Source code for MLV_toolbox.getMATpropertyStats

from .VecLD import VecLD
import numpy as np
from typing import Tuple

def getMATpropertyStats(vecLD: VecLD, 
                       property: str, 
                       numBins: int = 8
                       ) -> Tuple[VecLD, float, float]:
    """
    Computes statistics for a given property of a vectorized line drawing.

    Args:
        vecLD (dict): A dictionary representing the vectorized line drawing data structure.
        property (str): The name of the property to compute statistics for.
        num_bins (int): The number of bins to use for the histogram.

    Returns:
        tuple: A tuple containing the modified `vecLD` dictionary, the computed histogram, the bin edges, and a short name for the property.
    """
    
    binWidth = 1/numBins
    vecLD.__dict__[property + 'Bins'] = np.arange(binWidth/2, 1, binWidth) - binWidth/2
    vecLD.__dict__[property + 'Histograms'] = np.zeros((vecLD.numContours, numBins))
    vecLD.__dict__[property + 'normHistograms'] = np.zeros((vecLD.numContours, numBins))
    
    for c in range(vecLD['numContours']):
        thisProp = vecLD.__dict__[property][c]
        thisProp = thisProp[~np.isnan(thisProp)] # remove NaNs
        thisHist, _ = np.histogram(thisProp, bins=bins) # discard bin edges
        vecLD.__dict__[property + 'Histograms'][c, :] = thisHist
        vecLD.__dict__[property + 'NormHistograms'][c, :] = thisHist / vecLD.contourLengths[c] * 10000
    
    histogram = np.sum(vecLD.__dict__[property + "Histograms"], axis=0)
    vecLD.__dict__[property + "SumHistogram"] = histogram
    
    # normalize histogram by total contour length
    vecLD.__dict__[property + "NormSumHistogram"] = histogram / np.sum(vecLD.contourLengths) * 10000

    # set short name as first three letters of property
    shortName = property[:3]
    
    return vecLD, histogram, bins, shortName

setattr(VecLD, 'getMATpropertyStats', getMATpropertyStats)