#! /bin/python3 from perf_stat import Stat, CPU import argparse import os, glob import re import json from enum import Enum import math import numpy as np import matplotlib.pyplot as plt import itertools class Plot(Enum): BOX = 'box' LINE = 'line' def accumulate(stats_list: list[dict[str, str | int | float]], category: str, value: str): print(category) print(value) category_list = np.array([stats[category] for stats in stats_list if value in stats]) value_list = np.array([stats[value] for stats in stats_list if value in stats]) result: dict[np.ndarray] = dict() for category in np.sort(np.unique(category_list)): result[category] = value_list[category_list == category] return result def box_plot(ax, stats_list: list[dict[str, str | int | float]], x: Stat, y: Stat): data: dict[str, np.ndarray] = accumulate(stats_list, x, y) print("Plotted data: " + str(data)) ax.boxplot(data.values(), tick_labels=data.keys()) ax.set_ylabel(y.value) def line_plot( ax, stats_list: list[dict[str, str | int | float]], x: Stat, y: Stat, color: Stat ): x_data: dict[str, np.ndarray] = accumulate(stats_list, color, x) y_data: dict[str, np.ndarray] = accumulate(stats_list, color, y) for category in x_data.keys(): sorted_indices = np.argsort(x_data[category]) x_data[category] = x_data[category][sorted_indices] y_data[category] = y_data[category][sorted_indices] ax.plot(x_data[category], y_data[category], label=category) print("Plotted x data: " + str(x_data[category])) print("Plotted y data: " + str(y_data[category])) ax.set_ylabel(y) ax.grid(True) def visualize( stats_list: list[dict[str, str | int | float]], plot: Plot, rows: int, size_multiplier: int, font_size: int, x: Stat, y: Stat, color: Stat, filter_list: list[str] = [] ): # Remove stats entries containing undesired values (like a specific CPU). # stats_list = [stats for stats in stats_list # if len([stats[key] for key in stats.keys() # if stats[key] in filter_list]) == 0] #x = Stat.MAXWELL_SIZE #y = Stat.DTLB_MISS_RATE #color = Stat.SOLVER if y is None: #ys = [stat for stat in Stat if stat.value in stats_list[0].keys() ys = [stat for stat in stats_list[0].keys() if "power" not in stat] #and stat is not x #and y != color #and y != marker #and stat.value not in filter_list] fig, axes = plt.subplots(rows, int(math.ceil(len(ys) / rows)), figsize = (16 * size_multiplier, 9 * size_multiplier)) match plot: case Plot.BOX: for i, y in enumerate(ys): box_plot(axes[i % rows][int(i / rows)], stats_list, x, y) case Plot.LINE: for i, y in enumerate(ys): line_plot(axes[i % rows][int(i / rows)], stats_list, x, y, color) handles, labels = axes[i % rows][int(i / rows)].get_legend_handles_labels() else: fig, ax = plt.subplots() match plot: case Plot.BOX: box_plot(ax, stats_list, x, y) case Plot.LINE: line_plot(ax, stats_list, x, y, color) handles, labels = ax.get_legend_handles_labels() #box_plot(ax, stats, x, y) #line_plot(ax, stats, x, y, color) match plot: case Plot.BOX: title = f"{plot.value}_plot_of_{y.value.replace(' ', '_')}_vs_{x.value.replace(' ', '_')}_excluding_{filter_list}" case Plot.LINE: #title = f"{plot.value}_plot_of_{y.replace(' ', '_')}_vs_{x.replace(' ', '_')}_by_{color.replace(' ', '_')}_excluding_{filter_list}" title = "altra_spmv" fig.suptitle(title, fontsize = font_size) fig.legend(handles, labels, fontsize = font_size) fig.supxlabel(x, fontsize = font_size) plt.savefig(title + ".png", dpi = 100) plt.show() def main(): class Command(Enum): PARSE = 'parse' VISUALIZE = 'visualize' parser = argparse.ArgumentParser() parser.add_argument('command', choices=[x.value for x in Command]) parser.add_argument('filepath', help='the output for the ' + Command.PARSE.value + ' command or the input for the ' + Command.VISUALIZE.value + ' command') parser.add_argument('-i', '--input_dir', help='the input directory for the parse command') parser.add_argument('-p', '--plot', choices=[x.name.lower() for x in Plot], help = 'the type of plot') parser.add_argument('-r', '--rows', type=int, help = 'the number of rows to display when -y is not specified', default = 5) parser.add_argument('-s', '--size', type=int, help = 'figure size multiplier', default = 4) parser.add_argument('-fs', '--font_size', type=int, help = 'font size', default = 40) parser.add_argument('-x', #choices=[x.name.lower() for x in Stat], help = 'the name of the x axis') parser.add_argument('-y', #choices=[x.name.lower() for x in Stat], help = 'the name of the y axis') parser.add_argument('-c', '--color', #choices=[x.name.lower() for x in Stat], help = 'the name of the color') parser.add_argument('-f', '--filter', nargs = '+', help = 'a comma-separated string of names and values to filter out.', default = []) args = parser.parse_args() stats_list: list[dict] = list() if args.command == Command.PARSE.value: if (args.input_dir) is None: print("An input directory is required with -i") exit(-1) for filename in glob.glob(f'{args.input_dir.rstrip("/")}/*.json'): with open(filename, 'r') as file: stats_list.append(json.load(file)) print(filename + " loaded.") with open(args.filepath, 'w') as file: json.dump(stats_list, file, indent = 2) elif args.command == Command.VISUALIZE.value: with open(args.filepath, 'r') as file: stats_list = json.load(file) #x = Stat[args.x.upper()] if args.x is not None else None x = args.x #y = Stat[args.y.upper()] if args.y is not None else None y = args.y #color = Stat[args.color.upper()] if args.color is not None else None color = args.color visualize(stats_list, Plot[args.plot.upper()], args.rows, args.size, args.font_size, x, y, color, args.filter) if __name__ == '__main__': main()