utils
linc_convert.modalities.psoct._utils ¶
make_json ¶
make_json(oct_meta)
Make json from OCT metadata.
Expected input:
Image medium: 60% TDE Center Wavelength: 1294.84nm Axial resolution: 4.9um Lateral resolution: 4.92um FOV: 3x3mm Voxel size: 3x3x3um Depth focus range: 225um Number of focuses: 2 Focus #: 2 Slice thickness: 450um. Number of slices: 75 Slice #:23 Modality: dBI
struct_arr_to_dict ¶
struct_arr_to_dict(arr)
Convert a NumPy structured array (single record) to a dictionary.
Returns:
| Type | Description |
|---|---|
dict: Dictionary mapping field names to their values.
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find_experiment_params ¶
find_experiment_params(exp_file)
Load experiment parameters from a .mat file, detecting if it's a Fiji experiment.
Returns:
| Type | Description |
|---|---|
tuple:
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Raises:
| Type | Description |
|---|---|
ValueError: If no experiment key is found in the file.
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mat_vars ¶
mat_vars(mat_file)
Yield variable names from a .mat file, excluding internal variables.
Yields:
| Type | Description |
|---|---|
str: Variable names not starting with '__'.
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atleast_2d_trailing ¶
atleast_2d_trailing(arr)
Ensure the input is at least 2D by adding a new axis at the end if needed.
If the input is 1D, it becomes shape (N, 1). If the input is 0D (scalar), it becomes shape (1, 1). If it's already 2D or more, it's returned unchanged.
Returns:
| Type | Description |
|---|---|
np.ndarray: A 2D or higher NumPy array with at least two dimensions.
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