The fc_bench Python package allows to benchmark functions and much more
Introduction:
More documentation is available on fc_bench Python package dedicated web page with an User’s Guide (pdf).
Installation:
The fc_bench Python package is available from the Python Package Index, so to install/upgrade simply type
pip install fc_bench -U
Testing :
There are demos functions in the fc_bench.demos module named bench_*. For example, run the following code under Python:
from fc_bench import demos demos.bench_Lagrange()The output of this code is:
#--------------------------------------------------------------------------- # Setting inputs of Lagrange polynomial functions: y=LAGRANGE(X,Y,x) # where X is numpy.linspace(a,b,n+1), Y=fun(X) and x is random values on [a,b] # n is the order of the Lagrange polynomial # fun function is: lambda x: np.sin(x) # [a,b]=[-1,1] # X: (n+1,) numpy array # Y: (n+1,) numpy array # x: (m,) numpy array # Error[i] computed with fun[i] output: # lambda y: np.linalg.norm(y-fun(x),np.inf) #--------------------------------------------------------------------------- # Benchmarking functions: # fun[0], Lag: fc_bench.demos.Lagrange # fun[1], lagint: fc_bench.demos.lagint #--------------------------------------------------------------------------- # Comparative functions: # comp[i-1,0], compares outputs of fun[0] and fun[i] # lambda o1,o2: np.linalg.norm(o1-o2,np.inf) # For each comparative function: # - 1st input parameter is the output of fun[0] # - 2nd input parameter is the output of fun[i] #--------------------------------------------------------------------------- #date:2019-12-21_16-56-34 #nbruns:5 #numpy: <i8 <i8 f8 f8 f8 f8 f8 #format: {:>5} {:>5} {:6.3f} {:10.3e} {:9.3f} {:10.3e} {:9.3e} #labels: m n Lag(s) Error[0] lagint(s) Error[1] comp[0] 100 3 0.014 1.218e-03 0.019 1.218e-03 2.220e-16 100 5 0.021 1.162e-05 0.028 1.162e-05 4.441e-16 100 7 0.030 6.999e-08 0.037 6.999e-08 3.331e-16 100 11 0.048 8.699e-13 0.056 8.689e-13 2.554e-15 500 3 0.068 1.218e-03 0.095 1.218e-03 3.331e-16 500 5 0.108 1.163e-05 0.144 1.163e-05 6.661e-16 500 7 0.152 7.004e-08 0.190 7.004e-08 8.882e-16 500 11 0.244 8.766e-13 0.282 8.766e-13 2.887e-15
Metadata
Release files for fc-bench 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| fc_bench-0.2.0.tar.gz | 11.3 kB | Without provenance | Details for fc_bench-0.2.0.tar.gz |
Release files / fc_bench-0.2.0.tar.gz
| Download URL | fc_bench-0.2.0.tar.gz |
|---|---|
| Size | 11.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4eb490d370b72e1e3f88e7b369f00bf23148d604c6287ccba84f5b42a7b473c8
|
|
BLAKE2b-256 checksum How to use checksums |
a82d8d0ab764f0bacd6daccf3390a2221e803bc1015cd2c8b631da2404e4c709
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.41.0 CPython/3.6.9
|
Security for fc-bench 0.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.