rA = Resource(s, 'A', [A, B, C])
rB = Resource(s, 'B', [D, E, F])
rmap = dict([(start(t), t.resourceName())
for t in s.tasks] + [(end(t), t.resourceName())
for t in s.tasks])
s.graph.latex(outfile=open('tex/ex/d_precedence_graph.tex', 'w'),
width=9,
sep=3,
resources=rmap)
s.graph.latex(outfile=open('tex/ex/d_precedence_graph_lb.tex', 'w'),
width=9,
sep=3,
lb=[start(D)],
resources=rmap)
s.graph.latex(outfile=open('tex/ex/d_precedence_graph_ub.tex', 'w'),
width=9,
sep=3,
ub=[end(A)],
resources=rmap)
s.latex(outfile=open('tex/ex/d_scheduling_instance.tex', 'w'),
precedences=True,
windows=False)
ex.writeFile('graph_demo',
[['d_scheduling_instance'], ['d_precedence_graph']])
ex.writeFile('graph_bound_demo', [[
'd_precedence_graph', 'd_precedence_graph_lb', 'd_precedence_graph_ub'
]])
#
animated=True,
mandatory=True,
profile=[res],
precedences=False,
profp=-.000001,
rows=[[A, F], [E], [B], [C], [D]])
tt = Timetabling(res)
s.save()
while True:
if not tt.propagate():
break
s.latex(outfile,
animated=True,
precedences=False,
pruning=True,
rows=[[A, F], [E], [B], [C], [D]])
s.latex(outfile,
animated=True,
mandatory=True,
profile=[res],
precedences=False,
profp=-.000001,
rows=[[A, F], [E], [B], [C], [D]])
s.save()
ex.writeFile('timetabling_demo', 'd_timetabling', scale=.3)
resA = Resource(s, 'A', [A, B, C])
resB = Resource(s, 'B', [D, E, F])
resC = Resource(s, 'C', [G, H, I])
span = 25
s.setMakespanUB(span)
# rows = s.rowsFromPaths()
rows = [[A], [B], [C], [D], [E], [F], [G], [H], [I]]
random.seed(12345)
bnb = BranchAndBound(s)
printsched = lambda x: s.latex(outfile=outfile,
ub=True,
lb=True,
animated=True,
windows=False,
rows=rows,
width=span,
horizon=span,
decisions=[(d.tasks[int(d.value())], d.
tasks[1 - int(d.value())])
for d in x.decisions])
bnb.search(limit=None,
executeOnNode=printsched,
executeOnSolution=printsched)
ex.writeFile('branchandbound_demo', 'd_branchandbound_trace')
s.latex(outfile, animated=True, windows=False)
A << B
E << C
E << A
C << F
s.latex(outfile, animated=True, windows=False)
s.latex(outfile,
animated=True,
windows=True,
precedences=False,
rows=[[E], [A], [C], [B], [F], [D]],
shifts=([''] * 5 + ['Left']))
b1 = Resource(s, 'A', capacity=6, init=[B, F])
b2 = Resource(s, 'B', capacity=6, init=[A, C, D, E])
s.latex(outfile, animated=True, windows=False)
s.setDemand(A, 3)
s.setDemand(B, 4)
s.setDemand(C, 3)
s.setDemand(D, 2)
s.setDemand(E, 1)
s.setDemand(F, 1)
s.latex(outfile, animated=True, windows=False)
ex.writeFile('basic_demo', 'd_basic', scale=.5)
from PySched import *
import PySched.examples as ex
if __name__ == '__main__':
outfile = open('tex/ex/d_edgefinding.tex', 'w')
s = Schedule()
A = Task(s,duration=4,release=0,duedate=25,label='A')
B = Task(s,duration=3,release=1,duedate=9,label='B')
C = Task(s,duration=3,release=1,duedate=9,label='C')
D = Task(s,duration=5,release=7,duedate=14,label='D')
res = Resource(s, 'A', [A,B,C,D])
ef = EdgeFinding(res)
s.latex(outfile, animated=True)
while True:
s.save()
if not ef.propagate():
break
s.latex(outfile, animated=True, precedences=True, windows=True, rows=[[A],[B],[C],[D]], pruning=True, decisions=False)
ex.writeFile('edgefinding_demo', 'd_edgefinding', scale=.45)
Resource(s, name='C', init=example)
treefile = open('tex/ex/d_theta_tree.tex', 'w')
schedfile = open('tex/ex/d_theta.tex', 'w')
s.latex(schedfile, animated=True, rows=[[t] for t in example])
tt = theta.ThetaTree(example)
s.latex(schedfile, animated=True, rows=[[t] for t in tt.tasks])
s.latex(schedfile,
animated=True,
rows=[[t] for t in tt.tasks],
tasks=[],
stop='-')
for i, t in enumerate(sorted_example):
t.rank = i
for i, t in enumerate(sorted_example):
schedfile.write('\\uncover<%i->{' % (i + 3))
schedfile.write(t.strInterval(row=t.rank, mode='Left'))
schedfile.write('}\n')
tt.exec2latex(example, output=treefile)
ex.writeFile('thetatree_demo', ['d_theta', 'd_theta_tree'],
headers=['colorschedfigure', 'downthreelvltree'],
scale=.45)