diff --git a/rapidtide/workflows/rapidtide.py b/rapidtide/workflows/rapidtide.py index 7d99686f..ab9f9101 100755 --- a/rapidtide/workflows/rapidtide.py +++ b/rapidtide/workflows/rapidtide.py @@ -44,7 +44,7 @@ import rapidtide.miscmath as tide_math import rapidtide.multiproc as tide_multiproc import rapidtide.peakeval as tide_peakeval -import rapidtide.refineregressor as tide_refine +import rapidtide.refineregressor as tide_refineregressor import rapidtide.resample as tide_resample import rapidtide.simfuncfit as tide_simfuncfit import rapidtide.stats as tide_stats @@ -2663,7 +2663,7 @@ def rapidtide_main(argparsingfunc): lagfails, sigmafails, numinmask, - ) = tide_refine.makerefinemask( + ) = tide_refineregressor.makerefinemask( lagstrengths, lagtimes, lagsigma, @@ -2686,7 +2686,7 @@ def rapidtide_main(argparsingfunc): # align timecourses to prepare for refinement alignvoxels_func = addmemprofiling( - tide_refine.alignvoxels, + tide_refineregressor.alignvoxels, optiondict["memprofile"], "before aligning voxel timecourses", ) @@ -2715,7 +2715,7 @@ def rapidtide_main(argparsingfunc): LGR.info(f"align complete: {voxelsprocessed_rra=}") LGR.info("prenormalizing timecourses") - tide_refine.prenorm( + tide_refineregressor.prenorm( paddedshiftedtcs, refinemask, lagtimes, @@ -2729,7 +2729,7 @@ def rapidtide_main(argparsingfunc): ( voxelsprocessed_rr, paddedoutputdata, - ) = tide_refine.dorefine( + ) = tide_refineregressor.dorefine( paddedshiftedtcs, refinemask, weights, diff --git a/setup.cfg b/setup.cfg index e5f8ffbe..158b8402 100644 --- a/setup.cfg +++ b/setup.cfg @@ -66,7 +66,7 @@ py_modules = rapidtide/glmpass rapidtide/dlfilter rapidtide/wiener - rapidtide/refine + rapidtide/refineregressor rapidtide/_version rapidtide/workflows/parser_funcs rapidtide/workflows/aligntcs