"""The metrics module implements functions assessing prediction error for specific purposes."""

import numpy as np

def trapz(x, y):
    """Trapezoidal rule for integrating
    the curve defined by x-y pairs.
    Assume x and y are in the range [0,1]
    """
    assert len(x) == len(y), 'x and y need to be of same length'
    x = np.concatenate([x, array([0.0, 1.0])])
    y = np.concatenate([y, array([0.0, 1.0])])
    sort_idx = np.argsort(x)
    sx = x[sort_idx]
    sy = y[sort_idx]
    area = 0.0
    for ix in range(len(x)-1):
        area += 0.5*(sx[ix+1]-sx[ix])*(sy[ix+1]+sy[ix])
    return area


"""The metrics module implements functions assessing prediction error for specific purposes."""

import numpy as np


def trapz(x, y):
    """Trapezoidal rule for integrating
    the curve defined by x-y pairs.
    Assume x and y are in the range [0,1]
    """
    assert len(x) == len(y), 'x and y need to be of same length'
    x = np.concatenate([x, np.array([0.0, 1.0])])
    y = np.concatenate([y, np.array([0.0, 1.0])])
    sort_idx = np.argsort(x)
    sx = x[sort_idx]
    sy = y[sort_idx]
    area = 0.0
    for ix in range(len(x) - 1):
        area += 0.5 * (sx[ix + 1] - sx[ix]) * (sy[ix + 1] + sy[ix])
    return area

Add the missing 'np.' before 'array'
Add the missing 'np.' before 'array'
