Create column with function's output raise a ValueError

Question

I need to create a new column from the output of a function. Below the function:

def lane_shoulder_width_factor(lane: float, shoulder: float = 0.0) -> float:
    """Speed reduction factor based on lane and shoulder width.

    Args:
        lane: float
        shoulder: float

    Returns:
        float
    """
    max_lane_shoulder_width = 999
    min_lane_width = 2.7

    factor = {
        (min_lane_width, 3.0): {
            (0.0, 0.6): 10.3,
            (0.6, 1.2): 7.7,
            (1.2, 1.8): 5.6,
            (1.8, max_lane_shoulder_width): 3.5,
        },
        (3.0, 3.3): {
            (0.0, 0.6): 8.5,
            (0.6, 1.2): 5.9,
            (1.2, 1.8): 3.8,
            (1.8, max_lane_shoulder_width): 1.7,
        },
        (3.3, 3.6): {
            (0.0, 0.6): 7.5,
            (0.6, 1.2): 4.9,
            (1.2, 1.8): 2.8,
            (1.8, max_lane_shoulder_width): 0.7,
        },
        (3.6, 999): {
            (0.0, 0.6): 6.8,
            (0.6, 1.2): 4.2,
            (1.2, 1.8): 2.1,
            (1.8, max_lane_shoulder_width): 0.0,
        },
    }

    for key, value in factor.items():
        lane_width_min = key[0]
        lane_width_max = key[1]
        if lane_width_min <= lane < lane_width_max:
            for key2, value2 in value.items():
                shoulder_width_min = key2[0]
                shoulder_width_max = key2[1]
                if shoulder_width_min <= shoulder < shoulder_width_max:
                    return value2

Below the columns already into DataFrame:

fid              int64
direction        int64
flip             int64
w_lane         float64
w_shoulder     float64
maxspeed       float64

So, I create the new column using the function above:

    df['fls'] = lane_shoulder_width_factor(
        lane=df.w_lane,
        shoulder=df.w_shoulder
    )

The output is this error:

self = 0 False 1 False 2 False 3 False 4 False 5
False 6 False 7 False 8 False Name: w_lane, dtype: bool
@final
def __nonzero__(self):
  raise ValueError(
        f"The truth value of a {type(self).__name__} is ambiguous. "
        "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
    ) E       ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
/home/max/.cache/pypoetry/virtualenvs/mobilitypath-zlqRuy9I-py3.8/lib/python3.8/site-packages/pandas/core/generic.py:1527: ValueError

It isn't clear for me where is the problem. The values inside the columns w_lane and w_shoulder are inside the ranges.

Note: `else: pass` are useless (moot point), so you can remove them. What do you want the function to return when the condition is not met? — CristiFati, Apr 12 '22 at 15:14
Right, it is a my inattention. Previously there is a function. — MaxDragonheart, Apr 12 '22 at 15:20

score 0 · Accepted Answer · answered Apr 12 '22 at 16:14

0

I found a solution thanks to this answer:

    input_data['fls'] = np.vectorize(lane_shoulder_width_factor)(
        lane=input_data.w_lane, shoulder=input_data.w_shoulder
    )

answered Apr 12 '22 at 16:14

MaxDragonheart

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Create column with function's output raise a ValueError

1 Answers1