Hello yt users, I have a question about projection. I used ds.proj() and to_frb() to get an image array of the projected 'Electron_Density' of an entire dataset. I multiplied the mean of projected 'Electron_Density' by the entire area of x-y plane and got a sum of total mass of electrons. Then, I used ds.all_data() and mean() to get the mean of 'Electron_Density' in 3-dimensional. I multiplied the mean by the volume of the entire box of the dataset and got another sum of total mass of electrons. However, this sum did not match the sum I got from the projected 'Electron_Density' previously. Here are the codes I used: import yt import numpy as np ds = yt.load("redshift0100/redshift0100") print("Redshift =", ds.current_redshift) p = yt.ProjectionPlot(ds, 2, 'Electron_Density') density_image = p.frb['Electron_Density'] ed = density_image['Electron_Density'].convert_to_cgs() ed_ndarr = ed.to_ndarray() sum1 = ed_ndarr.mean() * ((105.82 * 3.085677581e+24)**2) print(sum1) dd = ds.all_data() ed_3d = dd['Electron_Density'].convert_to_cgs() sum2 = ed_3d.mean() * ((105.82 * 3.085677581e+24)**3) print(sum2) (105.82 * 3.085677581e+24) is the width of entire box in cm. I think sum1 and sum2 should be close to each other, but the result was that the two values did not match with each other. Is there any problem in the codes I used to get the values of sum1 and sum2? Could some one give me some help? Thank you very much! Sincerely, Hansheng