- Introduce a standard way to bind numpy arrays: py::array_t<T> and
.noconvert() on the argument
- Take py::array_t by value since it's just a small wrapper
- Update bindings
Three files conflicted:
- ClusterFinderMT::collect(): both sides rewrote it. Keep this branch's
version (f4bbbc9), which reads the stop flags before sweeping, over
main's (afce91b), which still samples queue emptiness mid-condition.
The staged splice had also lost a brace, swallowing popFront().
- python/aare/ClusterFinder.py: restore the CUDA API deleted by the
resolution (_cuda_available, _CUDA_ALGORITHMS, ClusterFinderCUDA,
find_cluster_views_batched_iter, ClusterFinderCUDAGraph), and main's
min_pedestal_samples forwarding, dropped as an adjacent hunk.
- bind_ClusterVector.hpp: keep py::module_local() (133cedf) alongside
main's new docstrings; without it _aare and _aare_cuda cannot both
register Cluster/ClusterVector under pybind11 3.
Does not build on its own: ClusterFinderFrozen and the CUDA drivers
still call Pedestal APIs main removed. Fixed in the follow-up.
Cleaned up the helper functions by:
- Added template for make_view (and new make_const_view) instead of the
copy paste implementation
- checks c_style and dimensions inside make_view
- test binding to be able to probe the checks in make_view
Call sites can be reviewed in a second PR since usage of const or
strictness of conversion depends...
- Default `ClusterVector` move operations simplifying the code and
fixing a bug.
- Fixed inconsistent frame number type (uint64/int32)
- Validate Python masks as one-dimensional, C-contiguous Boolean arrays,
handle empty masks safely, and reserve filtered storage based on the
selected cluster count.
- Align the C++ and Python API documentation with the implementation,
including concise `hitmap` and reduction documentation and a correctly
rendered constructor example.
Optimized pedestal tracking with FastPedestal and performance improvements to the cluster finder.
- ~2x faster hitting 14k FPS on benchmark dataset on 16 core threadripper pro
**Changes**
- No bounds check on interior of frame. (only within half of a cluster)
(~15% improvement)
- Cache threshold (std*n_rms) Biggest improvement comes from not
computing std for each access
- Cache pedestal subtracted frame
- Switched to FastPedestal which assumes we reached steady state
**Things tried but rejected:**
- Always store cluster values, commit on val==max (~15% drop in frame
rate)
**Options**
- using 16 bit clusters and 16 bit pedestal. (slows down the single
threaded case but allow us to reach 12k with multi threading)
**Other notes on performance**
- Passing in memory frames from python and doing nothing: 0.8us/frame
- Passing + pedestal subtraction: 28us/frame
- Passing + pedestal + cluster finding (no store): 652us/frame
- Passing + pedestal + cluster finding: 886 us/frame
- After upgrading to pybind11 3, duplicate registration of cluster-related
types across `_aare` and `_aare_cuda` started failing.
- Mark the `Cluster` and `ClusterVector` bindings as `py::module_local()` so
each extension owns its local registration.
Note: cluster objects from CPU and CUDA bindings are now distinct Python types.
- added rosenblatttransform
- added 3x3 eta methods
- interpolation can be used with various eta functions
- added documentation for interpolation, eta calculation
- exposed full eta struct in python
- disable ClusterFinder for 2x2 clusters
- factory function for ClusterVector
---------
Co-authored-by: Dhanya Thattil <dhanya.thattil@psi.ch>
Co-authored-by: Erik Fröjdh <erik.frojdh@psi.ch>
Changes to be able to run the example notebooks:
- Invert gain map on setting (multiplication is faster but user supplies
ADU/energy)
- Cast after applying gain map not to loose precision (Important for
int32 clusters)
- "factor" for ClusterFileSink
- Cluster size available to be able to create the right file sink
kferjaoui
mazzol_aandErik Fröjdh
