🔥 Remove (move to legacy_files) peaks.py

Changes.md

@@ -43,6 +43,10 @@ Major Changes from 3.0.1
 
     - The functions in this module have not been used and are unlikely to be used in the future.
 
+  - Remove fits/fit_model/peaks.py
+
+    - The classes (fitting models) defined in this module are essentially needless, **as you can use the + operator on the Model instances.**
+
   - modules that use the Bokeh.
 
     There is a dependency problem among bokeh, tornard, and Jupyter, which I cannot fix because I'm haven't use Bokeh. But note that hvplot can work with the current version.

src/arpes/fits/fit_models/peaks.py → legacy_files/peaks.py

@@ -1,4 +1,7 @@
-"""Includes multi-peak model definitions."""
+"""Includes multi-peak model definitions.
+
+arpes/fits/fit_models/peaks.py
+"""
 
 from __future__ import annotations
 

pyproject.toml

@@ -160,6 +160,7 @@ convention = "google"
 "tests/*" = ["PLR2004", "ERA001"]
 "resources/*" = ["INP001"]
 "src/arpes/endstations/igor_utils.py" = ["S605"]
+"legacy_files/*" = ["ALL"]
 
 [tool.ruff.format]
 # Like Black, use double quotes for strings.

src/arpes/fits/utilities.py

@@ -27,6 +27,7 @@
 from arpes.utilities import normalize_to_spectrum
 
 from . import mp_fits
+from .hot_pool import hot_pool
 
 if TYPE_CHECKING:
     from collections.abc import Iterable, Sequence
@@ -126,8 +127,8 @@ def broadcast_model(  # noqa: PLR0913
     weights: xr.DataArray | None = None,
     prefixes: Sequence[str] = "",
     window: xr.DataArray | None = None,
-    parallelize: bool | None = None,
     *,
+    parallelize: bool | None = None,
     progress: bool = True,
     safe: bool = False,
 ) -> xr.Dataset:
@@ -201,8 +202,6 @@ def broadcast_model(  # noqa: PLR0913
     if parallelize:
         logger.debug(f"Running fits (nfits={n_fits}) in parallel (n_threads={cpu_count()})")
 
-        from .hot_pool import hot_pool
-
         pool = hot_pool.pool
         exe_results = list(
             wrap_progress(

src/arpes/xarray_extensions.py

@@ -58,7 +58,6 @@
     Unpack,
 )
 
-from lmfit.model import propagate_err
 import matplotlib.pyplot as plt
 import numpy as np
 import xarray as xr