两个数据集的python生成器表达式

Question

#Find values that are in range
in_range = [lo_lim <= v <= hi_lim for v in values]
#Find runs of in-range values
runs = [sum(1 for _ in group) for v, group in groupby(in_range) if v]

#Estimate total time spent in-range
total_time = sum(v if v > 1 else (Buffer_Value*sample_rate) for v in runs)

我试图扩充这段代码，得到两组值和两对hi/lo极限， 为了计算在这些限制内花费的总时间，当同一点的“限制内”情况为真时的组合限制，即

如果有100个数据点（两个数据集长度相同，请检查每个点

if values_1[45] and values_2[45] are in their respective limits

然后算在范围内。 本质上把这个if转换成一个生成器表达式：

if lo_lim_1<=Data_Points_1[i]<=hi_lim_1 and lo_lim_2<=Data_Points_2[i]<=hi_lim_2:

计算运行次数，如果运行长度为一个数据点，则应用缓冲区，否则应用采样率转换。你知道吗

Answer 1

如果我理解你的问题，这应该管用。基本思想是zip将两个序列组合成一对对应的值，然后使用and操作查找它们都在相应范围内的情况：

#Find values that are in range
in_range = [lo_lim1 <= v1 <= hi_lim1 and lo_lim2 <= v2 <= hi_lim2 for v1, v2 in zip(values1, values2)]

# code is unchanged from here
#Find runs of in-range values
runs = [sum(1 for _ in group) for v, group in groupby(in_range) if v]  # this is the same as yours

#Estimate total time spent in-range
total_time = sum(v if v > 1 else (Buffer_Value*sample_rate) for v in runs)

在本例中，如果您使用的是python 2.x，则可以使用itertools.izip而不是zip来节省一些内存，对于python 2.x和3.x，可以使用生成器表达式来节省更多内存：

#Find values that are in range
in_range = (lo_lim1 <= v1 <= hi_lim1 and lo_lim2 <= v2 <= hi_lim2 for v1, v2 in zip(values1, values2))

#Find runs of in-range values
runs = (sum(1 for _ in group) for v, group in groupby(in_range) if v)  # this is the same as yours

#Estimate total time spent in-range
defval = Buffer_Value*sample_rate
total_time = sum(v if v > 1 else defval for v in runs)