def generate(surf, num_beams, num_rays, out_filename):
t = np.linspace(0., 1., NSTEPS)
filedir = path.dirname(out_filename)
if not path.exists(filedir):
makedirs(filedir)
if path.exists(out_filename
) and path.getmtime(out_filename) > path.getmtime(__file__):
print("Dataset is up to date, skipping.")
return
with open(out_filename, 'w') as out_file:
out_file.write('diff ' + str(num_beams * num_rays) + '\n')
rays = 0
for pivotPhi in np.linspace(-PHIRANGE / 2, PHIRANGE / 2, num_beams):
ax, ay = from_polar(RMIN, pivotPhi)
for dstPhi in np.linspace(-PHIRANGE / 2, PHIRANGE / 2, num_rays):
rays += 1
update_progress(rays * 100 / num_beams / num_rays)
bx, by = from_polar(RMAX, dstPhi)
func = np.vectorize(lambda x: surf(x * ax + (1 - x) * bx, x *
ay + (1 - x) * by))
result = np.trapz(func(t), t) * sqrt((ax - bx)**2 +
(ay - by)**2)
out_file.write(str(ax) + ' ' + str(ay) + ' ')
out_file.write(str(bx) + ' ' + str(by) + ' ')
out_file.write(str(result) + '\n')
def main():
datafiles = [
path.join('./data', f) for f in os.listdir('./data')
if path.isfile(path.join('./data', f))
]
pool = Pool()
completedTasks = 0
totalTasks = 0
def mp_callback(task):
nonlocal totalTasks, completedTasks
completedTasks += 1
update_progress(completedTasks / totalTasks * 100)
job_start = time.time()
print('Generating jobs...')
for datafile in datafiles:
prefix = 'out/' + path.splitext(path.basename(datafile))[0] + '/'
if not path.exists(prefix):
os.makedirs(prefix)
for solverType in ['ART', 'SIRT']:
solver_flag = ['--solver=' + solverType]
for name, cfg in config.items():
outname = prefix + solverType + '-' + name + '.png'
if path.exists(outname):
continue
totalTasks += 1
#reconstruct(datafile, solver_flag + cfg, outname)
pool.apply_async(reconstruct,
args=(datafile, solver_flag + cfg, outname),
callback=mp_callback)
print('Generated ' + str(totalTasks) + ' jobs.')
update_progress(0)
pool.close()
pool.join()
if totalTasks == 0: update_progress(100)
job_end = time.time()
print('Took {0:1f}s'.format(job_end - job_start))
def main():
datafiles = [path.join('./data', f) for f in os.listdir('./data') if path.isfile(path.join('./data', f))]
pool = Pool()
completedTasks = 0
totalTasks = 0
def mp_callback(task):
nonlocal totalTasks, completedTasks
completedTasks += 1
update_progress(completedTasks / totalTasks * 100)
job_start = time.time()
print('Generating jobs...')
for datafile in datafiles:
prefix = 'out/' + path.splitext(path.basename(datafile))[0] + '/'
if not path.exists(prefix):
os.makedirs(prefix)
for solverType in ['ART', 'SIRT']:
solver_flag = ['--solver=' + solverType]
for name, cfg in config.items():
outname = prefix + solverType + '-' + name + '.png'
if path.exists(outname):
continue
totalTasks += 1
#reconstruct(datafile, solver_flag + cfg, outname)
pool.apply_async(reconstruct, args = (datafile, solver_flag + cfg, outname), callback = mp_callback)
print('Generated ' + str(totalTasks) + ' jobs.')
update_progress(0)
pool.close()
pool.join()
if totalTasks == 0: update_progress(100)
job_end = time.time()
print('Took {0:1f}s'.format(job_end - job_start))
def generate(surf, num_beams, num_rays, out_filename):
t = np.linspace(0., 1., NSTEPS)
filedir = path.dirname(out_filename)
if not path.exists(filedir):
makedirs(filedir)
if path.exists(out_filename) and path.getmtime(out_filename) > path.getmtime(__file__):
print("Dataset is up to date, skipping.")
return
with open(out_filename, 'w') as out_file:
out_file.write('diff ' + str(num_beams * num_rays) + '\n')
rays = 0
for pivotPhi in np.linspace(-PHIRANGE / 2, PHIRANGE / 2, num_beams):
ax, ay = from_polar(RMIN, pivotPhi)
for dstPhi in np.linspace(-PHIRANGE / 2, PHIRANGE / 2, num_rays):
rays += 1
update_progress(rays * 100 / num_beams / num_rays)
bx, by = from_polar(RMAX, dstPhi)
func = np.vectorize(lambda x: surf(x * ax + (1 - x) * bx, x * ay + (1 - x) * by))
result = np.trapz(func(t), t) * sqrt((ax - bx) ** 2 + (ay - by) ** 2)
out_file.write(str(ax) + ' ' + str(ay) + ' ')
out_file.write(str(bx) + ' ' + str(by) + ' ')
out_file.write(str(result) + '\n')
def mp_callback(task):
nonlocal totalTasks, completedTasks
completedTasks += 1
update_progress(completedTasks / totalTasks * 100)
def mp_callback(task):
nonlocal totalTasks, completedTasks
completedTasks += 1
update_progress(completedTasks / totalTasks * 100)
