| """Utilities for mapping normalized target modalities to physical ranges.""" |
|
|
| from __future__ import annotations |
|
|
| import numpy as np |
|
|
|
|
| TARGET_CHANNELS = ["D", "Delta", "eta", "theta", "psi", "R"] |
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|
| def normalized_modalities_to_physical(target, channel_axis=0, clip=False): |
| """Map normalized grayscale modalities to nominal physical ranges. |
| |
| Use this only for targets encoded as |
| ``png_uint8_normalized_to_float32_0_1``. If a split already stores physical |
| Lu-Chipman values, do not apply this conversion again. |
| """ |
| target = np.asarray(target, dtype=np.float32) |
| values = np.moveaxis(target, channel_axis, 0) |
| if values.shape[0] != 6: |
| raise ValueError(f"Expected 6 target channels, got shape {target.shape}") |
|
|
| g = np.clip(values, 0.0, 1.0) if clip else values |
| physical = np.empty_like(g, dtype=np.float32) |
| physical[0] = g[0] |
| physical[1] = g[1] |
| physical[2] = np.pi * g[2] |
| physical[3] = np.pi * (g[3] - 0.5) |
| physical[4] = np.pi * (g[4] - 0.5) |
| physical[5] = np.pi * g[5] |
| return np.moveaxis(physical, 0, channel_axis) |
|
|
|
|
| def physical_modalities_to_normalized(target, channel_axis=0, clip=False): |
| """Map physical target modalities to normalized grayscale ranges.""" |
| target = np.asarray(target, dtype=np.float32) |
| values = np.moveaxis(target, channel_axis, 0) |
| if values.shape[0] != 6: |
| raise ValueError(f"Expected 6 target channels, got shape {target.shape}") |
|
|
| normalized = np.empty_like(values, dtype=np.float32) |
| normalized[0] = values[0] |
| normalized[1] = values[1] |
| normalized[2] = values[2] / np.pi |
| normalized[3] = values[3] / np.pi + 0.5 |
| normalized[4] = values[4] / np.pi + 0.5 |
| normalized[5] = values[5] / np.pi |
| if clip: |
| normalized = np.clip(normalized, 0.0, 1.0) |
| return np.moveaxis(normalized, 0, channel_axis) |
|
|
