setDebugLevel(1)
if not basePath.endswith("/"): basePath = basePath + "/"
if savenpz or saveuni or saveppm:
folderNo = simNo
simPath, simNo = ph.getNextSimPath(simNo, basePath)
# add some more info for json file
ph.paramDict["simNo"] = simNo
ph.paramDict["type"] = "smoke"
ph.paramDict["name"] = "gen6combined"
ph.paramDict["version"] = printBuildInfo()
ph.paramDict["creation_date"] = datetime.now().strftime(
"%Y-%m-%d %H:%M:%S")
ph.writeParams(simPath + "description.json") # export sim parameters
sys.stdout = ph.Logger(simPath)
print("Called on machine '" + os.uname()[1] + "' with: " +
str(" ".join(sys.argv)))
print("Saving to " + simPath + ", " + str(simNo))
# optional , backupFile(__file__, simPath)
if (npSeed < 0):
npSeed = np.random.randint(0, 2**32 - 1)
print("Random seed %d" % npSeed)
np.random.seed(npSeed)
# Init solvers -------------------------------------------------------------------#
sm_gs = vec3(res, res, res)
xl_gs = sm_gs * float(scaleFactor)
out_path_prefix, 0, basePath + 'test_%04d/' % load_model_test)
else:
test_path, load_model_test_new = ph.getNextTestPath(
testPathStartNo, basePath)
else:
test_path, load_model_test_new = ph.getNextTestPath(
testPathStartNo, basePath)
# logging & info
sys.stdout = ph.Logger(test_path)
print('Note: {}'.format(note))
print("\nCalled on machine '" + os.uname()[1] + "' with: " +
str(" ".join(sys.argv)))
print("\nUsing parameters:\n" + ph.paramsToString())
ph.writeParams(test_path +
"params.json") # export parameters in human readable format
if outputOnly:
print('*****OUTPUT ONLY*****')
# ---------------------------------------------
# TENSORFLOW SETUP
import scipy.misc
def save_img(out_path, img):
img = np.clip(img * 255.0, 0, 255).astype(np.uint8)
scipy.misc.imsave(out_path, img)
