Full graph generation code for Sims, Bakita, and Anderson, ECRTS 2019

gen_graphs_full.py

#!/usr/bin/python3
import matplotlib.pyplot as plt
import numpy

def read_sample(file):
    """Lazy function (generator) to read a file piece by piece.
    Default chunk size: 1k."""
    while True:
        line = file.readline()
        if line == b"*****\n":
            break
        if not line or line == "":
            break
        #    raise Exception("No more data to read from this sample file.")
        yield line

def load_data(file):
    header = file.readline()
    if not header:
        return (None,None)
    return (numpy.loadtxt(read_sample(file), delimiter=","), header.decode("utf-8").strip())

def util_header(header):
    elems = header.split(',')
    range_str = ""
    if ':' in header: # Autodetect new range-based utilizations
        ranges = eval(elems[3].replace(':',','))
        for elem in ranges:
            range_str += format_range(elem)
    else:
        range_str = format_range(elems[3:5])
    return "Task Utilization ∈ " + range_str
        
def format_range(domain):
    range_str = "[{0:.1f}, {1:.1f}]"
    """
    range_str = ""
    if float(domain[0]) == 0:
        range_str += "({0:.1f}, "
    else:
        range_str += "[{0:.1f}, "    
    if float(domain[1]) == 1:
        range_str += "{1:.1f})"
    else:
        range_str += "{1:.1f}]"
    """
    return range_str.format(float(domain[0]), float(domain[1]))

def format_header(header, util_on=True):
    elems = header.split(',')
    # Autodetect if this is uniform by inspecting the field count
    if ':' in header: # New, range-based system
        cores = "{0} Cores, ".format(int(elems[0]))
        util = util_header(header) + "\n" if util_on else ""
        sf = "{} Periods, Pessimistic Model".format(elems[8])
        #sf = s ∈ Gauss(0.72,{0:.2f}), f ∈ Gauss(0.72,{1:.2f})".format(float(elems[6]), float(elems[7]))
        #if len(elems) == 9:
        #    sf += ", {} Periods".format(elems[8])
        return cores + util + sf
    elif len(elems) > 10:
        cores = "{0} Cores, ".format(int(elems[0]))
        utile = util_header(header) + ", σ = {0:.3f}\n" if util_on else "σ = {0:.3f}, "
        utile = utile.format(float(elems[11]))
        sf = "s ∈ Uniform({0:.2f},{1:.2f}), f ∈ Uniform({2:.2f},{3:.2f})".format(float(elems[7]), float(elems[8]), float(elems[9]), float(elems[10]))
        return cores + utile + sf
    elif len(elems) > 8:
        cores = "{0} Cores, ".format(int(elems[0]))
        util = util_header(header) + "\n" if util_on else ""
        sf = "s ∈ Gauss(0.72,{0:.2f}), f ∈ Gauss(0.72,{1:.2f})".format(float(elems[7]), float(elems[8]))
        return cores + util + sf
        

def setup_figure(fig, header):
    #fig.legend(["[1] Oʙʟɪᴠɪᴏᴜs", "[2] Gʀᴇᴇᴅʏ-Tʜʀᴇᴀᴅ", "[3] Gʀᴇᴇᴅʏ-Pʜʏsɪᴄᴀʟ", "[4] Gʀᴇᴇᴅʏ-Mɪxᴇᴅ", "Oᴘᴛɪᴍᴀʟ"])#, loc="lower left")
    fig.legend(["CERT-MT (optimal)", "CERT-MT (greedy)", "Optimal Partitioned EDF"])
    fig.set_ylim(0,1.02)
    fig.set_xlabel('Utilization')
    fig.set_ylabel('Schedulability Ratio')
    fig.set_title(header)

def add_plot(target, dat, m_range_max=None):
    # Divide, but ignore if divisor is 0
    util_bins = dat[:,0]
    # Autodetect if we're plotting using the old unified count line, or the new per-alg count
    if len(dat[1]) <= 12:
        UMA_cols = dat[:,2:].T
        task_count = dat[:,1]
        things = numpy.divide(UMA_cols, task_count, out=numpy.zeros_like(UMA_cols), where=task_count!=0).T
    else:
        alg_cnt = len(dat[0,1:])//2
        sample_cnt = len(dat) - 1
        things = numpy.zeros((len(dat),alg_cnt))
        for i in range(sample_cnt):
            #print(dat[i,:])
            for j in range(alg_cnt):
                if dat[i,j*2+1] == 0:
                    things[i,j] = 0
                else:
                    things[i,j] = dat[i,j*2+2]/dat[i,j*2+1]
            #print(things[i,:])
    # Crop charts
    stop_idx = len(util_bins) - 1
    if m_range_max:
        for idx in range(len(util_bins)):
            if util_bins[idx] > m_range_max:
                stop_idx = idx
                break
    # Autodetect mode (SMART vs CERT-MT)
    if len(dat[1]) <= 12 and (sum(things[:stop_idx,0])!=0 or sum(things[:stop_idx,1])!=0 or sum(things[:stop_idx,2])!=0 or sum(things[:stop_idx,3])!=0 or sum(things[:stop_idx,4])!=0):
        # SMART
        target.plot(util_bins[:stop_idx], things[:stop_idx,0], "-")
        annotate_mode = 9 # Figure number to generate annotations for
        if annotate_mode == 1:
            target.annotate("[1,2,4]", xy=(20.75, 0.7), xycoords="data", xytext=(18.75, 0.7),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[3]", xy=(21.25, 0.5), xycoords="data", xytext=(23.25, 0.5),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
        elif annotate_mode == 6:
            target.annotate("[1,2,4]", xy=(5.35, 0.5), xycoords="data", xytext=(4.75, 0.5),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[3]", xy=(5.25, 0.7), xycoords="data", xytext=(5.75, 0.7),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
        elif annotate_mode == 7:
            target.annotate("[1,2,4]", xy=(19.75, 0.9), xycoords="data", xytext=(21.75, 0.9),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[3]", xy=(19, 0.9), xycoords="data", xytext=(18, 0.8),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
        elif annotate_mode == 8:
            target.annotate("[3]", xy=(17.7, 0.65), xycoords="data", xytext=(16.45, 0.50),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[1]", xy=(17.5, 0.9), xycoords="data", xytext=(16.25, 0.75),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[2,4]", xy=(18, 0.7), xycoords="data", xytext=(19.5, 0.7),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
        elif annotate_mode == 9:
            target.annotate("[1]", xy=(16.75, 0.15), xycoords="data", xytext=(16, 0.05),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[3]", xy=(16.9, 0.12), xycoords="data", xytext=(18.2, 0.21),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[2,4]", xy=(16.7, 0.25), xycoords="data", xytext=(18, 0.34),
                textcoords="data", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
        elif annotate_mode == 10:
            target.annotate("[2]", xy=(16.1, 0), xycoords="data", xytext=(0.05, 0.17),
                textcoords="axes fraction", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[1]", xy=(16.25, 0.75), xycoords="data", xytext=(0.03, 0.5),
                textcoords="axes fraction", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[3]", xy=(17.5, 0.4), xycoords="data", xytext=(0.37, 0.4),
                textcoords="axes fraction", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)
            target.annotate("[4]", xy=(16.75, 0.6), xycoords="data", xytext=(0.3, 0.6),
                textcoords="axes fraction", arrowprops=dict(facecolor="black",
                    shrink=0.1, width=2, headwidth=8, ), horizontalalignment="center",
                    verticalalignment="bottom",)

        target.plot(util_bins[:stop_idx], things[:stop_idx,1], "--")
        target.plot(util_bins[:stop_idx], things[:stop_idx,2], "-.")
        target.plot(util_bins[:stop_idx], things[:stop_idx,3], ":")
        if sum(things[:stop_idx,5])!=0:
            target.plot(util_bins[:stop_idx], things[:stop_idx,4])
    else:
        styles = ["-", "--", ":", "-."]
        st_idx = 0
        # CERT-MT
        for i in range(5,len(things[0])):
            if sum(things[:stop_idx,i]) > 0:
                target.plot(util_bins[:stop_idx], things[:stop_idx,i], styles[st_idx])
                st_idx += 1
    
def plot_util_quad_from_file(path, m_range_max=None, save=False):
    file = open(path, "rb")
    file.readline() # Dump first line
    fig = plt.figure()
    cached_header = ""
    for i in range(1,5):
        dat, header = load_data(file)
        if dat is None:
            break
        cached_header = header
        etc = fig.add_subplot(2,2,i)
        add_plot(etc, dat, m_range_max)
        setup_figure(etc, util_header(header))
    fig.suptitle(format_header(cached_header, util_on=False), fontsize=18)
    fig.tight_layout(rect=[0, 0.03, 1, 0.90])
    if not save:
        plt.show()
    else:
        sdir = "/playpen/jbakita/SMART-ECRTS19/uniform-normal/results2/graphs/"
        plt.savefig(sdir + format_header(cached_header, util_on=False) + ".pdf")
    plt.close(fig)
    
def plot_utils_from_file(path, m_range_max=None, save=None):
    if save:
        plt.rcParams['figure.figsize'] = [6, 3]
    else:
        plt.rcParams['figure.figsize'] = [14, 5]
    file = open(path, "rb")
    file.readline() # Dump first line
    # Read all
    dats = []
    while True:
        dat, header = load_data(file)
        if dat is None:
            break
        dats.append((dat,header))
    for (dat, header) in sorted(dats, key=lambda t: t[1][:-8]):
        f = plt.figure()
        fig = f.add_subplot(1, 1, 1)
        add_plot(fig, dat, m_range_max)
        setup_figure(fig, format_header(header, util_on=True))
        if not save:
            plt.show()
        else:
            #sdir = "/playpen/jbakita/SMART-ECRTS19/uniform-normal/results2/graphs/"
            plt.savefig(save + format_header(header, util_on=True).replace('\n',' ') + ".pdf", bbox_inches="tight")
        plt.close(f)

### TO USE ###
# 1. Change the annotate variable on line 112 to the figure number
# 2. Uncomment the plot command for that figure number
# 3. Access output in `results/graphs` per-algorithm
###

#Fig1 plot_utils_from_file("gaussian-average/results/16_1000_1_1_normal.txt", 1.5*16, "gaussian-average/results/graphs/")
#Fig10 plot_utils_from_file("uniform-normal/results/16_1000_055_65_1_65_1_normal.txt", 1.5*16, "uniform-normal/results/graphs/")
#Fig6 plot_utils_from_file("gaussian-average/results/4_1000_1_1_normal.txt", 1.5*4, "gaussian-average/results/graphs/")
#Fig7 plot_utils_from_file("gaussian-average/results/16_1000_1_1_normal.txt", 1.5*16, "gaussian-average/results/graphs/")
#Fig8 plot_utils_from_file("gaussian-average/results/16_1000_1_1_normal.txt", 1.5*16, "gaussian-average/results/graphs/")
#Fig9 plot_utils_from_file("gaussian-average/results/16_1000_1_1_normal.txt", 1.5*16, "gaussian-average/results/graphs/")