🚀 New ReflectionsData and ReflectionsCollection classes

xtl.diffraction.reflections.reflections:ReflectionsData
- New class for representing one column of some type of diffraction
  reflections data, e.g. intensities, phases, etc
- This is a wrapper around reciprocalspaceship.DataSet, which in turn is
  a subclass of pandas.DataFrame
- The class holds information about unit-cell, space group and whether
  the reflections are merged or not
- The reflections are indexed with a three-column (H,K,L) pd.MultiIndex
- .dtype and .mtz_type properties for retrieving the rs.MTZDtype and
  MTZ column type
- .as_dtype() and .as_mtz_type() methods for changing the rs.MTZDtype
  and MTZ column type
- Can be instantiated directly from Python/NumPy arrays, Pandas
  dataframes, gemmi.Mtz instances or rs.DataSeries
- Alternatively, it can be instantiated from MTZ or CIF files by
  specifying the file and column name in the .from_mtz() and .from_cif()
  methods

xtl.diffraction.reflections.reflections:ReflectionsCollection
- New class for representing multiple columns of diffraction reflections
  data, e.g. intensities, phases, etc
- This is a wrapper around reciprocalspaceship.DataSet, which in turn is
  a subclass of pandas.DataFrame
- The class holds information about unit-cell, space group and whether
  the reflections are merged or not
- The reflections are indexed with a three-column (H,K,L) pd.MultiIndex
- .dtypes and .mtz_types properties for retrieving the rs.MTZDtype and
  MTZ column types
- .as_dtype() and .as_mtz_type() methods for changing the rs.MTZDtype
  and MTZ column types
- Can be instantiated directly from Python/NumPy arrays, Pandas
  dataframes, gemmi.Mtz instances or rs.DataSeries
- Alternatively, it can be instantiated from MTZ or CIF files by
  specifying the file in the .from_mtz() and .from_cif() methods

xtl.diffraction.reflections.mtz_types:mtz_types
- Dictionary mapping of str -> rs.MTZDtype for all MTZ column types

pyproject.toml & requirements.txt
- Added reciprocalspaceship to the dependencies list

Author: dtriand

pyproject.toml

@@ -44,6 +44,7 @@ dependencies = [
     "pydantic>=2.11.5",
     "pyfai>=2023.9.0,<2024.10",
     "pyxray>=1.7.0",
+    "reciprocalspaceship>=1.0.3",
     "requests>=2.31.0",
     "rich>=13.6.0",
     "tabulate>=0.8.10",

requirements.txt

@@ -13,6 +13,7 @@ pint==0.19.2
 pydantic==2.11.5
 pyfai==2023.9.0
 pyxray==1.7.0
+reciprocalspaceship==1.0.3
 requests==2.31.0
 rich==13.9.4
 sphinx==8.1.3

src/xtl/diffraction/reflections/__init__.py

@@ -0,0 +1,5 @@
+__all__ = ['ReflectionsData', 'ReflectionsCollection', 'mtz_types']
+
+from .mtz_types import mtz_types
+from .reflections import ReflectionsData, ReflectionsCollection
+

src/xtl/diffraction/reflections/mtz_types.py

@@ -0,0 +1,13 @@
+import reciprocalspaceship as rs
+from reciprocalspaceship.dtypes.base import MTZDtype
+
+
+mtz_types: dict[str, MTZDtype] = {}
+"""Dictionary of MTZ column types to their corresponding rs.MTZDtype class"""
+
+mtz_summary = rs.summarize_mtz_dtypes(print_summary=False)
+for i in range(mtz_summary.shape[0]):
+    # Columns: ['MTZ Code', 'Name', 'Class', 'Internal']
+    cls_name = mtz_summary['Class'][i]
+    mtz_type = mtz_summary['MTZ Code'][i]
+    mtz_types[mtz_type] = getattr(rs.dtypes, cls_name)