def test_VBMSegment_outputs(): output_map = dict(bias_corrected_images=dict(), dartel_input_images=dict(), forward_deformation_field=dict(), inverse_deformation_field=dict(), jacobian_determinant_images=dict(), modulated_class_images=dict(), native_class_images=dict(), normalized_bias_corrected_images=dict(), normalized_class_images=dict(), pve_label_native_images=dict(), pve_label_normalized_images=dict(), pve_label_registered_images=dict(), transformation_mat=dict(), ) outputs = VBMSegment.output_spec() for key, metadata in output_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_VBMSegment_outputs(): output_map = dict( bias_corrected_images=dict(), dartel_input_images=dict(), forward_deformation_field=dict(), inverse_deformation_field=dict(), jacobian_determinant_images=dict(), modulated_class_images=dict(), native_class_images=dict(), normalized_bias_corrected_images=dict(), normalized_class_images=dict(), pve_label_native_images=dict(), pve_label_normalized_images=dict(), pve_label_registered_images=dict(), transformation_mat=dict(), ) outputs = VBMSegment.output_spec() for key, metadata in output_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_VBMSegment_inputs(): input_map = dict( bias_corrected_affine=dict( field='estwrite.output.bias.affine', usedefault=True, ), bias_corrected_native=dict( field='estwrite.output.bias.native', usedefault=True, ), bias_corrected_normalized=dict( field='estwrite.output.bias.warped', usedefault=True, ), bias_fwhm=dict( field='estwrite.opts.biasfwhm', usedefault=True, ), bias_regularization=dict( field='estwrite.opts.biasreg', usedefault=True, ), cleanup_partitions=dict( field='estwrite.extopts.cleanup', usedefault=True, ), csf_dartel=dict( field='estwrite.output.CSF.dartel', usedefault=True, ), csf_modulated_normalized=dict( field='estwrite.output.CSF.modulated', usedefault=True, ), csf_native=dict( field='estwrite.output.CSF.native', usedefault=True, ), csf_normalized=dict( field='estwrite.output.CSF.warped', usedefault=True, ), dartel_template=dict( field='estwrite.extopts.dartelwarp.normhigh.darteltpm', ), deformation_field=dict( field='estwrite.output.warps', usedefault=True, ), display_results=dict( field='estwrite.extopts.print', usedefault=True, ), gaussians_per_class=dict(usedefault=True, ), gm_dartel=dict( field='estwrite.output.GM.dartel', usedefault=True, ), gm_modulated_normalized=dict( field='estwrite.output.GM.modulated', usedefault=True, ), gm_native=dict( field='estwrite.output.GM.native', usedefault=True, ), gm_normalized=dict( field='estwrite.output.GM.warped', usedefault=True, ), ignore_exception=dict( nohash=True, usedefault=True, ), in_files=dict( copyfile=False, field='estwrite.data', mandatory=True, ), jacobian_determinant=dict( field='estwrite.jacobian.warped', usedefault=True, ), matlab_cmd=dict(), mfile=dict(usedefault=True, ), mrf_weighting=dict( field='estwrite.extopts.mrf', usedefault=True, ), paths=dict(), pve_label_dartel=dict( field='estwrite.output.label.dartel', usedefault=True, ), pve_label_native=dict( field='estwrite.output.label.native', usedefault=True, ), pve_label_normalized=dict( field='estwrite.output.label.warped', usedefault=True, ), sampling_distance=dict( field='estwrite.opts.samp', usedefault=True, ), spatial_normalization=dict(usedefault=True, ), tissues=dict(field='estwrite.tpm', ), use_mcr=dict(), use_sanlm_denoising_filter=dict( field='estwrite.extopts.sanlm', usedefault=True, ), use_v8struct=dict( min_ver='8', usedefault=True, ), warping_regularization=dict( field='estwrite.opts.warpreg', usedefault=True, ), wm_dartel=dict( field='estwrite.output.WM.dartel', usedefault=True, ), wm_modulated_normalized=dict( field='estwrite.output.WM.modulated', usedefault=True, ), wm_native=dict( field='estwrite.output.WM.native', usedefault=True, ), wm_normalized=dict( field='estwrite.output.WM.warped', usedefault=True, ), ) inputs = VBMSegment.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_VBMSegment_inputs(): input_map = dict(bias_corrected_affine=dict(field='estwrite.output.bias.affine', usedefault=True, ), bias_corrected_native=dict(field='estwrite.output.bias.native', usedefault=True, ), bias_corrected_normalized=dict(field='estwrite.output.bias.warped', usedefault=True, ), bias_fwhm=dict(field='estwrite.opts.biasfwhm', usedefault=True, ), bias_regularization=dict(field='estwrite.opts.biasreg', usedefault=True, ), cleanup_partitions=dict(field='estwrite.extopts.cleanup', usedefault=True, ), csf_dartel=dict(field='estwrite.output.CSF.dartel', usedefault=True, ), csf_modulated_normalized=dict(field='estwrite.output.CSF.modulated', usedefault=True, ), csf_native=dict(field='estwrite.output.CSF.native', usedefault=True, ), csf_normalized=dict(field='estwrite.output.CSF.warped', usedefault=True, ), dartel_template=dict(field='estwrite.extopts.dartelwarp.normhigh.darteltpm', ), deformation_field=dict(field='estwrite.output.warps', usedefault=True, ), display_results=dict(field='estwrite.extopts.print', usedefault=True, ), gaussians_per_class=dict(usedefault=True, ), gm_dartel=dict(field='estwrite.output.GM.dartel', usedefault=True, ), gm_modulated_normalized=dict(field='estwrite.output.GM.modulated', usedefault=True, ), gm_native=dict(field='estwrite.output.GM.native', usedefault=True, ), gm_normalized=dict(field='estwrite.output.GM.warped', usedefault=True, ), ignore_exception=dict(nohash=True, usedefault=True, ), in_files=dict(copyfile=False, field='estwrite.data', mandatory=True, ), jacobian_determinant=dict(field='estwrite.jacobian.warped', usedefault=True, ), matlab_cmd=dict(), mfile=dict(usedefault=True, ), mrf_weighting=dict(field='estwrite.extopts.mrf', usedefault=True, ), paths=dict(), pve_label_dartel=dict(field='estwrite.output.label.dartel', usedefault=True, ), pve_label_native=dict(field='estwrite.output.label.native', usedefault=True, ), pve_label_normalized=dict(field='estwrite.output.label.warped', usedefault=True, ), sampling_distance=dict(field='estwrite.opts.samp', usedefault=True, ), spatial_normalization=dict(usedefault=True, ), tissues=dict(field='estwrite.tpm', ), use_mcr=dict(), use_sanlm_denoising_filter=dict(field='estwrite.extopts.sanlm', usedefault=True, ), use_v8struct=dict(min_ver='8', usedefault=True, ), warping_regularization=dict(field='estwrite.opts.warpreg', usedefault=True, ), wm_dartel=dict(field='estwrite.output.WM.dartel', usedefault=True, ), wm_modulated_normalized=dict(field='estwrite.output.WM.modulated', usedefault=True, ), wm_native=dict(field='estwrite.output.WM.native', usedefault=True, ), wm_normalized=dict(field='estwrite.output.WM.warped', usedefault=True, ), ) inputs = VBMSegment.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value