rename "process" into "calculate" to better illustrate what is done

docs/apidoc/glassure.configuration.rst

@@ -4,7 +4,7 @@ glassure.configuration module
 This module contains all configurations classes necessary for the glassure package.
 The main entrypoints are the :class:`glassure.configuration.CalculationConfig` and :class: `glassure.configuration.DataModel` 
 pydantic models containing all necessary information for the analysis. These two configurations can then be used analysis
-parameters for the *process* function in the :mod:`glassure.calc` module to perform the analysis. The output of the calculation
+parameters for the :meth:`glassure.calc.calculate` calculate to perform the analysis. The output of the calculation
 will be a :class:`glassure.configuration.Result` object containing the results of the analysis.
 The models are then further split into submodels for better readability and maintainability.
 

glassure/calc.py

@@ -61,7 +61,7 @@ def create_process_configs(
     return data_config, calculation_config
 
 
-def process(data_config: DataConfig, calculation_config: CalculationConfig) -> Pattern:
+def calculate(data_config: DataConfig, calculation_config: CalculationConfig) -> Pattern:
     """
     Process the input configuration and return the result.
     """
@@ -214,7 +214,7 @@ def process(data_config: DataConfig, calculation_config: CalculationConfig) -> P
     )
 
     res = Result(
-        calculation_config=config,
+        calculation_config=config.model_copy(deep=True),
         sq=sq,
         fr=fr,
         gr=gr,

tests/test_calc.py

@@ -2,7 +2,7 @@
 import numpy as np
 
 from glassure.pattern import Pattern
-from glassure.calc import process, create_process_configs
+from glassure.calc import calculate, create_process_configs
 from glassure.configuration import OptimizeConfig, IntNormalization
 
 
@@ -29,7 +29,7 @@ def prepare_input():
 def test_process_input_base():
     input = prepare_input()
 
-    res = process(*input)
+    res = calculate(*input)
 
     assert len(res.sq.x) > 0
     assert len(res.fr.x) > 0
@@ -38,108 +38,108 @@ def test_process_input_base():
 
 def test_process_input_optimize_sq():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.optimize = OptimizeConfig()
-    res_optimize = process(data_input, calculation_input)
+    res_optimize = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_optimize.sq.y)
 
 
 def test_process_input_norm_int():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.normalization = IntNormalization()
-    res_int = process(data_input, calculation_input)
+    res_int = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_int.sq.y)
 
 
 def test_process_input_modification_fcn():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.use_modification_fcn = True
-    res_mod = process(data_input, calculation_input)
+    res_mod = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.fr.y, res_mod.fr.y)
 
 
 def test_process_input_linear_extrapolation():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.extrapolation.method = "linear"
-    res_lin = process(data_input, calculation_input)
+    res_lin = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_lin.sq.y)
 
 
 def test_process_input_spline_extrapolation():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.extrapolation.method = "spline"
-    res_spline = process(data_input, calculation_input)
+    res_spline = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_spline.sq.y)
 
 
 def test_process_input_poly_extrapolation():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.extrapolation.method = "poly"
-    res_poly = process(data_input, calculation_input)
+    res_poly = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_poly.sq.y)
 
 
 def test_process_extrapolation_with_s0():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.extrapolation.method = "linear"
     calculation_input.transform.extrapolation.s0 = 0.1
-    res_s0 = process(data_input, calculation_input)
+    res_s0 = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_s0.sq.y)
 
 
 def test_process_input_kn_correction():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.kn_correction = True
     calculation_input.transform.wavelength = 0.22
 
-    res_kn = process(data_input, calculation_input)
+    res_kn = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_kn.sq.y)
 
 
 def test_process_input_with_container_scattering():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.normalization.container_scattering = {"C": 1}
 
-    res_container = process(data_input, calculation_input)
+    res_container = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_container.sq.y)
 
 
 def test_process_input_with_container_scattering_and_kn():
     data_input, calculation_input = prepare_input()
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
     calculation_input.transform.kn_correction = True
     calculation_input.transform.wavelength = 0.22
 
-    res = process(data_input, calculation_input)
+    res = calculate(data_input, calculation_input)
 
     calculation_input.transform.normalization.container_scattering = {"C": 1}
 
-    res_container = process(data_input, calculation_input)
+    res_container = calculate(data_input, calculation_input)
 
     assert not np.array_equal(res.sq.y, res_container.sq.y)