本文整理汇总了Python中create_example_from_templates.ExampleFromTemplate类的典型用法代码示例。如果您正苦于以下问题：Python ExampleFromTemplate类的具体用法？Python ExampleFromTemplate怎么用？Python ExampleFromTemplate使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了ExampleFromTemplate类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
def main():
nidm_classes = {
"DisplayMaskMap": dict(
display_map_id="niiri:display_map_id",
label="Display Mask Map",
location="file://./DisplayMask.nii.gz",
user_defined="true",
filename="DisplayMask.nii.gz",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a..."
),
"CoordinateSpace-1": dict(
coordinate_space_id="niiri:coordinate_space_id_1",
label="Coordinate space 1",
voxel_to_world_mapping="[[-3, 0, 0, 78],[0, 3, 0, -112],[0, 0, 3, -70],[0, 0, 0, 1]]",
voxel_units="[ \\\"mm\\\", \\\"mm\\\", \\\"mm\\\" ]",
voxel_size="[ 3, 3, 3 ]",
coord_system="nidm:NIDM_0000051",
number_of_dim="3",
dimensions="[ 53, 63, 52 ]"),
"ActivityUsedEntity": dict(
activity_id="niiri:display_map_id",
activity_type="nidm:NIDM_0000049",
entity_id="niiri:height_threshold_id",
)
}
NIDM_SPM_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'spm', 'example005')
ttl_file = os.path.join(NIDM_SPM_DIR, 'nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例2: main
def main():
nidm_classes = {
"HeightThreshold_PFWE": dict(
height_threshold_id="niiri:height_threshold_id",
label="Height Threshold: p<0.05 (FWE)",
p_fwe="0.050000",
thresh_type="p-value FWE"
),
"FSL_ExtentThresholdNoType": dict(
extent_threshold_id="niiri:extent_threshold_id",
label="Extent Threshold: k>=0",
p_fwe="1.0"
),
"InferenceUsedThresh": dict(
inference_id="niiri:inference_id",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
)
}
NIDM_FSL_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'fsl', 'example002')
ttl_file = os.path.join(NIDM_FSL_DIR, 'fsl_nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例3: explicit_mask
def explicit_mask():
nidm_classes = {
"MaskMap": dict(
mask_id="niiri:explicit_mask_id",
label="Mask Map",
location="",
filename="",
user_defined="true",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="",
used_by_act_id="niiri:model_parameter_estimation_id"
),
"ActivityUsedEntity": dict(
activity_id="niiri:model_parameter_estimation_id",
activity_type=q_graph.qname(NIDM_MODEL_PARAMETERS_ESTIMATION),
entity_id="niiri:explicit_mask_id",
)
}
MIN_EX_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'test',
'minimal_examples', 'explicit_mask')
ttl_file = os.path.join(MIN_EX_DIR, 'nidm.ttl')
example = ExampleFromTemplate(
nidm_classes, ttl_file, False, remove_att=[
NIDM_IN_COORDINATE_SPACE,
PROV.atLocation, NFO.fileName, CRYPTO.sha512, DC.description])
example.create_example()示例4: f_test
def f_test():
nidm_classes = {
"ContrastExplainedMeanSquareMap": dict(
id="niiri:contrast_explained_mean_square_map_id",
label="Contrast Explained Mean Square Map",
location="file://./ContrastExplainedMeanSquareMap_F001.nii.gz",
filename="ContrastExplainedMeanSquareMap_F001.nii.gz",
format="image/nifti",
coordinate_space_id="",
sha="",
contrast_est_id="niiri:contrast_estimation_id",
),
"EntityWasGeneratedByActivity": dict(
activity_id="niiri:contrast_estimation_id",
activity_type=q_graph.qname(NIDM_CONTRAST_ESTIMATION),
entity_id="niiri:contrast_explained_mean_square_map_id",
)
}
MIN_EX_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'test',
'minimal_examples', 'f_test')
ttl_file = os.path.join(MIN_EX_DIR, 'nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False,
remove_att=[
NIDM_IN_COORDINATE_SPACE,
PROV.atLocation, CRYPTO.sha512])
example.create_example()示例5: design_matrix_event_related
def design_matrix_event_related():
nidm_classes = {
"DesignMatrix_1stLevel": dict(
design_matrix_id='niiri:design_matrix_id',
label="Design Matrix",
location="file://./DesignMatrix.csv",
format="text/csv",
filename="DesignMatrix.csv",
design_matrix_png_id="niiri:design_matrix_png_id",
regressors="",
design=q_graph.qname(NIDM_EVENT_RELATED_DESIGN),
hrf_basis="",
drift_model=""),
"ActivityUsedEntity": dict(
activity_id="niiri:model_parameter_estimation_id",
activity_type=q_graph.qname(NIDM_MODEL_PARAMETERS_ESTIMATION),
entity_id="niiri:design_matrix_id",
)
}
MIN_EX_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'test',
'minimal_examples', 'event_related_design')
ttl_file = os.path.join(MIN_EX_DIR, 'nidm.ttl')
example = ExampleFromTemplate(
nidm_classes, ttl_file, False,
remove_att=[NIDM_REGRESSOR_NAMES, NIDM_HAS_HRF_BASIS,
NIDM_HAS_DRIFT_MODEL])
example.create_example()示例6: main
def main():
nidm_classes = {
"HeightThreshold": dict(
height_threshold_id="niiri:height_threshold_id",
thresh_type=NIDM_P_VALUE_UNCORRECTED_QNAME,
label="Height Threshold: p<0.05 (uncorrected)",
value="0.050000",
),
"ExtentThresholdStat": dict(
extent_threshold_id="niiri:extent_threshold_id",
label="Extent Threshold: k>=0",
thresh_type=OBO_STATISTIC_QNAME,
cluster_size_vox="0",
),
"InferenceUsedThresh": dict(
inference_id="niiri:inference_id",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
)
}
NIDM_FSL_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'fsl', 'example003')
ttl_file = os.path.join(NIDM_FSL_DIR, 'fsl_nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例7: main
def main():
nidm_classes = {
"HeightThreshold": dict(
height_threshold_id="niiri:height_threshold_id",
thresh_type=OBO_P_VALUE_FWER_QNAME,
label="Height Threshold: p<0.05 (FWE)",
value="0.050000",
),
"ExtentThresholdStat": dict(
extent_threshold_id="niiri:extent_threshold_id",
label="Extent Threshold: k>=0",
thresh_type=OBO_STATISTIC_QNAME,
cluster_size_vox="0",
),
"InferenceUsedThresh": dict(
inference_id="niiri:inference_id",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
)
}
NIDM_FSL_DIR = os.path.join(os.path.dirname(
os.path.dirname(
os.path.abspath(__file__))), 'test', 'ground_truth',
'voxelwise_p050_fwe')
ttl_file = os.path.join(NIDM_FSL_DIR, 'nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例8: main
def main():
nidm_classes = {
"Inference": dict(
inference_id="niiri:inference_id_1",
label="Inference",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id="niiri:statistic_map_id",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
display_mask_id="niiri:display_map_id",
peak_def_id="niiri:peak_definition_criteria_id",
cluster_def_id="niiri:cluster_definition_criteria_id",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id"
),
"ConjunctionInference": dict(
conj_inference_id="niiri:conjunction_id_1",
label="Conjunction Inference",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id_1="niiri:statistic_map_id_1",
stat_map_id_2="niiri:statistic_map_id_2",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
display_mask_id="niiri:display_map_id",
peak_def_id="niiri:peak_definition_criteria_id",
cluster_def_id="niiri:cluster_definition_criteria_id",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id"
),
"SPM_KConjunctionInference": dict(
conj_inference_id="niiri:conjunction_id_2",
label="k-Conjunction Inference",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id_1="niiri:statistic_map_id_1",
stat_map_id_2="niiri:statistic_map_id_2",
global_null_degree="1",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
display_mask_id="niiri:display_map_id",
peak_def_id="niiri:peak_definition_criteria_id",
cluster_def_id="niiri:cluster_definition_criteria_id",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id"
),
}
NIDM_SPM_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'spm', "example004")
ttl_file = os.path.join(NIDM_SPM_DIR, 'spm_inference_activities.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例9: main
#.........这里部分代码省略.........
cluster_label_id="3",
cluster_size_in_resels="0.278388924695318",
p_value_unc="0.00497953247554004",
p_value_fwe="0.000255384009130943",
p_value_fdr="0.00829922079256674",
excursion_set_id="niiri:excursion_set_map_id"
),
"SupraThresholdCluster-4": dict(
cluster_id="niiri:supra_threshold_cluster_0004",
label="Supra-Threshold Cluster: 0004",
cluster_size_in_voxels="29",
cluster_label_id="4",
cluster_size_in_resels="0.218196724761195",
p_value_unc="0.0110257032104773",
p_value_fwe="0.000565384750377596",
p_value_fdr="0.0137821290130967",
excursion_set_id="niiri:excursion_set_map_id"
),
"SupraThresholdCluster-5": dict(
cluster_id="niiri:supra_threshold_cluster_0005",
label="Supra-Threshold Cluster: 0005",
cluster_size_in_voxels="12",
cluster_label_id="5",
cluster_size_in_resels="0.0902882999011843",
p_value_unc="0.0818393184514307",
p_value_fwe="0.00418900977248904",
p_value_fdr="0.0818393184514307",
excursion_set_id="niiri:excursion_set_map_id"
),
"Peak_ValueP-1": dict(
peak_id="niiri:peak_0001",
label="Peak: 0001",
location="niiri:coordinate_0001",
value="17.5207633972168",
equiv_z="INF",
p_uncorr="4.44089209850063e-16",
p_value_fwe="0",
p_value_fdr="1.19156591713838e-11",
cluster_id="niiri:supra_threshold_cluster_0001"
),
"Coordinate-1": dict(
coordinate_id="niiri:coordinate_0001",
label="Coordinate: 0001",
coord="[ -60, -25, 11 ]"
),
"Peak_ValueP-2": dict(
peak_id="niiri:peak_0002",
label="Peak: 0002",
location="niiri:coordinate_0002",
value="13.0321407318",
equiv_z="INF",
p_uncorr="4.44089209850063e-16",
p_value_fwe="0",
p_value_fdr="1.19156591714e-11",
cluster_id="niiri:supra_threshold_cluster_0001"
),
"Coordinate-2": dict(
coordinate_id="niiri:coordinate_0002",
label="Coordinate: 0002",
coord="[ -42, -31, 11 ]"
),
"Peak_ValueP-3": dict(
peak_id="niiri:peak_0003",
label="Peak: 0003",
location="niiri:coordinate_0003",
value="10.2856016159058",
equiv_z="INF",
p_uncorr="4.44089209850063e-16",
p_value_fwe="7.69451169446711e-12",
p_value_fdr="6.84121260274992e-10",
cluster_id="niiri:supra_threshold_cluster_0001"
),
"Coordinate-3": dict(
coordinate_id="niiri:coordinate_0003",
label="Coordinate: 0003",
coord="[ -66, -31, -1 ]"
),
"Peak_ValueP-4": dict(
peak_id="niiri:peak_0004",
label="Peak: 0004",
location="niiri:coordinate_0004",
value="13.5425577163696",
equiv_z="INF",
p_uncorr="4.44089209850063e-16",
p_value_fwe="0",
p_value_fdr="1.19156591713838e-11",
cluster_id="niiri:supra_threshold_cluster_0002"
),
"Coordinate-4": dict(
coordinate_id="niiri:coordinate_0004",
label="Coordinate: 0004",
coord="[ 63, -13, -4 ]"
)
}
NIDM_SPM_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'spm', "example003")
ttl_file = os.path.join(NIDM_SPM_DIR, 'spm_results_conjunction.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例10: main
#.........这里部分代码省略.........
),
"FSL_Coordinate-1-2": dict(
coordinate_id="niiri:coordinate_0001_2",
label="Coordinate 0001_2",
coord="[ -9.14, 30.5, 23.7 ]",
coord_in_vox="[ 33, 43, 28 ]"
),
"Peak-1-3": dict(
peak_id="niiri:peak_0001_3",
label="Peak 0001_3",
p_uncorr="0.00122277",
location="niiri:coordinate_0001_3",
equiv_z="3.03",
cluster_id="niiri:supra_threshold_cluster_0001"
),
"FSL_Coordinate-1-3": dict(
coordinate_id="niiri:coordinate_0001_3",
label="Coordinate 0001_3",
coord="[ -19.6, 17.4, 34.7 ]",
coord_in_vox="[ 36, 39, 30 ]"
),
"Peak-1-4": dict(
peak_id="niiri:peak_0001_4",
label="Peak 0001_4",
p_uncorr="0.00554262",
location="niiri:coordinate_0001_4",
equiv_z="2.54",
cluster_id="niiri:supra_threshold_cluster_0001"
),
"FSL_Coordinate-1-4": dict(
coordinate_id="niiri:coordinate_0001_4",
label="Coordinate 0001_4",
coord="[ -9.64, 40.1, 17.3 ]",
coord_in_vox="[ 33, 46, 27 ]"
),
"FSL_SearchSpaceMaskMap": dict(
search_space_id="niiri:search_space_mask_id",
location="SearchSpaceMask.nii.gz",
filename="SearchSpaceMask.nii.gz",
label="Search Space Mask Map",
user_defined="false",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_1",
search_vol_voxels="45203",
search_vol_units="1.93808e+06",
search_vol_resels="3753.84",
resel_size="12.0418",
noise_roughness="0.384676",
random_field_station="true",
sha="cc1a96a6111e5107eb08487e38e6d7f8164b9d1d3f1fc10948bdbcfaea642\
fe9bfae278c7fc372b65cac7232ea58fd8fb5914014e7b9a5d6200592b12b2a728b",
inference_id="niiri:inference_id_1",
noise_fwhm_in_voxels="[2.38803, 2.43263, 2.07288]",
noise_fwhm_in_units="[8.35811, 8.5142, 7.2551]"
),
"NIDMBundle": dict(
bundle_id="niiri:fsl_results_id",
label="NIDM-Results",
object_model="nidm:NIDM_0000027",
version="1.1.0",
time="2014-05-19T10:30:00.000+01:00",
export_id="niiri:export_id"
),
"FSL_Software": dict(
software_id="niiri:software_id",
software_type="scr:SCR_002823",
label="FSL",
version="5.0.x",
feat_version="6.00"
),
"GrandMeanMap": dict(
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="GrandMean.nii.gz",
filename="GrandMean.nii.gz",
format="image/nifti",
masked_median="9597.36",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="7a2703cea740e27a5170fb19e4a09b5e815e4b7e477bc75958404d675aa40\
8f53f747892a2ef4472f933cf5f12cd21cea99d5f5e551938081636fb6d4049473e",
model_pe_id="niiri:model_parameters_estimation_id"
),
"ExporterSoftware": dict(
software_id="niiri:exporter_id",
software_type="nidm:NIDM_0000167",
label="nidmfsl",
version="0.2.0"
),
"Export": dict(
export_id="niiri:export_id",
label="NIDM-Results export",
exporter_id="niiri:exporter_id"
)
}
NIDM_FSL_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'fsl', "example001")
ttl_file = os.path.join(NIDM_FSL_DIR, 'fsl_nidm.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例11: main
#.........这里部分代码省略.........
label="Search Space Mask Map",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_2",
expected_num_voxels="0.553331387916112",
expected_num_clusters="0.0889172687960151",
height_critical_fwe05="5.23529984739211",
height_critical_fdr05="6.22537899017334",
smallest_size_fwe05="1",
smallest_size_fdr05="3",
search_vol_voxels="65593",
search_vol_units="1771011",
resel_size="22.9229643140043",
search_vol_resels="2552.68032521656",
search_vol_resels_geom="[3, 72.3216126440484, 850.716735116472, \
2552.68032521656]",
noise_fwhm_in_voxels="[ 2.95881189165801, 2.96628446669584, \
2.61180425626264 ]",
noise_fwhm_in_units="[ 8.87643567497404, 8.89885340008753, \
7.83541276878791 ]",
random_field_station="false",
sha="e43b6e01b0463fe7d40782137867a",
inference_id="niiri:inference_id"
),
"FSL_ClusterCenterOfGravity": dict(
comment="Cluster Center Of Gravity",
center_of_gravity_id="niiri:center_of_gravity_1",
location="niiri:coordinate_0001",
label="Center of gravity",
cluster_id="niiri:supra_threshold_cluster_0001",
),
"CoordinateSpace": dict(
comment="Coordinate Space",
coordinate_space_id="niiri:coordinate_space_id_1",
label="Coordinate space 1",
voxel_to_world_mapping="[[-3, 0, 0, 78],[0, 3, 0, -112],\
[0, 0, 3, -50],[0, 0, 0, 1]]",
voxel_units="[ \\\"mm\\\", \\\"mm\\\", \\\"mm\\\" ]",
voxel_size="[ 3, 3, 3 ]",
coord_system="nidm:NIDM_0000051",
number_of_dim="3",
dimensions="[ 53, 63, 46 ]"),
"Image": dict(
comment="Image",
image_id="niiri:maximum_intensity_projection_id",
location="MaximumIntensityProjection.png",
filename="MaximumIntensityProjection.png",
format="image/png"
),
"GrandMeanMap": dict(
comment="Grand Mean Map",
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="GrandMean.nii.gz",
filename="GrandMean.nii.gz",
format="image/nifti",
masked_median="115",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a",
model_pe_id="niiri:model_pe_id"
),
"SPM_DriftModel": dict(
comment="SPM's DCT Drift Model",
id="niiri:drift_model_id",
label="SPM's DCT Drift Model",
cut_off="128"
),
"FSL_DriftModel": dict(
comment="FSL's Gaussian Running Line Drift Model",
id="niiri:drift_model_id",
label="FSL's Gaussian Running Line Drift Model",
cut_off="2"
),
"ClusterDefinitionCriteria-06": dict(
comment="Cluster connectivity: face",
cluster_definition_criteria_id="niiri:cluster_definition_criteria\
_id",
label="Cluster Connectivity Criterion: 6",
connectivity="nidm:NIDM_0000130"
),
"ClusterDefinitionCriteria-18": dict(
comment="Cluster connectivity: face or edge",
cluster_definition_criteria_id="niiri:cluster_definition_criteria\
_id",
label="Cluster Connectivity Criterion: 18",
connectivity="nidm:NIDM_0000128"
),
"ClusterDefinitionCriteria-26": dict(
comment="Cluster connectivity: face, edge or corner",
cluster_definition_criteria_id="niiri:cluster_definition_criteria\
_id",
label="Cluster Connectivity Criterion: 26",
connectivity="nidm:NIDM_0000129"
)
}
# Delete old examples
shutil.rmtree(EX_DIR)
os.mkdir(EX_DIR)
example = ExampleFromTemplate(nidm_classes, EX_DIR, True)
example.create_example()示例12: main
#.........这里部分代码省略.........
inference_id="niiri:inference_id"
),
"DerivedMap": dict(
derived_from_map_id="niiri:contrast_map_id_der",
derived_map_type="nidm:NIDM_0000002",
filename="con_0001.nii",
format="image/nifti",
sha="277dd1da13d391c33c172fb8c71060008cc66e173de6362eb857b0055b41e\
9bae57911f7ec4b45659905103b1139ebf3da0c2d04cf105bbce0cdc3004b643c22",
map_id="niiri:contrast_map_id"
),
"DerivedMap-2": dict(
derived_from_map_id="niiri:beta_map_id_2_der",
derived_map_type="nidm:NIDM_0000061",
filename="beta_0002.nii",
format="image/nifti",
sha="3f72b788762d9ab2c7ddb5e4d446872694ee42fc8897fe5317b54efb7924f\
784da6499065db897a49595d8763d1893ad65ad102b0c88f2e72e2d028173343008",
map_id="niiri:beta_map_id_2"
),
"NIDMBundle": dict(
bundle_id="niiri:spm_results_id",
label="NIDM-Results",
object_model="nidm:NIDM_0000027",
version="1.1.0",
time="2014-05-19T10:30:00.000+01:00",
export_id="niiri:export_id"
),
"SPM_ReselsPerVoxelMap": dict(
resels_per_voxel_map_id="niiri:resels_per_voxel_map_id",
label="Resels per Voxel Map",
location="ReselsPerVoxel.nii.gz",
filename="ReselsPerVoxel.nii.gz",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="2025dc6c33708b80708c2eba3215fb1149df236fb558a8e8f8f6cf34595fb\
54734fe5e436db3e192a424d99699dd7feb2f4a9020ceae8e7bcbd881b17825256a",
model_pe_id="niiri:model_pe_id"
),
"SPM_InferenceUsedRPVMap": dict(
inference_id="niiri:inference_id",
resels_per_voxel_map_id="niiri:resels_per_voxel_map_id"
),
"DerivedMap-RPVMap": dict(
derived_from_map_id="niiri:resels_per_voxel_map_id_der",
derived_map_type="nidm:NIDM_0000144",
filename="RPV.nii",
format="image/nifti",
sha="963283cdde607c40e4640c27453867bd0d70133b6d61482933862487c0f4a\
5acdb2e338a12a2605ee044b1aa47b5717f0c520b90ed3c49b5227f0483bd48512d",
map_id="niiri:resels_per_voxel_map_id"
),
"ClusterLabelsMap": dict(
cluster_label_map_id="niiri:cluster_label_map_id",
location="ClusterLabels.nii.gz",
filename="ClusterLabels.nii.gz",
format="image/nifti"
),
"SPM_Software": dict(
software_id="niiri:software_id",
software_type="nlx:nif-0000-00343",
label="SPM",
version="12.12.1"
),
"Image": dict(
image_id="niiri:maximum_intensity_projection_id",
location="MaximumIntensityProjection.png",
filename="MaximumIntensityProjection.png",
format="image/png"
),
"GrandMeanMap": dict(
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="GrandMean.nii.gz",
filename="GrandMean.nii.gz",
format="image/nifti",
masked_median="132.008995056152",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="4d3528031bce4a9c1b994b8124e6e0eddb9df90b49c84787652ed94df8c14\
c04ec92100a2d8ea86a8df24ba44617aca7457ddcb2f42253fc17e33296a1aea1cb",
model_pe_id="niiri:model_pe_id"
),
"ExporterSoftware": dict(
software_id="niiri:exporter_id",
software_type="nidm:NIDM_0000168",
label="spm_results_nidm",
version="12b.5858"
),
"Export": dict(
export_id="niiri:export_id",
label="NIDM-Results export",
exporter_id="niiri:exporter_id"
)
}
NIDM_SPM_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'spm', "example001")
ttl_file = os.path.join(NIDM_SPM_DIR, 'example001_spm_results.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例13: main
#.........这里部分代码省略.........
cluster_label_id="1",
cluster_size_in_resels="23.1209189500945",
p_value_unc="9.56276736481136e-52",
p_value_fwe="0",
p_value_fdr="7.65021389184909e-51",
excursion_set_id="niiri:excursion_set_map_id"
),
"Peak_ValueP": dict(
peak_id="niiri:peak_0001",
label="Peak 0001",
location="niiri:coordinate_0001",
value="13.9346199035645",
equiv_z="INF",
p_uncorr="4.44089209850063e-16",
p_value_fwe="0",
p_value_fdr="6.3705194444993e-11",
cluster_id="niiri:significant_cluster_0001"
),
"Coordinate": dict(
coordinate_id="niiri:coordinate_0001",
label="Coordinate: 0001",
coord="[ -60, -28, 13 ]"
),
"SearchSpaceMaskMap": dict(
search_space_id="niiri:search_space_mask_id",
location="file:///path/to/SearchSpaceMask.nii.gz",
filename="SearchSpaceMask.nii.gz",
label="Search Space Mask Map",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_2",
expected_num_voxels="0.553331387916112",
expected_num_clusters="0.0889172687960151",
height_critical_fwe05="5.23529984739211",
height_critical_fdr05="6.22537899017334",
smallest_size_fwe05="1",
smallest_size_fdr05="3",
search_vol_voxels="65593",
search_vol_units="1771011",
resel_size="22.9229643140043",
search_vol_resels="2552.68032521656",
search_vol_resels_geom="[3, 72.3216126440484, 850.716735116472, \
2552.68032521656]",
noise_fwhm_in_voxels="[ 2.95881189165801, 2.96628446669584, \
2.61180425626264 ]",
noise_fwhm_in_units="[ 8.87643567497404, 8.89885340008753, \
7.83541276878791 ]",
random_field_station="false",
sha="e43b6e01b0463fe7d40782137867a...",
inference_id="niiri:inference_id"
),
"FSL_ClusterCenterOfGravity": dict(
center_of_gravity_id="niiri:center_of_gravity_1",
location="niiri:coordinate_0001",
label="Center of gravity",
cluster_id="niiri:significant_cluster_0001",
),
"CoordinateSpace": dict(
coordinate_space_id="niiri:coordinate_space_id_1",
label="Coordinate space 1",
voxel_to_world_mapping="[[-3, 0, 0, 78],[0, 3, 0, -112],\
[0, 0, 3, -50],[0, 0, 0, 1]]",
voxel_units="[ \\\"mm\\\", \\\"mm\\\", \\\"mm\\\" ]",
voxel_size="[ 3, 3, 3 ]",
coord_system="nidm:NIDM_0000051",
number_of_dim="3",
dimensions="[ 53, 63, 46 ]"),
"Image": dict(
image_id="niiri:maximum_intensity_projection_id",
location="file:///path/to/MaximumIntensityProjection.png",
filename="MaximumIntensityProjection.png",
format="image/png"
),
"GrandMeanMap": dict(
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="file:///path/to/GrandMean.nii.gz",
filename="GrandMean.nii.gz",
format="image/nifti",
masked_median="115",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a...",
model_pe_id="niiri:model_pe_id"
),
"SPM_DriftModel": dict(
id="niiri:drift_model_id",
label="SPM's DCT Drift Model",
cut_off="128"
),
"FSL_DriftModel": dict(
id="niiri:drift_model_id",
label="FSL's Gaussian Running Line Drift Model",
cut_off="2"
)
}
NIDM_TERMS_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'terms')
EX_DIR = os.path.join(NIDM_TERMS_DIR, 'examples')
example = ExampleFromTemplate(nidm_classes, EX_DIR, True)
example.create_example()示例14: main
#.........这里部分代码省略.........
label="Inference 1",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id="niiri:statistic_map_id",
height_thresh_id="niiri:height_threshold_id",
extent_thresh_id="niiri:extent_threshold_id",
display_mask_id="niiri:display_map_id",
peak_def_id="niiri:peak_definition_criteria_id",
cluster_def_id="niiri:cluster_definition_criteria_id",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id",
),
"Inference-2": dict(
inference_id="niiri:inference_id_2",
label="Inference 2",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id="niiri:statistic_map_id_2",
height_thresh_id="niiri:height_threshold_id_2",
extent_thresh_id="niiri:extent_threshold_id_2",
display_mask_id="niiri:display_map_id_2",
peak_def_id="niiri:peak_definition_criteria_id_2",
cluster_def_id="niiri:cluster_definition_criteria_id_2",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id",
),
"ConjunctionInference": dict(
conj_inference_id="niiri:inference_id_3",
label="Conjunction Inference 3",
alternative_hyp="nidm:NIDM_0000060",
stat_map_id_1="niiri:statistic_map_id",
stat_map_id_2="niiri:statistic_map_id_2",
height_thresh_id="niiri:height_threshold_id_3",
extent_thresh_id="niiri:extent_threshold_id_3",
display_mask_id="niiri:display_map_id_3",
peak_def_id="niiri:peak_definition_criteria_id_3",
cluster_def_id="niiri:cluster_definition_criteria_id_3",
mask_id="niiri:mask_id_1",
software_id="niiri:software_id",
),
"DerivedMap-Contrast": dict(
derived_from_map_id="niiri:contrast_map_id_der",
derived_map_type="nidm:NIDM_0000002",
filename="con_0001.nii",
format="image/nifti",
sha="e43b6e01b0463fe7d40782137867a...",
map_id="niiri:contrast_map_id",
),
"NIDMBundle": dict(
bundle_id="niiri:spm_results_id",
label="NIDM-Results",
object_model="nidm:NIDM_0000027",
version="1.1.0",
time="2014-05-19T10:30:00.000+01:00",
),
"SPM_ReselsPerVoxelMap": dict(
resels_per_voxel_map_id="niiri:resels_per_voxel_map_id",
label="Resels per Voxel Map",
location="file:///path/to/ReselsPerVoxel.nii.gz",
filename="ReselsPerVoxel.nii.gz",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a...",
model_pe_id="niiri:model_pe_id",
),
"SPM_InferenceUsedRPVMap": dict(
inference_id="niiri:inference_id", resels_per_voxel_map_id="niiri:resels_per_voxel_map_id"
),
"SPM_InferenceUsedRPVMap-2": dict(
inference_id="niiri:inference_id_2", resels_per_voxel_map_id="niiri:resels_per_voxel_map_id"
),
"SPM_InferenceUsedRPVMap-3": dict(
inference_id="niiri:inference_id_3", resels_per_voxel_map_id="niiri:resels_per_voxel_map_id"
),
"DerivedMap-RPV": dict(
derived_from_map_id="niiri:resels_per_voxel_map_id_der",
derived_map_type="nidm:NIDM_0000144",
filename="RPV.nii",
format="image/nifti",
sha="e43b6e01b0463fe7d40782137867a...",
map_id="niiri:resels_per_voxel_map_id",
),
"SPM_Software": dict(
software_id="niiri:software_id", software_type="nlx:nif-0000-00343", label="SPM", version="12b.5853"
),
"GrandMeanMap": dict(
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="file:///path/to/GrandMean.nii.gz",
filename="GrandMean.nii.gz",
format="image/nifti",
masked_median="115",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a...",
model_pe_id="niiri:model_pe_id",
),
}
NIDM_SPM_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "spm", "example002")
ttl_file = os.path.join(NIDM_SPM_DIR, "spm_results_2contrasts.ttl")
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()示例15: main
#.........这里部分代码省略.........
coordinate_id="niiri:coordinate_0003",
label="Coordinate 3",
coord="[ -29.6, -73.8, -16.9 ]",
coord_in_vox="[ 40, 15, 12 ]",
),
"Peak-4": dict(
peak_id="niiri:peak_0004",
label="Peak 4",
p_uncorr="4.462172e-09",
location="niiri:coordinate_0004",
equiv_z="5.75",
cluster_id="niiri:significant_cluster_0001"
),
"FSL_Coordinate-4": dict(
coordinate_id="niiri:coordinate_0004",
label="Coordinate 4",
coord="[ 0.791, -87.2, 3.23 ]",
coord_in_vox="[ 39, 13, 12 ]"
),
"Peak-M5": dict(
peak_id="niiri:peak_0005",
label="Peak 5",
p_uncorr="2.178976e-09",
location="niiri:coordinate_0005",
equiv_z="5.87",
cluster_id="niiri:significant_cluster_0002"
),
"FSL_Coordinate-5": dict(
coordinate_id="niiri:coordinate_0005",
label="Coordinate 5",
coord="[ 16.1, -96.6, 5.82 ]",
coord_in_vox="[ 32, 10, 16 ]"
),
"Peak-6": dict(
peak_id="niiri:peak_0006",
label="Peak 6",
p_uncorr="8.022392e-09",
location="niiri:coordinate_0006",
equiv_z="5.65",
cluster_id="niiri:significant_cluster_0002"
),
"FSL_Coordinate-6": dict(
coordinate_id="niiri:coordinate_0006",
label="Coordinate 6",
coord="[ -25.5, -80.4, 15.3 ]",
coord_in_vox="[ 28, 7, 16 ]"
),
"FSL_SearchSpaceMaskMap": dict(
search_space_id="niiri:search_space_mask_id",
location="file://path/to/SearchSpaceMask.nii.gz",
filename_1="SearchSpaceMask.nii.gz",
filename_2="mask.nii.gz",
label="Search Space Mask Map",
user_defined="false",
format="image/nifti",
coordinate_space_id="niiri:coordinate_space_id_2",
search_vol_voxels="45359",
search_vol_units="1.93808e+06",
search_vol_resels="3753.84",
resel_size="12.2251",
noise_roughness="0.384676",
random_field_station="true",
sha="400a2f07d99ed9be06577e6ecc89222cf4b688c654bc89067da558e88b73b97dd1b25e6c98f2a735fa0a1409598cff7e6025bda55abb6b9f5ef65d8d307eeba8",
inference_id="niiri:inference_id",
noise_fwhm_in_voxels="[2.38803, 2.43263, 2.07288]",
noise_fwhm_in_units="[8.35811, 8.5142, 7.2551]"
),
"NIDMBundle": dict(
bundle_id="niiri:fsl_results_id",
label="NIDM-Results",
object_model="nidm:NIDM_0000027",
version="1.1.0",
time="2014-05-19T10:30:00.000+01:00"
),
"FSL_Software": dict(
software_id="niiri:software_id",
software_type="nlx:birnlex_2067",
label="FSL",
version="5.0.x",
feat_version="6.00"
),
"FSL_GrandMeanMap": dict(
grand_mean_map_id="niiri:grand_mean_map_id",
label="Grand Mean Map",
location="file://path/to/GrandMean.nii.gz",
filename_1="GrandMean.nii.gz",
filename_2="mean_func.nii.gz",
format="image/nifti",
masked_median="115",
coordinate_space_id="niiri:coordinate_space_id_1",
sha="e43b6e01b0463fe7d40782137867a...",
model_pe_id="niiri:model_pe_id"
)
}
NIDM_FSL_DIR = os.path.join(os.path.dirname(
os.path.dirname(os.path.abspath(__file__))), 'fsl')
ttl_file = os.path.join(NIDM_FSL_DIR, 'fsl_results.ttl')
example = ExampleFromTemplate(nidm_classes, ttl_file, False)
example.create_example()