57d419c21650c6bad57ba7ac6b3b14a219b16a3a,qucumber/complex_wavefunction.py,ComplexWavefunction,generate_hilbert_space,#ComplexWavefunction#Any#,227
Before Change
device=self.device, dtype=torch.double)
for i in range(1 << size):
d = i
for j in range(size):
d, r = divmod(d, 2)
space[i, size - j - 1] = int(r)
return space
def compute_normalization(self):
rCompute the normalization constant of the wavefunction.
After Change
if (size > self.size_cut):
raise ValueError("Size of the Hilbert space too large!")
else:
d = np.arange(2 ** size)
space = (((d[:, None] & (1 << np.arange(size)))) > 0)[:, ::-1]
space = space.astype(int)
return torch.tensor(space, dtype=torch.double, device=self.device)
def compute_normalization(self):
rCompute the normalization constant of the wavefunction.
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 9
Instances
Project Name: PIQuIL/QuCumber
Commit Name: 57d419c21650c6bad57ba7ac6b3b14a219b16a3a
Time: 2018-08-09
Author: emerali@users.noreply.github.com
File Name: qucumber/complex_wavefunction.py
Class Name: ComplexWavefunction
Method Name: generate_hilbert_space
Project Name: dmlc/dgl
Commit Name: f5eb80d221fec8690e8cfb087256671545bb9a5a
Time: 2020-08-11
Author: coin2028@hotmail.com
File Name: examples/pytorch/graphsage/train_sampling_unsupervised.py
Class Name: SAGE
Method Name: inference
Project Name: PIQuIL/QuCumber
Commit Name: 57d419c21650c6bad57ba7ac6b3b14a219b16a3a
Time: 2018-08-09
Author: emerali@users.noreply.github.com
File Name: qucumber/positive_wavefunction.py
Class Name: PositiveWavefunction
Method Name: generate_hilbert_space