pnumpy
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Quansight
Parallel NumPy seamlessly speeds up NumPy for large arrays (64K+ elements) with no change required to existing code.
Hi, I realy like the concept behind pnumpy, but might prefer if an import of pnumpy would not automagically monkey patch numpy, but only provide pnumpy.* entry points to parallel...
``` In [1]: import scipy.stats as st ...: arr = st.norm.rvs(loc=6000, scale=20, size=(300, 10)) ...: st.skewtest(arr) Out[1]: SkewtestResult(statistic=array([ 1.21508957, -0.60569814, 0.07676428, 0.10929194, -1.78128941, 1.3046305 , 1.03649957, -0.90213437, 1.39273949, 0.87478829]), pvalue=array([0.22433193,...
I was giving `pnumpy` a go, trying to run examples that work with numpy, and I run into this ValueError. From the traceback, the reason is not super obvious, and...
I suspect [the online docs](https://quansight.github.io/pnumpy/stable/index.html) are very much being developed dynamically, but anyway I ran into two minor things at a first glance: 1. There's no link from the documentation...
In `doc_src/source/conf.py` the `project` is still called "accelerated_numpy", which shows up in the [docs](https://quansight.github.io/numpy-threading-extensions/stable/index.html). Also on the the [index.rst](https://github.com/Quansight/numpy-threading-extensions/blob/main/doc_src/source/index.rst) page, which should get some of the benchmark goodness from the...
Per @mattip, create a 'benchmarking' page in the documentation. The page should include the following information: * instructions on how to set up and run the benchmark suite (via asv)...
When a ufunc loop is replaced there is no user callback argument, this makes it difficult for the routine being called to know what it is. I would rather funnel...
users often call "~np.isnan(arr)" this makes TWO passes and produces a temporary array in the process. Are we allowed to add "isnotnan" then the user can call np.isnotnan(arr). For instance...
I only recently downloaded the library and am not sure what the expected result is, but currently the benchmarks involving multiple threads do not show any improvement for me. possibly...
