def compute_boxplot(vs, experiment_interval=EXPERIMENT_INTERVAL): #box_entries = int(10.0 / MEASUREMENT_INTERVAL) box_entries = int(BOX_INTERVAL / MEASUREMENT_INTERVAL) ts = np.arange(len(vs)) * MEASUREMENT_INTERVAL #return fold(quantize(zip(ts, vs), box_entries), int(experiment_interval / (box_entries * MEASUREMENT_INTERVAL)), skip = 1) return fold(quantize(zip(ts, vs), box_entries), int(EXPERIMENT_INTERVAL / (box_entries * MEASUREMENT_INTERVAL)), skip = 1)
def compute_boxplot(vs, experiment_interval=EXPERIMENT_INTERVAL): #box_entries = int(10.0 / MEASUREMENT_INTERVAL) box_entries = int(BOX_INTERVAL / MEASUREMENT_INTERVAL) ts = np.arange(len(vs)) * MEASUREMENT_INTERVAL return fold(quantize(zip(ts, vs), box_entries), int(experiment_interval / (box_entries * MEASUREMENT_INTERVAL)), skip=1)
def compute_boxplot(xs): """ Combine the consecutive experiments into boxes """ #print(list(t_quantize(((x.t, 1) for x in xs), BOX_INTERVAL, align=EXPERIMENT_INTERVAL, #align_phase=12.0))) r = fold( t_quantize(((x.t, 1) for x in xs), BOX_INTERVAL, align=EXPERIMENT_INTERVAL, align_phase=12.0), int(EXPERIMENT_INTERVAL / BOX_INTERVAL) ) #r = list(r) #print(r) return r