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__init__.py
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__init__.py
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"""
Machine Learning module for NeuroImaging in python
--------------------------------------------------
Documentation is available in the docstrings and online at
http://nilearn.github.io.
Contents
--------
Nilearn aims at simplifying the use of the scikit-learn package in the context of
neuroimaging. It provides specific input/output functions, algorithms and
visualization tools.
Submodules
---------
datasets --- Utilities to download NeuroImaging datasets
decoding --- Decoding tools and algorithms
decomposition --- Includes a subject level variant of the ICA
algorithm called Canonical ICA
connectome --- Set of tools for computing functional connectivity matrices
and for sparse multi-subjects learning of Gaussian graphical models
image --- Set of functions defining mathematical operations
working on Niimg-like objects
input_data --- includes scikit-learn tranformers and tools to
preprocess neuro-imaging data
masking --- Utilities to compute and operate on brain masks
mass_univariate --- Defines a Massively Univariate Linear Model
estimated with OLS and permutation test
plotting --- Plotting code for nilearn
region --- Set of functions for extracting region-defined
signals
signal --- Set of preprocessing functions for time series
"""
import gzip
from .version import _check_module_dependencies, __version__
_check_module_dependencies()
# Monkey-patch gzip to have faster reads on large gzip files
if hasattr(gzip.GzipFile, 'max_read_chunk'):
gzip.GzipFile.max_read_chunk = 100 * 1024 * 1024 # 100Mb
# Boolean controlling the default globbing technique when using check_niimg
# and the os.path.expanduser usage in CacheMixin.
# Default value it True, set it to False to completely deactivate this
# behavior.
EXPAND_PATH_WILDCARDS = True
# Boolean controlling whether the joblib caches should be
# flushed if the version of certain modules changes (eg nibabel, as it
# does not respect the backward compatibility in some of its internal
# structures
# This is used in nilearn._utils.cache_mixin
CHECK_CACHE_VERSION = True
# list all submodules available in nilearn and version
__all__ = ['datasets', 'decoding', 'decomposition', 'connectome',
'image', 'input_data', 'masking', 'mass_univariate', 'plotting',
'region', 'signal', '__version__']