def __init__(self, params, experiments):
"""
Initialise the algorithm.
:param params: The input parameters
:param experiments: The list of experiments
"""
from libtbx.phil import parse
from dials.algorithms.background.gmodel import BackgroundAlgorithm
# Create some default parameters
if params is None:
params = self.phil().fetch(parse("")).extract()
else:
params = params.integration.background.gmodel
# Create the algorithm
self._algorithm = BackgroundAlgorithm(
experiments,
model=params.model,
robust=params.robust.algorithm,
tuning_constant=params.robust.tuning_constant,
min_pixels=params.min_pixels,
)
def __init__(self, params, experiments):
'''
Initialise the algorithm.
:param params: The input parameters
:param experiments: The list of experiments
'''
from libtbx.phil import parse
from dials.algorithms.background.gmodel import BackgroundAlgorithm
# Create some default parameters
if params is None:
params = self.phil().fetch(parse('')).extract()
else:
params = params.integration.background.gmodel
# Create the algorithm
self._algorithm = BackgroundAlgorithm(
experiments,
model = params.model,
robust = params.robust.algorithm,
tuning_constant = params.robust.tuning_constant,
min_pixels = params.min_pixels)
class GModelBackgroundExt(BackgroundIface):
''' An extension class implementing a robust GLM background algorithm. '''
name = 'gmodel'
@classmethod
def phil(cls):
from libtbx.phil import parse
phil = parse('''
robust {
algorithm = False
.type = bool
.help = "Use the robust algorithm"
tuning_constant = 1.345
.type = float
.help = "The tuning constant for robust estimation"
}
min_pixels = 10
.type = int(value_min=1)
.help = "The minimum number of pixels required"
model = None
.type = str
.help = "The model filename"
''')
return phil
def __init__(self, params, experiments):
'''
Initialise the algorithm.
:param params: The input parameters
:param experiments: The list of experiments
'''
from libtbx.phil import parse
from dials.algorithms.background.gmodel import BackgroundAlgorithm
# Create some default parameters
if params is None:
params = self.phil().fetch(parse('')).extract()
else:
params = params.integration.background.gmodel
# Create the algorithm
self._algorithm = BackgroundAlgorithm(
experiments,
model = params.model,
robust = params.robust.algorithm,
tuning_constant = params.robust.tuning_constant,
min_pixels = params.min_pixels)
def compute_background(self, reflections, image_volume=None):
'''
Compute the background.
:param reflections: The list of reflections
'''
return self._algorithm.compute_background(
reflections, image_volume=image_volume)
