Fix deprecated np.int aliases in bundled groupy library#1
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markfricker wants to merge 1 commit intoNanoscopyAI:mainfrom
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Fix deprecated np.int aliases in bundled groupy library#1markfricker wants to merge 1 commit intoNanoscopyAI:mainfrom
markfricker wants to merge 1 commit intoNanoscopyAI:mainfrom
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NumPy 1.24 (December 2022) removed the np.int, np.float, np.complex
and related aliases for built-in Python types. Any user running
nERdy+ with a current NumPy version encounters an AttributeError on
import, making the package completely unusable.
Changes (all in nERdy+/groupy/garray/):
- C4_array.py, D4_array.py, Z2_array.py, p4_array.py, p4m_array.py:
dtype=np.int → dtype=np.int64
.astype(np.int) → .astype(np.int64)
== np.int / != np.int → == np.int64 / != np.int64
- matrix_garray.py (additional Windows/platform fix):
data.dtype != np.int64
→ not np.issubdtype(data.dtype, np.integer)
np.int64 is the native integer type on Linux/Mac but Windows NumPy
uses np.int32 for default integer arrays, so the strict dtype
equality check raised a spurious ValueError on Windows.
Tested with NumPy 1.26, PyTorch 2.10 (CUDA 12.6), Python 3.12
on Windows 11. CPU and GPU inference both confirmed working.
Ref: https://numpy.org/doc/stable/release/1.24-notes.html
#expired-deprecations
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NumPy 1.24 (December 2022) removed the np.int, np.float, np.complex and related aliases for built-in Python types. Any user running nERdy+ with a current NumPy version encounters an AttributeError on import, making the package completely unusable.
Changes (all in nERdy+/groupy/garray/):
C4_array.py, D4_array.py, Z2_array.py, p4_array.py, p4m_array.py:
dtype=np.int → dtype=np.int64
.astype(np.int) → .astype(np.int64)
== np.int / != np.int → == np.int64 / != np.int64
matrix_garray.py (additional Windows/platform fix): data.dtype != np.int64 → not np.issubdtype(data.dtype, np.integer) np.int64 is the native integer type on Linux/Mac but Windows NumPy uses np.int32 for default integer arrays, so the strict dtype equality check raised a spurious ValueError on Windows.
Tested with NumPy 1.26, PyTorch 2.10 (CUDA 12.6), Python 3.12 on Windows 11. CPU and GPU inference both confirmed working.
Ref: https://numpy.org/doc/stable/release/1.24-notes.html
#expired-deprecations