do not issue warning in case of clipping

import time

from typing import Tuple

from multiprocessing import Pool

import warnings

import math

from dataclasses import dataclass

from typing import Union

        np.logical_or(x < np.iinfo(np.int16).min, x > np.iinfo(np.int16).max)

    )

    if clipped_samples > 0:

        warnings.warn(f"  Warning: {clipped_samples} samples clipped")

        # do not issue warning for clipping as it is expected that some implementations may produce out of bound values and the reference implementation clips them. Instead, just count the number of clipped samples and clip the values to int16 range before writing to file to avoid overflow issues.

        x = np.clip(x, np.iinfo(np.int16).min, np.iinfo(np.int16).max)

    if file_extension == ".wav":

        self, tag: str, pyTestsTag: str, testIndex: int = 0, totalTests: int = 0

    ):

        # Run CUT Cmdline

        testPrefix = f"[{tag} {testIndex}/{totalTests}]"

        _w = len(str(totalTests))

        testPrefix = f"[{tag} {testIndex:{_w}}/{totalTests}]"

        self.appendRunlog(

            context=self.formatTestHeader(testPrefix, "Running test", pyTestsTag)

        )

    def analyseOneCommand(

        self, tag: str, pyTestsTag: str, testIndex: int = 0, totalTests: int = 0

    ):

        testPrefix = f"[{tag} {testIndex}/{totalTests}]"

        _w = len(str(totalTests))

        testPrefix = f"[{tag} {testIndex:{_w}}/{totalTests}]"

        header = self.formatTestHeader(testPrefix, "Analyzing test", pyTestsTag)

        self.appendRunlog(context=header)

        non_be = None