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Add reports module (#802)
* Add reports module * Add template * Add config file * Add generate_figues script * Add test * Update test_reports.py * Update setup.cfg * Fix lint error * Add yaml to setup file * Update setup.cfg * Update default.yml * Update setup.cfg * Add report to example gallery * check online path * Plot coordinates * Update 10_plot_cbma_workflow.py * Update 10_plot_cbma_workflow.py * Update figures.py * Update 10_plot_cbma_workflow.py * [skip ci] update figures * [skip ci] add static plot * [skip ci] update path to report * [skip ci] update path * [skip ci] explore rtd directory tree * [skip ci] high res images * [skip ci] update path to report * [skip ci] close fig after saving * [skip ci] update path * [skip ci] try another path the report.html * [skip ci] change the path again............. * [skip ci] update path * [skip ci] update path * [skip ci] add cluster table * [skip ci] add title, caption, and description * [skip ci] update example * [skip ci] increase size of heatmap * [skip ci] add ids of studies excluded to summary * [skip ci] update table style * [skip ci] add dynamic coordinates plot * [skip ci] add legend * [skip ci] embed heatmaps wit iframe * [skip ci] change names to fit new bids-like format * [skip ci] pin pandas version * [skip ci] add summary diagnostics * [skip ci] work on copy of diagnostics * [skip ci] get threshold from diagnostics * [skip ci] add all possible combinations of results * [skip ci] add message when tables and map are empty * [skip ci] add alpha to dictionary * [skip ci] add label maps * [skip ci] add tail label * [skip ci] add mask * add documentation * fix typo * add tables naming convention to output * only plot coordinates for CBMAEstimator * fix typo * improve coverage * reduce report and yml file
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‎docs/api.rst

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@@ -336,6 +336,20 @@ For more information about fetching data from the internet, see :ref:`fetching t
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workflows.macm_workflow
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workflows.cbma_workflow
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:mod:`nimare.reports`: NiMARE report
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--------------------------------------------------
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.. automodule:: nimare.reports
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:no-members:
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:no-inherited-members:
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.. currentmodule:: nimare
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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reports.run_reports
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.. _api_base_ref:
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‎docs/outputs.rst

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NiMARE-generated files, especially ones made by meta-analyses, follow a naming convention somewhat based on BIDS.
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Here is the basic naming convention for statistical maps:
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Here is the basic naming convention for statistical maps and tables:
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.. code-block:: Text
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<value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>][_diag-<Jackknife|FocusCounter>].nii.gz
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<value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>][_diag-<Jackknife|FocusCounter>][_tail-<positive|negative>].nii.gz
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<value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>]_tab-<clust|counts>.tsv
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First, the ``value`` represents type of data in the map (e.g., z-statistic, t-statistic).

‎examples/02_meta-analyses/10_plot_cbma_workflow.py

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the fundamental steps of a CBMA meta-analysis.
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"""
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import os
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from pprint import pprint
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from pathlib import Path
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import matplotlib.pyplot as plt
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from nilearn.plotting import plot_stat_map
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from nimare.dataset import Dataset
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from nimare.reports.base import run_reports
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from nimare.utils import get_resource_path
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from nimare.workflows import cbma_workflow
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result.tables["z_corr-FDR_method-indep_diag-Jackknife_tab-counts"]
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###############################################################################
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# Methods
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# Report
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# -----------------------------------------------------------------------------
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# The MetaResult object also provides boilerplate text automatically generated by NiMARE,
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# which is released under the `CC0 <https://creativecommons.org/publicdomain/zero/1.0/>`_ license.
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print("Description:")
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pprint(result.description_)
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# Finally, a NiMARE report is generated from the MetaResult.
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root_dir = Path(os.getcwd()).parents[1]
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# Use the following path to run the documentation locally:
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# html_dir = root_dir / "docs" / "_build" / "html" / "auto_examples" / "02_meta-analyses"
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html_dir = root_dir / "_readthedocs" / "html" / "auto_examples" / "02_meta-analyses"
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html_dir.mkdir(parents=True, exist_ok=True)
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###############################################################################
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# References
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# ``````````````````````````````````````````````````````````````````````````````
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print("References:")
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pprint(result.bibtex_)
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run_reports(result, html_dir)
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####################################
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# .. raw:: html
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#
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# <iframe src="./report.html" style="border:none;" seamless="seamless" width="100%"\
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# height="1000px"></iframe>

‎nimare/__init__.py

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decode,
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io,
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meta,
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reports,
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resources,
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stats,
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utils,
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"io",
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"stats",
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"utils",
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"reports",
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"workflows",
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"__version__",
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]

‎nimare/diagnostics.py

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Returns
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-------
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contribution_table : :obj:`pandas.DataFrame` or None
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A DataFrame with information about relative contributions of each experiment to each
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cluster in the thresholded map.
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There is one row for each experiment.
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There is one column for each cluster, with column names being
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``PostiveTail``/``NegativeTail`` indicating the sign (+/-) of the cluster's
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statistical values, plus an integer indicating the cluster's associated value
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in the ``label_maps[0]``/``label_maps[1]`` output.
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If no clusters are found or a pairwise Estimator was used, ``None`` is returned.
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clusters_table : :obj:`pandas.DataFrame`
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A DataFrame with information about each cluster.
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There is one row for each cluster.
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The columns in this table include: ``Cluster ID`` (the cluster id, plus a letter
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for subpeaks only), ``X``/``Y``/``Z`` (coordinate for the center of mass),
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``Max Stat`` (statistical value of the peak), and ``Cluster Size (mm3)``
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(the size of the cluster, in cubic millimeters).
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If no clusters are found, this table will be empty.
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label_maps : :obj:`list`
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List of :obj:`nibabel.nifti1.Nifti1Image` objects of cluster label maps.
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Each cluster in the map has a single value, which corresponds to the cluster number
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of the column name in ``contribution_table``.
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If target_image has negative values after thresholding, first and second maps
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correspond to positive and negative tails.
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If no clusters are found, this list will be empty.
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:obj:`~nimare.results.MetaResult`
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Results of Diagnostics fitting.
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Notes
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-----
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This method adds two new keys to ``maps`` and ``tables`` attributes of the
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MetaResult object.
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- ``<target_image>_diag-<Jackknife|FocusCounter>_tab-counts`` :
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:obj:`pandas.DataFrame` or None.
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A DataFrame with information about relative contributions of each experiment
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to each cluster in the thresholded map.
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There is one row for each experiment.
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There is one column for each cluster, with column names being
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``PostiveTail``/``NegativeTail`` indicating the sign (+/-) of the cluster's
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statistical values, plus an integer indicating the cluster's associated value
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in the ``label_maps[0]``/``label_maps[1]`` output.
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If no clusters are found or a pairwise Estimator was used, ``None`` is returned.
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- ``<target_image>_tab-clust`` : :obj:`pandas.DataFrame`
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A DataFrame with information about each cluster.
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There is one row for each cluster.
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The columns in this table include: ``Cluster ID`` (the cluster id, plus a letter
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for subpeaks only), ``X``/``Y``/``Z`` (coordinate for the center of mass),
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``Max Stat`` (statistical value of the peak), and ``Cluster Size (mm3)``
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(the size of the cluster, in cubic millimeters).
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If no clusters are found, this table will be empty.
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- ``label_<target_image>_tail-<positive|negative>`` : :obj:`numpy.ndarray`
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Label maps.
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Each cluster in the map has a single value, which corresponds to the cluster number
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of the column name in ``contribution_table``.
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If target_image has negative values after thresholding, first and second maps
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correspond to positive and negative tails.
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If no clusters are found, this list will be empty.
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"""
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masker = result.estimator.masker
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diag_name = self.__class__.__name__

‎nimare/reports/__init__.py

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"""Reports module."""
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from .base import Report, run_reports
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from .figures import (
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gen_table,
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plot_clusters,
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plot_coordinates,
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plot_heatmap,
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plot_interactive_brain,
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plot_mask,
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plot_static_brain,
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)
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__all__ = [
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"Report",
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"run_reports",
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"gen_table",
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"plot_clusters",
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"plot_coordinates",
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"plot_heatmap",
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"plot_interactive_brain",
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"plot_mask",
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"plot_static_brain",
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]

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