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Commit d3d2bbf9 authored by René Schöne's avatar René Schöne
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Changing diagram label noncached to semiautomatic.

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%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import matplotlib.axes, matplotlib.ticker import matplotlib.axes, matplotlib.ticker
import matplotlib.patches as mpatches import matplotlib.patches as mpatches
%matplotlib inline %matplotlib inline
plt.ioff() plt.ioff()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
from glob import glob from glob import glob
from datetime import datetime from datetime import datetime
from itertools import * from itertools import *
from operator import itemgetter from operator import itemgetter
import json, sys, traceback, os, functools, traceback import json, sys, traceback, os, functools, traceback
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
_pngpath, _pdfpath = 'pngs/', 'pdfs/' _pngpath, _pdfpath = 'pngs/', 'pdfs/'
if not os.path.exists(_pngpath): if not os.path.exists(_pngpath):
os.mkdir(_pngpath) os.mkdir(_pngpath)
if not os.path.exists(_pdfpath): if not os.path.exists(_pdfpath):
os.mkdir(_pdfpath) os.mkdir(_pdfpath)
def pngpath(filename): def pngpath(filename):
return _pngpath + filename + '.png' return _pngpath + filename + '.png'
def pdfpath(filename): def pdfpath(filename):
return _pdfpath + filename + '.pdf' return _pdfpath + filename + '.pdf'
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
spec_files = glob('profiling/*/specs') spec_files = glob('profiling/*/specs')
spec_files.sort() spec_files.sort()
specs = {os.path.basename(os.path.dirname(f)):np.genfromtxt(f, delimiter=' ', dtype=int) specs = {os.path.basename(os.path.dirname(f)):np.genfromtxt(f, delimiter=' ', dtype=int)
for f in spec_files} for f in spec_files}
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
linestyles = ["-","--","-.",":"] linestyles = ["-","--","-.",":"]
colors = ('blue','black','red','orange','green','magenta','yellow', 'cyan', 'purple', 'firebrick') colors = ('blue','black','red','orange','green','magenta','yellow', 'cyan', 'purple', 'firebrick')
colorcycle = cycle(colors) colorcycle = cycle(colors)
lastpe = False lastpe = False
line_def = [] line_def = []
color_def = [] color_def = []
## Currently disabled due to fragile and unused output ## Currently disabled due to fragile and unused output
if False: if False:
for spec in specs: for spec in specs:
pe, comp, impl, mode = (spec[2], spec[4], spec[5], spec[6]) pe, comp, impl, mode = (spec[2], spec[4], spec[5], spec[6])
if not lastpe or lastpe != pe: if not lastpe or lastpe != pe:
color = next(colorcycle) color = next(colorcycle)
linecycle = cycle(linestyles) linecycle = cycle(linestyles)
line = next(linecycle) line = next(linecycle)
lastpe = pe lastpe = pe
line_def.append(line) line_def.append(line)
color_def.append(color) color_def.append(color)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def set_keys(*indices): def set_keys(*indices):
"""Returns a function that returns a tuple of key values""" """Returns a function that returns a tuple of key values"""
def get_keys(seq, indices=indices): def get_keys(seq, indices=indices):
keys = [] keys = []
for i in indices: for i in indices:
keys.append(seq[i]) keys.append(seq[i])
return tuple(keys) return tuple(keys)
return get_keys return get_keys
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def get_average_times(dat, dirCol, stepCol, timeCol): def get_average_times(dat, dirCol, stepCol, timeCol):
if dat.size == 1: if dat.size == 1:
return np.array([np.array([dat.item()[timeCol]])]) return np.array([np.array([dat.item()[timeCol]])])
dat.sort(order=['dir', 'step']) dat.sort(order=['dir', 'step'])
result = {} result = {}
for (c_dir, c_step), rows in groupby(dat, key=set_keys('dir','step')): for (c_dir, c_step), rows in groupby(dat, key=set_keys('dir','step')):
#print c_dir, c_step, rows #print c_dir, c_step, rows
c_dir, c_step, total_time, counter = None, None, 0, 0 c_dir, c_step, total_time, counter = None, None, 0, 0
for row in rows: for row in rows:
if not c_dir: if not c_dir:
c_dir = row[dirCol] c_dir = row[dirCol]
if not c_step: if not c_step:
c_step = row[stepCol] c_step = row[stepCol]
total_time+=row[timeCol] total_time+=row[timeCol]
counter += 1 counter += 1
result.setdefault(c_dir, []).append([c_step, total_time*1.0/counter]) result.setdefault(c_dir, []).append([c_step, total_time*1.0/counter])
result2 = [] result2 = []
for c_dir, rows in result.iteritems(): for c_dir, rows in result.iteritems():
inner = [] inner = []
result2.append([row[1] for row in rows]) result2.append([row[1] for row in rows])
# for row in rows: # for row in rows:
# inner.append(row[1]) # inner.append(row[1])
# result2.append(inner) # result2.append(inner)
return np.array([np.array(rows) for rows in result2]) return np.array([np.array(rows) for rows in result2])
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def is_axis(a): def is_axis(a):
return not type(a) is np.ndarray return not type(a) is np.ndarray
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
with open('profiling/kinds.json') as fd: with open('profiling/kinds.json') as fd:
kinds = json.load(fd) kinds = json.load(fd)
print 'Kinds: {}'.format(kinds) print 'Kinds: {}'.format(kinds)
``` ```
%% Output %% Output
Kinds: {u'strategies': [u'normal', u'flush', u'noncached'], u'changes': [u'update', u'sw', u'res', u'complex', u'mixed']} Kinds: {u'strategies': [u'normal', u'flush', u'noncached'], u'changes': [u'update', u'sw', u'res', u'complex', u'mixed']}
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
no_split, split_change_only, split_both = 0, 1, 2 no_split, split_change_only, split_both = 0, 1, 2
dat, dat2, dat3 = None, None, None dat, dat2, dat3 = None, None, None
def read_single_result(f, name, dtype, data_column, since): def read_single_result(f, name, dtype, data_column, since):
global dat, dat2, dat3 global dat, dat2, dat3
def convdate(text): def convdate(text):
return datetime.strptime(text, '%Y-%m-%dT%H:%M:%S.%f') return datetime.strptime(text, '%Y-%m-%dT%H:%M:%S.%f')
def convdir(text): def convdir(text):
return int(text[-3:]) return int(text[-3:])
def convstep(text): def convstep(text):
return int(text[0:2]) return int(text[0:2])
def safe_div(a, b): def safe_div(a, b):
return a/b if b>0 else "{}!".format(a) return a/b if b>0 else "{}!".format(a)
dat = np.genfromtxt(f, delimiter=',', names=True, dtype=dtype, dat = np.genfromtxt(f, delimiter=',', names=True, dtype=dtype,
converters={'timestamp':convdate, 'step':convstep, 'dir': convdir}) converters={'timestamp':convdate, 'step':convstep, 'dir': convdir})
if since: if since:
dat = dat[dat['timestamp'] > since ] dat = dat[dat['timestamp'] > since ]
dat2 = get_average_times(dat, 1, 2, data_column).transpose() dat2 = get_average_times(dat, 1, 2, data_column).transpose()
len_dat = 1 if len(dat.shape) == 0 else len(dat) len_dat = 1 if len(dat.shape) == 0 else len(dat)
if dat2.size == 0: if dat2.size == 0:
print 'Did not load any record for {}'.format(name) print 'Did not load any record for {}'.format(name)
else: else:
if len_dat > 1: if len_dat > 1:
print 'Loaded {0} record(s) for {1} ({2[0]}x{2[1]} unique) ~= {3} run(s)'.format( print 'Loaded {0} record(s) for {1} ({2[0]}x{2[1]} unique) ~= {3} run(s)'.format(
len_dat, name, dat2.shape, safe_div(len_dat,dat2.size)) len_dat, name, dat2.shape, safe_div(len_dat,dat2.size))
else: else:
print 'Loaded no data for {}'.format(name) print 'Loaded no data for {}'.format(name)
dat3 = dat2 dat3 = dat2
return dat2 return dat2
def read_results(prefix, name, dtype, data_column, since, splitted = no_split): def read_results(prefix, name, dtype, data_column, since, splitted = no_split):
if splitted in (split_change_only, split_both): if splitted in (split_change_only, split_both):
result = {} result = {}
for change in kinds['changes']: for change in kinds['changes']:
result.setdefault(change, {}) result.setdefault(change, {})
if splitted == split_both: if splitted == split_both:
for strategy in kinds['strategies']: for strategy in kinds['strategies']:
result[change].setdefault(strategy, {}) result[change].setdefault(strategy, {})
new_name = '{0}_{1}_{2}'.format(change, strategy, name) new_name = '{0}_{1}_{2}'.format(change, strategy, name)
f = 'profiling/splitted/{0}_{1}.csv'.format(prefix, new_name) f = 'profiling/splitted/{0}_{1}.csv'.format(prefix, new_name)
result[change][strategy] = read_single_result(f, new_name, dtype, data_column, since) result[change][strategy] = read_single_result(f, new_name, dtype, data_column, since)
else: # splitted == split_change_only else: # splitted == split_change_only
new_name = '{0}_{1}'.format(change, name) new_name = '{0}_{1}'.format(change, name)
f = 'profiling/splitted/{0}_{1}.csv'.format(prefix, new_name) f = 'profiling/splitted/{0}_{1}.csv'.format(prefix, new_name)
result[change] = read_single_result(f, new_name, dtype, data_column, since) result[change] = read_single_result(f, new_name, dtype, data_column, since)
return result return result
else: # splitted = no_split else: # splitted = no_split
f = 'profiling/{0}-{1}-results.csv'.format(prefix, name) f = 'profiling/{0}-{1}-results.csv'.format(prefix, name)
return read_single_result(f, name, dtype, data_column, since) return read_single_result(f, name, dtype, data_column, since)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def read_gen_results(impl, since = None): def read_gen_results(impl, since = None):
return read_results('gen', impl, ('datetime64[us]', int, int, float), 3, since, splitted = split_both) return read_results('gen', impl, ('datetime64[us]', int, int, float), 3, since, splitted = split_both)
def read_sol_results(solver, since = None): def read_sol_results(solver, since = None):
return read_results('sol', solver, ('datetime64[us]', int, int, int, int, int, float, float), 7, since, return read_results('sol', solver, ('datetime64[us]', int, int, int, int, int, float, float), 7, since,
splitted = split_change_only) splitted = split_change_only)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def safe(a, i, start = 0): def safe(a, i, start = 0):
try: try:
return a[start:,i] return a[start:,i]
except IndexError: except IndexError:
return np.zeros(a[:,0].size) return np.zeros(a[:,0].size)
def es(y, x): def es(y, x):
""" Ensure size of y compared to x """ """ Ensure size of y compared to x """
if y.shape[0] != x.shape[0]: if y.shape[0] != x.shape[0]:
y = np.ones(x.shape[0]) * y[0] y = np.ones(x.shape[0]) * y[0]
return y return y
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## ILP-Re-Generation and Solving Time ## ILP-Re-Generation and Solving Time
- ILP-Re-Generation describes the time it takes for the Scheme implementations to evaluate the attribute computing the ILP - ILP-Re-Generation describes the time it takes for the Scheme implementations to evaluate the attribute computing the ILP
- it does not include the time to read from and write to disk - it does not include the time to read from and write to disk
- "Java" denotes the Java- and EMF-based generation - "Java" denotes the Java- and EMF-based generation
- ILP Solving describes the time it takes the solvers (GLPK and Gurobi in this case) to solve the generated ILP - ILP Solving describes the time it takes the solvers (GLPK and Gurobi in this case) to solve the generated ILP
- "GLPK (Java)" denotes the time to solve the ILP generated by the Java-based generation with GLPK. Its format was modifiert slightly to be accepted by GLPK, as it was originally generated for lp_solve - "GLPK (Java)" denotes the time to solve the ILP generated by the Java-based generation with GLPK. Its format was modifiert slightly to be accepted by GLPK, as it was originally generated for lp_solve
- "GLPK (Scheme)" denotes the time to solve the ILP generated by any scheme implementation with GLPK - "GLPK (Scheme)" denotes the time to solve the ILP generated by any scheme implementation with GLPK
- the plots show different system configurations - the plots show different system configurations
- a system configuration is given by "r x ( c \* i \* m )", which describes a system with *r* resources and *c* software components with *i* implementations having *m* modes each. - a system configuration is given by "r x ( c \* i \* m )", which describes a system with *r* resources and *c* software components with *i* implementations having *m* modes each.
- for one such configuration the same experiment is run, i.e. the system is modified 7 times leading to the 7 steps, whereas only changes on hardware resources are made - for one such configuration the same experiment is run, i.e. the system is modified 7 times leading to the 7 steps, whereas only changes on hardware resources are made
- for the cases involving Java (both, generation and solving), the same time is used for every step, as the generation always starts from skretch. Further, the changes (e.g. change the value of a single hardware resource while generation) can not be reflected by the Java System Generator - for the cases involving Java (both, generation and solving), the same time is used for every step, as the generation always starts from skretch. Further, the changes (e.g. change the value of a single hardware resource while generation) can not be reflected by the Java System Generator
- on the x-axis, the steps of this manipulation are shown - on the x-axis, the steps of this manipulation are shown
- the initial generation of the ILP (step zero) is only shown below in numbers, as it would skew the diagrams - the initial generation of the ILP (step zero) is only shown below in numbers, as it would skew the diagrams
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
Header = ['timestamp', 'dir', 'step', 'rows', 'cols', 'non-zero', 'ilp-sol', 'ti-ilp-sol'] Header = ['timestamp', 'dir', 'step', 'rows', 'cols', 'non-zero', 'ilp-sol', 'ti-ilp-sol']
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
racket_dats = read_gen_results('plt-r6rs', since = datetime(2015,8,17,0,0,0)) racket_dats = read_gen_results('plt-r6rs', since = datetime(2015,8,17,0,0,0))
larceny_dats = read_gen_results('larceny', since = datetime(2015,6,12,0,0,0)) larceny_dats = read_gen_results('larceny', since = datetime(2015,6,12,0,0,0))
java_dats = read_gen_results('java') java_dats = read_gen_results('java')
``` ```
%% Output %% Output
Loaded 1584 record(s) for update_normal_plt-r6rs (8x31 unique) ~= 6 run(s) Loaded 1584 record(s) for update_normal_plt-r6rs (8x31 unique) ~= 6 run(s)
Loaded 504 record(s) for update_flush_plt-r6rs (8x31 unique) ~= 2 run(s) Loaded 504 record(s) for update_flush_plt-r6rs (8x31 unique) ~= 2 run(s)
Loaded 600 record(s) for update_noncached_plt-r6rs (8x31 unique) ~= 2 run(s) Loaded 600 record(s) for update_noncached_plt-r6rs (8x31 unique) ~= 2 run(s)
Loaded 588 record(s) for sw_normal_plt-r6rs (7x31 unique) ~= 2 run(s) Loaded 588 record(s) for sw_normal_plt-r6rs (7x31 unique) ~= 2 run(s)
Loaded 245 record(s) for sw_flush_plt-r6rs (7x31 unique) ~= 1 run(s) Loaded 245 record(s) for sw_flush_plt-r6rs (7x31 unique) ~= 1 run(s)
Loaded 602 record(s) for sw_noncached_plt-r6rs (7x31 unique) ~= 2 run(s) Loaded 602 record(s) for sw_noncached_plt-r6rs (7x31 unique) ~= 2 run(s)
Loaded 605 record(s) for res_normal_plt-r6rs (7x31 unique) ~= 2 run(s) Loaded 605 record(s) for res_normal_plt-r6rs (7x31 unique) ~= 2 run(s)
Loaded 245 record(s) for res_flush_plt-r6rs (7x31 unique) ~= 1 run(s) Loaded 245 record(s) for res_flush_plt-r6rs (7x31 unique) ~= 1 run(s)
Loaded 609 record(s) for res_noncached_plt-r6rs (7x31 unique) ~= 2 run(s) Loaded 609 record(s) for res_noncached_plt-r6rs (7x31 unique) ~= 2 run(s)
Loaded 242 record(s) for complex_normal_plt-r6rs (11x11 unique) ~= 2 run(s) Loaded 242 record(s) for complex_normal_plt-r6rs (11x11 unique) ~= 2 run(s)
Loaded 121 record(s) for complex_flush_plt-r6rs (11x11 unique) ~= 1 run(s) Loaded 121 record(s) for complex_flush_plt-r6rs (11x11 unique) ~= 1 run(s)
Loaded 121 record(s) for complex_noncached_plt-r6rs (11x11 unique) ~= 1 run(s) Loaded 121 record(s) for complex_noncached_plt-r6rs (11x11 unique) ~= 1 run(s)
Loaded 803 record(s) for mixed_normal_plt-r6rs (100x2 unique) ~= 4 run(s) Loaded 803 record(s) for mixed_normal_plt-r6rs (100x2 unique) ~= 4 run(s)
Loaded 359 record(s) for mixed_flush_plt-r6rs (100x2 unique) ~= 1 run(s) Loaded 359 record(s) for mixed_flush_plt-r6rs (100x2 unique) ~= 1 run(s)
Loaded 200 record(s) for mixed_noncached_plt-r6rs (100x2 unique) ~= 1 run(s) Loaded 200 record(s) for mixed_noncached_plt-r6rs (100x2 unique) ~= 1 run(s)
Loaded 512 record(s) for update_normal_larceny (8x31 unique) ~= 2 run(s) Loaded 512 record(s) for update_normal_larceny (8x31 unique) ~= 2 run(s)
Loaded no data for update_flush_larceny Loaded no data for update_flush_larceny
Loaded no data for update_noncached_larceny Loaded no data for update_noncached_larceny
Loaded 217 record(s) for sw_normal_larceny (7x31 unique) ~= 1 run(s) Loaded 217 record(s) for sw_normal_larceny (7x31 unique) ~= 1 run(s)
Loaded no data for sw_flush_larceny Loaded no data for sw_flush_larceny
Loaded no data for sw_noncached_larceny Loaded no data for sw_noncached_larceny
Loaded 217 record(s) for res_normal_larceny (7x31 unique) ~= 1 run(s) Loaded 217 record(s) for res_normal_larceny (7x31 unique) ~= 1 run(s)
Loaded no data for res_flush_larceny Loaded no data for res_flush_larceny
Loaded no data for res_noncached_larceny Loaded no data for res_noncached_larceny
Loaded 121 record(s) for complex_normal_larceny (11x11 unique) ~= 1 run(s) Loaded 121 record(s) for complex_normal_larceny (11x11 unique) ~= 1 run(s)
Loaded no data for complex_flush_larceny Loaded no data for complex_flush_larceny
Loaded no data for complex_noncached_larceny Loaded no data for complex_noncached_larceny
Loaded no data for mixed_normal_larceny Loaded no data for mixed_normal_larceny
Loaded no data for mixed_flush_larceny Loaded no data for mixed_flush_larceny
Loaded no data for mixed_noncached_larceny Loaded no data for mixed_noncached_larceny
Loaded 88 record(s) for update_normal_java (1x31 unique) ~= 2 run(s) Loaded 88 record(s) for update_normal_java (1x31 unique) ~= 2 run(s)
Loaded no data for update_flush_java Loaded no data for update_flush_java
Loaded no data for update_noncached_java Loaded no data for update_noncached_java
Loaded no data for sw_normal_java Loaded no data for sw_normal_java
Loaded no data for sw_flush_java Loaded no data for sw_flush_java
Loaded no data for sw_noncached_java Loaded no data for sw_noncached_java
Loaded no data for res_normal_java Loaded no data for res_normal_java
Loaded no data for res_flush_java Loaded no data for res_flush_java
Loaded no data for res_noncached_java Loaded no data for res_noncached_java
Loaded no data for complex_normal_java Loaded no data for complex_normal_java
Loaded no data for complex_flush_java Loaded no data for complex_flush_java
Loaded no data for complex_noncached_java Loaded no data for complex_noncached_java
Loaded no data for mixed_normal_java Loaded no data for mixed_normal_java
Loaded no data for mixed_flush_java Loaded no data for mixed_flush_java
Loaded no data for mixed_noncached_java Loaded no data for mixed_noncached_java
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
java_glpk_dats = read_sol_results('java', since = datetime(2015,6,22,0,0,0)) java_glpk_dats = read_sol_results('java', since = datetime(2015,6,22,0,0,0))
try: try:
glpk_dats = read_sol_results('glpk') glpk_dats = read_sol_results('glpk')
except: except:
print(traceback.format_exc()) print(traceback.format_exc())
gurobi_dats = read_sol_results('gurobi') gurobi_dats = read_sol_results('gurobi')
``` ```
%% Output %% Output
Loaded 23 record(s) for update_java (1x23 unique) ~= 1 run(s) Loaded 23 record(s) for update_java (1x23 unique) ~= 1 run(s)
Loaded no data for sw_java Loaded no data for sw_java
Loaded no data for res_java Loaded no data for res_java
Loaded no data for complex_java Loaded no data for complex_java
Loaded no data for mixed_java Loaded no data for mixed_java
Loaded 1928 record(s) for update_glpk (8x31 unique) ~= 7 run(s) Loaded 1928 record(s) for update_glpk (8x31 unique) ~= 7 run(s)
Loaded 241 record(s) for sw_glpk (7x31 unique) ~= 1 run(s) Loaded 241 record(s) for sw_glpk (7x31 unique) ~= 1 run(s)
Traceback (most recent call last): Traceback (most recent call last):
File "<ipython-input-14-a9613a72d048>", line 3, in <module> File "<ipython-input-14-a9613a72d048>", line 3, in <module>
glpk_dats = read_sol_results('glpk') glpk_dats = read_sol_results('glpk')
File "<ipython-input-11-3738473b7378>", line 5, in read_sol_results File "<ipython-input-11-3738473b7378>", line 5, in read_sol_results
splitted = split_change_only) splitted = split_change_only)
File "<ipython-input-10-b4f10b934785>", line 44, in read_results File "<ipython-input-10-b4f10b934785>", line 44, in read_results
result[change] = read_single_result(f, new_name, dtype, data_column, since) result[change] = read_single_result(f, new_name, dtype, data_column, since)
File "<ipython-input-10-b4f10b934785>", line 24, in read_single_result File "<ipython-input-10-b4f10b934785>", line 24, in read_single_result
len_dat, name, dat2.shape, safe_div(len_dat,dat2.size)) len_dat, name, dat2.shape, safe_div(len_dat,dat2.size))
IndexError: tuple index out of range IndexError: tuple index out of range
Loaded 216 record(s) for update_gurobi (8x27 unique) ~= 1 run(s) Loaded 216 record(s) for update_gurobi (8x27 unique) ~= 1 run(s)
Loaded no data for sw_gurobi Loaded no data for sw_gurobi
Loaded no data for res_gurobi Loaded no data for res_gurobi
Loaded no data for complex_gurobi Loaded no data for complex_gurobi
Loaded no data for mixed_gurobi Loaded no data for mixed_gurobi
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
p_ax_nr, p_line_def, p_col_def, p_label = 0, 1, 2, 3 p_ax_nr, p_line_def, p_col_def, p_label = 0, 1, 2, 3
p_gen_racket, p_gen_larceny, p_gen_java = 4, 5, 6 p_gen_racket, p_gen_larceny, p_gen_java = 4, 5, 6
p_sol_glpk, p_sol_gurobi, p_sol_java_glpk = 4, 5, 6 p_sol_glpk, p_sol_gurobi, p_sol_java_glpk = 4, 5, 6
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_gen(changeName, strategy, params): def draw_gen(changeName, strategy, params):
try: try:
name = 'gen_{0}_{1}'.format(changeName, strategy) name = 'gen_{0}_{1}'.format(changeName, strategy)
# needed number of axes equals ax_nr+1 now # needed number of axes equals ax_nr+1 now
f, ax_arr = plt.subplots(nrows = ax_nr+1, ncols = 3, sharex=True, sharey=True) f, ax_arr = plt.subplots(nrows = ax_nr+1, ncols = 3, sharex=True, sharey=True)
f.set_size_inches(25.5,3.5*(ax_nr+1)) f.set_size_inches(25.5,3.5*(ax_nr+1))
one_plot = ax_arr.shape[1] == 1 one_plot = ax_arr.shape[1] == 1
f.patch.set_facecolor('none') f.patch.set_facecolor('none')
f.patch.set_alpha(0.0) f.patch.set_alpha(0.0)
lines, labels = [], [] lines, labels = [], []
for p in params: for p in params:
ax_tup = ax_arr if one_plot else ax_arr[p[p_ax_nr]] ax_tup = ax_arr if one_plot else ax_arr[p[p_ax_nr]]
ax_j = ax_tup[0] ax_j = ax_tup[0]
ax_r = ax_tup[1] ax_r = ax_tup[1]
ax_l = ax_tup[2] ax_l = ax_tup[2]
# ax_j.set_ylim([0,50]) # ax_j.set_ylim([0,50])
# ax_r.set_ylim([0,10]) # ax_r.set_ylim([0,10])
# ax_l.set_ylim([0,10]) # ax_l.set_ylim([0,10])
# x_g = np.array(xrange(1,len(p[1])+1)) # start at one, since first gen-time is cut # x_g = np.array(xrange(1,len(p[1])+1)) # start at one, since first gen-time is cut
x_g = np.array(xrange(START_STEP,len(p[p_gen_racket])+START_STEP)) # start at zero x_g = np.array(xrange(START_STEP,len(p[p_gen_racket])+START_STEP)) # start at zero
line_java = ax_j.plot(x_g, p[p_gen_java][0]*np.ones(len(p[p_gen_racket])), ls = p[p_line_def], line_java = ax_j.plot(x_g, p[p_gen_java][0]*np.ones(len(p[p_gen_racket])), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
line_racket = ax_r.plot(x_g, es(p[p_gen_racket], x_g), ls = p[p_line_def], line_racket = ax_r.plot(x_g, es(p[p_gen_racket], x_g), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
line_larceny = ax_l.plot(x_g, es(p[p_gen_larceny], x_g), ls = p[p_line_def], line_larceny = ax_l.plot(x_g, es(p[p_gen_larceny], x_g), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
ax_l.legend(loc='upper left', bbox_to_anchor=(1, 1.02)) ax_l.legend(loc='upper left', bbox_to_anchor=(1, 1.02))
lines.append(line_racket[0]) lines.append(line_racket[0])
labels.append(p[p_label]) labels.append(p[p_label])
for ax in ax_arr if one_plot else ax_arr.flatten(): for ax in ax_arr if one_plot else ax_arr.flatten():
ax.set_ylabel('seconds') ax.set_ylabel('seconds')
ax.patch.set_alpha(1) ax.patch.set_alpha(1)
ax.patch.set_facecolor('white') ax.patch.set_facecolor('white')
# first_ax = ax_arr if one_plot else ax_arr[0] # first_ax = ax_arr if one_plot else ax_arr[0]
# plt.suptitle('ILP Generation Time', fontsize = 16) # plt.suptitle('ILP Generation Time', fontsize = 16)
# first_ax[0].set_title('Java') # first_ax[0].set_title('Java')
# first_ax[1].set_title('Racket') # first_ax[1].set_title('Racket')
# first_ax[2].set_title('Larceny') # first_ax[2].set_title('Larceny')
# Fine-tune figure; make subplots close to each other and hide x ticks for # Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plots. # all but bottom plots.
f.subplots_adjust(hspace=0.2) f.subplots_adjust(hspace=0.2)
plt.setp([a.get_xticklabels() for a in f.axes[:-3]], visible=False) plt.setp([a.get_xticklabels() for a in f.axes[:-3]], visible=False)
plt.setp([a.get_yticklabels() for a in f.axes], visible=True) plt.setp([a.get_yticklabels() for a in f.axes], visible=True)
plt.savefig(pdfpath(name), facecolor=f.get_facecolor(), edgecolor='none') plt.savefig(pdfpath(name), facecolor=f.get_facecolor(), edgecolor='none')
plt.savefig(pngpath(name), facecolor=f.get_facecolor(), edgecolor='none') plt.savefig(pngpath(name), facecolor=f.get_facecolor(), edgecolor='none')
except Exception as e: except Exception as e:
print 'Error while drawing gen in {0}-{1}: {2}'.format(change, strategy, e) print 'Error while drawing gen in {0}-{1}: {2}'.format(change, strategy, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_sol(changeName, params): def draw_sol(changeName, params):
try: try:
name = 'sol_{}'.format(changeName) name = 'sol_{}'.format(changeName)
f, ax_arr = plt.subplots(nrows = ax_nr+1, ncols = 3, sharex=True, sharey=True) f, ax_arr = plt.subplots(nrows = ax_nr+1, ncols = 3, sharex=True, sharey=True)
f.set_size_inches(25.5,3.5*(ax_nr+1)) f.set_size_inches(25.5,3.5*(ax_nr+1))
one_plot = ax_arr.shape[1] == 1 one_plot = ax_arr.shape[1] == 1
f.patch.set_facecolor('none') f.patch.set_facecolor('none')
f.patch.set_alpha(0.0) f.patch.set_alpha(0.0)
lines, labels = [], [] lines, labels = [], []
for p in params: for p in params:
ax_tup = ax_arr if one_plot else ax_arr[p[p_ax_nr]] ax_tup = ax_arr if one_plot else ax_arr[p[p_ax_nr]]
ax_javaglpk = ax_tup[0] ax_javaglpk = ax_tup[0]
ax_glpk = ax_tup[1] ax_glpk = ax_tup[1]
ax_gurobi = ax_tup[2] ax_gurobi = ax_tup[2]
x = np.array(xrange(0,len(p[p_sol_glpk]))) # start at zero x = np.array(xrange(0,len(p[p_sol_glpk]))) # start at zero
line_javaglpk = ax_javaglpk.plot(x, p[p_sol_java_glpk][0]*np.ones(len(p[p_sol_glpk])), ls = p[p_line_def], line_javaglpk = ax_javaglpk.plot(x, p[p_sol_java_glpk][0]*np.ones(len(p[p_sol_glpk])), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
line_glpk = ax_glpk.plot(x, es(p[p_sol_glpk],x), ls = p[p_line_def], line_glpk = ax_glpk.plot(x, es(p[p_sol_glpk],x), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
line_gurobi = ax_gurobi.plot(x, es(p[p_sol_gurobi],x), ls = p[p_line_def], line_gurobi = ax_gurobi.plot(x, es(p[p_sol_gurobi],x), ls = p[p_line_def],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
ax_gurobi.legend(loc='upper left', bbox_to_anchor=(1, 1.02)) ax_gurobi.legend(loc='upper left', bbox_to_anchor=(1, 1.02))
lines.append(line_glpk[0]) lines.append(line_glpk[0])
labels.append(p[p_label]) labels.append(p[p_label])
for ax in ax_arr if one_plot else ax_arr.flatten(): for ax in ax_arr if one_plot else ax_arr.flatten():
ax.set_ylabel('seconds') ax.set_ylabel('seconds')
ax.patch.set_alpha(1) ax.patch.set_alpha(1)
ax.patch.set_facecolor('white') ax.patch.set_facecolor('white')
# first_ax = ax_arr if one_plot else ax_arr[0] # first_ax = ax_arr if one_plot else ax_arr[0]
# plt.suptitle('ILP Solving Time', fontsize = 16) # plt.suptitle('ILP Solving Time', fontsize = 16)
# first_ax[0].set_title('GLPK (Java)') # first_ax[0].set_title('GLPK (Java)')
# first_ax[1].set_title('GLPK (Scheme)') # first_ax[1].set_title('GLPK (Scheme)')
# first_ax[2].set_title('Gurobi (Scheme)') # first_ax[2].set_title('Gurobi (Scheme)')
# Fine-tune figure; make subplots close to each other and hide x ticks for # Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plots. # all but bottom plots.
f.subplots_adjust(hspace=0.2) f.subplots_adjust(hspace=0.2)
plt.setp([a.get_xticklabels() for a in f.axes[:-3]], visible=False) plt.setp([a.get_xticklabels() for a in f.axes[:-3]], visible=False)
plt.setp([a.get_yticklabels() for a in f.axes], visible=True) plt.setp([a.get_yticklabels() for a in f.axes], visible=True)
plt.savefig(pdfpath(name)) plt.savefig(pdfpath(name))
plt.savefig(pngpath(name)) plt.savefig(pngpath(name))
except Exception as e: except Exception as e:
print 'Error while drawing sol in {0}: {1}'.format(changeName, e) print 'Error while drawing sol in {0}: {1}'.format(changeName, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_comp_sol(changeName, params): def draw_comp_sol(changeName, params):
try: try:
name = 'comp_sol_{}'.format(changeName) name = 'comp_sol_{}'.format(changeName)
indices = [3, 12, 14, 19] indices = [3, 12, 14, 19]
for i in indices: for i in indices:
p = params[i] p = params[i]
x = np.array(xrange(0,len(p[p_sol_glpk]))) # start at zero x = np.array(xrange(0,len(p[p_sol_glpk]))) # start at zero
line_javaglpk = plt.plot(x, p[p_sol_java_glpk][0]*np.ones(len(p[p_sol_glpk])), ls = linestyles[0], line_javaglpk = plt.plot(x, p[p_sol_java_glpk][0]*np.ones(len(p[p_sol_glpk])), ls = linestyles[0],
c = p[p_col_def], label = p[p_label]) c = p[p_col_def], label = p[p_label])
line_glpk = plt.plot(x, es(p[p_sol_glpk],x), ls = p[p_line_def], c = p[p_col_def]) line_glpk = plt.plot(x, es(p[p_sol_glpk],x), ls = p[p_line_def], c = p[p_col_def])
line_gurobi = plt.plot(x, es(p[p_sol_gurobi],x), ls = p[p_line_def], c = p[p_col_def]) line_gurobi = plt.plot(x, es(p[p_sol_gurobi],x), ls = p[p_line_def], c = p[p_col_def])
plt.legend(loc = 'right') plt.legend(loc = 'right')
plt.ylabel('seconds') plt.ylabel('seconds')
plt.suptitle('ILP Solving Time - Comparison', fontsize = 16) plt.suptitle('ILP Solving Time - Comparison', fontsize = 16)
plt.savefig(pdfpath(name)) plt.savefig(pdfpath(name))
plt.savefig(pngpath(name)) plt.savefig(pngpath(name))
except Exception as e: except Exception as e:
print 'Error while drawing comp-sol in {0}: {1}'.format(changeName, e) print 'Error while drawing comp-sol in {0}: {1}'.format(changeName, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
## Currently disabled due to fragile and unused output ## Currently disabled due to fragile and unused output
if False: if False:
START_STEP, MAX_PLOTS_IN_ONE = 0, 7 START_STEP, MAX_PLOTS_IN_ONE = 0, 7
for change in kinds['changes']: for change in kinds['changes']:
print 'Change = {}'.format(change) print 'Change = {}'.format(change)
for strategy in kinds['strategies']: for strategy in kinds['strategies']:
ax_nr = 0 ax_nr = 0
print 'Stategy = {}'.format(strategy) print 'Stategy = {}'.format(strategy)
current_plot, ax_nr, last_res = 0, 0, -1 current_plot, ax_nr, last_res = 0, 0, -1
gen_params = [] gen_params = []
for i in xrange(len(specs)): for i in xrange(len(specs)):
current_res = specs[i][2] current_res = specs[i][2]
current_plot += 1 current_plot += 1
if current_plot > MAX_PLOTS_IN_ONE and last_res != current_res: if current_plot > MAX_PLOTS_IN_ONE and last_res != current_res:
ax_nr += 1 ax_nr += 1
current_plot = 0 current_plot = 0
gen_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]), gen_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),
safe(racket_dats[change][strategy],i,START_STEP), safe(racket_dats[change][strategy],i,START_STEP),
safe(larceny_dats[change][strategy],i,START_STEP), safe(larceny_dats[change][strategy],i,START_STEP),
safe(java_dats[change][strategy],i)]) safe(java_dats[change][strategy],i)])
last_res = current_res last_res = current_res
draw_gen(change, strategy, gen_params) draw_gen(change, strategy, gen_params)
# end of for strategies # end of for strategies
sol_params = [] sol_params = []
ax_nr = 0 ax_nr = 0
for i in xrange(len(specs)): for i in xrange(len(specs)):
current_res = specs[i][2] current_res = specs[i][2]
current_plot += 1 current_plot += 1
if current_plot > MAX_PLOTS_IN_ONE and last_res != current_res: if current_plot > MAX_PLOTS_IN_ONE and last_res != current_res:
ax_nr += 1 ax_nr += 1
current_plot = 0 current_plot = 0
sol_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]), sol_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),
safe(glpk_dats[change],i), safe(glpk_dats[change],i),
safe(gurobi_dats[change],i), safe(gurobi_dats[change],i),
safe(java_glpk_dats[change],i)]) safe(java_glpk_dats[change],i)])
draw_sol(change, sol_params) draw_sol(change, sol_params)
draw_comp_sol(change, sol_params) draw_comp_sol(change, sol_params)
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Settings ## Settings
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
llong, lshort, lveryshort = 0, 1, 2 llong, lshort, lveryshort = 0, 1, 2
l = ['Flushed', '$fs$', 'f'] l = ['Flushed', '$fs$', 'f']
stt = {'normal' : ['Incremental', '$inc$', 'i'], stt = {'normal' : ['Incremental', '$inc$', 'i'],
'flush' : l, 'flushed': l, 'flush' : l, 'flushed': l,
'noncached': ['Noncached', '$nc$', 'n']} 'noncached': ['Semiautomatic', '$semi$', 's']}
def strategy_to_titel(strategy, length = llong): def strategy_to_titel(strategy, length = llong):
try: try:
return stt[strategy.lower()][length] return stt[strategy.lower()][length]
except KeyError: except KeyError:
raise Exception('Unknown strategy/length: {0} {1}'.format(strategy, length)) raise Exception('Unknown strategy/length: {0} {1}'.format(strategy, length))
def strategy2_to_titel(ratio): def strategy2_to_titel(ratio):
s1, s2 = ratio.split('To') s1, s2 = ratio.split('To')
return r'${0} \rightarrow {1}$'.format(strategy_to_titel(s1, lshort)[1:-1], strategy_to_titel(s2, lshort)[1:-1]) return r'${0} \rightarrow {1}$'.format(strategy_to_titel(s1, lshort)[1:-1], strategy_to_titel(s2, lshort)[1:-1])
def change_to_title(change): def change_to_title(change):
# if change == 'complex': # if change == 'complex':
# change = 'mixed' # change = 'mixed'
return change.title() return change.title()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
box_facecolor, median_color, box_edgecolor, whisker_color, average_color = range(5) box_facecolor, median_color, box_edgecolor, whisker_color, average_color = range(5)
def setBoxColors(bp, colors, apply_to = None, linewidth=2): def setBoxColors(bp, colors, apply_to = None, linewidth=2):
for box in bp['boxes']: for box in bp['boxes']:
box.set(facecolor = colors[box_facecolor], linewidth=linewidth, edgecolor= colors[box_edgecolor]) box.set(facecolor = colors[box_facecolor], linewidth=linewidth, edgecolor= colors[box_edgecolor])
for median in bp['medians']: for median in bp['medians']:
median.set(color=colors[median_color], linewidth=linewidth) median.set(color=colors[median_color], linewidth=linewidth)
for whisker in bp['whiskers']: for whisker in bp['whiskers']:
whisker.set(ls = 'dotted', color=colors[whisker_color]) whisker.set(ls = 'dotted', color=colors[whisker_color])
# strategy: (box.facecolor, median.color, box.edgecolor, whisker.color) # strategy: (box.facecolor, median.color, box.edgecolor, whisker.color)
strategy_colors = {'noncached':('yellow','black','black', 'black', 'black'), strategy_colors = {'noncached':('yellow','black','black', 'black', 'black'),
'flush': ('cyan','black','black', 'black', 'black'), 'flush': ('cyan','black','black', 'black', 'black'),
'normal': ('blue', 'white', 'blue', 'black', 'black')} 'normal': ('blue', 'white', 'blue', 'black', 'black')}
strategy_colors.update({k:('black', 'red') for k in ('NormalToFlushed', 'NormalToNoncached', 'FlushedToNoncached')}) strategy_colors.update({k:('black', 'red') for k in ('NormalToFlushed', 'NormalToNoncached', 'FlushedToNoncached')})
def draw_average_line(y, c): def draw_average_line(y, c):
plt.axhline(y, ls = '-', color = c, zorder = 1, linewidth=2) plt.axhline(y, ls = '-', color = c, zorder = 1, linewidth=2)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
for change in kinds['changes']: for change in kinds['changes']:
for strategy in kinds['strategies']: for strategy in kinds['strategies']:
cdat = racket_dats[change][strategy] cdat = racket_dats[change][strategy]
print change, strategy, np.average(cdat) print change, strategy, np.average(cdat)
``` ```
%% Output %% Output
update normal 1.77210853495 update normal 1.77210853495
update flush 10.7880389785 update flush 10.7880389785
update noncached 9.96998723118 update noncached 9.96998723118
sw normal 9.44708971546 sw normal 9.44708971546
sw flush 11.3443110599 sw flush 11.3443110599
sw noncached 13.7821516129 sw noncached 13.7821516129
res normal 4.0042525181 res normal 4.0042525181
res flush 7.77624654378 res flush 7.77624654378
res noncached 9.03863824885 res noncached 9.03863824885
complex normal 2.04215702479 complex normal 2.04215702479
complex flush 4.21195867769 complex flush 4.21195867769
complex noncached 5.55057024793 complex noncached 5.55057024793
mixed normal 3.41092375 mixed normal 3.41092375
mixed flush 22.4315775 mixed flush 22.4315775
mixed noncached 27.787 mixed noncached 27.787
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Boxplots for generation times ## Boxplots for generation times
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
for draw_average in (True, False): for draw_average in (True, False):
print 'Draw_average = ', draw_average print 'Draw_average = ', draw_average
for (data, name) in ((java_dats, 'java'), (racket_dats, 'racket'), (larceny_dats, 'larceny')): for (data, name) in ((java_dats, 'java'), (racket_dats, 'racket'), (larceny_dats, 'larceny')):
sys.stdout.write('\n{}:'.format(name)) sys.stdout.write('\n{}:'.format(name))
# change, strategy = 'mixed', 'normal' # change, strategy = 'mixed', 'normal'
# if True: # if True:
for change in kinds['changes']: for change in kinds['changes']:
if change == 'complex': if change == 'complex':
continue continue
sys.stdout.write('\n {}'.format(change)) sys.stdout.write('\n {}'.format(change))
# if True: # if True:
for strategy in kinds['strategies']: for strategy in kinds['strategies']:
sys.stdout.write(','+strategy) sys.stdout.write(','+strategy)
cdat = data[change][strategy] cdat = data[change][strategy]
if cdat.size == 1: if cdat.size == 1:
sys.stdout.write('/') sys.stdout.write('/')
continue continue
colors = strategy_colors[strategy] colors = strategy_colors[strategy]
if draw_average: if draw_average:
draw_average_line(np.average(cdat),colors[average_color]) draw_average_line(np.average(cdat),colors[average_color])
bp = plt.boxplot(cdat.transpose(), patch_artist=True) bp = plt.boxplot(cdat.transpose(), patch_artist=True)
setBoxColors(bp, colors, linewidth=1) setBoxColors(bp, colors, linewidth=1)
axes = plt.gca() axes = plt.gca()
axes.set_ylim([0,50]) axes.set_ylim([0,50])
# plt.title('{0} {1} {2}'.format(name.title(), change_to_title(change), strategy_to_titel(strategy))) # plt.title('{0} {1} {2}'.format(name.title(), change_to_title(change), strategy_to_titel(strategy)))
plt.ylabel('seconds', fontsize = 14) plt.ylabel('seconds', fontsize = 14)
plt.xlabel('step', fontsize = 14) plt.xlabel('step', fontsize = 14)
plt.setp(axes.xaxis.get_majorticklabels(), fontsize = 16) plt.setp(axes.xaxis.get_majorticklabels(), fontsize = 16)
plt.setp(axes.yaxis.get_majorticklabels(), fontsize = 16) plt.setp(axes.yaxis.get_majorticklabels(), fontsize = 16)
if change == 'mixed': if change == 'mixed':
for i, label in enumerate(axes.get_xticklabels()): for i, label in enumerate(axes.get_xticklabels()):
label.set_visible(i==0 or (i+1) % 10 == 0) label.set_visible(i==0 or (i+1) % 10 == 0)
# plt.gca().tick_params(axis='x', direction='out', top = 'off', bottom = 'on') # plt.gca().tick_params(axis='x', direction='out', top = 'off', bottom = 'on')
plt.gca().tick_params(axis='x', top = 'off', bottom = 'off') plt.gca().tick_params(axis='x', top = 'off', bottom = 'off')
fname = 'gen_bp_{0}{1}_{2}_{3}'.format(name,'_avg' if draw_average else '',change,strategy) fname = 'gen_bp_{0}{1}_{2}_{3}'.format(name,'_avg' if draw_average else '',change,strategy)
plt.savefig(pdfpath(fname)) plt.savefig(pdfpath(fname))
plt.savefig(pngpath(fname)) plt.savefig(pngpath(fname))
plt.close() plt.close()
print '' print ''
``` ```
%% Output %% Output
Draw_average = True Draw_average = True
java: java:
update,normal,flush/,noncached/ update,normal,flush/,noncached/
sw,normal/,flush/,noncached/ sw,normal/,flush/,noncached/
res,normal/,flush/,noncached/ res,normal/,flush/,noncached/
mixed,normal/,flush/,noncached/ mixed,normal/,flush/,noncached/
racket: racket:
update,normal,flush,noncached update,normal,flush,noncached
sw,normal,flush,noncached sw,normal,flush,noncached
res,normal,flush,noncached res,normal,flush,noncached
mixed,normal,flush,noncached mixed,normal,flush,noncached
larceny: larceny:
update,normal,flush/,noncached/ update,normal,flush/,noncached/
sw,normal,flush/,noncached/ sw,normal,flush/,noncached/
res,normal,flush/,noncached/ res,normal,flush/,noncached/
mixed,normal/,flush/,noncached/ mixed,normal/,flush/,noncached/
Draw_average = False Draw_average = False
java: java:
update,normal,flush/,noncached/ update,normal,flush/,noncached/
sw,normal/,flush/,noncached/ sw,normal/,flush/,noncached/
res,normal/,flush/,noncached/ res,normal/,flush/,noncached/
mixed,normal/,flush/,noncached/ mixed,normal/,flush/,noncached/
racket: racket:
update,normal,flush,noncached update,normal,flush,noncached
sw,normal,flush,noncached sw,normal,flush,noncached
res,normal,flush,noncached res,normal,flush,noncached
mixed,normal,flush,noncached mixed,normal,flush,noncached
larceny: larceny:
update,normal,flush/,noncached/ update,normal,flush/,noncached/
sw,normal,flush/,noncached/ sw,normal,flush/,noncached/
res,normal,flush/,noncached/ res,normal,flush/,noncached/
mixed,normal/,flush/,noncached/ mixed,normal/,flush/,noncached/
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Boxplots for solving times ## Boxplots for solving times
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
#for (data, name) in ((java_glpk_dats, 'java'), (glpk_dats, 'scheme-glpk'), (gurobi_dats, 'glpk-gurobi')): #for (data, name) in ((java_glpk_dats, 'java'), (glpk_dats, 'scheme-glpk'), (gurobi_dats, 'glpk-gurobi')):
## Skipped for now (Problems with reading solving times) ## Skipped for now (Problems with reading solving times)
if False: if False:
sys.stdout.write('\n{}:'.format(name)) sys.stdout.write('\n{}:'.format(name))
# change = 'mixed' # change = 'mixed'
# if True: # if True:
for change in kinds['changes']: for change in kinds['changes']:
if change == 'complex': if change == 'complex':
continue continue
sys.stdout.write('\n {}'.format(change)) sys.stdout.write('\n {}'.format(change))
cdat = data[change] cdat = data[change]
bp = plt.boxplot(cdat.transpose(), patch_artist=True) bp = plt.boxplot(cdat.transpose(), patch_artist=True)
setBoxColors(bp, 'black', linewidth=1) setBoxColors(bp, 'black', linewidth=1)
axes = plt.gca() axes = plt.gca()
axes.set_ylim([0,50]) axes.set_ylim([0,50])
# plt.title('{0} {1} {2}'.format(name.title(), change_to_title(change), strategy_to_titel(strategy))) # plt.title('{0} {1} {2}'.format(name.title(), change_to_title(change), strategy_to_titel(strategy)))
plt.ylabel('seconds') plt.ylabel('seconds')
plt.xlabel('step') plt.xlabel('step')
if change == 'mixed': if change == 'mixed':
for i, label in enumerate(axes.get_xticklabels()): for i, label in enumerate(axes.get_xticklabels()):
label.set_visible(i==0 or (i+1) % 10 == 0) label.set_visible(i==0 or (i+1) % 10 == 0)
# plt.gca().tick_params(axis='x', direction='out', top = 'off', bottom = 'on') # plt.gca().tick_params(axis='x', direction='out', top = 'off', bottom = 'on')
plt.gca().tick_params(axis='x', top = 'off', bottom = 'off') plt.gca().tick_params(axis='x', top = 'off', bottom = 'off')
fname = 'sol_bp_{0}_{1}'.format(name,change) fname = 'sol_bp_{0}_{1}'.format(name,change)
plt.savefig(pdfpath(fname)) plt.savefig(pdfpath(fname))
plt.savefig(pngpath(fname)) plt.savefig(pngpath(fname))
plt.close() plt.close()
print '' print ''
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
### Single diagram for update, res, sw. and only for racket. ### Single diagram for update, res, sw. and only for racket.
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
width = 0.6 width = 0.6
name = 'racket' name = 'racket'
for draw_average in (True, False): for draw_average in (True, False):
print 'Draw_average = ', draw_average print 'Draw_average = ', draw_average
for change in ['update', 'res', 'sw']:#, 'mixed']: for change in ['update', 'res', 'sw']:#, 'mixed']:
#change = 'mixed' #change = 'mixed'
#if True: #if True:
sys.stdout.write('\n {}'.format(change)) sys.stdout.write('\n {}'.format(change))
invisibles = [] invisibles = []
if draw_average: if draw_average:
# draw horizontal lines first # draw horizontal lines first
for strategy in ['noncached', 'flush', 'normal']: for strategy in ['noncached', 'flush', 'normal']:
draw_average_line(np.average(racket_dats[change][strategy]), strategy_colors[strategy][average_color]) draw_average_line(np.average(racket_dats[change][strategy]), strategy_colors[strategy][average_color])
# now draw boxplots in front # now draw boxplots in front
for i, strategy in enumerate(['noncached', 'flush', 'normal']): for i, strategy in enumerate(['noncached', 'flush', 'normal']):
y = racket_dats[change][strategy] y = racket_dats[change][strategy]
colors = strategy_colors[strategy] colors = strategy_colors[strategy]
bp = plt.boxplot(y.transpose(), patch_artist=True, positions = np.arange(y.shape[0])*4+i) bp = plt.boxplot(y.transpose(), patch_artist=True, positions = np.arange(y.shape[0])*4+i)
setBoxColors(bp, colors) setBoxColors(bp, colors)
# line, = plt.plot([1,1],c[0]+'-') # line, = plt.plot([1,1],c[0]+'-')
invisibles.append(mpatches.Patch(color=colors[box_facecolor], label=strategy_to_titel(strategy), linewidth = 1)) invisibles.append(mpatches.Patch(color=colors[box_facecolor], label=strategy_to_titel(strategy), linewidth = 1))
axes = plt.gca() axes = plt.gca()
y_len = y.shape[0] y_len = y.shape[0]
axes.set_ylim([0,50]) axes.set_ylim([0,50])
plt.ylabel('seconds', fontsize = 14) plt.ylabel('seconds', fontsize = 14)
plt.xlabel('step', fontsize = 14) plt.xlabel('step', fontsize = 14)
if change == 'mixed': if change == 'mixed':
axes.set_xlim([-1,y_len*4+1]) axes.set_xlim([-1,y_len*4+1])
axes.set_xticklabels(range(0,111,10)) axes.set_xticklabels(range(0,111,10))
axes.set_xticks(range(1,y_len*4+41,40)) axes.set_xticks(range(1,y_len*4+41,40))
else: else:
axes.set_xlim([-1,y_len*4-1]) axes.set_xlim([-1,y_len*4-1])
axes.set_xticklabels(range(1,y_len+1)) axes.set_xticklabels(range(1,y_len+1))
axes.set_xticks(range(1,y_len*4,4)) axes.set_xticks(range(1,y_len*4,4))
plt.setp(axes.xaxis.get_majorticklabels(), fontsize = 16) plt.setp(axes.xaxis.get_majorticklabels(), fontsize = 16)
plt.setp(axes.yaxis.get_majorticklabels(), fontsize = 16) plt.setp(axes.yaxis.get_majorticklabels(), fontsize = 16)
plt.legend(handles=invisibles, loc='best' if change == 'mixed' else 'upper center', plt.legend(handles=invisibles, loc='best' if change == 'mixed' else 'upper center',
ncol = 3, mode = "expand", prop={'size':13}, handletextpad = 0.3) ncol = 3, mode = "expand", prop={'size':12}, handletextpad = 0.3)
fname = 'gen_bp_{0}{1}_{2}'.format(name,'_avg' if draw_average else '',change) fname = 'gen_bp_{0}{1}_{2}'.format(name,'_avg' if draw_average else '',change)
plt.savefig(pdfpath(fname)) plt.savefig(pdfpath(fname))
plt.savefig(pngpath(fname)) plt.savefig(pngpath(fname))
plt.close() plt.close()
print '' print ''
``` ```
%% Output %% Output
Draw_average = True Draw_average = True
update update
res res
sw sw
Draw_average = False Draw_average = False
update update
res res
sw sw
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Boxplot for solving times ## Boxplot for solving times
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
#for (data, name) in ((java_glpk_dats, 'java'), (glpk_dats, 'glpk'), (gurobi_dats, 'gurobi')): #for (data, name) in ((java_glpk_dats, 'java'), (glpk_dats, 'glpk'), (gurobi_dats, 'gurobi')):
## Skipped for now (Problems with reading solving times) ## Skipped for now (Problems with reading solving times)
if False: if False:
print name+':' print name+':'
#change = 'update' #change = 'update'
for change in kinds['changes']: for change in kinds['changes']:
#if True: #if True:
sys.stdout.write(change+' ') sys.stdout.write(change+' ')
# if True: # if True:
cdat = data[change] cdat = data[change]
plt.boxplot(cdat.transpose()) plt.boxplot(cdat.transpose())
# plt.title('{0} {1}'.format(name.title(), change_to_title(change))) # plt.title('{0} {1}'.format(name.title(), change_to_title(change)))
plt.ylabel('seconds') plt.ylabel('seconds')
plt.xlabel('step') plt.xlabel('step')
fname = 'sol_bp_{0}_{1}'.format(name,change) fname = 'sol_bp_{0}_{1}'.format(name,change)
plt.savefig(pdfpath(fname)) plt.savefig(pdfpath(fname))
plt.savefig(pngpath(fname)) plt.savefig(pngpath(fname))
plt.close() plt.close()
print '' print ''
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Attribute metrics ## Attribute metrics
- X = {normal, flushed, noncached} - X = {normal, flushed, noncached}
- (X1,X2) = {(normal, flushed), (normal, noncached), (flushed, noncached)} - (X1,X2) = {(normal, flushed), (normal, noncached), (flushed, noncached)}
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def read_att_result(name = 'profiling/att-percentages.csv', adjust_number = True): def read_att_result(name = 'profiling/att-percentages.csv', adjust_number = True):
def cdir(text): def cdir(text):
prefix = text[:-4] prefix = text[:-4]
number = int(text[-3:]) number = int(text[-3:])
if not adjust_number or prefix == 'update': if not adjust_number or prefix == 'update':
return number return number
elif prefix == 'sw': elif prefix == 'sw':
return 31+number return 31+number
elif prefix == 'res': elif prefix == 'res':
return 62+number return 62+number
elif prefix == 'complex': elif prefix == 'complex':
return 93+number return 93+number
elif prefix == 'mixed': elif prefix == 'mixed':
return 104+number return 104+number
elif prefix == '': elif prefix == '':
pass pass
else: else:
print 'Unknown prefix "{0}"'.format(prefix) print 'Unknown prefix "{0}"'.format(prefix)
dat = np.genfromtxt(name, delimiter=',', names=True, dat = np.genfromtxt(name, delimiter=',', names=True,
#dtype=(int, float, float, float, float, float, float, float), #dtype=(int, float, float, float, float, float, float, float),
converters={'dir': cdir}) converters={'dir': cdir})
dat.sort(axis=0) dat.sort(axis=0)
print 'Loaded {0} ({1} zero-values) attribute metric run(s) from {2}'.format(dat.size, print 'Loaded {0} ({1} zero-values) attribute metric run(s) from {2}'.format(dat.size,
reduce(lambda total,row: total + 1*(row == 0.0) if isinstance(row,int) or isinstance(row,float) else reduce(lambda total,row: total + 1*(row == 0.0) if isinstance(row,int) or isinstance(row,float) else
reduce(lambda x,y: x+1 if y == 0 else x, row, 0),dat.tolist(),0), name) reduce(lambda x,y: x+1 if y == 0 else x, row, 0),dat.tolist(),0), name)
return dat return dat
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
att_dat = read_att_result() att_dat = read_att_result()
att_dat.dtype att_dat.dtype
``` ```
%% Output %% Output
Loaded 106 (0 zero-values) attribute metric run(s) from profiling/att-percentages.csv Loaded 106 (0 zero-values) attribute metric run(s) from profiling/att-percentages.csv
dtype([('dir', '<f8'), ('normalBaseline', '<f8'), ('flushedBaseline', '<f8'), ('noncachedBaseline', '<f8'), ('ratioNormalToFlushed', '<f8'), ('ratioNormalToNoncached', '<f8'), ('ratioFlushedToNoncached', '<f8'), ('speedupNormalToFlushed', '<f8'), ('speedupNormalToNoncached', '<f8'), ('speedupFlushedToNoncached', '<f8')]) dtype([('dir', '<f8'), ('normalBaseline', '<f8'), ('flushedBaseline', '<f8'), ('noncachedBaseline', '<f8'), ('ratioNormalToFlushed', '<f8'), ('ratioNormalToNoncached', '<f8'), ('ratioFlushedToNoncached', '<f8'), ('speedupNormalToFlushed', '<f8'), ('speedupNormalToNoncached', '<f8'), ('speedupFlushedToNoncached', '<f8')])
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
1) {X}cache-miss-rate: `total.X.computed / total.X.called` 1) {X}cache-miss-rate: `total.X.computed / total.X.called`
- the rate for cache-misses (1 - cache-hits) of the method X - the rate for cache-misses (1 - cache-hits) of the method X
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
width = 0.5 width = 0.5
x = att_dat['dir'] x = att_dat['dir']
for n, (l, c) in enumerate((('noncached', 'grey'), ('flushed', 'g'), ('normal', 'b'))): for n, (l, c) in enumerate((('noncached', 'grey'), ('flushed', 'g'), ('normal', 'b'))):
y = att_dat[l + 'Baseline'] y = att_dat[l + 'Baseline']
#plt.plot(x, y, label = l, color = c) #plt.plot(x, y, label = l, color = c)
plt.bar(x*4*width + n*width, y, width, label = strategy_to_titel(l), color = c) plt.bar(x*4*width + n*width, y, width, label = strategy_to_titel(l), color = c)
plt.legend(loc = 'best') plt.legend(loc = 'best')
plt.ylabel('% computed') plt.ylabel('% computed')
#plt.suptitle('Cache Miss-Rate', fontsize = 16) #plt.suptitle('Cache Miss-Rate', fontsize = 16)
fname = 'att_miss' fname = 'att_miss'
plt.savefig(pdfpath(fname)) plt.savefig(pdfpath(fname))
plt.savefig(pngpath(fname)) plt.savefig(pngpath(fname))
#!pdfcrop doc/att_miss.pdf doc/att_miss_cropped.pdf > /dev/null #!pdfcrop doc/att_miss.pdf doc/att_miss_cropped.pdf > /dev/null
plt.close() plt.close()
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
2) ratio{X1}To{X2}: `total.{X1}.computed / total.{X2}.called` 2) ratio{X1}To{X2}: `total.{X1}.computed / total.{X2}.called`
- the efficiency of the incremental approach in comparison to the method X2, - the efficiency of the incremental approach in comparison to the method X2,
i.e. the ratio between actual work done in X1 compared to possible work done with method X2 i.e. the ratio between actual work done in X1 compared to possible work done with method X2
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
x = att_dat['dir'] x = att_dat['dir']
for n, (name, c, ls) in enumerate((('FlushedToNoncached', 'orange', '--'), for n, (name, c, ls) in enumerate((('FlushedToNoncached', 'orange', '--'),
('NormalToFlushed', 'purple', '-'), ('NormalToFlushed', 'purple', '-'),
('NormalToNoncached', 'r', '-.'))): ('NormalToNoncached', 'r', '-.'))):
y = att_dat['ratio' + name] y = att_dat['ratio' + name]
plt.plot(x, y, label = strategy2_to_titel(name), c = c, ls = ls) plt.plot(x, y, label = strategy2_to_titel(name), c = c, ls = ls)
#plt.bar(x*3*width + n*width, y, width, label = l, color = c) #plt.bar(x*3*width + n*width, y, width, label = l, color = c)
plt.legend(loc = 'best') plt.legend(loc = 'best')
plt.ylabel('%') plt.ylabel('%')
#plt.suptitle('Attribute Ratios', fontsize = 16) #plt.suptitle('Attribute Ratios', fontsize = 16)
plt.savefig(pdfpath('att_r')) plt.savefig(pdfpath('att_r'))
plt.savefig(pngpath('att_r')) plt.savefig(pngpath('att_r'))
#!pdfcrop doc/att_r.pdf doc/att_r_cropped.pdf > /dev/null #!pdfcrop doc/att_r.pdf doc/att_r_cropped.pdf > /dev/null
plt.close() plt.close()
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
3) speedup{X1}To{X2}: `(total.{X2}.computed / total.{X2}.called) - (total.{X1}.computed / total.{X2}.called)` 3) speedup{X1}To{X2}: `(total.{X2}.computed / total.{X2}.called) - (total.{X1}.computed / total.{X2}.called)`
- = `baseline({X2}) - ratio({X1}, {X2})` - = `baseline({X2}) - ratio({X1}, {X2})`
- the "speed-up" of the incremental approach (normal or flushed) in comparison to the method X2 - the "speed-up" of the incremental approach (normal or flushed) in comparison to the method X2
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
x = att_dat['dir'] x = att_dat['dir']
for n, (l, c) in enumerate((('NormalToNoncached', 'r'), for n, (l, c) in enumerate((('NormalToNoncached', 'r'),
('FlushedToNoncached', 'orange'), ('FlushedToNoncached', 'orange'),
('NormalToFlushed', 'yellow'))): ('NormalToFlushed', 'yellow'))):
y = att_dat['speedup' + l] y = att_dat['speedup' + l]
plt.plot(x, y, label = strategy2_to_titel(l), color = c) plt.plot(x, y, label = strategy2_to_titel(l), color = c)
#plt.bar(x*3*width + n*width, y, width, label = l, color = c) #plt.bar(x*3*width + n*width, y, width, label = l, color = c)
plt.legend(loc = 'best') plt.legend(loc = 'best')
plt.ylabel('%') plt.ylabel('%')
plt.suptitle('Attribute Speed-Ups', fontsize = 16) plt.suptitle('Attribute Speed-Ups', fontsize = 16)
plt.savefig(pdfpath('att_sp')) plt.savefig(pdfpath('att_sp'))
plt.savefig(pngpath('att_sp')) plt.savefig(pngpath('att_sp'))
#!pdfcrop doc/att_sp.pdf doc/att_sp_cropped.pdf > /dev/null #!pdfcrop doc/att_sp.pdf doc/att_sp_cropped.pdf > /dev/null
plt.close() plt.close()
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Boxplots for attribute measures ## Boxplots for attribute measures
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
att_totals = {change: read_att_result(name = 'profiling/splitted/att-percentages_{}.csv'.format(change), att_totals = {change: read_att_result(name = 'profiling/splitted/att-percentages_{}.csv'.format(change),
adjust_number = False) for change in kinds['changes'] if change != 'complex'} adjust_number = False) for change in kinds['changes'] if change != 'complex'}
``` ```
%% Output %% Output
Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_update.csv Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_update.csv
Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_sw.csv Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_sw.csv
Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_res.csv Loaded 31 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_res.csv
Loaded 2 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_mixed.csv Loaded 2 (0 zero-values) attribute metric run(s) from profiling/splitted/att-percentages_mixed.csv
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
PRINT_NONCACHED = True PRINT_NONCACHED = True
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_att(x, fcolumn, flabel, title, fname_part, rotation_xaxis = None): def draw_att(x, fcolumn, flabel, title, fname_part, rotation_xaxis = None):
""" Draw boxplots for attribute """ Draw boxplots for attribute
@param:fcolum: function with one parameter (name) returning column name @param:fcolum: function with one parameter (name) returning column name
@param:flabel: function with one parameter (name) returning label @param:flabel: function with one parameter (name) returning label
@param:title: title of plot @param:title: title of plot
@param:fname_part: unique filename part for storing plot @param:fname_part: unique filename part for storing plot
@param:rotation_xaxis: rotation of xaxis ticks (default: no rotation)""" @param:rotation_xaxis: rotation of xaxis ticks (default: no rotation)"""
try: try:
changes_to_draw = [c for c in kinds['changes'] if c != 'complex'] changes_to_draw = [c for c in kinds['changes'] if c != 'complex']
fig, axes = plt.subplots(ncols=len(changes_to_draw)) fig, axes = plt.subplots(ncols=len(changes_to_draw))
# if not rotation_xaxis: # if not rotation_xaxis:
# print dir(fig) # print dir(fig)
# fig.suptitle(title, fontsize = 16) # fig.suptitle(title, fontsize = 16)
l = ['normal', 'flushed'] l = ['normal', 'flushed']
if PRINT_NONCACHED: if PRINT_NONCACHED:
l.append('noncached') l.append('noncached')
for i, change in enumerate(changes_to_draw): for i, change in enumerate(changes_to_draw):
att_dat = att_totals[change] att_dat = att_totals[change]
axes[i].boxplot([att_dat[fcolumn(name)] for name in x], axes[i].boxplot([att_dat[fcolumn(name)] for name in x],
labels = [flabel(name) for name in x]) labels = [flabel(name) for name in x])
# axes[i].set_title(change_to_title(change), fontsize=10) # axes[i].set_title(change_to_title(change), fontsize=10)
if i > 0: if i > 0:
axes[i].set_yticklabels([]) axes[i].set_yticklabels([])
for ax in axes.flatten(): for ax in axes.flatten():
if PRINT_NONCACHED: if PRINT_NONCACHED:
ax.set_ylim([0,1.05]) ax.set_ylim([0,1.05])
if rotation_xaxis: if rotation_xaxis:
plt.setp(ax.xaxis.get_majorticklabels(), rotation=rotation_xaxis) plt.setp(ax.xaxis.get_majorticklabels(), rotation=rotation_xaxis)
plt.setp(ax.xaxis.get_majorticklabels(), fontsize = 15) plt.setp(ax.xaxis.get_majorticklabels(), fontsize = 15)
plt.setp(ax.yaxis.get_majorticklabels(), fontsize = 15) plt.setp(ax.yaxis.get_majorticklabels(), fontsize = 15)
# plt.axes().xaxis.set_major_locator(matplotlib.ticker.FixedLocator(range(0, 3, 2))) # plt.axes().xaxis.set_major_locator(matplotlib.ticker.FixedLocator(range(0, 3, 2)))
# plt.axes().xaxis.set_minor_locator(matplotlib.ticker.FixedLocator([1])) # plt.axes().xaxis.set_minor_locator(matplotlib.ticker.FixedLocator([1]))
# plt.axes().xaxis.set_minor_formatter(matplotlib.ticker.FormatStrFormatter("%s")) # plt.axes().xaxis.set_minor_formatter(matplotlib.ticker.FormatStrFormatter("%s"))
# plt.axes().tick_params(which='major', pad=20, axis='x') # plt.axes().tick_params(which='major', pad=20, axis='x')
plt.subplots_adjust(top=0.85) plt.subplots_adjust(top=0.85)
plt.savefig(pdfpath(fname_part)) plt.savefig(pdfpath(fname_part))
plt.savefig(pngpath(fname_part)) plt.savefig(pngpath(fname_part))
# !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null # !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null
except Exception as e: except Exception as e:
print 'Error while drawing att in {0}: {1}'.format(change, e) print 'Error while drawing att in {0}: {1}'.format(change, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def baseline(x): def baseline(x):
return '{}Baseline'.format('flushed' if x == 'flush' else x) return '{}Baseline'.format('flushed' if x == 'flush' else x)
print 'Drawing cache-miss rate' print 'Drawing cache-miss rate'
draw_att(kinds['strategies'], baseline, functools.partial(strategy_to_titel, length = lshort), draw_att(kinds['strategies'], baseline, functools.partial(strategy_to_titel, length = lshort),
'Attribute Cache-Miss Rate', 'att_box_miss') 'Attribute Cache-Miss Rate', 'att_box_miss')
x = ['NormalToFlushed', 'NormalToNoncached', 'FlushedToNoncached'] x = ['NormalToFlushed', 'NormalToNoncached', 'FlushedToNoncached']
print 'Drawing ratios' print 'Drawing ratios'
draw_att(x, lambda x: 'ratio{}'.format(x), strategy2_to_titel, 'Attribute Ratios', 'att_box_r', rotation_xaxis = 30) draw_att(x, lambda x: 'ratio{}'.format(x), strategy2_to_titel, 'Attribute Ratios', 'att_box_r', rotation_xaxis = 30)
print 'Drawing speed-ups' print 'Drawing speed-ups'
draw_att(x, lambda x: 'speedup{}'.format(x), strategy2_to_titel, 'Attribute Speedups', 'att_box_sp', rotation_xaxis = 30) draw_att(x, lambda x: 'speedup{}'.format(x), strategy2_to_titel, 'Attribute Speedups', 'att_box_sp', rotation_xaxis = 30)
``` ```
%% Output %% Output
Drawing cache-miss rate Drawing cache-miss rate
Drawing ratios Drawing ratios
Drawing speed-ups Drawing speed-ups
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Graph for attribute metrics over steps ## Graph for attribute metrics over steps
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_att_graph(kind, nr,log=False): def draw_att_graph(kind, nr,log=False):
f_pattern = 'profiling/splitted/att-totals-{0}-{1}-{2}.csv' f_pattern = 'profiling/splitted/att-totals-{0}-{1}-{2}.csv'
cs = ['b',(0,0,0.5),'g',(0,0.5,0),'r',(0.7,0,0)] cs = ['b',(0,0,0.5),'g',(0,0.5,0),'r',(0.7,0,0)]
def cv_name(x): def cv_name(x):
return int(x[-3:]) return int(x[-3:])
try: try:
dats = [(s,np.genfromtxt(f_pattern.format(kind,nr,s), delimiter=',', names=True, dats = [(s,np.genfromtxt(f_pattern.format(kind,nr,s), delimiter=',', names=True,
converters={'name': cv_name})) for s in kinds['strategies']] converters={'name': cv_name})) for s in kinds['strategies']]
for i,(label,dat) in enumerate(dats): for i,(label,dat) in enumerate(dats):
plt.plot(dat['comp'],color=cs[2*i], label = label) plt.plot(dat['comp'],color=cs[2*i], label = label)
plt.plot(dat['called'], ls=':',color=cs[2*i+1]) plt.plot(dat['called'], ls=':',color=cs[2*i+1])
if log: if log:
ax = plt.gca() ax = plt.gca()
ax.set_yscale('log') ax.set_yscale('log')
plt.legend(loc='best') plt.legend(loc='best')
fname_part = '{0}_{1}{2}'.format(kind,nr,'_log' if log else '') fname_part = '{0}_{1}{2}'.format(kind,nr,'_log' if log else '')
plt.savefig(pdfpath(fname_part)) plt.savefig(pdfpath(fname_part))
plt.savefig(pngpath(fname_part)) plt.savefig(pngpath(fname_part))
# !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null # !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null
except Exception as e: except Exception as e:
print 'Error while drawing att graph for {0}: {1}'.format(kind, e) print 'Error while drawing att graph for {0}: {1}'.format(kind, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
draw_att_graph('mixed', '001') draw_att_graph('mixed', '001')
draw_att_graph('mixed', '001', log = True) draw_att_graph('mixed', '001', log = True)
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Graph for memory measurement ## Graph for memory measurement
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
def draw_mem_graph(kind, nr): def draw_mem_graph(kind, nr):
global dat_mem global dat_mem
f = 'profiling/{0}-{1}/memory.csv'.format(kind, nr) f = 'profiling/{0}-{1}/memory.csv'.format(kind, nr)
print f print f
def cv_date(x): def cv_date(x):
# return datetime.strptime(x, '%Y-%m-%dT%H:%M:%S.%f') # return datetime.strptime(x, '%Y-%m-%dT%H:%M:%S.%f')
return (datetime.strptime(x, '%Y-%m-%dT%H:%M:%S.%f') - datetime(1970,1,1)).total_seconds() return (datetime.strptime(x, '%Y-%m-%dT%H:%M:%S.%f') - datetime(1970,1,1)).total_seconds()
def cv_mem(x): def cv_mem(x):
return int(x) / 1024 return int(x) / 1024
raw_data = [] raw_data = []
with open(f) as fd: with open(f) as fd:
next(fd) next(fd)
for l in fd: for l in fd:
toks = l.split(',') toks = l.split(',')
raw_data.append((cv_date(toks[0]), cv_mem(toks[1]))) raw_data.append((cv_date(toks[0]), cv_mem(toks[1])))
# dat = np.genfromtxt(f, delimiter=',', names=True, dtype = ('datetime64[us]', int), # dat = np.genfromtxt(f, delimiter=',', names=True, dtype = ('datetime64[us]', int),
# converters={'timestamp': cv_date, 'vmsize':cv_mem}) # converters={'timestamp': cv_date, 'vmsize':cv_mem})
## print raw_data ## print raw_data
dat_mem = np.array(raw_data, dtype = [('timestamp', int), ('vmsize', int)]) dat_mem = np.array(raw_data, dtype = [('timestamp', int), ('vmsize', int)])
# dat_mem.dtype.names = 'timestamp', 'vmsize' # dat_mem.dtype.names = 'timestamp', 'vmsize'
try: try:
plt.plot(dat_mem['vmsize']) plt.plot(dat_mem['vmsize'])
plt.ylabel('VmSize (MB)') plt.ylabel('VmSize (MB)')
plt.xlabel('Time (Seconds)') plt.xlabel('Time (Seconds)')
# plt.legend(loc='best') # plt.legend(loc='best')
fname_part = 'memory_{0}-{1}'.format(kind,nr) fname_part = 'memory_{0}-{1}'.format(kind,nr)
plt.savefig(pdfpath(fname_part)) plt.savefig(pdfpath(fname_part))
plt.savefig(pngpath(fname_part)) plt.savefig(pngpath(fname_part))
# !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null # !pdfcrop {'doc/{}.pdf'.format(fname_part)} {'doc/{}_cropped.pdf'.format(fname_part)} > /dev/null
except Exception as e: except Exception as e:
print 'Error while drawing memory graph for {0}: {1}'.format(kind, e) print 'Error while drawing memory graph for {0}: {1}'.format(kind, e)
traceback.print_exc(file=sys.stdout) traceback.print_exc(file=sys.stdout)
finally: finally:
plt.close() plt.close()
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
draw_mem_graph('mixed', '001') draw_mem_graph('mixed', '001')
draw_mem_graph('mixed', '002') draw_mem_graph('mixed', '002')
``` ```
%% Output %% Output
profiling/mixed-001/memory.csv profiling/mixed-001/memory.csv
profiling/mixed-002/memory.csv profiling/mixed-002/memory.csv
......
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