API¶
tedana.workflows: Common workflows¶
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Run the “canonical” TE-Dependent ANAlysis workflow. |
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Estimate T2 and S0, and optimally combine data across TEs. |
tedana.decay: Modeling signal decay across echoes¶
Functions to estimate S0 and T2* from multi-echo data.
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Fit voxel-wise monoexponential decay models to data |
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Fit voxel- and timepoint-wise monoexponential decay models to data |
tedana.combine: Combining time series across echoes¶
Functions to optimally combine data across echoes.
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Optimally combine BOLD data across TEs, using only those echos with reliable signal across at least three echos. |
tedana.decomposition: Data decomposition¶
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Use principal components analysis (PCA) to identify and remove thermal noise from multi-echo data. |
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Perform ICA on data and returns mixing matrix |
tedana.metrics: Computing TE-dependence metrics¶
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Fit TE-dependence and -independence models to components. |
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Compute metrics used by Kundu v2.5 and v3.2 decision trees. |
tedana.selection: Component selection¶
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Perform manual selection of components. |
Classify components as “accepted,” “rejected,” or “ignored” based on relevant metrics. |
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Select PCA components using Kundu’s decision tree approach. |
tedana.gscontrol: Global signal control¶
Global signal control methods
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Removes global signal from individual echo catd and optcom time series |
Perform minimum image regression (MIR) to remove T1-like effects from BOLD-like components. |
tedana.io: Reading and writing data¶
Functions to handle file input/output
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Coerces input data files to required 3D array output |
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Writes data to filename in format of ref_img |
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Coerces data into NiftiImage format like ref_img |
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Save pandas DataFrame as a BIDS Derivatives-compatible json file. |
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Load a BIDS Derivatives decomposition json file into a pandas DataFrame. |
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Create component name with leading zeros matching number of components |
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Splits data time series into accepted component time series and remainder |
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Splits data into denoised / noise / ignored time series and saves to disk |
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Converts data to component space with mmix and saves to disk |
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Denoises ts and saves all resulting files to disk |
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Saves individually denoised echos to disk |
tedana.stats: Statistical functions¶
Statistical functions
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Performs least-squares fit of X against data |
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Converts data to component space using mmix |
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Gets F-statistic boundaries based on number of echos |
tedana.utils: Utility functions¶
Utilities for tedana package
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Sums arrays in arrs |
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Compute Dice’s similarity index between two numpy arrays. |
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Returns the power spectrum and corresponding frequencies when provided with a component time course and repitition time. |
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Takes input data and returns a sample x time array |
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Makes map of data specifying longest echo a voxel can be sampled with |
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Cluster-extent threshold and binarize image. |
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Unmasks data using non-zero entries of mask |
Convert seconds to milliseconds. |
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Convert milliseconds to seconds. |