Legacy versions of spm1d (0.1, 0.2 and M.0.1) are neither supported not available for download.
This document simply provides release information for users interested in spm1d’s developmental history.
Version 0.3 (Python and MATLAB)¶
Click here for descriptions of new features.
As of version 0.3 all version history notes now exist on spm1d’s github site.
Version 0.2 (Python)¶
Detailed inference information
Version 0.2.0006 (2014.07.09): Added a “h0reject” attribute to SPM inference objects to specify null hypothesis rejection decision.
Version 0.2.0005 (2014.06.24): Fixed a plotting bug which generated a “No paths provided” error if (a) an SPM object contains no suprathreshold clusters and (b) plotting is conducted in Spyder for Windows.
Version 0.2.0004 (2014.06.11): Added data check to all stats routines, including checks for zero variance nodes.
Version 0.2.0003 (2014.06.04): Updated to be be compatible with scipy version 0.14
Version 0.2.0002 (2014.05.27): Fixed a bug which returned p values of 2.0 when the entire field exceeds the threshold
Version 0.2.0001 (2014.05.25)
plotting functions now automatically scale the axis y limits by default
fixed a bug in one-way ANOVA which produced an error when testing more than three treatments/groups
fixed a bug in two-way ANOVA (main effects model) which produced an error when testing more than two levels of Factor A
Version M.0.1 (MATLAB)¶
Version M0.2.0005 (2014.11.28): Fixed an infinite value bug in ./spm1d/spm8/inference/spm_uc_RF.m to be compatible with recent Matlab versions.
Version M0.1.0004 (2014.07.09): Added a “h0reject” field to SPM inference structures to specify null hypothesis rejection decision.
Version M0.1.0003 (2014.06.27): Fixed an “extents” error that can appear when running ANOVA.
Version M0.1.0002 (2014.06.10): Added a feature: SPM inference structures now include cluster extents.
Version M0.1.0001 (2014.05.29): Fixed a bug which returned p values of NaN when the entire field exceeds the threshold
Version 0.1 (Python)¶
Basic data IO, plotting, and statistical tests (t tests, regression, one-way ANOVA, and general linear modelling).