Dear @PVDodeja - the read_pumas function automatically maps if the variable name is rate, but if the variable is named RATE, you need to explicitly map it as
read_pumas(df, rate = :RATE)
you can read the documentation here
help?> read_pumas
search: read_pumas
read_pumas(filepath::String; missingstring = ["", ".", "NA"], kwargs...)
read_pumas(
df::AbstractDataFrame;
observations=Symbol[:dv],
covariates=Symbol[],
id::Symbol=:id,
time::Symbol=:time,
evid::Union{Nothing,Symbol}=nothing,
amt::Symbol=:amt,
addl::Symbol=:addl,
ii::Symbol=:ii,
cmt::Symbol=:cmt,
rate::Symbol=:rate,
ss::Symbol=:ss,
route::Symbol=:route,
mdv::Symbol=nothing,
event_data::Bool=true,
covariates_direction::Symbol=:left,
check::Bool=event_data,
adjust_evid34::Bool=true
)
Import NMTRAN-formatted data. You can either pass a CSV file path as a String or a DataFrame as the first and only positional argument.
• df: DataFrame contaning the data to be converted to a Vector{<:Subject}.
• observations: dependent variables specified by a vector of column names.
• covariates: covariates specified by a vector of column names.
• id: specifies the ID column of the DataFrame.
• time: specifies the time column of the DataFrame.
• evid: specifies the event ID column of the DataFrame. See ?Pumas.Event for more details.
• amt: specifies the dose amount column of the DataFrame. See ?Pumas.Event for more details.
• addl: specifies the column of the DataFrame that indicated the number of repeated dose events. If not specified then the value is zero.
• ii: specifies the dose interval column of the DataFrame. See ?Pumas.Event for more details.
• cmt: specifies the compartment column of the DataFrame. See ?Pumas.Event for more details.
• rate: specifies the infusion rate column of the DataFrame. See ?Pumas.Event for more details.
• ss: specifies the steady state column of the DataFrame. See ?Pumas.Event for more details.
• route: specifies the route of administration column of the DataFrame. See ?Pumas.Event for more details.
• mdv: specifies the the column of the DataFrame indicating if observations are missing.
• event_data: toggles assertions applicable to event data. More specifically, checks if the following columns are present in the DataFrame, either as the default
values or as user-defined values: :id, :time, and :amt. If no :evid column is present, then a warning will be thrown, and :evid is set to 1 when :amt values are
>0 or not missing, or :evid is set to 0 when :amt values are missing and observations are not missing. Otherwise, read_pumas will throw an error.
• covariates_direction: specifies direction of covariate interpolation. Either :left (Last Observation Carried Forward, LOCF) (default), or :right (Next
Observation Carried Backward, NOCB). Notice, that for model with occasion variables it is important to use :left for the correct behavior of the interpolation.
• check: toggles NMTRAN compliance check of the input data. More specifically, checks if the following columns are present in the DataFrame, either as the default
values or as user-defined values: :id, :time, :amt, :cmt, :evid, :addl, :ii, :ss, and :route. Additional checks are:
• all variables in observations are numeric, i.e. Integer or AbstractFloat.
• :amt column is numeric, i.e. Integer or AbstractFloat.
• :cmt column is either a positive Integer, an AbstractString, or a Symbol.
• :amt values must be missing or 0 when evid = 0; or >=0 otherwise.
• all variables in observation are missing when evid = 1.
• :ii column must be present if :ss is specified or present.
• :ii values must be missing or 0 when evid = 0.
• :ii column must be >0 if :addl values are >0, and vice-versa.
• :addl column, if present, must be >=0 when evid = 1.
• :evid values must be !=0 when :amt values are >0, or :addl and :ii values are >0.
• adjust_evid34: toggles adjustment of time vector for reset events (evid = 3 and evid = 4). If true (the default) then the time of the previous event is added to
the time on record to ensure that the time vector is monotonically increasing.