nimare.meta.ibma
.IBMAEstimator
- class IBMAEstimator(*, mask=None, **kwargs)[source]
Bases:
Estimator
Base class for meta-analysis methods in
meta
.Changed in version 0.2.0:
Remove resample and memory_limit arguments. Resampling is now performed only if shape/affines are different.
New in version 0.0.12:
IBMA-specific elements of
Estimator
excised and used to createIBMAEstimator
.Generic kwargs and args converted to named kwargs. All remaining kwargs are for resampling.
Methods
fit
(dataset[, drop_invalid])Fit Estimator to Dataset.
get_params
([deep])Get parameters for this estimator.
load
(filename[, compressed])Load a pickled class instance from file.
save
(filename[, compress])Pickle the class instance to the provided file.
set_params
(**params)Set the parameters of this estimator.
- fit(dataset, drop_invalid=True)[source]
Fit Estimator to Dataset.
- Parameters:
- Returns:
Results of Estimator fitting.
- Return type:
- Variables:
inputs (
dict
) – Inputs used in _fit.
- classmethod load(filename, compressed=True)[source]
Load a pickled class instance from file.
- Parameters:
- Returns:
obj – Loaded class object.
- Return type:
class object
- set_params(**params)[source]
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.- Return type:
self