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Workaround issue #6, fix unit test timesteps

zolfa-add_slices_loading
Ruben Verweij 6 years ago
parent
commit
2a807946da
2 changed files with 8 additions and 5 deletions
  1. +3
    -3
      nd2reader/artificial.py
  2. +5
    -2
      nd2reader/parser.py

+ 3
- 3
nd2reader/artificial.py View File

@ -289,9 +289,9 @@ class ArtificialND2(object):
7, # CustomData|CustomDescriptionV1_0!", 7, # CustomData|CustomDescriptionV1_0!",
7, # CustomData|Camera_ExposureTime1!", 7, # CustomData|Camera_ExposureTime1!",
7, # CustomData|CameraTemp1!", 7, # CustomData|CameraTemp1!",
7, # CustomData|AcqTimesCache!",
7, # CustomData|AcqTimes2Cache!",
7, # CustomData|AcqFramesCache!",
[0], # CustomData|AcqTimesCache!",
[0], # CustomData|AcqTimes2Cache!",
[0], # CustomData|AcqFramesCache!",
7, # CustomDataVar|LUTDataV1_0!", 7, # CustomDataVar|LUTDataV1_0!",
7, # CustomDataVar|GrabberCameraSettingsV1_0!", 7, # CustomDataVar|GrabberCameraSettingsV1_0!",
7, # CustomDataVar|CustomDataV2_0!", 7, # CustomDataVar|CustomDataV2_0!",


+ 5
- 2
nd2reader/parser.py View File

@ -265,8 +265,11 @@ class Parser(object):
# The images for the various channels are interleaved within the same array. For example, the second image # The images for the various channels are interleaved within the same array. For example, the second image
# of a four image group will be composed of bytes 2, 6, 10, etc. If you understand why someone would design # of a four image group will be composed of bytes 2, 6, 10, etc. If you understand why someone would design
# a data structure that way, please send the author of this library a message. # a data structure that way, please send the author of this library a message.
number_of_true_channels = int((len(image_group_data) - 4) / (height * width))
image_data = np.reshape(image_group_data[image_data_start::number_of_true_channels], (height, width))
number_of_true_channels = int(len(image_group_data[image_data_start:]) / (height * width))
try:
image_data = np.reshape(image_group_data[image_data_start::number_of_true_channels], (height, width))
except ValueError:
image_data = np.reshape(image_group_data[image_data_start::number_of_true_channels], (height, int(len(image_group_data[image_data_start::number_of_true_channels])/height)))
# Skip images that are all zeros! This is important, since NIS Elements creates blank "gap" images if you # Skip images that are all zeros! This is important, since NIS Elements creates blank "gap" images if you
# don't have the same number of images each cycle. We discovered this because we only took GFP images every # don't have the same number of images each cycle. We discovered this because we only took GFP images every


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