bumpy scipy >= 1.11.0

Since 1.11.0, Cartwright's approach (eve="simpson") is the default for Simpson integration, see
https://docs.scipy.org/doc/scipy-1.11.0/reference/generated/scipy.integrate.simpson.html

devtools/conda-envs/test_env.yaml

@@ -6,7 +6,7 @@ dependencies:
 - python
 - six
 - numpy
-- scipy >=1.6.0
+- scipy >=1.11.0
 - matplotlib-base
 - pandas
 - scikit-learn

mdpow/fep.py

@@ -1085,8 +1085,8 @@ def analyze(self, force=False, stride=None, autosave=True, ncorrel=25000):
         .. versionchanged:: 0.9.0
            Change in how the Simpson's rule integration algorithm (namely,
            :func:`scipy.integrate.simpson`) handles even number of intervals:
-           Previously, the old `even="last"` was used but now Cartwright's
-           approach is always used. This change **leads to numerically
+           Previously, the old `even="last"` was used but since scipy 1.11.0
+           Cartwright's approach is used. This change **leads to numerically
            slightly different results** between MDPOW 0.9.0 and earlier
            versions.
         """

setup.py

@@ -60,7 +60,7 @@
     },
     install_requires=[
         "numpy>=1.6",
-        "scipy>=1.6.0",
+        "scipy>=1.11.0",
         "pyyaml",
         "GromacsWrapper>=0.5.1",
         "numkit",