def main(path):
# read the file
f = open(path)
line = f.readline() # throw away first line
# init the image
img = np.zeros((480, 640), np.uint8)
# find the range of the data
arange_min = 0
arange_max = 0
brange_min = 0
brange_max = 0
i = 0
try:
fd = open("test_data.pickle")
data, arange, brange = pickle.load(fd)
print "Loading pre-uniqueified data"
except:
print "Need to load the data"
print "Finding the range of the data"
data = None
if not (data):
# find the ranges
data = {}
for line in f:
elems = line.split(" ")
d = (ifm.from_fixed(int(elems[1],
2)), ifm.from_fixed(int(elems[2], 2)))
arange_min = min(arange_min, d[0])
arange_max = max(arange_min, d[0])
brange_min = min(brange_min, d[1])
brange_max = max(brange_min, d[1])
# writing once
data[d] = int(elems[3])
# count
i += 1
if i % 100000 == 0:
print i
arange = (arange_min, arange_max)
brange = (brange_min, brange_max)
# write out the ranges + data
fd = open("test_data.pickle", "w")
pickle.dump((data, arange, brange), fd)
print arange
print brange
# go through, line by line
print "Filling out the image"
for coord, count in data.iteritems():
# write out the data
x = round((coord[0] - arange[0]) / (arange[1] - arange[0]) * 640) % 640
y = round((coord[1] - brange[0]) / (brange[1] - brange[0]) * 480) % 480
img[y][x] = round((count / 127.0)**0.5 * 255.0)
# write out the file
im = Image.fromarray(img, mode="L")
im.save("ifm_test.png")
def main(path):
# read the file
f = open(path)
line = f.readline() # throw away first line
# init the image
img = np.zeros((480, 640), np.uint8)
# find the range of the data
arange_min = 0
arange_max = 0
brange_min = 0
brange_max = 0
i = 0
try:
fd = open("test_data.pickle")
data, arange, brange = pickle.load(fd)
print "Loading pre-uniqueified data"
except:
print "Need to load the data"
print "Finding the range of the data"
data = None
if not (data):
# find the ranges
data = {}
for line in f:
elems = line.split(" ")
d = (ifm.from_fixed(int(elems[1], 2)), ifm.from_fixed(int(elems[2], 2)))
arange_min = min(arange_min, d[0])
arange_max = max(arange_min, d[0])
brange_min = min(brange_min, d[1])
brange_max = max(brange_min, d[1])
# writing once
data[d] = int(elems[3])
# count
i += 1
if i % 100000 == 0:
print i
arange = (arange_min, arange_max)
brange = (brange_min, brange_max)
# write out the ranges + data
fd = open("test_data.pickle", "w")
pickle.dump((data, arange, brange), fd)
print arange
print brange
# go through, line by line
print "Filling out the image"
for coord, count in data.iteritems():
# write out the data
x = round((coord[0] - arange[0]) / (arange[1] - arange[0]) * 640) % 640
y = round((coord[1] - brange[0]) / (brange[1] - brange[0]) * 480) % 480
img[y][x] = round((count / 127.0) ** 0.5 * 255.0)
# write out the file
im = Image.fromarray(img, mode="L")
im.save("ifm_test.png")
if len(sys.argv) < 3:
print 'Usage "test_ifm [model_sim_outfile] [epsilon]"'
#read in file
filename = sys.argv[1]
f = open(filename, 'r')
epsilon = sys.argv[2]
#read constants from header
header = f.readline().split()
if len(header) < 3:
print 'Unparseable file header'
c_real = test_ifm_utils.from_fixed(int(header[1], 2))
c_img = test_ifm_utils.from_fixed(int(header[2], 2))
#create our floating point generator
j = JuliaSetGenerator(complex(c_real, c_img))
test_count = 0
wrong_count = 0
print "Commencing test"
print "---------------"
print ""
for line in f:
data = line.split()
if len(data) < 4:
print "Unparseable entry at line %s" % data[0]
if len(sys.argv) < 3: print 'Usage "test_ifm [model_sim_outfile] [epsilon]"' #read in file filename = sys.argv[1] f = open(filename, 'r') epsilon = sys.argv[2] #read constants from header header = f.readline().split() if len(header) < 3: print 'Unparseable file header' c_real = test_ifm_utils.from_fixed(int(header[1], 2)) c_img = test_ifm_utils.from_fixed(int(header[2], 2)) #create our floating point generator j = JuliaSetGenerator(complex(c_real, c_img)) test_count = 0 wrong_count = 0 print "Commencing test" print "---------------" print "" for line in f: data = line.split() if len(data) < 4: print "Unparseable entry at line %s"%data[0]