运行以下matlab代码：
% define new timeseries object, set Quality vector to zero
a=timeseries( ...
[1:6]', ...
[datenum('2010-1-1 0:00'):1/24:datenum('2010-1-1 05:59')]', ...
zeros(6,1) ...
);
% set meta data for new timeseries object
a.QualityInfo.Code = 0:1;
a.TimeInfo.Units = 'days';
a.TimeInfo.Increment = 1/24;
a.TimeInfo.Format = 'dd-mmm-yyyy HH:MM:SS';
a.TimeInfo.StartDate = datestr(0);
% extrapolate timevector and interpolate for half hours.
b=resample(a, ...
datenum('2009-12-31 21:00'):1/48:datenum('2010-1-1 05:59'), ...
'linear', ...
1 ...
)
提供输出：
Time vector characteristics
Length 18
Start date 31-Dec-2009 21:00:00
End date 01-Jan-2010 05:30:00
Data characteristics
Interpolation method linear
Size [18 1]
Data type double
Time Data Quality
---------------------------------------------------------------------------
31-Dec-2009 21:00:00 NaN 1
31-Dec-2009 21:30:00 NaN 1
31-Dec-2009 22:00:00 NaN 1
31-Dec-2009 22:30:00 NaN 1
31-Dec-2009 23:00:00 NaN 1
31-Dec-2009 23:30:00 NaN 1
01-Jan-2010 00:00:00 1 0
01-Jan-2010 00:30:00 1.5 1
01-Jan-2010 01:00:00 2 1
01-Jan-2010 01:30:00 2.5 1
01-Jan-2010 02:00:00 3 1
01-Jan-2010 02:30:00 3.5 1
01-Jan-2010 03:00:00 4 1
01-Jan-2010 03:30:00 4.5 1
01-Jan-2010 04:00:00 5 1
01-Jan-2010 04:30:00 5.5 1
01-Jan-2010 05:00:00 6 1
01-Jan-2010 05:30:00 NaN 1
虽然我期望输出：
Time vector characteristics
Length 18
Start date 31-Dec-2009 21:00:00
End date 01-Jan-2010 05:30:00
Data characteristics
Interpolation method linear
Size [18 1]
Data type double
Time Data Quality
---------------------------------------------------------------------------
31-Dec-2009 21:00:00 NaN 1
31-Dec-2009 21:30:00 NaN 1
31-Dec-2009 22:00:00 NaN 1
31-Dec-2009 22:30:00 NaN 1
31-Dec-2009 23:00:00 NaN 1
31-Dec-2009 23:30:00 NaN 1
01-Jan-2010 00:00:00 1 0
01-Jan-2010 00:30:00 1.5 1
01-Jan-2010 01:00:00 2 0
01-Jan-2010 01:30:00 2.5 1
01-Jan-2010 02:00:00 3 0
01-Jan-2010 02:30:00 3.5 1
01-Jan-2010 03:00:00 4 0
01-Jan-2010 03:30:00 4.5 1
01-Jan-2010 04:00:00 5 0
01-Jan-2010 04:30:00 5.5 1
01-Jan-2010 05:00:00 6 0
01-Jan-2010 05:30:00 NaN 1
给定输出和预期输出之间的差异是，对于插值和外插值，质量向量应仅设置为1，而不应设置为未更改的值。
在Matlab文档中写道，只有插入函数才能改变已经改变的观测值的质量代码。如该示例所示，情况并非如此。
有解决方法吗？
我的matlab版本是：MATLAB版本7.9.1.705（R2009b）Service Pack 1
答案 0 :(得分：0)
我自己找到了一个解决方法：
当您查看第192行的内置Matlab函数\ toobox \ matlab \ timeseries \ @timeseries \ resample.m时：
I = isnan(yin) | abs(yout-yin)>eps;
在此行上确定哪个指标（存储在I中）将获得质量代码1。
通常，你和阴之间的差异要大得多，在这种情况下差别是：
yout-yin
返回：
ans =
1.0e-008 *
0
-0.1118
-0.1118
-0.1118
而eps为：2.2204e-016
通过降低a.Data，我们可以解决Matlab内置函数中的错误::
% extrapolate timevector and interpolate for half hours.
CorrectionFactor = 1/max(max(a.Data))/1e7;
a.Data = a.Data * CorrectionFactor ;
b=resample(a, ...
datenum('2009-12-31 21:00'):1/48:datenum('2010-1-1 05:59'), ...
'linear', ...
1 ...
);
b.Data = b.Data / CorrectionFactor;
b
将作为输出：
Length 18
Start date 31-Dec-2009 21:00:00
End date 01-Jan-2010 05:30:00
Data characteristics
Interpolation method linear
Size [18 1]
Data type double
Time Data Quality
---------------------------------------------------------------------------
31-Dec-2009 21:00:00 NaN 1
31-Dec-2009 21:30:00 NaN 1
31-Dec-2009 22:00:00 NaN 1
31-Dec-2009 22:30:00 NaN 1
31-Dec-2009 23:00:00 NaN 1
31-Dec-2009 23:30:00 NaN 1
01-Jan-2010 00:00:00 1 0
01-Jan-2010 00:30:00 1.5 1
01-Jan-2010 01:00:00 2 0
01-Jan-2010 01:30:00 2.5 1
01-Jan-2010 02:00:00 3 1
01-Jan-2010 02:30:00 3.5 1
01-Jan-2010 03:00:00 4 0
01-Jan-2010 03:30:00 4.5 1
01-Jan-2010 04:00:00 5 0
01-Jan-2010 04:30:00 5.5 1
01-Jan-2010 05:00:00 6 1
01-Jan-2010 05:30:00 NaN 1
正如您所看到的， 01-Jan-2010 02:00:00 和 01-Jan-2010 05:00:00 仍有问题，可以通过调整定义时间向量的方式来解决。我们需要替换：
datenum('2010-1-1 0:00'):1/24:datenum('2010-1-1 05:59')
与
(datenum('2010-1-1 0:00')*24:datenum('2010-1-1 05:59')*24)/24
完整的解决方案将是：
% define new timeseries object, set Quality vector to zero
a=timeseries( ...
[1:6]', ...
[(datenum('2010-1-1 0:00')*24:datenum('2010-1-1 05:59')*24)/24]', ...
zeros(6,1) ...
);
% set meta data for new timeseries object
a.QualityInfo.Code = 0:1;
a.TimeInfo.Units = 'days';
a.TimeInfo.Increment = 1/24;
a.TimeInfo.Format = 'dd-mmm-yyyy HH:MM:SS';
a.TimeInfo.StartDate = datestr(0);
% extrapolate timevector and interpolate for half hours.
CorrectionFactor = 1/max(max(a.Data))/1e7;
a.Data = a.Data * CorrectionFactor ;
b=resample(a, ...
(datenum('2009-12-31 21:00')*48:datenum('2010-1-1 05:59')*48)/48, ...
'linear', ...
1 ...
);
b.Data = b.Data / CorrectionFactor;
b
，这给出了我们将要考虑的输出：
Time vector characteristics
Length 18
Start date 31-Dec-2009 21:00:00
End date 01-Jan-2010 05:30:00
Data characteristics
Interpolation method linear
Size [18 1]
Data type double
Time Data Quality
---------------------------------------------------------------------------
31-Dec-2009 21:00:00 NaN 1
31-Dec-2009 21:30:00 NaN 1
31-Dec-2009 22:00:00 NaN 1
31-Dec-2009 22:30:00 NaN 1
31-Dec-2009 23:00:00 NaN 1
31-Dec-2009 23:30:00 NaN 1
01-Jan-2010 00:00:00 1 0
01-Jan-2010 00:30:00 1.5 1
01-Jan-2010 01:00:00 2 0
01-Jan-2010 01:30:00 2.5 1
01-Jan-2010 02:00:00 3 0
01-Jan-2010 02:30:00 3.5 1
01-Jan-2010 03:00:00 4 0
01-Jan-2010 03:30:00 4.5 1
01-Jan-2010 04:00:00 5 0
01-Jan-2010 04:30:00 5.5 1
01-Jan-2010 05:00:00 6 0
01-Jan-2010 05:30:00 NaN 1