XMeans/plot.py at master · IngInx747/XMeans · GitHub

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import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

def read_node_from_file(filename:str):
    with open(filename, "r") as file:
        lines = file.readlines()
        tokens = lines[0].split()
        nv = int(tokens[0])
        xs, ys, ts = [], [], []
        for line in lines[1:]:
            tokens = line.split()
            x, y = np.float64(tokens[1]), np.float64(tokens[2])
            tag = int(tokens[3]) if len(tokens) > 3 else 0
            xs.append(x)
            ys.append(y)
            ts.append(tag)
        return np.array(xs), np.array(ys), np.array(ts, dtype=int)

color_map = mcolors.ListedColormap([
    'red', 'blue', 'green', 'yellow', 'gray', 'black', 'cyan', 'orange', 'purple',
    'lightgreen', 'magenta', 'brown', 'pink', 'olive'])

#color_map = mcolors.ListedColormap(mcolors.BASE_COLORS)
#color_map = mcolors.ListedColormap(mcolors.CSS4_COLORS)
#color_map = mcolors.ListedColormap(mcolors.XKCD_COLORS)

if __name__ == "__main__":
    import sys
    if len(sys.argv) == 2:
        filename = sys.argv[1]
        x, y, tag = read_node_from_file(filename)
        x0, x1 = min(x), max(x)
        y0, y1 = min(y), max(y)
        s = max(x1 - x0, y1 - y0)
        xc = (x0 + x1) * 0.5
        yc = (y0 + y1) * 0.5
        d = s * 0.6
        plt.scatter(x, y, c=tag, cmap=color_map)
        plt.axis('square')
        plt.xlim(xc - d, xc + d)
        plt.ylim(yc - d, yc + d)
        plt.show()