diff --git a/nd2reader/parser.py b/nd2reader/parser.py
index 8534e7996fad76eec9c1e85efe55caefb0d3d4bf..814712848dfd7dea3afd3c4d14d1e0f49c756a19 100644
--- a/nd2reader/parser.py
+++ b/nd2reader/parser.py
@@ -6,6 +6,7 @@ import six
import warnings
from pims.base_frames import Frame
import numpy as np
+from tqdm import tqdm
from nd2reader.common import get_version, read_chunk
from nd2reader.label_map import LabelMap
@@ -78,6 +79,38 @@ class Parser(object):
else:
return Frame(image, frame_no=frame_number, metadata=self._get_frame_metadata())
+ def get_slice_by_attributes(self, xywh, frame_number, field_of_view, channel, z_level, height, width):
+ """Gets a rectangular slice of an image based on its attributes alone
+
+ Args:
+ xywh: tuples containing (x, y, w, h) values of the
+ rectangular region to load
+ frame_number: the frame number
+ field_of_view: the field of view
+ channel_name: the color channel name
+ z_level: the z level
+ height: the height of the image
+ width: the width of the image
+
+ Returns:
+ Frame: the requested image
+
+ """
+ frame_number = 0 if frame_number is None else frame_number
+ field_of_view = 0 if field_of_view is None else field_of_view
+ channel = 0 if channel is None else channel
+ z_level = 0 if z_level is None else z_level
+
+ image_group_number = self._calculate_image_group_number(frame_number, field_of_view, z_level)
+ try:
+ timestamp, raw_image_data = self._get_raw_slice_data(
+ xywh, image_group_number, channel, height, width
+ )
+ except (TypeError):
+ return Frame([], frame_no=frame_number, metadata=self._get_frame_metadata())
+ else:
+ return Frame(raw_image_data, frame_no=frame_number, metadata=self._get_frame_metadata())
+
def get_image_by_attributes(self, frame_number, field_of_view, channel, z_level, height, width):
"""Gets an image based on its attributes alone
@@ -246,6 +279,79 @@ class Parser(object):
"""
return {channel: n for n, channel in enumerate(self.metadata["channels"])}
+ def _get_raw_slice_data(self, xywh, image_group_number, channel, height, width):
+ """Reads the raw bytes and the timestamp of a rectangular slice
+ of an image.
+
+ Args:
+ xywh: tuples containing (x, y, w, h) values of the
+ rectangular region to load
+ image_group_number: the image group number (see _calculate_image_group_number)
+ channel: the position (int) of the channel to load
+ height: the height of the image
+ width: the width of the image
+
+ Returns:
+
+ """
+ size_c = len(self.metadata["channels"])
+
+ x0, y0, w, h = xywh
+ chunk_location = self._label_map.get_image_data_location(image_group_number)
+ fh = self._fh
+
+ if chunk_location is None or fh is None:
+ return None
+ fh.seek(chunk_location)
+ # The chunk metadata is always 16 bytes long
+ chunk_metadata = fh.read(16)
+ header, relative_offset, data_length = struct.unpack("IIQ", chunk_metadata)
+ if header != 0xabeceda:
+ raise ValueError("The ND2 file seems to be corrupted.")
+ # 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.
+ fh.seek(chunk_location + 16 + relative_offset)
+
+ # Read timestamp (8 bytes)
+ timestamp = struct.unpack("d", fh.read(8))[0]
+
+ # Stitched Images: evaluate number of bytes to strip
+ # (with stitched images sometimes after each row we have a regular number of extra bytes)
+ n_unwanted_bytes = (data_length-8) % (height*width)
+ assert 0 == n_unwanted_bytes % height
+ rowskip = n_unwanted_bytes // height
+
+ # Read ROI: row-by-row
+ image_start_pos = chunk_location + 16 + relative_offset + 8
+
+ line_bytemask = np.zeros(size_c, dtype=np.bool)
+ line_bytemask[channel] = True
+ line_bytemask = np.tile(line_bytemask.repeat(2),w)
+
+ def get_line(y):
+ fh.seek(image_start_pos + size_c*2*((width)*y+x0) + y*rowskip)
+ return np.frombuffer(fh.read(size_c*2*w), np.byte)[line_bytemask]
+
+ data = [get_line(y) for y in tqdm(range(y0, y0+h))]
+ data = bytes().join(data)
+
+ image_group_data = array.array("H", data)
+ true_channels_no = int(len(image_group_data) / (h * w))
+
+ image_data = np.reshape(image_group_data, (h, w, true_channels_no))
+
+ missing_channels = ~np.any(image_data, axis=(0, 1))
+ image_data[..., missing_channels] = np.full(
+ (h, w, missing_channels.sum()), np.nan)
+
+ if np.any(missing_channels):
+ warnings.warn(
+ "ND2 file contains gap frames which are represented by "
+ + "np.nan-filled arrays; to convert to zeros use e.g. "
+ + "np.nan_to_num(array)")
+ return timestamp, image_data[...,0]
+
+
def _get_raw_image_data(self, image_group_number, channel_offset, height, width):
"""Reads the raw bytes and the timestamp of an image.
diff --git a/nd2reader/reader.py b/nd2reader/reader.py
index 4e14f42e3cd37f39f59ffb9dd5624c1a32287c82..295bded08427ac578f4bd0197fac6c52bd892464 100644
--- a/nd2reader/reader.py
+++ b/nd2reader/reader.py
@@ -69,6 +69,21 @@ class ND2Reader(FramesSequenceND):
except KeyError:
return 0
+ def get_roi(self, roi, c=0, t=0, z=0, x=0, y=0, v=0):
+ height = self.metadata['height']
+ width = self.metadata['width']
+ ylim = roi[0].indices(height)
+ xlim = roi[1].indices(width)
+
+ y = ylim[0]
+ x = xlim[0]
+ w = xlim[1]-xlim[0]
+ h = ylim[1]-ylim[0]
+
+ return self._parser.get_slice_by_attributes(
+ (x, y, w, h), t, v, c, z, height, width
+ )
+
def get_frame_2D(self, c=0, t=0, z=0, x=0, y=0, v=0):
"""Gets a given frame using the parser
Args: