[MNT] - Update docsite for module updates

doc/api.rst

@@ -174,6 +174,17 @@ Metric Object
    Metric
    check_metrics
 
+Metric Functions (GoF)
+~~~~~~~~~~~~~~~~~~~~~~
+
+.. currentmodule:: specparam.metrics.gof
+
+.. autosummary::
+   :toctree: generated/
+
+   compute_r_squared
+   compute_adj_r_squared
+
 Metric Functions (Error)
 ~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -187,16 +198,31 @@ Metric Functions (Error)
    compute_root_mean_squared_error
    compute_median_abs_error
 
-Metric Functions (GoF)
-~~~~~~~~~~~~~~~~~~~~~~
+Metric Functions (Pointwise error)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. currentmodule:: specparam.metrics.gof
+**Object Inputs**
+
+The following functions take in model objects directly.
+
+.. currentmodule:: specparam.metrics.pointwise
 
 .. autosummary::
-   :toctree: generated/
+    :toctree: generated/
 
-   compute_r_squared
-   compute_adj_r_squared
+    compute_pointwise_error
+    compute_pointwise_error_group
+
+**Array Inputs**
+
+The following functions operate on arrays of models and data, which may be useful for more custom work-flows.
+
+.. currentmodule:: specparam.metrics.pointwise
+
+.. autosummary::
+    :toctree: generated/
+
+    compute_pointwise_error_arr
 
 Data Objects
 ------------
@@ -276,51 +302,42 @@ An object for defining frequency band definitions.
 
    Bands
 
-Measures
---------
-
-Functionality to analyze power spectrum models and the results parameters / components.
-
-Model Errors
-~~~~~~~~~~~~
-
-Functions for analyzing the error of model fits.
+Parameters
+----------
 
-**Object Inputs**
+Functionality for working with and converting parameters.
 
-The following functions take in model objects directly.
+Converters
+~~~~~~~~~~
 
-.. currentmodule:: specparam.measures.pointwise
+.. currentmodule:: specparam.params.converter
 
 .. autosummary::
     :toctree: generated/
 
-    compute_pointwise_error
-    compute_pointwise_error_group
-
-**Array Inputs**
+    AperiodicParamConverter
+    PeriodicParamConverter
 
-The following functions operate on arrays of models and data, which may be useful for more custom work-flows.
+Aperiodic Parameters
+~~~~~~~~~~~~~~~~~~~~
 
-.. currentmodule:: specparam.measures.pointwise
+.. currentmodule:: specparam.params.aperiodic
 
 .. autosummary::
     :toctree: generated/
 
-    compute_pointwise_error_arr
-
-Parameters
-~~~~~~~~~~
+    compute_knee_frequency
+    compute_time_constant
 
-Measures & utilities for working with and converting parameters.
+Periodic Parameters
+~~~~~~~~~~~~~~~~~~~
 
-.. currentmodule:: specparam.measures.params
+.. currentmodule:: specparam.params.periodic
 
 .. autosummary::
     :toctree: generated/
 
-    compute_knee_frequency
-    compute_time_constant
+    compute_peak_height
 
 Simulation Code
 ---------------

doc/conf.py

@@ -23,7 +23,7 @@
 
 # Set project information
 project = 'specparam'
-copyright = '2018-{}, VoytekLab'.format(date.today().year)
+copyright = '2018-{}'.format(date.today().year)
 author = 'Thomas Donoghue'
 
 # Get and set the current version number

doc/make_doc_plots.py

@@ -9,7 +9,7 @@
 from specparam.sim.gen import gen_power_spectrum
 from specparam.plts.utils import check_ax
 from specparam.plts.spectra import plot_spectrum
-from specparam.utils.download import load_example_data
+from specparam.demo.download import load_example_data
 
 ###################################################################################################
 ###################################################################################################

examples/analyses/plot_dev_demo.py

@@ -48,7 +48,7 @@
 from specparam.measures.pointwise import compute_pointwise_error, compute_pointwise_error_group
 
 # Import helper utility to access data
-from specparam.utils.download import fetch_example_data
+from specparam.demo.download import fetch_example_data
 
 ###################################################################################################
 # Access Example Data
@@ -302,7 +302,7 @@
 ###################################################################################################
 
 # Print out the group results and plots of fit parameters
-fg.print_results()
+fg.print()
 fg.plot()
 
 ###################################################################################################
@@ -559,7 +559,7 @@
 ###################################################################################################
 
 # Check results and visualize the extracted model
-fm.print_results()
+fm.print()
 fm.plot()
 
 ###################################################################################################

examples/customize/plot_custom_algorithms.py

@@ -99,15 +99,15 @@
 class DummyAlgorithm(Algorithm):
     """Dummy object to mimic a fit algorithm."""
 
-    def __init__(self, modes=None, data=None, results=None, debug=False):
+    def __init__(self, modes=None, data=None, results=None, model=None, debug=False):
         """Initialize DummyAlgorithm instance."""
 
         # Initialize base algorithm object with algorithm metadata
         super().__init__(
             name='dummy_fit_algo',
             description='Dummy fit algorithm.',
             public_settings=DUMMY_ALGO_SETTINGS,
-            modes=modes, data=data, results=results, debug=debug)
+            modes=modes, data=data, results=results, model=None, debug=debug)
 
     def _fit(self):
         """Define the full fitting algorithm."""
@@ -133,7 +133,7 @@ def _fit(self):
 #       components (`model.results.model._ap_fit` & `model.results.model._peak_fit`)
 #
 # If the above  you do the above, the model object can be used as normal, and you can do
-# (fit / print_results / plot / report / as well as save and load results).
+# (fit / print / plot / report / as well as save and load results).
 #
 # There are also some additional procedures / outputs that a custom fit process may do:
 #
@@ -206,15 +206,15 @@ def _fit(self):
 class CustomAlgorithm(Algorithm):
     """Custom fitting algorithm."""
 
-    def __init__(self, guess_cf, modes=None, data=None, results=None, debug=False):
+    def __init__(self, guess_cf, modes=None, data=None, results=None, model=None, debug=False):
         """Initialize DummyAlgorithm instance."""
 
         # Initialize base algorithm object with algorithm metadata
         super().__init__(
             name='custom_fit_algo',
             description='Example custom algorithm.',
             public_settings=CUSTOM_ALGO_SETTINGS,
-            modes=modes, data=data, results=results, debug=debug)
+            modes=modes, data=data, results=results, model=None, debug=debug)
 
         ## Public settings
         self.settings.guess_cf = guess_cf

examples/customize/plot_custom_param_conversions.py

@@ -7,7 +7,8 @@
 
 from specparam import SpectralModel
 
-from specparam.utils.download import load_example_data
+# Import utility to load example data
+from specparam.demo import load_example_data
 
 # Import the default set of parameter conversions
 from specparam.convert.definitions import check_converters, DEFAULT_CONVERTERS

examples/manage/plot_fit_models_3d.py

@@ -246,5 +246,5 @@
 all_fg = combine_model_objs(fgs)
 
 # Explore the results from across all model fits
-all_fg.print_results()
+all_fg.print()
 all_fg.plot()

examples/models/plot_data_components.py

@@ -69,7 +69,7 @@
 #
 # To access these components, we can use the following `getter` methods:
 #
-# - :meth:`~specparam.SpectralModel.get_data`: allows for accessing data components
+# - :meth:`~specparam.SpectralModel.data.get_data`: allows for accessing data components
 # - :meth:`~specparam.SpectralModel.results.model.get_component`: allows for accessing model components
 #
 
@@ -86,12 +86,12 @@
 ###################################################################################################
 
 # Plot the peak removed spectrum data component
-plot_spectra(fm.data.freqs, fm.get_data('aperiodic'), color='black')
+plot_spectra(fm.data.freqs, fm.data.get_data('aperiodic'), color='black')
 
 ###################################################################################################
 
 # Plot the peak removed spectrum, with the model aperiodic fit
-plot_spectra(fm.data.freqs, [fm.get_data('aperiodic'), fm.results.model.get_component('aperiodic')],
+plot_spectra(fm.data.freqs, [fm.data.get_data('aperiodic'), fm.results.model.get_component('aperiodic')],
              colors=['black', 'blue'], linestyle=['-', '--'])
 
 ###################################################################################################
@@ -108,12 +108,12 @@
 ###################################################################################################
 
 # Plot the flattened spectrum data component
-plot_spectra(fm.data.freqs, fm.get_data('peak'), color='black')
+plot_spectra(fm.data.freqs, fm.data.get_data('peak'), color='black')
 
 ###################################################################################################
 
 # Plot the flattened spectrum data with the model peak fit
-plot_spectra(fm.data.freqs, [fm.get_data('peak'), fm.results.model.get_component('peak')],
+plot_spectra(fm.data.freqs, [fm.data.get_data('peak'), fm.results.model.get_component('peak')],
              colors=['black', 'green'], linestyle=['-', '--'])
 
 ###################################################################################################
@@ -156,7 +156,7 @@
 ###################################################################################################
 
 # Plot the peak removed spectrum, with the model aperiodic fit
-plot_spectra(fm.data.freqs, [fm.get_data('aperiodic', 'linear'),
+plot_spectra(fm.data.freqs, [fm.data.get_data('aperiodic', 'linear'),
              fm.results.model.get_component('aperiodic', 'linear')],
              colors=['black', 'blue'], linestyle=['-', '--'])
 
@@ -171,7 +171,7 @@
 
 # Plot the flattened spectrum data with the model peak fit
 plot_spectra(fm.data.freqs,
-             [fm.get_data('peak', 'linear'), fm.results.model.get_component('peak', 'linear')],
+             [fm.data.get_data('peak', 'linear'), fm.results.model.get_component('peak', 'linear')],
              colors=['black', 'green'], linestyle=['-', '--'])
 
 ###################################################################################################
@@ -191,8 +191,8 @@
 
 # Plot the linear data, showing the combination of peak + aperiodic matches the full data
 plot_spectra(fm.data.freqs,
-             [fm.get_data('full', 'linear'),
-              fm.get_data('aperiodic', 'linear') + fm.get_data('peak', 'linear')],
+             [fm.data.get_data('full', 'linear'),
+              fm.data.get_data('aperiodic', 'linear') + fm.data.get_data('peak', 'linear')],
              linestyle=['-', 'dashed'], colors=['black', 'red'], alpha=[0.3, 0.75])
 
 ###################################################################################################

examples/models/plot_model_component_relationships.py

@@ -16,7 +16,9 @@
 
 from specparam.utils.array import unlog
 from specparam.utils.select import nearest_ind
-from specparam.utils.download import load_example_data
+
+# Import utility to load example data
+from specparam.demo import load_example_data
 
 # Import function to directly compute peak heights
 from specparam.convert.params import compute_peak_height

motivations/measurements/plot_BandByBand.py

@@ -203,7 +203,7 @@ def compare_band_pw(fm1, fm2, band_def):
 
 # Plot the power spectra differences
 plot_spectra_shading(freqs,
-                     [fm_bands_g1.get_data('peak'), fm_bands_g2.get_data('peak')],
+                     [fm_bands_g1.data.get_data('peak'), fm_bands_g2.data.get_data('peak')],
                      log_powers=False, linewidth=3,
                      shades=bands.definitions, shade_colors=shade_cols,
                      labels=labels)
@@ -294,7 +294,7 @@ def compare_band_pw(fm1, fm2, band_def):
 
 # Plot the power spectra differences
 plot_spectra_shading(freqs,
-                     [fm_pa_g1.get_data('peak'), fm_pa_g2.get_data('peak')],
+                     [fm_pa_g1.data.get_data('peak'), fm_pa_g2.data.get_data('peak')],
                      log_powers=False, linewidth=3,
                      shades=bands.definitions, shade_colors=shade_cols,
                      labels=labels)

tutorials/plot_02-PSDModel.py

@@ -11,7 +11,7 @@
 from specparam import SpectralModel
 
 # Import a utility to download and load example data
-from specparam.utils.download import load_example_data
+from specparam.demo import load_example_data
 
 ###################################################################################################
 
@@ -78,7 +78,7 @@
 # The above method 'report', is a convenience method that calls a series of methods:
 #
 # - :meth:`~specparam.SpectralModel.fit`: fits the power spectrum model
-# - :meth:`~specparam.SpectralModel.print_results`: prints out the results
+# - :meth:`~specparam.SpectralModel.print`: prints out the results
 # - :meth:`~specparam.SpectralModel.plot`: plots the data and model fit
 #
 # Each of these methods can also be called individually.
@@ -90,7 +90,7 @@
 fm.fit(freqs, spectrum, freq_range)
 
 # After fitting, plotting and parameter fitting can be called independently:
-# fm.print_results()
+# fm.print()
 # fm.plot()
 
 ###################################################################################################