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ENH: added Apply VDM functionality to FieldMap SPM interface #3394

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Merged
merged 13 commits into from
Oct 21, 2021
Merged

ENH: added Apply VDM functionality to FieldMap SPM interface #3394

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5df9ce8
merged my changes from 2019 into the new version of nipype
Oct 18, 2021
bb56150
Merge remote-tracking branch 'upstream/master'
Oct 19, 2021
a57cdc2
run the make check-before-commit and edited the .zenodo file
Oct 19, 2021
674e9b0
run black on the preprocess.py file to improve formatting
Oct 20, 2021
411b58b
Revert "run the make check-before-commit and edited the .zenodo file"
Oct 20, 2021
65863b8
added my name to zenodo
Oct 20, 2021
7929843
test_auto_FieldMap.py automatically added
Oct 20, 2021
83fda45
separate apply and calculate VDM in two classes
Oct 20, 2021
9bcf65c
added auto tests
Oct 20, 2021
2e4bc83
now black-reformatted
Oct 20, 2021
f791fc1
* edited preprocess according to nipype team suggestions
Oct 21, 2021
f50b1ca
auto tests added to commit
Oct 21, 2021
4575810
Update nipype/interfaces/spm/preprocess.py
fabioboh Oct 21, 2021
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5 changes: 5 additions & 0 deletions .zenodo.json
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Expand Up @@ -313,6 +313,11 @@
"name": "Geisler, Daniel",
"orcid": "0000-0003-2076-5329"
},
{
"affiliation": "Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universit\u00e4t Dresden, Dresden, Germany",
"name": "Bernardoni, Fabio",
"orcid": "0000-0002-5112-405X"
},
{
"name": "Salvatore, John"
},
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2 changes: 1 addition & 1 deletion Makefile
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Expand Up @@ -2,7 +2,7 @@
# Files are then pushed to sourceforge using rsync with a command like this:
# rsync -e ssh nipype-0.1-py2.5.egg cburns,nipy@frs.sourceforge.net:/home/frs/project/n/ni/nipy/nipype/nipype-0.1/

PYTHON ?= python
PYTHON ?= python3

.PHONY: zipdoc sdist egg upload_to_pypi trailing-spaces clean-pyc clean-so clean-build clean-ctags clean in inplace test-code test-coverage test html specs check-before-commit check gen-base-dockerfile gen-main-dockerfile gen-dockerfiles

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72 changes: 17 additions & 55 deletions nipype/algorithms/tests/test_auto_ACompCor.py
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Expand Up @@ -4,56 +4,24 @@

def test_ACompCor_inputs():
input_map = dict(
components_file=dict(
usedefault=True,
),
failure_mode=dict(
usedefault=True,
),
components_file=dict(usedefault=True),
failure_mode=dict(usedefault=True),
header_prefix=dict(),
high_pass_cutoff=dict(
usedefault=True,
),
ignore_initial_volumes=dict(
usedefault=True,
),
high_pass_cutoff=dict(usedefault=True),
ignore_initial_volumes=dict(usedefault=True),
mask_files=dict(),
mask_index=dict(
requires=["mask_files"],
xor=["merge_method"],
),
mask_index=dict(requires=["mask_files"], xor=["merge_method"]),
mask_names=dict(),
merge_method=dict(
requires=["mask_files"],
xor=["mask_index"],
),
num_components=dict(
xor=["variance_threshold"],
),
pre_filter=dict(
usedefault=True,
),
realigned_file=dict(
extensions=None,
mandatory=True,
),
regress_poly_degree=dict(
usedefault=True,
),
merge_method=dict(requires=["mask_files"], xor=["mask_index"]),
num_components=dict(xor=["variance_threshold"]),
pre_filter=dict(usedefault=True),
realigned_file=dict(extensions=None, mandatory=True),
regress_poly_degree=dict(usedefault=True),
repetition_time=dict(),
save_metadata=dict(
usedefault=True,
),
save_pre_filter=dict(
usedefault=True,
),
use_regress_poly=dict(
deprecated="0.15.0",
new_name="pre_filter",
),
variance_threshold=dict(
xor=["num_components"],
),
save_metadata=dict(usedefault=True),
save_pre_filter=dict(usedefault=True),
use_regress_poly=dict(deprecated="0.15.0", new_name="pre_filter"),
variance_threshold=dict(xor=["num_components"]),
)
inputs = ACompCor.input_spec()

Expand All @@ -64,15 +32,9 @@ def test_ACompCor_inputs():

def test_ACompCor_outputs():
output_map = dict(
components_file=dict(
extensions=None,
),
metadata_file=dict(
extensions=None,
),
pre_filter_file=dict(
extensions=None,
),
components_file=dict(extensions=None),
metadata_file=dict(extensions=None),
pre_filter_file=dict(extensions=None),
)
outputs = ACompCor.output_spec()

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21 changes: 4 additions & 17 deletions nipype/algorithms/tests/test_auto_ActivationCount.py
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Expand Up @@ -3,14 +3,7 @@


def test_ActivationCount_inputs():
input_map = dict(
in_files=dict(
mandatory=True,
),
threshold=dict(
mandatory=True,
),
)
input_map = dict(in_files=dict(mandatory=True), threshold=dict(mandatory=True))
inputs = ActivationCount.input_spec()

for key, metadata in list(input_map.items()):
Expand All @@ -20,15 +13,9 @@ def test_ActivationCount_inputs():

def test_ActivationCount_outputs():
output_map = dict(
acm_neg=dict(
extensions=None,
),
acm_pos=dict(
extensions=None,
),
out_file=dict(
extensions=None,
),
acm_neg=dict(extensions=None),
acm_pos=dict(extensions=None),
out_file=dict(extensions=None),
)
outputs = ActivationCount.output_spec()

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16 changes: 3 additions & 13 deletions nipype/algorithms/tests/test_auto_AddCSVColumn.py
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Expand Up @@ -6,14 +6,8 @@ def test_AddCSVColumn_inputs():
input_map = dict(
extra_column_heading=dict(),
extra_field=dict(),
in_file=dict(
extensions=None,
mandatory=True,
),
out_file=dict(
extensions=None,
usedefault=True,
),
in_file=dict(extensions=None, mandatory=True),
out_file=dict(extensions=None, usedefault=True),
)
inputs = AddCSVColumn.input_spec()

Expand All @@ -23,11 +17,7 @@ def test_AddCSVColumn_inputs():


def test_AddCSVColumn_outputs():
output_map = dict(
csv_file=dict(
extensions=None,
),
)
output_map = dict(csv_file=dict(extensions=None))
outputs = AddCSVColumn.output_spec()

for key, metadata in list(output_map.items()):
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14 changes: 2 additions & 12 deletions nipype/algorithms/tests/test_auto_AddCSVRow.py
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Expand Up @@ -4,13 +4,7 @@

def test_AddCSVRow_inputs():
input_map = dict(
_outputs=dict(
usedefault=True,
),
in_file=dict(
extensions=None,
mandatory=True,
),
_outputs=dict(usedefault=True), in_file=dict(extensions=None, mandatory=True)
)
inputs = AddCSVRow.input_spec()

Expand All @@ -20,11 +14,7 @@ def test_AddCSVRow_inputs():


def test_AddCSVRow_outputs():
output_map = dict(
csv_file=dict(
extensions=None,
),
)
output_map = dict(csv_file=dict(extensions=None))
outputs = AddCSVRow.output_spec()

for key, metadata in list(output_map.items()):
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33 changes: 7 additions & 26 deletions nipype/algorithms/tests/test_auto_AddNoise.py
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Expand Up @@ -4,27 +4,12 @@

def test_AddNoise_inputs():
input_map = dict(
bg_dist=dict(
mandatory=True,
usedefault=True,
),
dist=dict(
mandatory=True,
usedefault=True,
),
in_file=dict(
extensions=None,
mandatory=True,
),
in_mask=dict(
extensions=None,
),
out_file=dict(
extensions=None,
),
snr=dict(
usedefault=True,
),
bg_dist=dict(mandatory=True, usedefault=True),
dist=dict(mandatory=True, usedefault=True),
in_file=dict(extensions=None, mandatory=True),
in_mask=dict(extensions=None),
out_file=dict(extensions=None),
snr=dict(usedefault=True),
)
inputs = AddNoise.input_spec()

Expand All @@ -34,11 +19,7 @@ def test_AddNoise_inputs():


def test_AddNoise_outputs():
output_map = dict(
out_file=dict(
extensions=None,
),
)
output_map = dict(out_file=dict(extensions=None))
outputs = AddNoise.output_spec()

for key, metadata in list(output_map.items()):
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70 changes: 17 additions & 53 deletions nipype/algorithms/tests/test_auto_ArtifactDetect.py
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Expand Up @@ -4,61 +4,25 @@

def test_ArtifactDetect_inputs():
input_map = dict(
bound_by_brainmask=dict(
usedefault=True,
),
global_threshold=dict(
usedefault=True,
),
intersect_mask=dict(
usedefault=True,
),
mask_file=dict(
extensions=None,
),
bound_by_brainmask=dict(usedefault=True),
global_threshold=dict(usedefault=True),
intersect_mask=dict(usedefault=True),
mask_file=dict(extensions=None),
mask_threshold=dict(),
mask_type=dict(
mandatory=True,
),
mask_type=dict(mandatory=True),
norm_threshold=dict(
mandatory=True,
xor=["rotation_threshold", "translation_threshold"],
),
parameter_source=dict(
mandatory=True,
),
plot_type=dict(
usedefault=True,
),
realigned_files=dict(
mandatory=True,
),
realignment_parameters=dict(
mandatory=True,
),
rotation_threshold=dict(
mandatory=True,
xor=["norm_threshold"],
),
save_plot=dict(
usedefault=True,
),
translation_threshold=dict(
mandatory=True,
xor=["norm_threshold"],
),
use_differences=dict(
maxlen=2,
minlen=2,
usedefault=True,
),
use_norm=dict(
requires=["norm_threshold"],
usedefault=True,
),
zintensity_threshold=dict(
mandatory=True,
),
mandatory=True, xor=["rotation_threshold", "translation_threshold"]
),
parameter_source=dict(mandatory=True),
plot_type=dict(usedefault=True),
realigned_files=dict(mandatory=True),
realignment_parameters=dict(mandatory=True),
rotation_threshold=dict(mandatory=True, xor=["norm_threshold"]),
save_plot=dict(usedefault=True),
translation_threshold=dict(mandatory=True, xor=["norm_threshold"]),
use_differences=dict(maxlen=2, minlen=2, usedefault=True),
use_norm=dict(requires=["norm_threshold"], usedefault=True),
zintensity_threshold=dict(mandatory=True),
)
inputs = ArtifactDetect.input_spec()

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10 changes: 2 additions & 8 deletions nipype/algorithms/tests/test_auto_CalculateMedian.py
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Expand Up @@ -4,11 +4,7 @@

def test_CalculateMedian_inputs():
input_map = dict(
in_files=dict(),
median_file=dict(),
median_per_file=dict(
usedefault=True,
),
in_files=dict(), median_file=dict(), median_per_file=dict(usedefault=True)
)
inputs = CalculateMedian.input_spec()

Expand All @@ -18,9 +14,7 @@ def test_CalculateMedian_inputs():


def test_CalculateMedian_outputs():
output_map = dict(
median_files=dict(),
)
output_map = dict(median_files=dict())
outputs = CalculateMedian.output_spec()

for key, metadata in list(output_map.items()):
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13 changes: 3 additions & 10 deletions nipype/algorithms/tests/test_auto_CalculateNormalizedMoments.py
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Expand Up @@ -4,13 +4,8 @@

def test_CalculateNormalizedMoments_inputs():
input_map = dict(
moment=dict(
mandatory=True,
),
timeseries_file=dict(
extensions=None,
mandatory=True,
),
moment=dict(mandatory=True),
timeseries_file=dict(extensions=None, mandatory=True),
)
inputs = CalculateNormalizedMoments.input_spec()

Expand All @@ -20,9 +15,7 @@ def test_CalculateNormalizedMoments_inputs():


def test_CalculateNormalizedMoments_outputs():
output_map = dict(
moments=dict(),
)
output_map = dict(moments=dict())
outputs = CalculateNormalizedMoments.output_spec()

for key, metadata in list(output_map.items()):
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