def CreateWssMovementData(recipes, dir): result = [] g.show(str(len(recipes.WssCreator))) for i in xrange(0, len(recipes.WssCreator)): recipes.Reset() recipes.Goto(-23, 1) recipes.AddWss(i) PlaceReadingHeads(recipes.recipe) goto(150000) g.fit() g.update() x, y, res = FindWssByDirection(True, distForward)[0] x += 23 y += -21 y = y % distForward result.append((x, y, res)) pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_ForwardWssBase.pkl"), "wb")) g.note(str(result))
def fit_if_not_visible():
try:
r = rect(g.getrect())
if (not r.empty) and (not r.visible()): g.fit()
except:
# getrect failed because pattern is too big
g.fit()
def make(blocks):
g.new("circuit")
for block in blocks:
fname = "blocks/{}.mc".format(block[0])
paste(g, fname, *transfo(block[1], block[2]))
g.fit()
g.save("circuit.mc", "mc")
def CreateWssMovementData(recipes, dir):
result = []
g.show(str(len(recipes.WssCreator)))
for i in xrange(0, len(recipes.WssCreator)):
recipes.Reset()
recipes.Goto(-23, 1)
recipes.AddWss(i)
PlaceReadingHeads(recipes.recipe)
goto(150000)
g.fit()
g.update()
x, y, res = FindWssByDirection(True, distForward)[0]
x += 23
y += -21
y = y % distForward
result.append((x, y, res))
pickle.dump(
result,
open(
path.join(dir,
str(step) + "_" + str(period) + "_ForwardWssBase.pkl"),
"wb"))
g.note(str(result))
def fit_if_not_visible():
try:
r = rect(g.getrect())
if (not r.empty) and (not r.visible()): g.fit()
except:
# getrect failed because pattern is too big
g.fit()
def trygliders(ginfo):
gdistance = ginfo / 4
phase = ginfo % 4
bstatus = boxstatus
pstatus = popstatus
for num in xrange(8):
tlist = form(celllist, num)
rect = boxform(fullrect, num)
g.new('')
g.putcells(tlist)
gx = rect[0] - 3 - gdistance
gy = rect[1] - 3 - gdistance
for w in xrange(rect[2] + 5):
g.new('')
g.putcells(tlist)
g.putcells(glider[phase], gx + w, gy)
g.fit()
g.update()
for gen in xrange(1000):
g.run(1)
if int(g.getpop()) <= 2:
g.new('')
g.show("Found clean glider destruction.")
status = 0, num, phase, [gx + w, gy]
putcells_and_fit(result(celllist, status))
g.exit()
box = g.getrect()[2:]
# Checking the bounding box size and population against the current lowest found.
if reduce(mul, box) < reduce(mul, bstatus[0]):
bstatus = (box, num, phase, [gx + w, gy])
pop = int(g.getpop())
if pop < pstatus[0]:
pstatus = (pop, num, phase, [gx + w, gy])
# Show results if the user presses certain keys
event = g.getevent()
if event.startswith("key x"):
g.new('')
put_result_pair(celllist, bstatus, pstatus)
g.select(g.getrect())
g.copy()
g.select([])
g.note(
"Minimum bounding box and population collisions copied to clipboard."
)
if event.startswith("key q"):
g.new('')
g.show("Search stopped.")
put_result_pair(celllist, bstatus, pstatus)
g.fit()
g.exit()
g.show(
"Searching for a 1-glider destruction... press <x> to copy minimum bounding box and population results to clipboard; press <q> to quit. Stats: minimum bounding box %dx%d, minimum population %d"
% (bstatus[0][0], bstatus[0][1], pstatus[0]))
return bstatus, pstatus
def main():
apgcode = canonise()
if not apgcode:
g.warn(
'Failed to detect periodic behaviour after {} generations.'.format(
MAXPERIOD))
# 2G collisions
if apgcode in twoGcols:
cols = twoGcols[apgcode]
else:
cols = []
# 3G and 4G collisions
for cFile in compFiles:
with open(cFile) as cF:
found_code = False
for l in cF:
line = l.strip()
if not found_code:
if line == apgcode:
found_code = True
continue
elif '>' in line:
in_code, gstr, _ = line.split(">")
if in_code:
g.warn(
'Non-empty starting target in glider collision - Not implemented'
)
else:
cols.append(gstr)
else:
break
Ncols = len(cols)
if Ncols:
try:
cols = [reconstruct(col) for col in cols]
except Exception:
g.note(str(cols))
g.new("solutions")
g.show("{} collisions found".format(Ncols))
g.setname(apgcode)
if Ncols <= 20:
N = 5
else:
N = math.ceil(math.sqrt(Ncols)) + 1
offset = 100
for i, col in enumerate(cols):
g.putcells(col, int((i % N) * offset), int((i // N) * offset))
g.fit()
else:
g.note(
"No glider collisions found for constellation {}. Better luck next time"
.format(apgcode))
def TestRecipe(recipe, recipes): recipes.Goto(-23, 1) for i in xrange(0, len(recipe)): recipes.recipe.append(recipe[i] + recipes.blockY - recipes.blockX) PlaceReadingHeads(recipes.recipe) goto(150000) g.fit() g.update() x, y, res = FindWssByDirection(True, distForward)[0] x += 23 y += -21 y = y % distForward
def TestRecipe(recipe, recipes):
recipes.Goto(-23, 1)
for i in xrange(0, len(recipe)):
recipes.recipe.append(recipe[i] + recipes.blockY - recipes.blockX)
PlaceReadingHeads(recipes.recipe)
goto(150000)
g.fit()
g.update()
x, y, res = FindWssByDirection(True, distForward)[0]
x += 23
y += -21
y = y % distForward
def getinp(s):
###########################
temp = g.getcell(x, y)
g.setcell(x, y, 5)
g.show(s + "Ptr:" + str(ptr) + " x:" + str(x) + " y:" + str(y))
g.fit()
g.update()
g.setcell(x, y, temp)
# return
k = g.getevent()
count = 0
while k == "":
sleep(.01)
k = g.getevent()
count += 1
if k == "key q none": g.exit()
return
def better_randfill():
g.new('')
g.select([-10, -10, GRID_SIZE[0], GRID_SIZE[1]])
g.randfill(random.randrange(50))
g.select([])
g.autoupdate(True)
cnt = 0
for x in range(0, GENS):
cnt += 1
if not g.empty():
g.run(1)
if is_static():
break
time.sleep(0.05)
else:
break
if cnt % 10 == 0:
g.fit()
def add_shooter(cost, inserter_cells, left_g, right_g=[], flip=True):
global shoot_defs
g.new('')
g.putcells(inserter_cells)
g.putcells(left_g)
g.putcells(right_g)
g.run(2048)
reaction_cells = g.getcells([-150,-150,300,300])
g.run(512)
if not all(g.getcell(x, y) for x, y in gld_pairs):
g.fit()
g.update()
assert(False)
stable_cells = set(zip(reaction_cells[::2], reaction_cells[1::2]))
for _ in range(4):
g.run(1)
for i in range(0, len(reaction_cells), 2):
tup = reaction_cells[i], reaction_cells[i+1]
if tup in stable_cells and not g.getcell(*tup):
stable_cells.remove(tup)
stable_cells2 = []
for x, y in stable_cells:
stable_cells2.append(x)
stable_cells2.append(y)
stable_cells = stable_cells2
tup = (cost, inserter_cells, left_g, right_g, reaction_cells, stable_cells)
shoot_defs.append(tup)
if flip:
shoot_defs.append((cost,
f(inserter_cells),
f(right_g),
f(left_g),
f(reaction_cells),
f(stable_cells)))
def CreateWssMovementData(recipes, dir, isUp = True): result = [] for i in xrange(0, len(recipes.WssCreator)): g.show(str(i)) recipes.Reset() if isUp: recipes.Goto(-23, 1) recipes.AddWss(i) PlaceReadingHeads(recipes.recipe) goto(150000) g.fit() g.update() if isUp: x, y, res = FindWssByDirection(isUp, distForward)[0] x += 23 y += -21 y = y % distForward else: x, y, res = FindWssByDirection(isUp, distBack)[0] y = y % distBack result.append((x, y, res)) if isUp: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_ForwardWssBase.pkl"), "wb")) else: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_BackwardWssBase.pkl"), "wb")) g.note(str(result))
def CreateWssMovementData(recipes, dir, isUp = True): result = [] for i in xrange(0, len(recipes.WssCreator)): g.show(str(i)) recipes.Reset() if isUp: recipes.Goto(-23, 1) recipes.AddWss(i) PlaceReadingHeads(recipes.recipe) goto(150000) g.fit() g.update() if isUp: x, y, res = FindWssByDirection(isUp, distForward)[0] x += 23 y += -21 y = y % distForward else: x, y, res = FindWssByDirection(isUp, distBack)[0] y = y % distBack result.append((x, y, res)) if isUp: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_ForwardWssBase.pkl"), "wb")) else: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_BackwardWssBase.pkl"), "wb")) g.note(str(result))
def main():
g.setstep(0)
g.setalgo('QuickLife')
velocity = g.getstring('Please specify velocity', '(2,1)c/6')
a, b, p = parse_velocity(velocity)
params = partial_derivatives(a, b, p)
dvdy = params['dvdy']
dudy = params['dudy']
dvdt = params['dvdt']
cells = g.getcells(g.getrect())
cells = zip(cells[::2], cells[1::2])
gcells = []
for (u, v) in cells:
for t in xrange(p):
xp = dvdy * u - dudy * v - a * t
yq = v - t * dvdt
if (xp % p != 0):
continue
if (yq % dvdy != 0):
continue
x = xp // p
y = yq // dvdy
gcells.append((t, x, y))
spacing = max([x for (_, x, _) in gcells]) - min([x for (_, x, _) in gcells])
spacing += 10
gcells = [(x + spacing * t, y) for (t, x, y) in gcells]
g.setlayer(g.addlayer())
g.putcells([x for y in gcells for x in y])
g.fit()
def display(self, title = "untitled", x = 0, y = 0, A = identity):
"""Paste pattern into new universe and display it all."""
golly.new(title)
golly.putcells(self, x, y, *A)
golly.fit()
golly.setcursor(zoomin)
for column in range(15):
pixels[31 + row][(color - 1) * 31 + column] = bg_col
for row in range(7):
for column in range(7):
pixels[46 + row][(color - 1) * 31 + column] = bg_col
# use rule_name.tree and icon info to create rule_name.rule
ConvertTreeToRule(rule_name, total_states, pixels)
# switch to the new rule
golly.new(rule_name + '-demo.rle')
golly.setalgo('RuleLoader')
golly.setrule(rule_name)
golly.setcell(0, 0, encode(0, 0, 0)) # start with a single turmite
golly.show('Created ' + rule_name + '.rule and selected that rule.')
'''
# we make a turmite testbed so we don't miss interesting behaviour
# create an area of random initial configuration with a few turmites
for x in range(-300,-100):
for y in range(-100,100):
if x%50==0 and y%50==0:
golly.setcell(x,y,n_colors) # start with a turmite facing N
else:
golly.setcell(x,y,random.randint(0,n_colors-1))
# create a totally random area (many turmites)
for x in range(-200,-100):
for y in range(200,300):
golly.setcell(x,y,random.randint(0,total_states-1))
g.putcells(frontBackPart, d + dx, 3 * d + dy)
if toPlaceFirstSL:
g.putcells(frontSL, d + dx, d + dy + helixSLdy)
def MakeForwardRecipe(helixSLdy, distance, dx, dy, recipe):
d = (distance - 98) / 2
frontSL = g.parse("bo$obo$o2bo$b2o!", 132 + d + dx, 314 + d + dy)
curd = helixSLdy + distance
for r in recipe:
if r != 'SKIP':
g.putcells(frontSL, 0, curd + r)
curd += distance
'''
if directionType == "B":
for y in xrange(-3 * len(hwssRecipe), 1):
MakeBackwardSalvo(step, 0, distBack * y, step * len(hwssRecipe) + 100, y == 0, y == 0)
MakeBackwardRecipe(step, 0, 0, hwssRecipe)
else:
for y in xrange(0, 3 * len(hwssRecipe) + 1):
MakeForwardSalvo(step, distForward * y, y == 0, y == 0)
MakeForwardRecipe(step, 0, 0, hwssRecipe)
g.fit()
'''
OFFcell += RuleBits
ONcell += RuleBits
g.autoupdate(True)
g.new(layername)
g.setalgo("QuickLife") # qlife's setcell is faster
for j in xrange(selheight):
for i in xrange(selwidth):
golly.show("Placing (" + str(i+1) + "," + str(j+1) + ") tile" +
" in a " + str(selwidth) + " by " + str(selheight) + " rectangle.")
if livecell[i][j]:
ONcell.put(2048 * i - 5, 2048 * j - 5)
else:
OFFcell.put(2048 * i - 5, 2048 * j - 5)
g.fit()
g.show("")
g.setalgo("HashLife") # no point running a metapattern without hashing
g.setoption("hyperspeed", False) # avoid going too fast
g.setbase(8)
g.setstep(4)
g.step() # save start and populate hash tables
# g.run(35328) # run one full cycle (can lock up Golly if construction has failed)
#
# Note that the first cycle is abnormal, since it does not advance the metapattern by
# one metageneration: the first set of communication signals to adjacent cells is
# generated during this first cycle. Thus at the end of 35328 ticks, the pattern
# is ready to start its first "normal" metageneration (where cell states may change).
#
def dmprinter(pdy, copies=1):
''' Generate & display a dot matrix printer for named bitmap pattern '''
#Horizontal pixel separation between LineMakers. minimum = 5
LMsx = 5
#Horizontal distance between bitmap pixels. Constant, due to LineMaker period
pdx = 15
#Distance between LineMakers
LMdx, LMdy = -LMsx * pdx, pdy
#Get bitmap pattern from current selection.
bm = get_bitmap()
#Make printer in a new layer
golly.duplicate()
golly.setoption("syncviews", False)
#Build new window title from old
title = golly.getname().split('.')[0]
title = '%s_Printer [%d] v0.10' % (title, pdy)
golly.new(title)
#Make sure we're using the standard Life generation rule
golly.setrule("B3/S23")
#Bitmap dimensions. Width MUST be of form 4m, for m >=1
bmheight = len(bm)
bmwidth = len(bm[0])
mid = (bmheight + 1) // 2
loopw = (bmwidth - 8) // 4
loopm = pdx * loopw
#Gliders, heading north-east
g0 = pattern('2bo$2o$b2o!')
g1 = pattern('obo$2o$bo!')
gliders = [
g0, g1,
g1(0, 2, rccw),
g0(0, 2, rccw),
g0(2, 2, flip),
g1(2, 2, flip),
g1(2, 0, rcw),
g0(2, 0, rcw)
]
#Create full Glider loop.
gg = []
ox, oy = 35, 23
for j in xrange(loopw + 1):
dd = pdx * j
gg += [
gliders[0](ox + dd, oy - dd), gliders[1](ox + 8 + dd, oy - 7 - dd)
]
dd = loopm
gg += [gliders[2](45 + dd, 4 - dd), gliders[3](37 + dd, -3 - dd)]
ox, oy = 26 + loopm, -4 - loopm
for j in xrange(loopw + 1):
dd = pdx * j
gg += [
gliders[4](ox - dd, oy + dd), gliders[5](ox - 8 - dd, oy + 7 + dd)
]
dd = loopm
gg += [gliders[6](16, 15), gliders[7](24, 22)]
parity = 2 * ((loopw + 1) * (0, 0) + (1, 1))
def buildLM():
''' Build a complete LineMaker '''
#Populate glider loop. (jj, ii) are bitmap coords
gloop = pattern()
for j in xrange(bmwidth):
jj = (j - delta + bmwidth - 1) % bmwidth
#Is there a pixel at this location?
if bm[ii][jj] == parity[j]:
gloop += gg[j] #Add glider to the loop
#Only put LineMaker if glider loop isn't empty
if len(gloop) > 0:
(LMBlank + gloop).put(Lx, Ly, trans)
#Assemble blank LineMaker
LMBlank = linemaker(loopm)
#Do upper LineMakers
trans = identity
for i in xrange(mid):
ii = mid - (i + 1)
io = mid + (i + 1)
Lx, Ly = io * LMdx, ii * LMdy
delta = LMsx * io
buildLM()
#Do lower LineMakers
trans = flip_y
for i in xrange(mid, bmheight):
ii = i
io = i + 2
Lx, Ly = io * LMdx + pdx, ii * LMdy + 128
delta = LMsx * io - 1
buildLM()
#Eaters facing south-east & north-east
eaterSE = pattern('2o$bo$bobo$2b2o!')
eaterNE = eaterSE(0, 10, flip_y)
eY = 59
eaters = (eaterNE(0, eY), eaterSE(0, eY))
#Eater horizontal displacement. Must be odd
#bmwidth muliplier determines number of copies visible 'outside' printer.
eX = (bmheight + 1) * LMdx - (copies * bmwidth - 1) * pdx
eX = 1 + eX // 2 * 2 #Adjust parity
all = pattern()
for i in xrange(bmheight):
all += eaters[i % (1 + LMsx % 2)](eX, i * LMdy)
all.put()
#Centre view over bitmap output area
golly.setpos(str(-pdx * bmwidth // 2 + (bmheight - 1) * LMdx),
str(Ly // 2))
#golly.setmag(-2) #Aliasing effects happen at smaller scales than -2 :(
golly.fit()
def fit_if_not_visible():
# fit pattern in viewport if not empty and not completely visible
r = rect(g.getselrect())
if (not r.empty) and (not r.visible()): g.fit()
def export_icons(iconsection, rulename):
global multi_color_icons
if multi_color_icons:
# prepend a new @COLORS section with the average colors in each icon
iconsection = create_average_colors(iconsection) + iconsection
# replace any illegal filename chars with underscores
filename = rulename.replace("/", "_").replace("\\", "_")
# we will only create/update a .rule file in the user's rules folder
# (ie. we don't modify the supplied Rules folder)
rulepath = g.getdir("rules") + filename + ".rule"
fileexists = os.path.isfile(rulepath)
if fileexists:
# .rule file already exists so replace or add @ICONS section
rulefile = open(rulepath, "rU")
# create a temporary file for writing new rule info
temphdl, temppath = mkstemp()
tempfile = open(temppath, "w")
wroteicons = False
skiplines = False
for line in rulefile:
if line.startswith("@ICONS"):
# replace the existing @ICONS section
tempfile.write(iconsection)
wroteicons = True
skiplines = True
elif line.startswith("@COLORS") and multi_color_icons:
# skip the existing @COLORS section
# (iconsection contains a new @COLORS section)
skiplines = True
elif skiplines and line.startswith("@"):
if wroteicons: tempfile.write("\n")
skiplines = False
if not skiplines:
tempfile.write(line)
if not wroteicons:
# .rule file had no @ICONS section
tempfile.write("\n")
tempfile.write(iconsection)
# close files
rulefile.close()
tempfile.flush()
tempfile.close()
os.close(temphdl)
# remove original .rule file and rename temporary file
os.remove(rulepath)
move(temppath, rulepath)
else:
# .rule file doesn't exist so create it
rulefile = open(rulepath, "w")
rulefile.write("@RULE " + filename + "\n\n")
if not multi_color_icons:
# grayscale icons, so check if Rules/filename.rule exists
# and if so copy any existing @COLORS section
suppliedrule = g.getdir("app") + "Rules/" + filename + ".rule"
if os.path.isfile(suppliedrule):
colordata = get_color_section(suppliedrule)
if len(colordata) > 0:
rulefile.write(colordata)
rulefile.write(iconsection)
rulefile.flush()
rulefile.close()
# create another layer for displaying the new icons
if g.numlayers() < g.maxlayers():
g.addlayer()
g.new("icon test")
g.setrule(rulename)
for i in range(g.numstates() - 1):
g.setcell(i, 0, i + 1)
g.fit()
g.setoption("showicons", True)
g.update()
if fileexists:
g.note("Updated the icon data in " + rulepath)
else:
g.note("Created " + rulepath)
''' setconf2.py clears grid and sets just as specified by configuration conf2 in parameters.py ''' import parameters reload(parameters) from parameters import conf2, nstates from golly import setcell, clear, select, getrect, fit, show if len(getrect()) > 0: select(getrect()) clear(0) for i in range(0,len(conf2),2): c = conf2[i] if i+1 < len(conf2): c += conf2[i+1] * nstates setcell(i//2,0,c) show(str(i)) select([]) fit()
def prepare_burp():
highway_robber=pattern("""
143bo$143b3o$146bo$145b2o2$126bo42bo$126b3o38b3o$129bo36bo$128b2o11b2o
23b2o7b2o$141b2o32bo$108bo64bobo$108b3o6b2o54b2o$111bo5b2o$110b2o3$
111b2o$111b2o3b2o$116b2o35b2o23bo$154bo22bobo$151b3o8b2o14bo$151bo11bo
$98bo7bo53b3o$86bo11b3o5b3o51bo$84b3o14bo7bo32b2o$68bo14bo16b2o6b2o32b
obo30b2o$68b3o12b2o59bo30bobo$71bo72b2o31bo$70b2o105b2o$159bob2o$159b
2obo$71b2o$71b2o17b2o76b2o$90b2o76b2o5$104b2o$87b2o14bobo$87bo15bo74b
2o$88b3o11b2o74bo$90bo85bobo$84b2o90b2o$84bo$85b3o$87bo2$158b2o$159bo$
68b2o89bobo$67bobo90b2o$67bo25b2o$66b2o25bo$74b2o15bobo$74b2o15b2o98b
2o6bo$187bobo2bo4b3o$185b3ob2o5bo$184bo11b2o$185b3ob2o$177b2o8bob2o$
177b2o2$161b2o32b2o3b2o$161b2o32b2o3b2o$153b2o$88b2o2b2ob2o57bo18b2ob
2o$73b2o13bobo2bobo58bobo16b2obo$72bobo16b2o3bo58b2o21bo26bo$72bo19bob
2o76bob5o25bobo$71b2o16bo2bobo77b2o31bo$88bobobobo80b2o$89b2ob2o82bo$
173b3o$173bo33bo$171bobo31b3o$171b2o31bo$187b2o14bobo$187b2o15bo$83b2o
$83b2o$202b2o$202b2o2$175b2o$175b2o$72b2o123b2o$73bo19b2o102bo$73bobo
17bo76b2o26b3o$74b2o15bobo60b2o14b2o28bo$86bo4b2o62bo$85bobo64b3o$54bo
30bobo64bo$54b3o17b2o10bo$57bo15bobo$56b2o15bo116b2o$72b2o116bo$36b2o
49b2o102b3o$29b2o5b2o49bo105bo$29b2o57b3o6bo$90bo4b3o$94bo$31b2o17b2o
29b2o11b2o14b2o$31b2o17bo30b2o27b2o$25b2o21bobo$25b2o21b2o$116b2o$116b
2o36b2o$112b2o41bo$112b2o41bobo$156b2o$56b2o122b2o$56b2o11b2o109b2o$
69bo47b2o$70b3o44b2o$72bo2$22bo$22b3o55b2o96b2o$25bo53bobo96bo$24b2o
47b2o4bo99b3o$73b2o3b2o101bo$179b2o$76b4o99bo$75bo3bo97bobo$75b2o100b
2o$53b2o33bo22b2o$19b2o32b2o33b3o20bo$20bo70bo20b3o$20bobo67b2o22bo44b
o$21b2o136b3o$162bo$115bo45b2o$35b2o28b2o46b3o$35bobo27b2o45bo$37bo41b
2o6b2o23b2o$37b2o40b2o6bo2b2o$83b2o3b2obo$83b2o4bo89b2o$17bob2o68bo89b
o$17b2obo67b2obob2o18b2o62bobo$87bo2b2ob2o18bobo61b2o$26b2o60bo26bo$
26b2o33b2o26b3ob2o20b2o$60bo2bo27bobo66b2o$61bobo29bo66b2o15b2o$62bo
29b2ob2o80bobo$94bobo82bo$94bo84b2o$93b2o3$160b2o$160bo$158bobo$158b2o
2$16bo$16b3o$19bo33bo121b2obo$18b2o33b3o53b2o64bob2o$56bo52b2o$11bo43b
obo110b2o$11b3o42bo111b2o$14bo123bo$13b2o121b3o$57b2o19bo56bo$57b2o17b
3o19b2o20bo14b2o$75bo23bo19bobo$75b2o22bobo17bobo$100b2o15bobobobo34b
2o$10b2o19b2o79bo4b2o3b2o10bo24bo$10b2o19b2o47b2o29bobo19bobo23bobo$
80b2o29bobo19bobo24b2o$4bo95b2o10bo21bo4b2o$4b3o25b2o65bobo20b2o15bobo
$2o5bo24bo57b2o7bo21bobo17bo$bo4b2o25b3o54bo7b2o21bo19b2o36bo$bobo31bo
52bobo22b2o5b2o55b3o$2b2o29b2o53b2o23bo62bo$33bo17b2o61b3o28b2o29b2o$
31bobo4bo11bobo63bo28bo$31b2o3b3o11bo92bobo$35bo13b2o92b2o$35b2o94b2o$
61b2o68b2o$61b2o$b2o178b2o$b2o178bo$36b2o141bobo$36b2o141b2o3$27b2o37b
2o97b2o$27b2o36bobo51b2o43bobo$65bo54bo43bo$64b2o54bobo40b2o$121b2o2$
181b2obo$181bob2o2$40bo133b2o$38b3o133b2o$37bo$37b2o$138b2o$138b2o$42b
2o$42b2o78b2o$122b2o$114b2o$52b2o61bo18b2ob2o$52bo62bobo16b2obo$50bobo
63b2o21bo$50b2o81bob5o$13b2o118b2o$12bobo121b2o$12bo124bo$11b2o99bobo
19b3o$112b2obo18bo$23b2o90b3o$23b2o87b2o4bo$112bob5o$114bo$113bo3b2o$
108bo3bo3bobo$106b3o3b2o3bo$105bo$28b2o75b2o29b2o39b2o$27bobo106b2o38b
o2bo$27bo149b2o$26b2o2$131b2o$131b2o$135b2o$14b2o119b2o$14b2o35bo$49b
3o$48bo80b2o$48b2o63b2o14b2o$79bo33bo$68b2o7b3o34b3o$69bo6bo39bo$69bob
o4b2o$70b2o$109b2o$109bobo$111bo$111b2o7$103b2o$103bo$104b3o$106bo$13b
o19b2o$12bobo10b2o6bo5b2o41b2o$11bo2bo10bo8b3obobo41bo$12b2o9bobo10bob
o7b2o28b2obo3b3o$23b2o12b2o7b2o28b2ob4o2bo$82bo$64b2o6b2o2b2ob2o$63bob
o6bo4bobo$63bo9b4o2bo$62b2o7bobo2bobo$71b2o4bo!""")
connecting_neck=pattern("""
24bo$22b3o$21bo$21b2o$6b2o$7bo$7bobo$8b2o10bo$19bobo$19bobo$20bo4b2o$
8b2o15bobo$7bobo17bo$7bo19b2o$6b2o6$17b2o$17b2o7$23b2ob2o$22bobobobo$
5b2o16bo2bobo$6bo19bob2o$6bobo16b2o3bo$7b2o13bobo2bobo$22b2o2b2ob2o11$
8b2o15b2o$8b2o15bobo$2o25bo$bo25b2o$bobo$2b2o4$21bo107bo$19b3o106bobo$
18bo109bobo$18b2o106b3ob2o$24bo100bo$22b3o12bo84bo2b4ob2o$21bo15b3o82b
3o3bob2o$21b2o17bo84bo$39b2o83b2o26b2o$152bo$150bobo$150b2o2$24b2o$5b
2o17b2o76bo$5b2o95b3o6b2o$105bo5b2o41b2obo$104b2o48bob2o$4b2o$5bo141b
2o$2b3o12b2o86b2o40b2o$2bo14bo16b2o6b2o61b2o3b2o$18b3o14bo7bo66b2o$20b
o11b3o5b3o$32bo7bo$78bo51b2o3b2o$76b3o13bo38bo3bo$75bo16b3o33b3o5b3o$
50b2o23b2o18bo32bo9bo$45b2o3b2o42b2o42bobo$45b2o92b2o3$44b2o76b2o$45bo
5b2o69b2o$42b3o6b2o104b2o$42bo41b2o71bo$84b2o69bobo$61b2o92b2o$60bobo
62bo$60bo62b3o$59b2o10b2o49bo$72bo48bobo$69b3o9b2o39bo43b2o$69bo11bo
19b2o56b2o6bo$82bo17bobo56bo6bo$81b2o17bo19b2o35bobo6b2o$99b2o19b2o35b
2o$116b2o$116bo$117b3o24b2o$119bo23bobo$143bo25b2o$142b2o25b2o4$146b2o
$145bobo$145bo4b2o$144b2o5bo$148b3o5bo$148bo6bobo$156bo!""")
transmitter2c3=pattern("""
180b2o$180b2o$219bo$219b3o$178b2o42bo$116bo61b2o41b2o$115bobo47b2o99b
2o14bo$116bo49bo74b2o24bo14b3o$166bobo73bo13b2o6b3o18bo$167b2o73bobo
11b2o6bo19b2o12bo$110b2o51b2o78b2o53b3o$110b2o23b2o26b2o136bo$102b2o
31bo164b2o$103bo29bobo$103bobo27b2o$104b2o4b2o$110b2o162b2o$274b2o$
144b2o30b2o$102b2o40bo31b2o$102bo39bobo$104bob2o34b2o43b2o144b2o$103b
2ob2o78bo2bo143b2o$124b2o60bobo23b2o57b2o$103b2ob2o16b2o61bo20bo3b2o
57bo20b2o$104bobo100bobo26b2o14b2o3b2o13bo20bo$104bobo99bobo21b2o5bo
15bo3bo13b2o17b3o61b2o$105bo100bo23bobob3o13b3o5b3o29bo63b2o5b2o$205b
2o16b2o7bobo15bo9bo100b2o$223b2o7b2o152b2o6bo$169b2o125b2o84bobo2bo4b
3o$169b2o124bobo61b2o19b3ob2o5bo$295bo63b2o18bo11b2o$294b2o69b2o13b3ob
2o$365b2o15bob2o$131b2o151bo$131b2o149b3o12b2o$281bo16bo91b2o3b2o$271b
2o8b2o12b3o92b2o3b2o$272bo22bo$272bobo27b2o30b2o$273b2o28bo17b2o11b2o$
39bo82bo136bo27b2o11b3o19bo77bo$38bobo79b3o136b3o25b2o11bo18b3o77bobo$
39bo79bo142bo56bo80bo$108bo10b2o140b2o$37b5o65bobo228b2o$37bo4bo64bobo
177b2o50bo28b2o$40bo2bo61b3ob2o20bo155b2o47b3o29bo$12bo27b2obo60bo24b
3o204bo29bobo$12b3o10b2o10bo5bob2obo49bo6b3ob2o17bo104bo132b2o$15bo9b
2o9bobo4bobob2o49b3o6bob2o17b2o103b3o146b2o$4b2o8b2o20bo2bo2b2obo30b2o
23bo134bo145b2o$5bo31b2o6bo31bo6b2o14b2o133b2o11b2o13b2o$5bobo37b3o29b
obo4b2o39b2o121b2o13b2o$6b2o40bo23b2o4b2o44bo2bo87bo73b2o$47b2o23bobo
50b2o88b3o5b2o64bo$70bobob3o141bo4b2o62bobo$66b2o2b2o5bo139b2o68b2o81b
2o$4bob2o58b2o8b2o292b2o$2b3ob2o384b2o$bo216b2o172bo$2b3ob2o80b2o128b
2o3b2o123b2o15b2o26b3o$4bobo30b2o49b2o23b2o108b2o122bobo15b2o28bo$4bob
o30b2o74bo233bo$5bo108b3o229b2o$116bo77b2o7b2o$100b2o24b2o66b2o7bobo$
28b2o66bo3b2o24bo30b2o42bobob3o$28b2o65bobo29b3o2b2o24bo42b2o5bo40b2o
18b2obo112b2o$34b2o58bobo32bo3bo13b2o6b3o49b2o40bobo17bob2o112bo$34bo
19b2o38bo38bobo11b2o6bo95bo134b3o$30bo5bo16bobo37b2o24b2o13b2o115b2o
135bo$29bobo3b2o16bo65b2o164b2obo$30bo21b2o231bob2o$31b3o$33bo79b2o
163b2o$113b2o163b2o$117b2o46b2o$66b2o49b2o46b2o$66b2o$349b2o$350bo$71b
2o39b2o98b2o136bobo$70bobo39b2o99bo54b2o81b2o$70bo91b2o46b3o56bo105b2o
$69b2o91bo47bo58bobo103b2o$143b2o3b2o13bo106b2o$82b2o60bo3bo13b2o$82b
2o57b3o5b3o$141bo9bo40b2o$193bo$27bo162b3o180b2o$26bobo161bo182bo$26bo
2bo262b2o80b3o$27b2o263bo83bo$118b2o22bo147bobo81b2o$119bo20b3o99bo18b
o28b2ob2o79bo$116b3o20bo102b3o7b2o5b3o31bobo76bobo$116bo22b2o104bo6b2o
4bo34bobo76b2o$5b2o237b2o12b2o10b2o20b2ob2o$5b2o264bo24bo$9b2o104bo
155bobo18b2obo$9b2o104b3o139b2o13b2o18b2obobo56bo$23b2o93bo133b2o3b2o
37b2o56b3o$23b2o92b2o23b2o108b2o103bo$139b2o2bo212b2o28b2o$139bob2o71b
2o56b2o112bo$141bo71bobo55bobo110bobo$141bo71bo49bo7bo108b2o2b2o$116b
2o18b2obob2o69b2o47b3o5b3o108b2o$35b2o78bobo18b2ob2o2bo116bo7bo$35b2o
78bo26bo117b2o6b2o$13b2o99b2o20b2ob3o$14bo122bobo239b2o4b2o$11b3o123bo
241b2o4b2o$11bo90b2o30b2ob2o$102bo31bobo$100bobo5b2o26bo$99bobo6b2o26b
2o140b2o$95b2o3bo177b2o72b2o35bo$95b2o254bobo33b3o$20b2o69b2o194b2o62b
o34bo$21bo70bo194bo62b2o34b2o$18b3o71bobo193b3o63b2o$18bo74b2o195bo63b
2o3bo$233bo47b2o75bobo6b2o$233b3o46bo76bobo5b2o$236bo44bo79bo$235bobo
43b2o78b2o$120b2o4b2o108bo30bo$120b2o4b2o139b3o$270bo$237b2o30b2o8b2o
74bo$237b2o40bo61bo13b3o35b2o$121b2o154bobo59b3o16bo34b2o$121b2o2b2o
150b2o59bo18b2o$125bobo93bo41b2o73b2o$127bo92bobo40b2o26b2o$97b2o28b2o
91bobo68bo23bo72b2o$98bo119b3ob2o65bobo23b3o70b2o$95b3o119bo71b2o27bo
73b2o$95bo118bo2b4ob2o39b2o52b2o73b2o$214b3o3bob2o39b2o$217bo130b2o$
175bo40b2o26b2o102b2o36b2o$113b2o60b3o66bo126b2o13b2o$113bobo46b2o3b2o
9bo14b2o47bobo126bobo$77bo37bo2bo2bo40b2o3b2o8b2o15bo47b2o43b2o84bo$
77b3o35b7o71bo93b2o72b2o10b2o$80bo112b2o113b2o51bo$38b2o39b2o36b5o33b
2o151b2o41b2o9b3o$38b2o77bo4bo2b2o29bo174b2o19bo11bo$120bo2bo2bo29bobo
87b2obo81bobo17bo$120b2obobo31b2o87bob2o83bo17b2o$117bo5bob2o194b2o10b
2o$105b2o9bobo4bo72b2o41b2o80bo$105b2o9bo2bo2b2o72b2o41b2o70b2o9b3o$
117b2o193bo11bo$96b2obo211bo$96bob2o211b2o$160b2o$61b2o98bo60b2o3b2o$
61b2o8b2o85b3o28b2o32bo3bo$72bo85bo31bo15b2o12b3o5b3o29b2o$69b3o117bo
17bo12bo9bo28bobo$47b2o20bo119b2o13b3o23bobo26bo$48bo155bo26b2o25b2o
14b2o$10b2o33b3o70b2o153bo2bo$10b2o33bo29b2o41b2o154b2o$6bo50b2o15bobo
$6b3o48bo16bo98b2o$9bo48b3o12b2o98b2o54b2o$8b2o11bo38bo103b2o64bo$20bo
bo7b2o131bobo51b2o11bobo$20bobo7b2o44b2o85bo54bo12b2o$21bo55bo84b2o54b
obo$74b3o142b2o2b2o$74bo148b2o$81b2o34b2o$82bo34bobo$18b2o59b3o37bo$
18b2o59bo39b2o97b2o4b2o$4b2o212b2o4b2o$4b2o$2o$2o162bo$107bob2o3b2o48b
3o$105b3ob2o3bo52bo$104bo10b3o48b2o$105b3ob2o6bo101b2o$107b2o2bo106bob
o$110b2o106bo$217b2o2$164b2o$164b2o$188b2o$188bobo$190bo$24b2o164b2o$
23bobo$24bo4$132bo4b2o$131bobo2bobo7b2o$130bo2b4o9bo$26b2obo100bobo4bo
6bobo$26bob2o99b2ob2o2b2o6b2o$127bo$19b2o103bo2b4ob2o$19b2o103b3o3bob
2o$127bo40b2o$126b2o39bobo$52b2o103bo9bo$52b2o49b2o52b3o5b3o54b2o$104b
o55bo3bo57b2o$91bo11bo55b2o3b2o$9b2o39b2o39b3o9b2o$10bo39b2o42bo$10bob
o24b2o42b2o10b2o$11b2o25bo43bo150b2o$38bobo41bobo91b2o55bo$39b2o42b2o
91b2o53bobo$35b2o69b2o123b2o$35b2o69b2o75bob2o$29b2o152b2obo$29bo188b
2o$27bobo187bobo$27b2o109b2o77bo$132b2o4bobo75b2o$133bo6bo38b2o$48b2o
66b2o12b3o7b2o37bobo$48b2o47b2o18bo12bo50bo$97bo16b3o36b2o26b2o$59b2o
37b3o13bo39bo$58bo2bo38bo50b3o3bob2o59b2o$58bobo23b2o65bo2b4ob2o58bobo
$59bo20bo3b2o68bo64bo$79bobo73b3ob2o57b2o$7b2o69bobo76b2o2bo$7b2o17b2o
50bo81b2o84bo$26b2o49b2o165b3o$243bo$41b2o200b2o$41b2o2$219bo$219b3o$
222bo$221b2o23b2o$243b2o2bo$243bob2o$245bo$245bo$220b2o18b2obob2o$219b
obo18b2ob2o2bo$219bo26bo$218b2o20b2ob3o$241bobo$51bo189bo$12b2o35b3o
186b2ob2o$12b2o34bo189bobo$48b2o190bo$81bo158b2o$81b3o$17b2o65bo$17b2o
64b2o$13b2o$13b2o2$57b2o159b2o$19b2o36b2o158bobo$19b2o13b2o181bo$33bob
o180b2o$33bo181bo$32b2o10b2o74bo94b3o$45bo72b3o97bo$42b3o9b2o61bo99b2o
$42bo11bo20b2o40b2o17bo39bo$55bo20bo59b3o37b3o$54b2o17b3o63bo39bo$73bo
64b2o38b2o12bo$192b3o$159bo35bo19b2o$79b2o78b3o32b2o19b2o$78bobo81bo
76b2o$78bo82b2o11b2o63bobo$77b2o95b2o65bo$241b2o2$80b2o$81bo$78b3o$78b
o$85b2o30b2o$86bo17b2o11b2o$83b3o19bo80b2o$83bo18b3o82bo$102bo81b3o$
184bo2$153b2o$147b2o5bo20b2o13b2o$147bobob3o21bobo11bobo$140b2o7bobo
25bo11bo$140b2o7b2o26b2o9b2o3$191b2o$192bo$189b3o19b2o21b2o$189bo20bob
o21b2o$196b2o12bo17b2o$197bo11b2o17b2o$194b3o$194bo$230b2o$223b2o5b2o$
223b2o5$89b2o$89b2o8$63bo$62bobo$62bobo$61b2ob2o16b2o$82b2o$61b2ob2o$
62bob2o34b2o$60bo39bobo$60b2o40bo$102b2o2$68b2o$62b2o4b2o$61bobo27b2o$
61bo29bobo$60b2o31bo$68b2o23b2o$68b2o$86b2o$82bo3b2o$74bo6bobo$73bobo
4bobo$74bo5bo$79b2o!""")
head2c3=pattern("8b2o$3bo2bo2bo$3b6o2$3b6o$2bo6bo$2bo2b5o$obobo$2o2bo$4bo$3b2o!")
body2c3=pattern("6bo$b6o$o$o2b6o$obo6bo$obo2b5o$b2obo$4bo$4bo$3b2o!")
tail2c3=pattern("5b2o$5b2o2$b6o$o5bo$o2b3o$obo$o2bo$b2o!")
wire2c3=head2c3(625,388) + tail2c3(2143,1905)
for i in range(631,2142,6): # 251 body segments
wire2c3+=body2c3(i,i-236) # first one at (631, 395)
receiver2c3=pattern("""
208bo$207bobo$208bo3$213b2o$188b2o23b2o$189bo31b2o$189bobo29bo$190b2o
27bobo$213b2o4b2o$213b2o2$179b2o$180bo40b2o$180bobo39bo$181b2o34b2obo$
217b2ob2o$199b2o$199b2o16b2ob2o$218bobo$218bobo$219bo8$192b2o$192b2o8$
55b2o$48b2o5b2o$48b2o$85bo$83b3o$50b2o17b2o11bo$50b2o17bo12b2o$44b2o
21bobo20bo$44b2o21b2o19b3o$87bo$87b2o3$90b2o9b2o26b2o7b2o$90bo11bo25bo
bo7b2o$88bobo11bobo21b3obobo$88b2o13b2o20bo5b2o39bo$125b2o45b3o$175bo
14bo$95bo78b2o12b3o$41bo51b3o91bo$41b3o48bo94b2o$44bo47b2o$43b2o$186b
2o$167b2o17b2o$167b2o3$61b2o$61bo$59bobo42b2o$59b2o43b2o11b2o51b2o$
117bo53bo$84b2o32b3o48bo$42b2o40bo35bo48b2o$42b2o15b2o24b3o85b2o$59bob
o25bo12b2o38b2o32bo$61bo38bo39bo30b3o$61b2o38b3o37b3o27bo$103bo39bo3$
42b2o$42bo$40bobo$40b2o4$57b2obo$57bob2o2$50b2o$50b2o122b2o$173bobo$
173bo29b2o$172b2o29bobo$205bo$178b2o25b2o$177bobo4b2o$40b2o135bo7bo$
41bo134b2o4b3o$41bobo138bo$42b2o146b2o$189bobo$189bo$188b2o$61bo$59b3o
$58bo$58b2o$206b2o$182bo23bobo$63b2o117b3o23bo$63b2o120bo22b2o$184b2o
14b2o$200b2o$73b2o$73bo$71bobo$71b2o$34b2o$33bobo$33bo$32b2o2$44b2o$
44b2o$160b2o7b2o30b2o$92b2o66b2o7bobo29bobo$92b2o45bo27bobob3o29bo$
139b3o25b2o5bo28b2o$142bo30b2o$90b2o49b2o$49b2o39b2o$48bobo26b2o43bo$
48bo29bo43b3o$47b2o29bobo44bo$79b2o43b2o11b2o$75b2o60b2o$75b2o4$177b2o
21b2o$66b2o108bobo21b2o$66bo109bo17b2o$64bobo21b2o85b2o17b2o$48b2o14b
2o22b2o$48b2o93b2o$52bo46b2o39b2o2bo2b2o47b2o$48b2o2b3o43bo2bo38b2obo
3bo41b2o5b2o$48b2o5bo42bobo23b2o17bobobo10b2o29b2o$54b2o43bo20bo3b2o
14b2obob2o12bo$119bobo12b2o4bo2bo12b3o$118bobo13b2o6b2o12bo$67b2o49bo$
66bobo48b2o$67bo$81b2o$81b2o4$47b2o$47b2o5$49bo$19b2o28b3o$12b2o5b2o
31bo92bo$12b2o37b2o90b3o11bo$47b2o93bo14b3o$47bo94b2o16bo14bo$14b2o33b
o109b2o12b3o$14b2o32b2o69bo52bo$8b2o109b3o50b2o$8b2o112bo$121b2o$171b
2o$152b2o17b2o$45b2o105b2o$45b2o17b2o$64b2o3$65b2o$65bo89b2o$52b2o12b
3o41bo23b2o20bo$35b2o16bo14bo40bobo22bo19bo$35bo14b3o57bo14b2o8b3o16b
2o$28bo7b3o11bo74bo11bo20b2o$26b3o9bo87b3o30bo$25bo102bo27b3o$25b2o
129bo$17b2o93b2o$17b2o92bobo$111bo$110b2o62b2o$126b2obo44bobo$126bob2o
46bo$176b2o$34b2o83b2o$34bo84b2o$32bobo$32b2o3$166b2o$166b2o2$157b2obo
$157bob2o2$36b2o$36bobo$38bo91b2o44b2o$38b2o90bo44bobo$28b2o98bobo44bo
$28b2o98b2o44b2o$9bob2o$9b2obo2$18b2o135b2o$18b2o136bo$156bobo$157b2o
15b2o$114b2o58b2o$114bo2b2o$115b2obo$116bo40b2o$28b2o86bobo4b2o31bobo$
28bo88b2o5bo31bo$26bobo94bo31b2o$26b2o68b2o25b2o$70bo25bo$58bo11b3o21b
obo$56b3o14bo20b2o$40bo14bo16b2o$40b3o12b2o70b2o44b2o$43bo58b2o24bo44b
o$4b2o36b2o59bo13b2o6b3o46b3o$5bo97bobo11b2o6bo50bo$5bobo96b2o$3b2ob2o
35b2o$2bobo38b2o17b2o$2bobo57b2o$b2ob2o20b2o$bo24bo$2bob2o18bobo108b2o
$obob2o18b2o109b2o$2o$59b2o32b2o$59bo20b2o11b2o$24b2o35bo19bo67b2o21b
2o$24bobo33b2o16b3o67bobo21b2o$26bo29b2o20bo53b2o14bo17b2o$26b3o27bo
75bo14b2o17b2o$29bo27b3o37b2o14b2o3b2o13bo$28b2o29bo38bo15bo3bo13b2o$
95b3o13b3o5b3o46b2o$95bo15bo9bo39b2o5b2o$161b2o4$18b2o$18b2o2$9b2o$10b
o$7b3o45b2o$7bo47b2o$15b2o32b2o$15bo33b2o$16bo$15b2o$51b2o$44b2o5b2o$
44b2o!""")
inserter2c3=pattern("""
51bo$49b3o$23b2o23bo$24bo23b2o$24bobo$25b2o2b2o37bo$29b2o35b3o15bo9bo$
65bo18b3o5b3o$52b2o11b2o20bo3bo$52b2o32b2o3b2o8$23b2o52b2o$22bobo16b2o
34b2o$22bo18bobo45b2o$21b2o20bo44bo2bo$37b2o4b2o44b2o4b2o$37bo2bo54bob
o$39b2o56bo$30b2o65b2o$30b2o20b2o33b2o$53bo34bo$50b3o32b3o$50bo34bo2$
19bo$19b3o$22bo$21b2o2$85b2o$85bo$86b3o$88bo2$40b2o$40bo$38bobo$38b2o
12$20b2o15b2o$19bobo15b2o$19bo$18b2o6$25bo$25b3o$28bo$27b2o28b2o$57bo$
55bobo$51b2o2b2o$51b2o4$50b2o4b2o$50b2o4b2o5$23b2o35bo$22bobo33b3o$22b
o34bo$21b2o34b2o$25b2o$25b2o3bo$29bobo6b2o$30bobo5b2o$32bo$32b2o$24b2o
$25bo$25bobo$26b2o2b2o$30b2o32b2o$64b2o4$59b2o$59b2o$63b2o$63b2o3$24b
2o31b2o$23bobo16b2o13b2o$23bo18bobo$22b2o20bo$38b2o4b2o$38bo2bo$40b2o$
31b2o$31b2o7$21b2o$22bo$22bobo$23b2o$39bo$37b3o$36bo$36b2o3$10b2o$10b
2o7$43b2o$43b2o4$38b2o$38b2o$2o40b2o$2o40b2o3$36b2o$21b2o13b2o$21bobo$
23bo$23b2o!""")
all=highway_robber(86,0) + connecting_neck(195,262) + transmitter2c3(347,219) \
+ wire2c3 + receiver2c3(2103,1763) + inserter2c3(2024,2042)
while g.numlayers()>1: g.dellayer()
all.display("Stable Pseudo-Heisenburp Device")
g.setmag(0)
setposint(120,200)
g.setname("Highway Robber")
g.clone()
g.setname("2c/3 Transmitter")
setposint(500,400)
g.clone()
g.setname("2c/3 Receiver")
setposint(2175,2000)
g.clone()
g.setname("Stable Pseudo-Heisenburp Device")
g.clone()
g.setname("Glider Fleet")
setposint(330,290)
# since the tiles change size depending on how many layers have been created,
# have to create all five layers before checking visibility of components --
# now go back and check that the critical areas are all visible:
g.setlayer(0)
while not g.visrect([100,100,150,175]): g.setmag(g.getmag()-1)
g.setlayer(1)
while not g.visrect([350,225,400,350]): g.setmag(g.getmag()-1)
g.setlayer(2)
while not g.visrect([2100,1750,225,300]): g.setmag(g.getmag()-1)
g.setlayer(3)
g.fit()
g.setlayer(4)
while not g.visrect([0,200,300,400]): g.setmag(g.getmag()-1)
g.update()
def putcells_and_fit(celllist):
g.putcells(celllist)
g.fit()
def CreateWssMovementData(recipes, dir, isUp=True):
result = []
for i in xrange(0, len(recipes.WssCreator)):
recipes.Reset()
if isUp:
recipes.Goto(-23, 1)
recipes.AddWss(i)
PlaceReadingHeads(recipes.recipe)
if isUp:
gen = period * (len(recipes.recipe) + 10)
while gen % (2 * distForward) != 0:
gen += 1
goto(gen)
g.fit()
g.update()
rect = g.getrect()
g.select([rect[0], -6 * distBack, rect[2], 7 * distBack])
g.clear(1)
x, y, res = FindWssByDirection(isUp, distForward)[0]
x += 23
y += -21
y = y % distForward
else:
gen = period * (len(recipes.recipe) + 10)
while gen % (2 * distBack) != 0:
gen += 1
goto(gen)
g.fit()
g.update()
rect = g.getrect()
helixy = CalcHelix(recipes.recipe)
g.select([rect[0], helixy - distBack, rect[2], 7 * distBack])
g.clear(1)
x, y, res = FindWssByDirection(isUp, distBack)[0]
y = y % distBack
result.append((x, y, res))
if isUp:
pickle.dump(
result,
open(
path.join(
dir,
str(step) + "_" + str(period) + "_ForwardWssBaseAuto.pkl"),
"wb"))
else:
pickle.dump(
result,
open(
path.join(
dir,
str(step) + "_" + str(period) +
"_BackwardWssBaseAuto.pkl"), "wb"))
recipes.Reset()
def display(self, title = "untitled", x = 0, y = 0, A = identity):
"""Paste pattern into new universe and display it all."""
golly.new(title)
golly.putcells(self, x, y, *A)
golly.fit()
golly.setcursor(zoomin)
def fit_if_not_visible(): # fit pattern in viewport if not empty and not completely visible r = rect(g.getrect()) if (not r.empty) and (not r.visible()): g.fit()
def CreateWssMovementData(recipes, dir, isUp = True): result = [] for i in xrange(0, len(recipes.WssCreator)): recipes.Reset() if isUp: recipes.Goto(-23, 1) recipes.AddWss(i) PlaceReadingHeads(recipes.recipe) if isUp: gen = period * (len(recipes.recipe) + 10) while gen % (2 * distForward) != 0: gen += 1 goto(gen) g.fit() g.update() rect = g.getrect() g.select([rect[0], -6 * distBack, rect[2], 7 * distBack]) g.clear(1) x, y, res = FindWssByDirection(isUp, distForward)[0] x += 23 y += -21 y = y % distForward else: gen = period * (len(recipes.recipe) + 10) while gen % (2 * distBack) != 0: gen += 1 goto(gen) g.fit() g.update() rect = g.getrect() helixy = CalcHelix(recipes.recipe) g.select([rect[0], helixy - distBack, rect[2], 7 * distBack]) g.clear(1) x, y, res = FindWssByDirection(isUp, distBack)[0] y = y % distBack result.append((x, y, res)) if isUp: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_ForwardWssBaseAuto.pkl"), "wb")) else: pickle.dump(result, open(path.join(dir, str(step) + "_" + str(period) + "_BackwardWssBaseAuto.pkl"), "wb")) recipes.Reset()
def export_icons(iconsection, rulename):
global multi_color_icons
if multi_color_icons:
# prepend a new @COLORS section with the average colors in each icon
iconsection = create_average_colors(iconsection) + iconsection
# replace any illegal filename chars with underscores
filename = rulename.replace("/","_").replace("\\","_")
# we will only create/update a .rule file in the user's rules folder
# (ie. we don't modify the supplied Rules folder)
rulepath = g.getdir("rules") + filename + ".rule"
fileexists = os.path.isfile(rulepath)
if fileexists:
# .rule file already exists so replace or add @ICONS section
rulefile = open(rulepath,"rU")
# create a temporary file for writing new rule info
temphdl, temppath = mkstemp()
tempfile = open(temppath,"w")
wroteicons = False
skiplines = False
for line in rulefile:
if line.startswith("@ICONS"):
# replace the existing @ICONS section
tempfile.write(iconsection)
wroteicons = True
skiplines = True
elif line.startswith("@COLORS") and multi_color_icons:
# skip the existing @COLORS section
# (iconsection contains a new @COLORS section)
skiplines = True
elif skiplines and line.startswith("@"):
if wroteicons: tempfile.write("\n")
skiplines = False
if not skiplines:
tempfile.write(line)
if not wroteicons:
# .rule file had no @ICONS section
tempfile.write("\n")
tempfile.write(iconsection)
# close files
rulefile.close()
tempfile.flush()
tempfile.close()
os.close(temphdl)
# remove original .rule file and rename temporary file
os.remove(rulepath)
move(temppath, rulepath)
else:
# .rule file doesn't exist so create it
rulefile = open(rulepath,"w")
rulefile.write("@RULE " + filename + "\n\n")
if not multi_color_icons:
# grayscale icons, so check if Rules/filename.rule exists
# and if so copy any existing @COLORS section
suppliedrule = g.getdir("app") + "Rules/" + filename + ".rule"
if os.path.isfile(suppliedrule):
colordata = get_color_section(suppliedrule)
if len(colordata) > 0:
rulefile.write(colordata)
rulefile.write(iconsection)
rulefile.flush()
rulefile.close()
# create another layer for displaying the new icons
if g.numlayers() < g.maxlayers():
g.addlayer()
g.new("icon test")
g.setrule(rulename)
for i in xrange(g.numstates()-1):
g.setcell(i, 0, i+1)
g.fit()
g.setoption("showicons",True)
g.update()
if fileexists:
g.note("Updated the icon data in " + rulepath)
else:
g.note("Created " + rulepath)
def prepare_burp():
highway_robber=pattern("""
143bo$143b3o$146bo$145b2o2$126bo42bo$126b3o38b3o$129bo36bo$128b2o11b2o
23b2o7b2o$141b2o32bo$108bo64bobo$108b3o6b2o54b2o$111bo5b2o$110b2o3$
111b2o$111b2o3b2o$116b2o35b2o23bo$154bo22bobo$151b3o8b2o14bo$151bo11bo
$98bo7bo53b3o$86bo11b3o5b3o51bo$84b3o14bo7bo32b2o$68bo14bo16b2o6b2o32b
obo30b2o$68b3o12b2o59bo30bobo$71bo72b2o31bo$70b2o105b2o$159bob2o$159b
2obo$71b2o$71b2o17b2o76b2o$90b2o76b2o5$104b2o$87b2o14bobo$87bo15bo74b
2o$88b3o11b2o74bo$90bo85bobo$84b2o90b2o$84bo$85b3o$87bo2$158b2o$159bo$
68b2o89bobo$67bobo90b2o$67bo25b2o$66b2o25bo$74b2o15bobo$74b2o15b2o98b
2o6bo$187bobo2bo4b3o$185b3ob2o5bo$184bo11b2o$185b3ob2o$177b2o8bob2o$
177b2o2$161b2o32b2o3b2o$161b2o32b2o3b2o$153b2o$88b2o2b2ob2o57bo18b2ob
2o$73b2o13bobo2bobo58bobo16b2obo$72bobo16b2o3bo58b2o21bo26bo$72bo19bob
2o76bob5o25bobo$71b2o16bo2bobo77b2o31bo$88bobobobo80b2o$89b2ob2o82bo$
173b3o$173bo33bo$171bobo31b3o$171b2o31bo$187b2o14bobo$187b2o15bo$83b2o
$83b2o$202b2o$202b2o2$175b2o$175b2o$72b2o123b2o$73bo19b2o102bo$73bobo
17bo76b2o26b3o$74b2o15bobo60b2o14b2o28bo$86bo4b2o62bo$85bobo64b3o$54bo
30bobo64bo$54b3o17b2o10bo$57bo15bobo$56b2o15bo116b2o$72b2o116bo$36b2o
49b2o102b3o$29b2o5b2o49bo105bo$29b2o57b3o6bo$90bo4b3o$94bo$31b2o17b2o
29b2o11b2o14b2o$31b2o17bo30b2o27b2o$25b2o21bobo$25b2o21b2o$116b2o$116b
2o36b2o$112b2o41bo$112b2o41bobo$156b2o$56b2o122b2o$56b2o11b2o109b2o$
69bo47b2o$70b3o44b2o$72bo2$22bo$22b3o55b2o96b2o$25bo53bobo96bo$24b2o
47b2o4bo99b3o$73b2o3b2o101bo$179b2o$76b4o99bo$75bo3bo97bobo$75b2o100b
2o$53b2o33bo22b2o$19b2o32b2o33b3o20bo$20bo70bo20b3o$20bobo67b2o22bo44b
o$21b2o136b3o$162bo$115bo45b2o$35b2o28b2o46b3o$35bobo27b2o45bo$37bo41b
2o6b2o23b2o$37b2o40b2o6bo2b2o$83b2o3b2obo$83b2o4bo89b2o$17bob2o68bo89b
o$17b2obo67b2obob2o18b2o62bobo$87bo2b2ob2o18bobo61b2o$26b2o60bo26bo$
26b2o33b2o26b3ob2o20b2o$60bo2bo27bobo66b2o$61bobo29bo66b2o15b2o$62bo
29b2ob2o80bobo$94bobo82bo$94bo84b2o$93b2o3$160b2o$160bo$158bobo$158b2o
2$16bo$16b3o$19bo33bo121b2obo$18b2o33b3o53b2o64bob2o$56bo52b2o$11bo43b
obo110b2o$11b3o42bo111b2o$14bo123bo$13b2o121b3o$57b2o19bo56bo$57b2o17b
3o19b2o20bo14b2o$75bo23bo19bobo$75b2o22bobo17bobo$100b2o15bobobobo34b
2o$10b2o19b2o79bo4b2o3b2o10bo24bo$10b2o19b2o47b2o29bobo19bobo23bobo$
80b2o29bobo19bobo24b2o$4bo95b2o10bo21bo4b2o$4b3o25b2o65bobo20b2o15bobo
$2o5bo24bo57b2o7bo21bobo17bo$bo4b2o25b3o54bo7b2o21bo19b2o36bo$bobo31bo
52bobo22b2o5b2o55b3o$2b2o29b2o53b2o23bo62bo$33bo17b2o61b3o28b2o29b2o$
31bobo4bo11bobo63bo28bo$31b2o3b3o11bo92bobo$35bo13b2o92b2o$35b2o94b2o$
61b2o68b2o$61b2o$b2o178b2o$b2o178bo$36b2o141bobo$36b2o141b2o3$27b2o37b
2o97b2o$27b2o36bobo51b2o43bobo$65bo54bo43bo$64b2o54bobo40b2o$121b2o2$
181b2obo$181bob2o2$40bo133b2o$38b3o133b2o$37bo$37b2o$138b2o$138b2o$42b
2o$42b2o78b2o$122b2o$114b2o$52b2o61bo18b2ob2o$52bo62bobo16b2obo$50bobo
63b2o21bo$50b2o81bob5o$13b2o118b2o$12bobo121b2o$12bo124bo$11b2o99bobo
19b3o$112b2obo18bo$23b2o90b3o$23b2o87b2o4bo$112bob5o$114bo$113bo3b2o$
108bo3bo3bobo$106b3o3b2o3bo$105bo$28b2o75b2o29b2o39b2o$27bobo106b2o38b
o2bo$27bo149b2o$26b2o2$131b2o$131b2o$135b2o$14b2o119b2o$14b2o35bo$49b
3o$48bo80b2o$48b2o63b2o14b2o$79bo33bo$68b2o7b3o34b3o$69bo6bo39bo$69bob
o4b2o$70b2o$109b2o$109bobo$111bo$111b2o7$103b2o$103bo$104b3o$106bo$13b
o19b2o$12bobo10b2o6bo5b2o41b2o$11bo2bo10bo8b3obobo41bo$12b2o9bobo10bob
o7b2o28b2obo3b3o$23b2o12b2o7b2o28b2ob4o2bo$82bo$64b2o6b2o2b2ob2o$63bob
o6bo4bobo$63bo9b4o2bo$62b2o7bobo2bobo$71b2o4bo!""")
connecting_neck=pattern("""
24bo$22b3o$21bo$21b2o$6b2o$7bo$7bobo$8b2o10bo$19bobo$19bobo$20bo4b2o$
8b2o15bobo$7bobo17bo$7bo19b2o$6b2o6$17b2o$17b2o7$23b2ob2o$22bobobobo$
5b2o16bo2bobo$6bo19bob2o$6bobo16b2o3bo$7b2o13bobo2bobo$22b2o2b2ob2o11$
8b2o15b2o$8b2o15bobo$2o25bo$bo25b2o$bobo$2b2o4$21bo107bo$19b3o106bobo$
18bo109bobo$18b2o106b3ob2o$24bo100bo$22b3o12bo84bo2b4ob2o$21bo15b3o82b
3o3bob2o$21b2o17bo84bo$39b2o83b2o26b2o$152bo$150bobo$150b2o2$24b2o$5b
2o17b2o76bo$5b2o95b3o6b2o$105bo5b2o41b2obo$104b2o48bob2o$4b2o$5bo141b
2o$2b3o12b2o86b2o40b2o$2bo14bo16b2o6b2o61b2o3b2o$18b3o14bo7bo66b2o$20b
o11b3o5b3o$32bo7bo$78bo51b2o3b2o$76b3o13bo38bo3bo$75bo16b3o33b3o5b3o$
50b2o23b2o18bo32bo9bo$45b2o3b2o42b2o42bobo$45b2o92b2o3$44b2o76b2o$45bo
5b2o69b2o$42b3o6b2o104b2o$42bo41b2o71bo$84b2o69bobo$61b2o92b2o$60bobo
62bo$60bo62b3o$59b2o10b2o49bo$72bo48bobo$69b3o9b2o39bo43b2o$69bo11bo
19b2o56b2o6bo$82bo17bobo56bo6bo$81b2o17bo19b2o35bobo6b2o$99b2o19b2o35b
2o$116b2o$116bo$117b3o24b2o$119bo23bobo$143bo25b2o$142b2o25b2o4$146b2o
$145bobo$145bo4b2o$144b2o5bo$148b3o5bo$148bo6bobo$156bo!""")
transmitter2c3=pattern("""
180b2o$180b2o$219bo$219b3o$178b2o42bo$116bo61b2o41b2o$115bobo47b2o99b
2o14bo$116bo49bo74b2o24bo14b3o$166bobo73bo13b2o6b3o18bo$167b2o73bobo
11b2o6bo19b2o12bo$110b2o51b2o78b2o53b3o$110b2o23b2o26b2o136bo$102b2o
31bo164b2o$103bo29bobo$103bobo27b2o$104b2o4b2o$110b2o162b2o$274b2o$
144b2o30b2o$102b2o40bo31b2o$102bo39bobo$104bob2o34b2o43b2o144b2o$103b
2ob2o78bo2bo143b2o$124b2o60bobo23b2o57b2o$103b2ob2o16b2o61bo20bo3b2o
57bo20b2o$104bobo100bobo26b2o14b2o3b2o13bo20bo$104bobo99bobo21b2o5bo
15bo3bo13b2o17b3o61b2o$105bo100bo23bobob3o13b3o5b3o29bo63b2o5b2o$205b
2o16b2o7bobo15bo9bo100b2o$223b2o7b2o152b2o6bo$169b2o125b2o84bobo2bo4b
3o$169b2o124bobo61b2o19b3ob2o5bo$295bo63b2o18bo11b2o$294b2o69b2o13b3ob
2o$365b2o15bob2o$131b2o151bo$131b2o149b3o12b2o$281bo16bo91b2o3b2o$271b
2o8b2o12b3o92b2o3b2o$272bo22bo$272bobo27b2o30b2o$273b2o28bo17b2o11b2o$
39bo82bo136bo27b2o11b3o19bo77bo$38bobo79b3o136b3o25b2o11bo18b3o77bobo$
39bo79bo142bo56bo80bo$108bo10b2o140b2o$37b5o65bobo228b2o$37bo4bo64bobo
177b2o50bo28b2o$40bo2bo61b3ob2o20bo155b2o47b3o29bo$12bo27b2obo60bo24b
3o204bo29bobo$12b3o10b2o10bo5bob2obo49bo6b3ob2o17bo104bo132b2o$15bo9b
2o9bobo4bobob2o49b3o6bob2o17b2o103b3o146b2o$4b2o8b2o20bo2bo2b2obo30b2o
23bo134bo145b2o$5bo31b2o6bo31bo6b2o14b2o133b2o11b2o13b2o$5bobo37b3o29b
obo4b2o39b2o121b2o13b2o$6b2o40bo23b2o4b2o44bo2bo87bo73b2o$47b2o23bobo
50b2o88b3o5b2o64bo$70bobob3o141bo4b2o62bobo$66b2o2b2o5bo139b2o68b2o81b
2o$4bob2o58b2o8b2o292b2o$2b3ob2o384b2o$bo216b2o172bo$2b3ob2o80b2o128b
2o3b2o123b2o15b2o26b3o$4bobo30b2o49b2o23b2o108b2o122bobo15b2o28bo$4bob
o30b2o74bo233bo$5bo108b3o229b2o$116bo77b2o7b2o$100b2o24b2o66b2o7bobo$
28b2o66bo3b2o24bo30b2o42bobob3o$28b2o65bobo29b3o2b2o24bo42b2o5bo40b2o
18b2obo112b2o$34b2o58bobo32bo3bo13b2o6b3o49b2o40bobo17bob2o112bo$34bo
19b2o38bo38bobo11b2o6bo95bo134b3o$30bo5bo16bobo37b2o24b2o13b2o115b2o
135bo$29bobo3b2o16bo65b2o164b2obo$30bo21b2o231bob2o$31b3o$33bo79b2o
163b2o$113b2o163b2o$117b2o46b2o$66b2o49b2o46b2o$66b2o$349b2o$350bo$71b
2o39b2o98b2o136bobo$70bobo39b2o99bo54b2o81b2o$70bo91b2o46b3o56bo105b2o
$69b2o91bo47bo58bobo103b2o$143b2o3b2o13bo106b2o$82b2o60bo3bo13b2o$82b
2o57b3o5b3o$141bo9bo40b2o$193bo$27bo162b3o180b2o$26bobo161bo182bo$26bo
2bo262b2o80b3o$27b2o263bo83bo$118b2o22bo147bobo81b2o$119bo20b3o99bo18b
o28b2ob2o79bo$116b3o20bo102b3o7b2o5b3o31bobo76bobo$116bo22b2o104bo6b2o
4bo34bobo76b2o$5b2o237b2o12b2o10b2o20b2ob2o$5b2o264bo24bo$9b2o104bo
155bobo18b2obo$9b2o104b3o139b2o13b2o18b2obobo56bo$23b2o93bo133b2o3b2o
37b2o56b3o$23b2o92b2o23b2o108b2o103bo$139b2o2bo212b2o28b2o$139bob2o71b
2o56b2o112bo$141bo71bobo55bobo110bobo$141bo71bo49bo7bo108b2o2b2o$116b
2o18b2obob2o69b2o47b3o5b3o108b2o$35b2o78bobo18b2ob2o2bo116bo7bo$35b2o
78bo26bo117b2o6b2o$13b2o99b2o20b2ob3o$14bo122bobo239b2o4b2o$11b3o123bo
241b2o4b2o$11bo90b2o30b2ob2o$102bo31bobo$100bobo5b2o26bo$99bobo6b2o26b
2o140b2o$95b2o3bo177b2o72b2o35bo$95b2o254bobo33b3o$20b2o69b2o194b2o62b
o34bo$21bo70bo194bo62b2o34b2o$18b3o71bobo193b3o63b2o$18bo74b2o195bo63b
2o3bo$233bo47b2o75bobo6b2o$233b3o46bo76bobo5b2o$236bo44bo79bo$235bobo
43b2o78b2o$120b2o4b2o108bo30bo$120b2o4b2o139b3o$270bo$237b2o30b2o8b2o
74bo$237b2o40bo61bo13b3o35b2o$121b2o154bobo59b3o16bo34b2o$121b2o2b2o
150b2o59bo18b2o$125bobo93bo41b2o73b2o$127bo92bobo40b2o26b2o$97b2o28b2o
91bobo68bo23bo72b2o$98bo119b3ob2o65bobo23b3o70b2o$95b3o119bo71b2o27bo
73b2o$95bo118bo2b4ob2o39b2o52b2o73b2o$214b3o3bob2o39b2o$217bo130b2o$
175bo40b2o26b2o102b2o36b2o$113b2o60b3o66bo126b2o13b2o$113bobo46b2o3b2o
9bo14b2o47bobo126bobo$77bo37bo2bo2bo40b2o3b2o8b2o15bo47b2o43b2o84bo$
77b3o35b7o71bo93b2o72b2o10b2o$80bo112b2o113b2o51bo$38b2o39b2o36b5o33b
2o151b2o41b2o9b3o$38b2o77bo4bo2b2o29bo174b2o19bo11bo$120bo2bo2bo29bobo
87b2obo81bobo17bo$120b2obobo31b2o87bob2o83bo17b2o$117bo5bob2o194b2o10b
2o$105b2o9bobo4bo72b2o41b2o80bo$105b2o9bo2bo2b2o72b2o41b2o70b2o9b3o$
117b2o193bo11bo$96b2obo211bo$96bob2o211b2o$160b2o$61b2o98bo60b2o3b2o$
61b2o8b2o85b3o28b2o32bo3bo$72bo85bo31bo15b2o12b3o5b3o29b2o$69b3o117bo
17bo12bo9bo28bobo$47b2o20bo119b2o13b3o23bobo26bo$48bo155bo26b2o25b2o
14b2o$10b2o33b3o70b2o153bo2bo$10b2o33bo29b2o41b2o154b2o$6bo50b2o15bobo
$6b3o48bo16bo98b2o$9bo48b3o12b2o98b2o54b2o$8b2o11bo38bo103b2o64bo$20bo
bo7b2o131bobo51b2o11bobo$20bobo7b2o44b2o85bo54bo12b2o$21bo55bo84b2o54b
obo$74b3o142b2o2b2o$74bo148b2o$81b2o34b2o$82bo34bobo$18b2o59b3o37bo$
18b2o59bo39b2o97b2o4b2o$4b2o212b2o4b2o$4b2o$2o$2o162bo$107bob2o3b2o48b
3o$105b3ob2o3bo52bo$104bo10b3o48b2o$105b3ob2o6bo101b2o$107b2o2bo106bob
o$110b2o106bo$217b2o2$164b2o$164b2o$188b2o$188bobo$190bo$24b2o164b2o$
23bobo$24bo4$132bo4b2o$131bobo2bobo7b2o$130bo2b4o9bo$26b2obo100bobo4bo
6bobo$26bob2o99b2ob2o2b2o6b2o$127bo$19b2o103bo2b4ob2o$19b2o103b3o3bob
2o$127bo40b2o$126b2o39bobo$52b2o103bo9bo$52b2o49b2o52b3o5b3o54b2o$104b
o55bo3bo57b2o$91bo11bo55b2o3b2o$9b2o39b2o39b3o9b2o$10bo39b2o42bo$10bob
o24b2o42b2o10b2o$11b2o25bo43bo150b2o$38bobo41bobo91b2o55bo$39b2o42b2o
91b2o53bobo$35b2o69b2o123b2o$35b2o69b2o75bob2o$29b2o152b2obo$29bo188b
2o$27bobo187bobo$27b2o109b2o77bo$132b2o4bobo75b2o$133bo6bo38b2o$48b2o
66b2o12b3o7b2o37bobo$48b2o47b2o18bo12bo50bo$97bo16b3o36b2o26b2o$59b2o
37b3o13bo39bo$58bo2bo38bo50b3o3bob2o59b2o$58bobo23b2o65bo2b4ob2o58bobo
$59bo20bo3b2o68bo64bo$79bobo73b3ob2o57b2o$7b2o69bobo76b2o2bo$7b2o17b2o
50bo81b2o84bo$26b2o49b2o165b3o$243bo$41b2o200b2o$41b2o2$219bo$219b3o$
222bo$221b2o23b2o$243b2o2bo$243bob2o$245bo$245bo$220b2o18b2obob2o$219b
obo18b2ob2o2bo$219bo26bo$218b2o20b2ob3o$241bobo$51bo189bo$12b2o35b3o
186b2ob2o$12b2o34bo189bobo$48b2o190bo$81bo158b2o$81b3o$17b2o65bo$17b2o
64b2o$13b2o$13b2o2$57b2o159b2o$19b2o36b2o158bobo$19b2o13b2o181bo$33bob
o180b2o$33bo181bo$32b2o10b2o74bo94b3o$45bo72b3o97bo$42b3o9b2o61bo99b2o
$42bo11bo20b2o40b2o17bo39bo$55bo20bo59b3o37b3o$54b2o17b3o63bo39bo$73bo
64b2o38b2o12bo$192b3o$159bo35bo19b2o$79b2o78b3o32b2o19b2o$78bobo81bo
76b2o$78bo82b2o11b2o63bobo$77b2o95b2o65bo$241b2o2$80b2o$81bo$78b3o$78b
o$85b2o30b2o$86bo17b2o11b2o$83b3o19bo80b2o$83bo18b3o82bo$102bo81b3o$
184bo2$153b2o$147b2o5bo20b2o13b2o$147bobob3o21bobo11bobo$140b2o7bobo
25bo11bo$140b2o7b2o26b2o9b2o3$191b2o$192bo$189b3o19b2o21b2o$189bo20bob
o21b2o$196b2o12bo17b2o$197bo11b2o17b2o$194b3o$194bo$230b2o$223b2o5b2o$
223b2o5$89b2o$89b2o8$63bo$62bobo$62bobo$61b2ob2o16b2o$82b2o$61b2ob2o$
62bob2o34b2o$60bo39bobo$60b2o40bo$102b2o2$68b2o$62b2o4b2o$61bobo27b2o$
61bo29bobo$60b2o31bo$68b2o23b2o$68b2o$86b2o$82bo3b2o$74bo6bobo$73bobo
4bobo$74bo5bo$79b2o!""")
head2c3=pattern("8b2o$3bo2bo2bo$3b6o2$3b6o$2bo6bo$2bo2b5o$obobo$2o2bo$4bo$3b2o!")
body2c3=pattern("6bo$b6o$o$o2b6o$obo6bo$obo2b5o$b2obo$4bo$4bo$3b2o!")
tail2c3=pattern("5b2o$5b2o2$b6o$o5bo$o2b3o$obo$o2bo$b2o!")
wire2c3=head2c3(625,388) + tail2c3(2143,1905)
for i in range(631,2142,6): # 251 body segments
wire2c3+=body2c3(i,i-236) # first one at (631, 395)
receiver2c3=pattern("""
208bo$207bobo$208bo3$213b2o$188b2o23b2o$189bo31b2o$189bobo29bo$190b2o
27bobo$213b2o4b2o$213b2o2$179b2o$180bo40b2o$180bobo39bo$181b2o34b2obo$
217b2ob2o$199b2o$199b2o16b2ob2o$218bobo$218bobo$219bo8$192b2o$192b2o8$
55b2o$48b2o5b2o$48b2o$85bo$83b3o$50b2o17b2o11bo$50b2o17bo12b2o$44b2o
21bobo20bo$44b2o21b2o19b3o$87bo$87b2o3$90b2o9b2o26b2o7b2o$90bo11bo25bo
bo7b2o$88bobo11bobo21b3obobo$88b2o13b2o20bo5b2o39bo$125b2o45b3o$175bo
14bo$95bo78b2o12b3o$41bo51b3o91bo$41b3o48bo94b2o$44bo47b2o$43b2o$186b
2o$167b2o17b2o$167b2o3$61b2o$61bo$59bobo42b2o$59b2o43b2o11b2o51b2o$
117bo53bo$84b2o32b3o48bo$42b2o40bo35bo48b2o$42b2o15b2o24b3o85b2o$59bob
o25bo12b2o38b2o32bo$61bo38bo39bo30b3o$61b2o38b3o37b3o27bo$103bo39bo3$
42b2o$42bo$40bobo$40b2o4$57b2obo$57bob2o2$50b2o$50b2o122b2o$173bobo$
173bo29b2o$172b2o29bobo$205bo$178b2o25b2o$177bobo4b2o$40b2o135bo7bo$
41bo134b2o4b3o$41bobo138bo$42b2o146b2o$189bobo$189bo$188b2o$61bo$59b3o
$58bo$58b2o$206b2o$182bo23bobo$63b2o117b3o23bo$63b2o120bo22b2o$184b2o
14b2o$200b2o$73b2o$73bo$71bobo$71b2o$34b2o$33bobo$33bo$32b2o2$44b2o$
44b2o$160b2o7b2o30b2o$92b2o66b2o7bobo29bobo$92b2o45bo27bobob3o29bo$
139b3o25b2o5bo28b2o$142bo30b2o$90b2o49b2o$49b2o39b2o$48bobo26b2o43bo$
48bo29bo43b3o$47b2o29bobo44bo$79b2o43b2o11b2o$75b2o60b2o$75b2o4$177b2o
21b2o$66b2o108bobo21b2o$66bo109bo17b2o$64bobo21b2o85b2o17b2o$48b2o14b
2o22b2o$48b2o93b2o$52bo46b2o39b2o2bo2b2o47b2o$48b2o2b3o43bo2bo38b2obo
3bo41b2o5b2o$48b2o5bo42bobo23b2o17bobobo10b2o29b2o$54b2o43bo20bo3b2o
14b2obob2o12bo$119bobo12b2o4bo2bo12b3o$118bobo13b2o6b2o12bo$67b2o49bo$
66bobo48b2o$67bo$81b2o$81b2o4$47b2o$47b2o5$49bo$19b2o28b3o$12b2o5b2o
31bo92bo$12b2o37b2o90b3o11bo$47b2o93bo14b3o$47bo94b2o16bo14bo$14b2o33b
o109b2o12b3o$14b2o32b2o69bo52bo$8b2o109b3o50b2o$8b2o112bo$121b2o$171b
2o$152b2o17b2o$45b2o105b2o$45b2o17b2o$64b2o3$65b2o$65bo89b2o$52b2o12b
3o41bo23b2o20bo$35b2o16bo14bo40bobo22bo19bo$35bo14b3o57bo14b2o8b3o16b
2o$28bo7b3o11bo74bo11bo20b2o$26b3o9bo87b3o30bo$25bo102bo27b3o$25b2o
129bo$17b2o93b2o$17b2o92bobo$111bo$110b2o62b2o$126b2obo44bobo$126bob2o
46bo$176b2o$34b2o83b2o$34bo84b2o$32bobo$32b2o3$166b2o$166b2o2$157b2obo
$157bob2o2$36b2o$36bobo$38bo91b2o44b2o$38b2o90bo44bobo$28b2o98bobo44bo
$28b2o98b2o44b2o$9bob2o$9b2obo2$18b2o135b2o$18b2o136bo$156bobo$157b2o
15b2o$114b2o58b2o$114bo2b2o$115b2obo$116bo40b2o$28b2o86bobo4b2o31bobo$
28bo88b2o5bo31bo$26bobo94bo31b2o$26b2o68b2o25b2o$70bo25bo$58bo11b3o21b
obo$56b3o14bo20b2o$40bo14bo16b2o$40b3o12b2o70b2o44b2o$43bo58b2o24bo44b
o$4b2o36b2o59bo13b2o6b3o46b3o$5bo97bobo11b2o6bo50bo$5bobo96b2o$3b2ob2o
35b2o$2bobo38b2o17b2o$2bobo57b2o$b2ob2o20b2o$bo24bo$2bob2o18bobo108b2o
$obob2o18b2o109b2o$2o$59b2o32b2o$59bo20b2o11b2o$24b2o35bo19bo67b2o21b
2o$24bobo33b2o16b3o67bobo21b2o$26bo29b2o20bo53b2o14bo17b2o$26b3o27bo
75bo14b2o17b2o$29bo27b3o37b2o14b2o3b2o13bo$28b2o29bo38bo15bo3bo13b2o$
95b3o13b3o5b3o46b2o$95bo15bo9bo39b2o5b2o$161b2o4$18b2o$18b2o2$9b2o$10b
o$7b3o45b2o$7bo47b2o$15b2o32b2o$15bo33b2o$16bo$15b2o$51b2o$44b2o5b2o$
44b2o!""")
inserter2c3=pattern("""
51bo$49b3o$23b2o23bo$24bo23b2o$24bobo$25b2o2b2o37bo$29b2o35b3o15bo9bo$
65bo18b3o5b3o$52b2o11b2o20bo3bo$52b2o32b2o3b2o8$23b2o52b2o$22bobo16b2o
34b2o$22bo18bobo45b2o$21b2o20bo44bo2bo$37b2o4b2o44b2o4b2o$37bo2bo54bob
o$39b2o56bo$30b2o65b2o$30b2o20b2o33b2o$53bo34bo$50b3o32b3o$50bo34bo2$
19bo$19b3o$22bo$21b2o2$85b2o$85bo$86b3o$88bo2$40b2o$40bo$38bobo$38b2o
12$20b2o15b2o$19bobo15b2o$19bo$18b2o6$25bo$25b3o$28bo$27b2o28b2o$57bo$
55bobo$51b2o2b2o$51b2o4$50b2o4b2o$50b2o4b2o5$23b2o35bo$22bobo33b3o$22b
o34bo$21b2o34b2o$25b2o$25b2o3bo$29bobo6b2o$30bobo5b2o$32bo$32b2o$24b2o
$25bo$25bobo$26b2o2b2o$30b2o32b2o$64b2o4$59b2o$59b2o$63b2o$63b2o3$24b
2o31b2o$23bobo16b2o13b2o$23bo18bobo$22b2o20bo$38b2o4b2o$38bo2bo$40b2o$
31b2o$31b2o7$21b2o$22bo$22bobo$23b2o$39bo$37b3o$36bo$36b2o3$10b2o$10b
2o7$43b2o$43b2o4$38b2o$38b2o$2o40b2o$2o40b2o3$36b2o$21b2o13b2o$21bobo$
23bo$23b2o!""")
all=highway_robber(86,0) + connecting_neck(195,262) + transmitter2c3(347,219) \
+ wire2c3 + receiver2c3(2103,1763) + inserter2c3(2024,2042)
while g.numlayers()>1: g.dellayer()
all.display("Stable Pseudo-Heisenburp Device")
g.setmag(0)
setposint(120,200)
g.setname("Highway Robber")
g.clone()
g.setname("2c/3 Transmitter")
setposint(500,400)
g.clone()
g.setname("2c/3 Receiver")
setposint(2175,2000)
g.clone()
g.setname("Stable Pseudo-Heisenburp Device")
g.clone()
g.setname("Glider Fleet")
setposint(330,290)
# since the tiles change size depending on how many layers have been created,
# have to create all five layers before checking visibility of components --
# now go back and check that the critical areas are all visible:
g.setlayer(0)
while not g.visrect([100,100,150,175]): g.setmag(g.getmag()-1)
g.setlayer(1)
while not g.visrect([350,225,400,350]): g.setmag(g.getmag()-1)
g.setlayer(2)
while not g.visrect([2100,1750,225,300]): g.setmag(g.getmag()-1)
g.setlayer(3)
g.fit()
g.setlayer(4)
while not g.visrect([0,200,300,400]): g.setmag(g.getmag()-1)
g.update()
important = important.split()[0:5]
commands.append((important[0], int(important[1]), int(important[2]),
important[3], important[4]))
pointer = [0, 0]
instruction_pointer = "start"
while True:
command = commands[[i[0] for i in commands].index(instruction_pointer)]
pointer = [pointer[0] + command[1], pointer[1] + command[2]]
x = pointer[0]
y = pointer[1]
print(command, pointer)
if golly.getcell(x, y):
golly.fit()
golly.exit()
else:
golly.setcell(x, y, 1)
neighbours = [
golly.getcell(x - 1, y),
golly.getcell(x + 1, y),
golly.getcell(x, y - 1),
golly.getcell(x, y + 1),
]
if any(neighbours):
instruction_pointer = command[3]
for state in range(n_states):
for color in range(n_colors):
bg_col = palette[color]
fg_col = palette[state+n_colors]
mid = [(f+b)/2 for f,b in zip(fg_col,bg_col)]
for row in range(15):
for column in range(15):
pixels[row][(encode(color,state)-1)*15+column] = [bg_col,fg_col,highlight,mid][icon15x15[row][column]]
for row in range(7):
for column in range(7):
pixels[15+row][(encode(color,state)-1)*15+column] = [bg_col,fg_col,highlight,mid][icon7x7[row][column]]
for color in range(n_colors):
bg_col = palette[color]
for row in range(15):
for column in range(15):
pixels[row][(color-1)*15+column] = bg_col
for row in range(7):
for column in range(7):
pixels[15+row][(color-1)*15+column] = bg_col
WriteBMP(pixels,golly.getdir('rules')+rule_name+'.icons')
# now we can switch to the new rule
golly.setalgo('RuleTree')
golly.setrule(rule_name)
golly.new(rule_name+'-demo.rle')
golly.setcell(0,0,encode(0,0)) # start with a single turmite
golly.fit()
golly.show('Created '+rule_name+'.tree and '+rule_name+'.icons, and selected this rule.')
t, twd, tht = color_text(
"%s size: %d x %d (%d cells)" % (label, r.wd, r.ht, totalcells),
extrastate)
t.put(0, -ylen - 15 - tht)
t, twd, tht = color_text("% FREQUENCY", extrastate)
t.put(-35 - tht, -(ylen - twd) / 2, rccw)
for perc in xrange(0, 101, 10):
t, twd, tht = color_text(str(perc), extrastate)
y = -perc * (ylen / 100)
t.put(-twd - 10, y - tht / 2)
### draw_line(-3, y, 0, y, extrastate)
# draw dotted horizontal line from 0 to xlen
for x in xrange(0, xlen, 2):
g.setcell(x, y, extrastate)
t, twd, tht = color_text("STATE", extrastate)
t.put((xlen - twd) / 2, 30)
for state in xrange(extrastate):
t, twd, tht = color_text(str(state), extrastate)
t.put(barwd * (state + 1) - barwd / 2 - twd / 2, 10)
draw_bar(state, extrastate)
# display result at scale 1:1
g.fit()
g.setmag(0)
g.show("")
def main ():
g.update ()
g.check (False)
path = g.getstring ("Output directory:")
files = glob.glob (os.path.join (path, "*.out"))
mingls = g.getstring ("Min number of gliders at accept:")
if mingls == "":
mingl = 0
minpop = 0
maxpop = 1024
else:
mingl = int (mingls)
minpops = g.getstring ("Min population except catalyzers:")
if minpops == "":
minpop = 0
maxpop = 1024
else:
minpop = int (minpops)
maxpop = int (g.getstring ("Max population except catalyzers:"))
if g.getname () != "catbellman_temp":
g.addlayer ()
hashdir = {}
catlist = []
catix = 0
g.new ("catbellman_temp")
g.setrule ("LifeBellman")
for fix, filename in enumerate (files):
patt = g.getrect ()
if patt != []:
g.select (patt)
g.clear (0)
g.setgen ("0")
with open(filename, 'r') as f:
filetext = f.read ()
if fix % 16 == 0:
g.show ("Analysing " + str (fix) + "/" + str (len (files)))
(gogen, glcnt) = convbellman (filetext, 0, 0)
if gogen == -1:
gogen = 128
(use, hash) = analyse (gogen, glcnt, minpop, maxpop, mingl)
if use:
if not hash in hashdir:
catlist.append ([])
hashdir [hash] = catix
catix += 1
cat = hashdir [hash]
catlist [cat].append (filetext)
g.new ("catbellman_temp")
g.setrule ("LifeBellman")
fix = 0
y = 0
for cat in catlist:
x = 96 * (len (cat) - 1)
for filetext in cat:
convbellman (filetext, x, y)
x -= 96
fix += 1
if fix % 32 == 0:
g.show ("Rendering " + str (fix) + "/" + str (len (files)))
g.fit ()
g.check (True)
g.update ()
g.check (False)
y += 96
g.show ("Done")
g.fit ()
g.setstep (-1)
g.check (True)
