#16 Start thinking on tiny morphologist use case implementation

bv_use_cases/tiny_morphologist/__init__.py

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+from soma.controller import field, file
+from capsul.api import Process, Pipeline
+
+
+class BiasCorrection(Process):
+    input: field(type_=file())
+    strength: float = 0.8
+    output: field(type_=file(), output=True)
+
+    def execute(self):
+        with open(self.input) as f:
+            content = self.read()
+        content = f'{content}\nBias correction with strength={self.strength}'
+        with open(self.output, 'w') as f:
+            f.write(content)
+
+class SPMNormalization(Process):
+    input: field(type_=file())
+    template: field(type_=file())
+    output: field(type_=file(), output=True)
+
+    def execute(self):
+        with open(self.input) as f:
+            content = self.read()
+        content = f'{content}\nSPM normalization with template "{self.template}"'
+        with open(self.output, 'w') as f:
+            f.write(content)
+
+class AimsNormalization(Process):
+    input: field(type_=file())
+    origin: field(type_=list[float], default_factory=lambda: [1.2, 3.4, 5.6])
+    output: field(type_=file(), output=True)
+
+    def execute(self):
+        with open(self.input) as f:
+            content = self.read()
+        content = f'{content}\nSPM normalization with origin={self.origin}'
+        with open(self.output, 'w') as f:
+            f.write(content)
+
+class SplitBrain(Process):
+    input: field(type_=file())
+    right_output: field(type_=file(), output=True)
+    left_output: field(type_=file(), output=True)
+
+    def execute(self):
+        with open(self.input) as f:
+            content = self.read()
+        content = f'{content}\nBias correction with strength={self.strength}'
+        with open(self.output, 'w') as f:
+            f.write(content)
+
+
+class ProcessHemisphere(Process):
+    input: field(type_=file())
+    output: field(type_=file(), output=True)
+
+    def execute(self):
+        with open(self.input) as f:
+            content = self.read()
+        content = f'{content}\nProcess hemisphere'
+        with open(self.output, 'w') as f:
+            f.write(content)
+
+class TinyMorphologist(Pipeline):
+    def pipeline_definition(self):
+        self.add_process('nobias', BiasCorrection)
+        self.add_switch('normalization', ['none', 'spm', 'aims'], ['output'])
+        self.add_process('spm_normalization', SPMNormalization)
+        self.add_process('aims_normalization', AimsNormalization)
+        self.add_process('split', SplitBrain)
+        self.add_process('right_hemi', ProcessHemisphere)
+        self.add_process('left_hemi', ProcessHemisphere)
+
+        self.add_link('nobias.output->normalization.none_switch_output')
+
+        self.add_link('nobias.output->spm_normalization.input')
+        self.add_link('spm_normalization.output->normalization.spm_switch_output')
+
+        self.add_link('nobias.output->aims_normalization.input')
+        self.add_link('aims_normalization.output->normalization.aims_switch_output')
+
+        self.add_link('normalization.output->split.input')
+        self.add_link('split.right_output->right_hemi.input')
+        self.export_parameter('right_hemi', 'output', 'right_hemisphere')
+        self.add_link('split.left_output->left_hemi.input')
+        self.export_parameter('left_hemi', 'output', 'left_hemisphere')
+
+

bv_use_cases/tiny_morphologist/__main__.py

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+import os
+import shutil
+import tempfile
+from bv_use_cases import tiny_morphologist
+
+from capsul.api import Capsul
+
+subjects = (
+    'aleksander',
+    'casimiro',
+    'christophorus',
+    'christy',
+    'conchobhar',
+    'cornelia',
+    'dakila',
+    'demosthenes',
+    'devin',
+    'ferit',
+    'gautam',
+    'hikmat',
+    'isbel',
+    'ivona',
+    'jordana',
+    'justyn',
+    'katrina',
+    'lyda',
+    'melite',
+    'mina',
+    'odalric',
+    'rainbow',
+    'rashn',
+    'shufen',
+    'simona',
+    'svanhildur',
+    'thilini',
+    'til',
+    'vanessza',
+    'victoria'
+)
+
+# Create temporary directory for the use case
+tmp = tempfile.mkdtemp()
+try:
+    # Create BIDS directory
+    bids = f'{tmp}/bids'
+    # Write Capsul specific information
+    os.mkdir(bids)
+    with open(f'{bids}/capsul.json', 'w') as f:
+        json.dump({
+            'paths_layout': 'bids-1.6'
+        }, f)
+
+    # Create BrainVISA directory
+    brainvisa = f'{tmp}/brainvisa'
+    os.mkdir(brainvisa)
+    # Write Capsul specific information
+    with open(f'{brainvisa}/capsul.json', 'w') as f:
+        json.dump({
+            'paths_layout': 'brainvisa-6.0'
+        }, f)
+
+    # Generate fake T1 and T2 data in bids directory
+    for subject in subjects:
+        for session in ('m0', 'm12', 'm24'):
+            for data_type in ('T1w', 'T2w'):
+                file = f'{bids}/rawdata/sub-{subject}/ses-{session}/anat/sub-{subject}_ses-{session}_{data_type}.nii'
+                d = os.path.dirname(file)
+                if not os.path.exists(d):
+                    os.makedirs(d)
+                with open(file, 'w') as f:
+                    print(f'{data_type} acquisition for subject {subject} acquired in session {session}', file=f)
+
+    capsul = Capsul()
+    # Input dataset is declared as following BIDS organization in capsul.json
+    # therefore a BIDS specific object is returned
+    input_dataset = capsul.dataset(bids)
+    # Output dataset is declared as following BrainVISA organization in capsul.json
+    # therefore a BrainVISA specific object is returned
+    output_dataset = capsul.dataset(brainvisa)
+    # Create a main pipeline that will contain all the morphologist pipelines
+    # we want to execute
+    processing_pipeline = capsul.custom_pipeline()
+    # Parse the dataset with BIDS-specific query (here "suffix" is part
+    #  of BIDS specification). The object returned contains info for main
+    # BIDS fields (sub, ses, acq, etc.)
+    for t1_mri in dataset.find(suffix='T1w'):
+        # Create a TinyMorphologist pipeline
+        tiny_morphologist = capsul.executable('bv_use_cases.tiny_morphologist.TinyMorphologist')
+        # Set the input data
+        tiny_morphologist.input = t1_mri.path
+        # Complete outputs following BraiVISA organization
+        # Make the link between BIDS metadata and BrainVISA metadata 
+        output_dataset.set_output_paths(tiny_morphologist,
+            subject=t1_mri.sub,
+            acquisition=t1_mri.acq,
+        )
+        # Add the current TinyMorhpologist pipeline to the main
+        # pipeline that will be executed
+        custom_pipeline.add_executable(tiny_morphologist)
+    # Finally execute all the TinyMorphologist instances
+    capsul.run(processing_pipeline)
+finally:
+    shutil.rmtree(tmp)