AtsushiSakai/PythonRobotics · error · ValueError

Input array should only contain 0 and 1

Error message

Input array should only contain 0 and 1

What it means

Raised by compute_udf when the input boolean field contains values other than 0 and 1. The undirected distance transform (via the dt distance transform) requires a binary obstacle map, so any other value makes the result meaningless and is rejected up front.

Source

Thrown at Mapping/DistanceMap/distance_map.py:106

def compute_udf(obstacles):
    """
    Compute the unsigned distance field (UDF) from a boolean field.

    Parameters
    ----------
    obstacles : array_like
        A 2D boolean array where '1' represents obstacles and '0' represents free space.

    Returns
    -------
    array_like
        A 2D array of distances from the nearest obstacle, with the same dimensions as `bool_field`.
    """
    edt = obstacles.copy()
    if not np.all(np.isin(edt, [0, 1])):
        raise ValueError("Input array should only contain 0 and 1")
    edt = np.where(edt == 0, INF, edt)
    edt = np.where(edt == 1, 0, edt)
    for row in range(len(edt)):
        dt(edt[row])
    edt = edt.T
    for row in range(len(edt)):
        dt(edt[row])
    edt = edt.T
    return np.sqrt(edt)


def dt(d):
    """
    Compute 1D distance transform under the squared Euclidean distance

    Parameters
    ----------
    d : array_like

View on GitHub (pinned to 1fe4fb980f)

Solutions

1. Binarize the array before calling: np.where(field > threshold, 1, 0) or field.astype(bool).astype(int).
2. Verify the data pipeline producing the obstacle map only emits 0/1.
3. Add an assertion np.all(np.isin(field, [0, 1])) in your own code to catch bad input early.

Example fix

// before
udf = compute_udf(occupancy)  # occupancy holds 0..1 probabilities

// after
binary = (occupancy > 0.5).astype(int)
udf = compute_udf(binary)

import numpy as np
assert np.all(np.isin(field, [0, 1])), 'obstacle field must be binary'

def is_binary_field(a) -> bool:
    import numpy as np
    return isinstance(a, np.ndarray) and np.all(np.isin(a, [0, 1]))

When it happens

Trigger: Calling compute_udf(obstacles) (or compute_sdf) with a float array, an occupancy grid containing probabilities (0..1), or an array with True/False plus other labels like 2 or 255.

Common situations: Feeding a grayscale map, a normalized occupancy probability grid, or a segmentation mask with multiple classes into a function that expects a strictly binary obstacle field.

Related errors

• x coordinates must be sorted in ascending order

AI-assisted analysis of AtsushiSakai/PythonRobotics@1fe4fb980f (2026-08-28). Data as JSON: /api/errors/90a5c11c9a438517. Report an issue: GitHub.