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from pims import FramesSequenceND, Frame
from nd2reader.parser import Parser
import numpy as np
class ND2Reader(FramesSequenceND):
"""PIMS wrapper for the ND2 parser
"""
def __init__(self, filename):
self.filename = filename
# first use the parser to parse the file
self._fh = open(filename, "rb")
self._parser = Parser(self._fh)
# Setup metadata
self.metadata = self._parser.metadata
# Set data type
self._dtype = self._parser.get_dtype_from_metadata()
# Setup the axes
self._setup_axes()
@classmethod
def class_exts(cls):
"""Let PIMS open function use this reader for opening .nd2 files
"""
return {'nd2'} | super(ND2Reader, cls).class_exts()
def close(self):
"""Correctly close the file handle
"""
if self._fh is not None:
self._fh.close()
def get_frame(self, i):
"""Return one frame
Args:
i: The frame number
Returns:
numpy.ndarray: The requested frame
"""
fetch_all_channels = 'c' in self.bundle_axes
if fetch_all_channels:
return self._get_frame_all_channels(i)
else:
return self.get_frame_2D(self.default_coords['c'], i, self.default_coords['z'])
def _get_frame_all_channels(self, i):
"""Get all color channels for this frame
Args:
i: The frame number
Returns:
numpy.ndarray: The requested frame, with all color channels.
"""
frames = None
for c in range(len(self.metadata["channels"])):
frame = self.get_frame_2D(c, i, self.default_coords['z'])
if frames is None:
frames = Frame([frame])
else:
frames = np.concatenate((frames, [frame]), axis=0)
return frames
def get_frame_2D(self, c, t, z):
"""Gets a given frame using the parser
Args:
c: The color channel number
t: The frame number
z: The z stack number
Returns:
numpy.ndarray: The requested frame
"""
c_name = self.metadata["channels"][c]
return self._parser.get_image_by_attributes(t, 0, c_name, z, self.metadata["height"], self.metadata["width"])
@property
def parser(self):
"""
Returns the parser object.
Returns:
Parser: the parser object
"""
return self._parser
@property
def pixel_type(self):
"""Return the pixel data type
Returns:
dtype: the pixel data type
"""
return self._dtype
def _setup_axes(self):
"""Setup the xyctz axes, iterate over t axis by default
"""
self._init_axis('x', self.metadata["width"])
self._init_axis('y', self.metadata["height"])
self._init_axis('c', len(self.metadata["channels"]))
self._init_axis('t', len(self.metadata["frames"]))
self._init_axis('z', len(self.metadata["z_levels"]))
# provide the default
self.iter_axes = 't'
def get_timesteps(self):
"""Get the timesteps of the experiment
Returns:
np.ndarray: an array of times in milliseconds.
"""
timesteps = np.array([])
current_time = 0.0
for loop in self.metadata['experiment']['loops']:
if loop['stimulation']:
continue
timesteps = np.concatenate(
(timesteps, np.arange(current_time, current_time + loop['duration'], loop['sampling_interval'])))
current_time += loop['duration']
# if experiment did not finish, number of timesteps is wrong. Take correct amount of leading timesteps.
return timesteps[:self.metadata['num_frames']]