def dorun(SNR=<NUM_LIT:20>, njitters=<NUM_LIT:20>, samples=<NUM_LIT:10>, noise_samples=<NUM_LIT:10>, sweeps=<NUM_LIT:20>, burn=<NUM_LIT:10>):
jitters = np.logspace(-<NUM_LIT:6>, np.log10(<NUM_LIT:0.5>), njitters)<EOL>crbs, vals, errs, poss = [], [], [], []<EOL>for i,t in enumerate(jitters):<EOL><INDENT>print('<STR_LIT>', i, t)<EOL>for j in range(samples):<EOL><INDENT>print('<STR_LIT:image>', j, '<STR_LIT:|>', end='<STR_LIT:U+0020>') <EOL>s,im,pos = zjitter(jitter=t)<EOL>common.set_image(s, im, <NUM_LIT:1.0>/SNR)<EOL>crbs.append(crb(s))<EOL>val, err = sample(s, im, <NUM_LIT:1.0>/SNR, N=noise_samples, sweeps=sweeps, burn=burn)<EOL>poss.append(pos)<EOL>vals.append(val)<EOL>errs.append(err)<EOL><DEDENT><DEDENT>shape0 = (njitters, samples, -<NUM_LIT:1>)<EOL>shape1 = (njitters, samples, noise_samples, -<NUM_LIT:1>)<EOL>crbs = np.array(crbs).reshape(shape0)<EOL>vals = np.array(vals).reshape(shape1)<EOL>errs = np.array(errs).reshape(shape1)<EOL>poss = np.array(poss).reshape(shape0)<EOL>return  [crbs, vals, errs, poss, jitters]<EOL>
we want to display the errors introduced by pixelation so we plot:
    * CRB, sampled error vs exposure time

a = dorun(ntimes=10, samples=5, noise_samples=5, sweeps=20, burn=8)