fooof-tools · TomDonoghue · Mar 9, 2026 · Mar 9, 2026 · Mar 9, 2026 · Mar 9, 2026
diff --git a/specparam/algorithms/algorithm.py b/specparam/algorithms/algorithm.py
@@ -33,12 +33,15 @@ class Algorithm():
         Data object with spectral data and metadata.
     results : Results
         Results object with model fit results and metrics.
+    model : SpectralModel, optional
+        The model object this object is linked to, to provide access to other attributes.
     debug :  bool
         Whether to run in debug state, raising an error if encountered during fitting.
     """
 
     def __init__(self, name, description, public_settings, private_settings=None,
-                 data_format='spectrum', modes=None, data=None, results=None, debug=False):
+                 data_format='spectrum', modes=None, data=None, results=None, model=None,
+                 debug=False):
         """Initialize Algorithm object."""
 
         self.name = name
@@ -66,6 +69,8 @@ def __init__(self, name, description, public_settings, private_settings=None,
 
         self.set_debug(debug)
 
+        self._model = model
+
 
     def _fit_prechecks(self, verbose):
         """Pre-checks to run before the fit function - if are some, overload this function."""
@@ -178,13 +183,14 @@ class AlgorithmCF(Algorithm):
     """
 
     def __init__(self, name, description, public_settings, private_settings=None,
-                 data_format='spectrum', modes=None, data=None, results=None, debug=False):
+                 data_format='spectrum', modes=None, data=None, results=None,
+                 model=None, debug=False):
         """Initialize Algorithm object."""
 
         Algorithm.__init__(self, name=name, description=description,
                            public_settings=public_settings, private_settings=private_settings,
                            data_format=data_format, modes=modes, data=data, results=results,
-                           debug=debug)
+                           model=model, debug=debug)
 
         self._cf_settings_desc = CURVE_FIT_SETTINGS
         self._cf_settings = SettingsValues(self._cf_settings_desc.names)

diff --git a/specparam/algorithms/spectral_fit.py b/specparam/algorithms/spectral_fit.py
@@ -106,7 +106,7 @@ class SpectralFitAlgorithm(AlgorithmCF):
     def __init__(self, peak_width_limits=(0.5, 12.0), max_n_peaks=np.inf, min_peak_height=0.0,
                  peak_threshold=2.0, ap_percentile_thresh=0.025, ap_guess=None, ap_bounds=None,
                  cf_bound=1.5, bw_std_edge=1.0, gauss_overlap_thresh=0.75, maxfev=5000,
-                 tol=0.00001, modes=None, data=None, results=None, debug=False):
+                 tol=0.00001, modes=None, data=None, results=None, model=None, debug=False):
         """Initialize base model object"""
 
         # Initialize base algorithm object with algorithm metadata
@@ -115,7 +115,7 @@ def __init__(self, peak_width_limits=(0.5, 12.0), max_n_peaks=np.inf, min_peak_h
             description='Original parameterizing neural power spectra algorithm.',
             public_settings=SPECTRAL_FIT_SETTINGS_DEF,
             private_settings=SPECTRAL_FIT_PRIVATE_SETTINGS_DEF,
-            modes=modes, data=data, results=results, debug=debug)
+            modes=modes, data=data, results=results, model=model, debug=debug)
 
         ## Public settings
         self.settings.peak_width_limits = peak_width_limits

diff --git a/specparam/data/data.py b/specparam/data/data.py
@@ -7,6 +7,7 @@
 
 from specparam.sim.gen import gen_freqs
 from specparam.data import SpectrumMetaData, ModelChecks
+from specparam.utils.array import unlog
 from specparam.utils.spectral import trim_spectrum
 from specparam.utils.checks import check_input_options
 from specparam.reports.strings import gen_data_str
@@ -36,6 +37,8 @@ class Data():
         Whether to check the spectral data. If so, raises an error for any NaN / Inf values.
     format : {'power'}
         The representation format of the data.
+    model : SpectralModel, optional
+        The model object this object is linked to, to provide access to other attributes.
 
     Attributes
     ----------
@@ -55,7 +58,7 @@ class Data():
     All power values are stored internally in log10 scale.
     """
 
-    def __init__(self, check_freqs=True, check_data=True, format='power'):
+    def __init__(self, check_freqs=True, check_data=True, format='power', model=None):
         """Initialize Data object."""
 
         self._reset_data(True, True)
@@ -70,6 +73,7 @@ def __init__(self, check_freqs=True, check_data=True, format='power'):
         check_input_options(format, FORMATS, 'format')
         self.format = format
 
+        self._model = model
 
     @property
     def has_data(self):
@@ -154,6 +158,54 @@ def get_meta_data(self):
         return SpectrumMetaData(**{key : getattr(self, key) for key in self._meta_fields})
 
 
+    def get_data(self, component='full', space='log'):
+        """Get a data component.
+
+        Parameters
+        ----------
+        component : {'full', 'aperiodic', 'peak'}
+            Which data component to return.
+                'full' - full power spectrum
+                'aperiodic' - isolated aperiodic data component
+                'peak' - isolated peak data component
+        space : {'log', 'linear'}
+            Which space to return the data component in.
+                'log' - returns in log10 space.
+                'linear' - returns in linear space.
+
+        Returns
+        -------
+        output : 1d array
+            Specified data component, in specified spacing.
+
+        Notes
+        -----
+        The 'space' parameter doesn't just define the spacing of the data component
+        values, but rather defines the space of the additive data definition such that
+        `power_spectrum = aperiodic_component + peak_component`.
+        With space set as 'log', this combination holds in log space.
+        With space set as 'linear', this combination holds in linear space.
+        """
+
+        if not self.has_data:
+            raise NoDataError("No data available to fit, can not proceed.")
+        assert space in ['linear', 'log'], "Input for 'space' invalid."
+
+        if component == 'full':
+            output = self.power_spectrum if space == 'log' \
+                else unlog(self.power_spectrum)
+        elif component == 'aperiodic':
+            output = self._model.results.model._spectrum_peak_rm if space == 'log' else \
+                unlog(self.power_spectrum) / unlog(self._model.results.model._peak_fit)
+        elif component == 'peak':
+            output = self._model.results.model._spectrum_flat if space == 'log' else \
+                unlog(self.power_spectrum) - unlog(self._model.results.model._ap_fit)
+        else:
+            raise ValueError('Input for component invalid.')
+
+        return output
+
+
     def plot(self, plt_log=False, **plt_kwargs):
         """Plot the power spectrum."""
 
@@ -339,10 +391,10 @@ class Data2D(Data):
     All power values are stored internally in log10 scale.
     """
 
-    def __init__(self):
+    def __init__(self, *args, **kwargs):
         """Initialize Data2D object."""
 
-        Data.__init__(self)
+        Data.__init__(self, *args, **kwargs)
 
         self.power_spectra = None
 
@@ -451,10 +503,10 @@ class Data2DT(Data2D):
     All power values are stored internally in log10 scale.
     """
 
-    def __init__(self):
+    def __init__(self, *args, **kwargs):
         """Initialize Data2DT object."""
 
-        Data2D.__init__(self)
+        Data2D.__init__(self, *args, **kwargs)
 
 
     @property
@@ -521,10 +573,10 @@ class Data3D(Data2DT):
     All power values are stored internally in log10 scale.
     """
 
-    def __init__(self):
+    def __init__(self, *args, **kwargs):
         """Initialize Data3D object."""
 
-        Data2DT.__init__(self)
+        Data2DT.__init__(self, *args, **kwargs)
 
         self.spectrograms = None
 

diff --git a/specparam/models/base.py b/specparam/models/base.py
@@ -2,7 +2,6 @@
 
 from copy import deepcopy
 
-from specparam.utils.array import unlog
 from specparam.utils.checks import check_array_dim
 from specparam.modes.modes import Modes
 from specparam.modutils.errors import NoDataError
@@ -56,7 +55,7 @@ def add_modes(self, aperiodic_mode, periodic_mode):
             Mode for periodic component, or string specifying which mode to use.
         """
 
-        self.modes = Modes(aperiodic=aperiodic_mode, periodic=periodic_mode)
+        self.modes = Modes(aperiodic=aperiodic_mode, periodic=periodic_mode, model=self)
 
         if getattr(self, 'results', None):
             self.results.modes = self.modes
@@ -66,54 +65,6 @@ def add_modes(self, aperiodic_mode, periodic_mode):
             self.algorithm._reset_subobjects(modes=self.modes, results=self.results)
 
 
-    def get_data(self, component='full', space='log'):
-        """Get a data component.
-
-        Parameters
-        ----------
-        component : {'full', 'aperiodic', 'peak'}
-            Which data component to return.
-                'full' - full power spectrum
-                'aperiodic' - isolated aperiodic data component
-                'peak' - isolated peak data component
-        space : {'log', 'linear'}
-            Which space to return the data component in.
-                'log' - returns in log10 space.
-                'linear' - returns in linear space.
-
-        Returns
-        -------
-        output : 1d array
-            Specified data component, in specified spacing.
-
-        Notes
-        -----
-        The 'space' parameter doesn't just define the spacing of the data component
-        values, but rather defines the space of the additive data definition such that
-        `power_spectrum = aperiodic_component + peak_component`.
-        With space set as 'log', this combination holds in log space.
-        With space set as 'linear', this combination holds in linear space.
-        """
-
-        if not self.data.has_data:
-            raise NoDataError("No data available to fit, can not proceed.")
-        assert space in ['linear', 'log'], "Input for 'space' invalid."
-
-        if component == 'full':
-            output = self.data.power_spectrum if space == 'log' \
-                else unlog(self.data.power_spectrum)
-        elif component == 'aperiodic':
-            output = self.results.model._spectrum_peak_rm if space == 'log' else \
-                unlog(self.data.power_spectrum) / unlog(self.results.model._peak_fit)
-        elif component == 'peak':
-            output = self.results.model._spectrum_flat if space == 'log' else \
-                unlog(self.data.power_spectrum) - unlog(self.results.model._ap_fit)
-        else:
-            raise ValueError('Input for component invalid.')
-
-        return output
-
-
     def print_settings(self, description=False, concise=False):
         """Print out the current settings.
 

diff --git a/specparam/models/event.py b/specparam/models/event.py
@@ -57,11 +57,12 @@ def __init__(self, *args, **kwargs):
                                    verbose=kwargs.pop('verbose', True),
                                    **kwargs)
 
-        self.data = Data3D()
+        self.data = Data3D(model=self)
 
         self.results = Results3D(modes=self.modes,
                                  metrics=kwargs.pop('metrics', None),
-                                 bands=kwargs.pop('bands', None))
+                                 bands=kwargs.pop('bands', None),
+                                 model=self)
 
         self.algorithm._reset_subobjects(data=self.data, results=self.results)
 

diff --git a/specparam/models/group.py b/specparam/models/group.py
@@ -60,11 +60,12 @@ def __init__(self, *args, **kwargs):
                                verbose=kwargs.pop('verbose', True),
                                **kwargs)
 
-        self.data = Data2D()
+        self.data = Data2D(model=self)
 
         self.results = Results2D(modes=self.modes,
                                  metrics=kwargs.pop('metrics', None),
-                                 bands=kwargs.pop('bands', None))
+                                 bands=kwargs.pop('bands', None),
+                                 model=self)
 
         self.algorithm._reset_subobjects(data=self.data, results=self.results)
 

diff --git a/specparam/models/model.py b/specparam/models/model.py
@@ -95,14 +95,14 @@ def __init__(self, aperiodic_mode='fixed', periodic_mode='gaussian',
             update_converters(DEFAULT_CONVERTERS, converters)
         BaseModel.__init__(self, aperiodic_mode, periodic_mode, converters, verbose)
 
-        self.data = Data()
+        self.data = Data(model=self)
 
-        self.results = Results(modes=self.modes, metrics=metrics, bands=bands)
+        self.results = Results(modes=self.modes, metrics=metrics, bands=bands, model=self)
 
         algorithm_settings = {} if algorithm_settings is None else algorithm_settings
         self.algorithm = check_algorithm_definition(algorithm, ALGORITHMS)(
             **algorithm_settings, modes=self.modes, data=self.data,
-            results=self.results, debug=debug, **model_kwargs)
+            results=self.results, debug=debug, model=self, **model_kwargs)
 
 
     @replace_docstring_sections([docs_get_section(Data.add_data.__doc__, 'Parameters'),

diff --git a/specparam/models/time.py b/specparam/models/time.py
@@ -53,11 +53,12 @@ def __init__(self, *args, **kwargs):
                                     verbose=kwargs.pop('verbose', True),
                                     **kwargs)
 
-        self.data = Data2DT()
+        self.data = Data2DT(model=self)
 
         self.results = Results2DT(modes=self.modes,
                                   metrics=kwargs.pop('metrics', None),
-                                  bands=kwargs.pop('bands', None))
+                                  bands=kwargs.pop('bands', None),
+                                  model=self)
 
         self.algorithm._reset_subobjects(data=self.data, results=self.results)
 

diff --git a/specparam/modes/modes.py b/specparam/modes/modes.py
@@ -17,9 +17,11 @@ class Modes():
         Aperiodic mode.
     periodic : str or Mode
         Periodic mode.
+    model : SpectralModel, optional
+        The model object this object is linked to, to provide access to other attributes.
     """
 
-    def __init__(self, aperiodic, periodic):
+    def __init__(self, aperiodic, periodic, model=None):
         """Initialize modes."""
 
         # Set list of component names
@@ -29,6 +31,8 @@ def __init__(self, aperiodic, periodic):
         self.aperiodic = check_mode_definition(aperiodic, AP_MODES)
         self.periodic = check_mode_definition(periodic, PE_MODES)
 
+        self.model = model
+
 
     def check_params(self):
         """Check the description of the parameters for each mode."""