bump version to v0.9

README.md

@@ -41,14 +41,15 @@ solver will need the ability to solve complex symmetric (non-Hermitian)
 linear systems, ideally with double precision.
 
 - [Source repository](https://mpxd.net/code/jan/meanas)
-- PyPI *TBD*
+- [PyPI](https://pypi.org/project/meanas)
+- [Github mirror](https://github.com/anewusername/meanas)
 
 
 ## Installation
 
 **Requirements:**
 
-* python >=3.8
+* python >=3.11
 * numpy
 * scipy
 

meanas/__init__.py

@@ -6,7 +6,7 @@ See the readme or `import meanas; help(meanas)` for more info.
 
 import pathlib
 
-__version__ = '0.8'
+__version__ = '0.9'
 __author__ = 'Jan Petykiewicz'
 
 

meanas/fdfd/functional.py

@@ -200,7 +200,7 @@ def poynting_e_cross_h(dxes: dx_lists_t) -> Callable[[cfdfield_t, cfdfield_t], c
 
     Note:
         If `E` and `H` are peak amplitudes as assumed elsewhere in this code,
-        the time-average of the poynting vector is `<S> = Re(S)/2 = Re(E x H) / 2`.
+        the time-average of the poynting vector is `<S> = Re(S)/2 = Re(E x H*) / 2`.
         The factor of `1/2` can be omitted if root-mean-square quantities are used
         instead.
 

meanas/fdfd/operators.py

@@ -324,6 +324,7 @@ def poynting_e_cross(e: vcfdfield_t, dxes: dx_lists_t) -> sparse.spmatrix:
     fx, fy, fz = [shift_circ(i, shape, 1) for i in range(3)]
 
     dxag = [dx.ravel(order='C') for dx in numpy.meshgrid(*dxes[0], indexing='ij')]
+    dxbg = [dx.ravel(order='C') for dx in numpy.meshgrid(*dxes[1], indexing='ij')]
     Ex, Ey, Ez = [ei * da for ei, da in zip(numpy.split(e, 3), dxag)]
 
     block_diags = [[ None,     fx @ -Ez, fx @  Ey],
@@ -331,7 +332,7 @@ def poynting_e_cross(e: vcfdfield_t, dxes: dx_lists_t) -> sparse.spmatrix:
                    [ fz @ -Ey, fz @  Ex, None]]
     block_matrix = sparse.bmat([[sparse.diags(x) if x is not None else None for x in row]
                                 for row in block_diags])
-    P = block_matrix @ sparse.diags(numpy.concatenate(dxag))
+    P = block_matrix @ sparse.diags(numpy.concatenate(dxbg))
     return P
 
 

pyproject.toml

@@ -33,7 +33,7 @@ classifiers = [
     "License :: OSI Approved :: GNU Affero General Public License v3",
     "Topic :: Scientific/Engineering :: Physics",
     ]
-requires-python = ">=3.8"
+requires-python = ">=3.11"
 include = [
     "LICENSE.md"
     ]