jim
9 years ago
11 changed files with 459 additions and 411 deletions
Split View
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+0 -11nd2reader/driver/driver.py
-
+0 -397nd2reader/driver/v3.py
-
+0 -0nd2reader/imreader/__init__.py
-
+0 -0nd2reader/imreader/v2.py
-
+96 -0nd2reader/imreader/v3.py
-
+3 -3nd2reader/interface.py
-
+62 -0nd2reader/model/metadata.py
-
+1 -0nd2reader/parser/__init__.py
-
+2 -0nd2reader/parser/parser.py
-
+0 -0nd2reader/parser/v2.py
-
+295 -0nd2reader/parser/v3.py
+ 0
- 11
nd2reader/driver/driver.py
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| @ -1,11 +0,0 @@ | |||
| def get_driver(filename, version): | |||
| """ | |||
| Instantiates the correct driver for the ND2, which allows us to parse metadata and access images. | |||
| :param filename: the path to the ND2 | |||
| :type filename: str | |||
| :param version: the version of the ND2. Note that this is different than the version of NIS Elements used to create the ND2. | |||
| :type version: tuple | |||
| """ | |||
| return 1 | |||
+ 0
- 397
nd2reader/driver/v3.py
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| @ -1,397 +0,0 @@ | |||
| # -*- coding: utf-8 -*- | |||
| import array | |||
| from datetime import datetime | |||
| import numpy as np | |||
| import re | |||
| import struct | |||
| import six | |||
| from nd2reader.model.image import Image | |||
| class Nd2Parser(object): | |||
| """ | |||
| Reads .nd2 files, provides an interface to the metadata, and generates numpy arrays from the image data. | |||
| You should not ever need to instantiate this class manually unless you're a developer. | |||
| """ | |||
| 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, filename): | |||
| self._absolute_start = None | |||
| self._filename = filename | |||
| self._fh = None | |||
| self._channels = None | |||
| self._channel_count = None | |||
| self._chunk_map_start_location = None | |||
| self._cursor_position = 0 | |||
| self._dimension_text = None | |||
| self._fields_of_view = None | |||
| self._label_map = {} | |||
| self._metadata = {} | |||
| self._read_map() | |||
| self._time_indexes = None | |||
| self._parse_metadata() | |||
| self._z_levels = None | |||
| def get_image(self, index): | |||
| channel_offset = index % len(self._metadata.channels) | |||
| fov = self._calculate_field_of_view(index) | |||
| channel = self._calculate_channel(index) | |||
| z_level = self._calculate_z_level(index) | |||
| image_group_number = int(index / len(self._metadata.channels)) | |||
| frame_number = self._calculate_frame_number(image_group_number, fov, z_level) | |||
| timestamp, image = self._get_raw_image_data(image_group_number, channel_offset, self._metadata.height, self._metadata.width) | |||
| image.add_params(timestamp, frame_number, fov, channel, z_level) | |||
| @property | |||
| def absolute_start(self): | |||
| """ | |||
| The date and time when acquisition began. | |||
| :rtype: datetime.datetime() | |||
| """ | |||
| if self._absolute_start is None: | |||
| for line in self.metadata[six.b('ImageTextInfo')][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 | |||
| raise ValueError("This ND2 has no recorded start time. This is probably a bug.") | |||
| return self._absolute_start | |||
| @property | |||
| def channels(self): | |||
| """ | |||
| 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.) | |||
| :rtype: list | |||
| """ | |||
| if not self._channels: | |||
| self._channels = [] | |||
| metadata = self.metadata[six.b('ImageMetadataSeq')][six.b('SLxPictureMetadata')][six.b('sPicturePlanes')] | |||
| try: | |||
| validity = self.metadata[six.b('ImageMetadata')][six.b('SLxExperiment')][six.b('ppNextLevelEx')][six.b('')][0][six.b('ppNextLevelEx')][six.b('')][0][six.b('pItemValid')] | |||
| except KeyError: | |||
| # 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 | |||
| self._channels.append(chan[six.b('sDescription')].decode("utf8")) | |||
| return self._channels | |||
| @property | |||
| def fields_of_view(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. | |||
| :rtype: list | |||
| """ | |||
| if self._fields_of_view is None: | |||
| self._fields_of_view = self._parse_dimension_text(r""".*?XY\((\d+)\).*?""") | |||
| return self._fields_of_view | |||
| @property | |||
| def frames(self): | |||
| """ | |||
| The number of cycles. | |||
| :rtype: list | |||
| """ | |||
| if self._time_indexes is None: | |||
| self._time_indexes = self._parse_dimension_text(r""".*?T'\((\d+)\).*?""") | |||
| return self._time_indexes | |||
| @property | |||
| def z_levels(self): | |||
| """ | |||
| The different levels in the Z-plane. Just a sequence from 0 to n. | |||
| :rtype: list | |||
| """ | |||
| if self._z_levels is None: | |||
| self._z_levels = self._parse_dimension_text(r""".*?Z\((\d+)\).*?""") | |||
| return self._z_levels | |||
| def _calculate_field_of_view(self, frame_number): | |||
| images_per_cycle = len(self.z_levels) * len(self.channels) | |||
| return int((frame_number - (frame_number % images_per_cycle)) / images_per_cycle) % len(self.fields_of_view) | |||
| def _calculate_channel(self, frame_number): | |||
| return self.channels[frame_number % len(self.channels)] | |||
| def _calculate_z_level(self, frame_number): | |||
| return self.z_levels[int(((frame_number - (frame_number % len(self.channels))) / len(self.channels)) % len(self.z_levels))] | |||
| @property | |||
| def _file_handle(self): | |||
| if self._fh is None: | |||
| self._fh = open(self._filename, "rb") | |||
| return self._fh | |||
| def _get_raw_image_data(self, image_group_number, channel_offset, height, width): | |||
| """ | |||
| Reads the raw bytes and the timestamp of an image. | |||
| :param image_group_number: groups are made of images with the same time index, field of view and z-level. | |||
| :type image_group_number: int | |||
| :param channel_offset: the offset in the array where the bytes for this image are found. | |||
| :type channel_offset: int | |||
| :return: (int, array.array()) or None | |||
| """ | |||
| chunk = self._label_map[six.b("ImageDataSeq|%d!" % image_group_number)] | |||
| data = self._read_chunk(chunk) | |||
| # All images in the same image group share the same timestamp! So if you have complicated image data, | |||
| # your timestamps may not be entirely accurate. Practically speaking though, they'll only be off by a few | |||
| # seconds unless you're doing something super weird. | |||
| timestamp = struct.unpack("d", data[:8])[0] | |||
| image_group_data = array.array("H", data) | |||
| image_data_start = 4 + channel_offset | |||
| # The images for the various channels are interleaved within the same array. For example, the second image | |||
| # of a four image group will be composed of bytes 2, 6, 10, etc. If you understand why someone would design | |||
| # a data structure that way, please send the author of this library a message. | |||
| image_data = np.reshape(image_group_data[image_data_start::len(self.channels)], (height, width)) | |||
| # Skip images that are all zeros! This is important, since NIS Elements creates blank "gap" images if you | |||
| # don't have the same number of images each cycle. We discovered this because we only took GFP images every | |||
| # other cycle to reduce phototoxicity, but NIS Elements still allocated memory as if we were going to take | |||
| # them every cycle. | |||
| if np.any(image_data): | |||
| return timestamp, Image(image_data) | |||
| return None | |||
| @property | |||
| def _dimensions(self): | |||
| """ | |||
| 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. | |||
| :rtype: str | |||
| """ | |||
| if self._dimension_text is None: | |||
| for line in self.metadata[six.b('ImageTextInfo')][six.b('SLxImageTextInfo')].values(): | |||
| if six.b("Dimensions:") in line: | |||
| metadata = line | |||
| break | |||
| else: | |||
| raise ValueError("Could not parse metadata dimensions!") | |||
| for line in metadata.split(six.b("\r\n")): | |||
| if line.startswith(six.b("Dimensions:")): | |||
| self._dimension_text = line | |||
| break | |||
| else: | |||
| raise ValueError("Could not parse metadata dimensions!") | |||
| return self._dimension_text | |||
| def _calculate_image_group_number(self, time_index, fov, z_level): | |||
| """ | |||
| Images are grouped together if they share the same time index, field of view, and z-level. | |||
| :type time_index: int | |||
| :type fov: int | |||
| :type z_level: int | |||
| :rtype: int | |||
| """ | |||
| return time_index * len(self.fields_of_view) * len(self.z_levels) + (fov * len(self.z_levels) + z_level) | |||
| def _calculate_frame_number(self, image_group_number, fov, z_level): | |||
| return (image_group_number - (fov * len(self.z_levels) + z_level)) / (len(self.fields_of_view) * len(self.z_levels)) | |||
| @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. | |||
| :rtype: dict | |||
| """ | |||
| channel_offset = {} | |||
| for n, channel in enumerate(self._channels): | |||
| channel_offset[channel] = n | |||
| return channel_offset | |||
| def _parse_dimension_text(self, pattern): | |||
| try: | |||
| count = int(re.match(pattern, self._dimensions).group(1)) | |||
| except AttributeError: | |||
| return [0] | |||
| except TypeError: | |||
| match = re.match(pattern, self._dimensions.decode("utf8")) | |||
| if not match: | |||
| return [0] | |||
| return list(range(int(match.group(1)))) | |||
| else: | |||
| return list(range(count)) | |||
| @property | |||
| def _total_images_per_channel(self): | |||
| """ | |||
| The total number of images per channel. Warning: this may be inaccurate as it includes "gap" images. | |||
| :rtype: int | |||
| """ | |||
| return self.metadata[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiSequenceCount')] | |||
| def _parse_metadata(self): | |||
| """ | |||
| Reads all metadata. | |||
| """ | |||
| for label in self._label_map.keys(): | |||
| if label.endswith(six.b("LV!")) or six.b("LV|") in label: | |||
| data = self._read_chunk(self._label_map[label]) | |||
| stop = label.index(six.b("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(six.b("!"), 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 _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(six.b("\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, data): | |||
| """ | |||
| Reads hierarchical data, analogous to a Python dict. | |||
| """ | |||
| new_count, length = struct.unpack("<IQ", data.read(12)) | |||
| length -= data.tell() - self._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): | |||
| """ | |||
| ND2s use various codes to indicate different data types, which we translate here. | |||
| """ | |||
| 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[data_type](data) | |||
| def _read_metadata(self, data, count): | |||
| """ | |||
| Iterates over each element some section of the metadata and parses it. | |||
| """ | |||
| data = six.BytesIO(data) | |||
| metadata = {} | |||
| for _ in range(count): | |||
| self._cursor_position = data.tell() | |||
| header = data.read(2) | |||
| if not header: | |||
| # We've reached the end of some hierarchy of data | |||
| break | |||
| if six.PY3: | |||
| header = header.decode("utf8") | |||
| 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.keys(): | |||
| 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 | |||
nd2reader/driver/__init__.py → nd2reader/imreader/__init__.py
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nd2reader/driver/v2.py → nd2reader/imreader/v2.py
View File
+ 96
- 0
nd2reader/imreader/v3.py
View File
| @ -0,0 +1,96 @@ | |||
| # -*- coding: utf-8 -*- | |||
| import array | |||
| from datetime import datetime | |||
| import numpy as np | |||
| import re | |||
| import struct | |||
| import six | |||
| from nd2reader.model.image import Image | |||
| class V3ImageReader(object): | |||
| def __init__(self, metadata): | |||
| self._metadata = metadata | |||
| def _calculate_field_of_view(self, frame_number): | |||
| images_per_cycle = len(self._metadata.z_levels) * len(self._metadata.channels) | |||
| return int((frame_number - (frame_number % images_per_cycle)) / images_per_cycle) % len(self._metadata.fields_of_view) | |||
| def _calculate_channel(self, frame_number): | |||
| return self._metadata.channels[frame_number % len(self._metadata.channels)] | |||
| def _calculate_z_level(self, frame_number): | |||
| return self._metadata.z_levels[int(((frame_number - (frame_number % len(self._metadata.channels))) / len(self._metadata.channels)) % len(self._metadata.z_levels))] | |||
| def _calculate_image_group_number(self, time_index, fov, z_level): | |||
| """ | |||
| Images are grouped together if they share the same time index, field of view, and z-level. | |||
| :type time_index: int | |||
| :type fov: int | |||
| :type z_level: int | |||
| :rtype: int | |||
| """ | |||
| return time_index * len(self._metadata.fields_of_view) * len(self._metadata.z_levels) + (fov * len(self._metadata.z_levels) + z_level) | |||
| def _calculate_frame_number(self, image_group_number, fov, z_level): | |||
| return (image_group_number - (fov * len(self._metadata.z_levels) + z_level)) / (len(self._metadata.fields_of_view) * len(self._metadata.z_levels)) | |||
| def get_image(self, index): | |||
| channel_offset = index % len(self._metadata.channels) | |||
| fov = self._calculate_field_of_view(index) | |||
| channel = self._calculate_channel(index) | |||
| z_level = self._calculate_z_level(index) | |||
| image_group_number = int(index / len(self._metadata.channels)) | |||
| frame_number = self._calculate_frame_number(image_group_number, fov, z_level) | |||
| timestamp, image = self._get_raw_image_data(image_group_number, channel_offset, self._metadata.height, self._metadata.width) | |||
| image.add_params(timestamp, frame_number, fov, channel, z_level) | |||
| @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. | |||
| :rtype: dict | |||
| """ | |||
| channel_offset = {} | |||
| for n, channel in enumerate(self._channels): | |||
| channel_offset[channel] = n | |||
| return channel_offset | |||
| def _get_raw_image_data(self, image_group_number, channel_offset, height, width): | |||
| """ | |||
| Reads the raw bytes and the timestamp of an image. | |||
| :param image_group_number: groups are made of images with the same time index, field of view and z-level. | |||
| :type image_group_number: int | |||
| :param channel_offset: the offset in the array where the bytes for this image are found. | |||
| :type channel_offset: int | |||
| :return: (int, array.array()) or None | |||
| """ | |||
| chunk = self._label_map[six.b("ImageDataSeq|%d!" % image_group_number)] | |||
| data = self._read_chunk(chunk) | |||
| # All images in the same image group share the same timestamp! So if you have complicated image data, | |||
| # your timestamps may not be entirely accurate. Practically speaking though, they'll only be off by a few | |||
| # seconds unless you're doing something super weird. | |||
| timestamp = struct.unpack("d", data[:8])[0] | |||
| image_group_data = array.array("H", data) | |||
| image_data_start = 4 + channel_offset | |||
| # The images for the various channels are interleaved within the same array. For example, the second image | |||
| # of a four image group will be composed of bytes 2, 6, 10, etc. If you understand why someone would design | |||
| # a data structure that way, please send the author of this library a message. | |||
| image_data = np.reshape(image_group_data[image_data_start::len(self.channels)], (height, width)) | |||
| # Skip images that are all zeros! This is important, since NIS Elements creates blank "gap" images if you | |||
| # don't have the same number of images each cycle. We discovered this because we only took GFP images every | |||
| # other cycle to reduce phototoxicity, but NIS Elements still allocated memory as if we were going to take | |||
| # them every cycle. | |||
| if np.any(image_data): | |||
| return timestamp, Image(image_data) | |||
| return None | |||
+ 3
- 3
nd2reader/interface.py
View File
+ 62
- 0
nd2reader/model/metadata.py
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| @ -0,0 +1,62 @@ | |||
| class Metadata(object): | |||
| """ A simple container for ND2 metadata. """ | |||
| def __init__(self, channels, date, fields_of_view, frames, z_levels): | |||
| self._channels = channels | |||
| self._date = date | |||
| self._fields_of_view = fields_of_view | |||
| self._frames = frames | |||
| self._z_levels = z_levels | |||
| @property | |||
| def date(self): | |||
| """ | |||
| The date and time when acquisition began. | |||
| :rtype: datetime.datetime() | |||
| """ | |||
| return self._date | |||
| @property | |||
| def channels(self): | |||
| """ | |||
| 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.) | |||
| :rtype: list | |||
| """ | |||
| return self._channels | |||
| @property | |||
| def fields_of_view(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. | |||
| :rtype: list | |||
| """ | |||
| return self._fields_of_view | |||
| @property | |||
| def frames(self): | |||
| """ | |||
| The number of cycles. | |||
| :rtype: list | |||
| """ | |||
| return self._frames | |||
| @property | |||
| def z_levels(self): | |||
| """ | |||
| The different levels in the Z-plane. Just a sequence from 0 to n. | |||
| :rtype: list | |||
| """ | |||
| return self._z_levels | |||
+ 1
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nd2reader/parser/__init__.py
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| @ -0,0 +1 @@ | |||
| from . parser import get_parser | |||
+ 2
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nd2reader/parser/parser.py
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| @ -0,0 +1,2 @@ | |||
| def get_parser(filename, major_version, minor_version): | |||
| parsers = {} | |||
nd2reader/parser.py → nd2reader/parser/v2.py
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+ 295
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nd2reader/parser/v3.py
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| @ -0,0 +1,295 @@ | |||
| # -*- coding: utf-8 -*- | |||
| import array | |||
| from datetime import datetime | |||
| from nd2reader.model.metadata import Metadata | |||
| import re | |||
| import six | |||
| import struct | |||
| class V3Parser(object): | |||
| """ Parses ND2 files and creates a Metadata and ImageReader 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, filename): | |||
| self._filename = filename | |||
| self._fh = None | |||
| self._metadata = None | |||
| def _parse_date(self, metadata_dict): | |||
| """ | |||
| The date and time when acquisition began. | |||
| :rtype: datetime.datetime() | |||
| """ | |||
| for line in metadata_dict[six.b('ImageTextInfo')][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 | |||
| raise ValueError("This ND2 has no recorded start time. This is probably a bug.") | |||
| def _parse_channels(self, metadata_dict): | |||
| """ | |||
| 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.) | |||
| :rtype: list | |||
| """ | |||
| channels = [] | |||
| metadata = metadata_dict[six.b('ImageMetadataSeq')][six.b('SLxPictureMetadata')][six.b('sPicturePlanes')] | |||
| try: | |||
| validity = metadata_dict[six.b('ImageMetadata')][six.b('SLxExperiment')][six.b('ppNextLevelEx')][six.b('')][0][six.b('ppNextLevelEx')][six.b('')][0][six.b('pItemValid')] | |||
| except KeyError: | |||
| # 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, metadata_dict): | |||
| """ | |||
| 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. | |||
| :rtype: list | |||
| """ | |||
| return self._parse_dimension(r""".*?XY\((\d+)\).*?""", metadata_dict) | |||
| def _parse_frames(self, metadata_dict): | |||
| """ | |||
| The number of cycles. | |||
| :rtype: list | |||
| """ | |||
| return self._parse_dimension(r""".*?T'\((\d+)\).*?""", metadata_dict) | |||
| def _parse_z_levels(self, metadata_dict): | |||
| """ | |||
| The different levels in the Z-plane. Just a sequence from 0 to n. | |||
| :rtype: list | |||
| """ | |||
| return self._parse_dimension(r""".*?Z\((\d+)\).*?""", metadata_dict) | |||
| @property | |||
| def _file_handle(self): | |||
| if self._fh is None: | |||
| self._fh = open(self._filename, "rb") | |||
| return self._fh | |||
| def _parse_dimension_text(self, metadata_dict): | |||
| """ | |||
| 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. | |||
| :rtype: str | |||
| """ | |||
| for line in metadata_dict[six.b('ImageTextInfo')][six.b('SLxImageTextInfo')].values(): | |||
| if six.b("Dimensions:") in line: | |||
| metadata = line | |||
| break | |||
| else: | |||
| raise ValueError("Could not parse metadata dimensions!") | |||
| for line in metadata.split(six.b("\r\n")): | |||
| if line.startswith(six.b("Dimensions:")): | |||
| dimension_text = line | |||
| break | |||
| else: | |||
| raise ValueError("Could not parse metadata dimensions!") | |||
| return dimension_text | |||
| def _parse_dimension(self, pattern, metadata_dict): | |||
| try: | |||
| dimension_text = self._parse_dimension_text(metadata_dict) | |||
| count = int(re.match(pattern, dimension_text).group(1)) | |||
| except AttributeError: | |||
| return [0] | |||
| except TypeError: | |||
| match = re.match(pattern, dimension_text.decode("utf8")) | |||
| if not match: | |||
| return [0] | |||
| return list(range(int(match.group(1)))) | |||
| else: | |||
| return list(range(count)) | |||
| def _parse_total_images_per_channel(self, metadata_dict): | |||
| """ | |||
| The total number of images per channel. Warning: this may be inaccurate as it includes "gap" images. | |||
| :rtype: int | |||
| """ | |||
| return metadata_dict[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiSequenceCount')] | |||
| def _parse_metadata(self): | |||
| """ | |||
| Reads all metadata. | |||
| """ | |||
| metadata_dict = {} | |||
| label_map = self._build_label_map() | |||
| for label in label_map.keys(): | |||
| if label.endswith(six.b("LV!")) or six.b("LV|") in label: | |||
| data = self._read_chunk(label_map[label]) | |||
| stop = label.index(six.b("LV")) | |||
| metadata_dict[label[:stop]] = self._read_metadata(data, 1) | |||
| channels = self._parse_channels(metadata_dict) | |||
| date = self._parse_fields_of_view(metadata_dict) | |||
| fields_of_view = self._parse_fields_of_view(metadata_dict) | |||
| frames = self._parse_frames(metadata_dict) | |||
| z_levels = self._parse_z_levels(metadata_dict) | |||
| self._metadata = Metadata(channels, date, fields_of_view, frames, z_levels) | |||
| 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: dict | |||
| """ | |||
| label_map = {} | |||
| 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(V3Parser.CHUNK_MAP_START) + 32 | |||
| while True: | |||
| data_start = raw_text.index(six.b("!"), label_start) + 1 | |||
| key = raw_text[label_start: data_start] | |||
| location, length = struct.unpack("QQ", raw_text[data_start: data_start + 16]) | |||
| if key == V3Parser.CHUNK_MAP_END: | |||
| # We've reached the end of the chunk map | |||
| break | |||
| label_map[key] = location | |||
| label_start = data_start + 16 | |||
| return label_map | |||
| 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 != V3Parser.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 _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(six.b("\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, data): | |||
| """ | |||
| Reads hierarchical data, analogous to a Python dict. | |||
| """ | |||
| new_count, length = struct.unpack("<IQ", data.read(12)) | |||
| length -= data.tell() - self._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): | |||
| """ | |||
| ND2s use various codes to indicate different data types, which we translate here. | |||
| """ | |||
| 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[data_type](data) | |||
| def _read_metadata(self, data, count): | |||
| """ | |||
| Iterates over each element some section of the metadata and parses it. | |||
| """ | |||
| data = six.BytesIO(data) | |||
| metadata = {} | |||
| for _ in range(count): | |||
| self._cursor_position = data.tell() | |||
| header = data.read(2) | |||
| if not header: | |||
| # We've reached the end of some hierarchy of data | |||
| break | |||
| if six.PY3: | |||
| header = header.decode("utf8") | |||
| 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.keys(): | |||
| 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 | |||