Altra visualization works!
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2c115359c3
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@ -18,11 +18,11 @@ class Plot(Enum):
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BOX = 'box'
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LINE = 'line'
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def accumulate(stats_list: list[dict[str, str | int | float]], category: str, value: str):
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print(category)
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print(value)
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category_list = np.array([stats[category] for stats in stats_list if value in stats])
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value_list = np.array([stats[value] for stats in stats_list if value in stats])
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def accumulate(data_list: list[dict[str, str | int | float]], category: Stat, value: Stat):
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#print(category.name)
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#print(value.name)
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category_list = np.array([stats[category.name] for stats in data_list if value.name in stats])
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value_list = np.array([stats[value.name] for stats in data_list if value.name in stats])
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result: dict[np.ndarray] = dict()
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for category in np.sort(np.unique(category_list)):
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@ -30,34 +30,34 @@ def accumulate(stats_list: list[dict[str, str | int | float]], category: str, va
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return result
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def box_plot(ax, stats_list: list[dict[str, str | int | float]], x: Stat, y: Stat):
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data: dict[str, np.ndarray] = accumulate(stats_list, x, y)
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def box_plot(ax, data_list: list[dict[str, str | int | float]], x: Stat, y: Stat):
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data: dict[str, np.ndarray] = accumulate(data_list, x, y)
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print("Plotted data: " + str(data))
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#print("Plotted data: " + str(data))
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ax.boxplot(data.values(), tick_labels=data.keys())
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ax.set_ylabel(y.value)
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def line_plot(
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ax, stats_list: list[dict[str, str | int | float]],
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ax, data_list: list[dict[str, str | int | float]],
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x: Stat, y: Stat, color: Stat
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):
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x_data: dict[str, np.ndarray] = accumulate(stats_list, color, x)
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y_data: dict[str, np.ndarray] = accumulate(stats_list, color, y)
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x_data: dict[str, np.ndarray] = accumulate(data_list, color, x)
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y_data: dict[str, np.ndarray] = accumulate(data_list, color, y)
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for category in x_data.keys():
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sorted_indices = np.argsort(x_data[category])
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x_data[category] = x_data[category][sorted_indices]
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y_data[category] = y_data[category][sorted_indices]
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ax.plot(x_data[category], y_data[category], label=category)
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print("Plotted x data: " + str(x_data[category]))
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print("Plotted y data: " + str(y_data[category]))
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#print("Plotted x data: " + str(x_data[category]))
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#print("Plotted y data: " + str(y_data[category]))
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ax.set_ylabel(y)
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ax.set_ylabel(y.value)
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ax.grid(True)
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def visualize(
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stats_list: list[dict[str, str | int | float]],
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data_list: list[dict[str, str | int | float]],
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plot: Plot,
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rows: int,
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size_multiplier: int,
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@ -68,7 +68,7 @@ def visualize(
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filter_list: list[str] = []
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):
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# Remove stats entries containing undesired values (like a specific CPU).
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# stats_list = [stats for stats in stats_list
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# data_list = [stats for stats in data_list
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# if len([stats[key] for key in stats.keys()
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# if stats[key] in filter_list]) == 0]
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@ -77,21 +77,25 @@ def visualize(
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#color = Stat.SOLVER
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if y is None:
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#ys = [stat for stat in Stat if stat.value in stats_list[0].keys()
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ys = [stat for stat in stats_list[0].keys() if "power" not in stat]
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#ys = [stat for stat in Stat if stat.name in data_list[0].keys()]
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#ys = [stat for stat in data_list[0].keys() if "power" not in stat]
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#and stat is not x
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#and y != color
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#and y != marker
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#and stat.value not in filter_list]
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# Create sorted, deduped list of all stats in data_list.
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ys = [Stat[stat_name] for stat_name in sorted(list(set([stat_name for data in data_list for stat_name in data if type(data[stat_name]) is not list])))]
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print([stat.value for stat in ys])
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fig, axes = plt.subplots(rows, int(math.ceil(len(ys) / rows)),
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figsize = (16 * size_multiplier, 9 * size_multiplier))
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match plot:
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case Plot.BOX:
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for i, y in enumerate(ys):
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box_plot(axes[i % rows][int(i / rows)], stats_list, x, y)
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box_plot(axes[i % rows][int(i / rows)], data_list, x, y)
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case Plot.LINE:
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for i, y in enumerate(ys):
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line_plot(axes[i % rows][int(i / rows)], stats_list, x, y, color)
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line_plot(axes[i % rows][int(i / rows)], data_list, x, y, color)
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handles, labels = axes[i % rows][int(i / rows)].get_legend_handles_labels()
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else:
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@ -99,9 +103,9 @@ def visualize(
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match plot:
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case Plot.BOX:
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box_plot(ax, stats_list, x, y)
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box_plot(ax, data_list, x, y)
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case Plot.LINE:
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line_plot(ax, stats_list, x, y, color)
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line_plot(ax, data_list, x, y, color)
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handles, labels = ax.get_legend_handles_labels()
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@ -116,7 +120,7 @@ def visualize(
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title = "altra_spmv"
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fig.suptitle(title, fontsize = font_size)
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fig.legend(handles, labels, fontsize = font_size)
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fig.supxlabel(x, fontsize = font_size)
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fig.supxlabel(x.value, fontsize = font_size)
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plt.savefig(title + ".png", dpi = 100)
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plt.show()
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@ -138,19 +142,22 @@ def main():
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help = 'font size',
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default = 40)
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parser.add_argument('-x',
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#choices=[x.name.lower() for x in Stat],
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choices=[x.name.lower() for x in Stat],
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help = 'the name of the x axis')
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parser.add_argument('-y',
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#choices=[x.name.lower() for x in Stat],
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choices=[x.name.lower() for x in Stat],
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help = 'the name of the y axis')
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parser.add_argument('-c', '--color',
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#choices=[x.name.lower() for x in Stat],
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choices=[x.name.lower() for x in Stat],
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help = 'the name of the color')
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parser.add_argument('-f', '--filter', nargs = '+',
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help = 'a comma-separated string of names and values to filter out.',
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default = [])
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args = parser.parse_args()
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args.plot = Plot[args.plot.upper()]
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args.x = Stat[args.x.upper()] if args.x is not None else None
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args.y = Stat[args.y.upper()] if args.y is not None else None
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args.color = Stat[args.color.upper()] if args.color is not None else None
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data_list: list[dict] = list()
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@ -159,14 +166,17 @@ def main():
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data_list.append(json.load(file))
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print(filename + " loaded.")
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print(data_list)
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#x = Stat[args.x.upper()] if args.x is not None else None
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x = args.x
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#y = Stat[args.y.upper()] if args.y is not None else None
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y = args.y
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#color = Stat[args.color.upper()] if args.color is not None else None
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color = args.color
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visualize(data_list, args.plot, args.rows, args.size, args.font_size, x, y, color, args.filter)
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visualize(
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data_list,
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args.plot,
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args.rows,
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args.size,
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args.font_size,
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args.x,
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args.y,
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args.color,
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args.filter
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)
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if __name__ == '__main__':
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main()
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