def test_labelled_cells(): # Create a scene scene = Scene() # specify that you want a view from the top # Gerate the coordinates of N cells across 3 regions regions = ["MOs", "VISp", "ZI"] N = 1000 # getting 1k cells per region, but brainrender can deal with >1M cells easily. # Render regions scene.add_brain_regions(regions, alpha=.2) # Get fake cell coordinates cells = [] # to store x,y,z coordinates for region in regions: region_cells = scene.get_n_random_points_in_region(region=region, N=N) cells.extend(region_cells) x, y, z = [c[0] for c in cells], [c[1] for c in cells], [c[2] for c in cells] cells = pd.DataFrame(dict(x=x, y=y, z=z)) # Add cells scene.add_cells(cells, color='darkseagreen', res=12, radius=25)
import brainrender brainrender.SHADER_STYLE = 'cartoon' from brainrender.scene import Scene # Create a scene scene = Scene() # specify that you want a view from the top # Gerate the coordinates of N cells across 3 regions regions = ["MOs", "VISp", "ZI"] N = 1000 # getting 1k cells per region, but brainrender can deal with >1M cells easily. # Render regions scene.add_brain_regions(regions, alpha=.2) # Get fake cell coordinates cells = [] # to store x,y,z coordinates for region in regions: region_cells = scene.get_n_random_points_in_region(region=region, N=N) cells.extend(region_cells) x, y, z = [c[0] for c in cells], [c[1] for c in cells], [c[2] for c in cells] cells = pd.DataFrame(dict( x=x, y=y, z=z)) # ! <- coordinates should be stared as a pandas dataframe # Add cells scene.add_cells(cells, color='darkseagreen', res=12, radius=25) # render scene.render()