adriancaruana

import numpy as np
from numpy.typing import ArrayLike, NDArray


def clip_histogram(histogram: NDArray, bin_edges: NDArray, threshold: float):
    # Apply threshold to the distribution to exclude all values below the threshold. Note: Since
    # we're using histograms, we might have the threshold fall within a bin, so we need to
    # interpolate the value of the bin to the threshold, and artificially reduce the ratio for
    # the bin by the fractional amount of the bin that's below the threshold.  

adriancaruana

#!/usr/bin/python3
# Generate requirements.txt automatically from live environment
# Run like this: ./get_package_versions.py >> requirements.txt
# Requires pip>=22.* (if fails, try: python3 -m pip install --upgrade pip)
from pip._internal.metadata import get_default_environment
wildcard_bugfix = lambda ver: ".".join(ver.split(".")[:2]) + ".*"
reqs = "\n".join(
    f"{package.metadata_dict['name']}=={wildcard_bugfix(package.metadata_dict['version'])}"
    for package in sorted(list(get_default_environment().iter_installed_distributions()), key=lambda x: str(x).lower())
)