Enhance Plotting and Display Features, Improve Calibration Handling and Consistency

.github/workflows/building-deploying-docs.yml

@@ -4,7 +4,7 @@ on:
   # Trigger the workflow on push
   push:
     # To the develop and master branches
-    branches: [develop, master, docs]
+    branches: [develop, master, docs, d-spacing]
 
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
@@ -101,7 +101,7 @@ jobs:
       - name: Convert ${{ env.NOTEBOOKS_DIR }}/*.py to docs/${{env.NOTEBOOKS_DIR }}/*.ipynb
         run: |
           cp -R ${{ env.NOTEBOOKS_DIR }}/data docs/${{ env.NOTEBOOKS_DIR }}/
-          jupytext ${{ env.NOTEBOOKS_DIR }}/*.py --to ipynb
+          jupytext ${{ env.NOTEBOOKS_DIR }}/*.py --from py:percent --to ipynb
           mv ${{ env.NOTEBOOKS_DIR }}/*.ipynb docs/${{ env.NOTEBOOKS_DIR }}/
 
       # The following step is needed to avoid the following message during the build:

.github/workflows/testing-code.yaml

@@ -23,6 +23,11 @@ concurrency:
     ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
+env:
+  # Set the environment variables to be used in all jobs defined in this workflow
+  # Set the CI_BRANCH environment variable to be the branch name
+  CI_BRANCH: ${{ github.head_ref || github.ref_name }}
+
 jobs:
   testing-code:
 

.github/workflows/testing-tutorials.yaml

@@ -14,6 +14,11 @@ concurrency:
     ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
+env:
+  # Set the environment variables to be used in all jobs defined in this workflow
+  # Set the CI_BRANCH environment variable to be the branch name
+  CI_BRANCH: ${{ github.head_ref || github.ref_name }}
+
 jobs:
   testing-tutorials:
 

docs/mkdocs.yml

@@ -77,6 +77,8 @@ nav:
           - Ni pd-neut-cwl: tutorials/pdf_pd-neut-cwl_Ni.ipynb
           - Si pd-neut-tof: tutorials/pdf_pd-neut-tof_Si-NOMAD.ipynb
           - NaCl pd-xray: tutorials/pdf_pd-xray_NaCl.ipynb
+      - Workshops & Schools:
+          - 2025 DMSC: tutorials/dmsc-summer-school-2025_analysis-powder-diffraction.ipynb
   - API Reference:
       - API Reference: api-reference/index.md
       - core: api-reference/core.md

docs/tutorials/index.md

@@ -66,3 +66,11 @@ The tutorials are organized into the following categories.
 - [NaCl `pd-xray`](pdf_pd-xray_NaCl.ipynb) –
   Demonstrates a PDF analysis of NaCl using data collected from an X-ray
   powder diffraction experiment.
+
+## Workshops & Schools
+
+- [2025 DMSC](dmsc-summer-school-2025_analysis-powder-diffraction.ipynb) –
+  A workshop tutorial that demonstrates a Rietveld refinement of the 
+  La0.5Ba0.5CoO3 crystal structure using time-of-flight neutron powder 
+  diffraction data simulated with McStas. This tutorial is designed for 
+  the ESS DMSC Summer School 2025.

src/easydiffraction/__init__.py

@@ -19,7 +19,10 @@
 from easydiffraction.summary import Summary
 
 # Utils
-from easydiffraction.utils.utils import download_from_repository
+from easydiffraction.utils.utils import (
+    download_from_repository,
+    get_value_from_xye_header
+)
 from easydiffraction.utils.formatting import (
     chapter,
     section,
@@ -39,5 +42,6 @@
     "chapter",
     "section",
     "paragraph",
-    'download_from_repository'
+    "download_from_repository",
+    "get_value_from_xye_header"
 ]

src/easydiffraction/analysis/analysis.py

@@ -2,7 +2,10 @@
 import numpy as np
 from typing import List, Optional, Union
 
-from easydiffraction.utils.utils import render_table
+from easydiffraction.utils.utils import (
+    render_cif,
+    render_table
+)
 from easydiffraction.utils.formatting import (
     paragraph,
     warning
@@ -204,8 +207,15 @@ def how_to_access_parameters(self) -> None:
             print(warning(f"No parameters found."))
             return
 
-        columns_headers = ['Code variable', 'Unique ID for CIF']
-        columns_alignment = ["left", "left"]
+        columns_headers = ['datablock',
+                           'category',
+                           'entry',
+                           'parameter',
+                           'How to Access in Python Code',
+                           'Unique Identifier for CIF Constraints']
+
+        columns_alignment = ['left', 'left', 'left', 'left', 'left', 'left']
+
         columns_data = []
         project_varname = self.project._varname
         for datablock_type, params in params.items():
@@ -215,12 +225,17 @@ def how_to_access_parameters(self) -> None:
                     category_key = param.category_key
                     entry_id = param.collection_entry_id
                     param_key = param.name
-                    variable = f"{project_varname}.{datablock_type}['{datablock_id}'].{category_key}"
+                    code_variable = f"{project_varname}.{datablock_type}['{datablock_id}'].{category_key}"
                     if entry_id:
-                        variable += f"['{entry_id}']"
-                    variable += f".{param_key}"
-                    uid = param._generate_human_readable_unique_id()
-                    columns_data.append([variable, uid])
+                        code_variable += f"['{entry_id}']"
+                    code_variable += f".{param_key}"
+                    cif_uid = param._generate_human_readable_unique_id()
+                    columns_data.append([datablock_id,
+                                         category_key,
+                                         entry_id,
+                                         param_key,
+                                         code_variable,
+                                         cif_uid])
 
         print(paragraph("How to access parameters"))
         render_table(columns_headers=columns_headers,
@@ -384,14 +399,19 @@ def fit(self):
 
         if self.fit_mode == 'joint':
             print(paragraph(f"Using all experiments 🔬 {experiment_ids} for '{self.fit_mode}' fitting"))
-            self.fitter.fit(sample_models, experiments, calculator, weights=self.joint_fit_experiments)
+            self.fitter.fit(sample_models,
+                            experiments,
+                            calculator,
+                            weights=self.joint_fit_experiments)
         elif self.fit_mode == 'single':
             for expt_name in experiments.ids:
                 print(paragraph(f"Using experiment 🔬 '{expt_name}' for '{self.fit_mode}' fitting"))
                 experiment = experiments[expt_name]
                 dummy_experiments = Experiments()  # TODO: Find a better name
                 dummy_experiments.add(experiment)
-                self.fitter.fit(sample_models, dummy_experiments, calculator)
+                self.fitter.fit(sample_models,
+                                dummy_experiments,
+                                calculator)
         else:
             raise NotImplementedError(f"Fit mode {self.fit_mode} not implemented yet.")
 
@@ -417,14 +437,6 @@ def as_cif(self):
         return "\n".join(lines)
 
     def show_as_cif(self) -> None:
-        cif_text = self.as_cif()
-        lines = cif_text.splitlines()
-        max_width = max(len(line) for line in lines)
-        padded_lines = [f"│ {line.ljust(max_width)} │" for line in lines]
-        top = f"╒{'═' * (max_width + 2)}╕"
-        bottom = f"╘{'═' * (max_width + 2)}╛"
-
-        print(paragraph(f"Analysis 🧮 info as cif"))
-        print(top)
-        print("\n".join(padded_lines))
-        print(bottom)
+        cif_text: str = self.as_cif()
+        paragraph_title: str = paragraph(f"Analysis 🧮 info as cif")
+        render_cif(cif_text, paragraph_title)

src/easydiffraction/analysis/calculators/calculator_base.py

@@ -3,6 +3,7 @@
 from typing import List, Any
 
 from easydiffraction.core.singletons import ConstraintsHandler
+from easydiffraction.sample_models.sample_model import SampleModel
 from easydiffraction.sample_models.sample_models import SampleModels
 from easydiffraction.experiments.experiment import Experiment
 
@@ -22,16 +23,22 @@ def engine_imported(self) -> bool:
         pass
 
     @abstractmethod
-    def calculate_structure_factors(self, sample_model: SampleModels, experiment: Experiment) -> None:
+    def calculate_structure_factors(
+            self,
+            sample_model: SampleModel,
+            experiment: Experiment
+    ) -> None:
         """
         Calculate structure factors for a single sample model and experiment.
         """
         pass
 
-    def calculate_pattern(self,
-                          sample_models: SampleModels,
-                          experiment: Experiment,
-                          called_by_minimizer: bool = False) -> np.ndarray:
+    def calculate_pattern(
+            self,
+            sample_models: SampleModels,
+            experiment: Experiment,
+            called_by_minimizer: bool = False
+    ) -> np.ndarray:
         """
         Calculate the diffraction pattern for multiple sample models and a single experiment.
 
@@ -84,10 +91,12 @@ def calculate_pattern(self,
         return y_calc_total
 
     @abstractmethod
-    def _calculate_single_model_pattern(self,
-                                        sample_model: SampleModels,
-                                        experiment: Experiment,
-                                        called_by_minimizer: bool) -> np.ndarray:
+    def _calculate_single_model_pattern(
+            self,
+            sample_model: SampleModels,
+            experiment: Experiment,
+            called_by_minimizer: bool
+    ) -> np.ndarray:
         """
         Calculate the diffraction pattern for a single sample model and experiment.
 
@@ -101,7 +110,11 @@ def _calculate_single_model_pattern(self,
         """
         pass
 
-    def _get_valid_linked_phases(self, sample_models: SampleModels, experiment: Experiment) -> List[Any]:
+    def _get_valid_linked_phases(
+            self,
+            sample_models: SampleModels,
+            experiment: Experiment
+    ) -> List[Any]:
         """
         Get valid linked phases from the experiment.
 
@@ -126,4 +139,4 @@ def _get_valid_linked_phases(self, sample_models: SampleModels, experiment: Expe
         if not valid_linked_phases:
             print('Warning: None of the linked phases found in Sample Models. Returning empty pattern.')
 
-        return valid_linked_phases
+        return valid_linked_phases

src/easydiffraction/analysis/calculators/calculator_crysfml.py

@@ -1,16 +1,18 @@
 import numpy as np
 from typing import Any, Dict, List, Union
-from .calculator_base import CalculatorBase
-from easydiffraction.utils.formatting import warning
+
 from easydiffraction.sample_models.sample_models import SampleModels
 from easydiffraction.sample_models.sample_models import SampleModel
 from easydiffraction.experiments.experiment import Experiment
 from easydiffraction.experiments.experiments import Experiments
 
+from .calculator_base import CalculatorBase
+
 try:
     from pycrysfml import cfml_py_utilities
+    print("✅ 'pycrysfml' calculation engine is successfully imported.")
 except ImportError:
-    print(warning('"pycrysfml" module not found. This calculator will not work.'))
+    print("⚠️ 'pycrysfml' module not found. This calculation engine will not be available.")
     cfml_py_utilities = None
 
 
@@ -25,7 +27,11 @@ class CrysfmlCalculator(CalculatorBase):
     def name(self) -> str:
         return "crysfml"
 
-    def calculate_structure_factors(self, sample_models: SampleModels, experiments: Experiments) -> None:
+    def calculate_structure_factors(
+            self,
+            sample_models: SampleModels,
+            experiments: Experiments
+    ) -> None:
         """
         Call Crysfml to calculate structure factors.
 
@@ -61,7 +67,11 @@ def _calculate_single_model_pattern(
             y = []
         return y
 
-    def _adjust_pattern_length(self, pattern: List[float], target_length: int) -> List[float]:
+    def _adjust_pattern_length(
+            self,
+            pattern: List[float],
+            target_length: int
+    ) -> List[float]:
         """
         Adjusts the length of the pattern to match the target length.
 
@@ -77,7 +87,11 @@ def _adjust_pattern_length(self, pattern: List[float], target_length: int) -> Li
             return pattern[:target_length]
         return pattern
 
-    def _crysfml_dict(self, sample_model: SampleModels, experiment: Experiment) -> Dict[str, Union[Experiment, SampleModel]]:
+    def _crysfml_dict(
+            self,
+            sample_model: SampleModels,
+            experiment: Experiment
+    ) -> Dict[str, Union[Experiment, SampleModel]]:
         """
         Converts the sample model and experiment into a dictionary format for Crysfml.
 
@@ -95,7 +109,10 @@ def _crysfml_dict(self, sample_model: SampleModels, experiment: Experiment) -> D
             "experiments": [experiment_dict]
         }
 
-    def _convert_sample_model_to_dict(self, sample_model: SampleModels) -> Dict[str, SampleModel]:
+    def _convert_sample_model_to_dict(
+            self,
+            sample_model: SampleModel
+    ) -> Dict[str, Any]:
         """
         Converts a sample model into a dictionary format.
 
@@ -133,7 +150,10 @@ def _convert_sample_model_to_dict(self, sample_model: SampleModels) -> Dict[str,
 
         return sample_model_dict
 
-    def _convert_experiment_to_dict(self, experiment: Experiment) -> Dict[str, Any]:
+    def _convert_experiment_to_dict(
+            self,
+            experiment: Experiment
+    ) -> Dict[str, Any]:
         """
         Converts an experiment into a dictionary format.
 
@@ -148,8 +168,8 @@ def _convert_experiment_to_dict(self, experiment: Experiment) -> Dict[str, Any]:
         peak = getattr(experiment, "peak", None)
 
         x_data = experiment.datastore.pattern.x
-        two_theta_min = float(x_data.min())
-        two_theta_max = float(x_data.max())
+        twotheta_min = float(x_data.min())
+        twotheta_max = float(x_data.max())
 
         exp_dict = {
             "NPD": {
@@ -163,9 +183,9 @@ def _convert_experiment_to_dict(self, experiment: Experiment) -> Dict[str, Any]:
                 #"_pd_instr_reflex_s_l": peak_asymm.s_l.value if peak_asymm else 0.0,
                 #"_pd_instr_reflex_d_l": peak_asymm.d_l.value if peak_asymm else 0.0,
                 "_pd_meas_2theta_offset": instrument.calib_twotheta_offset.value if instrument else 0.0,
-                "_pd_meas_2theta_range_min": two_theta_min,
-                "_pd_meas_2theta_range_max": two_theta_max,
-                "_pd_meas_2theta_range_inc": (two_theta_max - two_theta_min) / len(x_data)
+                "_pd_meas_2theta_range_min": twotheta_min,
+                "_pd_meas_2theta_range_max": twotheta_max,
+                "_pd_meas_2theta_range_inc": (twotheta_max - twotheta_min) / len(x_data)
             }
         }