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wrong var name fix
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@steelec
steelec committed Dec 17, 2024
1 parent db7d551 commit 30916de
Showing 1 changed file with 36 additions and 35 deletions.
71 changes: 36 additions & 35 deletions macaque_CB/2d_slice_registration_all_fns_parallel_HPC_regTests_v5_cascadetest_res.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,16 +64,16 @@

output_dir = f'/tmp/slice_reg_perSliceTemplate_image_weights_dwnsmple_parallel_v2_{rescale}_casc_v5_test/'
# _df = pd.read_csv('/data/neuralabc/neuralabc_volunteers/macaque/all_TP_image_idxs_file_lookup.csv')
# missing_idxs_to_fill = [32,59,120,160,189,228] #these are the slice indices with missing or terrible data, fill with mean of neigbours
missing_idxs_to_fill = [32,59,120,160,189,228] #these are the slice indices with missing or terrible data, fill with mean of neigbours
# output_dir = '/data/data_drive/Macaque_CB/processing/results_from_cell_counts/slice_reg_perSliceTemplate_image_weights_all_tmp/'
_df = pd.read_csv('/data/data_drive/Macaque_CB/processing/results_from_cell_counts/all_TP_image_idxs_file_lookup.csv')

missing_idxs_to_fill = [5,32]
# missing_idxs_to_fill = [5,32]
# missing_idxs_to_fill = [3]
# missing_idxs_to_fill = None
all_image_fnames = list(_df['file_name'].values)

all_image_fnames = all_image_fnames[0:50] #for testing
# all_image_fnames = all_image_fnames[0:50] #for testing

print('*********************************************************************************************************')
print(f'Output directory: {output_dir}')
Expand Down Expand Up @@ -885,6 +885,7 @@ def generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=4,
- `'mean'`: The mean of the current and neighboring slices.
- `'median'`: The median of the current and neighboring slices.
- `'nonlin'`: A non-linear version of the template using the 'intermediate_nonlin_mean' method.
- `'nochange'`: The deformed slice itself as the template
5. **Saving Slice Templates**:
- If `per_slice_template` is set to True, templates for each slice are saved individually, both for median and non-linear methods, as applicable.
Expand Down Expand Up @@ -971,7 +972,7 @@ def generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=4,
header = nibabel.Nifti1Header()
header.set_data_shape(interp_slice.shape)

affine = create_affine(slice_img.shape)
affine = create_affine(interp_slice.shape)
affine[0,0] = in_plane_res_x/1000
affine[1,1] = in_plane_res_y/1000
affine[2,2] = in_plane_res_z/1000
Expand Down Expand Up @@ -1703,38 +1704,38 @@ def setup_logging(dataset_name, out_dir):
scaling_factor=scaling_factor)

## loop over cascades to see what this does for us
# iter_tag = ""
# num_cascade_iterations = 5
# anchor_slice_idxs = numpy.linspace(0,len(all_image_fnames)-1,num_cascade_iterations+2).astype(int)
# anchor_slice_idxs = anchor_slice_idxs[1:-1] #remove the first and last, as they will denote 1st and last indices of the stack
# for iter in range(num_cascade_iterations):
# if iter == 0:
# input_source_file_tag = 'coreg0nl'
iter_tag = ""
num_cascade_iterations = 5
anchor_slice_idxs = numpy.linspace(0,len(all_image_fnames)-1,num_cascade_iterations+2).astype(int)
anchor_slice_idxs = anchor_slice_idxs[1:-1] #remove the first and last, as they will denote 1st and last indices of the stack
for iter in range(num_cascade_iterations):
if iter == 0:
input_source_file_tag = 'coreg0nl'

# else:
# input_source_file_tag = iter_tag #updates with the previous iteration
# iter_tag = f'_cascade_{iter}'
# run_cascading_coregistrations(output_dir, subject,
# all_image_fnames, anchor_slice_idx = anchor_slice_idxs[iter],
# missing_idxs_to_fill = missing_idxs_to_fill,
# zfill_num=zfill_num, input_source_file_tag=input_source_file_tag,
# reg_level_tag=iter_tag, previous_target_tag=None)

# template = generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=zfill_num,reg_level_tag=iter_tag,
# per_slice_template=True,
# missing_idxs_to_fill=missing_idxs_to_fill,scaling_factor=scaling_factor)

input_source_file_tag = 'coreg0nl'
reg_level_tag = "coreg0nl_cascade"
run_cascading_coregistrations(output_dir, subject,
all_image_fnames, anchor_slice_idx = None,
missing_idxs_to_fill = missing_idxs_to_fill,
zfill_num=zfill_num, input_source_file_tag=input_source_file_tag,
reg_level_tag=reg_level_tag, previous_target_tag=None,run_syn=False)

template = generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=zfill_num,reg_level_tag=reg_level_tag,
per_slice_template=True,
missing_idxs_to_fill=missing_idxs_to_fill,slice_template_type='nochange',scaling_factor=scaling_factor)
else:
input_source_file_tag = iter_tag #updates with the previous iteration
iter_tag = f'_cascade_{iter}'
run_cascading_coregistrations(output_dir, subject,
all_image_fnames, anchor_slice_idx = anchor_slice_idxs[iter],
missing_idxs_to_fill = missing_idxs_to_fill,
zfill_num=zfill_num, input_source_file_tag=input_source_file_tag,
reg_level_tag=iter_tag, previous_target_tag=None)

template = generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=zfill_num,reg_level_tag=iter_tag,
per_slice_template=True,
missing_idxs_to_fill=missing_idxs_to_fill,scaling_factor=scaling_factor)

# input_source_file_tag = 'coreg0nl'
# reg_level_tag = "coreg0nl_cascade"
# run_cascading_coregistrations(output_dir, subject,
# all_image_fnames, anchor_slice_idx = None,
# missing_idxs_to_fill = missing_idxs_to_fill,
# zfill_num=zfill_num, input_source_file_tag=input_source_file_tag,
# reg_level_tag=reg_level_tag, previous_target_tag=None,run_syn=False)

# template = generate_stack_and_template(output_dir,subject,all_image_fnames,zfill_num=zfill_num,reg_level_tag=reg_level_tag,
# per_slice_template=True,
# missing_idxs_to_fill=missing_idxs_to_fill,slice_template_type='nochange',scaling_factor=scaling_factor)

## ****************************** Iteration 1
# in all cases, we go:
Expand Down

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