plot(r[:nevals[0,k]+1], '-')
cal_values.append(guesses[-1, :, :])
- cal_outs.append(results[-1, :, :])
+
+ # results are zeros after [nevals:]
+ # pick off the last real measurement
+ r = zeros_like(results[-1, :, :])
+ for i in range(r.shape[0]):
+ for j in range(r.shape[1]):
+ r[i, j] = results[nevals[i,j]-1, i, j]
+ cal_outs.append(r)
+
+ #cal_outs.append(results[-1, :, :])
nrun += 1
cv = array(cal_values)
data = 1e3*(2.5/2/2**13)*co[:, 0, k]
dm = max((abs(data.min()), abs(data.max())))
print dm
- dm = 50
+ dm = max(dm, 50)
hist(data, bins=100, range=(-dm, dm), align='left')
xlim((-dm, dm))
- ylim((0, 50))
+ #ylim((0, 50))
subplot(N_PLOTS, N_COLS, 1)
title('Offset DAC value')