1.2.2

Bug fixes

• Fix issue with BOLD to T1w registration (#230, #238, #239)
• Also detect exclude.json files that are placed in the reports/ folder (#228)
• Improve error message when the FreeSurfer license file is missing (#231)
• Fix a rare calculation error for fd_mean and related image quality metrics (#237, #241)
• Fix various warning messages (#247)
• Fix performance issue when collecting inputs for group statistics ()
• Fix a user interface issue where the option Start over after models was missing (#259, #260)
• Fix an issue where sub- prefixes were not recognized correctly when filtering inputs for group statistics (#264)
• Fix an issue when writing mixed data type columns to the text files in the reports/ folder (#274)
• Fix warnings for missing quality check information (#276)
• Fix errors when aggregating subjects with different numbers of scans during group statistics (#280)
• Fix error when fMRIPrep skips a BOLD file (#285)

Maintenance

• Bump indexed_gzip (#240)
• Bump nipype after bug fix (#255)
• Bump fmriprep after bug fix (#262)
• Upgrade to Python 3.10, clean up code and add more unit tests (#269)
• Make continuous integration tests run faster (#282, #284)
• Add type checking and linting to continuous integration (#285)

1.2.1

Bug fixes

• Fix issues that occurred after re-scaling fd_perc to be percent (#217)
• Catch error when NaN values occur within the linear algebra code (#215)
• Reduce memory usage when running large workflows by only loading the
  chunks that will be necessary for the current process (#216)
• Improve memory usage prediction for cluster submission scripts (#219)
• Update metadata module with better log messages (#220)

1.2.0

New features and enhancements

• Improve the assignment of field maps to functional scans, print
  warnings when detecting an incomplete field map or when a complete
  field map is not recognized by fMRIPrep (#115 and #192)
• Remove conditions that have no events from the task-based model. This
  is important for designs where the conditions depend on subject
  performance (#90)
• Output additional images during group mode. Voxel-wise descriptive
  statistics (#142), typical subject-level variance (#148)
• Divide outputs into subfolders to make navigating the files easier
• Output metadata to sidecar files, including resolution, field-of-view
  and field map type (#154 and #181)
• Add an option to skip dummy/non-steady-state scans and modify event
  onsets accordingly (#167, #176, #182 and #187)
• Improve performance during workflow creation (#192)

Bug fixes

• Update fMRIPrep to fix normalization bug (#51)
• Improve memory usage prediction. Fixes BrokenProcessPool and
  Killed: 137 errors (#125, #156 and #157)
• Refactor Dockerfile to correctly re-build matplotlib caches
  (#107)
• Fix assignment of event files to functional scans. Make sure that the
  assignment is consistent between what is shown in the user interface
  and during workflow creation. Add unit tests (#139)
• Fix crashes for datasets deviating from the BIDS specification
  and remove misleading warnings for incompatible and hidden files
• Fix AssertionError crash when no group model is specified
• Rephrase user interface for loading .mat event files. Do not say
  that the time unit (seconds or scans) is missing, which was
  confusing.
• Fix various crashes when running on a cluster
• Fix user interface crash when no categorical variables are defined in
  a spreadsheet
• Fix loading subject-level results during group model. Get rid of
  LoadResult nodes, instead use a subclass of Node (#137)
• Use slower but more robust least-squares solve for group statistics
  (#141)
• Fix performance issue during t2z_convert procedure during group
  statistics (#143, #144 and #145)
• Remove output from heterogeneity group statistics that was causing
  performance issues (#146)
• Fix confusing EOFError message on exit by gracefully stopping
  child processes before exit (#130 and #160)
• Fix running FreeSurfer with run_reconall option (#87)
• Add error message when running on an unsupported file system such as
  FAT (#102)
• Fix confusing error message when no features are specified (#147)
• Re-scale fd_perc output to percent (#186)
• Reduce user interface memory usage (#191)
• Fix automated testing hanging on the logging worker (#192)

Maintenance

• Update Python to version 3.8
• Update templateflow, pybids, nibabel
• Pin dipy version due to incompatibility with nipype
• Pin indexed_gzip version due to incompatibility of newer version
  with some files (#85)
• Add new Singularity container build workflow (#97 and #138)
• Improve documentation to suggest running Singularity with
  --containall instead of --no-home --cleanenv
• Refactor code to use defaultdict to increase readability
• Add more type hints
• Rename main branch from master to main
• Add pre-commit and pip-tools to better manage dependencies
• Install as many dependencies as possible via conda and the rest
  via pip (#164)
• Refactor workflow code to allow handling of surface-based functional
  images (#161)
• In-progress refactor model package into schema package. Use
  dataclasses for better integration with type checkers (#173, #174
  and #178)

1.2.0rc2

1.2.0rc2

1.2.0rc1

1.2.0rc1

1.1.1

Enhancements

• Add user interface checks for slice timing so that errors in configuration can be detected before running
• Reduce memory usage

Bug fixes

• Fix using curly brackets in a tag regex, for example /data/{subject:[0-9]{5}}.nii.gz
• Fix disabling the high pass filter for task-based feature extraction
• Fix performance issue with importing large BIDS datasets that contain field maps
• Fix matplotlib error (#107)
• Fix performance issue for large datasets (#105)

1.1.0

With many thanks to @jstaph for contributions

New features and enhancements

• Create high-performance computing cluster submission scripts for Torque/PBS
  and SGE cluster as well (#71)
• Calculate additional statistics such as heterogeneity
  (https://doi.org/fzx69f) and a test that data is
  missing-completely-at-random via logistic regression (#67)
• Always enable ICA-AROMA even when its outputs are not required for feature
  extraction so that its report image is always available for quality assessment
  (#75)
• Support loading presets or plugins that may make it easier to do harmonized
  analyses across many sites (#8)
• Support adding derivatives of the HRF to task-based GLM design matrices
• Support detecting the amount of available memory when running as a cluster
  job, or when running as a container with a memory limit such as when using
  Docker on Mac

Maintenance

• Add type hints to code. This allows a type checker like pyright to suggest
  possible error sources ahead of time, making programming more efficient
• Add openpyxl and xlsxwriter dependencies to support reading/writing Excel
  XLSX files
• Update numpy, scipy and nilearn versions
• Add additional automated tests

Bug fixes

• Fix importing slice timing information from a file after going back to the
  prompt via undo (#55)
• Fix a warning when loading task event timings from a MAT-file.
  NiftiheaderLoader tried to load metadata for it like it would for a NIfTI file
  (#56)
• Fix numpy array broadcasting error when loading data from 3D NIfTI files
  that have been somehow marked as being four-dimensional
• Fix misunderstanding of the output value resels of FSL's smoothest
  command. The value refers to the size of a resel, not the number of them in
  the image. The helper function _critical_z now taked this into account now.
  (nipy/nipype#3316)
• Fix naming of output files in derivatives/halfpipe and grouplevel folder
  so that capitalization is consistent with original IDs and names (#57)
• Fix the summary display after BIDS import to show the number of "subjects"
  and not the number of "subs"
• Fix getting the required metadata fields for an image type by implementing a
  helper function
• Fix outputting source files for the quality check web app (#62)
• Fix assigning field maps to specific functional images, which is done by a
  mapping between field map taks and functional image tags. The mapping is
  automatically inferred for BIDS datasets and manually specified otherwise
  (#66)
• Force re-calculation of nipype workflows after HALFpipe update so that
  changes from the new version are applied in existing working directories as
  well
• Do not fail task-based feature extraction if no events are available for a
  particular condition for a particular subject (#58)
• Force using a recent version of the indexed_gzip dependency to avoid error
  (#85)
• Improve loading delimited data in loadspreadsheet function
• Fix slice timing calculation in user interface

1.1.0rc1

• Performance improvements for large datasets

• Improve running on SGE and Torque/PBS clusters

• Bug fixes

• Does not fail even when events are missing for a condition for a participant

• Check missing-completely-at-random assumption via logistic regression at group level

1.0.1

Release 1.0.1

1.0.0

Merge pull request #42 from HippocampusGirl/rel/1.0.0

Make release 1.0