Output
JudiLing.write2csv
— FunctionWrite results into a csv file. This function takes as input the results from the learn_paths
and build_paths
functions, including the information on gold paths that is optionally returned as second output result.
JudiLing.write2df
— FunctionReformat results into a dataframe. This function takes as input the results from the learn_paths
and build_paths
functions, including the information on gold paths that is optionally returned as second output result.
JudiLing.write_comprehension_eval
— FunctionWrite comprehension evaluation into a CSV file, include target and predicted ids and indentifiers and their correlations.
JudiLing.write2csv
— Methodwrite2csv(res, data, cue_obj_train, cue_obj_val, filename)
Write results into csv file for the results from learn_paths
and build_paths
.
Obligatory Arguments
res::Array{Array{Result_Path_Info_Struct,1},1}
: the results fromlearn_paths
orbuild_paths
data::DataFrame
: the datasetcue_obj_train::Cue_Matrix_Struct
: the cue object for training datasetcue_obj_val::Cue_Matrix_Struct
: the cue object for validation datasetfilename::String
: the filename
Optional Arguments
grams::Int64=3
: the number n in n-gram cuestokenized::Bool=false
: if true, the dataset target is tokenizedsep_token::Union{Nothing, String, Char}=nothing
: separatorstart_end_token::Union{String, Char}="#"
: start and end token in boundary cuesoutput_sep_token::Union{String, Char}=""
: output separatorpath_sep_token::Union{String, Char}=":"
: path separatortarget_col::Union{String, Symbol}=:Words
: the column name for target stringsroot_dir::String="."
: dir path for project root diroutput_dir::String="."
: output dir inside root dir
Examples
# writing results for training data
JudiLing.write2csv(
res_train,
latin_train,
cue_obj_train,
cue_obj_train,
"res_latin_train.csv",
grams=3,
tokenized=false,
sep_token=nothing,
start_end_token="#",
output_sep_token="",
path_sep_token=":",
target_col=:Word,
root_dir=".",
output_dir="test_out")
# writing results for validation data
JudiLing.write2csv(
res_val,
latin_val,
cue_obj_train,
cue_obj_val,
"res_latin_val.csv",
grams=3,
tokenized=false,
sep_token=nothing,
start_end_token="#",
output_sep_token="",
path_sep_token=":",
target_col=:Word,
root_dir=".",
output_dir="test_out")
JudiLing.write2csv
— Methodwrite2csv(gpi::Vector{Gold_Path_Info_Struct}, filename)
Write results into csv file for the gold paths' information optionally returned by learn_paths
and build_paths
.
Obligatory Arguments
gpi::Vector{Gold_Path_Info_Struct}
: the gold paths' informationfilename::String
: the filename
Optional Arguments
root_dir::String="."
: dir path for project root diroutput_dir::String="."
: output dir inside root dir
Examples
# write gold standard paths to csv for training data
JudiLing.write2csv(
gpi_train,
"gpi_latin_train.csv",
root_dir=".",
output_dir="test_out"
)
# write gold standard paths to csv for validation data
JudiLing.write2csv(
gpi_val,
"gpi_latin_val.csv",
root_dir=".",
output_dir="test_out"
)
JudiLing.write2csv
— Methodwrite2csv(ts::Threshold_Stat_Struct, filename)
Write results into csv file for threshold and tolerance proportion for each timestep.
Obligatory Arguments
gpi::Vector{Gold_Path_Info_Struct}
: the gold paths' informationfilename::String
: the filename
Optional Arguments
root_dir::String="."
: dir path for project root diroutput_dir::String="."
: output dir inside root dir
Examples
JudiLing.write2csv(ts, "ts.csv", root_dir = @__DIR__, output_dir="out")
JudiLing.write2df
— Methodwrite2df(res, data, cue_obj_train, cue_obj_val)
Reformat results into a dataframe for the results form learn_paths
and build_paths
functions.
Obligatory Arguments
res
: output oflearn_paths
orbuild_paths
data::DataFrame
: the datasetcue_obj_train
: cue object of the training data setcue_obj_val
: cue object of the validation data set
Optional Arguments
grams::Int64=3
: the number n in n-gram cuestokenized::Bool=false
: if true, the dataset target is tokenizedsep_token::Union{Nothing, String, Char}=nothing
: separatorstart_end_token::Union{String, Char}="#"
: start and end token in boundary cuesoutput_sep_token::Union{String, Char}=""
: output separatorpath_sep_token::Union{String, Char}=":"
: path separatortarget_col::Union{String, Symbol}=:Words
: the column name for target strings
Examples
# writing results for training data
JudiLing.write2df(
res_train,
latin_train,
cue_obj_train,
cue_obj_train,
grams=3,
tokenized=false,
sep_token=nothing,
start_end_token="#",
output_sep_token="",
path_sep_token=":",
target_col=:Word)
# writing results for validation data
JudiLing.write2df(
res_val,
latin_val,
cue_obj_train,
cue_obj_val,
grams=3,
tokenized=false,
sep_token=nothing,
start_end_token="#",
output_sep_token="",
path_sep_token=":",
target_col=:Word)
JudiLing.write2df
— Methodwrite2df(gpi::Vector{Gold_Path_Info_Struct})
Write results into a dataframe for the gold paths' information optionally returned by learn_paths
and build_paths
.
Obligatory Arguments
gpi::Vector{Gold_Path_Info_Struct}
: the gold paths' information
Examples
# write gold standard paths to df for training data
JudiLing.write2csv(gpi_train)
# write gold standard paths to df for validation data
JudiLing.write2csv(gpi_val)
JudiLing.write2df
— Methodwrite2df(ts::Threshold_Stat_Struct)
Write results into a dataframe for threshold and tolerance proportion for each timestep.
Obligatory Arguments
ts::Threshold_Stat_Struct
: the threshold and tolerance proportion
Examples
JudiLing.write2df(ts)
JudiLing.write_comprehension_eval
— Methodwrite_comprehension_eval(SChat, SC, data, target_col, filename)
Write comprehension evaluation into a CSV file, include target and predicted ids and indentifiers and their correlations.
Obligatory Arguments
SChat::Matrix
: the Shat/Chat matrixSC::Matrix
: the S/C matrixdata::DataFrame
: the datatarget_col::Symbol
: the name of target columnfilename::String
: the filename/filepath
Optional Arguments
k
: top k candidatesroot_dir::String="."
: dir path for project root diroutput_dir::String="."
: output dir inside root dir
Examples
JudiLing.write_comprehension_eval(Chat, cue_obj.C, latin, :Word, "output.csv",
k=10, root_dir=@__DIR__, output_dir="out")
JudiLing.write_comprehension_eval
— Methodwrite_comprehension_eval(SChat, SC, SC_rest, data, data_rest, target_col, filename)
Write comprehension evaluation into a CSV file for both training and validation datasets, include target and predicted ids and indentifiers and their correlations.
Obligatory Arguments
SChat::Matrix
: the Shat/Chat matrixSC::Matrix
: the S/C matrixSC_rest::Matrix
: the rest S/C matrixdata::DataFrame
: the datadata_rest::DataFrame
: the rest datatarget_col::Symbol
: the name of target columnfilename::String
: the filename/filepath
Optional Arguments
k
: top k candidatesroot_dir::String="."
: dir path for project root diroutput_dir::String="."
: output dir inside root dir
Examples
JudiLing.write_comprehension_eval(Shat_val, S_val, S_train, latin_val, latin_train,
:Word, "all_output.csv", k=10, root_dir=@__DIR__, output_dir="out")
JudiLing.save_L_matrix
— Methodsave_L_matrix(L, filename)
Save lexome matrix into csv file.
Obligatory Arguments
L::L_Matrix_Struct
: the lexome matrix structfilename::String
: the filename/filepath
Examples
JudiLing.save_L_matrix(L, joinpath(@__DIR__, "L.csv"))
JudiLing.load_L_matrix
— Methodload_L_matrix(filename)
Load lexome matrix from csv file.
Obligatory Arguments
filename::String
: the filename/filepath
Optional Arguments
header::Bool=false
: header in csv
Examples
L_load = JudiLing.load_L_matrix(joinpath(@__DIR__, "L.csv"))
JudiLing.save_S_matrix
— Methodsave_S_matrix(S, filename, data, target_col)
Save S matrix into a csv file.
Obligatory Arguments
S::Matrix
: the S matrixfilename::String
: the filename/filepathdata::DataFrame
: the datatarget_col::Symbol
: the name of target column
Optional Arguments
sep::Bool=" "
: separator in CSV file
Examples
JudiLing.save_S_matrix(S, joinpath(@__DIR__, "S.csv"), latin, :Word)
JudiLing.load_S_matrix
— Methodload_S_matrix(filename)
Load S matrix from a csv file.
Obligatory Arguments
filename::String
: the filename/filepath
Optional Arguments
header::Bool=false
: header in csvsep::Bool=" "
: separator in CSV file
Examples
JudiLing.load_S_matrix(joinpath(@__DIR__, "S.csv"))