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Updates for python3 #13

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Updates for python3 #13

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22 changes: 12 additions & 10 deletions pywrapper/setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
from Cython.Distutils import build_ext
import numpy, os, platform, sys
from os.path import join as pjoin
import six


# Obtain the numpy include directory. This logic works across numpy versions.
Expand All @@ -18,10 +19,10 @@ def check_for_flag(flag_str, truemsg=False, falsemsg=False):
enabled = False

if enabled and not truemsg == False:
print truemsg
print(truemsg)
elif not enabled and not falsemsg == False:
print falsemsg
print " $ sudo "+flag_str+"=ON python setup.py install"
print(falsemsg)
print(" $ sudo "+flag_str+"=ON python setup.py install")
return enabled

use_cuda = check_for_flag("WITH_CUDA", \
Expand All @@ -31,9 +32,9 @@ def check_for_flag(flag_str, truemsg=False, falsemsg=False):
"Compiling with trace enabled for Bresenham's Line", \
"Compiling without trace enabled for Bresenham's Line")

print
print "--------------"
print
print()
print("--------------")
print()

# support for compiling in clang
if platform.system().lower() == "darwin":
Expand Down Expand Up @@ -62,10 +63,10 @@ def locate_cuda():
# print os.environ
# first check if the CUDAHOME env variable is in use
if os.path.isdir("/usr/local/cuda-7.5"):
home = "/usr/local/cuda-7.5"
home = "/usr/local/cuda-7.5"
nvcc = pjoin(home, 'bin', 'nvcc')
elif os.path.isdir("/usr/local/cuda"):
home = "/usr/local/cuda"
home = "/usr/local/cuda"
nvcc = pjoin(home, 'bin', 'nvcc')
elif 'CUDAHOME' in os.environ:
home = os.environ['CUDAHOME']
Expand All @@ -81,7 +82,8 @@ def locate_cuda():
cudaconfig = {'home':home, 'nvcc':nvcc,
'include': pjoin(home, 'include'),
'lib64': pjoin(home, 'lib64')}
for k, v in cudaconfig.iteritems():

for k, v in six.iteritems(cudaconfig):
if not os.path.exists(v):
raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))

Expand All @@ -93,7 +95,7 @@ def locate_cuda():

# compiler_flags = ["-w","-std=c++11", "-march=native", "-ffast-math", "-fno-math-errno"]
compiler_flags = ["-w","-std=c++11", "-march=native", "-ffast-math", "-fno-math-errno", "-O3"]
nvcc_flags = ['-arch=sm_20', '--ptxas-options=-v', '-c', '--compiler-options', "'-fPIC'", "-w","-std=c++11"]
nvcc_flags = ['-arch=sm_61', '--ptxas-options=-v', '-c', '--compiler-options', "'-fPIC'", "-w","-std=c++11"]
include_dirs = ["../", numpy_include]
depends = ["../includes/*.h"]
sources = ["RangeLibc.pyx","../vendor/lodepng/lodepng.cpp"]
Expand Down
33 changes: 16 additions & 17 deletions pywrapper/test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,8 +27,8 @@
# print range_libc.USE_LRU_CACHE
# print range_libc.LRU_CACHE_SIZE

# testMap = range_libc.PyOMap("../maps/basement_hallways_5cm.png",1)
testMap = range_libc.PyOMap("../maps/synthetic.map.png",1)
# testMap = range_libc.PyOMap(b"../maps/basement_hallways_5cm.png",1)
testMap = range_libc.PyOMap(b"../maps/synthetic.map.png",1)
# testMap = range_libc.PyOMap("/home/racecar/racecar-ws/src/TA_examples/lab5/maps/basement.png",1)

if testMap.error():
Expand Down Expand Up @@ -56,19 +56,19 @@

# make_scan(510,520,np.pi/2.0,61)

print "Init: bl"
print("Init: bl")
bl = range_libc.PyBresenhamsLine(testMap, 500)
print "Init: rm"
print("Init: rm")
rm = range_libc.PyRayMarching(testMap, 500)
print "Init: cddt"
print("Init: cddt")
cddt = range_libc.PyCDDTCast(testMap, 500, 108)
cddt.prune()
print "Init: glt"
print("Init: glt")
glt = range_libc.PyGiantLUTCast(testMap, 500, 108)
# this is for testing the amount of raw functional call overhead, does not compute ranges
# null = range_libc.PyNull(testMap, 500, 108)

for x in xrange(10):
for x in range(10):
vals = np.random.random((3,num_vals)).astype(np.float32)
vals[0,:] *= (testMap.width() - 2.0)
vals[1,:] *= (testMap.height() - 2.0)
Expand All @@ -78,28 +78,27 @@
ranges = np.zeros(num_vals, dtype=np.float32)

test_states = [None]*num_vals
for i in xrange(num_vals):
for i in range(num_vals):
test_states[i] = (vals[0,i], vals[1,i], vals[2,i])

def bench(obj,name):
print "Running:", name
print("Running:", name)
start = time.clock()
obj.calc_range_many(vals, ranges)
end = time.clock()
dur_np = end - start
print ",,,"+name+" np: finished computing", ranges.shape[0], "ranges in", dur_np, "sec"
print(",,,"+name+" np: finished computing", ranges.shape[0], "ranges in", dur_np, "sec")
start = time.clock()
ranges_slow = map(lambda x: obj.calc_range(*x), test_states)
ranges_slow = [*map(lambda x: obj.calc_range(*x), test_states)]
end = time.clock()
dur = end - start

diff = np.linalg.norm(ranges - np.array(ranges_slow))
diff = np.linalg.norm(np.array(ranges) - np.array(ranges_slow))
if diff > 0.001:
print ",,,"+"Numpy result different from slow result, investigation possibly required. norm:", diff
print(",,,"+"Numpy result different from slow result, investigation possibly required. norm:", diff)
# print "DIFF:", diff

print ",,,"+name+": finished computing", ranges.shape[0], "ranges in", dur, "sec"
print ",,,"+"Numpy speedup:", dur/dur_np
print(",,,"+name+": finished computing", ranges.shape[0], "ranges in", dur, "sec")
print(",,,"+"Numpy speedup:", dur/dur_np)

bench(bl, "bl")
bench(rm, "rm")
Expand Down Expand Up @@ -129,4 +128,4 @@ def bench(obj,name):

# this is for testing the amount of raw functional call overhead, does not compute ranges
# bench(null, "null")
print "DONE"
print("DONE")