💬 update type hints

src/arpes/_typing.py

@@ -184,7 +184,8 @@ class AnalyzerInfo(TypedDict, total=False):
     see analyzer_info in xarray_extensions.py (around line# 1490)
     """
 
-    name: str
+    analyzer: str
+    analyzer_name: str
     lens_mode: str | None
     lens_mode_name: str | None
     acquisition_mode: str
@@ -200,7 +201,7 @@ class AnalyzerInfo(TypedDict, total=False):
     work_function: float
     #
     is_slit_vertical: bool
-    radius: str | float
+    analyzer_radius: str | float
 
 
 class _PumpInfo(TypedDict, total=False):
@@ -337,7 +338,7 @@ class ExperimentInfo(
     AnalyzerInfo,
     total=False,
 ):
-    pass
+    analyzer_detail: AnalyzerInfo
 
 
 class ARPESAttrs(Spectrometer, LightSourceInfo, SampleInfo, total=False):

src/arpes/fits/fit_models/x_model_mixin.py

@@ -282,7 +282,7 @@ def _real_data_etc_from_xarray(
         real_data, flat_data = data.values, data.values
         assert len(real_data.shape) == self.n_dims
         coord_values = {}
-        new_dim_order: list[str]
+        new_dim_order: list[str] = []
         if self.n_dims == 1:
             coord_values["x"] = data.coords[next(iter(data.indexes))].values
         else:

src/arpes/plotting/fits.py

@@ -18,6 +18,7 @@
 
 if TYPE_CHECKING:
     import lmfit as lf
+    from numpy.typing import NDArray
 
 
 def plot_fit(model_result: lf.Model, ax: Axes | None = None) -> None:
@@ -49,11 +50,10 @@ def plot_fit(model_result: lf.Model, ax: Axes | None = None) -> None:
     ax.set_xlim(left=np.min(x), right=np.max(x))
 
 
-def plot_fits(model_results: list[lf.Model], ax: Axes | None = None) -> None:
+def plot_fits(model_results: list[lf.Model], axs: NDArray[np.object_] | None = None) -> None:
     """Plots several fits onto a grid of axes."""
     n_results = len(model_results)
-    if ax is None:
-        _fig, ax, _ax_extra = simple_ax_grid(n_results, sharex="col", sharey="row")
+    axs = axs if axs else simple_ax_grid(n_results, sharex="col", sharey="row")[1]
 
-    for axi, model_result in zip(ax, model_results, strict=False):
+    for axi, model_result in zip(axs, model_results, strict=False):
         plot_fit(model_result, ax=axi)

src/arpes/plotting/utils.py

@@ -15,7 +15,7 @@
 from datetime import UTC
 from logging import DEBUG, INFO, Formatter, StreamHandler, getLogger
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Literal, Unpack
+from typing import TYPE_CHECKING, Any, Literal, Unpack, reveal_type
 
 import matplotlib as mpl
 import matplotlib.pyplot as plt
@@ -316,7 +316,6 @@ def simple_ax_grid(
     ax, ax_rest = ax.ravel()[:n_axes], ax.ravel()[n_axes:]
     for axi in ax_rest:
         invisible_axes(axi)
-
     return fig, ax, ax_rest
 
 

src/arpes/provenance.py

@@ -52,6 +52,7 @@ class Provenance(TypedDict, total=False):
 
     VERSION: str
     jupyter_notebook_name: str
+    name: str
 
     record: Provenance
     jupyter_context: list[str]

src/arpes/utilities/jupyter.py

@@ -130,7 +130,7 @@ def get_full_notebook_information() -> NoteBookInfomation | None:
     return None
 
 
-def get_notebook_name() -> str | None:
+def get_notebook_name() -> str:
     """Gets the unqualified name of the running Jupyter notebook if not password protected.
 
     As an example, if you were running a notebook called "Doping-Analysis.ipynb"
@@ -142,7 +142,7 @@ def get_notebook_name() -> str | None:
     jupyter_info = get_full_notebook_information()
     if jupyter_info:
         return Path(jupyter_info["session"]["notebook"]["name"]).stem
-    return None
+    return ""
 
 
 def generate_logfile_path() -> Path:

src/arpes/workflow.py

@@ -146,7 +146,7 @@ def go_to_figures() -> None:
     _open_path(path)
 
 
-def get_running_context() -> tuple[Incomplete, Path]:
+def get_running_context() -> tuple[str, Path]:
     return get_notebook_name(), Path.cwd()
 
 

src/arpes/xarray_extensions.py

@@ -1590,11 +1590,14 @@ def undulator_info(self) -> dict[str, str | float | None]:
     def analyzer_detail(self) -> AnalyzerInfo:
         """Details about the analyzer, its capabilities, and metadata."""
         return {
-            "name": self._obj.attrs.get("analyzer_name", self._obj.attrs.get("analyzer", "")),
+            "analyzer_name": self._obj.attrs.get(
+                "analyzer_name",
+                self._obj.attrs.get("analyzer", ""),
+            ),
             "parallel_deflectors": self._obj.attrs.get("parallel_deflectors", False),
             "perpendicular_deflectors": self._obj.attrs.get("perpendicular_deflectors", False),
             "analyzer_type": self._obj.attrs.get("analyzer_type", ""),
-            "radius": self._obj.attrs.get("analyzer_radius", np.nan),
+            "analyzer_radius": self._obj.attrs.get("analyzer_radius", np.nan),
         }
 
     @property

tests/test_basic_data_loading.py

@@ -71,8 +71,8 @@ class TestMetadata:
                         "probe_detail": None,
                         "analyzer_detail": {
                             "analyzer_type": "hemispherical",
-                            "radius": 150,
-                            "name": "Specs PHOIBOS 150",
+                            "analyzer_radius": 150,
+                            "analyzer_name": "Specs PHOIBOS 150",
                             "parallel_deflectors": False,
                             "perpendicular_deflectors": False,
                         },
@@ -160,10 +160,10 @@ class TestMetadata:
                         "probe": None,
                         "probe_detail": None,
                         "analyzer_detail": {
-                            "name": "Scienta R8000",
+                            "analyzer_name": "Scienta R8000",
                             "parallel_deflectors": False,
                             "perpendicular_deflectors": False,
-                            "radius": np.nan,
+                            "analyzer_radius": np.nan,
                             "analyzer_type": "hemispherical",
                         },
                     },
@@ -249,8 +249,8 @@ class TestMetadata:
                         "probe_detail": None,
                         "analyzer_detail": {
                             "analyzer_type": "hemispherical",
-                            "radius": np.nan,
-                            "name": "Scienta R4000",
+                            "analyzer_radius": np.nan,
+                            "analyzer_name": "Scienta R4000",
                             "parallel_deflectors": False,
                             "perpendicular_deflectors": True,
                         },