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Delete reproduction_effort/preprocessing.py

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David Rotermund 2024-02-14 22:42:59 +01:00 committed by GitHub
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reproduction_effort/preprocessing.py
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import torch
import numpy as np
import matplotlib.pyplot as plt
import h5py # type: ignore
from functions.preprocessing import preprocessing
if __name__ == "__main__":
if torch.cuda.is_available():
device_name: str = "cuda:0"
else:
device_name = "cpu"
print(f"Using device: {device_name}")
device: torch.device = torch.device(device_name)
filename_metadata: str = "raw/Exp001_Trial001_Part001_meta.txt"
filename_data: str = "Exp001_Trial001_Part001.mat"
filename_mask: str = "2020-12-08maskPixelraw2.mat"
first_none_ramp_frame: int = 100
spatial_width: float = 2
temporal_width: float = 0.1
target_camera: list[str] = ["acceptor", "donor"]
regressor_cameras: list[str] = ["oxygenation", "volume"]
data_acceptor, data_donor, mask = preprocessing(
filename_metadata=filename_metadata,
filename_data=filename_data,
filename_mask=filename_mask,
device=device,
first_none_ramp_frame=first_none_ramp_frame,
spatial_width=spatial_width,
temporal_width=temporal_width,
target_camera=target_camera,
regressor_cameras=regressor_cameras,
)
ratio_sequence: torch.Tensor = data_acceptor / data_donor
new: np.ndarray = ratio_sequence.cpu().numpy()
file_handle = h5py.File("old.mat", "r")
old: np.ndarray = np.array(file_handle["ratioSequence"])
# HDF5 loads everything backwards...
old = np.moveaxis(old, 0, -1)
old = np.moveaxis(old, 0, -2)
pos_x = 25
pos_y = 75
plt.subplot(2, 1, 1)
new_select = new[pos_x, pos_y, :]
old_select = old[pos_x, pos_y, :]
plt.plot(new_select, label="New")
plt.plot(old_select, "--", label="Old")
plt.plot(old_select - new_select + 1.0, label="Old - New + 1")
plt.title(f"Position: {pos_x}, {pos_y}")
plt.legend()
plt.subplot(2, 1, 2)
differences = (np.abs(new - old)).max(axis=-1)
plt.imshow(differences)
plt.title("Max of abs(new-old) along time")
plt.colorbar()
plt.show()