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# -*- coding: utf-8 -*-
from nd2reader.model import ImageGroup
from nd2reader.parser import get_parser
from nd2reader.version import get_version
import warnings
class Nd2(object):
"""
Allows easy access to NIS Elements .nd2 image files.
"""
def __init__(self, filename):
self._filename = filename
self._fh = open(filename, "rb")
major_version, minor_version = get_version(self._fh)
parser = get_parser(self._fh, major_version, minor_version)
self._driver = parser.driver
self._metadata = parser.metadata
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if self._fh is not None:
self._fh.close()
def __repr__(self):
return "\n".join(["<ND2 %s>" % self._filename,
"Created: %s" % (self.date if self.date is not None else "Unknown"),
"Image size: %sx%s (HxW)" % (self.height, self.width),
"Frames: %s" % len(self.frames),
"Channels: %s" % ", ".join(["'%s'" % str(channel) for channel in self.channels]),
"Fields of View: %s" % len(self.fields_of_view),
"Z-Levels: %s" % len(self.z_levels)
])
def __len__(self):
"""
This should be the total number of images in the ND2, but it may be inaccurate. If the ND2 contains a
different number of images in a cycle (i.e. there are "gap" images) it will be higher than reality.
:rtype: int
"""
return self._metadata.total_images_per_channel * len(self.channels)
def __getitem__(self, item):
"""
Allows slicing ND2s.
:type item: int or slice
:rtype: nd2reader.model.Image() or generator
"""
if isinstance(item, int):
try:
image = self._driver.get_image(item)
except KeyError:
raise IndexError
else:
return image
elif isinstance(item, slice):
return self._slice(item.start, item.stop, item.step)
raise IndexError
def _slice(self, start, stop, step):
"""
Allows for iteration over a selection of the entire dataset.
:type start: int
:type stop: int
:type step: int
:rtype: nd2reader.model.Image()
"""
start = start if start is not None else 0
step = step if step is not None else 1
stop = stop if stop is not None else len(self)
# This weird thing with the step allows you to iterate backwards over the images
for i in range(start, stop)[::step]:
yield self[i]
@property
def image_sets(self):
"""
Iterates over groups of related images. This is useful if your ND2 contains multiple fields of view.
A typical use case might be that you have, say, four areas of interest that you're monitoring, and every
minute you take a bright field and GFP image of each one. For each cycle, this method would produce four
ImageSet objects, each containing one bright field and one GFP image.
:return: model.ImageSet()
"""
warnings.warn("Nd2.image_sets will be removed from the nd2reader library in the near future.",
DeprecationWarning)
for frame in self.frames:
image_group = ImageGroup()
for fov in self.fields_of_view:
for channel_name in self.channels:
for z_level in self.z_levels:
image = self.get_image(frame, fov, channel_name, z_level)
if image is not None:
image_group.add(image)
yield image_group
@property
def date(self):
return self._metadata.date
@property
def z_levels(self):
return self._metadata.z_levels
@property
def fields_of_view(self):
return self._metadata.fields_of_view
@property
def channels(self):
return self._metadata.channels
@property
def frames(self):
return self._metadata.frames
@property
def height(self):
"""
:return: height of each image, in pixels
:rtype: int
"""
return self._metadata.height
@property
def width(self):
"""
:return: width of each image, in pixels
:rtype: int
"""
return self._metadata.width
def get_image(self, frame_number, field_of_view, channel_name, z_level):
"""
Returns an Image if data exists for the given parameters, otherwise returns None.
:type frame_number: int
:param field_of_view: the label for the place in the XY-plane where this image was taken.
:type field_of_view: int
:param channel_name: the name of the color of this image
:type channel_name: str
:param z_level: the label for the location in the Z-plane where this image was taken.
:type z_level: int
:rtype: nd2reader.model.Image()
"""
return self._driver.get_image_by_attributes(frame_number, field_of_view, channel_name, z_level, self.height, self.width)
def close(self):
self._fh.close()