def lightmap(nm, cm, light, ambient):
width, height = nm.size
cwidth, cheight = cm.size
if cwidth != width or cheight != height:
print("Resolutions do not match.")
exit()
shaded = Image.new('RGBA', (width, height), color=(0, 0, 0, 0))
prog = ProgressBar(height)
print("\nLight Map:")
for y in range(0, height):
prog.show(y)
for x in range(0, width):
(cr, cg, cb, ca) = cm.getpixel((x, y))
(r, g, b, a) = nm.getpixel((x, y))
if a != 0:
normal = vmath.Vector3(\
(r/255 - 0.5) * 2,
(g/255 - 0.5) * 2,
(b/255 - 0.5) * 2)
angle = normal.angle(light, 'deg')
illumination = 1 - (angle / 180)
illumination = ambient + (1 - ambient) * illumination
cr = int(illumination * cr)
cg = int(illumination * cg)
cb = int(illumination * cb)
shaded.putpixel((x, y), (cr, cg, cb, ca))
return shaded
def colormap(hm, gradient, smoothness):
width, height = hm.size
img = Image.new('RGBA', (width, height), color=(0, 0, 0, 0))
colorlist = []
for g in range(len(gradient) - 1):
(start, color) = gradient[g]
(nextStart, nextColor) = gradient[g + 1]
begin = start * smoothness
end = (nextStart - start) * smoothness
sublist = list(Color(color).range_to(Color(nextColor), end))
colorlist += sublist
prog = ProgressBar(height)
print("\nColor Map:")
for y in range(0, height):
prog.show(y)
for x in range(0, width):
value = hm.getpixel((x, y))
if value != -2147483648:
setpixel(x, y, value, colorlist, img)
return img
def to_png(tif):
width, height = tif.size
img = Image.new('RGBA', (width, height), color=(0, 0, 0, 0))
prog = ProgressBar(height - 1)
print("\nTo PNG:")
for y in range(0, height - 1):
prog.show(y)
for x in range(0, width - 1):
value = tif.getpixel((x, y))
setpixel(x, y, value, img)
print("\n")
return img
def normalmap(hm, sobelscale):
width, height = hm.size
nm = Image.new('RGBA', (width, height), color=(0, 0, 0, 0))
prog = ProgressBar(height)
print("\nNormal Map:")
for y in range(0, height):
prog.show(y)
for x in range(0, width):
value = hm.getpixel((x, y))
if value != -2147483648:
normal = sobel(x, y, hm, sobelscale)
color = (\
int(normal.x * 255),
int(normal.y * 255),
int(normal.z * 255), 255)
nm.putpixel((x, y), color)
return nm
def projectmap(hm, scale):
width, height = hm.size
img = Image.new('I', (width, height), color=(-2147483648))
rwidth, rheight = img.size
R = rwidth / 6.1
prog = ProgressBar(height)
print("\nProjection Map:")
for y in range(0, height):
prog.show(y)
for x in range(0, width):
value = hm.getpixel((x, y))
(lat, long) = cylToLatLon(x - width / 2, y, scale)
(mapx, mapy) = robinson(lat, long, R)
img.putpixel((int(mapx + rwidth / 2), int(mapy + rheight / 2)),
value)
return img
def heightmap(hm, scale):
SCALER = scale
width, height = hm.size
img = Image.new('I', (width // SCALER, height // SCALER), color='red')
prog = ProgressBar(height)
print("\nHeight Map:")
for y in range(0, height, SCALER):
prog.show(y)
for x in range(0, width // 2, SCALER):
value = hm.getpixel((x, y))
rightVal = hm.getpixel((x + width // 2, y))
try:
img.putpixel((x // SCALER * 2, y // SCALER), value)
img.putpixel((x // SCALER * 2 + 1, y // SCALER), rightVal)
except IndexError:
pass
return img
## Initialize Happiness dictionary
print "INITIALIZE DATA..."
CHILD_PREF = pd.read_csv('../input/child_wishlist_v2.csv',
header=None).drop(0, 1).values
GIFT_PREF = pd.read_csv('../input/gift_goodkids_v2.csv',
header=None).drop(0, 1).values
'''
==========================
Here we build a dictionary to compute single scores for all three types of children
'''
print "INITIALIZE GIFT HAPPINESS..."
GIFT_HAPPINESS = {}
pbar.setBar(N_GIFT_TYPE)
for g in range(N_GIFT_TYPE):
pbar.show(g)
GIFT_HAPPINESS[g] = defaultdict(lambda: -1. / (2 * N_GIFT_PREF))
for i, c in enumerate(GIFT_PREF[g]):
GIFT_HAPPINESS[g][c] = 1. * (N_GIFT_PREF - i) / N_GIFT_PREF
print "INITIALIZE CHILD HAPPINESS..."
CHILD_HAPPINESS = {}
pbar.setBar(N_CHILDREN)
for c in range(N_CHILDREN):
pbar.show(c)
CHILD_HAPPINESS[c] = defaultdict(lambda: -1. / (2 * N_CHILD_PREF))
for i, g in enumerate(CHILD_PREF[c]):
CHILD_HAPPINESS[c][g] = 1. * (N_CHILD_PREF - i) / N_CHILD_PREF
'''
==========================
Here we build a 2D hash_table to compute single scores for all the triplets
neighbor = ""
lc = 0
# open input+output file
fh = open(sopts.inputfile, 'r')
fhout = open(sopts.outputfile, 'w') # rewrite
fhout.write("timestamp,neighbor,capabilities,mrr_T,mrr_t,mrr_P,rate,throughput,ewma_prob,this_prob,this_succ,this_attempt,success,attempts\n")
linebuffer = []
headers = False
t0 = time()
print "getting length of file... ",
numlines = get_num_lines(sopts.inputfile)
if (numlines > -1):
print "%d lines" % numlines
progress = ProgressBar(50)
progress.show(0)
else:
print "failed"
while (main_loop):
try:
filepos = fh.tell() # remember position before reading
line = fh.readline()
if ((not "\n" in line) and (line != '')):
fh.seek(filepos)
else:
if (line != ''):
lc += 1
if (lc % 10000 == 0 and numlines > -1):
duration = (time() - t0)
t0 = time()
