theory:
from_: fit
theoryid:
from_: theory
use_cuts: "fromfit"
pdf:
from_: fit
experiments:
from_: fit
dataspecs:
- fit: NNPDF31_nlo_as_0118_1000
- fit: NNPDF31_nnlo_as_0118_1000
actions_:
- matched_datasets_from_dataspecs::dataspecs plot_fancy_dataspecs
gives the wrong results in that the datasets incorrectly resolve to the first (NLO) value. It works fine if
experiments:
from_: fit
is inside each dataspec. This has to do with the fact that even though we specify write=False in the validphys production rules, the parameter is not propagated to resolve_signature_params. This change:
diff --git a/src/reportengine/configparser.py b/src/reportengine/configparser.py
index 26138aa..3d79657 100644
--- a/src/reportengine/configparser.py
+++ b/src/reportengine/configparser.py
@@ -294,7 +294,7 @@ class Config(metaclass=ConfigMetaClass):
ns,
input_params= input_params,
max_index=max_index,
- parents=parents)
+ parents=parents, write=False)
except KeyError:
if param.default is not sig.empty:
pval = param.default
appears to fix the problem, but then some other test fails. Have to check if correctly propagating the argument works. Or rewrite the whole thing in a way that is not crazy.
The following validphys runcard
gives the wrong results in that the datasets incorrectly resolve to the first (NLO) value. It works fine if
is inside each dataspec. This has to do with the fact that even though we specify
write=False
in the validphys production rules, the parameter is not propagated toresolve_signature_params
. This change:appears to fix the problem, but then some other test fails. Have to check if correctly propagating the argument works. Or rewrite the whole thing in a way that is not crazy.