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Delete stage_2_make_heartbeat_mask.py
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import matplotlib.pyplot as plt # type:ignore
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import matplotlib
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import numpy as np
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import torch
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import os
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import argh
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from matplotlib.widgets import Slider, Button # type:ignore
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from functools import partial
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from functions.gauss_smear_individual import gauss_smear_individual
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from functions.create_logger import create_logger
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from functions.get_torch_device import get_torch_device
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from functions.load_config import load_config
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def main(*, config_filename: str = "config.json") -> None:
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mylogger = create_logger(
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save_logging_messages=True,
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display_logging_messages=True,
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log_stage_name="stage_2",
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)
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config = load_config(mylogger=mylogger, filename=config_filename)
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path: str = config["ref_image_path"]
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use_channel: str = "donor"
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spatial_width: float = 4.0
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temporal_width: float = 0.1
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threshold: float = 0.05
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heartbeat_mask_threshold_file: str = os.path.join(
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path, "heartbeat_mask_threshold.npy"
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)
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if os.path.isfile(heartbeat_mask_threshold_file):
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mylogger.info(
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f"loading previous threshold file: {heartbeat_mask_threshold_file}"
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)
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threshold = float(np.load(heartbeat_mask_threshold_file)[0])
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mylogger.info(f"initial threshold is {threshold}")
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image_ref_file: str = os.path.join(path, use_channel + ".npy")
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image_var_file: str = os.path.join(path, use_channel + "_var.npy")
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heartbeat_mask_file: str = os.path.join(path, "heartbeat_mask.npy")
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device = get_torch_device(mylogger, config["force_to_cpu"])
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mylogger.info(f"loading image reference file: {image_ref_file}")
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image_ref: np.ndarray = np.load(image_ref_file)
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image_ref /= image_ref.max()
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mylogger.info(f"loading image heartbeat power: {image_var_file}")
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image_var: np.ndarray = np.load(image_var_file)
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image_var /= image_var.max()
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mylogger.info("Smear the image heartbeat power patially")
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temp, _ = gauss_smear_individual(
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input=torch.tensor(image_var[..., np.newaxis], device=device),
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spatial_width=spatial_width,
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temporal_width=temporal_width,
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use_matlab_mask=False,
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)
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temp /= temp.max()
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mylogger.info("-==- DONE -==-")
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image_3color = np.concatenate(
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(
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np.zeros_like(image_ref[..., np.newaxis]),
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image_ref[..., np.newaxis],
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temp.cpu().numpy(),
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),
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axis=-1,
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)
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mylogger.info("Prepare image")
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display_image = image_3color.copy()
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display_image[..., 2] = display_image[..., 0]
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mask = np.where(image_3color[..., 2] >= threshold, 1.0, np.nan)[..., np.newaxis]
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display_image *= mask
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display_image = np.nan_to_num(display_image, nan=1.0)
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value_sort = np.sort(image_var.flatten())
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value_sort_max = value_sort[int(value_sort.shape[0] * 0.95)] * 3
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print(value_sort_max)
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mylogger.info("-==- DONE -==-")
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mylogger.info("Create figure")
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fig: matplotlib.figure.Figure = plt.figure()
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image_handle = plt.imshow(display_image, vmin=0, vmax=1, cmap="hot")
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mylogger.info("Add controls")
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def next_frame(
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i: float, images: np.ndarray, image_handle: matplotlib.image.AxesImage
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) -> None:
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nonlocal threshold
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threshold = i
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display_image: np.ndarray = images.copy()
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display_image[..., 2] = display_image[..., 0]
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mask: np.ndarray = np.where(images[..., 2] >= i, 1.0, np.nan)[..., np.newaxis]
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display_image *= mask
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display_image = np.nan_to_num(display_image, nan=1.0)
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image_handle.set_data(display_image)
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return
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def on_clicked_accept(event: matplotlib.backend_bases.MouseEvent) -> None:
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nonlocal threshold
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nonlocal image_3color
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nonlocal path
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nonlocal mylogger
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nonlocal heartbeat_mask_file
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nonlocal heartbeat_mask_threshold_file
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mylogger.info(f"Threshold: {threshold}")
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mask: np.ndarray = image_3color[..., 2] >= threshold
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mylogger.info(f"Save mask to: {heartbeat_mask_file}")
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np.save(heartbeat_mask_file, mask)
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mylogger.info(f"Save threshold to: {heartbeat_mask_threshold_file}")
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np.save(heartbeat_mask_threshold_file, np.array([threshold]))
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exit()
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def on_clicked_cancel(event: matplotlib.backend_bases.MouseEvent) -> None:
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exit()
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axfreq = fig.add_axes(rect=(0.4, 0.9, 0.3, 0.03))
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slice_slider = Slider(
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ax=axfreq,
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label="Threshold",
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valmin=0,
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valmax=value_sort_max,
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valinit=threshold,
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valstep=value_sort_max / 1000.0,
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)
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axbutton_accept = fig.add_axes(rect=(0.3, 0.85, 0.2, 0.04))
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button_accept = Button(
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ax=axbutton_accept, label="Accept", image=None, color="0.85", hovercolor="0.95"
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)
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button_accept.on_clicked(on_clicked_accept) # type: ignore
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axbutton_cancel = fig.add_axes(rect=(0.55, 0.85, 0.2, 0.04))
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button_cancel = Button(
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ax=axbutton_cancel, label="Cancel", image=None, color="0.85", hovercolor="0.95"
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)
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button_cancel.on_clicked(on_clicked_cancel) # type: ignore
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slice_slider.on_changed(
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partial(next_frame, images=image_3color, image_handle=image_handle)
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)
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mylogger.info("Display")
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plt.show()
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if __name__ == "__main__":
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argh.dispatch_command(main)
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