Пример #1
0
def test_glm_background_calculator():
  from dials.algorithms.background.glm.algorithm import GLMBackgroundCalculatorFactory
  algorithm = GLMBackgroundCalculatorFactory.create(data.experiments)
  reflections = flex.reflection_table_to_list_of_reflections(data.reflections)

  count = 0
  for r in reflections:
    try:
      algorithm(r)
    except Exception:
      count += 1
  assert len(reflections) == 15193
  assert count == 333
Пример #2
0
    def create(cls, experiments, params=None):
        """
        Select the background calculator
        """
        from dials.algorithms.background.simple.algorithm import (
            SimpleBackgroundCalculatorFactory, )
        from dials.algorithms.background.glm.algorithm import (
            GLMBackgroundCalculatorFactory, )
        from dials.algorithms.background.gmodel.algorithm import (
            GModelBackgroundCalculatorFactory, )

        # Get the parameters
        if params is None:
            from dials.command_line.integrate import phil_scope

            params = phil_scope.extract()

        # Select the factory function
        selection = params.integration.background.algorithm
        if selection == "simple":

            # Get parameters
            params = params.integration.background.simple

            # Create some keyword parameters
            kwargs = {
                "model": params.model.algorithm,
                "outlier": params.outlier.algorithm,
                "min_pixels": params.min_pixels,
            }

            # Create all the keyword parameters
            if params.outlier.algorithm == "null":
                pass
            elif params.outlier.algorithm == "truncated":
                kwargs["lower"] = params.outlier.truncated.lower
                kwargs["upper"] = params.outlier.truncated.upper
            elif params.outlier.algorithm == "nsigma":
                kwargs["lower"] = params.outlier.nsigma.lower
                kwargs["upper"] = params.outlier.nsigma.upper
            elif params.outlier.algorithm == "normal":
                kwargs["min_pixels"] = params.outlier.normal.min_pixels
            elif params.outlier.algorithm == "plane":
                kwargs["fraction"] = params.outlier.plane.fraction
                kwargs["n_sigma"] = params.outlier.plane.n_sigma
            elif params.outlier.algorithm == "tukey":
                kwargs["lower"] = params.outlier.tukey.lower
                kwargs["upper"] = params.outlier.tukey.upper

            # Create the algorithm
            algorithm = SimpleBackgroundCalculatorFactory.create(
                experiments, **kwargs)

        elif selection == "glm":

            # Get the parameters
            params = params.integration.background.glm

            # Create the algorithm
            algorithm = GLMBackgroundCalculatorFactory.create(
                experiments,
                model=params.model.algorithm,
                tuning_constant=params.robust.tuning_constant,
                min_pixels=params.min_pixels,
            )

        elif selection == "gmodel":

            # Get the parameters
            params = params.integration.background.gmodel

            # Create the algorithm
            algorithm = GModelBackgroundCalculatorFactory.create(
                experiments,
                model=params.model,
                robust=params.robust.algorithm,
                tuning_constant=params.robust.tuning_constant,
                min_pixels=params.min_pixels,
            )

        else:
            raise RuntimeError("Unknown background algorithm")

        # Return the background calculator
        return algorithm
Пример #3
0
  def create(Class, experiments, params=None):
    '''
    Select the background calculator

    '''
    from dials.algorithms.background.simple.algorithm import SimpleBackgroundCalculatorFactory
    from dials.algorithms.background.glm.algorithm import GLMBackgroundCalculatorFactory
    from dials.algorithms.background.gmodel.algorithm import GModelBackgroundCalculatorFactory

    # Get the parameters
    if params is None:
      from dials.command_line.integrate import phil_scope
      params = phil_scope.extract()

    # Select the factory function
    selection = params.integration.background.algorithm
    if selection == "simple":

      # Get parameters
      params = params.integration.background.simple

      # Create some keyword parameters
      kwargs = {
        'model'      : params.model.algorithm,
        'outlier'    : params.outlier.algorithm,
        'min_pixels' : params.min_pixels
      }

      # Create all the keyword parameters
      if params.outlier.algorithm == 'null':
        pass
      elif params.outlier.algorithm == 'truncated':
        kwargs['lower'] = params.outlier.truncated.lower
        kwargs['upper'] = params.outlier.truncated.upper
      elif params.outlier.algorithm == 'nsigma':
        kwargs['lower'] = params.outlier.nsigma.lower
        kwargs['upper'] = params.outlier.nsigma.upper
      elif params.outlier.algorithm == 'normal':
        kwargs['min_pixels'] = params.outlier.normal.min_pixels
      elif params.outlier.algorithm == 'plane':
        kwargs['fraction'] = params.outlier.plane.fraction
        kwargs['n_sigma'] = params.outlier.plane.n_sigma
      elif params.outlier.algorithm == 'tukey':
        kwargs['lower'] = params.outlier.tukey.lower
        kwargs['upper'] = params.outlier.tukey.upper

      # Create the algorithm
      algorithm = SimpleBackgroundCalculatorFactory.create(experiments, **kwargs)

    elif selection == "glm":

      # Get the parameters
      params = params.integration.background.glm

      # Create the algorithm
      algorithm = GLMBackgroundCalculatorFactory.create(
        experiments,
        model           = params.model.algorithm,
        tuning_constant = params.robust.tuning_constant,
        min_pixels      = params.min_pixels)

    elif selection == "gmodel":

      # Get the parameters
      params = params.integration.background.gmodel

      # Create the algorithm
      algorithm = GModelBackgroundCalculatorFactory.create(
        experiments,
        model           = params.model,
        robust          = params.robust.algorithm,
        tuning_constant = params.robust.tuning_constant,
        min_pixels      = params.min_pixels)

    else:
      raise RuntimeError("Unknown background algorithm")

    # Return the background calculator
    return algorithm