"""
Various useful utilities (duh)
"""

import numpy as np

def sampled_time(sample_rate=1, start=0, end=1, offset=0):
    return offset + np.arange(start, end, 1/sample_rate)

def rot_vector(phi1=0.12345):
    """
    Return a unit vector rotated by phi radians.
    """

    unit = np.array([
                phi1,
                phi1 - np.pi/2
            ])

    return np.cos(unit)

def detect_edges(threshold, data, rising=True, falling=False):
    """
    Detect rising/falling edges in data, returning the indices
    of the detected edges.

    https://stackoverflow.com/a/50365462
    """

    mask = np.full(len(data), False)

    if rising:
        mask |= (data[:-1] < threshold) & (data[1:] > threshold)

    if falling:
        mask |= (data[:-1] > threshold) & (data[1:] < threshold)

    return np.flatnonzero(mask)+1