Seeding error is not very clear or informative.
One general thought would be to somehow state throughout the code where the errors are occurring.
Eg: to say this is a seeding error
[2397 rows x 14 columns]
(1183, 15)
level_0 index place ... destination_age_strata no_perturb amount2
0 1214 862 20000 ... age18to64 True 45.327554
1 1215 1372 56000 ... age18to64 True 3.481962
2 1216 908 23000 ... age18to64 True 25.507546
3 1217 1301 50000 ... age18to64 True 27.069163
4 1218 956 26000 ... age18to64 True 368.206025
... ... ... ... ... ... ... ...
1178 2392 1635 16000 ... age18to64 False NaN
1179 2393 1916 30000 ... age18to64 False NaN
1180 2394 1415 02000 ... age18to64 False NaN
1181 2395 1636 16000 ... age18to64 False NaN
1182 2396 1416 02000 ... age18to64 False NaN
[1183 rows x 15 columns]
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: The provided dictionary does not allow to isolate a compartment: {'infection_stage': 'S', 'vaccination_stage': 'unvaccinated', 'variant_type': 'WILD', 'age_strata': 'age18to64'} isolate Empty DataFrame
<... omitted ...> name
0 S ... S_unvaccinated_OMICRON_age0to17
1 S ... S_unvaccinated_OMICRON_age18to64
2 S ... S_unvaccinated_OMICRON_age65to100
3 S ... S_unvaccinated_BA2_age0to17
4 S ... S_unvaccinated_BA2_age18to64
.. ... ... ...
625 I3 ... I3_waned3rd_BQ1_age18to64
626 I3 ... I3_waned3rd_BQ1_age65to100
627 I3 ... I3_waned3rd_XBB_age0to17
628 I3 ... I3_waned3rd_XBB_age18to64
629 I3 ... I3_waned3rd_XBB_age65to100
jcblemai
commented
10 months ago
Seeding error is not very clear or informative. One general thought would be to somehow state throughout the code where the errors are occurring. Eg: to say this is a seeding error