plot-comparison-of-implementation-variants.py

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#
# You might have to add . to the PYTHONPATH
#
import matplotlib.pyplot as plt
import argparse
import tarfile
import os
 
from noh import (
    Choices,
    ParallelisationVariants,
    Parallelisation_DomainDecomposition,
    StorageVariants,
    SortingVariants,
    AllKernelOptimisationVariants,
    Storage_Scattered,
    BasicKernelOptimisationVariants,
    KernelOptimisation_NoOptimisation,
)
 
Symbols = ["-o", "-s", "-v", "-^"]
 
 
def plot_for_subset_of_variants(
    choices,
    tar,
    plt,
):
    data_files = tar.getnames()
    data_points = []
    for choice in choices:
        print("study choice/variant {}".format(choice))
        for file in data_files:
            if choice + ".out" in file:
                print("read file {}".format(file))
                time_stepping_cost = 0
                tar.extract(file)
                input_file = open(file, "r")
                for line in input_file:
                    if "time stepping:" in line:
                        time_stepping_cost = float(
                            line.split("time stepping:")[1].split("s")[0]
                        )
                print("cost is {}s".format(time_stepping_cost))
                data_points.append(time_stepping_cost)
                os.remove(file)
 
    thread_count = archive_file.split("-threads")[0].split("-")[-1]
    plt.plot(
        data_points,
        Symbols[args.file.index(archive_file)],
        label=thread_count + " threads",
    )
 
 
def construct_labels(
    sub_choices,
):
    """!
 
    You can pass in the subchoices directly, or you can simply pass in some
    strings. The routine takes the points in the identifier and replaces them
    with linebreaks.
 
    """
    return [x.replace(".", "\n") for x in sub_choices]
 
 
def add_legend_and_labels(
    plt,
    labels_on_x_axis,
):
    """!
 
    Add the labels of the choices as x-ticks and rotate them by 90 degrees.
    After that, we have to extend the whitespace underneath the plot, as the
    labels otherwise don't fit in.
 
    """
    plt.xticks(
        range(0, len(labels_on_x_axis)),
        labels_on_x_axis,
        rotation="vertical",
        fontsize=6,
    )
    plt.ylabel("time [t]=s")
    plt.legend()
    plt.subplots_adjust(bottom=0.3)
 
 
if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description="SPH comparison of different implementation variants"
    )
    parser.add_argument(
        "file",
        nargs="+",
        help="Filename of the file to parse. You can specify multiple files.",
    )
    parser.add_argument(
        "-o", "--output", dest="output", required=True, help="Output file"
    )
    args = parser.parse_args()
 
    # ===========================
    # All variants
    # ===========================
    sub_choices = Choices
    plt.clf()
    for archive_file in args.file:
        print("Study file {}".format(archive_file))
        plot_for_subset_of_variants(
            sub_choices, tarfile.open(archive_file, "r:gz"), plt
        )
    add_legend_and_labels(
        plt,
        construct_labels(sub_choices),
    )
    print("Write to file {}.pdf and {}.png".format(args.output, args.output))
    plt.savefig(args.output + ".pdf")
    plt.savefig(args.output + ".png")
    plt.yscale("log")
    plt.savefig(args.output + "-log.pdf")
    plt.savefig(args.output + "-log.png")
 
    # ===========================
    # Only domain decomposition
    # ===========================
    sub_choices = [
        parallelisation_variant
        + "."
        + storage
        + "."
        + sorting
        + "."
        + kernel_optimisation
        for parallelisation_variant in [Parallelisation_DomainDecomposition]
        for storage in [Storage_Scattered]
        for sorting in SortingVariants
        for kernel_optimisation in BasicKernelOptimisationVariants
    ] + [
        parallelisation_variant
        + "."
        + storage
        + "."
        + sorting
        + "."
        + kernel_optimisation
        for parallelisation_variant in [Parallelisation_DomainDecomposition]
        for storage in StorageVariants
        for sorting in SortingVariants
        for kernel_optimisation in AllKernelOptimisationVariants
    ]
    plt.clf()
    for archive_file in args.file:
        print("Study file {}".format(archive_file))
        plot_for_subset_of_variants(
            sub_choices, tarfile.open(archive_file, "r:gz"), plt
        )
    add_legend_and_labels(
        plt,
        construct_labels(
            [
                x.replace(Parallelisation_DomainDecomposition + ".", "")
                for x in sub_choices
            ]
        ),
    )
    print("Write to file {}.pdf and {}.png".format(args.output, args.output))
    plt.savefig(args.output + "-domain-decomposition.pdf")
    plt.savefig(args.output + "-domain-decomposition.png")
    plt.yscale("log")
    plt.savefig(args.output + "-domain-decomposition-log.pdf")
    plt.savefig(args.output + "-domain-decomposition-log.png")
 
    # ===========================
    # Without any optimisation
    # ===========================
    sub_choices = [
        parallelisation_variant
        + "."
        + storage
        + "."
        + sorting
        + "."
        + kernel_optimisation
        for parallelisation_variant in [Parallelisation_DomainDecomposition]
        for storage in [Storage_Scattered] + StorageVariants
        for sorting in SortingVariants
        for kernel_optimisation in [KernelOptimisation_NoOptimisation]
    ]
    plt.clf()
    for archive_file in args.file:
        print("Study file {}".format(archive_file))
        plot_for_subset_of_variants(
            sub_choices, tarfile.open(archive_file, "r:gz"), plt
        )
    add_legend_and_labels(
        plt,
        construct_labels(
            [
                x.replace(Parallelisation_DomainDecomposition + ".", "")
                for x in sub_choices
            ]
        ),
    )
    print("Write to file {}.pdf and {}.png".format(args.output, args.output))
    plt.savefig(args.output + "-compare-only-storage.pdf")
    plt.savefig(args.output + "-compare-only-storage.png")
    plt.yscale("log")
    plt.savefig(args.output + "-compare-only-storage-log.pdf")
    plt.savefig(args.output + "-compare-only-storage-log.png")