Example data for using napari-pyclesperanto-assistant

<p>CalibZAPWfixed_000154_max.tif</p> <p>* Maximum projection of a part of a Drosophila melanogaster embryo showing cell divisions, marked with histone-GFP. Imaged using lightsheet microscopy in Gene Myers lab, MPI-CBG / CSBD Dresden</p> <p>CLIJ_benchmarking_000350.raw.tif</p> <p>* 3D Volume of a Drosophila melanogaster during gastrulation marked histone-GFP.&nbsp;Imaged using lightsheet microscopy in Gene Myers lab, MPI-CBG / CSBD Dresden. This dataset was earlier published&nbsp;<a href="https://bds.mpi-cbg.de/CLIJ_benchmarking_data/">https://bds.mpi-cbg.de/CLIJ_benchmarking_data</a><br> <br> EM_C_6_c0.tif2</p> <p>*&nbsp;Arabidopsis ovule primordium</p> <p>* This file has been resaved to TIF</p> <p>* It originates from&nbsp;https://datadryad.org/stash/dataset/doi:10.5061/dryad.02v6wwq2c It was originally available under CC0 Public Domain by&nbsp;Baroux, C&eacute;lia, University of Zurich,&nbsp;Mendocilla-Sato, Ethel, University of Zurich,&nbsp;Autran, Daphn&eacute;, IRD Montpellier<br> <br> Haase_MRT_tfl3d1.tif</p> <p>* This MRI dataset of the&nbsp;author was acquired at University Hospital Carl Gustav Carus of the University of Technology, TU Dresden as part of academic training of&nbsp;students in the Department of Radiology<br> <br> tissue.tif,&nbsp;tissue_measurements.tif</p> <p>* Simulated tissue + measurement. Code provided for reporducibility:</p> <p>import pyclesperanto_prototype as cle<br> import numpy as np<br> import matplotlib<br> from numpy.random import random</p> <p>cle.select_device(&quot;RTX&quot;)</p> <p># Generate artificial cells as test data<br> tissue = cle.artificial_tissue_2d()</p> <p># fill it with random measurements<br> values = random([int(cle.maximum_of_all_pixels(tissue))])<br> for i, y in enumerate(values):<br> &nbsp; &nbsp; if (i != 95):<br> &nbsp; &nbsp; &nbsp; &nbsp; values[i] = values[i] * 10 + 45<br> &nbsp; &nbsp; else:<br> &nbsp; &nbsp; &nbsp; &nbsp; values[i] = values[i] * 10 + 90</p> <p>measurements = cle.push(np.asarray([values]))</p> <p># visualize measurements in space<br> tissue_measurements = cle.replace_intensities(tissue, measurements)</p>