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import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', '..')))
import utils3d
import numpy as np
import torch
def run():
for i in range(100):
if i == 0:
spatial = []
else:
dim = np.random.randint(4)
spatial = [np.random.randint(1, 10) for _ in range(dim)]
fovy = np.random.uniform(5 / 180 * np.pi, 175 / 180 * np.pi, spatial)
aspect = np.random.uniform(0.01, 100, spatial)
near = np.random.uniform(0.1, 100, spatial)
far = np.random.uniform(near*2, 1000, spatial)
expected = utils3d.numpy.perspective(fovy, aspect, near, far)
device = [torch.device('cpu'), torch.device('cuda')][np.random.randint(2)]
fovy = torch.tensor(fovy, device=device)
aspect = torch.tensor(aspect, device=device)
near = torch.tensor(near, device=device)
far = torch.tensor(far, device=device)
actual = utils3d.torch.perspective(fovy, aspect, near, far).cpu().numpy()
assert np.allclose(expected, actual), '\n' + \
'Input:\n' + \
f'\tfovy: {fovy}\n' + \
f'\taspect: {aspect}\n' + \
f'\tnear: {near}\n' + \
f'\tfar: {far}\n' + \
'Actual:\n' + \
f'{actual}\n' + \
'Expected:\n' + \
f'{expected}'
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