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import numpy as np
import skimage.io
import logging
from io import BytesIO
import array
import struct
log = logging.getLogger(__name__)
class Channel(object):
def __init__(self, name, camera, exposure_time):
self._name = name
self._camera = camera
self._exposure_time = exposure_time
@property
def name(self):
return self._name
@property
def camera(self):
return self._camera
@property
def exposure_time(self):
return self._exposure_time
class ImageSet(object):
"""
A group of images that share the same timestamp. NIS Elements doesn't store a unique timestamp for every
image, rather, it stores one for each set of images that share the same field of view and z-axis level.
"""
def __init__(self):
self._images = []
def add(self, image):
"""
:type image: nd2reader.model.Image()
"""
self._images.append(image)
def __iter__(self):
for image in self._images:
yield image
class Image(object):
def __init__(self, timestamp, raw_array, field_of_view, channel, z_level, height, width):
self._timestamp = timestamp
self._raw_data = raw_array
self._field_of_view = field_of_view
self._channel = channel
self._z_level = z_level
self._height = height
self._width = width
self._data = None
@property
def field_of_view(self):
return self._field_of_view
@property
def timestamp(self):
"""
The number of seconds after the beginning of the acquisition that the image was taken. Note that for a given field
of view and z-level offset, if you have images of multiple channels, they will all be given the same timestamp.
No, this doesn't make much sense. But that's how ND2s are structured, so if your experiment depends on millisecond
accuracy, you need to find an alternative imaging system.
"""
return self._timestamp / 1000.0
@property
def channel(self):
return self._channel
@property
def z_level(self):
return self._z_level
@property
def data(self):
if self._data is None:
# The data is just a flat, 1-dimensional array. We convert it to a 2D array and cast the data points as 16-bit integers
self._data = np.reshape(self._raw_data, (self._height, self._width)).astype(np.int64).astype(np.uint16)
return self._data
@property
def is_valid(self):
return np.any(self.data)
def show(self):
skimage.io.imshow(self.data)
skimage.io.show()
class MetadataItem(object):
def __init__(self, start, data):
self._datatype = ord(data[start])
self._label_length = 2 * ord(data[start + 1])
self._data = data
@property
def is_valid(self):
return self._datatype > 0
@property
def key(self):
return self._data[2:self._label_length].decode("utf16").encode("utf8")
@property
def length(self):
return self._length
@property
def data_start(self):
return self._label_length + 2
@property
def _body(self):
"""
All data after the header.
"""
return self._data[self.data_start:]
def _get_bytes(self, count):
return self._data[self.data_start: self.data_start + count]
@property
def value(self):
parser = {1: self._parse_unsigned_char,
2: self._parse_unsigned_int,
3: self._parse_unsigned_int,
5: self._parse_unsigned_long,
6: self._parse_double,
8: self._parse_string,
9: self._parse_char_array,
11: self._parse_metadata_item
}
return parser[self._datatype]()
def _parse_unsigned_char(self):
self._length = 1
return self._unpack("B", self._get_bytes(self._length))
def _parse_unsigned_int(self):
self._length = 4
return self._unpack("I", self._get_bytes(self._length))
def _parse_unsigned_long(self):
self._length = 8
return self._unpack("Q", self._get_bytes(self._length))
def _parse_double(self):
self._length = 8
return self._unpack("d", self._get_bytes(self._length))
def _parse_string(self):
# the string is of unknown length but ends at the first instance of \x00\x00
stop = self._body.index("\x00\x00")
self._length = stop
return self._body[:stop - 1].decode("utf16").encode("utf8")
def _parse_char_array(self):
array_length = self._unpack("Q", self._get_bytes(8))
self._length = array_length + 8
return array.array("B", self._body[8:array_length])
def _parse_metadata_item(self):
count, length = struct.unpack("<IQ", self._get_bytes(12))
metadata_set = MetadataSet(self._body, 0, count)
def _unpack(self, kind, data):
"""
:param kind: the datatype to interpret the bytes as (see: https://docs.python.org/2/library/struct.html#struct-format-strings)
:type kind: str
:param data: the bytes to be converted
:type data: bytes
Parses a sequence of bytes and converts them to a Python data type.
struct.unpack() returns a tuple but we only want the first element.
"""
return struct.unpack(kind, data)[0]
class MetadataSet(object):
"""
A container of metadata items. Can contain other MetadataSet objects.
"""
def __init__(self, data, start, item_count):
self._items = []
self._parse(data, start, item_count)
def _parse(self, data, start, item_count):
for item in range(item_count):
metadata_item = MetadataItem(start, data)
if not metadata_item.is_valid:
break
start += metadata_item.length
class Chunkmap(object):
def __init__(self):
pass
def read(self, filename):
with open(filename, "rb") as f:
data = f.read(-1)
self.parse(data, 1)
def parse(self, data, count):
data = BytesIO(data)
res = {}
total_count = 0
for c in range(count):
lastpos = data.tell()
total_count += 1
hdr = data.read(2)
if not hdr:
break
typ = ord(hdr[0])
bname = data.read(2*ord(hdr[1]))
name = bname.decode("utf16")[:-1].encode("utf8")
if typ == 1:
value, = struct.unpack("B", data.read(1))
elif typ in [2, 3]:
value, = struct.unpack("I", data.read(4))
elif typ == 5:
value, = struct.unpack("Q", data.read(8))
elif typ == 6:
value, = struct.unpack("d", data.read(8))
elif typ == 8:
value = data.read(2)
while value[-2:] != "\x00\x00":
value += data.read(2)
value = value.decode("utf16")[:-1].encode("utf8")
elif typ == 9:
cnt, = struct.unpack("Q", data.read(8))
value = array.array("B", data.read(cnt))
elif typ == 11:
curpos = data.tell()
newcount, length = struct.unpack("<IQ", data.read(12))
curpos = data.tell()
length -= data.tell()-lastpos
nextdata = data.read(length)
value = self.parse(nextdata, newcount)
# Skip some offsets
data.read(newcount * 8)
else:
assert 0, "%s hdr %x:%x unknown" % (name, ord(hdr[0]), ord(hdr[1]))
if not name in res:
res[name] = value
else:
if not isinstance(res[name], list):
res[name] = [res[name]]
res[name].append(value)
x = data.read()
assert not x, "skip %d %s" % (len(x), repr(x[:30]))
return res