def test_scale_scale_2(self):
import numpy as np
import fit2x
x = np.arange(0, 16)
y = np.ones_like(x) * 100
y2 = y * 10
data = fit2x.DecayCurve(x, y2)
settings = {
"data": data,
"constant_background": 0,
"active": True,
"start": 0,
"stop": -1
}
ds = fit2x.DecayScale(**settings)
model = fit2x.DecayCurve(x, y)
self.assertEqual(
np.allclose(ds.data.y,
np.ones_like(ds.data.y) * 1000), True)
self.assertEqual(np.allclose(model.y,
np.ones_like(ds.data.y) * 100), True)
ds.add(model)
self.assertEqual(np.sum(model.y), np.sum(ds.data.y))
def test_scale_scale_3(self):
ds = fit2x.DecayScale(**settings)
# Scaling considering noise & background of data
ds.constant_background = 100
# Set number of photons to negative value for scaling
model = fit2x.DecayCurve(x, y)
ds.add(model)
self.assertEqual(np.allclose(model.y, ds.data.y - 100), True)
self.assertEqual(ds.number_of_photons, 16000)
def test_scale_scale_1(self):
x = np.arange(0, 16)
y = np.ones_like(x) * 100
y2 = y * 10
data = fit2x.DecayCurve(x, y2)
settings = {
"data": data,
"constant_background": 0,
"active": True,
"start": 0,
"stop": -1
}
ds = fit2x.DecayScale(**settings)
model = fit2x.DecayCurve(x, y)
ds.add(model)
self.assertEqual(np.allclose(model.y, data.y), True)
ds.active = False
self.assertEqual(ds.active, False)
model = fit2x.DecayCurve(x, y)
ds.add(model)
self.assertEqual(np.allclose(model.y, y), True)
def test_scale_init(self):
ds = fit2x.DecayScale(**settings)
self.assertEqual(np.allclose(ds.data.y, data.y), True)
self.assertEqual(np.allclose(ds.data.x, data.x), True)
self.assertEqual(ds.constant_background, 0.0)
self.assertEqual(ds.active, True)
def __init__(
self,
data_settings=None, # type: DataSettings
lifetime_settings=None, # type: LifetimeSettings
convolution_settings=None, # type: ConvolutionSettings
scatter_settings=None, # type: PatternSettings
background_settings=None, # type: PatternSettings
pileup_settings=None, # type: PileupSettings
scaling_settings=None, # type: ScalingSettings
linearization_settings=None, # type: LinearizationSettings
score_settings=None # type: ScoreSettings
):
super().__init__()
if data_settings is None:
data_settings = DataSettings()
if lifetime_settings is None:
lifetime_settings = LifetimeSettings()
if convolution_settings is None:
convolution_settings = ConvolutionSettings()
if background_settings is None:
background_settings = PatternSettings()
if scatter_settings is None:
scatter_settings = PatternSettings()
if pileup_settings is None:
pileup_settings = PileupSettings()
if linearization_settings is None:
linearization_settings = LinearizationSettings()
if scaling_settings is None:
scaling_settings = ScalingSettings()
if score_settings is None:
score_settings = ScoreSettings()
# init decay curves
data, irf = self.make_decay_curves(*data_settings)
model = fit2x.DecayCurve(data.x)
lifetime_handler = fit2x.DecayLifetimeHandler(*lifetime_settings)
decay_convolution = fit2x.DecayConvolution(lifetime_handler, irf,
*convolution_settings)
decay_scatter = fit2x.DecayPattern(*scatter_settings)
decay_scatter.data = irf
decay_background = fit2x.DecayPattern(*background_settings)
decay_pileup = fit2x.DecayPileup(data, *pileup_settings)
decay_linearization = fit2x.DecayLinearization(*linearization_settings)
decay_scale = fit2x.DecayScale(data, *scaling_settings)
decay_score = fit2x.DecayScore(model, data, *score_settings)
self._data, self._irf, self._model = data, irf, model
self.lifetime_handler = lifetime_handler
self.decay_convolution = decay_convolution
self.decay_scatter = decay_scatter
self.decay_pileup = decay_pileup
self.decay_linearization = decay_linearization
self.decay_scale = decay_scale
self.decay_background = decay_background
self.decay_score = decay_score
self._decay_modifier = [
self.decay_convolution,
self.decay_scatter,
# self.decay_pileup, # TODO: seems broken
self.decay_linearization,
self.decay_scale,
self.decay_background,
]