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160 lines
6.3 KiB
160 lines
6.3 KiB
# -*- coding: utf-8 -*-
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from nd2reader.model import Image, ImageSet
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from nd2reader.parser import Nd2Parser
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import six
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class Nd2(Nd2Parser):
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"""
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Allows easy access to NIS Elements .nd2 image files.
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"""
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def __init__(self, filename):
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super(Nd2, self).__init__(filename)
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self._filename = filename
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def __repr__(self):
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return "\n".join(["<ND2 %s>" % self._filename,
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"Created: %s" % self._absolute_start.strftime("%Y-%m-%d %H:%M:%S"),
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"Image size: %sx%s (HxW)" % (self.height, self.width),
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"Image cycles: %s" % len(self.time_indexes),
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"Channels: %s" % ", ".join(["'%s'" % str(channel) for channel in self.channels]),
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"Fields of View: %s" % len(self.fields_of_view),
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"Z-Levels: %s" % len(self.z_levels)
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])
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def __len__(self):
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"""
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This should be the total number of images in the ND2, but it may be inaccurate. If the ND2 contains a
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different number of images in a cycle (i.e. there are "gap" images) it will be higher than reality.
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:rtype: int
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"""
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return self._image_count * self._channel_count
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def __getitem__(self, item):
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"""
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Allows slicing ND2s.
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>>> nd2 = Nd2("my_images.nd2")
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>>> image = nd2[16] # gets 17th frame
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>>> for image in nd2[100:200]: # iterate over the 100th to 200th images
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>>> do_something(image.data)
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>>> for image in nd2[::-1]: # iterate backwards
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>>> do_something(image.data)
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>>> for image in nd2[37:422:17]: # do something super weird if you really want to
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>>> do_something(image.data)
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:type item: int or slice
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:rtype: nd2reader.model.Image() or generator
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"""
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if isinstance(item, int):
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try:
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channel_offset = item % len(self.channels)
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fov = self._calculate_field_of_view(item)
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channel = self._calculate_channel(item)
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z_level = self._calculate_z_level(item)
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timestamp, raw_image_data = self._get_raw_image_data(item, channel_offset)
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image = Image(timestamp, raw_image_data, fov, channel, z_level, self.height, self.width)
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except (TypeError, ValueError):
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return None
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else:
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return image
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elif isinstance(item, slice):
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return self._slice(item.start, item.stop, item.step)
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raise IndexError
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def _slice(self, start, stop, step):
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"""
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Allows for iteration over a selection of the entire dataset.
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:type start: int
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:type stop: int
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:type step: int
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:rtype: nd2reader.model.Image() or None
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"""
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start = start if start is not None else 0
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step = step if step is not None else 1
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stop = stop if stop is not None else len(self)
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# This weird thing with the step allows you to iterate backwards over the images
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for i in range(start, stop)[::step]:
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yield self[i]
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@property
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def image_sets(self):
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"""
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Iterates over groups of related images. This is useful if your ND2 contains multiple fields of view.
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A typical use case might be that you have, say, four areas of interest that you're monitoring, and every
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minute you take a bright field and GFP image of each one. For each cycle, this method would produce four
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ImageSet objects, each containing one bright field and one GFP image.
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:return: model.ImageSet()
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"""
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for time_index in self.time_indexes:
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image_set = ImageSet()
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for fov in self.fields_of_view:
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for channel_name in self.channels:
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for z_level in self.z_levels:
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image = self.get_image(time_index, fov, channel_name, z_level)
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if image is not None:
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image_set.add(image)
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yield image_set
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@property
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def height(self):
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"""
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:return: height of each image, in pixels
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:rtype: int
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"""
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return self.metadata[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiHeight')]
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@property
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def width(self):
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"""
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:return: width of each image, in pixels
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:rtype: int
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"""
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return self.metadata[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiWidth')]
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def _calculate_field_of_view(self, frame_number):
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images_per_cycle = len(self.z_levels) * len(self.channels)
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return int((frame_number - (frame_number % images_per_cycle)) / images_per_cycle) % len(self.fields_of_view)
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def _calculate_channel(self, frame_number):
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return self._channels[frame_number % len(self.channels)]
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def _calculate_z_level(self, frame_number):
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return self.z_levels[int(((frame_number - (frame_number % len(self.channels))) / len(self.channels)) % len(self.z_levels))]
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def get_image(self, time_index, field_of_view, channel_name, z_level):
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"""
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Returns an Image if data exists for the given parameters, otherwise returns None. In general, you should avoid
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using this method unless you're very familiar with the structure of ND2 files. If you have a use case that
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cannot be met by the `__iter__` or `image_sets` methods above, please create an issue on Github.
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:param time_index: the frame number
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:type time_index: int
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:param field_of_view: the label for the place in the XY-plane where this image was taken.
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:type field_of_view: int
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:param channel_name: the name of the color of this image
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:type channel_name: str
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:param z_level: the label for the location in the Z-plane where this image was taken.
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:type z_level: int
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:rtype: nd2reader.model.Image() or None
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"""
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image_group_number = self._calculate_image_group_number(time_index, field_of_view, z_level)
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try:
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timestamp, raw_image_data = self._get_raw_image_data(image_group_number, self._channel_offset[channel_name])
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image = Image(timestamp, raw_image_data, field_of_view, channel_name, z_level, self.height, self.width)
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except TypeError:
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return None
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else:
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return image
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