cpp-lln-lab · Remi-Gau · Sep 17, 2023 · Aug 26, 2023 · Aug 26, 2023 · Aug 26, 2023
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -55,11 +55,6 @@ repos:
   - id: black
     args: [--config=pyproject.toml]
 
-- repo: https://github.com/asottile/setup-cfg-fmt
-  rev: v2.4.0
-  hooks:
-  - id: setup-cfg-fmt
-
 - repo: https://github.com/asottile/pyupgrade
   rev: v3.10.1
   hooks:

diff --git a/demos/face_repetition/test_face_rep.m b/demos/face_repetition/test_face_rep.m
@@ -48,7 +48,7 @@
   %  resolutions_to_test = 2;
 end
 
-parfor iResolution = 1:numel(resolutions_to_test)
+for iResolution = 1:numel(resolutions_to_test)
 
   this_res = resolutions_to_test(iResolution);
 

diff --git a/demos/openneuro/ds000001_aroma_run.m b/demos/openneuro/ds000001_aroma_run.m
@@ -6,7 +6,7 @@
 clear;
 clc;
 
-COPY = false;
+COPY = true;
 SUBJECT_LEVEL_DO = true;
 
 addpath(fullfile(pwd, '..', '..'));

diff --git a/demos/openneuro/models/model-ds000114_desc-testRetestVerbal_smdl.json b/demos/openneuro/models/model-ds000114_desc-testRetestVerbal_smdl.json
@@ -4,7 +4,8 @@
   "Description": "BIDS stats model for linebisection / oververbgeneration / overwordrepetition / covertverbgeneration tasks",
   "Input": {
     "task": [
-      "overtverbgeneration"
+      "overtverbgeneration",
+      "overtwordrepetition"
     ],
     "space": [
       "MNI152NLin2009cAsym"

diff --git a/lib/utils/range.m b/lib/utils/range.m
@@ -0,0 +1,22 @@
+function y = range(x,dim)
+% Sample range.
+%
+% USAGE::
+%
+%   Y = range(X) returns the range of the values in X.
+%
+%   For a vector input, Y is the difference between the maximum and minimum values
+%   For a matrix input, Y is a vector containing the range for each column.
+%   For N-D arrays, range operates along the first non-singleton dimension.
+%
+%   range treats NaNs as missing values, and ignores them.
+%
+%   Y = range(X,DIM) operates along the dimension DIM.
+%
+
+
+if nargin < 2
+    y = max(x) - min(x);
+else
+    y = max(x,[],dim) - min(x,[],dim);
+end
diff --git a/pyproject.toml b/pyproject.toml
@@ -22,6 +22,7 @@ requires-python = ">=3.8"
 dependencies = [
     "bsmschema",
     "rich",
+    "rich-argparse"
 ]
 classifiers = [
     "Development Status :: 3 - Alpha",
@@ -126,5 +127,6 @@ module = [
     "bsmschema.models",
     "rich",
     "rich.logging",
+    "rich_argparse",
 ]
 ignore_missing_imports = true
diff --git a/src/batches/stats/setBatchEstimateModel.m b/src/batches/stats/setBatchEstimateModel.m
@@ -1,16 +1,19 @@
-function matlabbatch = setBatchEstimateModel(matlabbatch, opt, nodeName, contrastsList, groups)
+function matlabbatch = setBatchEstimateModel(matlabbatch, opt, tmp, contrastsList, groups)
   %
   % Set up the estimate model batch for run/subject or group level GLM
   %
   % USAGE::
   %
-  %   matlabbatch = setBatchEstimateModel(matlabbatch, opt)
+  %   % for subject level
+  %   matlabbatch = setBatchEstimateModel(matlabbatch, opt, subLabel)
+  %
+  %   % for group level
   %   matlabbatch = setBatchEstimateModel(matlabbatch, opt, nodeName, contrastsList, groups)
   %
   % :param matlabbatch:
   % :type  matlabbatch: structure
   %
-  % :type opt:  structure
+  % :type  opt:  structure
   % :param opt: Options chosen for the analysis.
   %             See checkOptions.
   %
@@ -29,29 +32,40 @@
   switch nargin
 
     % run  / subject level
-    case 2
+    case 3
+
+      subLabel = tmp;
+
+      outputDir = getFFXdir(subLabel, opt);
 
       printBatchName('estimate subject level fmri model', opt);
 
       if iscell(matlabbatch)
+        opt.orderBatches.specify = 1;
+
         spmMatFile = cfg_dep('fMRI model specification SPM file', ...
-                             substruct( ...
-                                       '.', 'val', '{}', {1}, ...
+                             substruct('.', 'val', '{}', {opt.orderBatches.specify}, ...
                                        '.', 'val', '{}', {1}, ...
                                        '.', 'val', '{}', {1}), ...
                              substruct('.', 'spmmat'));
 
       elseif ischar(matlabbatch) && isdir(matlabbatch)
-        outputDir = matlabbatch;
         spmMatFile = {fullfile(outputDir, 'SPM.mat')};
         matlabbatch = {};
       end
 
       matlabbatch = returnEstimateModelBatch(matlabbatch, spmMatFile, opt);
 
+      opt.orderBatches.estimate = numel(matlabbatch);
+      matlabbatch = setBatchGoodnessOfFit(matlabbatch, opt);
+
+      matlabbatch = setBatchInformationCriteria(matlabbatch, opt, outputDir);
+
       % group level
     case 5
 
+      nodeName = tmp;
+
       if ischar(contrastsList)
         contrastsList = cellstr(contrastsList);
       end
@@ -76,8 +90,11 @@
         opt.QA.glm.do = false();
 
         matlabbatch = returnEstimateModelBatch(matlabbatch, spmMatFile, opt);
+        opt.orderBatches.estimate = numel(matlabbatch);
+        matlabbatch = setBatchGoodnessOfFit(matlabbatch, opt);
+        matlabbatch = setBatchInformationCriteria(matlabbatch, opt, rfxDir);
 
-        matlabbatch{end + 1}.spm.stats.review.spmmat = spmMatFile;
+        matlabbatch{end + 1}.spm.stats.review.spmmat = spmMatFile; %#ok<*AGROW>
         matlabbatch{end}.spm.stats.review.display.matrix = 1;
         matlabbatch{end}.spm.stats.review.print = false;
 
@@ -89,7 +106,7 @@
 
     otherwise
 
-      error('Should have 2 or 5 inputs...');
+      error('Should have 3 or 5 inputs...');
 
   end
 

diff --git a/src/batches/stats/setBatchGoodnessOfFit.m b/src/batches/stats/setBatchGoodnessOfFit.m
@@ -0,0 +1,20 @@
+function matlabbatch = setBatchGoodnessOfFit(matlabbatch, opt)
+
+  % (C) Copyright 2023 bidspm developers
+
+  if bids.internal.is_octave()
+    % https://github.com/cpp-lln-lab/bidspm/pull/1135#issuecomment-1722455363
+    notImplemented(mfilename(), ...
+                   'Goodness of fit not implemented in Octave.', ...
+                   opt);
+    return
+  end
+
+  MA_inspect_GoF.SPM_mat(1) = cfg_dep('Model estimation: SPM.mat File', ...
+                                      returnDependency(opt, 'estimate'), ...
+                                      substruct('.', 'spmmat'));
+  MA_inspect_GoF.plot_type = 1;
+
+  matlabbatch{end + 1}.spm.tools.MACS.MA_inspect_GoF = MA_inspect_GoF;
+
+end
diff --git a/src/batches/stats/setBatchInformationCriteria.m b/src/batches/stats/setBatchInformationCriteria.m
@@ -0,0 +1,28 @@
+function matlabbatch = setBatchInformationCriteria(matlabbatch, opt, outputDir)
+
+  % (C) Copyright 2023 bidspm developers
+  MA_model_space.dir = {outputDir};
+  MA_model_space.models{1}{1}(1) = cfg_dep('Model estimation: SPM.mat File', ...
+                                           returnDependency(opt, 'estimate'), ...
+                                           substruct('.', 'spmmat'));
+  MA_model_space.names = {'GLM'};
+
+  matlabbatch{end + 1}.spm.tools.MACS.MA_model_space = MA_model_space;
+
+  MA_classic_ICs_auto.MS_mat(1) = cfg_dep('MA: define model space: model space (MS.mat file)', ...
+                                          substruct('.', 'val', '{}', {numel(matlabbatch)}, ...
+                                                    '.', 'val', '{}', {1}, ...
+                                                    '.', 'val', '{}', {1}, ...
+                                                    '.', 'val', '{}', {1}), ...
+                                          substruct('.', 'MS_mat'));
+  MA_classic_ICs_auto.ICs.AIC = 1;
+  MA_classic_ICs_auto.ICs.AICc = 0;
+  MA_classic_ICs_auto.ICs.BIC = 1;
+  MA_classic_ICs_auto.ICs.DIC = 0;
+  MA_classic_ICs_auto.ICs.HQC = 0;
+  MA_classic_ICs_auto.ICs.KIC = 0;
+  MA_classic_ICs_auto.ICs.KICc = 0;
+
+  matlabbatch{end + 1}.spm.tools.MACS.MA_classic_ICs_auto = MA_classic_ICs_auto;
+
+end
diff --git a/src/parsers.py b/src/parsers.py
@@ -2,10 +2,9 @@
 
 import argparse
 import logging
-from typing import IO
 
-import rich
 from rich.logging import RichHandler
+from rich_argparse import RichHelpFormatter
 
 from . import _version  # type: ignore
 
@@ -29,24 +28,18 @@ def bidspm_log(name: str = "bidspm") -> logging.Logger:
     return logging.getLogger(name)
 
 
-class MuhParser(argparse.ArgumentParser):
-    def _print_message(self, message: str, file: IO[str] | None = None) -> None:
-        rich.print(message, file=file)
-
-
-# TODO qplit in several parsers like in matlab
-
-
-def common_parser() -> MuhParser:
-    parser = MuhParser(
+def common_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
         description="bidspm is a SPM base BIDS app",
         epilog="""
         \n- all parameters use ``snake_case``,
+
         \n- most "invalid" calls simply initialize bidspm.
 
         For a more readable version of this help section,
         see the online https://bidspm.readthedocs.io/en/latest/usage_notes.html.
         """,
+        formatter_class=RichHelpFormatter,
     )
 
     parser.add_argument(
@@ -67,8 +60,6 @@ def common_parser() -> MuhParser:
         "output_dir",
         help="""
         Fullpath to the directory where the output files will be stored.
-        If you are running group level analysis this folder should be prepopulated
-        with the results of the participant level analysis.
         """,
         nargs=1,
     )
@@ -311,7 +302,7 @@ def common_parser() -> MuhParser:
 
 def validate_parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser(
-        description="validate bids stats model",
+        description="validate bids stats model", formatter_class=RichHelpFormatter
     )
 
     parser.add_argument(

diff --git a/src/utils/returnDependency.m b/src/utils/returnDependency.m
@@ -9,21 +9,41 @@
 
   % (C) Copyright 2021 bidspm developers
 
-  handledDependencies = {'segment', 'skullStripping', 'skullStrippingMask'...
-                         'coregister', 'selectAnat', 'realign', ...
-                         'MACS_model_space', 'MACS_BMS_group_auto', ...
-                         'mean', 'smooth', 'mask', 'maskedMean', 'rename'};
+  handledDependencies = {'estoiamte', ...
+                         'segment', ...
+                         'skullStripping', ...
+                         'skullStrippingMask'...
+                         'coregister', ...
+                         'selectAnat', ...
+                         'realign', ...
+                         'MACS_model_space', ...
+                         'MACS_BMS_group_auto', ...
+                         'mean', ...
+                         'smooth', ...
+                         'mask', ...
+                         'maskedMean', ...
+                         'rename'};
 
   switch type
 
-    case {'segment', 'skullStripping', 'mean', 'smooth', 'mask', 'maskedMean', ...
-          'skullStrippingMask'}
+    case {'segment', ...
+          'skullStripping', ...
+          'mean', ...
+          'smooth', ...
+          'mask', ...
+          'maskedMean', ...
+          'skullStrippingMask', ...
+          'estimate'}
       dep = substruct('.', 'val', '{}', {opt.orderBatches.(type)}, ...
                       '.', 'val', '{}', {1}, ...
                       '.', 'val', '{}', {1});
 
-    case {'coregister', 'selectAnat', 'realign', ...
-          'MACS_model_space', 'MACS_BMS_group_auto', 'rename'}
+    case {'coregister', ...
+          'selectAnat', ...
+          'realign', ...
+          'MACS_model_space', ...
+          'MACS_BMS_group_auto', ...
+          'rename'}
       dep = substruct('.', 'val', '{}', {opt.orderBatches.(type)}, ...
                       '.', 'val', '{}', {1}, ...
                       '.', 'val', '{}', {1}, ...

diff --git a/src/workflows/stats/bidsFFX.m b/src/workflows/stats/bidsFFX.m
@@ -248,10 +248,7 @@ function checkRootNode(opt)
                                                                         'before estimation', ...
                                                                         subLabel)));
     case 'estimate'
-      if isempty(matlabbatch)
-        matlabbatch = outputDir;
-      end
-      matlabbatch = setBatchEstimateModel(matlabbatch, opt);
+      matlabbatch = setBatchEstimateModel(matlabbatch, opt, subLabel);
       matlabbatch = setBatchPrintFigure(matlabbatch, opt, ...
                                         fullfile(outputDir, ...
                                                  designMatrixFigureName(opt, ...

diff --git a/tests/data/models/model-nback_smdl.json b/tests/data/models/model-nback_smdl.json
@@ -17,12 +17,14 @@
       ],
       "Model": {
         "X": [
-          "nback"
+          "trial_type.scene*",
+          "trial_type.face*"
         ],
         "Type": "glm",
         "HRF": {
           "Variables": [
-            ""
+            "trial_type.scene*",
+            "trial_type.face*"
           ],
           "Model": "spm"
         },
@@ -36,6 +38,12 @@
               "mask"
             ]
           }
+        },
+        "Software": {
+          "SPM": {
+            "InclusiveMaskingThreshold": 0.8,
+            "SerialCorrelation": "FAST"
+          }
         }
       },
       "Contrasts": [
@@ -53,7 +61,8 @@
       "DummyContrasts": {
         "Test": "t",
         "Contrasts": [
-          ""
+          "trial_type.scene*",
+          "trial_type.face*"
         ]
       }
     },

diff --git a/tests/tests_batches/stats/test_setBatchSubjectLevelGLMSpec.m b/tests/tests_batches/stats/test_setBatchSubjectLevelGLMSpec.m
@@ -113,9 +113,9 @@ function test_setBatchSubjectLevelGLMSpec_fmriprep()
   opt = checkOptions(opt);
 
   matlabbatch = {};
-  % bids matlab issue?
-  % events.TSV are in the root of the synthetic dataset
-  % matlabbatch = setBatchSubjectLevelGLMSpec(matlabbatch, BIDS, opt, subLabel);
+
+  BIDS = getLayout(opt);
+  matlabbatch = setBatchSubjectLevelGLMSpec(matlabbatch, BIDS, opt, subLabel);
 
 end