def _get_table(self, attribute, domain=None):
#get original table
table = AbsoluteReport._get_table(self, attribute, domain)
#if table is coverage, and in problem resolution, take also initial-h-value and add a column of the ratio
if attribute == 'coverage' :
h_attr = Attribute('initial_h_value', min_wins=False, absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
ratio_col = {}
h_col = {}
hstar_col = {}
# Filter those rows which have no significant changes
for row in table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
ratio = ratio_table.get(row)
print ratio
ratio_col[row] = ratio['WORK-lmcut']
h_col[row] = h[0]
hstar_col[row] = hstar[0]
table.set_column_order(table.col_names + ['h*'])
table.add_col('h*/h(s)', ratio_col)
table.add_col('h(s)', h_col)
table.add_col('h*', hstar_col)
table.min_wins = None
table.colored = False
return table
def _get_statistics_table(self, attribute, domain=None):
#get original table
table = AbsoluteReport._get_table(self, attribute, domain)
#if attribute is statistics, take also initial-h-value and add a column of the ratio
if attribute == 'statistics' :
h_attr = Attribute('initial_h_value', min_wins=False, absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
ff_h_value_attr = Attribute('initial_ff_h_value', min_wins=False, absolute=True)
ff_h_value_table = AbsoluteReport._get_table(self, ff_h_value_attr, domain)
ratio_col = {}
h_col = {}
hstar_col = {}
ff_h_value_col = {}
h_ff_to_h = []
for row in table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
ff_h_val = ff_h_value_table.get_row(row)
ratio = ratio_table.get(row)
ratio_col[row] = ratio[self.nick]
h_col[row] = h[0]
ff_h_value_col[row] = ff_h_val[0]
hstar_col[row] = hstar[0]
# build h-ff/h:
if(ff_h_val[0] != None and hstar[0] != None):
if hstar[0] != 0:
h_ff_to_h.append(ff_h_val[0]/hstar[0])
table.set_column_order(table.col_names + ['h*'])
table.add_col('h*/h(s)', ratio_col)
table.add_col('h(s)', h_col)
table.add_col('ff_h(s)', ff_h_value_col)
table.add_col('h*', hstar_col)
table.min_wins = None
table.colored = False
# domain_dir = self.outFile + '/' + domain
# tools.makedirs(domain_dir)
# domain_file = domain_dir + '/' + 'PAC_Statistics.csv'
# with open(domain_file, 'w') as csvfile:
# writer = csv.writer(csvfile)
# [writer.writerow(r) for r in table]
self.save_stat_table_to_file(domain,table)
self.create_commulative_h_ff_to_h_table(domain, h_ff_to_h)
return table
def _get_statistics_table(self, attribute, domain=None):
#get original table
table = AbsoluteReport._get_table(self, attribute, domain)
#if attribute is statistics, take also initial-h-value and add a column of the ratio
if attribute == 'statistics':
h_attr = Attribute('initial_h_value',
min_wins=False,
absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
ff_h_value_attr = Attribute('initial_ff_h_value',
min_wins=False,
absolute=True)
ff_h_value_table = AbsoluteReport._get_table(
self, ff_h_value_attr, domain)
ratio_col = {}
h_col = {}
hstar_col = {}
ff_h_value_col = {}
h_ff_to_h = []
for row in table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
ratio = ratio_table.get(row)
ratio_col[row] = ratio[self.nick]
h_col[row] = h[0]
hstar_col[row] = hstar[0]
ff_h_val = ff_h_value_table.get_row(row)
ff_h_value_col[row] = ff_h_val[0]
# build h-ff/h:
if (ff_h_val[0] != None and hstar[0] != None):
if hstar[0] != 0:
h_ff_to_h.append(hstar[0] / ff_h_val[0])
table.set_column_order(table.col_names + ['h*'])
table.add_col('h*/h(s)', ratio_col)
table.add_col('h(s)', h_col)
table.add_col('h*', hstar_col)
table.add_col('ff_h(s)', ff_h_value_col)
table.min_wins = None
table.colored = False
self.save_stat_table_to_file(domain, table)
self.create_commulative_h_ff_to_h_table(domain, h_ff_to_h)
return table
def get_points(self, domain):
"""
By default plot the configs on the x-axis and the attribute values on
the y-axis. All values are in the same category.
"""
h_attr = Attribute('initial_h_value', min_wins=False, absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
coverage_attr = Attribute('coverage', min_wins=False, absolute=True)
coverage_table = AbsoluteReport._get_table(self, coverage_attr, domain)
hstar_to_h = {}
total_solved = 0
counter = 0
for row in h_table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
hstar_val = hstar[0]
h_val = h[0]
coverage = coverage_table.get_row(row)
coverage_val = coverage[0]
if hstar_val is not None and h_val is not None and h_val > 0:
hstar_to_h[counter] = hstar_val / h_val
else:
hstar_to_h[counter] = 0
counter = counter + 1
if coverage_val > 0:
total_solved = total_solved + 1
ratios = {
0.75, 0.8, 0.85, 0.9, 0.95, 1, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3,
1.35, 1.4, 1.45, 1.5, 1.55, 1.6, 1.65, 1.7, 1.75, 1.8, 1.85, 1.9,
1.95, 2, 2.05, 2.1, 2.15, 2.2, 2.25, 2.3, 2.35, 2.4, 2.45, 2.5,
2.55, 2.6, 2.65, 2.7, 2.75, 2.8, 2.85, 2.9, 2.95, 3.0, 3.05, 3.1,
3.15, 3.2, 3.25, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55, 3.6, 3.65, 3.7
}
percentages = Set()
for ratio in ratios:
_sum = 0
for key in hstar_to_h:
if hstar_to_h[key] <= ratio and hstar_to_h[key] > 0:
_sum = _sum + 1
if total_solved == 0:
_sum_percent = 0
else:
_sum_percent = _sum * 100 / total_solved
percentages.add((ratio, _sum_percent))
return list(percentages)
def get_points(self, domain):
"""
By default plot the configs on the x-axis and the attribute values on
the y-axis. All values are in the same category.
"""
h_attr = Attribute('initial_h_value', min_wins=False, absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
coverage_attr = Attribute('coverage', min_wins=False, absolute=True)
coverage_table = AbsoluteReport._get_table(self, coverage_attr, domain)
hstar_to_h = {}
total_solved = 0
counter = 0
for row in h_table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
hstar_val = hstar[0]
h_val = h[0]
coverage = coverage_table.get_row(row)
coverage_val = coverage[0]
if hstar_val is not None and h_val is not None and h_val > 0:
hstar_to_h[counter] = hstar_val / h_val
else:
hstar_to_h[counter] = 0
counter = counter + 1
if coverage_val > 0:
total_solved = total_solved + 1
ratios = {0.75,0.8,0.85,0.9,0.95,1,1.05,1.1,1.15,1.2,1.25,1.3,1.35,1.4,1.45,1.5,1.55,1.6,1.65,1.7,1.75,1.8,1.85,1.9,1.95,2,2.05,2.1,2.15,2.2,2.25,2.3,2.35,2.4,2.45,2.5,2.55,2.6,2.65,2.7,2.75,2.8,2.85,2.9,2.95,3.0,3.05,3.1,3.15,3.2,3.25,3.3,3.35,3.4,3.45,3.5,3.55,3.6,3.65,3.7}
percentages = Set()
for ratio in ratios:
_sum = 0
for key in hstar_to_h:
if hstar_to_h[key] <= ratio and hstar_to_h[key] > 0:
_sum = _sum + 1
if total_solved == 0:
_sum_percent = 0
else:
_sum_percent = _sum*100 / total_solved
percentages.add((ratio,_sum_percent))
return list(percentages)
def _get_table(self, attribute, domain=None):
#get original table
table = AbsoluteReport._get_table(self, attribute, domain)
#if table is coverage, and in problem resolution, take also initial-h-value and add a column of the ratio
if attribute == 'coverage':
h_attr = Attribute('initial_h_value',
min_wins=False,
absolute=True)
h_table = AbsoluteReport._get_table(self, h_attr, domain)
hstar_attr = Attribute('cost', min_wins=False, absolute=True)
hstar_table = AbsoluteReport._get_table(self, hstar_attr, domain)
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
ratio_col = {}
h_col = {}
hstar_col = {}
# Filter those rows which have no significant changes
for row in table.row_names:
hstar = hstar_table.get_row(row)
h = h_table.get_row(row)
ratio = ratio_table.get(row)
print ratio
ratio_col[row] = ratio['WORK-lmcut']
h_col[row] = h[0]
hstar_col[row] = hstar[0]
table.set_column_order(table.col_names + ['h*'])
table.add_col('h*/h(s)', ratio_col)
table.add_col('h(s)', h_col)
table.add_col('h*', hstar_col)
table.min_wins = None
table.colored = False
return table
def _get_table(self, attribute, domain=None):
table = AbsoluteReport._get_table(self, attribute, domain)
quotient_col = {}
percent_col = {}
# Filter those rows which have no significant changes
for row in table.row_names:
val1, val2 = table.get_row(row)
if not val1 and not val2:
# Delete row if both values are missing (None) or 0.
del table[row]
continue
elif val1 is None or val2 is None:
# Don't add quotient if exactly one value is None.
quotient_col[row] = NOT_AVAILABLE
continue
abs_change = abs(val1 - val2)
if val1 == 0 or val2 == 0:
# If one value is 0, only add row if the change is big enough.
if abs_change >= self.abs_change:
quotient_col[row] = NOT_AVAILABLE
else:
del table[row]
continue
quotient = val2 / val1
percent_change = abs(quotient - 1.0)
if (percent_change >= self.rel_change
and abs_change >= self.abs_change):
quotient_col[row] = quotient
percent_col[row] = percent_change
else:
del table[row]
# Add table also if there were missing cells
if len(quotient_col) == 0:
return 'No changes.'
table.set_column_order(table.col_names + ['Factor'])
table.add_col('Factor', quotient_col)
table.add_col('%-Change', percent_col)
table.min_wins = None
table.colored = False
return table
def _get_table(self, attribute, domain=None):
table = AbsoluteReport._get_table(self, attribute, domain)
quotient_col = {}
percent_col = {}
# Filter those rows which have no significant changes
for row in table.row_names:
val1, val2 = table.get_row(row)
if not val1 and not val2:
# Delete row if both values are missing (None) or 0.
del table[row]
continue
elif val1 is None or val2 is None:
# Don't add quotient if exactly one value is None.
quotient_col[row] = NOT_AVAILABLE
continue
abs_change = abs(val1 - val2)
if val1 == 0 or val2 == 0:
# If one value is 0, only add row if the change is big enough.
if abs_change >= self.abs_change:
quotient_col[row] = NOT_AVAILABLE
else:
del table[row]
continue
quotient = val2 / val1
percent_change = abs(quotient - 1.0)
if percent_change >= self.rel_change and abs_change >= self.abs_change:
quotient_col[row] = quotient
percent_col[row] = percent_change
else:
del table[row]
# Add table also if there were missing cells
if len(quotient_col) == 0:
return "No changes."
table.set_column_order(table.col_names + ["Factor"])
table.add_col("Factor", quotient_col)
table.add_col("%-Change", percent_col)
table.min_wins = None
table.colored = False
return table
def create_commulative_h_star_table(self, domain):
#get relevant value from original table
cost_attr = Attribute('cost', min_wins=False, absolute=True)
cost_table = AbsoluteReport._get_table(self, cost_attr, domain)
#define list of costs:
cost_list = []
#calculate number of solved problems
total_solved = 0
for row in cost_table.row_names:
curr_val = cost_table.get(row)
val = curr_val[self.nick]
if val > 0:
total_solved = total_solved + 1
cost_list.append(val)
cost_set = list(set(cost_list)) # remove duplicate element
cost_dict = {}
for value in sorted(cost_set):
smaller_than_value_counter = 0;
for compared_value in cost_list:
if compared_value <= value:
smaller_than_value_counter += 1
cost_dict[value] = smaller_than_value_counter*100 / total_solved
#write results into .cvs file:
domain_dir = self.outFile + '/' + domain
tools.makedirs(domain_dir)
domain_file = domain_dir + '/' + 'PAC_Commulative_hstar.csv'
file = open(domain_file, "w")
sorted_cost_dict_keys = sorted(cost_dict.keys())
for hstar in sorted_cost_dict_keys:
toWrite = str(hstar) + ',' + str(cost_dict[hstar]) + '\n'
file.write(toWrite)
file.close()
def create_commulative_h_star_table(self, domain):
#get relevant value from original table
cost_attr = Attribute('cost', min_wins=False, absolute=True)
cost_table = AbsoluteReport._get_table(self, cost_attr, domain)
#define list of costs:
cost_list = []
#calculate number of solved problems
total_solved = 0
for row in cost_table.row_names:
curr_val = cost_table.get(row)
val = curr_val[self.nick]
if val > 0:
total_solved = total_solved + 1
cost_list.append(val)
cost_set = list(set(cost_list)) # remove duplicate element
cost_dict = {}
for value in sorted(cost_set):
smaller_than_value_counter = 0
for compared_value in cost_list:
if compared_value <= value:
smaller_than_value_counter += 1
cost_dict[value] = smaller_than_value_counter * 100 / total_solved
#write results into .cvs file:
domain_dir = self.outFile + '/' + domain
tools.makedirs(domain_dir)
domain_file = domain_dir + '/' + 'PAC_Commulative_hstar.csv'
file = open(domain_file, "w")
sorted_cost_dict_keys = sorted(cost_dict.keys())
for hstar in sorted_cost_dict_keys:
toWrite = str(hstar) + ',' + str(cost_dict[hstar]) + '\n'
file.write(toWrite)
file.close()
def _get_commulative_table(self, domain):
#init new table
title = 'Commulative'
columns = {'Percentage', 'h*/h(s)'}
min_wins = False
colored = True
table = reports.Table(title=title, min_wins=min_wins, colored=colored)
table.set_column_order(columns)
link = '#%s' % title
formatter = reports.CellFormatter(link=link)
table.cell_formatters[table.header_row][
table.header_column] = formatter
domain_dir = self.outFile + '/' + domain
tools.makedirs(domain_dir)
domain_file = domain_dir + '/' + 'PAC_Commulative_ratio.csv'
file = open(domain_file, "w")
#get relevant value from original table
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
#define arrays to work
ratios = [
0.75, 0.8, 0.85, 0.9, 0.95, 1, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3,
1.35, 1.4, 1.45, 1.5, 1.55, 1.6, 1.65, 1.7, 1.75, 1.8, 1.85, 1.9,
1.95, 2, 2.05, 2.1, 2.15, 2.2, 2.25, 2.3, 2.35, 2.4, 2.45, 2.5,
2.55, 2.6, 2.65, 2.7, 2.75, 2.8, 2.85, 2.9, 2.95, 3.0, 3.05, 3.1,
3.15, 3.2, 3.25, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55, 3.6, 3.65, 3.7,
3.75, 3.80, 3.85, 3.9, 3.95, 4.0, 4.05, 4.1, 4.15, 4.2, 2.25, 4.3,
4.35, 4.4, 4.45, 4.5
]
names = [
'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm',
'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z',
'za', 'zb', 'zc', 'zd', 'ze', 'zf', 'zg', 'zh', 'zi', 'zj', 'zk',
'zl', 'zm', 'zn', 'zo', 'aa', 'ab', 'ac', 'ad', 'ae', 'af', 'ag',
'ah', 'ai', 'aj', 'ak', 'al', 'am', 'an', 'ao', 'ap', 'aq', 'ar',
'as', 'at', 'au', 'av', 'aw', 'ax', 'ay', 'az', 'ba', 'bb', 'bc',
'bd', 'be', 'bf', 'bg', 'bh', 'bi'
]
counter = 0
#calculate number of solved problems
total_solved = 0
for row in ratio_table.row_names:
curr_val = ratio_table.get(row)
val = curr_val[self.nick]
if val > 0:
total_solved = total_solved + 1
#for each ratio (1,1.05...), find the number of problems with this ratio, calc percentage and add row
for ratio in ratios:
_sum = 0
for row in ratio_table.row_names:
curr_val = ratio_table.get(row)
val = curr_val[self.nick]
if val <= ratio and val > 0:
_sum = _sum + 1
if total_solved == 0:
_sum_percent = 0
else:
_sum_percent = _sum * 100 / total_solved
#add new row
row_to_add = {}
row_to_add['Percentage'] = _sum_percent
row_to_add['h*/h(s)'] = ratio
table.add_row(names[counter], row_to_add)
counter = counter + 1
#TODO - save only one ratio per percentage
toWrite = str(ratio) + ',' + str(_sum_percent) + '\n'
file.write(toWrite)
file.close()
self.create_commulative_h_star_table(domain)
return table
def _get_commulative_table(self, domain):
#init new table
title = 'Commulative'
columns = {'Percentage','h*/h(s)'}
min_wins = False
colored = True
table = reports.Table(title=title, min_wins=min_wins, colored=colored)
table.set_column_order(columns)
link = '#%s' % title
formatter = reports.CellFormatter(link=link)
table.cell_formatters[table.header_row][table.header_column] = formatter
domain_dir = self.outFile + '/' + domain
tools.makedirs(domain_dir)
domain_file = domain_dir + '/' + 'PAC_Commulative_ratio.csv'
file = open(domain_file, "w")
#get relevant value from original table
ratio_attr = Attribute('hstar_to_h', min_wins=False, absolute=True)
ratio_table = AbsoluteReport._get_table(self, ratio_attr, domain)
#define arrays to work
ratios = [0.75,0.8,0.85,0.9,0.95,1,1.05,1.1,1.15,1.2,1.25,1.3,1.35,1.4,1.45,1.5,1.55,1.6,1.65,1.7,1.75,1.8,1.85,1.9,1.95,2,2.05,2.1,2.15,2.2,2.25,2.3,2.35,2.4,2.45,2.5,2.55,2.6,2.65,2.7,2.75,2.8,2.85,2.9,2.95,3.0,3.05,3.1,3.15,3.2,3.25,3.3,3.35,3.4,3.45,3.5,3.55,3.6,3.65,3.7,3.75,3.80,3.85,3.9,3.95,4.0,4.05,4.1,4.15,4.2,2.25,4.3,4.35,4.4,4.45,4.5]
names = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z','za','zb','zc','zd','ze','zf','zg','zh','zi','zj','zk','zl','zm','zn','zo','aa','ab','ac','ad','ae','af','ag','ah','ai','aj','ak','al','am','an','ao','ap','aq','ar','as','at', 'au','av','aw','ax','ay','az','ba','bb','bc','bd','be','bf','bg','bh','bi']
counter = 0
#calculate number of solved problems
total_solved = 0
for row in ratio_table.row_names:
curr_val = ratio_table.get(row)
val = curr_val[self.nick]
if val > 0:
total_solved = total_solved + 1
#for each ratio (1,1.05...), find the number of problems with this ratio, calc percentage and add row
for ratio in ratios:
_sum = 0
for row in ratio_table.row_names:
curr_val = ratio_table.get(row)
val = curr_val[self.nick]
if val <= ratio and val > 0:
_sum = _sum + 1
if total_solved == 0:
_sum_percent = 0
else:
_sum_percent = _sum*100 / total_solved
#add new row
row_to_add = {}
row_to_add['Percentage'] = _sum_percent
row_to_add['h*/h(s)'] = ratio
table.add_row(names[counter],row_to_add)
counter = counter + 1
#TODO - save only one ratio per percentage
toWrite = str(ratio)+','+str(_sum_percent)+'\n'
file.write(toWrite)
file.close()
self.create_commulative_h_star_table(domain)
return table
