You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 

319 lines
11 KiB

# -*- coding: utf-8 -*-
from datetime import datetime
from nd2reader.model.metadata import Metadata
from nd2reader.model.label import LabelMap
from nd2reader.parser.base import BaseParser
from nd2reader.driver.v3 import V3Driver
from nd2reader.common.v3 import read_chunk, read_array, read_metadata
import re
import six
import struct
import xmltodict
def ignore_missing(func):
def wrapper(*args, **kwargs):
try:
return func(*args, **kwargs)
except:
return None
return wrapper
class V3RawMetadata(object):
def __init__(self, fh, label_map):
self._fh = fh
self._label_map = label_map
@property
@ignore_missing
def image_text_info(self):
return read_metadata(read_chunk(self._fh, self._label_map.image_text_info), 1)
@property
@ignore_missing
def image_metadata_sequence(self):
return read_metadata(read_chunk(self._fh, self._label_map.image_metadata_sequence), 1)
@property
@ignore_missing
def image_calibration(self):
return read_metadata(read_chunk(self._fh, self._label_map.image_calibration), 1)
@property
@ignore_missing
def image_attributes(self):
return read_metadata(read_chunk(self._fh, self._label_map.image_attributes), 1)
@property
@ignore_missing
def x_data(self):
return read_array(self._fh, 'double', self._label_map.x_data)
@property
@ignore_missing
def y_data(self):
return read_array(self._fh, 'double', self._label_map.y_data)
@property
@ignore_missing
def z_data(self):
return read_array(self._fh, 'double', self._label_map.z_data)
@property
@ignore_missing
def roi_metadata(self):
return read_metadata(read_chunk(self._fh, self._label_map.roi_metadata), 1)
@property
@ignore_missing
def pfs_status(self):
return read_array(self._fh, 'int', self._label_map.pfs_status)
@property
@ignore_missing
def pfs_offset(self):
return read_array(self._fh, 'int', self._label_map.pfs_offset)
@property
@ignore_missing
def camera_exposure_time(self):
return read_array(self._fh, 'double', self._label_map.camera_exposure_time)
@property
@ignore_missing
def lut_data(self):
return xmltodict.parse(read_chunk(self._fh, self._label_map.lut_data))
@property
@ignore_missing
def grabber_settings(self):
return xmltodict.parse(read_chunk(self._fh, self._label_map.grabber_settings))
@property
@ignore_missing
def custom_data(self):
return xmltodict.parse(read_chunk(self._fh, self._label_map.custom_data))
@property
@ignore_missing
def app_info(self):
return xmltodict.parse(read_chunk(self._fh, self._label_map.app_info))
@property
@ignore_missing
def camera_temp(self):
camera_temp = read_array(self._fh, 'double', self._label_map.camera_temp)
if camera_temp:
for temp in map(lambda x: round(x * 100.0, 2), camera_temp):
yield temp
@property
@ignore_missing
def acquisition_times(self):
acquisition_times = read_array(self._fh, 'double', self._label_map.acquisition_times)
if acquisition_times:
for acquisition_time in map(lambda x: x / 1000.0, acquisition_times):
yield acquisition_time
@property
@ignore_missing
def image_metadata(self):
if self._label_map.image_metadata:
return read_metadata(read_chunk(self._fh, self._label_map.image_metadata), 1)
class V3Parser(BaseParser):
""" Parses ND2 files and creates a Metadata and driver object. """
CHUNK_HEADER = 0xabeceda
CHUNK_MAP_START = six.b("ND2 FILEMAP SIGNATURE NAME 0001!")
CHUNK_MAP_END = six.b("ND2 CHUNK MAP SIGNATURE 0000001!")
def __init__(self, fh):
"""
:type fh: file
"""
if six.PY3:
super().__init__(fh)
else:
super(V3Parser, self).__init__(fh)
self._label_map = self._build_label_map()
self.raw_metadata = V3RawMetadata(self._fh, self._label_map)
self._parse_metadata()
@property
def driver(self):
"""
Provides an object that knows how to look up and read images based on an index.
"""
return V3Driver(self.metadata, self._label_map, self._fh)
def _parse_metadata(self):
"""
Reads all metadata and instantiates the Metadata object.
"""
height = self.raw_metadata.image_attributes[six.b('SLxImageAttributes')][six.b('uiHeight')]
width = self.raw_metadata.image_attributes[six.b('SLxImageAttributes')][six.b('uiWidth')]
date = self._parse_date(self.raw_metadata)
fields_of_view = self._parse_fields_of_view(self.raw_metadata)
frames = self._parse_frames(self.raw_metadata)
z_levels = self._parse_z_levels(self.raw_metadata)
total_images_per_channel = self._parse_total_images_per_channel(self.raw_metadata)
channels = self._parse_channels(self.raw_metadata)
pixel_microns = self.raw_metadata.image_calibration.get(six.b('SLxCalibration'), {}).get(six.b('dCalibration'))
self.metadata = Metadata(height, width, channels, date, fields_of_view, frames, z_levels, total_images_per_channel, pixel_microns)
def _parse_date(self, raw_metadata):
"""
The date and time when acquisition began.
:type raw_metadata: V3RawMetadata
:rtype: datetime.datetime() or None
"""
for line in raw_metadata.image_text_info[six.b('SLxImageTextInfo')].values():
line = line.decode("utf8")
absolute_start_12 = None
absolute_start_24 = None
# ND2s seem to randomly switch between 12- and 24-hour representations.
try:
absolute_start_24 = datetime.strptime(line, "%m/%d/%Y %H:%M:%S")
except (TypeError, ValueError):
pass
try:
absolute_start_12 = datetime.strptime(line, "%m/%d/%Y %I:%M:%S %p")
except (TypeError, ValueError):
pass
if not absolute_start_12 and not absolute_start_24:
continue
return absolute_start_12 if absolute_start_12 else absolute_start_24
return None
def _parse_channels(self, raw_metadata):
"""
These are labels created by the NIS Elements user. Typically they may a short description of the filter cube
used (e.g. "bright field", "GFP", etc.)
:type raw_metadata: V3RawMetadata
:rtype: list
"""
channels = []
metadata = raw_metadata.image_metadata_sequence[six.b('SLxPictureMetadata')][six.b('sPicturePlanes')]
try:
validity = raw_metadata.image_metadata[six.b('SLxExperiment')][six.b('ppNextLevelEx')][six.b('')][0][six.b('ppNextLevelEx')][six.b('')][0][six.b('pItemValid')]
except (KeyError, TypeError):
# If none of the channels have been deleted, there is no validity list, so we just make one
validity = [True for _ in metadata]
# Channel information is contained in dictionaries with the keys a0, a1...an where the number
# indicates the order in which the channel is stored. So by sorting the dicts alphabetically
# we get the correct order.
for (label, chan), valid in zip(sorted(metadata[six.b('sPlaneNew')].items()), validity):
if not valid:
continue
channels.append(chan[six.b('sDescription')].decode("utf8"))
return channels
def _parse_fields_of_view(self, raw_metadata):
"""
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.
:type raw_metadata: V3RawMetadata
:rtype: list
"""
return self._parse_dimension(r""".*?XY\((\d+)\).*?""", raw_metadata)
def _parse_frames(self, raw_metadata):
"""
The number of cycles.
:type raw_metadata: V3RawMetadata
:rtype: list
"""
return self._parse_dimension(r""".*?T'?\((\d+)\).*?""", raw_metadata)
def _parse_z_levels(self, raw_metadata):
"""
The different levels in the Z-plane. Just a sequence from 0 to n.
:type raw_metadata: V3RawMetadata
:rtype: list
"""
return self._parse_dimension(r""".*?Z\((\d+)\).*?""", raw_metadata)
def _parse_dimension_text(self, raw_metadata):
"""
While there are metadata values that represent a lot of what we want to capture, they seem to be unreliable.
Sometimes certain elements don't exist, or change their data type randomly. However, the human-readable text
is always there and in the same exact format, so we just parse that instead.
:type raw_metadata: V3RawMetadata
:rtype: str
"""
for line in raw_metadata.image_text_info[six.b('SLxImageTextInfo')].values():
if six.b("Dimensions:") in line:
metadata = line
break
else:
return six.b("")
for line in metadata.split(six.b("\r\n")):
if line.startswith(six.b("Dimensions:")):
dimension_text = line
break
else:
return six.b("")
return dimension_text
def _parse_dimension(self, pattern, raw_metadata):
"""
:param pattern: a valid regex pattern
:type pattern: str
:type raw_metadata: V3RawMetadata
:rtype: list of int
"""
dimension_text = self._parse_dimension_text(raw_metadata)
if six.PY3:
dimension_text = dimension_text.decode("utf8")
match = re.match(pattern, dimension_text)
if not match:
return [0]
count = int(match.group(1))
return list(range(count))
def _parse_total_images_per_channel(self, raw_metadata):
"""
The total number of images per channel. Warning: this may be inaccurate as it includes "gap" images.
:type raw_metadata: V3RawMetadata
:rtype: int
"""
return raw_metadata.image_attributes[six.b('SLxImageAttributes')][six.b('uiSequenceCount')]
def _build_label_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.
:rtype: LabelMap
"""
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)
return LabelMap(raw_text)