def _mosaic_get_full_block(sorted_mosaics):
"""
Generate a full datablock containing all timepoints
"""
# For each slice / mosaic create a data volume block
data_blocks = []
for index in range(0, len(sorted_mosaics)):
data_blocks.append(_mosaic_to_block(sorted_mosaics[index]))
# Add the data_blocks together to one 4d block
size_x = numpy.shape(data_blocks[0])[0]
size_y = numpy.shape(data_blocks[0])[1]
size_z = numpy.shape(data_blocks[0])[2]
size_t = len(data_blocks)
full_block = numpy.zeros((size_x, size_y, size_z, size_t), dtype=data_blocks[0].dtype)
for index in range(0, size_t):
full_block[:, :, :, index] = data_blocks[index]
# Apply the rescaling if needed
common.apply_scaling(full_block, sorted_mosaics[0])
return full_block
def _singleframe_to_block(grouped_dicoms):
"""
Generate a full datablock containing all timepoints
"""
# For each slice / mosaic create a data volume block
data_blocks = []
for index in range(0, len(grouped_dicoms)):
print('Creating block %s of %s' % (index + 1, len(grouped_dicoms)))
current_block = _stack_to_block(grouped_dicoms[index])
current_block = current_block[:, :, :, numpy.newaxis]
data_blocks.append(current_block)
try:
full_block = numpy.concatenate(data_blocks, axis=3)
except:
traceback.print_exc()
raise ConversionError("MISSING_DICOM_FILES")
# Apply the rescaling if needed
common.apply_scaling(full_block, grouped_dicoms[0][0])
return full_block
def _singleframe_to_block(grouped_dicoms):
"""
Generate a full datablock containing all timepoints
"""
# For each slice / mosaic create a data volume block
data_blocks = []
for index in range(0, len(grouped_dicoms)):
logger.info('Creating block %s of %s' % (index + 1, len(grouped_dicoms)))
current_block = _stack_to_block(grouped_dicoms[index])
current_block = current_block[:, :, :, numpy.newaxis]
data_blocks.append(current_block)
try:
full_block = numpy.concatenate(data_blocks, axis=3)
except:
traceback.print_exc()
raise ConversionError("MISSING_DICOM_FILES")
# Apply the rescaling if needed
common.apply_scaling(full_block, grouped_dicoms[0][0])
return full_block
def _mosaic_get_full_block(sorted_mosaics):
"""
Generate a full datablock containing all timepoints
"""
# For each slice / mosaic create a data volume block
data_blocks = []
for index in range(0, len(sorted_mosaics)):
data_blocks.append(_mosaic_to_block(sorted_mosaics[index]))
# Add the data_blocks together to one 4d block
size_x = numpy.shape(data_blocks[0])[0]
size_y = numpy.shape(data_blocks[0])[1]
size_z = numpy.shape(data_blocks[0])[2]
size_t = len(data_blocks)
full_block = numpy.zeros((size_x, size_y, size_z, size_t), dtype=data_blocks[0].dtype)
for index in range(0, size_t):
full_block[:, :, :, index] = data_blocks[index]
# Apply the rescaling if needed
common.apply_scaling(full_block, sorted_mosaics[0])
return full_block
