Fix asymmetry and save/restore peak profile type in experiment CIF (#144)

* Update save_as paths to include 'data/' directory and adjust test function to use temporary directory

* Add crysfml

* Update notebooks

* Clean up

* Add simple integration test for crysfml

* Bump pycrysfml to 0.2.1

* Add pytest marker to neutron_pd_cwl_lbco_crysfml test

* Extend package test script by adding pycrysfml

* Fix scipp integration test

* Move jupyterlab and pixi-kernel out from pyproject.toml

* Remove unnecessary libcxx addition for osx-64 in test.yml

* Add custom PyPI index support for pycrysfml in test.yml

* Update .gitignore to include data directory for tutorial runtime

* Apply latest templates

* Add temporary rule ignores for docstring and datetime checks in pyproject.toml

* Apply new templates

* Update index hash for data integrity in utils.py

* Add reverse flag to fit_sequential for reverse-order processing

* Update tutorials index

* Update tutorial

* Add initial structure and analysis configuration files

* Fix asymmetry and save/restore peak_profile_type in experiment CIF

* Refactor switchable-type restore into _restore_switchable_types

* Update test example

* Update data-index.json known hash in utils.py

Author: AndrewSazonov

docs/docs/tutorials/ed-13.py

@@ -575,7 +575,7 @@
 # #### Show Free Parameters
 #
 # We can check which parameters are free to be refined by calling the
-# `show_free_params` method of the `analysis` object of the project.
+# `free_params` method of the `analysis.display` object of the project.
 
 # %% [markdown] tags=["doc-link"]
 # 📖 See

docs/docs/tutorials/ed-17.py

@@ -270,6 +270,12 @@
 # %%
 project.analysis.fit()
 
+# %% [markdown]
+# #### Compare measured and calculated patterns for the first fit.
+
+# %%
+project.plotter.plot_meas_vs_calc(expt_name='d20', show_residual=True)
+
 # %% [markdown]
 # #### Run Sequential Fitting
 #
@@ -301,11 +307,20 @@ def extract_diffrn(file_path):
     data_dir=data_dir,
     extract_diffrn=extract_diffrn,
     max_workers='auto',
+    reverse=True,
 )
 
 # %% [markdown]
 # #### Replay a Dataset
 #
+# Apply fitted parameters from the first CSV row and plot the result.
+
+# %%
+project.apply_params_from_csv(row_index=0)
+project.plotter.plot_meas_vs_calc(expt_name='d20', show_residual=True)
+
+# %% [markdown]
+#
 # Apply fitted parameters from the last CSV row and plot the result.
 
 # %%

src/easydiffraction/analysis/calculators/cryspy.py

@@ -297,6 +297,13 @@ def _update_experiment_in_cryspy_dict(
                 cryspy_resolution[3] = experiment.peak.broad_lorentz_x.value
                 cryspy_resolution[4] = experiment.peak.broad_lorentz_y.value
 
+                if 'asymmetry_parameters' in cryspy_expt_dict:
+                    cryspy_asymmetry = cryspy_expt_dict['asymmetry_parameters']
+                    cryspy_asymmetry[0] = experiment.peak.asym_empir_1.value
+                    cryspy_asymmetry[1] = experiment.peak.asym_empir_2.value
+                    cryspy_asymmetry[2] = experiment.peak.asym_empir_3.value
+                    cryspy_asymmetry[3] = experiment.peak.asym_empir_4.value
+
             elif experiment.type.beam_mode.value == BeamModeEnum.TIME_OF_FLIGHT:
                 cryspy_expt_name = f'tof_{experiment.name}'
                 cryspy_expt_dict = cryspy_dict[cryspy_expt_name]
@@ -507,6 +514,10 @@ def _cif_peak_section(
             'broad_gauss_w': '_pd_instr_resolution_W',
             'broad_lorentz_x': '_pd_instr_resolution_X',
             'broad_lorentz_y': '_pd_instr_resolution_Y',
+            'asym_empir_1': '_pd_instr_reflex_asymmetry_p1',
+            'asym_empir_2': '_pd_instr_reflex_asymmetry_p2',
+            'asym_empir_3': '_pd_instr_reflex_asymmetry_p3',
+            'asym_empir_4': '_pd_instr_reflex_asymmetry_p4',
         }
     elif expt_type.beam_mode.value == BeamModeEnum.TIME_OF_FLIGHT:
         peak_mapping = {
@@ -522,7 +533,7 @@ def _cif_peak_section(
 
     cif_lines.append('')
     for local_attr_name, engine_key_name in peak_mapping.items():
-        attr_obj = getattr(peak, local_attr_name)
+        attr_obj = getattr(peak, local_attr_name, None)
         if attr_obj is not None:
             cif_lines.append(f'{engine_key_name} {attr_obj.value}')
 

src/easydiffraction/core/singleton.py

@@ -1,11 +1,15 @@
 # SPDX-FileCopyrightText: 2026 EasyScience contributors <https://github.com/easyscience>
 # SPDX-License-Identifier: BSD-3-Clause
 
+from __future__ import annotations
+
 from typing import Any
 from typing import Self
 
 from asteval import Interpreter
 
+from easydiffraction.utils.logging import log
+
 # ======================================================================
 
 
@@ -111,6 +115,20 @@ def apply(self) -> None:
                 # Evaluate the RHS expression using the current values
                 rhs_value = ae(rhs_expr)
 
+                # asteval silently returns None for undefined names
+                # instead of raising an exception; errors are stored in
+                # ae.error.
+                if ae.error:
+                    error_msgs = '; '.join(str(e.get_error()) for e in ae.error)
+                    ae.error.clear()
+                    log.error(
+                        f"Constraint '{lhs_alias} = {rhs_expr}' could not be "
+                        f'evaluated: {error_msgs}. '
+                        f'Make sure every name in the expression is registered '
+                        f'as an alias via analysis.aliases.create().',
+                        exc_type=ValueError,
+                    )
+
                 # Get the actual parameter object we want to update
                 param = self._alias_to_param[lhs_alias].param
 

src/easydiffraction/datablocks/experiment/categories/peak/base.py

@@ -2,7 +2,12 @@
 # SPDX-License-Identifier: BSD-3-Clause
 """Base class for peak profile categories."""
 
+from __future__ import annotations
+
 from easydiffraction.core.category import CategoryItem
+from easydiffraction.core.validation import AttributeSpec
+from easydiffraction.core.variable import StringDescriptor
+from easydiffraction.io.cif.handler import CifHandler
 
 
 class PeakBase(CategoryItem):
@@ -11,3 +16,24 @@ class PeakBase(CategoryItem):
     def __init__(self) -> None:
         super().__init__()
         self._identity.category_code = 'peak'
+
+        type_info = getattr(type(self), 'type_info', None)
+        default_tag = type_info.tag if type_info is not None else ''
+        self._profile_type: StringDescriptor = StringDescriptor(
+            name='profile_type',
+            description='Active peak profile type tag',
+            value_spec=AttributeSpec(default=default_tag),
+            cif_handler=CifHandler(names=['_peak.profile_type']),
+        )
+
+    @property
+    def profile_type(self) -> StringDescriptor:
+        """
+        CIF identifier for the active peak profile type.
+
+        Returns
+        -------
+        StringDescriptor
+            The descriptor holding the profile type tag string.
+        """
+        return self._profile_type

src/easydiffraction/datablocks/experiment/categories/peak/cwl.py

@@ -57,7 +57,7 @@ class CwlSplitPseudoVoigt(
         beam_mode=frozenset({BeamModeEnum.CONSTANT_WAVELENGTH}),
     )
     calculator_support = CalculatorSupport(
-        calculators=frozenset({CalculatorEnum.CRYSPY, CalculatorEnum.CRYSFML}),
+        calculators=frozenset({CalculatorEnum.CRYSPY}),
     )
 
     def __init__(self) -> None:
@@ -81,7 +81,7 @@ class CwlThompsonCoxHastings(
         beam_mode=frozenset({BeamModeEnum.CONSTANT_WAVELENGTH}),
     )
     calculator_support = CalculatorSupport(
-        calculators=frozenset({CalculatorEnum.CRYSPY, CalculatorEnum.CRYSFML}),
+        calculators=frozenset({CalculatorEnum.CRYSFML}),
     )
 
     def __init__(self) -> None:

src/easydiffraction/datablocks/experiment/categories/peak/cwl_mixins.py

@@ -157,7 +157,7 @@ def __init__(self) -> None:
             description='Empirical asymmetry coefficient p1',
             units='',
             value_spec=AttributeSpec(
-                default=0.1,
+                default=0.0,
                 validator=RangeValidator(),
             ),
             cif_handler=CifHandler(names=['_peak.asym_empir_1']),
@@ -167,7 +167,7 @@ def __init__(self) -> None:
             description='Empirical asymmetry coefficient p2',
             units='',
             value_spec=AttributeSpec(
-                default=0.2,
+                default=0.0,
                 validator=RangeValidator(),
             ),
             cif_handler=CifHandler(names=['_peak.asym_empir_2']),
@@ -177,7 +177,7 @@ def __init__(self) -> None:
             description='Empirical asymmetry coefficient p3',
             units='',
             value_spec=AttributeSpec(
-                default=0.3,
+                default=0.0,
                 validator=RangeValidator(),
             ),
             cif_handler=CifHandler(names=['_peak.asym_empir_3']),
@@ -187,7 +187,7 @@ def __init__(self) -> None:
             description='Empirical asymmetry coefficient p4',
             units='',
             value_spec=AttributeSpec(
-                default=0.4,
+                default=0.0,
                 validator=RangeValidator(),
             ),
             cif_handler=CifHandler(names=['_peak.asym_empir_4']),

src/easydiffraction/datablocks/experiment/item/base.py

@@ -23,6 +23,7 @@
     LinkedPhasesFactory,
 )
 from easydiffraction.datablocks.experiment.categories.peak.factory import PeakFactory
+from easydiffraction.io.cif.parse import read_cif_str
 from easydiffraction.io.cif.serialize import experiment_to_cif
 from easydiffraction.utils.logging import console
 from easydiffraction.utils.logging import log
@@ -122,6 +123,22 @@ def show_current_diffrn_type(self) -> None:
         console.paragraph('Current diffrn type')
         console.print(self.diffrn_type)
 
+    def _restore_switchable_types(self, block: object) -> None:
+        """
+        Restore switchable category types from a parsed CIF block.
+
+        Called by the factory immediately after the experiment object is
+        created and before any category parameters are loaded from CIF.
+        Subclasses with switchable categories must override this method
+        and call their ``_set_<type>`` private setter for each category
+        whose active implementation is identified by a CIF type tag.
+
+        Parameters
+        ----------
+        block : object
+            Parsed ``gemmi.cif.Block`` to read type tags from.
+        """
+
     @property
     def as_cif(self) -> str:
         """Serialize this experiment to a CIF fragment."""
@@ -762,3 +779,47 @@ def show_current_peak_profile_type(self) -> None:
         """Print the currently selected peak profile type."""
         console.paragraph('Current peak profile type')
         console.print(self.peak_profile_type)
+
+    def _set_peak_profile_type(self, new_type: str) -> None:
+        """
+        Switch the peak profile type without console output.
+
+        Used internally by the factory when restoring state from CIF so
+        that no user-facing warnings or progress messages are emitted.
+        Invalid type tags are logged as warnings and ignored.
+
+        Parameters
+        ----------
+        new_type : str
+            Peak profile type tag (e.g. ``'split pseudo-voigt'``).
+        """
+        supported = PeakFactory.supported_for(
+            scattering_type=self.type.scattering_type.value,
+            beam_mode=self.type.beam_mode.value,
+        )
+        supported_tags = [k.type_info.tag for k in supported]
+        if new_type not in supported_tags:
+            log.warning(
+                f"Unsupported peak profile '{new_type}' in CIF. "
+                f'Supported: {supported_tags}. Keeping default.',
+            )
+            return
+        self._peak = PeakFactory.create(new_type)
+        self._peak_profile_type = new_type
+
+    def _restore_switchable_types(self, block: object) -> None:
+        """
+        Restore switchable category types for powder experiments.
+
+        Reads ``_peak.profile_type`` from the CIF block and switches to
+        the matching peak implementation before category parameters are
+        loaded, ensuring profile-specific descriptors are present.
+
+        Parameters
+        ----------
+        block : object
+            Parsed ``gemmi.cif.Block`` to read type tags from.
+        """
+        peak_type = read_cif_str(block, '_peak.profile_type')
+        if peak_type is not None:
+            self._set_peak_profile_type(peak_type)

src/easydiffraction/datablocks/experiment/item/factory.py

@@ -120,6 +120,10 @@ def _from_gemmi_block(
         expt_class = cls._resolve_class(expt_type)
         expt_obj = expt_class(name=name, type=expt_type)
 
+        # Restore switchable category types before loading parameters
+        # so implementation-specific descriptors exist for from_cif.
+        expt_obj._restore_switchable_types(block)
+
         for category in expt_obj.categories:
             category.from_cif(block)
 

src/easydiffraction/datablocks/experiment/item/total_pd.py

@@ -14,6 +14,7 @@
 from easydiffraction.datablocks.experiment.item.enums import SampleFormEnum
 from easydiffraction.datablocks.experiment.item.enums import ScatteringTypeEnum
 from easydiffraction.datablocks.experiment.item.factory import ExperimentFactory
+from easydiffraction.utils.logging import log
 
 if TYPE_CHECKING:
     from easydiffraction.datablocks.experiment.categories.experiment_type import ExperimentType
@@ -86,7 +87,7 @@ def _load_ascii_data_to_experiment(self, data_path: str) -> int:
 
         default_sy = 0.03
         if data.shape[1] < _MIN_COLUMNS_XY_SY:
-            print(f'Warning: No uncertainty (sy) column provided. Defaulting to {default_sy}.')
+            log.warning(f'No uncertainty (sy) column provided. Defaulting to {default_sy}.')
 
         x = data[:, 0]
         y = data[:, 1]