def gofast(newgen, delay):
''' Fast goto '''
#Save current settings
oldbase = g.getbase()
# oldhash = g.setoption("hashing", True)
g.show('gofast running, hit escape to abort')
oldsecs = time()
#Advance by binary powers, to maximize advantage of hashing
g.setbase(2)
for i, b in enumerate(intbits(newgen)):
if b:
g.setstep(i)
g.step()
g.dokey(g.getkey())
newsecs = time()
if newsecs - oldsecs >= delay: # do an update every sec
oldsecs = newsecs
g.update()
if g.empty():
break
g.show('')
#Restore settings
# g.setoption("hashing", oldhash)
g.setbase(oldbase)
def envelope ():
# draw stacked layers using same location and scale
g.setoption("stacklayers", 1)
g.show("Hit escape key to stop script...")
while True:
g.run(1)
if g.empty():
g.show("Pattern died out.")
break
# copy current pattern to envelope layer;
# we temporarily disable event checking so thumb scrolling
# and other mouse events won't cause confusing changes
currpatt = g.getcells(g.getrect())
g.check(0)
g.setlayer(envindex)
g.putcells(currpatt)
g.setlayer(currindex)
g.check(1)
step = 1
exp = g.getstep()
if exp > 0:
step = g.getbase()**exp
if int(g.getgen()) % step == 0:
# display all 3 layers (envelope, start, current)
g.update()
def envelope():
# draw stacked layers using same location and scale
g.setoption("stacklayers", 1)
g.show("Hit escape key to stop script...")
while True:
g.run(1)
if g.empty():
g.show("Pattern died out.")
break
# copy current pattern to envelope layer;
# we temporarily disable event checking so thumb scrolling
# and other mouse events won't cause confusing changes
currpatt = g.getcells(g.getrect())
g.check(0)
g.setlayer(envindex)
g.putcells(currpatt)
g.setlayer(currindex)
g.check(1)
step = 1
exp = g.getstep()
if exp > 0:
step = g.getbase()**exp
if int(g.getgen()) % step == 0:
# display all 3 layers (envelope, start, current)
g.update()
def goto(newgen, delay):
g.show("goto running, hit escape to abort...")
oldsecs = time()
# before stepping we advance by 1 generation, for two reasons:
# 1. if we're at the starting gen then the *current* step size
# will be saved (and restored upon Reset/Undo) rather than a
# possibly very large step size
# 2. it increases the chances the user will see updates and so
# get some idea of how long the script will take to finish
# (otherwise if the base is 10 and a gen like 1,000,000,000
# is given then only a single step() of 10^9 would be done)
if delay <= 1.0:
g.run(1)
newgen -= 1
# use fast stepping (thanks to PM 2Ring)
for i, d in enumerate(intbase(newgen, g.getbase())):
if d > 0:
g.setstep(i)
for j in xrange(d):
if g.empty():
g.show("Pattern is empty.")
return
g.step()
newsecs = time()
if newsecs - oldsecs >= delay: # time to do an update?
oldsecs = newsecs
g.update()
g.show("")
def gofast(newgen, delay):
''' Fast goto '''
#Save current settings
oldbase = g.getbase()
# oldhash = g.setoption("hashing", True)
g.show('gofast running, hit escape to abort')
oldsecs = time()
#Advance by binary powers, to maximize advantage of hashing
g.setbase(2)
for i, b in enumerate(intbits(newgen)):
if b:
g.setstep(i)
g.step()
g.dokey(g.getkey())
newsecs = time()
if newsecs - oldsecs >= delay: # do an update every sec
oldsecs = newsecs
g.update()
if g.empty():
break
g.show('')
#Restore settings
# g.setoption("hashing", oldhash)
g.setbase(oldbase)
def goto(newgen, delay):
g.show("goto running, hit escape to abort...")
oldsecs = time()
# before stepping we advance by 1 generation, for two reasons:
# 1. if we're at the starting gen then the *current* step size
# will be saved (and restored upon Reset/Undo) rather than a
# possibly very large step size
# 2. it increases the chances the user will see updates and so
# get some idea of how long the script will take to finish
# (otherwise if the base is 10 and a gen like 1,000,000,000
# is given then only a single step() of 10^9 would be done)
if delay <= 1.0:
g.run(1)
newgen -= 1
# use fast stepping (thanks to PM 2Ring)
for i, d in enumerate(intbase(newgen, g.getbase())):
if d > 0:
g.setstep(i)
for j in range(d):
if g.empty():
g.show("Pattern is empty.")
return
g.step()
newsecs = time()
if newsecs - oldsecs >= delay: # time to do an update?
oldsecs = newsecs
g.update()
g.show("")
def GotoLimited(gen, power):
g.setbase(8)
g.setstep(power)
while gen > int(g.getgen()) + g.getbase()**power:
g.step()
g.update()
goto(gen)
def GotoLimited(gen, power): g.setbase(8) g.setstep(power) while gen > int(g.getgen()) + g.getbase()**power: g.step() g.update() goto(gen)
def goto(newgen):
currgen = int(g.getgen())
if newgen < currgen:
# try to go back to starting gen (not necessarily 0) and
# then forwards to newgen; note that reset() also restores
# algorithm and/or rule, so too bad if user changed those
# after the starting info was saved;
# first save current location and scale
midx, midy = g.getpos()
mag = g.getmag()
g.reset()
# restore location and scale
g.setpos(midx, midy)
g.setmag(mag)
# current gen might be > 0 if user loaded a pattern file
# that set the gen count
currgen = int(g.getgen())
if newgen < currgen:
g.error("Can't go back any further; pattern was saved " +
"at generation " + str(currgen) + ".")
return
if newgen == currgen: return
oldsecs = time()
# before stepping we advance by 1 generation, for two reasons:
# 1. if we're at the starting gen then the *current* step size
# will be saved (and restored upon Reset/Undo) rather than a
# possibly very large step size
# 2. it increases the chances the user will see updates and so
# get some idea of how long the script will take to finish
# (otherwise if the base is 10 and a gen like 1,000,000,000
# is given then only a single step() of 10^9 would be done)
g.run(1)
currgen += 1
# use fast stepping (thanks to PM 2Ring)
oldstep = g.getstep()
for i, d in enumerate(intbase(newgen - currgen, g.getbase())):
if d > 0:
g.setstep(i)
for j in xrange(d):
if g.empty():
g.show("Pattern is empty.")
return
g.step()
newsecs = time()
if newsecs - oldsecs >= 1.0: # do an update every sec
oldsecs = newsecs
g.update()
g.setstep(oldstep)
def goto(newgen):
currgen = int(g.getgen())
if newgen < currgen:
# try to go back to starting gen (not necessarily 0) and
# then forwards to newgen; note that reset() also restores
# algorithm and/or rule, so too bad if user changed those
# after the starting info was saved;
# first save current location and scale
midx, midy = g.getpos()
mag = g.getmag()
g.reset()
# restore location and scale
g.setpos(midx, midy)
g.setmag(mag)
# current gen might be > 0 if user loaded a pattern file
# that set the gen count
currgen = int(g.getgen())
if newgen < currgen:
g.error("Can't go back any further; pattern was saved " +
"at generation " + str(currgen) + ".")
return
if newgen == currgen: return
oldsecs = time()
# before stepping we advance by 1 generation, for two reasons:
# 1. if we're at the starting gen then the *current* step size
# will be saved (and restored upon Reset/Undo) rather than a
# possibly very large step size
# 2. it increases the chances the user will see updates and so
# get some idea of how long the script will take to finish
# (otherwise if the base is 10 and a gen like 1,000,000,000
# is given then only a single step() of 10^9 would be done)
g.run(1)
currgen += 1
# use fast stepping (thanks to PM 2Ring)
oldstep = g.getstep()
for i, d in enumerate(intbase(newgen - currgen, g.getbase())):
if d > 0:
g.setstep(i)
for j in xrange(d):
if g.empty():
g.show("Pattern is empty.")
return
g.step()
newsecs = time()
if newsecs - oldsecs >= 1.0: # do an update every sec
oldsecs = newsecs
g.update()
g.setstep(oldstep)
g.show("Step %i of %i, Topo %i" % (i + 1, numsteps, posi))
event = g.getevent()
if event.startswith("key"):
evt, ch, mods = event.split()
if ch == "q":
out = 1
numsteps = i
break
fit_if_not_visible()
# poplist.sort(key=dict(zip(poplist, genlist)).get)
# save some info before we switch layers
stepsize = "%i^%i" % (g.getbase(), g.getstep())
pattname = g.getname()
# create population plot in separate layer
g.setoption("stacklayers", 0)
g.setoption("tilelayers", 0)
g.setoption("showlayerbar", 1)
layername = "population plot"
poplayer = -1
for i in xrange(g.numlayers()):
if g.getname(i) == layername:
poplayer = i
break
if poplayer == -1 and g.numlayers() == g.maxlayers():
g.exit("You need to delete a layer.")
oldsecs = time()
for i in xrange(numsteps):
g.step()
poplist.append( int(g.getpop()) )
genlist.append( int(g.getgen()) )
newsecs = time()
if newsecs - oldsecs >= 1.0: # show pattern every second
oldsecs = newsecs
fit_if_not_visible()
g.update()
g.show("Step %i of %i" % (i+1, numsteps))
fit_if_not_visible()
# save some info before we switch layers
stepsize = "%i^%i" % (g.getbase(), g.getstep())
pattname = g.getname()
# create population plot in separate layer
g.setoption("stacklayers", 0)
g.setoption("tilelayers", 0)
g.setoption("showlayerbar", 1)
if poplayer == -1:
poplayer = g.addlayer()
else:
g.setlayer(poplayer)
g.new(layername)
# use same rule but without any suffix (we don't want a bounded grid)
g.setrule(g.getrule().split(":")[0])