Browse Source

much refactor. very change

master
Jim Rybarski 10 years ago
parent
commit
d06153fa0d
4 changed files with 305 additions and 357 deletions
  1. +126
    -41
      nd2reader/__init__.py
  2. +0
    -19
      nd2reader/model/__init__.py
  3. +179
    -0
      nd2reader/parser.py
  4. +0
    -297
      nd2reader/reader.py

+ 126
- 41
nd2reader/__init__.py View File

@ -1,27 +1,31 @@
# -*- coding: utf-8 -*-
from nd2reader.model import Channel
import array
from datetime import datetime
import logging
from nd2reader.model import Image, ImageSet
from nd2reader.reader import Nd2FileReader
from nd2reader.parser import Nd2Parser
import numpy as np
import re
import struct
log = logging.getLogger(__name__)
log.addHandler(logging.StreamHandler())
log.setLevel(logging.WARN)
class Nd2(Nd2FileReader):
def __init__(self, filename):
class Nd2(Nd2Parser):
def __init__(self, filename, image_sets=False):
super(Nd2, self).__init__(filename)
self._use_image_sets = image_sets
def __iter__(self):
"""
Just return every image in order (might not be exactly the order that the images were physically taken, but it will
be within a few seconds). A better explanation is probably needed here.
if self._use_image_sets:
return self.image_sets()
else:
return self.images()
"""
def images(self):
for i in range(self._image_count):
for fov in range(self.field_of_view_count):
for z_level in range(self.z_level_count):
@ -30,34 +34,27 @@ class Nd2(Nd2FileReader):
if image.is_valid:
yield image
def image_sets(self, field_of_view, time_indices=None, channels=None, z_levels=None):
"""
Gets all the images for a given field of view and
"""
timepoint_set = xrange(self.time_index_count) if time_indices is None else time_indices
channel_set = [channel.name for channel in self.channels] if channels is None else channels
z_level_set = xrange(self.z_level_count) if z_levels is None else z_levels
for timepoint in timepoint_set:
def image_sets(self):
for time_index in xrange(self.time_index_count):
image_set = ImageSet()
for channel_name in channel_set:
for z_level in z_level_set:
image = self.get_image(timepoint, field_of_view, channel_name, z_level)
if image.is_valid:
image_set.add(image)
for fov in range(self.field_of_view_count):
for channel_name in self.channels:
for z_level in xrange(self.z_level_count):
image = self.get_image(time_index, fov, channel_name, z_level)
if image.is_valid:
image_set.add(image)
yield image_set
self._channel_offset = None
@property
def metadata(self):
return self._metadata
def get_image(self, time_index, fov, channel_name, z_level):
image_set_number = self._calculate_image_set_number(time_index, fov, z_level)
timestamp, raw_image_data = self._get_raw_image_data(image_set_number, self._channel_offset[channel_name])
return Image(timestamp, raw_image_data, fov, channel_name, z_level, self.height, self.width)
@property
def channels(self):
metadata = self._metadata['ImageMetadataSeq']['SLxPictureMetadata']['sPicturePlanes']
metadata = self.metadata['ImageMetadataSeq']['SLxPictureMetadata']['sPicturePlanes']
try:
validity = self._metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx'][''][0]['ppNextLevelEx'][''][0]['pItemValid']
validity = self.metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx'][''][0]['ppNextLevelEx'][''][0]['pItemValid']
except KeyError:
# If none of the channels have been deleted, there is no validity list, so we just make one
validity = [True for i in metadata]
@ -67,26 +64,28 @@ class Nd2(Nd2FileReader):
for (label, chan), valid in zip(sorted(metadata['sPlaneNew'].items()), validity):
if not valid:
continue
name = chan['sDescription']
exposure_time = metadata['sSampleSetting'][label]['dExposureTime']
camera = metadata['sSampleSetting'][label]['pCameraSetting']['CameraUserName']
yield Channel(name, camera, exposure_time)
yield chan['sDescription']
@property
def channel_names(self):
def height(self):
"""
A convenience method for getting an alphabetized list of channel names.
:return: height of each image, in pixels
:return: list[str]
"""
return self.metadata['ImageAttributes']['SLxImageAttributes']['uiHeight']
@property
def width(self):
"""
for channel in sorted(self.channels, key=lambda x: x.name):
yield channel.name
:return: width of each image, in pixels
"""
return self.metadata['ImageAttributes']['SLxImageAttributes']['uiWidth']
@property
def absolute_start(self):
if self._absolute_start is None:
for line in self._metadata['ImageTextInfo']['SLxImageTextInfo'].values():
for line in self.metadata['ImageTextInfo']['SLxImageTextInfo'].values():
absolute_start_12 = None
absolute_start_24 = None
# ND2s seem to randomly switch between 12- and 24-hour representations.
@ -101,4 +100,90 @@ class Nd2(Nd2FileReader):
if not absolute_start_12 and not absolute_start_24:
continue
self._absolute_start = absolute_start_12 if absolute_start_12 else absolute_start_24
return self._absolute_start
return self._absolute_start
@property
def channel_count(self):
pattern = r""".*?λ\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def field_of_view_count(self):
"""
The metadata contains information about fields of view, but it contains it even if some fields
of view were cropped. We can't find anything that states which fields of view are actually
in the image data, so we have to calculate it. There probably is something somewhere, since
NIS Elements can figure it out, but we haven't found it yet.
"""
pattern = r""".*?XY\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def time_index_count(self):
"""
The number of image sets. If images were acquired using some kind of cycle, all images at each step in the
program will have the same timestamp (even though they may have varied by a few seconds in reality). For example,
if you have four fields of view that you're constantly monitoring, and you take a bright field and GFP image of
each, and you repeat that process 100 times, you'll have 800 individual images. But there will only be 400
time indexes.
:rtype: int
"""
pattern = r""".*?T'\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def z_level_count(self):
pattern = r""".*?Z\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@staticmethod
def as_numpy_array(arr):
return np.frombuffer(arr)
@property
def _channel_offset(self):
"""
Image data is interleaved for each image set. That is, if there are four images in a set, the first image
will consist of pixels 1, 5, 9, etc, the second will be pixels 2, 6, 10, and so forth. Why this would be the
case is beyond me, but that's how it works.
"""
channel_offset = {}
for n, channel in enumerate(self.channels):
self._channel_offset[channel.name] = n
return channel_offset
def _get_raw_image_data(self, image_set_number, channel_offset):
chunk = self._label_map["ImageDataSeq|%d!" % image_set_number]
data = self._read_chunk(chunk)
timestamp = struct.unpack("d", data[:8])[0]
# The images for the various channels are interleaved within each other.
image_data = array.array("H", data)
image_data_start = 4 + channel_offset
return timestamp, image_data[image_data_start::self.channel_count]
def _calculate_image_set_number(self, time_index, fov, z_level):
return time_index * self.field_of_view_count * self.z_level_count + (fov * self.z_level_count + z_level)

+ 0
- 19
nd2reader/model/__init__.py View File

@ -5,25 +5,6 @@ import logging
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


+ 179
- 0
nd2reader/parser.py View File

@ -0,0 +1,179 @@
# -*- coding: utf-8 -*-
import array
from collections import namedtuple
import struct
from StringIO import StringIO
field_of_view = namedtuple('FOV', ['number', 'x', 'y', 'z', 'pfs_offset'])
class Nd2Parser(object):
CHUNK_HEADER = 0xabeceda
CHUNK_MAP_START = "ND2 FILEMAP SIGNATURE NAME 0001!"
CHUNK_MAP_END = "ND2 CHUNK MAP SIGNATURE 0000001!"
"""
Reads .nd2 files, provides an interface to the metadata, and generates numpy arrays from the image data.
"""
def __init__(self, filename):
self._absolute_start = None
self._filename = filename
self._fh = None
self._chunk_map_start_location = None
self._cursor_position = None
self._dimension_text = None
self._label_map = {}
self.metadata = {}
self._read_map()
self._parse_metadata()
@property
def _file_handle(self):
if self._fh is None:
self._fh = open(self._filename, "rb")
return self._fh
@property
def _dimensions(self):
if self._dimension_text is None:
for line in self.metadata['ImageTextInfo']['SLxImageTextInfo'].values():
if "Dimensions:" in line:
metadata = line
break
else:
raise ValueError("Could not parse metadata dimensions!")
for line in metadata.split("\r\n"):
if line.startswith("Dimensions:"):
self._dimension_text = line
break
else:
raise ValueError("Could not parse metadata dimensions!")
return self._dimension_text
@property
def _image_count(self):
return self.metadata['ImageAttributes']['SLxImageAttributes']['uiSequenceCount']
@property
def _sequence_count(self):
return self.metadata['ImageEvents']['RLxExperimentRecord']['uiCount']
def _parse_metadata(self):
for label in self._label_map.keys():
if not label.endswith("LV!") or "LV|" in label:
continue
data = self._read_chunk(self._label_map[label])
stop = label.index("LV")
self.metadata[label[:stop]] = self._read_metadata(data, 1)
def _read_map(self):
"""
Every label ends with an exclamation point, however, we can't directly search for those to find all the labels
as some of the bytes contain the value 33, which is the ASCII code for "!". So we iteratively find each label,
grab the subsequent data (always 16 bytes long), advance to the next label and repeat.
"""
self._file_handle.seek(-8, 2)
chunk_map_start_location = struct.unpack("Q", self._file_handle.read(8))[0]
self._file_handle.seek(chunk_map_start_location)
raw_text = self._file_handle.read(-1)
label_start = raw_text.index(Nd2Parser.CHUNK_MAP_START) + 32
while True:
data_start = raw_text.index("!", label_start) + 1
key = raw_text[label_start: data_start]
location, length = struct.unpack("QQ", raw_text[data_start: data_start + 16])
if key == Nd2Parser.CHUNK_MAP_END:
# We've reached the end of the chunk map
break
self._label_map[key] = location
label_start = data_start + 16
def _read_chunk(self, chunk_location):
"""
Gets the data for a given chunk pointer
"""
self._file_handle.seek(chunk_location)
# The chunk metadata is always 16 bytes long
chunk_metadata = self._file_handle.read(16)
header, relative_offset, data_length = struct.unpack("IIQ", chunk_metadata)
if header != Nd2Parser.CHUNK_HEADER:
raise ValueError("The ND2 file seems to be corrupted.")
# We start at the location of the chunk metadata, skip over the metadata, and then proceed to the
# start of the actual data field, which is at some arbitrary place after the metadata.
self._file_handle.seek(chunk_location + 16 + relative_offset)
return self._file_handle.read(data_length)
def _z_level_count(self):
st = self._read_chunk(self._label_map["CustomData|Z!"])
return len(array.array("d", st))
def _parse_unsigned_char(self, data):
return struct.unpack("B", data.read(1))[0]
def _parse_unsigned_int(self, data):
return struct.unpack("I", data.read(4))[0]
def _parse_unsigned_long(self, data):
return struct.unpack("Q", data.read(8))[0]
def _parse_double(self, data):
return struct.unpack("d", data.read(8))[0]
def _parse_string(self, data):
value = data.read(2)
while not value.endswith("\x00\x00"):
# the string ends at the first instance of \x00\x00
value += data.read(2)
return value.decode("utf16")[:-1].encode("utf8")
def _parse_char_array(self, data):
array_length = struct.unpack("Q", data.read(8))[0]
return array.array("B", data.read(array_length))
def _parse_metadata_item(self, args):
data, cursor_position = args
new_count, length = struct.unpack("<IQ", data.read(12))
length -= data.tell() - cursor_position
next_data_length = data.read(length)
value = self._read_metadata(next_data_length, new_count)
# Skip some offsets
data.read(new_count * 8)
return value
def _get_value(self, data, data_type):
parser = {1: {'method': self._parse_unsigned_char, 'args': data},
2: {'method': self._parse_unsigned_int, 'args': data},
3: {'method': self._parse_unsigned_int, 'args': data},
5: {'method': self._parse_unsigned_long, 'args': data},
6: {'method': self._parse_double, 'args': data},
8: {'method': self._parse_string, 'args': data},
9: {'method': self._parse_char_array, 'args': data},
11: {'method': self._parse_metadata_item, 'args': (data, self._cursor_position)}}
return parser[data_type]['method'](parser[data_type]['args'])
def _read_metadata(self, data, count):
data = StringIO(data)
metadata = {}
for _ in xrange(count):
self._cursor_position = data.tell()
header = data.read(2)
if not header:
break
data_type, name_length = map(ord, header)
name = data.read(name_length * 2).decode("utf16")[:-1].encode("utf8")
value = self._get_value(data, data_type)
if name not in metadata:
metadata[name] = value
else:
if not isinstance(metadata[name], list):
# We have encountered this key exactly once before. Since we're seeing it again, we know we
# need to convert it to a list before proceeding.
metadata[name] = [metadata[name]]
# We've encountered this key before so we're guaranteed to be dealing with a list. Thus we append
# the value to the already-existing list.
metadata[name].append(value)
return metadata

+ 0
- 297
nd2reader/reader.py View File

@ -1,297 +0,0 @@
# -*- coding: utf-8 -*-
from abc import abstractproperty
import array
from collections import namedtuple
import numpy as np
import struct
import re
from StringIO import StringIO
from nd2reader.model import Image
field_of_view = namedtuple('FOV', ['number', 'x', 'y', 'z', 'pfs_offset'])
class Nd2FileReader(object):
CHUNK_HEADER = 0xabeceda
CHUNK_MAP_START = "ND2 FILEMAP SIGNATURE NAME 0001!"
CHUNK_MAP_END = "ND2 CHUNK MAP SIGNATURE 0000001!"
"""
Reads .nd2 files, provides an interface to the metadata, and generates numpy arrays from the image data.
"""
def __init__(self, filename):
self._absolute_start = None
self._filename = filename
self._file_handler = None
self._channel_offset = None
self._chunk_map_start_location = None
self._cursor_position = None
self._label_map = {}
self._metadata = {}
self._read_map()
self._parse_metadata()
self.__dimensions = None
@staticmethod
def as_numpy_array(arr):
return np.frombuffer(arr)
def get_image(self, time_index, fov, channel_name, z_level):
image_set_number = self._calculate_image_set_number(time_index, fov, z_level)
timestamp, raw_image_data = self.get_raw_image_data(image_set_number, self.channel_offset[channel_name])
return Image(timestamp, raw_image_data, fov, channel_name, z_level, self.height, self.width)
@abstractproperty
def channels(self):
raise NotImplemented
@property
def height(self):
"""
:return: height of each image, in pixels
"""
return self._metadata['ImageAttributes']['SLxImageAttributes']['uiHeight']
@property
def width(self):
"""
:return: width of each image, in pixels
"""
return self._metadata['ImageAttributes']['SLxImageAttributes']['uiWidth']
@property
def _dimensions(self):
if self.__dimensions is None:
# The particular slot that this data shows up in changes (seemingly) randomly
for line in self._metadata['ImageTextInfo']['SLxImageTextInfo'].values():
if "Dimensions:" in line:
metadata = line
break
else:
raise Exception("Could not parse metadata dimensions!")
for line in metadata.split("\r\n"):
if line.startswith("Dimensions:"):
self.__dimensions = line
break
return self.__dimensions
@property
def fh(self):
if self._file_handler is None:
self._file_handler = open(self._filename, "rb")
return self._file_handler
@property
def time_index_count(self):
"""
The number of image sets. If images were acquired using some kind of cycle, all images at each step in the
program will have the same timestamp (even though they may have varied by a few seconds in reality). For example,
if you have four fields of view that you're constantly monitoring, and you take a bright field and GFP image of
each, and you repeat that process 100 times, you'll have 800 individual images. But there will only be 400
time indexes.
:rtype: int
"""
pattern = r""".*?T'\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def z_level_count(self):
pattern = r""".*?Z\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def field_of_view_count(self):
"""
The metadata contains information about fields of view, but it contains it even if some fields
of view were cropped. We can't find anything that states which fields of view are actually
in the image data, so we have to calculate it. There probably is something somewhere, since
NIS Elements can figure it out, but we haven't found it yet.
"""
pattern = r""".*?XY\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def channel_count(self):
pattern = r""".*?λ\((\d+)\).*?"""
try:
count = int(re.match(pattern, self._dimensions).group(1))
except AttributeError:
return 1
else:
return count
@property
def _image_count(self):
return self._metadata['ImageAttributes']['SLxImageAttributes']['uiSequenceCount']
@property
def _sequence_count(self):
return self._metadata['ImageEvents']['RLxExperimentRecord']['uiCount']
@property
def channel_offset(self):
"""
Image data is interleaved for each image set. That is, if there are four images in a set, the first image
will consist of pixels 1, 5, 9, etc, the second will be pixels 2, 6, 10, and so forth. Why this would be the
case is beyond me, but that's how it works.
"""
if self._channel_offset is None:
self._channel_offset = {}
for n, channel in enumerate(self.channels):
self._channel_offset[channel.name] = n
return self._channel_offset
def _calculate_image_set_number(self, time_index, fov, z_level):
return time_index * self.field_of_view_count * self.z_level_count + (fov * self.z_level_count + z_level)
def get_raw_image_data(self, image_set_number, channel_offset):
chunk = self._label_map["ImageDataSeq|%d!" % image_set_number]
data = self._read_chunk(chunk)
timestamp = struct.unpack("d", data[:8])[0]
# The images for the various channels are interleaved within each other.
image_data = array.array("H", data)
image_data_start = 4 + channel_offset
return timestamp, image_data[image_data_start::self.channel_count]
def _parse_metadata(self):
for label in self._label_map.keys():
if not label.endswith("LV!") or "LV|" in label:
continue
data = self._read_chunk(self._label_map[label])
stop = label.index("LV")
self._metadata[label[:stop]] = self._read_file(data, 1)
def _read_map(self):
"""
Every label ends with an exclamation point, however, we can't directly search for those to find all the labels
as some of the bytes contain the value 33, which is the ASCII code for "!". So we iteratively find each label,
grab the subsequent data (always 16 bytes long), advance to the next label and repeat.
"""
self.fh.seek(-8, 2)
chunk_map_start_location = struct.unpack("Q", self.fh.read(8))[0]
self.fh.seek(chunk_map_start_location)
raw_text = self.fh.read(-1)
label_start = raw_text.index(Nd2FileReader.CHUNK_MAP_START) + 32
while True:
data_start = raw_text.index("!", label_start) + 1
key = raw_text[label_start: data_start]
location, length = struct.unpack("QQ", raw_text[data_start: data_start + 16])
if key == Nd2FileReader.CHUNK_MAP_END:
# We've reached the end of the chunk map
break
self._label_map[key] = location
label_start = data_start + 16
def _read_chunk(self, chunk_location):
"""
Gets the data for a given chunk pointer
"""
self.fh.seek(chunk_location)
# The chunk metadata is always 16 bytes long
chunk_metadata = self.fh.read(16)
header, relative_offset, data_length = struct.unpack("IIQ", chunk_metadata)
if header != Nd2FileReader.CHUNK_HEADER:
raise ValueError("The ND2 file seems to be corrupted.")
# We start at the location of the chunk metadata, skip over the metadata, and then proceed to the
# start of the actual data field, which is at some arbitrary place after the metadata.
self.fh.seek(chunk_location + 16 + relative_offset)
return self.fh.read(data_length)
def _z_level_count(self):
name = "CustomData|Z!"
st = self._read_chunk(self._label_map[name])
return len(array.array("d", st))
def _parse_unsigned_char(self, data):
return struct.unpack("B", data.read(1))[0]
def _parse_unsigned_int(self, data):
return struct.unpack("I", data.read(4))[0]
def _parse_unsigned_long(self, data):
return struct.unpack("Q", data.read(8))[0]
def _parse_double(self, data):
return struct.unpack("d", data.read(8))[0]
def _parse_string(self, data):
value = data.read(2)
while not value.endswith("\x00\x00"):
# the string ends at the first instance of \x00\x00
value += data.read(2)
return value.decode("utf16")[:-1].encode("utf8")
def _parse_char_array(self, data):
array_length = struct.unpack("Q", data.read(8))[0]
return array.array("B", data.read(array_length))
def _parse_metadata_item(self, args):
data, cursor_position = args
new_count, length = struct.unpack("<IQ", data.read(12))
length -= data.tell() - cursor_position
next_data_length = data.read(length)
value = self._read_file(next_data_length, new_count)
# Skip some offsets
data.read(new_count * 8)
return value
def _get_value(self, data, data_type):
parser = {1: {'method': self._parse_unsigned_char, 'args': data},
2: {'method': self._parse_unsigned_int, 'args': data},
3: {'method': self._parse_unsigned_int, 'args': data},
5: {'method': self._parse_unsigned_long, 'args': data},
6: {'method': self._parse_double, 'args': data},
8: {'method': self._parse_string, 'args': data},
9: {'method': self._parse_char_array, 'args': data},
11: {'method': self._parse_metadata_item, 'args': (data, self._cursor_position)}}
return parser[data_type]['method'](parser[data_type]['args'])
def _read_file(self, data, count):
data = StringIO(data)
metadata = {}
for _ in xrange(count):
self._cursor_position = data.tell()
header = data.read(2)
if not header:
break
data_type, name_length = map(ord, header)
name = data.read(name_length * 2).decode("utf16")[:-1].encode("utf8")
value = self._get_value(data, data_type)
if name not in metadata:
metadata[name] = value
else:
if not isinstance(metadata[name], list):
# We have encountered this key exactly once before. Since we're seeing it again, we know we
# need to convert it to a list before proceeding.
metadata[name] = [metadata[name]]
# We've encountered this key before so we're guaranteed to be dealing with a list. Thus we append
# the value to the already-existing list.
metadata[name].append(value)
return metadata

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