BIOMOD.models.out
, BIOMOD.projection.out
or BIOMOD.ensemble.models.out
objectsR/biomod2_classes_3.R
getters.out.Rd
These functions allow the user to easily retrieve informations stored in the different biomod2 objects from the different modeling steps, such as modeling options and formated data, models used or not, predictions, evaluations, variables importance.
# S4 method for class 'BIOMOD.formated.data'
get_species_data(obj)
# S4 method for class 'BIOMOD.formated.data.PA'
get_species_data(obj)
# S4 method for class 'BIOMOD.formated.data'
get_eval_data(obj)
# S4 method for class 'BIOMOD.models.out'
get_options(obj)
# S4 method for class 'BIOMOD.models.out'
get_calib_lines(obj, as.data.frame = FALSE, PA = NULL, run = NULL)
# S4 method for class 'BIOMOD.models.out'
get_formal_data(obj, subinfo = NULL)
# S4 method for class 'BIOMOD.models.out'
get_predictions(
obj,
evaluation = FALSE,
full.name = NULL,
PA = NULL,
run = NULL,
algo = NULL,
model.as.col = FALSE
)
# S4 method for class 'BIOMOD.models.out'
get_built_models(obj, full.name = NULL, PA = NULL, run = NULL, algo = NULL)
# S4 method for class 'BIOMOD.models.out'
get_evaluations(
obj,
full.name = NULL,
PA = NULL,
run = NULL,
algo = NULL,
metric.eval = NULL
)
# S4 method for class 'BIOMOD.models.out'
get_variables_importance(
obj,
full.name = NULL,
PA = NULL,
run = NULL,
algo = NULL,
expl.var = NULL
)
# S4 method for class 'BIOMOD.projection.out'
get_projected_models(
obj,
full.name = NULL,
PA = NULL,
run = NULL,
algo = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL
)
# S4 method for class 'BIOMOD.projection.out'
free(obj)
# S4 method for class 'BIOMOD.projection.out'
get_predictions(
obj,
metric.binary = NULL,
metric.filter = NULL,
full.name = NULL,
PA = NULL,
run = NULL,
algo = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL,
model.as.col = FALSE,
...
)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_formal_data(obj, subinfo = NULL)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_built_models(
obj,
full.name = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL,
algo = NULL
)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_kept_models(obj)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_predictions(
obj,
evaluation = FALSE,
full.name = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL,
algo = NULL,
model.as.col = FALSE
)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_evaluations(
obj,
full.name = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL,
algo = NULL,
metric.eval = NULL
)
# S4 method for class 'BIOMOD.ensemble.models.out'
get_variables_importance(
obj,
full.name = NULL,
merged.by.algo = NULL,
merged.by.run = NULL,
merged.by.PA = NULL,
filtered.by = NULL,
algo = NULL,
expl.var = NULL
)
a BIOMOD.formated.data
, BIOMOD.formated.data.PA
,
BIOMOD.models.out
, BIOMOD.projection.out
or
BIOMOD.ensemble.models.out
object
a logical
defining whether output should be returned as
data.frame
or array
object
(optional, default NULL
)
A vector
containing pseudo-absence set to be loaded, must be among PA1
,
PA2
, ...
, allData
(optional, default NULL
)
A vector
containing repetition set to be loaded, must be among RUN1
,
RUN2
, ...
, allRun
a character
corresponding to the information to be extracted, must be
among NULL
, expl.var.names
, resp.var
, expl.var
, MinMax
,
eval.resp.var
, eval.expl.var
(see Details)
a logical
defining whether evaluation data should be used or not
(optional, default NULL
)
A vector
containing model names to be kept, must be either all
or a
sub-selection of model names that can be obtained with the get_built_models
function
(optional, default NULL
)
A character
containing algorithm to be loaded, must be either
ANN
, CTA
, FDA
, GAM
, GBM
, GLM
, MARS
,
MAXENT
, MAXNET
, RF
, SRE
, XGBOOST
(optional, default FALSE
)
A boolean
given to get_predictions
. If TRUE
prediction are returned as a wide data.frame
with each column containing
predictions for a single model and corresponding to the old output given by
biomod2 in version < 4.2-2. If FALSE
predictions are returned
as a long data.frame
with many additional informations readily
available.
(optional, default NULL
)
A vector
containing evaluation metric to be kept, must be among POD
,
FAR
, POFD
, SR
, ACCURACY
, BIAS
, ROC
, TSS
,
KAPPA
, OR
, ORSS
, CSI
, ETS
, BOYCE
, MPA
(optional, default NULL
)
A vector
containing explanatory variables to be kept, that can be obtained with the
get_formal_data(obj, subinfo = 'expl.var.names')
function
(optional, default NULL
)
A character
containing merged algorithm to be loaded, must be among
ANN
, CTA
, FDA
, GAM
, GBM
, GLM
, MARS
,
MAXENT
, MAXNET
, RF
, SRE
, XGBOOST
, mergedAlgo
(optional, default NULL
)
A vector
containing merged repetition set to be loaded, must be among RUN1
,
RUN2
, ...
, mergedRun
(optional, default NULL
)
A vector
containing merged pseudo-absence set to be loaded, must be among PA1
,
PA2
, ...
, mergedData
(optional, default NULL
)
A vector
containing evaluation metric selected to filter single models to build the
ensemble models, must be among POD
, FAR
, POFD
, SR
,
ACCURACY
, BIAS
, ROC
, TSS
, KAPPA
, OR
, ORSS
,
CSI
, ETS
, BOYCE
, MPA
(optional, default NULL
)
A vector
containing evaluation metric selected to transform predictions into binary
values, must be among POD
, FAR
, POFD
, SR
, ACCURACY
,
BIAS
, ROC
, TSS
, KAPPA
, OR
, ORSS
, CSI
,
ETS
, BOYCE
, MPA
(optional, default NULL
)
A vector
containing evaluation metric to filter predictions, must be among POD
,
FAR
, POFD
, SR
, ACCURACY
, BIAS
, ROC
, TSS
,
KAPPA
, OR
, ORSS
, CSI
, ETS
, BOYCE
, MPA
(optional, one or several of the following arguments depending on the selected function)
get_species_data
a data.frame
combining data.species
,
coord
, data.env.var
(and PA.table
) slots of
BIOMOD.formated.data
(or BIOMOD.formated.data.PA
) object
get_eval_data
a data.frame
combining eval.data.species
,
eval.coord
, eval.data.env.var
slots of
BIOMOD.formated.data
or BIOMOD.formated.data.PA
object
get_options
a
BIOMOD.stored.options-class
object from the
models.options
slot of a BIOMOD.models.out-class
object
get_calib_lines
a
BIOMOD.stored.data.frame-class
object from the calib.lines
slot of a BIOMOD.models.out
object
get_projected_models
a vector
from the
models.projected
slot of a BIOMOD.projection.out
object
get_predictions
a BIOMOD.stored.data
object
from the proj.out
slot of a BIOMOD.models.out
,
BIOMOD.projection.out
or
BIOMOD.ensemble.models.out
object
get_kept_models
a vector
containing names of the kept
models of a BIOMOD.ensemble.models.out
object
get_formal_data
depending on the subinfo
parameter :
NULL
a BIOMOD.stored.formated.data-class
(or
BIOMOD.stored.models.out-class
) object from the
formated.input.data
(or models.out
) slot of a
BIOMOD.models.out
(or
BIOMOD.ensemble.models.out
) object
expl.var.names
a vector
from the
expl.var.names
slot of a BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
resp.var
a vector
from the data.species
slot
of the formated.input.data
slot of a
BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
expl.var
a data.frame
from the data.env.var
slot of the formated.input.data
slot of a
BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
MinMax
a list
of minimum and maximum values (or
levels if factorial) of variable contained in the data.env.var
slot of the formated.input.data
slot of a
BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
eval.resp.var
a vector
from the
eval.data.species
slot of the formated.input.data
slot of
a BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
eval.expl.var
a data.frame
from the
eval.data.env.var
slot of the formated.input.data
slot of
a BIOMOD.models.out
or
BIOMOD.ensemble.models.out
object
get_built_models
a vector
from the
models.computed
slot (or em.computed
) of a
BIOMOD.models.out
(or
BIOMOD.ensemble.models.out
) object
get_evaluations
a data.frame from the models.evaluation
slot (or model_evaluation
of each model in em.computed
) of a
BIOMOD.models.out
(or BIOMOD.ensemble.models.out
)
object. Contains evaluation metric for different models and dataset.
Evaluation metric are calculated on the calibrating data (column calibration
),
on the cross-validation data (column validation
) or on the evaluation data
(column evaluation
).
For cross-validation data, see CV.[...]
parameters in BIOMOD_Modeling
function ; for evaluation data, see
eval.[...]
parameters in BIOMOD_FormatingData
.
get_variables_importance
a
BIOMOD.stored.data.frame-class
from
the variables.importance
slot (or model_variables_importance
of each model in em.models
) of a BIOMOD.models.out
(or BIOMOD.ensemble.models.out
) object
BIOMOD.models.out
, BIOMOD.projection.out
,
BIOMOD.ensemble.models.out
Other Toolbox functions:
getters.bm
,
load_stored_object()
,
predict.bm
,
predict.em
,
predict2.bm
,
predict2.em