Neuroimaging in Python — NiBabel 5.4.0.dev1+g3b1c7b37 documentation (original) (raw)
benchmarks
¶
Module: benchmarks.bench_array_to_file
¶
Benchmarks for array_to_file routine
Run benchmarks with:
import nibabel as nib nib.bench()
Run this benchmark with:
pytest -c
Module: benchmarks.bench_arrayproxy_slicing
¶
Benchmarks for ArrayProxy slicing of gzipped and non-gzipped files
Run benchmarks with:
import nibabel as nib nib.bench()
Run this benchmark with:
pytest -c
Module: benchmarks.bench_fileslice
¶
Benchmarks for fileslicing
import nibabel as nib nib.bench()
Run this benchmark with:
pytest -c
bench_fileslice([bytes, file_, gz, bz2, zst]) |
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run_slices(file_like[, repeat, offset, order]) |
Module: benchmarks.bench_finite_range
¶
Benchmarks for finite_range routine
Run benchmarks with:
import nibabel as nib nib.bench()
Run this benchmark with:
pytest -c
Module: benchmarks.bench_load_save
¶
Benchmarks for load and save of image arrays
Run benchmarks with:
import nibabel as nib nib.bench()
Run this benchmark with:
pytest -c
Module: benchmarks.butils
¶
Benchmarking utilities
print_git_title(title) | Prints title string with git hash if possible, and underline |
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bench_array_to_file¶
nibabel.benchmarks.bench_array_to_file.bench_array_to_file()¶
bench_arrayproxy_slicing¶
nibabel.benchmarks.bench_arrayproxy_slicing.bench_arrayproxy_slicing()¶
bench_fileslice¶
nibabel.benchmarks.bench_fileslice.bench_fileslice(bytes=True, file_=True, gz=True, bz2=False, zst=True)¶
run_slices¶
nibabel.benchmarks.bench_fileslice.run_slices(file_like, repeat=3, offset=0, order='F')¶
bench_finite_range¶
nibabel.benchmarks.bench_finite_range.bench_finite_range()¶
bench_load_save¶
nibabel.benchmarks.bench_load_save.bench_load_save()¶
print_git_title¶
nibabel.benchmarks.butils.print_git_title(title)¶
Prints title string with git hash if possible, and underline