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# Run the current pattern for a given number of steps (using current
# step size) and create a plot of population vs time in separate layer.
# Author: Andrew Trevorrow (andrew@trevorrow.com), May 2007.
import golly as g
from glife import getminbox, rect, rccw
from glife.text import make_text
from time import time
# --------------------------------------------------------------------
# size of plot
xlen = 500 # length of x axis
ylen = 500 # length of y axis
# --------------------------------------------------------------------
# draw a line of cells from x1,y1 to x2,y2 using Bresenham's algorithm
def draw_line(x1, y1, x2, y2):
g.setcell(x1, y1, 1)
if x1 == x2 and y1 == y2: return
dx = x2 - x1
ax = abs(dx) * 2
sx = 1
if dx < 0: sx = -1
dy = y2 - y1
ay = abs(dy) * 2
sy = 1
if dy < 0: sy = -1
if ax > ay:
d = ay - (ax / 2)
while x1 != x2:
g.setcell(x1, y1, 1)
if d >= 0:
y1 += sy
d -= ax
x1 += sx
d += ay
else:
d = ax - (ay / 2)
while y1 != y2:
g.setcell(x1, y1, 1)
if d >= 0:
x1 += sx
d -= ay
y1 += sy
d += ax
g.setcell(x2, y2, 1)
# --------------------------------------------------------------------
# fit pattern in viewport if not empty and not completely visible
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()
# --------------------------------------------------------------------
if g.empty(): g.exit("There is no pattern.")
# check that a layer is available for population plot
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.")
# prompt user for number of steps
numsteps = xlen
s = g.getstring("Enter the number of steps:",
str(numsteps), "Population plotter")
if len(s) > 0: numsteps = int(s)
if numsteps <= 0: g.exit()
# generate pattern for given number of steps
poplist = [ int(g.getpop()) ]
genlist = [ int(g.getgen()) ]
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])
deadr, deadg, deadb = g.getcolor("deadcells")
if (deadr + deadg + deadb) / 3 > 128:
# use black if light background
g.setcolors([1,0,0,0])
else:
# use white if dark background
g.setcolors([1,255,255,255])
minpop = min(poplist)
maxpop = max(poplist)
if minpop == maxpop:
# avoid division by zero
minpop -= 1
popscale = float(maxpop - minpop) / float(ylen)
mingen = min(genlist)
maxgen = max(genlist)
genscale = float(maxgen - mingen) / float(xlen)
# draw axes with origin at 0,0
draw_line(0, 0, xlen, 0)
draw_line(0, 0, 0, -ylen)
# add annotation using mono-spaced ASCII font
t = make_text(pattname.upper(), "mono")
bbox = getminbox(t)
t.put((xlen - bbox.wd) / 2, -ylen - 10 - bbox.ht)
t = make_text("POPULATION", "mono")
bbox = getminbox(t)
t.put(-10 - bbox.ht, -(ylen - bbox.wd) / 2, rccw)
t = make_text(str(minpop), "mono")
bbox = getminbox(t)
t.put(-bbox.wd - 10, -bbox.ht / 2)
t = make_text(str(maxpop), "mono")
bbox = getminbox(t)
t.put(-bbox.wd - 10, -ylen - bbox.ht / 2)
t = make_text("GENERATION (step=%s)" % stepsize, "mono")
bbox = getminbox(t)
t.put((xlen - bbox.wd) / 2, 10)
t = make_text(str(mingen), "mono")
bbox = getminbox(t)
t.put(-bbox.wd / 2, 10)
t = make_text(str(maxgen), "mono")
bbox = getminbox(t)
t.put(xlen - bbox.wd / 2, 10)
# display result at scale 1:1
g.fit()
g.setmag(0)
g.show("")
# plot the data (do last because it could take a while if numsteps is huge)
x = int(float(genlist[0] - mingen) / genscale)
y = int(float(poplist[0] - minpop) / popscale)
oldsecs = time()
for i in xrange(numsteps):
newx = int(float(genlist[i+1] - mingen) / genscale)
newy = int(float(poplist[i+1] - minpop) / popscale)
draw_line(x, -y, newx, -newy)
x = newx
y = newy
newsecs = time()
if newsecs - oldsecs >= 1.0: # update plot every second
oldsecs = newsecs
g.update()
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