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ca7299e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | # Copyright 2021 AlQuraishi Laboratory
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch
def gdt(p1, p2, mask, cutoffs):
n = torch.sum(mask, dim=-1)
p1 = p1.float()
p2 = p2.float()
distances = torch.sqrt(torch.sum((p1 - p2)**2, dim=-1))
scores = []
for c in cutoffs:
score = torch.sum((distances <= c) * mask, dim=-1) / n
scores.append(score)
return sum(scores) / len(scores)
def gdt_ts(p1, p2, mask):
return gdt(p1, p2, mask, [1., 2., 4., 8.])
def gdt_ha(p1, p2, mask):
return gdt(p1, p2, mask, [0.5, 1., 2., 4.])
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