#print("local_path")
# Check whether the image is not present
if fs.is_file(local_path):
log.warning(
"The '" + name +
"' remotely cached image is still present locally. Keeping this file and throwing the remote file away."
)
continue
else:
# Infomr
log.info("Downloading the '" + name + "' file to [" + origin_path +
"] ...")
# Download
remote.download_file_to(path, origin_path, remove=True)
# Success
log.success("Succesfully retrieved the '" + name + "' image ...")
# Inform the user
log.info("Clearing the remote data structure ...")
# Clear the entire data structure now
remote.clear_directory(remote_data_path)
# -----------------------------------------------------------------
# Get the image paths
paths, error_paths = get_data_image_and_error_paths(modeling_path)
if np.isclose(factor, config.factor, rtol=0.01):
the_image_path = image_path
break
# Check
if the_image_path is None:
raise ValueError("Could not find the truncated " + filter_name +
" image with a truncation factor of " +
str(config.factor))
# -----------------------------------------------------------------
# Download the image to a temporary path
filename = time.unique_name("truncated_" + filter_name + "_" +
str(config.factor))
filepath = remote.download_file_to(the_image_path,
pts_temp_dir,
new_name=filename)
# -----------------------------------------------------------------
# Open the image
frame = Frame.from_file(filepath)
# -----------------------------------------------------------------
# Plot the truncated image
plotting.plot_box(frame)
# -----------------------------------------------------------------
