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gelles-brandeis / tapqir

Bayesian analysis of co-localization single-molecule microscopy image data.
Apache License 2.0
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Fit Data errors #339

Closed jc-brandeis closed 2 years ago

jc-brandeis commented 2 years ago

Fitting the data ... Iteration #56800. Loaded a model checkpoint from /home/jchung/YNE30June2022/.tapqir/cosmos-model.tpqr

0% 0/100000 [00:01<?, ?it/s]

KeyError Traceback (most recent call last) File ~/anaconda3/envs/tapqir-env/lib/python3.8/site-packages/tapqir/gui.py:502, in fitCmd(b, layout, out, DEFAULTS) 500 DEFAULTS["priors"].update(layout["priors"].children[0].kwargs) 501 with out: --> 502 fit( 503 **layout.kwargs, 504 k_max=2, 505 funsor=False, 506 pykeops=True, 507 no_input=True, 508 progress_bar=tqdm_notebook, 509 ) 511 out.clear_output(wait=True)

File ~/anaconda3/envs/tapqir-env/lib/python3.8/site-packages/tapqir/main.py:460, in fit(model, cuda, nbatch_size, fbatch_size, learning_rate, num_iter, k_max, matlab, funsor, pykeops, overwrite, no_input, progress_bar) 458 model.init(learning_rate, nbatch_size, fbatch_size) 459 try: --> 460 model.run(num_iter, progress_bar=progress_bar) 461 except CudaOutOfMemoryError: 462 logger.exception("Failed to fit the data")

File ~/anaconda3/envs/tapqir-env/lib/python3.8/site-packages/tapqir/models/model.py:223, in Model.run(self, num_iter, progress_bar) 221 # save a checkpoint every 200 iterations 222 if not self.iter % 200: --> 223 self.save_checkpoint(writer) 224 if use_crit and self.converged: 225 logger.info(f"Iteration #{self.iter} model converged.")

File ~/anaconda3/envs/tapqir-env/lib/python3.8/site-packages/tapqir/models/model.py:273, in Model.save_checkpoint(self, writer) 271 self.converged = False 272 if len(self._rolling["-ELBO"]) == self._rolling["-ELBO"].maxlen: --> 273 crit = all( 274 torch.tensor(self._rolling[p]).std() 275 / torch.tensor(self._rolling[p])[-50:].std() 276 < 1.05 277 for p in self.conv_params 278 ) 279 if crit: 280 self.converged = True

File ~/anaconda3/envs/tapqir-env/lib/python3.8/site-packages/tapqir/models/model.py:274, in (.0) 271 self.converged = False 272 if len(self._rolling["-ELBO"]) == self._rolling["-ELBO"].maxlen: 273 crit = all( --> 274 torch.tensor(self._rolling[p]).std() 275 / torch.tensor(self._rolling[p])[-50:].std() 276 < 1.05 277 for p in self.conv_params 278 ) 279 if crit: 280 self.converged = True

KeyError: 'lamda_loc'

ordabayevy commented 2 years ago

Thanks for reporting the bug @jc-brandeis ! This should be now fixed in the new release 1.1.2 of Tapqir.