TRANS_PROFILE

This topic describes TRANS_PROFILE variants (R8, Ra8, R9, Ra9, R10, Ra10, R11, Ra11) for transforming from one time resolution to another.

To get an overview of all the transformation function variants, see:

Transform group functions

R8

About the function

Converts a time series into a finer resolution. The function uses the SUM method as a basis for the distribution.

Syntax

• TRANS_PROFILE(t,t)

Description

TYPE	Description
t	Input time series to be converted.
t	Profile series stating how the values are distributed on each period connected to a value on the input data series. Gives the resolution of the result.

The distribution of the values is done like this:

Vi = Value calculated for the time point i in the result time series

AI = Value from the input time series for the distributed period

NI = Number of valid time point to distributed the input value into

Pi = Profile value for the time point i in the result time series

MI = Calculated mean value for the profile series for the distributed period

Example

Profile = @TIME_MASK('HOUR',{'HOUR','HOUR+15x','HOUR+30x','HOUR+45x'},{1,2,3,2},'MIN15')

Result time series = @TRANS_PROFILE(@t('Ts5'),Profile)

Note! This set up gives the same result as @DISTRIBUTE(@t('Ts5'),MaskSeries,Profile) where the mask series argument is true for all the time points.

Ra8

About the function

Same as R8, but with absolute handling of the profile. The profile can be scaled using a scaling factor, defined as first argument.

Syntax

• TRANS_PROFILE(d,t,t)

Description

#	Type	Description
1	d	Scaling factor. If the scaling factor is 0, relative profiling is used, i.e. the function behaves like R8.
2	t	Input time series to be converted.
3	t	Profile series stating how the values are distributed in each period connected to a value on the input data series. Gives the resolution of the result.

The distribution of the values is done like this:

K is a scaling factor coming from argument 1 in the function. The other symbols used in the formula are the same as described in R8.

Example 1

Profile = @TIME_MASK('HOUR',{'HOUR','HOUR+15x','HOUR+30x','HOUR+45x'},{1,2,3,2},'MIN15')

Result time series = @TRANS_PROFILE(1,@t('Ts5'),Profile)

Note! This set up gives the same result as @DISTRIBUTE(1,@t('Ts5'),MaskSeries,Profile) where the mask series argument is true for all the time points.

Example 2

Profile = @TIME_MASK('HOUR',{'HOUR','HOUR+15x','HOUR+30x','HOUR+45x'},{1,2,3,2},'MIN15')

Result time series = @TRANS_PROFILE(10,@t('Ts5'),Profile)

Note! This set up gives the same result as @DISTRIBUTE(10,@t('Ts5'),MaskSeries,Profile) where the mask series argument is true for all the time points.

R9

About the function

Same as the function R8, but with an extra argument deciding distribution method.

Syntax

• TRANS_PROFILE(t,t,s)

Description

#	TYPE	Description
1	t	Input time series to be converted.
2	t	Profile series stating how the values are distributed on each period connected to a value on the input data series. Gives the resolution on the result.
3	s	Valid distribution methods 'MEAN', 'AVERAGE' or 'SUM'. 'SUM' gives exactly the same result as R8.

Vi = Value calculated for the time point i in the result time series

AI = Value from the input time series for the distributed period

Pi = Profile value for the time point i in the result time series

MI = Calculated mean value for the profile series for the distributed period

If the value on the input data series is 0, the value is calculated like this:

Vi = Pi - MI

Ra9

About the function

Same as R9, but with absolute handling of the profile. The profile can be scaled using a scaling factor, defined in argument 1.

Syntax

• TRANS_PROFILE(d,t,t,s)

Description

#	Type	Description
1	d	Scaling factor. If the scaling factor is 0, relative profiling is used, i.e. the function behaves like R9.
2	t	Input time series to be converted.
3	t	Profile series stating how the values are distributed on each period connected to a value on the input data series. Gives the resolution on the result.
4	s	Valid distribution methods 'MEAN', 'AVERAGE' or 'SUM'. 'SUM' gives exactly the same result as Ra8.

The distribution of the values is done like this:

K is a scaling factor coming from argument 1 in the function. The other symbols used in the formula are the same as described in R9.

R10

About the function

Same as R8 but uses a mask series in argument 3.

Syntax

• TRANS_PROFILE(t,t,t)

Description

#	TYPE	Description
1	t	Input time series to be converted.
2	t	Profile series stating how the values are distributed on each period connected to a value on the input data series.
3	t	Mask series representing the distributed time interval. Defines the resolution of the result time series.

The distribution of the values is done like this:

Vi = Value calculated for the time point i in the result time series

AI = Value from the input time series for the distributed period

NI = Number of valid time point to distributed the input value into

Pi = Profile value for the time point i in the result time series

MI = Calculated mean value for the profile series for the distributed period

If the value on the input data series is 0, the value is calculated like this:

Vi= Pi- MI

See also R7 that offers the same functionality.

Ra10

About the function

Same as R10, but with absolute handling of profile. The profile can be scaled using a scaling factor defined in argument 1.

Syntax

• TRANS_PROFILE(d,t,t,t)

Description

#	Type	Description
1	d	Scaling factor. If the scaling factor is 0, relative profiling is used, i.e. the function behaves like R10.
2	t	Input time series to be converted.
3	t	Profile series stating how the values are distributed in each period connected to a value on the input data series.
4	t	Mask series representing the distributed time interval. Defines the resolution of the result time series.

The distribution of the values is done like this:

K is a scaling factor coming from argument 1 in the function. The other symbols used in the formula are the same as described in R10.

R11

About the function

Same function as R10, but with an extra argument deciding distribution method. Valid values are 'MEAN', 'AVERAGE' or 'SUM'. The last value gives the exact same result as R10.

Syntax

• TRANS_PROFILE(t,t,t,s)

Description

#	Type	Description
1	t	Input time series to be converted.
2	t	Profile series stating how the values are distributed on each period connected to a value on the input data series.
3	t	Mask series representing the distributed time interval. Defines the resolution of the result time series.
4	s	Valid distribution methods 'MEAN', 'AVERAGE' or 'SUM'. 'SUM' gives exactly the same result as R10.

When the method is mean/average value based, the values are calculated like this:

Vi = Value calculated for the time point i in the result time series

AI = Value from the input time series for the distributed period

Pi = Profile value for the time point i in the result time series

MI = Calculated mean value for the profile series for the distributed period

If the value on the input data series is 0, the value is calculated like this:

Vi = Pi - MI

Ra11

About the function

Same as R11, but with absolute handling of profile. The profile can be scaled using a scaling factor, defined in argument 1.

Syntax

• TRANS_PROFILE(d,t,t,t,s)

Description

#	Type	Description
1	d	Scaling factor. If the scaling factor is 0, relative profiling is used, i.e. the function behaves like R10.
2	t	Input time series to be converted.
3	t	Profile series stating how the values are distributed on each period connected to a value on the input data series.
4	t	Mask series representing the distributed time interval. Defines the resolution of the result time series.
5	s	Valid distribution methods 'MEAN', 'AVERAGE' or 'SUM'. 'SUM' gives exactly the same result as R10.

The distribution of the values is done like this:

K is a scaling factor coming from argument 1 in the function. The other symbols used in the formula are the same as described in R11.