def test_multiply_operation_sparse_input_fakeghost_four(self):
print("\n test_multiply_operation_sparse_input_fakeghost_four...")
v_output = vc.multiply(input_svar,
scalar=5,
fakeghost=4,
make_float32=False)
d_output = input_svar * 5
msgs = "test_multiply_operation_sparse_input_fakeghost_four"
self.assertTrue((d_output == v_output).all(), msg=msgs)
def test_multiply_operation_sparse_input_blocks_ten(self):
print("\n test_multiply_operation_sparse_input_blocks_ten...")
v_output = vc.multiply(input_svar,
scalar=5,
no_of_blocks=10,
make_float32=False)
d_output = input_svar * 5
msgs = "test_multiply_operation_sparse_input_blocks_ten"
self.assertTrue((d_output == v_output).all(), msg=msgs)
def test_multiply_operation_dense_input_fakeghost_one(self):
print("\n test_multiply_operation_dense_input_fakeghost_one...")
v_output = vc.multiply(input_dvar,
scalar=5,
fakeghost=1,
make_float32=False)
d_output = input_dvar * 5
msgs = "test_multiply_operation_dense_input_fakeghost_one"
self.assertTrue((d_output == v_output).all(), msg=msgs)
def __test_multiply_operation(self,input_var):
print("\n multiply Voxel testing...")
start_time = t.time()
v_output = vc.multiply(input_var,scalar=5,no_of_blocks=PL[0],fakeghost=PL[1],make_float32=False)
print("multiply Voxel testing time taken: ",(t.time() - start_time)," sec")
#print("\n multiply Default testing...")
start_time = t.time()
d_output = input_var*5
print("multiply Default testing time taken: ",(t.time() - start_time)," sec")
msgs = "multiply_operation_FAIL_with parameters: scalar=5, ",PL
self.assertTrue((d_output==v_output).all(), msg=msgs)
d = ndimage.white_tophat(input_var,
size=None,
footprint=None,
structure=structure,
output=None,
mode='reflect',
cval=0.0,
origin=0)
print("scipy white_tophat: ", (t.time() - start_time), " sec")
print("\nresult: ", (d == output).all())
#16.multiply..............
print("\nmultiply VoxelProcessing")
start_time = t.time()
output = vc.multiply(input_var,
make_float32=False,
no_of_blocks=7,
fakeghost=2,
scalar=10)
print("vc multiply: ", (t.time() - start_time), " sec")
print("\nmultiply Default")
start_time = t.time()
d = input_var * 10
print("scipy multiply: ", (t.time() - start_time), " sec")
print("\nresult: ", (d == output).all())
# # print(output[134][156][98])
# # print(d[134][156][98])
# # t = np.setdiff1d(output, d)
# # print(len(t))
def test_multiply_operation_sparse_input_scalar_float(self):
print("\n test_multiply_operation_sparse_input_scalar_float...")
v_output = vc.multiply(input_svar, scalar=5.5, make_float32=False)
d_output = input_svar * 5.5
msgs = "test_multiply_operation_sparse_input_scalar_float"
self.assertTrue((d_output == v_output).all(), msg=msgs)
size=None,
footprint=None,
structure=structure,
output=None,
mode='reflect',
cval=0.0,
origin=0)
#15
output_var = vc.white_tophat(input_var,
no_of_blocks=4,
fakeghost=2,
make_float32=True,
size=None,
footprint=None,
structure=structure,
output=None,
mode='reflect',
cval=0.0,
origin=0)
#16
output_var = vc.multiply(input_var,
no_of_blocks=4,
fakeghost=2,
make_float32=True,
scalar=1)
#17
output_var = vc.nothing(input_var,
no_of_blocks=4,
fakeghost=2,
make_float32=True)