
    <expand macro="n_jobs"/>
    <expand macro="verbose"/>
    <yield/>
  </xml>