From cdae81d3f065cd1f667040b6b430221742df57c5 Mon Sep 17 00:00:00 2001 From: Neea Date: Thu, 23 Nov 2023 17:09:41 -0500 Subject: [PATCH] update perf plotting --- plot/bar.py | 120 ++++++++++++------ ...__bar_acc_PT-1_ref_result_perf_darwin.pdf} | Bin 20056 -> 14736 bytes ...__bar_acc_PT-1_ref_result_perf_debian.pdf} | Bin 20071 -> 14726 bytes ...__bar_acc_PT-1_ref_result_perf_ubuntu.pdf} | Bin 20080 -> 14722 bytes ..._bar_acc_PT-1_ref_result_perf_windows.pdf} | Bin 20050 -> 14705 bytes .../__bar_acc_PT-2_ref_result_perf_darwin.pdf | Bin 0 -> 14672 bytes .../__bar_acc_PT-2_ref_result_perf_debian.pdf | Bin 0 -> 14660 bytes .../__bar_acc_PT-2_ref_result_perf_ubuntu.pdf | Bin 0 -> 14683 bytes ...__bar_acc_PT-2_ref_result_perf_windows.pdf | Bin 0 -> 14664 bytes ref_result/__bar_acc_ref_result_attacks.pdf | Bin 23849 -> 24083 bytes ref_result/__bar_acc_ref_result_original.pdf | Bin 23810 -> 24042 bytes ref_result/__bar_acc_ref_result_reset.pdf | Bin 23888 -> 24121 bytes 12 files changed, 78 insertions(+), 42 deletions(-) rename ref_result/{__bar_acc_ref_result_perf_debian.pdf => __bar_acc_PT-1_ref_result_perf_darwin.pdf} (57%) rename ref_result/{__bar_acc_ref_result_perf_ubuntu.pdf => __bar_acc_PT-1_ref_result_perf_debian.pdf} (57%) rename ref_result/{__bar_acc_ref_result_perf_darwin.pdf => __bar_acc_PT-1_ref_result_perf_ubuntu.pdf} (57%) rename ref_result/{__bar_acc_ref_result_perf_windows.pdf => __bar_acc_PT-1_ref_result_perf_windows.pdf} (57%) create mode 100644 ref_result/__bar_acc_PT-2_ref_result_perf_darwin.pdf create mode 100644 ref_result/__bar_acc_PT-2_ref_result_perf_debian.pdf create mode 100644 ref_result/__bar_acc_PT-2_ref_result_perf_ubuntu.pdf create mode 100644 ref_result/__bar_acc_PT-2_ref_result_perf_windows.pdf diff --git a/plot/bar.py b/plot/bar.py index 1e5761b..5c3f70b 100644 --- a/plot/bar.py +++ b/plot/bar.py @@ -7,18 +7,21 @@ from plot import ResultData col0 = [240 / 255, 249 / 255, 232 / 255, 1] -col1 = [186 / 255, 228 / 255, 188 / 255, 1] -col2 = [123 / 255, 204 / 255, 196 / 255, 1] -col3 = [43 / 255, 140 / 255, 190 / 255, 1] -col4 = [220 / 255, 220 / 255, 220 / 255, 1] +col1 = [255 / 255, 201 / 255, 71 / 255, 1] +col2 = [100 / 255, 204 / 255, 197 / 255, 1] +col3 = [55 / 255, 71 / 255, 79 / 255, + 1] # [34 / 255, 40 / 255, 49 / 255, 1] +col4 = [7 / 255, 102 / 255, 173 / 255, 1] col5 = [8 / 255, 104 / 255, 172 / 255, 1] light_blue = [166 / 255, 206 / 255, 227 / 255, 1] dark_blue = [15 / 255, 90 / 255, 160 / 255, 1] -white = [1, 1, 1, 1] +white = [1] * 4 # global options -plt.rcParams["font.family"] = "Arial" -plt.rcParams['hatch.linewidth'] = .4 +overall = 'overall' +patterns = [None, None, None, None, None] +plt.rcParams['font.family'] = ['Arial'] +plt.rcParams['hatch.linewidth'] = .5 def gradient(light, dark): @@ -41,34 +44,37 @@ def multi_bar(ax, results, cat_names, colors): uniq_rl = [x for k, v in groupby(rlbl) for x in [k] + [' '] * (sum(1 for __ in v) - 1)] labels = [i for i, _ in enumerate(results)] - has_ov = llbl[-1].lower() == "overall" + has_ov = llbl[-1] == overall data = np.array([v for _, v in results]) data_cum = data.cumsum(axis=1) ay = ax.secondary_yaxis('right') ax.invert_yaxis() barh = ([0.6] * (len(llbl) - 2)) + [.8 if has_ov else 0.6] - totals = [sum(d) - .75 for d in data[1:]] + totals = [sum(d) - .3 for d in data[1:]] for i, (name, color) in enumerate(zip(cat_names, colors)): widths = data[1:, i] starts = data_cum[1:, i] - widths ax.barh(labels[1:], widths, left=starts, height=barh, - label=name, color=color, zorder=0) + label=name, color=color, zorder=0, lw=0, + hatch=patterns[i], + edgecolor=[.95, .95, .95, 1]) bars = ax.barh( - labels[1:], totals, left=.35, height=barh, color='none', - lw=.5, edgecolor=[0, 0, 0, .85], zorder=2, hatch=None) + labels[1:], totals, left=.1, height=barh, color='none', + lw=0.3, edgecolor=[0, 0, 0, 1], zorder=2, hatch=None) for idx in [i for i, tot in enumerate(totals) if tot < 1]: bars[idx].set_linewidth(0) - ax.set_yticklabels(llbl, weight='light') + ax.set_yticklabels(llbl) ax.set_yticks(np.arange(0, len(llbl), 1)) ax.set_xlim(0, np.sum(data, axis=1).max()) ax.yaxis.set_tick_params(length=0) - ay.set_yticklabels(uniq_rl, weight='light') + ay.set_yticklabels(uniq_rl) ay.set_ticks(np.arange(0, len(rlbl), 1)) ay.yaxis.set_tick_params(length=0) - if has_ov: - ax.get_yticklabels()[len(llbl) - 1].set_fontweight('bold') + for idx, lbl in enumerate(llbl): + if idx < len(ax.get_yticklabels()) and lbl == overall: + ax.get_yticklabels()[idx].set_fontweight('bold') ax.get_yticklabels()[0].set_ha("left") ax.get_yticklabels()[0].set_position((.035, 0)) ay.spines["right"].set_visible(False) @@ -81,16 +87,17 @@ def multi_bar(ax, results, cat_names, colors): ax.set_xticklabels([]) -def plot_acc(data, mean_data, subplots, plot_name, data_labels, - sort_key=None, colors=None, dlen=4): +def plot_acc(input_data, plot_name, data_labels, + sort_key=None, colors=None, dlen=4, overall_bar=True): + data, mean_data, subplots = input_data[0] if colors is None: color_count = len(mean_data) colors = get_color_scheme(color_count) colors.reverse() # determine plot size - sp_n = len(subplots) - plot_height = 1 + 4.5 * (len(data) / 24.) + sp_n, pl_n = len(subplots), len(input_data) + plot_height = (1 if overall_bar else .7) + 4.5 * (len(data) / 24.) h_ratios = [1] if sp_n == 1 else \ [len([x for x in data.values() if c == x[0][0]]) + (3 if i == sp_n - 1 else 0) @@ -100,7 +107,7 @@ def plot_acc(data, mean_data, subplots, plot_name, data_labels, # setup figure fig, axes = plt.subplots( - sp_n, 1, figsize=(3, plot_height), + sp_n, pl_n, figsize=(3 * pl_n, plot_height), gridspec_kw={'height_ratios': h_ratios}) ax = axes if sp_n == 1 else axes[-1] plt.subplots_adjust(wspace=0, hspace=0) @@ -108,22 +115,25 @@ def plot_acc(data, mean_data, subplots, plot_name, data_labels, # draw sub plots for i, ckey in enumerate(subplots): cdata = [(x[0][1:], x[1]) for x in data.values() - if ckey in x[0][0]] + if ckey == x[0][0]] if sort_key is not None: cdata.sort(key=sort_key) cdata.insert(0, (('', ckey), [0] * dlen)) - if ckey == subplots[-1]: + if ckey == subplots[-1] and overall_bar: empty = [((' ', ' '), [0] * dlen)] - overall = [v / sum(mean_data) * 100 for v in mean_data] - cdata = cdata + empty + [(('', 'overall'), overall)] + ov = [v / sum(mean_data) * 100 for v in mean_data] + cdata = cdata + empty + [(('', overall), ov)] multi_bar(axes if len(subplots) == 1 else axes[i], cdata, data_labels, colors=colors) # full figure formatting leg = fig.legend(data_labels, ncol=2, bbox_to_anchor=(0.22, 1.05), loc='upper left', frameon=False, - handlelength=.9, handletextpad=0.2, + handlelength=.9, handletextpad=0.4, columnspacing=.8, borderpad=0) + for p in leg.get_patches(): + p.set_edgecolor([0, 0, 0, .85]) + p.set_linewidth(.75) ax.yaxis.set_tick_params(length=0) ax.set_xticks([0, 25, 50, 75, 100]) @@ -133,7 +143,8 @@ def plot_acc(data, mean_data, subplots, plot_name, data_labels, ax.xaxis.set_visible(True) for i, lbl in enumerate(subplots): ax_ = axes if sp_n == 1 else axes[i] - shift = 0 if sp_n > 1 and lbl == subplots[-1] else .03 + shift = 0 if sp_n > 1 and lbl == subplots[-1] else \ + (.1 if sp_n == 1 else .03) box = ax_.get_position() box.y0 += shift box.y1 += shift @@ -147,10 +158,18 @@ def plot_acc(data, mean_data, subplots, plot_name, data_labels, class BarData(ResultData): - def get_acc_data(self): - nums = [BarData.fmt(r) for r in self.raw_rata] + def get_acc_data(self, key_test): + is_perf = 'perf' in self.directory + nums = [BarData.fmt(r) for r in self.raw_rata if key_test(r)] means = np.rint(np.mean(np.array( [v for _, v in nums]), axis=0)).tolist() + if not is_perf: + cnums = [BarData.fmt( + r, key="Comparison", att="CPGD") + for r in self.raw_rata if + ResultData.attack(r) == 'CPGD'] + if len(cnums): + nums += cnums cats = sorted(list(set([x for ((x, _, _), _) in nums]))) ndict = dict(enumerate(nums)) return ndict, means, cats @@ -165,8 +184,9 @@ def attack(r): return ResultData.attack(r).upper() @staticmethod - def fmt(r): - keys = (BarData.cls(r), BarData.name(r), BarData.attack(r)) + def fmt(r, key=None, att=None): + keys = (key or BarData.cls(r), BarData.name(r), + att or BarData.attack(r)) valid = round(BarData.valid(r)) evades = round(BarData.evades(r)) - valid accurate = round(BarData.acc(r)) - evades - valid @@ -177,15 +197,31 @@ def plot_name(self, pattern, out_dir): return self.fn_pattern('pdf', pattern, out_dir) +def make_plot(bdata, out_dir, is_perf, plot_name, key_test, + overall_bar=True): + bar_inputs = [[d.get_acc_data(key_test) for d in bdata][0]] + # assert (bars have same shape) + legend = ['valid', 'evasive', 'accurate', 'inaccurate'] + plot_acc(bar_inputs, + data_labels=legend, overall_bar=overall_bar, + plot_name=bdata[0].plot_name(plot_name, out_dir), + sort_key=(lambda x: (x[0][0], len(x[0][1]), x[0][1])) + if is_perf else + (lambda x: (x[0][0], x[0][1]))) + + def plot_bars(data_dir, out_dir=None): - bdata = BarData(data_dir) - if bdata.n_results: - nums, means, cats = bdata.get_acc_data() - plot_acc(nums, means, subplots=cats, - data_labels=[ - 'valid', 'evasive', 'accurate', 'inaccurate'], - plot_name=bdata.plot_name('bar_acc', out_dir), - sort_key= - (lambda x: (x[0][0], x[0][1])) - if 'perf' not in data_dir else - (lambda x: (x[0][0], x[0][1]))) + dirs = data_dir.split(',') + is_perf = 'perf/' in data_dir + bdata = [BarData(d) for d in dirs] + if is_perf: + for cats in ['PT-1', 'PT-2']: + key_test = lambda r: cats in BarData.name(r) + if len(bdata) and bdata[0].n_results: + make_plot( + bdata, out_dir, is_perf, 'bar_acc_' + cats, + key_test, overall_bar=False) + else: + key_test = lambda r: ResultData.attack(r) != 'CPGD' + if len(bdata) and bdata[0].n_results: + make_plot(bdata, out_dir, is_perf, 'bar_acc', key_test) diff --git a/ref_result/__bar_acc_ref_result_perf_debian.pdf b/ref_result/__bar_acc_PT-1_ref_result_perf_darwin.pdf similarity index 57% rename from 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