381 lines
11 KiB
Plaintext
381 lines
11 KiB
Plaintext
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os, sys
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sys.path.append(os.path.abspath(os.path.dirname(os.path.abspath(__file__))+"/../scripts"))
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import fileinput
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import numpy as np
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import matplotlib as mpl
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import re
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show = False
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if len(sys.argv) > 1 and sys.argv[1] == 'show':
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show = True
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if not show:
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mpl.use('pgf')
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import matplotlib.pyplot as plt
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from common import set_size, config_plt, get_colors
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config_plt()
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def loadData(fn):
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content = []
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with open(fn) as f:
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content = f.readlines()
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zipcontent = zip(content[0::3], content[1::3], content[2::3])
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values = {}
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for lconf, ltime, lresult in zipcontent:
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match = re.search(r"f: [a-z_]*_([a-z]+).*grasp: ([0-9]+), outer: ([0-9]+), inner: ([0-9]+).*threads: (\d+)", lconf)
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if match:
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method = match.group(1)
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grasp_n = int(match.group(2))
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outer = int(match.group(3))
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inner = int(match.group(4))
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ncores = int(match.group(5))
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match = re.search(r"user ([^ ]+) sys (.*)$", ltime)
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if match:
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user = float(match.group(1))
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sys = float(match.group(2))
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if method == 'firstlevel':
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time = (user+sys) / min(ncores, grasp_n)
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else:
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time = (user+sys) / ncores
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if not ncores in values:
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values[ncores] = []
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values[ncores].append(time);
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return values
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def exportLegend(legend, filename):
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fig = legend.figure
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fig.canvas.draw()
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fig.savefig(filename, format='pdf', bbox_inches=legend.get_window_extent().transformed(fig.dpi_scale_trans.inverted()))
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def figSeq(title, xlabel, rotation, output, datasrcs, scale, error=False):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"time (s)")
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nd = len(datasrcs)
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labels = [datasrc[1] for datasrc in datasrcs]
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plt.xticks(range(len(labels)), labels, rotation=rotation, ha='right')
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width = 0.5
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pos = .5-.5*nd
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x = 0
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(labels, label)
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for k, a in values.items():
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m = np.mean(a)
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s = 2.5758 * np.std(a) / np.sqrt(len(a)) # confiance 99 %
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plt.bar(x, m, width=width, color=barcolor, label=label)
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if error:
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plt.errorbar(x, m, s, elinewidth=2, capsize=4, ecolor=errcolor)
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label=''
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pos = pos + 1
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x = x+1
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fig.set_size_inches(set_size(455.24408, scale))
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if not show:
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fig.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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def figCores(title, xlabel, xticks, output, datasrcs, scale, ycor=np.NaN, legendfile='', error=False):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"time (s)")
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plt.xticks(xticks)
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if not np.isnan(ycor):
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plt.gca().yaxis.set_label_coords(ycor, .5)
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nd = len(datasrcs)
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labels = [datasrc[1] for datasrc in datasrcs]
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width = 0.16
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pos = .5-.5*nd
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(labels, label)
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for k, a in values.items():
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x = int(k)
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m = np.mean(a)
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s = 2.5758 * np.std(a) / np.sqrt(len(a)) # confiance 99 %
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x = x + pos*width
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plt.bar(x, m, width=width, color=barcolor, label=label)
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if error:
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plt.errorbar(x, m, s, elinewidth=.6, capsize=.6, ecolor=errcolor)
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label=''
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pos = pos + 1
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fig.set_size_inches(set_size(455.24408, scale))
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bbox = (.9, .88)
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if legendfile != '': # isolation of the legend
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bbox = (2, 2)
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# legend = fig.legend(bbox_to_anchor=bbox)
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# if legendfile != '':
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# if legendfile != 'x':
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# exportLegend(legend, legendfile)
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# legend.remove()
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if not show:
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fig.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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def figCoresSpeedup(title, xlabel, xticks, output, basetime, datasrcs, scale, legendfile=''):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"speed up")
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plt.xticks(xticks)
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plt.gca().yaxis.set_label_coords(-.105, .5)
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nd = len(datasrcs)
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labels = [datasrc[1] for datasrc in datasrcs]
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width = 0.25
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pos = .5-.5*nd
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(labels, label)
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if 1 in values:
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values.pop(1)
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for k, a in values.items():
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x = int(k)
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m = basetime/np.mean(a)
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x = x + pos*width
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plt.bar(x, m, width=width, color=barcolor, label=label)
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label=''
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pos = pos + 1
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fig.set_size_inches(set_size(455.24408, scale))
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bbox = (.485, .88)
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if legendfile != '': # isolation of the legend
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bbox = (2, 2)
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# legend = fig.legend(bbox_to_anchor=bbox)
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# if legendfile != '':
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# if legendfile != 'x':
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# exportLegend(legend, legendfile)
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# legend.remove()
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if not show:
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fig.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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def figSizeSpeedup(title, xlabel, xticks, output, basetimes, cores, datasrcs, scale, legendfile=''):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"speed up")
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plt.xticks(xticks)
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plt.gca().yaxis.set_label_coords(-.11, .5)
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nd = len(datasrcs)
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labels = [datasrc[1] for datasrc in datasrcs]
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width = 0.5
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pos = .5-.5*nd
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for fs, label in datasrcs:
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barcolor, errcolor = get_colors(labels, label)
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xi = 0
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for f in fs:
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valuesAllCores = loadData(f)
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values = valuesAllCores[cores]
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x = xticks[xi]
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m = basetimes[xi]/np.mean(values)
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x = x + pos*width
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plt.bar(x, m, width=width, color=barcolor, label=label)
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label=''
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xi = xi + 1
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pos = pos + 1
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fig.set_size_inches(set_size(455.24408, scale))
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bbox = (1.31, .88)
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if legendfile != '': # isolation of the legend
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bbox = (2, 2)
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legend = fig.legend(bbox_to_anchor=bbox)
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if legendfile != '':
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if legendfile != 'x':
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exportLegend(legend, legendfile)
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legend.remove()
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if not show:
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fig.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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# script
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plts = []
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for dataset in ['dj38', 'qa194']:
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plt = figSeq(u"", u"method", 45,
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"plots/rt_graspels_"+dataset+"_24_20_20_seq.pdf", [
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_hw_seq_v', 'hw_seq'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_sk_seq', 'sk_seq'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_hw_par_v', 'hw_par'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_sk_par_firstlevel', 'sk_firstlevel'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_sk_par_staticpool', 'sk_staticpool'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_sk_par_dynamicpool', 'sk_dynamicpool'],
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['data_graspels/seq/rt_seq_'+dataset+'_24_20_20_sk_par_thread', 'sk_thread'],
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],
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scale=.8,
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error=True
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)
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plts.append(plt)
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for dataset in ['dj38', 'qa194']:
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plt = figCores(u"", u"number of cores", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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"plots/rt_graspels_"+dataset+"_24_20_20_par.pdf", [
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['data_graspels/var_cores/rt_cores_'+dataset+'_24_20_20_hw_par_v', 'hw_par'],
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['data_graspels/var_cores/rt_cores_'+dataset+'_24_20_20_sk_par_firstlevel', 'sk_firstlevel'],
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['data_graspels/var_cores/rt_cores_'+dataset+'_24_20_20_sk_par_staticpool', 'sk_staticpool'],
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['data_graspels/var_cores/rt_cores_'+dataset+'_24_20_20_sk_par_dynamicpool', 'sk_dynamicpool'],
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['data_graspels/var_cores/rt_cores_'+dataset+'_24_20_20_sk_par_thread', 'sk_thread'],
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],
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scale=.8,
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error=False
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)
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plts.append(plt)
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legendfile = 'plots/rt_graspels_qa194_var_grasp_par_legend.pdf'
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for grasp_n in range(4, 21, 4):
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plt = figCores(u"", u"number of cores", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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"plots/rt_graspels_qa194_v"+str(grasp_n)+"_20_20_par.pdf", [
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_hw_par_v', 'hw_par'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_firstlevel', 'sk_firstlevel'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_staticpool', 'sk_staticpool'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_dynamicpool', 'sk_dynamicpool'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_thread', 'sk_thread'],
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],
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scale=.48,
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ycor=-.16,
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legendfile=legendfile,
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error=False
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)
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plts.append(plt)
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legendfile = 'x'
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# legendfile = 'plots/rt_graspels_qa194_var_els_iter_max_par_legend.pdf'
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# for els_iter_max in [1, 2, 4, 8, 12, 16, 20, 30, 40, 50]:
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# plt = figCores(u"", u"number of cores", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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# "plots/rt_graspels_qa194_4_v"+str(els_iter_max)+"_20_par.pdf", [
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# ['data_graspels/var_els/rt_cores_qa194_4_'+str(els_iter_max)+'_20_hw_par_v', 'hw_par'],
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# ['data_graspels/var_els/rt_cores_qa194_4_'+str(els_iter_max)+'_20_sk_par_firstlevel', 'sk_firstlevel'],
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# ['data_graspels/var_els/rt_cores_qa194_4_'+str(els_iter_max)+'_20_sk_par_staticpool', 'sk_staticpool'],
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# ['data_graspels/var_els/rt_cores_qa194_4_'+str(els_iter_max)+'_20_sk_par_dynamicpool', 'sk_dynamicpool'],
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# ['data_graspels/var_els/rt_cores_qa194_4_'+str(els_iter_max)+'_20_sk_par_thread', 'sk_thread'],
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# ],
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# scale=.48,
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# ycor=-.13,
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# legendfile=legendfile,
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# error=True
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# )
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# plts.append(plt)
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# legendfile = 'x'
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for grasp_n in range(4, 21, 4):
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values = loadData('data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_hw_par_v')
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basetime = np.mean(values[1])
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plt = figCoresSpeedup(u"", u"number of cores", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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"plots/rt_graspels_qa194_"+str(grasp_n)+"_20_20_speedup.pdf", basetime, [
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_hw_par_v', 'hw_par'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_firstlevel', 'sk_firstlevel'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_staticpool', 'sk_staticpool'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_dynamicpool', 'sk_dynamicpool'],
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['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_thread', 'sk_thread'],
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],
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||
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|
scale=.8
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||
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)
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plts.append(plt)
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||
|
|
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||
|
|
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||
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|
# for cores in [1, 2, 4, 6, 8, 10, 12, 14, 16, 18]:
|
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|
|
# # for cores in [16]:
|
||
|
|
# basetimes = []
|
||
|
|
# for grasp_n in range(4, 21, 4):
|
||
|
|
# values = loadData('data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_hw_par_v')
|
||
|
|
# basetimes.append(np.mean(values[1]))
|
||
|
|
# values = loadData('data_graspels/var_cores/rt_cores_qa194_24_20_20_hw_par_v')
|
||
|
|
# basetimes.append(np.mean(values[1]))
|
||
|
|
#
|
||
|
|
# hw_par = ['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_hw_par_v' for grasp_n in range(4, 21, 4)]
|
||
|
|
# hw_par.append('data_graspels/var_cores/rt_cores_qa194_24_20_20_hw_par_v')
|
||
|
|
# firstlevel = ['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_firstlevel' for grasp_n in range(4, 21, 4)]
|
||
|
|
# firstlevel.append('data_graspels/var_cores/rt_cores_qa194_24_20_20_sk_par_firstlevel')
|
||
|
|
# staticpool = ['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_staticpool' for grasp_n in range(4, 21, 4)]
|
||
|
|
# staticpool.append('data_graspels/var_cores/rt_cores_qa194_24_20_20_sk_par_staticpool')
|
||
|
|
# dynamicpool = ['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_dynamicpool' for grasp_n in range(4, 21, 4)]
|
||
|
|
# dynamicpool.append('data_graspels/var_cores/rt_cores_qa194_24_20_20_sk_par_dynamicpool')
|
||
|
|
# thread = ['data_graspels/var_grasp/rt_cores_qa194_'+str(grasp_n)+'_20_20_sk_par_thread' for grasp_n in range(4, 21, 4)]
|
||
|
|
# thread.append('data_graspels/var_cores/rt_cores_qa194_24_20_20_sk_par_thread')
|
||
|
|
#
|
||
|
|
# plt = figSizeSpeedup(u"", u"$N$", [4, 8, 12, 16, 20, 24],
|
||
|
|
# "plots/rt_graspels_qa194_all_20_20_speedup_"+str(cores)+".pdf", basetimes, cores, [
|
||
|
|
# [hw_par, 'hw_par'],
|
||
|
|
# [firstlevel, 'sk_firstlevel'],
|
||
|
|
# [staticpool, 'sk_staticpool'],
|
||
|
|
# [dynamicpool, 'sk_dynamicpool'],
|
||
|
|
# [thread, 'sk_thread'],
|
||
|
|
# ],
|
||
|
|
# scale=.7
|
||
|
|
# )
|
||
|
|
# plts.append(plt)
|
||
|
|
|
||
|
|
|
||
|
|
if show:
|
||
|
|
for plt in plts:
|
||
|
|
plt.show()
|