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Casting bound values as float in inference_parameter.py to prevent parsing errors #405

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merged 4 commits into from
Dec 6, 2024
Merged

Casting bound values as float in inference_parameter.py to prevent parsing errors #405

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aeb230b
Update `inference_parameter.py`
emprzy Nov 22, 2024
8e80204
Implementing Joseph's suggestion
emprzy Dec 4, 2024
c97841d
Update `inference_parameter.py`
emprzy Dec 6, 2024
9c6d3dd
Merge branch 'dev' into scientific_notation_parsing
emprzy Dec 6, 2024
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16 changes: 8 additions & 8 deletions flepimop/gempyor_pkg/src/gempyor/inference_parameter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,8 +55,8 @@ def add_modifier(self, pname, ptype, parameter_config, subpops):
pname=pname,
subpop=sp,
pdist=parameter_config["value"].as_random_distribution(),
lb=parameter_config["value"]["a"].get(),
ub=parameter_config["value"]["b"].get(),
lb=parameter_config["value"]["a"].get(float),
ub=parameter_config["value"]["b"].get(float),
)

# grouped subpop have one parameter per group
Expand All @@ -67,8 +67,8 @@ def add_modifier(self, pname, ptype, parameter_config, subpops):
pname=pname,
subpop=",".join(group),
pdist=parameter_config["value"].as_random_distribution(),
lb=parameter_config["value"]["a"].get(),
ub=parameter_config["value"]["b"].get(),
lb=parameter_config["value"]["a"].get(float),
ub=parameter_config["value"]["b"].get(float),
)
elif parameter_config["method"].get() == "MultiPeriodModifier":
affected_subpops_grp = []
Expand Down Expand Up @@ -97,8 +97,8 @@ def add_modifier(self, pname, ptype, parameter_config, subpops):
pname=pname,
subpop=sp,
pdist=parameter_config["value"].as_random_distribution(),
lb=parameter_config["value"]["a"].get(),
ub=parameter_config["value"]["b"].get(),
lb=parameter_config["value"]["a"].get(float),
ub=parameter_config["value"]["b"].get(float),
)

# grouped subpop have one parameter per group
Expand All @@ -109,8 +109,8 @@ def add_modifier(self, pname, ptype, parameter_config, subpops):
pname=pname,
subpop=",".join(group),
pdist=parameter_config["value"].as_random_distribution(),
lb=parameter_config["value"]["a"].get(),
ub=parameter_config["value"]["b"].get(),
lb=parameter_config["value"]["a"].get(float),
ub=parameter_config["value"]["b"].get(float),
)
else:
raise ValueError(f"Unknown method {parameter_config['method']}")
Expand Down