Delete analyse_raw_data.py
This commit is contained in:
David Rotermund
GitHub
parent
c8da0b7d2a
commit
f8399f78a7
1 changed files with 0 additions and 150 deletions
|
|
@ -1,150 +0,0 @@
|
|||
import torch
|
||||
from functions.Anime import Anime
|
||||
from functions.DataContainer import DataContainer
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import argh
|
||||
import os
|
||||
|
||||
|
||||
def main(
|
||||
path: str = "/data_1/hendrik/2021-06-17/M3859M/raw",
|
||||
experiment_id: int = 1,
|
||||
trial_id: int = 1,
|
||||
use_svd: bool = True, # i.e. use SVD
|
||||
mask_threshold: float | None = 0.0025, # Between 0 and 1.0
|
||||
show_example_timeseries: bool = True,
|
||||
example_position_x: int = 280,
|
||||
example_position_y: int = 440,
|
||||
movie_play: bool = True,
|
||||
movie_vmin_scale: float | None = 0.05,
|
||||
movie_vmax_scale: float | None = 0.1,
|
||||
movie_enable_mask: bool = True,
|
||||
movie_export: bool = False,
|
||||
export_results: bool = True,
|
||||
export_path: str = "Export",
|
||||
):
|
||||
if use_svd:
|
||||
print("SVD mode")
|
||||
else:
|
||||
print("Classic mode")
|
||||
|
||||
if movie_export is False:
|
||||
movie_file: str | None = None
|
||||
else:
|
||||
if use_svd:
|
||||
movie_file = f"SVD_Exp{experiment_id}_Trial{trial_id}.mp4"
|
||||
else:
|
||||
movie_file = f"Classic_Exp{experiment_id}_Trial{trial_id}.mp4"
|
||||
|
||||
if export_results:
|
||||
os.makedirs(export_path, exist_ok=True)
|
||||
|
||||
initital_mask_name: str | None = None
|
||||
initital_mask_update: bool = True
|
||||
initital_mask_roi: bool = False # default: True
|
||||
|
||||
start_position: int = 0
|
||||
start_position_coefficients: int = 100
|
||||
|
||||
svd_iterations: int = 1 # SVD iterations: Do not touch! Keep at 1
|
||||
bin_size: int = 4
|
||||
|
||||
display_logging_messages: bool = False
|
||||
save_logging_messages: bool = False
|
||||
|
||||
# Post data processing modifiations
|
||||
gaussian_blur_kernel_size: int | None = 3
|
||||
gaussian_blur_sigma: float = 1.0
|
||||
bin_size_post: int | None = None
|
||||
|
||||
# ------------------------
|
||||
example_position_x = example_position_x // bin_size
|
||||
example_position_y = example_position_y // bin_size
|
||||
if bin_size_post is not None:
|
||||
example_position_x = example_position_x // bin_size_post
|
||||
example_position_y = example_position_y // bin_size_post
|
||||
|
||||
torch_device: torch.device = torch.device(
|
||||
"cuda:0" if torch.cuda.is_available() else "cpu"
|
||||
)
|
||||
|
||||
af = DataContainer(
|
||||
path=path,
|
||||
device=torch_device,
|
||||
display_logging_messages=display_logging_messages,
|
||||
save_logging_messages=save_logging_messages,
|
||||
)
|
||||
result, mask = af.automatic_load(
|
||||
experiment_id=experiment_id,
|
||||
trial_id=trial_id,
|
||||
start_position=start_position,
|
||||
remove_heartbeat=use_svd, # i.e. use SVD
|
||||
iterations=svd_iterations,
|
||||
bin_size=bin_size,
|
||||
initital_mask_name=initital_mask_name,
|
||||
initital_mask_update=initital_mask_update,
|
||||
initital_mask_roi=initital_mask_roi,
|
||||
start_position_coefficients=start_position_coefficients,
|
||||
gaussian_blur_kernel_size=gaussian_blur_kernel_size,
|
||||
gaussian_blur_sigma=gaussian_blur_sigma,
|
||||
bin_size_post=bin_size_post,
|
||||
threshold=mask_threshold,
|
||||
)
|
||||
|
||||
if show_example_timeseries:
|
||||
plt.plot(result[:, example_position_x, example_position_y].cpu())
|
||||
plt.show()
|
||||
|
||||
if export_results:
|
||||
if use_svd:
|
||||
np.save(
|
||||
os.path.join(export_path, f"SVD_{experiment_id}_{trial_id}_data.npy"),
|
||||
result.cpu().numpy(),
|
||||
)
|
||||
|
||||
if mask is not None:
|
||||
np.save(
|
||||
os.path.join(
|
||||
export_path, f"SVD_{experiment_id}_{trial_id}_mask.npy"
|
||||
),
|
||||
result.cpu().numpy(),
|
||||
)
|
||||
|
||||
else:
|
||||
np.save(
|
||||
os.path.join(
|
||||
export_path, f"Classic_{experiment_id}_{trial_id}_data.npy"
|
||||
),
|
||||
result.cpu().numpy(),
|
||||
)
|
||||
|
||||
if mask is not None:
|
||||
np.save(
|
||||
os.path.join(
|
||||
export_path, f"Classic_{experiment_id}_{trial_id}_mask.npy"
|
||||
),
|
||||
result.cpu().numpy(),
|
||||
)
|
||||
|
||||
if movie_play:
|
||||
ani = Anime()
|
||||
if movie_enable_mask:
|
||||
ani.show(
|
||||
result - 1.0,
|
||||
mask=mask,
|
||||
vmin_scale=movie_vmin_scale,
|
||||
vmax_scale=movie_vmax_scale,
|
||||
movie_file=movie_file,
|
||||
)
|
||||
else:
|
||||
ani.show(
|
||||
result - 1.0,
|
||||
vmin_scale=movie_vmin_scale,
|
||||
vmax_scale=movie_vmax_scale,
|
||||
movie_file=movie_file,
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
argh.dispatch_command(main)
|
||||
Loading…
Reference in a new issue