Datasets:
Formats:
json
Languages:
English
Size:
1K - 10K
Tags:
programmable-matter
nanofabrication
hierarchical-self-assembly
dna-origami
material-voxels
kinetic-proofreading
License:
| """Meaningful cross-checks: conservation, analytic absorption, stochastic comparison, | |
| code separation, interface count, and irreducible fusion failures.""" | |
| import unittest, json, math | |
| import numpy as np | |
| from simulate import * | |
| class ModelTests(unittest.TestCase): | |
| def test_generator_conservation(self): | |
| Q,a,b=generator(.03,.09,.01,.2,.1,2) | |
| self.assertTrue(np.allclose(Q.sum(1),0)) | |
| off=Q.copy();np.fill_diagonal(off,0);self.assertGreaterEqual(off.min(),0) | |
| def test_absorption_against_renewal_formula(self): | |
| for r in (0,1,2): | |
| pc,pw,lim,mean,fuel=local_stats(.03,.09,.01,.2,.1,r,100000.) | |
| self.assertAlmostEqual(pc+pw,1.,places=9);self.assertAlmostEqual(pw,lim,places=9) | |
| def test_random_symmetry(self): | |
| pc,pw,*_=local_stats(.01,.15,.01,.01,.1,0,10000.) | |
| self.assertAlmostEqual(pw/pc,15.,places=9) | |
| def test_hierarchy_counts(self): | |
| for N in (16,64,4096): | |
| self.assertEqual(sum(x[0] for x in level_plan(N,'locking',Parameters())),N-1) | |
| def test_no_hidden_repair(self): | |
| p=Parameters(hold_loss=0.,fusion_error=.01,deadline=1e9) | |
| x=evaluate(64,'locking',p) | |
| self.assertLessEqual(x['perfect_yield'],.99**63+1e-9) | |
| def test_code_distance(self): | |
| words=np.loadtxt(ROOT/'results/example_codebook.csv',delimiter=',',dtype=int) | |
| D=(words[:,None,:]!=words[None,:,:]).sum(-1);D+=np.eye(len(words),dtype=int)*99 | |
| self.assertGreaterEqual(D.min(),3) | |
| def test_gillespie_vs_matrix_exponential(self): | |
| data=json.loads((ROOT/'results/gillespie_validation.json').read_text()) | |
| for case in data: | |
| n=case['monte_carlo']['reps'] | |
| for p,f in zip(case['exact'],case['monte_carlo']['fractions']): | |
| self.assertLess(abs(p-f),6*math.sqrt(max(p*(1-p),1/n)/n)+2/n) | |
| def test_incorrect_occupancy_reduced_by_checks(self): | |
| a=local_stats(.03,.09,.01,.2,.1,0,1e5)[1] | |
| b=local_stats(.03,.09,.01,.2,.1,2,1e5)[1] | |
| self.assertLess(b,a) | |
| def test_all_record_probabilities(self): | |
| for x in json.loads((ROOT/'results/baseline_details.json').read_text()): | |
| for r in x['detail']: | |
| self.assertAlmostEqual(r['correct']+r['wrong']+r['missing'],1,places=9) | |
| self.assertTrue(all(0<=r[k]<=1 for k in ('correct','wrong','missing'))) | |
| if __name__=='__main__':unittest.main(verbosity=2) | |