- seqread: lazily read delta_t

- calculate timeinterval more efficiently
- remove timeval field
- bugfix in retrieving laser wavelenghts and powers
- add series/pos to summary
- cziread: better assign lightsources to channels

ndbioimage/__init__.py

@@ -17,12 +17,12 @@ from parfor import parfor
 from tiffwrite import IJTiffFile
 from numbers import Number
 from argparse import ArgumentParser
-from ndbioimage.transforms import Transform, Transforms
-from ndbioimage.jvm import JVM
 from typing import List
 from pathlib import Path
 from importlib.metadata import version
 from traceback import print_exc
+from ndbioimage.transforms import Transform, Transforms
+from ndbioimage.jvm import JVM
 
 
 try:
@@ -535,8 +535,9 @@ class Imread(np.lib.mixins.NDArrayOperatorsMixin, metaclass=ABCMeta):
             self.objective = find(instrument.objectives, id=self.ome.images[0].objective_settings.id)
         else:
             self.objective = None
-        self.timeval = [find(image.pixels.planes, the_c=0, the_t=t, the_z=0).delta_t for t in range(self.shape['t'])]
-        self.timeinterval = np.diff(self.timeval).mean() if len(self.timeval) > 1 else 0
+        t0 = find(image.pixels.planes, the_c=0, the_t=0, the_z=0).delta_t
+        t1 = find(image.pixels.planes, the_c=0, the_t=self.shape['t'] - 1, the_z=0).delta_t
+        self.timeinterval = (t1 - t0) / (self.shape['t'] - 1) if self.shape['t'] > 1 else None
         try:
             self.binning = [int(i) for i in image.pixels.channels[0].detector_settings.binning.value.split('x')]
             self.pxsize *= self.binning[0]
@@ -562,9 +563,9 @@ class Imread(np.lib.mixins.NDArrayOperatorsMixin, metaclass=ABCMeta):
                      for channel in image.pixels.channels
                      if channel.detector_settings
                      and find(instrument.detectors, id=channel.detector_settings.id).amplification_gain]
-        self.laserwavelengths = [(channel.emission_wavelength_quantity.to(self.ureg.nm).m,)
-                                 for channel in pixels.channels if channel.emission_wavelength_quantity]
-        self.laserpowers = try_default(lambda channel: [(1 - channel.light_source_settings.attenuation,)
+        self.laserwavelengths = [(channel.excitation_wavelength_quantity.to(self.ureg.nm).m,)
+                                 for channel in pixels.channels if channel.excitation_wavelength_quantity]
+        self.laserpowers = try_default(lambda: [(1 - channel.light_source_settings.attenuation,)
                                                 for channel in pixels.channels], [])
         self.filter = try_default(lambda: [find(instrument.filter_sets, id=channel.filter_set_ref.id).model
                                            for channel in image.pixels.channels], None)
@@ -697,6 +698,7 @@ class Imread(np.lib.mixins.NDArrayOperatorsMixin, metaclass=ABCMeta):
     def summary(self):
         """ gives a helpful summary of the recorded experiment """
         s = [f"path/filename: {self.path}",
+             f"series/pos:    {self.series}",
              f"reader:        {self.__class__.__module__.split('.')[-1]}",
              f"shape ({self.axes}):".ljust(15) + f"{' x '.join(str(i) for i in self.shape)}"]
         if self.pxsize_um:

ndbioimage/readers/cziread.py

@@ -360,10 +360,12 @@ class Reader(Imread, ABC):
 
             light_sources_settings = channel.find("LightSourcesSettings")
             # no space in ome for multiple lightsources simultaneously
+            if len(light_sources_settings) > idx:
+                light_source_settings = light_sources_settings[idx]
+            else:
                 light_source_settings = light_sources_settings[0]
             light_source_settings = model.LightSourceSettings(
-                id="_".join([light_source_settings.find("LightSource").attrib["Id"]
-                             for light_source_settings in light_sources_settings]),
+                id=light_source_settings.find("LightSource").attrib["Id"],
                 attenuation=float(text(light_source_settings.find("Attenuation"))),
                 wavelength=float(text(light_source_settings.find("Wavelength"))),
                 wavelength_unit=nm)
@@ -376,7 +378,7 @@ class Reader(Imread, ABC):
                     color=model.simple_types.Color(text(channels_ds[channel.attrib["Id"]].find("Color"))),
                     detector_settings=model.DetectorSettings(id=detector.attrib["Id"], binning=binning),
                     emission_wavelength=text(channel.find("EmissionWavelength")),
-                    excitation_wavelength=text(channel.find("ExcitationWavelength")),
+                    excitation_wavelength=light_source_settings.wavelength,
                     filter_set_ref=model.FilterSetRef(id=ome.instruments[0].filter_sets[filterset_idx].id),
                     illumination_type=text(channel.find("IlluminationType")),
                     light_source_settings=light_source_settings,

ndbioimage/readers/seqread.py

@@ -5,10 +5,35 @@ from ndbioimage import Imread
 from pathlib import Path
 from functools import cached_property
 from ome_types import model
+from ome_types._base_type import quantity_property
 from itertools import product
 from datetime import datetime
 from abc import ABC
-from parfor import pmap
+
+
+def lazy_property(function, field, *arg_fields):
+    def lazy(self):
+        if self.__dict__.get(field) is None:
+            self.__dict__[field] = function(*[getattr(self, arg_field) for arg_field in arg_fields])
+            self.__fields_set__.add(field)
+        return self.__dict__[field]
+    return property(lazy)
+
+
+class Plane(model.Plane):
+    """ Lazily retrieve delta_t from metadata """
+    def __init__(self, t0, file, **kwargs):
+        super().__init__(**kwargs)
+        setattr(self.__class__, 'delta_t', lazy_property(self.get_delta_t, 'delta_t', 't0', 'file'))
+        setattr(self.__class__, 'delta_t_quantity', quantity_property('delta_t'))
+        self.__dict__['t0'] = t0
+        self.__dict__['file'] = file
+
+    @staticmethod
+    def get_delta_t(t0, file):
+        with tifffile.TiffFile(file) as tif:
+            info = yaml.safe_load(tif.pages[0].tags[50839].value['Info'])
+        return float((datetime.strptime(info["Time"], "%Y-%m-%d %H:%M:%S %z") - t0).seconds)
 
 
 class Reader(Imread, ABC):
@@ -65,19 +90,10 @@ class Reader(Imread, ABC):
                     physical_size_z=metadata["Info"]["Summary"]["z-step_um"]),
                 objective_settings=model.ObjectiveSettings(id="Objective:0")))
 
-        def timeval_fun(i):
-            with tifffile.TiffFile(self.filedict[i]) as tif:
-                info = yaml.safe_load(tif.pages[0].tags[50839].value['Info'])
-            return (datetime.strptime(info["Time"], "%Y-%m-%d %H:%M:%S %z") - t0).seconds
-
-        length = size_c * size_z * size_t
-        timeval = pmap(timeval_fun, product(range(size_c), range(size_z), range(size_t)), length=length,
-                       serial=length <= 24, desc='Reading metadata')
-
-        for (c, z, t), time in zip(product(range(size_c), range(size_z), range(size_t)), timeval):
+        for c, z, t in product(range(size_c), range(size_z), range(size_t)):
             ome.images[0].pixels.planes.append(
-                model.Plane(
-                    the_c=c, the_z=z, the_t=t, exposure_time=metadata["Info"]["Exposure-ms"] / 1000, delta_t=time))
+                Plane(t0, self.filedict[c, z, t],
+                      the_c=c, the_z=z, the_t=t, exposure_time=metadata["Info"]["Exposure-ms"] / 1000))
 
         # compare channel names from metadata with filenames
         pattern_c = re.compile(r"img_\d{3,}_(.*)_\d{3,}$")

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ndbioimage"
-version = "2023.7.0"
+version = "2023.7.1"
 description = "Bio image reading, metadata and some affine registration."
 authors = ["W. Pomp <w.pomp@nki.nl>"]
 license = "GPLv3"