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build_tree_toy.py
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build_tree_toy.py
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import torch
import torch.nn as nn
import torch.nn.functional as F
import os
import sys
import random
import logging
global directions
PI = torch.acos(torch.tensor(-1.0))
directions = None
otho = []
basic_directions = set()
transforms = []
def init_directions(chaos_limit=4, calc_dmap=True):
global directions
if directions is not None:
return num_directions()
directions = []
for xx in reversed(range(0, chaos_limit + 1)):
for yy in reversed(range(0, chaos_limit + 1)):
for zz in reversed(range(0, chaos_limit + 1)):
x = 2 * xx - chaos_limit
y = 2 * yy - chaos_limit
z = 2 * zz - chaos_limit
# print(x, y, z)
# if x < 0:
# continue
# if abs(x) < 1e-6 and y < 0:
# continue
# if abs(x) < 1e-6 and abs(y) < 1e-6 and z < 0:
# continue
d = torch.tensor([x, y, z]).float()
if d.norm() < 1e-6:
continue
d /= d.norm()
for d2 in directions:
if (d - d2).norm() < 1e-6 or (d + d2).norm() < 1e-6:
d = None
break
if d is None:
continue
directions.append(d)
otho.append(set())
if abs(x) + abs(y) + abs(z) == 1:
basic_directions.add(len(directions) - 1)
logging.info(f"init_directions: # = {len(directions)}")
for i, d in enumerate(directions):
for j, e in enumerate(directions):
if d.dot(e).abs().item() < 1e-6:
otho[i].add(j)
x, y, z = d.numpy().tolist()
# logging.debug(f"{i}: {' '.join(map(lambda x : '%.6lf' % x, d.cpu().numpy().tolist()))} otho = {otho[i]}")
print(f"{{{x}, {y}, {z}}},")
init_directions(10)