API¶
nimare.dataset
: Dataset IO¶
Classes for representing datasets of images and/or coordinates.
nimare.dataset |
Classes for representing datasets of images and/or coordinates. |
nimare.dataset.Dataset (source[, target, mask]) |
Storage container for a coordinate- and/or image-based meta-analytic dataset/database. |
nimare.meta
: Meta-analytic algorithms¶
Coordinate-, image-, and effect-size-based meta-analysis estimators.
nimare.meta |
Coordinate-, image-, and effect-size-based meta-analysis estimators. |
nimare.meta.esma |
Effect-size meta-analysis functions |
nimare.meta.ibma |
Image-based meta-analysis estimators |
nimare.meta.cbma.kernel |
Methods for estimating thresholded cluster maps from neuroimaging contrasts (Contrasts) from sets of foci and optional additional information (e.g., sample size and test statistic values). |
nimare.meta.cbma.ale |
CBMA methods from the activation likelihood estimation (ALE) family |
nimare.meta.cbma.mkda |
CBMA methods from the multilevel kernel density analysis (MKDA) family |
nimare.meta.cbma.model |
Model-based coordinate-based meta-analysis estimators |
nimare.correct
: Multiple comparisons correction¶
Multiple comparisons correction
nimare.correct |
Multiple comparisons correction |
nimare.correct.FWECorrector ([method]) |
Perform family-wise error rate correction on a meta-analysis. |
nimare.correct.FDRCorrector ([alpha, method]) |
Perform false discovery rate correction on a meta-analysis. |
nimare.annotate
: Automated annotation¶
Automated annotation tools
nimare.annotate |
Automated annotation tools |
nimare.annotate.ontology |
Automated annotation tools for existing ontologies. |
nimare.annotate.topic |
Automated annotation with text-derived topic models. |
nimare.annotate.vector |
Automated annotation with text-derived vector models. |
nimare.annotate.text |
Text extraction tools. |
nimare.decode
: Functional characterization analysis¶
Functional decoding tools
nimare.decode |
Functional decoding tools |
nimare.decode.discrete |
Methods for decoding subsets of voxels (e.g., ROIs) or experiments (e.g., from meta-analytic clustering on a database) into text. |
nimare.decode.continuous |
Methods for decoding unthresholded brain maps into text. |
nimare.decode.encode |
Methods for encoding text into brain maps. |
nimare.parcellate
: Meta-analytic parcellation¶
Meta-analytic parcellation tools
nimare.parcellate |
Meta-analytic parcellation tools |
nimare.parcellate.cbp |
Coactivation-based parcellation |
nimare.parcellate.mamp |
Meta-analytic activation modeling-based parcellation (MAMP). |
nimare.parcellate.mapbot |
Meta-analytic parcellation based on text (MAPBOT). |
nimare.io
: Input/Output¶
Input/Output operations.
nimare.io |
Input/Output operations. |
nimare.io.convert_neurosynth_to_json (…[, …]) |
Convert Neurosynth dataset text file to a NiMARE json file. |
nimare.io.convert_sleuth_to_dict (text_file) |
Convert Sleuth text file to a dictionary. |
nimare.io.convert_sleuth_to_json (text_file, …) |
Convert Sleuth output text file into json. |
nimare.io.convert_sleuth_to_dataset (text_file) |
Convert Sleuth output text file into dictionary and create NiMARE Dataset with dictionary. |
nimare.stats
: Statistical functions¶
Various statistical helper functions
nimare.stats |
Various statistical helper functions |
nimare.stats.one_way (data, n) |
One-way chi-square test of independence. |
nimare.stats.two_way (cells) |
Two-way chi-square test of independence. |
nimare.stats.pearson (x, y) |
Correlates row vector x with each row vector in 2D array y. |
nimare.stats.null_to_p (test_value, null_array) |
Return two-sided p-value for test value against null array. |
nimare.stats.p_to_z (p[, tail]) |
Convert p-values to z-values. |
nimare.stats.t_to_z (t_values, dof) |
From Vanessa Sochat’s TtoZ package. |
nimare.stats.fdr (p[, q]) |
Determine FDR threshold given a p value array and desired false discovery rate q. |
nimare.utils
: Utility functions and submodules¶
Utilities
nimare.utils |
Utilities |
nimare.utils.get_template ([space, mask]) |
Load template file. |
nimare.utils.listify (obj) |
Wraps all non-list or tuple objects in a list; provides a simple way to accept flexible arguments. |
nimare.utils.round2 (ndarray) |
Numpy rounds X.5 values to nearest even integer. |
nimare.utils.vox2mm (ijk, affine) |
Convert matrix subscripts to coordinates. |
nimare.utils.mm2vox (xyz, affine) |
Convert coordinates to matrix subscripts. |
nimare.utils.tal2mni (coords) |
Python version of BrainMap’s tal2icbm_other.m. |
nimare.utils.mni2tal (coords) |
Python version of BrainMap’s icbm_other2tal.m. |
nimare.utils.get_resource_path () |
Returns the path to general resources, terminated with separator. |
nimare.workflows
: Common workflows¶
Common meta-analytic workflows
nimare.workflows |
Common meta-analytic workflows |
nimare.workflows.ale |
Workflow for running an ALE meta-analysis from a Sleuth text file. |
nimare.workflows.conperm |
Workflow for running a contrast permutation meta-analysis on a set of images. |
nimare.workflows.macm |
Perform MACM with ALE algorithm. |
nimare.workflows.peaks2maps |
Workflow for contrast permutation meta-analysis on images constructed from coordinates using the Peaks2Maps kernel. |
nimare.workflows.scale |
Workflow for running a SCALE meta-analysis from a Sleuth text file. |
nimare.base
: Base classes¶
Base classes for datasets.
nimare.base |
Base classes for datasets. |
nimare.base.base |
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nimare.base.estimators |