def test_mesure_soleves2(rooms,width_domain):
max_depth = 40
def BeamSolve(beam_width):
algorithm = beam_search.BeamSearch(beam_width, max_depth)
heuristic = heuristics.PowerHeuristic()
agent = measure_agent.MeasureAgent(algorithm, heuristic)
def solution_len(*args, **kwrds):
solution = agent.solve(*args, **kwrds)
if solution is None: solution = []
return [len(solution)]
return solution_len
x = width_domain
solve_impl_list = [ BeamSolve(i) for i in x ]
header = ['No','RoomId'] + ['Beam%s' % i for i in x]
#rooms = dict(all_static_rooms.items()[:7])
#rooms = all_static_rooms
print
print
results = mes2.compare_measured_soleves(solve_impl_list, rooms, 1000)
#named_results = [[name] + list(r) for r , name in zip(results,solve_impl_names)]
time_table = [range(len(results[0][0]))] + results[1]
t = xplot.table_to_csv2(time_table,header=header)
psave(t, r'C:\Users\inesmeya\Desktop\source\din\t.pck')
#y = [ for coll in time_table[2:] ]
y = [ reduce(lambda x,y: x + int(y != 0),coll,0) for coll in time_table[2:]]
print
print "GGGG y=", y
y = [ 100.0 * float(i) / float(len(rooms)) for i in y ]
print
print "GGGG y=", y
dir = r'C:\Users\inesmeya\Desktop\source\din'
html_name = dir + '\\' + 'index.html'
img_name = dir + '\\' + 'img.png'
xplot.html.add_header("Picture Demo")
#pylab.axvspan(0, 400, 0, 100)
xplot.plot_result((('width', x),('solved', y)), title='Picture title', label='label', filename=img_name)
xplot.html.add_img(img_name)
xplot.html.add_header("Table demo")
xplot.html.add_paragraph("Tons of text about this particular table")
xplot.html.add_table(time_table, 'The Title of table', header=header)
xplot.html.save(html_name)
#print d
print t
def test_mesure_soleves(self):
max_depth = 40
def BeamSolve(beam_width):
algorithm = beam_search.BeamSearch(beam_width, max_depth)
heuristic = heuristics.PowerHeuristic()
agent = measure_agent.MeasureAgent(algorithm, heuristic)
def solution_len(*args, **kwrds):
solution = agent.solve(*args, **kwrds)
if solution is None: solution = []
return [len(solution)]
return solution_len
beam3 = BeamSolve(2)
beam7 = BeamSolve(7)
beam11 = BeamSolve(50)
solve_impl_list = [beam3, beam7, beam11]
header = ['No', 'RoomId', 'Beam3', 'Beam7', 'Beam11']
rooms = dict(all_static_rooms.items()[:7])
print
print
results = mes2.compare_measured_soleves(solve_impl_list, rooms, 1000)
#named_results = [[name] + list(r) for r , name in zip(results,solve_impl_names)]
time_table = [range(len(results[0][0]))] + results[1]
t = xplot.table_to_csv2(time_table, header=header)
y = [
reduce(lambda x, y: x + int(y != 0), coll)
for coll in time_table[2:]
]
x = [2, 7, 50]
dir = r'C:\Users\inesmeya\Desktop\source\din'
html_name = dir + '\\' + 'index.html'
img_name = dir + '\\' + 'img.png'
xplot.html.add_header("Pincture Demo")
xplot.plot_result((('width', x), ('solved', y)),
title='Picture title',
label='lable',
filename=img_name)
xplot.html.add_img(img_name)
xplot.html.add_header("Table demo")
xplot.html.add_paragraph("Tons of text about this particular table")
xplot.html.add_table(time_table, 'The Title of table', header=header)
xplot.html.save(html_name)
print xplot.table_to_csv2()
#print d
print t
def test_mesure_soleves(self):
max_depth = 40
def BeamSolve(beam_width):
algorithm = beam_search.BeamSearch(beam_width, max_depth)
heuristic = heuristics.PowerHeuristic()
agent = measure_agent.MeasureAgent(algorithm, heuristic)
def solution_len(*args, **kwrds):
solution = agent.solve(*args, **kwrds)
if solution is None: solution = []
return [len(solution)]
return solution_len
beam3 = BeamSolve(2)
beam7 = BeamSolve(7)
beam11 = BeamSolve(50)
solve_impl_list = [beam3,beam7,beam11]
header = ['No','RoomId','Beam3','Beam7','Beam11']
rooms = dict(all_static_rooms.items()[:7])
print
print
results = mes2.compare_measured_soleves(solve_impl_list, rooms, 1000)
#named_results = [[name] + list(r) for r , name in zip(results,solve_impl_names)]
time_table = [range(len(results[0][0]))] + results[1]
t = xplot.table_to_csv2(time_table,header=header)
y = [reduce(lambda x,y: x + int(y != 0),coll) for coll in time_table[2:]]
x = [2,7,50]
dir = r'C:\Users\inesmeya\Desktop\source\din'
html_name = dir + '\\' + 'index.html'
img_name = dir + '\\' + 'img.png'
xplot.html.add_header("Pincture Demo")
xplot.plot_result((('width', x),('solved', y)), title='Picture title', label='lable', filename=img_name)
xplot.html.add_img(img_name)
xplot.html.add_header("Table demo")
xplot.html.add_paragraph("Tons of text about this particular table")
xplot.html.add_table(time_table, 'The Title of table', header=header)
xplot.html.save(html_name)
print xplot.table_to_csv2()
#print d
print t
def test_mesure_soleves2(rooms, width_domain):
max_depth = 40
def BeamSolve(beam_width):
algorithm = beam_search.BeamSearch(beam_width, max_depth)
heuristic = heuristics.PowerHeuristic()
agent = measure_agent.MeasureAgent(algorithm, heuristic)
def solution_len(*args, **kwrds):
solution = agent.solve(*args, **kwrds)
if solution is None: solution = []
return [len(solution)]
return solution_len
x = width_domain
solve_impl_list = [BeamSolve(i) for i in x]
header = ['No', 'RoomId'] + ['Beam%s' % i for i in x]
#rooms = dict(all_static_rooms.items()[:7])
#rooms = all_static_rooms
print
print
results = mes2.compare_measured_soleves(solve_impl_list, rooms, 1000)
#named_results = [[name] + list(r) for r , name in zip(results,solve_impl_names)]
time_table = [range(len(results[0][0]))] + results[1]
t = xplot.table_to_csv2(time_table, header=header)
psave(t, r'C:\Users\inesmeya\Desktop\source\din\t.pck')
#y = [ for coll in time_table[2:] ]
y = [
reduce(lambda x, y: x + int(y != 0), coll, 0)
for coll in time_table[2:]
]
print
print "GGGG y=", y
y = [100.0 * float(i) / float(len(rooms)) for i in y]
print
print "GGGG y=", y
dir = r'C:\Users\inesmeya\Desktop\source\din'
html_name = dir + '\\' + 'index.html'
img_name = dir + '\\' + 'img.png'
xplot.html.add_header("Picture Demo")
#pylab.axvspan(0, 400, 0, 100)
xplot.plot_result((('width', x), ('solved', y)),
title='Picture title',
label='label',
filename=img_name)
xplot.html.add_img(img_name)
xplot.html.add_header("Table demo")
xplot.html.add_paragraph("Tons of text about this particular table")
xplot.html.add_table(time_table, 'The Title of table', header=header)
xplot.html.save(html_name)
#print d
print t
