iteration = 1
niters = 4
# create data array
y = np.zeros( (nsteps+1, 2, N, 3) )
# load initial data
y0, charge_src, charge_targ, dipstr_src, dipvec_src = mu.load_initial_data(input_dir)
y[0,:] = y0[:]
# load pfasst data
mu.load_pfasst_data(output_dir, y, level, iteration)
# load pfasst data
idx = 1 # for velocity (niters, nsteps, N, 3)
data = mc.get_data(output_dir, nsources, idx)
data2 = np.zeros((niters, nsteps+1, 2, N, 3))
mu.load_pfasst_data_all(output_dir, data2, level)
err = abs ( data - data2[:,1:,1,:nsources] )
magerr = np.zeros((niters, nsteps, nsources))
maxmag = np.zeros((niters, nsteps))
p = np.zeros(maxmag.shape)
""""
for k in range(niters):
for i in range(nsteps):
for j in range(nsources):
magerr[k,i,j] = la.norm(err[k,i,j,:])
# Run #--------------------------------------- data_dir = "/home/namdi/Documents/School/UNC/Parallel_Time/Data" fpath = data_dir + "/Results/2014_05/10" fpath = fpath + "/pmrfmm_s64_a3_f5" # load parameters fname = fpath + "/t_0/info.txt" nsources, ntargets, distribution = mu.load_parameters2(fname) # the data has shape (niters, nsteps, N, 3) # the data does not contain the initial condition idx = 1 vel = mc.get_data(fpath, nsources, idx) # load initial data y0 (2, N, 3) fpath = fpath + "/t_0" y0, charge_src, charge_targ, dipstr_src, dipvec_src = mu.load_initial_data(fpath) # store the number of steps (not including the initial condition) and iterations niters = vel.shape[0] nsteps = vel.shape[1] # the mommentum of the initial condition mom0 = sum(y0[1,:]) mom = np.zeros((niters, nsteps,3)) mag = np.zeros((niters, nsteps)) p = np.zeros(mag.shape)
