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# -*- coding: utf-8 -*-
import numpy as np # type: ignore
def get_unwanted_bytes_ids(image_group_data, image_data_start, height, width):
# Check if the byte array size conforms to the image axes size. If not, check
# that the number of unexpected (unwanted) bytes is a multiple of the number of
# rows (height), as the same number of unwanted bytes is expected to be
# appended at the end of each row. Then, returns the indexes of the unwanted
# bytes.
# Skip the first 4 elements that correspond to the time stamp
number_of_true_channels = int(len(image_group_data[4:]) / (height * width))
n_unwanted_bytes = (len(image_group_data[4:])) % (height * width)
if not n_unwanted_bytes:
return np.arange(0)
assert 0 == n_unwanted_bytes % height, (
"An unexpected number of extra bytes was encountered based on the expected"
+ " frame size, therefore the file could not be parsed."
)
return np.arange(
image_data_start + width * number_of_true_channels,
len(image_group_data) - n_unwanted_bytes + 1,
width * number_of_true_channels,
)
def remove_parsed_unwanted_bytes(image_group_data, image_data_start, height, width):
# Stitched ND2 files have been reported to contain unexpected (according to
# image shape) zero bytes at the end of each image data row. This hinders
# proper reshaping of the data. Hence, here the unwanted zero bytes are
# identified and removed.
unwanted_byte_ids = get_unwanted_bytes_ids(
image_group_data, image_data_start, height, width
)
if 0 != len(unwanted_byte_ids):
image_group_data = np.delete(np.array(image_group_data), unwanted_byte_ids)
return image_group_data