#! /usr/bin/env python import sys import re import yt import numpy as np sys.path.insert(1, '../../../../warpx/Regression/Checksum/') import checksumAPI tolerance = sys.float_info.epsilon print('tolerance = ', tolerance) filename = sys.argv[1] psatd = True if re.search('psatd', filename) else False averaged = True if re.search('avg', filename) else False ds = yt.load( filename ) ad = ds.all_data() xb = ad['beam', 'particle_position_x'].to_ndarray() xe = ad['plasma_e', 'particle_position_x'].to_ndarray() zb = ad['beam', 'particle_position_z'].to_ndarray() ze = ad['plasma_e', 'particle_position_z'].to_ndarray() filename = 'orig_restart_plt00010' if psatd: filename = 'orig_restart_psatd_plt00010' if averaged: filename = 'orig_restart_psatd_time_avg_plt00010' ds = yt.load( filename ) ad = ds.all_data() xb0 = ad['beam', 'particle_position_x'].to_ndarray() xe0 = ad['plasma_e', 'particle_position_x'].to_ndarray() zb0 = ad['beam', 'particle_position_z'].to_ndarray() ze0 = ad['plasma_e', 'particle_position_z'].to_ndarray() xb.sort() xb0.sort() assert(np.max(abs(xb-xb0))