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165 lines
5.3 KiB
165 lines
5.3 KiB
# -*- coding: utf-8 -*-
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from nd2reader.model import ImageGroup
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from nd2reader.parser import get_parser
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from nd2reader.version import get_version
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import warnings
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class Nd2(object):
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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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self._filename = filename
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self._fh = open(filename, "rb")
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major_version, minor_version = get_version(self._fh)
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parser = get_parser(self._fh, major_version, minor_version)
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self._driver = parser.driver
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self._metadata = parser.metadata
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc_val, exc_tb):
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if self._fh is not None:
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self._fh.close()
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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.date if self.date is not None else "Unknown"),
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"Image size: %sx%s (HxW)" % (self.height, self.width),
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"Frames: %s" % len(self.frames),
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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._metadata.total_images_per_channel * len(self.channels)
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def __getitem__(self, item):
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"""
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Allows slicing ND2s.
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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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image = self._driver.get_image(item)
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except KeyError:
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raise IndexError
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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()
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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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warnings.warn("Nd2.image_sets will be removed from the nd2reader library in the near future.",
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DeprecationWarning)
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for frame in self.frames:
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image_group = ImageGroup()
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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(frame, fov, channel_name, z_level)
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if image is not None:
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image_group.add(image)
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yield image_group
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@property
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def date(self):
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return self._metadata.date
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@property
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def z_levels(self):
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return self._metadata.z_levels
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@property
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def fields_of_view(self):
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return self._metadata.fields_of_view
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@property
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def channels(self):
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return self._metadata.channels
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@property
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def frames(self):
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return self._metadata.frames
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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.height
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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.width
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def get_image(self, frame_number, 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.
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:type frame_number: 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()
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"""
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return self._driver.get_image_by_attributes(frame_number, field_of_view, channel_name, z_level, self.height, self.width)
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def close(self):
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self._fh.close()
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