GMM GPU update#127
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Add RIFT.precision and route all extended-precision dtype use through it.
* RIFT.precision (new): RiftFloat resolves to numpy.longdouble whenever
the platform's long double has itemsize > 8 (e.g. Linux x86_64), and
otherwise falls back to numpy.float64. Also exports
RIFT_FLOAT_HIGH_PRECISION and RIFT_FLOAT_NAME. Eliminates the
import-time AttributeError when numpy.float128 is absent (macOS arm64,
Windows MSVC, non-x86 Linux, future numpy 2.x platforms).
* Integrator package: replace every numpy.float128 / np.float128 in
mcsampler.py, mcsamplerEnsemble.py, mcsamplerGPU.py,
mcsamplerAdaptiveVolume.py, mcsamplerNFlow.py, mcsamplerPortfolio.py,
statutils.py
with RiftFloat. The dtype-equality guards in mcsamplerGPU and
mcsamplerNFlow ("if weights_alt.dtype == numpy.float128: cast to
float64") degrade gracefully when RiftFloat == float64 (the
conditional astype becomes a no-op).
* likelihood/factored_likelihood.py and
interpolators/BayesianLeastSquares.py: same RiftFloat swap, so they
also import cleanly on platforms without np.float128.
* CI (.github/workflows/ci.yml): add rift_O4d_gmm_gpu to the trigger
branches; expand the install matrix to 3.9-3.13; convert
import-check and test-run into a two-lane matrix:
- legacy : python 3.9 + numpy==1.24.4 (historical green build)
- modern : python 3.12 + numpy>=2.0,<3.0 (forward-looking gate)
Numpy is pinned after requirements.txt, so the unpinned 'numpy' line
in requirements.txt is preserved. Test-log artifacts are named
per-lane so failures from each can be uploaded independently.
No behavioral change on the existing legacy CI lane: RiftFloat is
numpy.longdouble there, which is the exact 16-byte type previously
spelled numpy.float128. The modern CI lane is the new gate.
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Issues:
Most modern environments and our containers do this .... only ancient installations will fail (eg my old python3.8 environments) |
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xpy port for mcsamplerEnsemble
Stabilization against future numpy versions. Broader test suite.
Portability (np.float128 not universally supported)