[[inference-and-evaluation-troubleshoots]]
Inference and evaluation Troubleshoots
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Although the inference/evaluation generally run smoothly we try to list
out some possible troubleshoots and corresponding solutions.

[width="99%",cols="<32%,<68%",options="header",]
|=======================================================================
|Issue |Putative solution
|map_base::at() exception |This exception is most likely thrown by a
Gene_Choice event in the inference. Try/Catch handling is runtime costly
thus some checks are not performed on the fly. Explanation: This is most
likely the inference receiving a genomic template whose name does not
exist in the model realizations. Solution: make sure the genomic
templates (and their names) used for alignments correspond to those
contained in your model file.

|All 0 output |All marginal files contains 0 parameters after one
iteration. All sequences have zero likelihood in the
_inference_logs.txt_ file. Explanation: none of the scenarios had a
sufficiently high likelihood to reach the likelihood threshold.
Solution: use the `--L_thresh` argument to decrease the likelihood
threshold, if the code becomes utterly slow see below. ** In general
while inferring one should make sure not too many sequences are assigned
a zero likelihood since it would introduce a systematic bias in the
learned distribution **

|Extreme slowness |Runtimes are very far from the ones given in the
<<runtimes, Runtimes section>>. Check the mean number of errors in the _inference_logs.txt_
file. If these numbers are higher than you would expect from your data
(e.g if you are not studying hypermutated data) check your alignments
statistics. A possible explanation would be an incorrect setting of the
alignment offsets bounds
|=======================================================================

