How to get Damage Matrix in nCode GUI?

Javier Vique

DesignLife embedded Add-On, available in Mechanical, allows to plot the Damage Matrix of a node. Is there any way to get the same plot in nCode GUI?

Javier Vique

We can make use of the Scripting glyph for getting the Damage Matrix. Assuming that you have a MultiColumn object with damage, mean and range on the fourth, fifth and sixth column, and defining as input of your Scripting glyph a MultiColumn input and as output a Histrogram output, the script to be used is shown below, defining 64 bins for range and mean. Result:

def glyphscript(engineState):

    import Glyph

    import numpy as np


    es = engineState

    in_MC = es.GetInputMultiColumn(0)

    hiout = es.GetOutputHistogram(0)

    in_table = in_MC.GetTable(0,0)

    num_rows = in_table.GetRowCount()

    range_s = []

    means = []

    damage = []

    for i in range(num_rows):

        range_s.append(in_table.GetValue(5,i)) 

        means.append(in_table.GetValue(4,i))

        damage.append(in_table.GetValue(3,i))


    numBins = 64

    buffer_user = 10


    ## Bins creation

    # Step 1: Define the buffer and calculate min and max for both x and y

    min_x = np.min(range_s)

    max_x = np.max(range_s)

    min_y = np.min(means)

    max_y = np.max(means)

    # Create boundaries for bins with buffer

    min_bound_x = max(min_x - buffer_user,0)

    max_bound_x = max_x + buffer_user

    min_bound_y = min_y - buffer_user

    max_bound_y = max_y + buffer_user


    # Step 2: Generate 64 evenly spaced bins for x and y

    bins_x = np.linspace(min_bound_x, max_bound_x, numBins+1)  # 65 because you need 64 intervals

    bins_y = np.linspace(min_bound_y, max_bound_y, numBins+1)


    # Step 3: Create a 2D array to hold the sum of z values in each bin

    bin_sums = np.zeros((numBins, numBins))  # For storing the sum of z values in each bin


    # Step 4: Assign each (x, y) pair to a bin and sum damage (z)

    for i in range(len(means)):

        # Find which bin (for both x and y) the current point falls into

        bin_idx_x = np.digitize(range_s[i], bins_x) - 1  # -1 to adjust to 0-based index

        bin_idx_y = np.digitize(means[i], bins_y) - 1  # -1 for same reason


        # Accumulate the z value (total sum) in the appropriate bin

        bin_sums[bin_idx_x, bin_idx_y] += damage[i]


    # Step 5: Calculate the center values of x and y for each bin

    # The center of each bin is the midpoint between the bin edges

    bin_centers_x = (bins_x[:-1] + bins_x[1:]) / 2

    bin_centers_y = (bins_y[:-1] + bins_y[1:]) / 2


    mat = Glyph.Matrix()

    atts = dict(Type=2, SubType=2, xmin=min_bound_x, xmax=max_bound_x, xbincount=numBins, xtitle="Range", xunits="MPa", ymin=min_bound_y, ymax=max_bound_y, ybincount=numBins, ytitle="Mean", yunits="MPa", ztitle="damage", zunits="Count")

    mat.SetAttributes(atts)


    for i in range(len(bin_centers_x)):

        for j in range(len(bin_centers_y)):

            mat.IncXYBin(i,j,bin_sums[i,j])


    hiout.PutMatrix(0,mat)

    hiout.SetChanNumber(0,1)

    hiout.SetChanTitle(0,"Damage Matrix")


    return ''