# -*- coding: utf-8 -*- from datetime import datetime from nd2reader.model.metadata import Metadata, CameraSettings 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_camera_metadata() 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_camera_metadata(self): """ Gets parsed data about the physical cameras used to produce images and throws them in a dictionary. """ self.camera_metadata = {} for camera_setting in self._parse_camera_settings(): self.camera_metadata[camera_setting.channel_name] = camera_setting 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) self.metadata = Metadata(height, width, channels, date, fields_of_view, frames, z_levels, total_images_per_channel) def _parse_camera_settings(self): """ Looks up information in the raw metadata about the camera(s) and puts it into a CameraSettings object. Duplicate cameras can be returned if the same one was used for multiple channels. """ for n, camera in enumerate(self.raw_metadata.image_metadata_sequence[six.b('SLxPictureMetadata')][six.b('sPicturePlanes')][six.b('sSampleSetting')].values()): name = camera[six.b('pCameraSetting')][six.b('CameraUserName')] id = camera[six.b('pCameraSetting')][six.b('CameraUniqueName')] exposure = camera[six.b('dExposureTime')] x_binning = camera[six.b('pCameraSetting')][six.b('FormatFast')][six.b('fmtDesc')][six.b('dBinningX')] y_binning = camera[six.b('pCameraSetting')][six.b('FormatFast')][six.b('fmtDesc')][six.b('dBinningY')] optical_configs = camera[six.b('sOpticalConfigs')] # This definitely is not working right. It seems to be totally inconsistent in each of the sample ND2s that I have. # Fixing one breaks another. if six.b('') in optical_configs.keys(): channel_name = optical_configs[six.b('')][six.b('sOpticalConfigName')] yield CameraSettings(name, id, exposure, x_binning, y_binning, channel_name) else: channel_names = [channel[six.b('Name')] for key, channel in camera[six.b('pCameraSetting')][six.b('Metadata')][six.b('Channels')].items()] for channel_name in channel_names: yield CameraSettings(name, id, exposure, x_binning, y_binning, channel_name) 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)