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Merged
henrikjacobsenfys merged 11 commits into from
Jun 22, 2026
Merged

Standardize dirty flag #211

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6e8acb3
code cleanup
henrikjacobsenfys Jun 18, 2026
f8c21b7
simplify analysis1d
henrikjacobsenfys Jun 18, 2026
b23aa1b
Clean up analysis
henrikjacobsenfys Jun 18, 2026
2af2ef9
improve docstrings
henrikjacobsenfys Jun 18, 2026
08d7421
Clean up convolutions
henrikjacobsenfys Jun 18, 2026
be66c8c
standardize dirty flag
henrikjacobsenfys Jun 18, 2026
58930a0
add rebin to analysis
henrikjacobsenfys Jun 19, 2026
cd3ad21
fix missing docstrings
henrikjacobsenfys Jun 19, 2026
d4fb98d
address PR review: expose public dirty flag, strengthen Q similarity …
henrikjacobsenfys Jun 19, 2026
cbb4332
claude reviewing the code
henrikjacobsenfys Jun 19, 2026
890c871
A few more tests
henrikjacobsenfys Jun 19, 2026
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1 change: 1 addition & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -44,3 +44,4 @@ CMakeLists.txt.user*
.cache/
*.log
*.zip
.claude/
200 changes: 95 additions & 105 deletions src/easydynamics/analysis/analysis.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -66,9 +66,8 @@ def __init__(
parameters are added.
"""

# Avoid triggering updates before the object is fully
# initialized
self._call_updaters = False
self._analysis_list: list[Analysis1d] = []
self._analysis_list_is_dirty = True
super().__init__(
display_name=display_name,
unique_name=unique_name,
Expand All @@ -80,13 +79,6 @@ def __init__(
extra_parameters=extra_parameters,
)

self._analysis_list = []
if self.Q is not None:
self._create_analysis_list()

# Now we can allow updates to trigger recalculations
self._call_updaters = True

#############
# Properties
#############
Expand All @@ -101,6 +93,7 @@ def analysis_list(self) -> list[Analysis1d]:
list[Analysis1d]
A list of Analysis1d objects, one for each Q index.
"""
self._ensure_analysis_list_current()
return self._analysis_list

@analysis_list.setter
Expand Down Expand Up @@ -131,6 +124,58 @@ def analysis_list(self, _value: list[Analysis1d]) -> None:
#############
# Other methods
#############
def rebin(
self,
dimensions: dict[str, int | sc.Variable],
confirm: bool = False,
) -> None:
"""
Rebin the experiment data along specified dimensions and update the analysis.

If Q values change (in count or magnitude), ``confirm=True`` is required. This clears Q
from ``sample_model`` and ``instrument_model`` (including resolution and background
sub-models) so they can accept the new Q values when the analysis list is next rebuilt.

Parameters
----------
dimensions : dict[str, int | sc.Variable]
A dictionary mapping dimension names to number of bins (int) or bin edges
(sc.Variable).
confirm : bool, default=False
Must be ``True`` when rebinning changes the Q values (count or magnitude), since this
clears Q from all models. Raises ``ValueError`` otherwise.

Raises
------
ValueError
If rebinning changes Q and ``confirm`` is not ``True``.
"""
old_Q = np.asarray(self.Q.values) if self.Q is not None else None
old_binned_data = self.experiment._binned_data # noqa: SLF001

self.experiment.rebin(dimensions)
new_Q = np.asarray(self.Q.values) if self.Q is not None else None

q_changed = (
old_Q is not None
and new_Q is not None
and (len(old_Q) != len(new_Q) or not np.allclose(old_Q, new_Q))
)

if q_changed and not confirm:
self.experiment._binned_data = old_binned_data # noqa: SLF001
raise ValueError(
'Rebinning changed Q values, which requires clearing Q from sample_model and '
'instrument_model (including resolution and background sub-models). '
'Pass confirm=True to proceed.'
)

if q_changed:
self.sample_model.clear_Q(confirm=True)
self.instrument_model.clear_Q(confirm=True)

self._analysis_list_is_dirty = True

def calculate(
self,
Q_index: int | None = None,
Expand Down Expand Up @@ -249,8 +294,6 @@ def plot_data_and_model(
values available for plotting.
RuntimeError
If not in a Jupyter notebook environment.
TypeError
If plot_components or add_background is not True or False.

Returns
-------
Expand Down Expand Up @@ -279,14 +322,9 @@ def plot_data_and_model(
'No Q values available for plotting. Please check the experiment data.'
)

if not isinstance(plot_components, bool):
raise TypeError('plot_components must be True or False.')

if not isinstance(add_background, bool):
raise TypeError('add_background must be True or False.')

if not isinstance(plot_residuals, bool):
raise TypeError('plot_residuals must be True or False.')
self._verify_bool(plot_components, 'plot_components')
self._verify_bool(add_background, 'add_background')
self._verify_bool(plot_residuals, 'plot_residuals')

if energy is None:
energy = self.energy
Expand All @@ -300,39 +338,8 @@ def plot_data_and_model(
include_residuals=plot_residuals,
)

plot_kwargs_defaults = {
'title': self.display_name,
'linestyle': {},
'marker': {},
'color': {},
'markerfacecolor': {},
'keep': 'energy',
}

for key in data_and_model:
if key == 'Data':
plot_kwargs_defaults['linestyle'][key] = 'none'
plot_kwargs_defaults['marker'][key] = 'o'
plot_kwargs_defaults['color'][key] = 'black'
plot_kwargs_defaults['markerfacecolor'][key] = 'none'

elif key == 'Model':
plot_kwargs_defaults['linestyle'][key] = '-'
plot_kwargs_defaults['marker'][key] = None
plot_kwargs_defaults['color'][key] = 'red'
plot_kwargs_defaults['markerfacecolor'][key] = 'none'

elif key == 'Residuals':
plot_kwargs_defaults['linestyle'][key] = 'none'
plot_kwargs_defaults['marker'][key] = 'o'
plot_kwargs_defaults['color'][key] = 'blue'
plot_kwargs_defaults['markerfacecolor'][key] = 'none'

else:
plot_kwargs_defaults['linestyle'][key] = '--'
plot_kwargs_defaults['marker'][key] = None

# Overwrite defaults with any user-provided kwargs
plot_kwargs_defaults = self._build_plot_style_defaults(data_and_model)
plot_kwargs_defaults['keep'] = 'energy'
plot_kwargs_defaults.update(kwargs)

if plot_residuals:
Expand Down Expand Up @@ -384,9 +391,6 @@ def data_and_model_to_datagroup(
If there is no data to include in the DataGroup, or if there are no Q values available
for creating the DataGroup.

TypeError
If add_background is not True or False. If include_components is not True or False.

Returns
-------
sc.DataGroup
Expand All @@ -401,14 +405,9 @@ def data_and_model_to_datagroup(
'No Q values available for creating DataGroup. Please check the experiment data.'
)

if not isinstance(add_background, bool):
raise TypeError('add_background must be True or False.')

if not isinstance(include_components, bool):
raise TypeError('include_components must be True or False.')

if not isinstance(include_residuals, bool):
raise TypeError('include_residuals must be True or False.')
self._verify_bool(add_background, 'add_background')
self._verify_bool(include_components, 'include_components')
self._verify_bool(include_residuals, 'include_residuals')

energy = self._verify_energy(energy)

Expand Down Expand Up @@ -442,6 +441,8 @@ def parameters_to_dataset(self) -> sc.Dataset:
------
UnitError
If there are inconsistent units for the same parameter across different Q values.
ValueError
If duplicate parameter names exist for the same Q index.

Returns
-------
Expand All @@ -452,20 +453,28 @@ def parameters_to_dataset(self) -> sc.Dataset:

ds = sc.Dataset(coords={'Q': self.Q})

# Collect all parameter names
all_names = {
# Collect all parameter names in first-seen order
all_names = dict.fromkeys(
param.name
for analysis in self.analysis_list
for param in analysis.get_all_parameters()
}
)

# Storage
values = {name: [] for name in all_names}
variances = {name: [] for name in all_names}
units = {}

for analysis in self.analysis_list:
pars = {p.name: p for p in analysis.get_all_parameters()}
all_params = analysis.get_all_parameters()
param_names = [p.name for p in all_params]
if len(param_names) != len(set(param_names)):
dups = sorted({n for n in param_names if param_names.count(n) > 1})
raise ValueError(
f'Duplicate parameter names at Q_index {analysis.Q_index}: {dups}. '
'Rename components so all parameters have unique names.'
)
pars = {p.name: p for p in all_params}

for name in all_names:
if name in pars:
Expand Down Expand Up @@ -603,45 +612,37 @@ def free_energy_offset(self, Q_index: int | None = None) -> None:
def _on_experiment_changed(self) -> None:
"""
Update the Q values in the sample and instrument models when the experiment changes.

Also update all the Analysis1d objects with the new experiment.
"""
if self._call_updaters:
super()._on_experiment_changed()
for analysis in self.analysis_list:
analysis.experiment = self.experiment
super()._on_experiment_changed()
self._analysis_list_is_dirty = True

def _on_sample_model_changed(self) -> None:
"""
Update the Q values in the sample model when the sample model changes.

Also update all the Analysis1d objects with the new sample model.
"""
if self._call_updaters:
super()._on_sample_model_changed()
for analysis in self.analysis_list:
analysis.sample_model = self.sample_model
super()._on_sample_model_changed()
self._analysis_list_is_dirty = True

def _on_instrument_model_changed(self) -> None:
"""
Update the Q values in the instrument model when the instrument model changes.

Also update all the Analysis1d objects with the new instrument model.
"""
if self._call_updaters:
super()._on_instrument_model_changed()
for analysis in self.analysis_list:
analysis.instrument_model = self.instrument_model
super()._on_instrument_model_changed()
self._analysis_list_is_dirty = True

def _on_convolution_settings_changed(self) -> None:
"""
Update the convolution settings in all Analysis1d objects when the convolution settings
change.
Update the convolution settings when they change.
"""
if self._call_updaters:
super()._on_convolution_settings_changed()
for analysis1d in self.analysis_list:
analysis1d.convolution_settings = self.convolution_settings
super()._on_convolution_settings_changed()
self._analysis_list_is_dirty = True

def _ensure_analysis_list_current(self) -> None:
"""Rebuild the analysis list if any dependency has changed since it was last built."""
if self._analysis_list_is_dirty:
if self.Q is not None:
self._create_analysis_list()
self._analysis_list_is_dirty = False

def _create_analysis_list(self) -> None:
"""
Expand All @@ -652,7 +653,6 @@ def _create_analysis_list(self) -> None:
for Q_index in range(len(self.Q)):
analysis = Analysis1d(
display_name=f'{self.display_name}_Q{Q_index}',
unique_name=(f'{self.unique_name}_Q{Q_index}'),
experiment=self.experiment,
sample_model=self.sample_model,
instrument_model=self.instrument_model,
Expand Down Expand Up @@ -682,8 +682,6 @@ def _fit_single_Q(self, Q_index: int) -> FitResults:
The results of the fit for the specified Q index.
"""

Q_index = self._verify_Q_index(Q_index)

return self.analysis_list[Q_index].fit()

def _fit_all_Q_independently(self) -> list[FitResults]:
Expand Down Expand Up @@ -720,9 +718,7 @@ def _fit_all_Q_simultaneously(self) -> FitResults:
ws.append(weight)

# Make sure the convolver is up to date for this Q index
analysis1d._convolver = analysis1d._create_convolver( # noqa: SLF001
energy=x
)
analysis1d.refresh_convolver(energy=x)

mf = MultiFitter(
fit_objects=self.analysis_list,
Expand Down Expand Up @@ -799,18 +795,12 @@ def _create_components_dataset(
The energy values to use for calculating the components. If None, uses the energy from
the experiment.

Raises
------
TypeError
If add_background is not True or False.

Returns
-------
sc.Dataset
A scipp Dataset where each entry is a component of the model, with dimensions "Q".
"""
if not isinstance(add_background, bool):
raise TypeError('add_background must be True or False.')
self._verify_bool(add_background, 'add_background')

if energy is None:
energy = self.energy
Expand Down
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