Minor upgrade of the prodixy_xy (#7)

* Don't use TypedDict in prodigy_xy.

There was a problem when a value that was expected to be float
 (like excitation energy) was stored in text file without dot
 and was recognised as int. Now all values are treated as float
 if they are numeric and only "curves_scan" and "values_scan"
 are converted to integer.

 Casting to TypedDict was not solving that problem.

* Add Marek Kopciuszynski to Additional contributors.

AUTHORS.md

@@ -12,3 +12,4 @@ rainsty
 kcurrier6
 Tommaso (Tommaso Pincelli)
 cgfatuzzo (Claudia Fatuzzo)
+Marek Kopciuszynski

src/arpes/endstations/prodigy_xy.py

@@ -22,7 +22,7 @@
 
 import re
 from pathlib import Path
-from typing import TYPE_CHECKING, Literal, TypedDict, cast
+from typing import TYPE_CHECKING
 
 import numpy as np
 import xarray as xr
@@ -35,32 +35,9 @@
 MAP_DIMENSION = 3
 SECOND_DIM_NAME = "nonenergy"
 
-Measure_type = Literal["FAT", "SnapshotFAT", "Magnification"]
 __all__ = ["load_xy"]
 
 
-class ProdigyXYParams(TypedDict, total=False):
-    group: str
-    region: str
-    acquisition_date: str
-    analysis_method: str
-    analyzer: str
-    analyzer_lens: str
-    analyzer_slit: str
-    scan_mode: Measure_type
-    curves_scan: int
-    values_curve: int
-    dwell_time: float
-    excitation_energy: float
-    kinetic_energy: float
-    pass_energy: float
-    bias_voltage: float
-    detector_voltage: float
-    eff_workfunction: float
-    source: str
-    comment: str
-    ordinate_range: str
-
 
 class ProdigyXY:
     """Class for Prodigy exported xy file.
@@ -79,7 +56,7 @@ class ProdigyXY:
 
     def __init__(self, list_from_xy_file: list[str] | None = None) -> None:
         """Initialize."""
-        self.params: ProdigyXYParams = cast(ProdigyXYParams, {})
+        self.params: dict[str, str | float | int] = {}
         self.axis_info: dict[str, tuple[NDArray[np.float_], str]] = {}
         self.intensity: NDArray[np.float_]
         if list_from_xy_file is not None:
@@ -203,7 +180,7 @@ def load_xy(
         return data_array
 
 
-def _parse_xy_head(xy_data_params: list[str]) -> ProdigyXYParams:
+def _parse_xy_head(xy_data_params: list[str]) -> dict[str, str | int | float]:
     """Parse Common head part.
 
     Parameters
@@ -228,8 +205,12 @@ def _parse_xy_head(xy_data_params: list[str]) -> ProdigyXYParams:
             break
         key, _, value = line[1:].partition(":")
         temp_params[key.strip()] = _formatted_value(value)
-    common_params: ProdigyXYParams = cast(ProdigyXYParams, clean_keys(temp_params))
-    return common_params
+
+    temp_params = clean_keys(temp_params)
+    temp_params["curves_scan"] = int(temp_params["curves_scan"])
+    temp_params["values_curve"] = int(temp_params["values_curve"])
+
+    return temp_params
 
 
 def _parse_xy_dims(xy_data_params: list[str]) -> dict[str, NDArray[np.float_]]:
@@ -282,10 +263,9 @@ def _parse_xy_dims(xy_data_params: list[str]) -> dict[str, NDArray[np.float_]]:
     return clean_keys(xy_dims)
 
 
-def _formatted_value(value: str) -> int | float | str:
+def _formatted_value(value: str) -> float | str:
+    """Convert string value to float if possible."""
     value = value.strip()
-    if value.isnumeric():
-        return int(value)
     try:
         return float(value)
     except ValueError:

tests/test_prodigy_xy.py

@@ -25,6 +25,8 @@ def test_parameters(self, sample_xy: ProdigyXY) -> None:
         assert sample_xy.axis_info["d1"][1] == "eV"
         assert sample_xy.axis_info["d2"][1] == "nonenergy"
         assert sample_xy.axis_info["d3"][1] == "polar"
+        assert isinstance(sample_xy.params["detector_voltage"], float)
+        assert isinstance(sample_xy.params["values_curve"], int)
         np.testing.assert_almost_equal(sample_xy.params["eff_workfunction"], 4.31)
         np.testing.assert_almost_equal(sample_xy.params["excitation_energy"], 21.2182)
         np.testing.assert_almost_equal(sample_xy.axis_info["d1"][0][5], 20.080305)