From 9aed3cb62394e6b42410152ea9cf4c76716cac77 Mon Sep 17 00:00:00 2001
From: jim <jim@rybarski.com>
Date: Wed, 12 Nov 2014 17:58:23 -0600
Subject: [PATCH] refactored a bit

---
 nd2reader/__init__.py         | 345 +---------------------------------
 nd2reader/model/__init__.py   |  45 ++++-
 nd2reader/service/__init__.py | 311 ++++++++++++++++++++++++++++++
 run.py                        |  20 +-
 4 files changed, 364 insertions(+), 357 deletions(-)
 create mode 100644 nd2reader/service/__init__.py

diff --git a/nd2reader/__init__.py b/nd2reader/__init__.py
index f70c1c5..5253eb7 100644
--- a/nd2reader/__init__.py
+++ b/nd2reader/__init__.py
@@ -1,342 +1,11 @@
-import array
-import numpy as np
-import struct
-from collections import namedtuple
-from StringIO import StringIO
-from nd2reader.model import Channel
-from pprint import pprint
+import logging
+from nd2reader.service import BaseNd2
 
-chunk = namedtuple('Chunk', ['location', 'length'])
-field_of_view = namedtuple('FOV', ['number', 'x', 'y', 'z', 'pfs_offset'])
+log = logging.getLogger("nd2reader")
+log.addHandler(logging.StreamHandler())
+log.setLevel(logging.DEBUG)
 
 
-class Nd2(object):
+class Nd2(BaseNd2):
     def __init__(self, filename):
-        self._parser = Nd2Parser(filename)
-
-    @property
-    def timepoint_count(self):
-        return len(self._parser.metadata['ImageEvents']['RLxExperimentRecord']['pEvents'][''])
-
-    @property
-    def height(self):
-        return self._parser.metadata['ImageAttributes']['SLxImageAttributes']['uiHeight']
-
-    @property
-    def width(self):
-        return self._parser.metadata['ImageAttributes']['SLxImageAttributes']['uiWidth']
-
-    @property
-    def fields_of_view(self):
-        """
-        Fields of view are the various places in the xy-plane where images were taken.
-
-        """
-        # Grab all the metadata about fields of view
-        fov_metadata = self.metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']
-        # The attributes include x, y, and z coordinates, and perfect focus (PFS) offset
-        fov_attributes = fov_metadata['uLoopPars']['Points']['']
-        # If you crop fields of view from your ND2 file, the metadata is retained and only this list is
-        # updated to indicate that the fields of view have been deleted.
-        fov_validity = fov_metadata['pItemValid']
-        # We only yield valid (i.e. uncropped) fields of view
-        for number, (fov, valid) in enumerate(zip(fov_attributes, fov_validity)):
-            if valid:
-                yield field_of_view(number=number + 1,
-                                    x=fov['dPosX'],
-                                    y=fov['dPosY'],
-                                    z=fov['dPosZ'],
-                                    pfs_offset=fov['dPFSOffset'])
-
-    @property
-    def fov_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.
-
-        """
-        return sum(self.metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['pItemValid'])
-
-    @property
-    def channels(self):
-        metadata = self.metadata['ImageMetadataSeq']['SLxPictureMetadata']['sPicturePlanes']
-        validity = self.metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['ppNextLevelEx']['']['pItemValid']
-        # 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['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)
-
-    @property
-    def channel_count(self):
-        return self.metadata['ImageAttributes']["SLxImageAttributes"]["uiComp"]
-
-    @property
-    def zoom_levels(self):
-        for i in self.metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['ppNextLevelEx'][''].items():
-            yield i
-
-    @property
-    def z_level_count(self):
-        """
-        The number of different z-axis levels.
-
-        """
-        return 1
-
-    @property
-    def metadata(self):
-        return self._parser.metadata
-
-    def get_images(self, fov_number, channel_name, z_axis):
-        pass
-
-    def get_image(self, nr):
-        d = self._parser._read_chunk(self._parser._label_map["ImageDataSeq|%d!" % nr].location)
-        timestamp = struct.unpack("d", d[:8])[0]
-        res = [timestamp]
-        # The images for the various channels are interleaved within each other.
-        for i in range(self.channel_count):
-            a = array.array("H", d)
-            res.append(a[4+i::self.channel_count])
-        # TODO: Are you missing a zoom level? Is there extra data here? Can you get timestamps now?
-        return res
-
-
-class Nd2Parser(object):
-    """
-    Reads .nd2 files, provides an interface to the metadata, and generates numpy arrays from the image data.
-
-    """
-    def __init__(self, filename):
-        self._filename = filename
-        self._file_handler = None
-        self._chunk_map_start_location = None
-        self._label_map = {}
-        self._metadata = {}
-        self._read_map()
-        self._parse_dict_data()
-
-    @property
-    def fh(self):
-        if self._file_handler is None:
-            self._file_handler = open(self._filename, "rb")
-        return self._file_handler
-
-    def _parse_dict_data(self):
-        # TODO: Don't like this name
-        for label in self._top_level_dict_labels:
-            chunk_location = self._label_map[label].location
-            data = self._read_chunk(chunk_location)
-            stop = label.index("LV")
-            self._metadata[label[:stop]] = self.read_lv_encoding(data, 1)
-
-    @property
-    def metadata(self):
-        return self._metadata
-
-    @property
-    def _top_level_dict_labels(self):
-        # TODO: I don't like this name either
-        for label in self._label_map.keys():
-            if label.endswith("LV!") or "LV|" in label:
-                yield label
-
-    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.
-
-        """
-        raw_text = self._get_raw_chunk_map_text()
-        label_start = self._find_first_label_offset(raw_text)
-        while True:
-            data_start = self._get_data_start(label_start, raw_text)
-            label, value = self._extract_map_key(label_start, data_start, raw_text)
-            if label == "ND2 CHUNK MAP SIGNATURE 0000001!":
-                # We've reached the end of the chunk map
-                break
-
-            self._label_map[label] = value
-            label_start = data_start + 16
-
-    @staticmethod
-    def _find_first_label_offset(raw_text):
-        """
-        The chunk map starts with some number of (seemingly) useless bytes, followed
-        by "ND2 FILEMAP SIGNATURE NAME 0001!". We return the location of the first character after this sequence,
-        which is the actual beginning of the chunk map.
-
-        """
-        return raw_text.index("ND2 FILEMAP SIGNATURE NAME 0001!") + 32
-
-    @staticmethod
-    def _get_data_start(label_start, raw_text):
-        """
-        The data for a given label begins immediately after the first exclamation point
-
-        """
-        return raw_text.index("!", label_start) + 1
-
-    @staticmethod
-    def _extract_map_key(label_start, data_start, raw_text):
-        """
-        Chunk map entries are a string label of arbitrary length followed by 16 bytes of data, which represent
-        the byte offset from the beginning of the file where that data can be found.
-
-        """
-        key = raw_text[label_start: data_start]
-        location, length = struct.unpack("QQ", raw_text[data_start: data_start + 16])
-        return key, chunk(location=location, length=length)
-
-    @property
-    def chunk_map_start_location(self):
-        """
-        The position in bytes from the beginning of the file where the chunk map begins.
-        The chunk map is a series of string labels followed by the position (in bytes) of the respective data.
-
-        """
-        if self._chunk_map_start_location is None:
-            # Put the cursor 8 bytes before the end of the file
-            self.fh.seek(-8, 2)
-            # Read the last 8 bytes of the file
-            self._chunk_map_start_location = struct.unpack("Q", self.fh.read(8))[0]
-        return self._chunk_map_start_location
-
-    def _read_chunk(self, chunk_location):
-        """
-        Gets the data for a given chunk pointer
-
-        """
-        self.fh.seek(chunk_location)
-        chunk_data = self._read_chunk_metadata()
-        header, relative_offset, data_length = self._parse_chunk_metadata(chunk_data)
-        return self._read_chunk_data(chunk_location, relative_offset, data_length)
-
-    def _read_chunk_metadata(self):
-        """
-        Gets the chunks metadata, which is always 16 bytes
-
-        """
-        return self.fh.read(16)
-
-    def _read_chunk_data(self, chunk_location, relative_offset, data_length):
-        """
-        Reads the actual data for a given chunk
-
-        """
-        # 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)
-
-    @staticmethod
-    def _parse_chunk_metadata(chunk_data):
-        """
-        Finds out everything about a given chunk. Every chunk begins with the same value, so if that's ever
-        different we can assume the file has suffered some kind of damage.
-
-        """
-        header, relative_offset, data_length = struct.unpack("IIQ", chunk_data)
-        if header != 0xabeceda:
-            raise ValueError("The ND2 file seems to be corrupted.")
-        return header, relative_offset, data_length
-
-    def _get_raw_chunk_map_text(self):
-        """
-        Reads the entire chunk map and returns it as a string.
-
-        """
-        self.fh.seek(self.chunk_map_start_location)
-        return self.fh.read(-1)
-
-    @staticmethod
-    def as_numpy_array(arr):
-        return np.frombuffer(arr)
-
-    def read_lv_encoding(self, data, count):
-        data = StringIO(data)
-        res = {}
-        for c in range(count):
-            lastpos = data.tell()
-            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:
-                newcount, length = struct.unpack("<IQ", data.read(12))
-                length -= data.tell()-lastpos
-                nextdata = data.read(length)
-                value = self.read_lv_encoding(nextdata, newcount)
-                # XXX do not know for what these offsets? are
-                unknown = array.array("I", 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
-
-#
-# class LVLine(object):
-#     def __init__(self, line):
-#         self._line = line
-#         self._extract()
-#
-#     def _extract(self):
-#         if self._type == 11:
-#             count, length = struct.unpack("<IQ", self._line[self._name_end: self._name_end + 12])
-#             newline = self._line[self._name_end + 12:]
-#
-#     @property
-#     def name(self):
-#         return self._line[2: self._name_end].decode("utf16").encode("utf8")
-#
-#     @property
-#     def _type(self):
-#         return ord(self._line[0])
-#
-#     @property
-#     def _name_end(self):
-#         """
-#         Length is given as number of characters, but since it's unicode (which is two-bytes per character) we return
-#         twice the number.
-#
-#         """
-#         return ord(self._line[1]) * 2
-#
-#
-# class LVData(object):
-#     def __init__(self, data):
-#         self._extracted_data = LVLine(data)
\ No newline at end of file
+        super(Nd2, self).__init__(filename)
\ No newline at end of file
diff --git a/nd2reader/model/__init__.py b/nd2reader/model/__init__.py
index 5415ecb..e14a54e 100644
--- a/nd2reader/model/__init__.py
+++ b/nd2reader/model/__init__.py
@@ -1,3 +1,7 @@
+import numpy as np
+import skimage.io
+
+
 class Channel(object):
     def __init__(self, name, camera, exposure_time):
         self._name = name
@@ -19,6 +23,43 @@ class Channel(object):
         return self._exposure_time
 
 
-class Image(object):
+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.timestamp = None
\ No newline at end of file
+        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, height, width):
+        self._timestamp = timestamp
+        self._raw_data = raw_array
+        self._height = height
+        self._width = width
+
+    @property
+    def timestamp(self):
+        # TODO: Convert to datetime object
+        return self._timestamp
+
+    @property
+    def data(self):
+        return np.reshape(self._raw_data, (self._height, self._width))
+
+    def show(self):
+        skimage.io.imshow(self.data)
+        skimage.io.show()
\ No newline at end of file
diff --git a/nd2reader/service/__init__.py b/nd2reader/service/__init__.py
new file mode 100644
index 0000000..af115a8
--- /dev/null
+++ b/nd2reader/service/__init__.py
@@ -0,0 +1,311 @@
+import array
+import numpy as np
+import struct
+from StringIO import StringIO
+from collections import namedtuple
+import logging
+from nd2reader.model import Channel, ImageSet, Image
+
+log = logging.getLogger("nd2reader")
+chunk = namedtuple('Chunk', ['location', 'length'])
+field_of_view = namedtuple('FOV', ['number', 'x', 'y', 'z', 'pfs_offset'])
+
+
+class BaseNd2(object):
+    def __init__(self, filename):
+        self._parser = Nd2Reader(filename)
+
+    @property
+    def height(self):
+        return self._parser.metadata['ImageAttributes']['SLxImageAttributes']['uiHeight']
+
+    @property
+    def width(self):
+        return self._parser.metadata['ImageAttributes']['SLxImageAttributes']['uiWidth']
+
+    def _get_timepoint_count(self):
+        return len(self._parser.metadata['ImageEvents']['RLxExperimentRecord']['pEvents'][''])
+
+    @property
+    def _fields_of_view(self):
+        """
+        Fields of view are the various places in the xy-plane where images were taken.
+
+        """
+        # Grab all the metadata about fields of view
+        fov_metadata = self._metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']
+        # The attributes include x, y, and z coordinates, and perfect focus (PFS) offset
+        fov_attributes = fov_metadata['uLoopPars']['Points']['']
+        # If you crop fields of view from your ND2 file, the metadata is retained and only this list is
+        # updated to indicate that the fields of view have been deleted.
+        fov_validity = fov_metadata['pItemValid']
+        # We only yield valid (i.e. uncropped) fields of view
+        for number, (fov, valid) in enumerate(zip(fov_attributes, fov_validity)):
+            if valid:
+                yield field_of_view(number=number + 1,
+                                    x=fov['dPosX'],
+                                    y=fov['dPosY'],
+                                    z=fov['dPosZ'],
+                                    pfs_offset=fov['dPFSOffset'])
+
+    @property
+    def _fov_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.
+
+        """
+        return sum(self._metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['pItemValid'])
+
+    @property
+    def _channels(self):
+        metadata = self._metadata['ImageMetadataSeq']['SLxPictureMetadata']['sPicturePlanes']
+        validity = self._metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['ppNextLevelEx']['']['pItemValid']
+        # 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['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)
+
+    @property
+    def _channel_count(self):
+        return self._metadata['ImageAttributes']["SLxImageAttributes"]["uiComp"]
+
+    # @property
+    # def _z_levels(self):
+    #     for i in self._metadata['ImageMetadata']['SLxExperiment']['ppNextLevelEx']['']['ppNextLevelEx'][''].items():
+    #         yield i
+
+    # @property
+    # def _z_level_count(self):
+    #     """
+    #     The number of different z-axis levels.
+    #
+    #     """
+    #     return 1
+
+    @property
+    def _metadata(self):
+        return self._parser.metadata
+
+    def _get_image_set(self, nr):
+        chunk = self._parser._label_map["ImageDataSeq|%d!" % nr]
+        d = self._parser._read_chunk(chunk.location)
+        timestamp = struct.unpack("d", d[:8])[0]
+        image_set = ImageSet()
+        # The images for the various channels are interleaved within each other.
+        for i in range(self._channel_count):
+            image_data = array.array("H", d)
+            image = Image(timestamp, image_data[4+i::self._channel_count], self.height, self.width)
+            image_set.add(image)
+        return image_set
+
+
+class Nd2Reader(object):
+    """
+    Reads .nd2 files, provides an interface to the metadata, and generates numpy arrays from the image data.
+
+    """
+    def __init__(self, filename):
+        self._filename = filename
+        self._file_handler = None
+        self._chunk_map_start_location = None
+        self._label_map = {}
+        self._metadata = {}
+        self._read_map()
+        self._parse_dict_data()
+
+    @property
+    def fh(self):
+        if self._file_handler is None:
+            self._file_handler = open(self._filename, "rb")
+        return self._file_handler
+
+    def _parse_dict_data(self):
+        # TODO: Don't like this name
+        for label in self._top_level_dict_labels:
+            chunk_location = self._label_map[label].location
+            data = self._read_chunk(chunk_location)
+            stop = label.index("LV")
+            self._metadata[label[:stop]] = self.read_lv_encoding(data, 1)
+
+    @property
+    def metadata(self):
+        return self._metadata
+
+    @property
+    def _top_level_dict_labels(self):
+        # TODO: I don't like this name either
+        for label in self._label_map.keys():
+            if label.endswith("LV!") or "LV|" in label:
+                yield label
+
+    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.
+
+        """
+        raw_text = self._get_raw_chunk_map_text()
+        label_start = self._find_first_label_offset(raw_text)
+        while True:
+            data_start = self._get_data_start(label_start, raw_text)
+            label, value = self._extract_map_key(label_start, data_start, raw_text)
+            if label == "ND2 CHUNK MAP SIGNATURE 0000001!":
+                # We've reached the end of the chunk map
+                break
+
+            self._label_map[label] = value
+            label_start = data_start + 16
+
+    @staticmethod
+    def _find_first_label_offset(raw_text):
+        """
+        The chunk map starts with some number of (seemingly) useless bytes, followed
+        by "ND2 FILEMAP SIGNATURE NAME 0001!". We return the location of the first character after this sequence,
+        which is the actual beginning of the chunk map.
+
+        """
+        return raw_text.index("ND2 FILEMAP SIGNATURE NAME 0001!") + 32
+
+    @staticmethod
+    def _get_data_start(label_start, raw_text):
+        """
+        The data for a given label begins immediately after the first exclamation point
+
+        """
+        return raw_text.index("!", label_start) + 1
+
+    @staticmethod
+    def _extract_map_key(label_start, data_start, raw_text):
+        """
+        Chunk map entries are a string label of arbitrary length followed by 16 bytes of data, which represent
+        the byte offset from the beginning of the file where that data can be found.
+
+        """
+        key = raw_text[label_start: data_start]
+        location, length = struct.unpack("QQ", raw_text[data_start: data_start + 16])
+        return key, chunk(location=location, length=length)
+
+    @property
+    def chunk_map_start_location(self):
+        """
+        The position in bytes from the beginning of the file where the chunk map begins.
+        The chunk map is a series of string labels followed by the position (in bytes) of the respective data.
+
+        """
+        if self._chunk_map_start_location is None:
+            # Put the cursor 8 bytes before the end of the file
+            self.fh.seek(-8, 2)
+            # Read the last 8 bytes of the file
+            self._chunk_map_start_location = struct.unpack("Q", self.fh.read(8))[0]
+        return self._chunk_map_start_location
+
+    def _read_chunk(self, chunk_location):
+        """
+        Gets the data for a given chunk pointer
+
+        """
+        self.fh.seek(chunk_location)
+        chunk_data = self._read_chunk_metadata()
+        header, relative_offset, data_length = self._parse_chunk_metadata(chunk_data)
+        return self._read_chunk_data(chunk_location, relative_offset, data_length)
+
+    def _read_chunk_metadata(self):
+        """
+        Gets the chunks metadata, which is always 16 bytes
+
+        """
+        return self.fh.read(16)
+
+    def _read_chunk_data(self, chunk_location, relative_offset, data_length):
+        """
+        Reads the actual data for a given chunk
+
+        """
+        # 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)
+
+    @staticmethod
+    def _parse_chunk_metadata(chunk_data):
+        """
+        Finds out everything about a given chunk. Every chunk begins with the same value, so if that's ever
+        different we can assume the file has suffered some kind of damage.
+
+        """
+        header, relative_offset, data_length = struct.unpack("IIQ", chunk_data)
+        if header != 0xabeceda:
+            raise ValueError("The ND2 file seems to be corrupted.")
+        return header, relative_offset, data_length
+
+    def _get_raw_chunk_map_text(self):
+        """
+        Reads the entire chunk map and returns it as a string.
+
+        """
+        self.fh.seek(self.chunk_map_start_location)
+        return self.fh.read(-1)
+
+    @staticmethod
+    def as_numpy_array(arr):
+        return np.frombuffer(arr)
+
+    def read_lv_encoding(self, data, count):
+        data = StringIO(data)
+        res = {}
+        total_count = 0
+        for c in range(count):
+            lastpos = data.tell()
+            total_count += 1
+            # log.debug("%s: %s" % (total_count, lastpos))
+            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")
+            log.debug(name)
+            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:
+                newcount, length = struct.unpack("<IQ", data.read(12))
+                length -= data.tell()-lastpos
+                nextdata = data.read(length)
+                value = self.read_lv_encoding(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
\ No newline at end of file
diff --git a/run.py b/run.py
index 6333009..241e480 100644
--- a/run.py
+++ b/run.py
@@ -5,20 +5,6 @@ from skimage import io
 
 # n = Nd2("/home/jim/Desktop/nd2hacking/test-141111.nd2")
 n = Nd2("/home/jim/Desktop/nd2hacking/YFP-dsRed-GFP-BF.nd2")
-
-# print("Height: ", n.height)
-# print("Width: ", n.width)
-# for fov in n.fields_of_view:
-#     print(fov.number, fov.x, fov.y, fov.z, fov.pfs_offset)
-#
-for chan in n.channels:
-    print(chan.name, chan.camera)
-# pprint(len(n.metadata['ImageMetadata']['SLxExperiment']['uLoopPars']['pPeriod']['']))
-
-# res = n.get_image(6)
-# print(res[0])
-# arr = np.reshape(res[1], (n.height, n.width))
-# io.imshow(arr)
-# io.show()
-
-# pprint(n.metadata)
\ No newline at end of file
+image_set = n._get_image_set(3)
+for image in image_set:
+    image.show()
\ No newline at end of file