Models
Index
UncertaintyQuantification.Model
UncertaintyQuantification.ParallelModel
UncertaintyQuantification.UQModel
UncertaintyQuantification.evaluate!
UncertaintyQuantification.evaluate!
Types
UncertaintyQuantification.Model Type
julia
Model(f::Function, name::Symbol)
The function f
must accept a DataFrame
and return the result of the model for each row in the DataFrame
as a vector. The name
is used to add the output to the DataFrame
.
UncertaintyQuantification.ParallelModel Type
julia
ParallelModel(f::Function, name::Symbol)
The ParallelModel
does what the Model
does with a small difference. The function f
is passed a DataFrameRow
not the full DataFrame
. If workers (through Distributed
) are present, the rows are evaluated in parallel.
Methods
UncertaintyQuantification.evaluate! Method
julia
evaluate!(m::Model, df::DataFrame)
Calls m.func
with df
and adds the result to the DataFrame
as a column m.name
UncertaintyQuantification.evaluate! Method
julia
evaluate!(m::ParallelModel, df::DataFrame)
Calls m.func
for each row of df
and adds the result to the DataFrame
as a column m.name
. If workers are added through Distributed
, the rows will be evaluated in parallel.