Commit 9def0152 authored by Uwe Schulzweida's avatar Uwe Schulzweida
Browse files

Docu update.

parent 63cc98bd
......@@ -9,13 +9,12 @@
@BeginDescription
This operator computes percentiles over all timesteps of the same day in @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in
@file{ifile2} and @file{ifile3}, respectively. The default number of
histogram bins is 101. The default can be overridden by defining the
environment variable @env{CDO_PCTL_NBINS}. The files @file{ifile2} and
@file{ifile3} should be the result of corresponding @mod{daymin} and @mod{daymax}
operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in @file{ifile2} and
@file{ifile3}, respectively. The default number of histogram bins is 101.
The default can be overridden by defining the environment variable @env{CDO_PCTL_NBINS}.
The files @file{ifile2} and @file{ifile3} should be the result of corresponding @mod{daymin}
and @mod{daymax} operations, respectively.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
@EndDescription
@EndModule
......@@ -26,7 +25,7 @@ The time stamp in @file{ofile} is from the middle contributing timestep of @file
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = pth percentile {i(t',x), t_1<t'<=t_n}
@EndifMan
......
......@@ -11,7 +11,7 @@
This module computes statistical values over timesteps of the same day.
Depending on the chosen operator the minimum, maximum, sum, average, variance
or standard deviation of timesteps of the same day is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......@@ -21,7 +21,7 @@ The time stamp in @file{ofile} is from the middle contributing timestep of @file
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = min{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -40,7 +40,7 @@ o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = max{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -59,7 +59,7 @@ o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = sum{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -78,7 +78,7 @@ o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = mean{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -97,7 +97,7 @@ o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = avg{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -116,7 +116,7 @@ o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = var{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -135,7 +135,7 @@ o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = var1{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -154,7 +154,7 @@ o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = std{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -173,7 +173,7 @@ o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = std1{i(t',x), t_1<t'<=t_n}
@EndifMan
......
......@@ -30,8 +30,8 @@ the number of observations being larger than all ensembles.
ensrkhistspace computes a ranked histogram at each timestep reducing each
horizontal grid to a 1x1 grid and keeping the time axis as in @file{obsfile}.
Contrary ensrkhistspace computes a histogram at each grid point keeping the
horizontal grid for each variable and reducing the time-axis. The time infor-
mation is that from the last timestep in @file{obsfile}.
horizontal grid for each variable and reducing the time-axis. The time information
is that from the last timestep in @file{obsfile}.
@EndDescription
@EndModule
......
......@@ -9,13 +9,12 @@
@BeginDescription
This operator computes percentiles over all timesteps of the same hour in @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in
@file{ifile2} and @file{ifile3}, respectively. The default number of
histogram bins is 101. The default can be overridden by setting the
environment variable @env{CDO_PCTL_NBINS} to a different value. The files
@file{ifile2} and @file{ifile3} should be the result of corresponding
@mod{hourmin} and @mod{hourmax} operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in @file{ifile2} and
@file{ifile3}, respectively. The default number of histogram bins is 101.
The default can be overridden by defining the environment variable @env{CDO_PCTL_NBINS}.
The files @file{ifile2} and @file{ifile3} should be the result of corresponding @mod{hourmin}
and @mod{hourmax} operations, respectively.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
@EndDescription
@EndModule
......
......@@ -11,7 +11,7 @@
This module computes statistical values over timesteps of the same hour.
Depending on the chosen operator the minimum, maximum, sum, average, variance
or standard deviation of timesteps of the same hour is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......
......@@ -9,13 +9,12 @@
@BeginDescription
This operator computes percentiles over all timesteps of the same month in @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in
@file{ifile2} and @file{ifile3}, respectively. The default number of
histogram bins is 101. The default can be overridden by setting the
environment variable @env{CDO_PCTL_NBINS} to a different value. The files
@file{ifile2} and @file{ifile3} should be the result of corresponding
@mod{monmin} and @mod{monmax} operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
The algorithm uses histograms with minimum and maximum bounds given in @file{ifile2} and
@file{ifile3}, respectively. The default number of histogram bins is 101.
The default can be overridden by defining the environment variable @env{CDO_PCTL_NBINS}.
The files @file{ifile2} and @file{ifile3} should be the result of corresponding @mod{monmin}
and @mod{monmax} operations, respectively.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
@EndDescription
@EndModule
......
......@@ -11,7 +11,7 @@
This module computes statistical values over timesteps of the same month.
Depending on the chosen operator the minimum, maximum, sum, average, variance
or standard deviation of timesteps of the same month is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......@@ -40,7 +40,7 @@ o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = max{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -59,7 +59,7 @@ o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = sum{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -78,7 +78,7 @@ o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = mean{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -97,7 +97,7 @@ o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = avg{i(t',x), t_1<t'<=t_n}
@EndifMan
......@@ -116,7 +116,7 @@ o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = var{i(t',x), t_1 < t' <= t_n}
@EndifMan
......@@ -135,7 +135,7 @@ o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = var1{i(t',x), t_1 < t' <= t_n}
@EndifMan
......@@ -154,7 +154,7 @@ o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = std{i(t',x), t_1 < t' <= t_n}
@EndifMan
......@@ -173,7 +173,7 @@ o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same month it is:
o(t,x) = std1{i(t',x), t_1 < t' <= t_n}
@EndifMan
......
......@@ -8,7 +8,7 @@
@BeginDescription
This module computes running percentiles over a selected number of timesteps in @file{ifile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......
......@@ -11,7 +11,7 @@
This module computes running statistical values over a selected number of timesteps. Depending on
the chosen operator the minimum, maximum, sum, average, variance or standard deviation of a selected
number of consecutive timesteps read from @file{ifile} is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......
......@@ -10,10 +10,10 @@
@BeginDescription
This operator computes percentiles over all timesteps in @file{ifile1} of the same season.
The algorithm uses histograms with minimum and maximum bounds given in @file{ifile2} and @file{ifile3},
respectively. The default number of histogram bins is 101. The default can be overridden by setting
the environment variable @env{CDO_PCTL_NBINS} to a different value. The files @file{ifile2} and
@file{ifile3} should be the result of corresponding @mod{seasmin} and @mod{seasmax} operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
respectively. The default number of histogram bins is 101. The default can be overridden
by defining the environment variable @env{CDO_PCTL_NBINS}. The files @file{ifile2} and @file{ifile3}
should be the result of corresponding @mod{seasmin} and @mod{seasmax} operations, respectively.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
Be careful about the first and the last output timestep, they may be incorrect values
if the seasons have incomplete timesteps.
@EndDescription
......@@ -26,14 +26,13 @@ if the seasons have incomplete timesteps.
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = pth percentile {i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
\vspace*{1mm}
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
\vspace*{1mm}
@BeginMath
......
......@@ -11,7 +11,7 @@
This module computes statistical values over timesteps of the same season.
Depending on the chosen operator the minimum, maximum, sum, average, variance
or standard deviation of timesteps of the same season is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
Be careful about the first and the last output timestep, they may be incorrect values
if the seasons have incomplete timesteps.
@EndDescription
......@@ -23,13 +23,12 @@ if the seasons have incomplete timesteps.
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = min{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -43,13 +42,12 @@ o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = max{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -63,13 +61,12 @@ o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = sum{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -83,13 +80,12 @@ o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = mean{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -103,13 +99,12 @@ o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = avg{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -123,13 +118,12 @@ o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = var{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -143,13 +137,12 @@ o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = var1{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -163,13 +156,12 @@ o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = std{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -183,13 +175,12 @@ o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same season it is:
o(t,x) = std1{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of
the same season it is: \\
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same season it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{std1}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......
......@@ -10,10 +10,10 @@
@BeginDescription
This operator computes percentiles over all timesteps in @file{ifile1}. The algorithm uses
histograms with minimum and maximum bounds given in @file{ifile2} and @file{ifile3}, respectively.
The default number of histogram bins is 101. The default can be overridden by setting the
environment variable @env{CDO_PCTL_NBINS} to a different value. The files @file{ifile2} and @file{ifile3}
should be the result of corresponding @mod{timmin} and @mod{timmax} operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
The default number of histogram bins is 101. The default can be overridden by defining the
environment variable @env{CDO_PCTL_NBINS}. The files @file{ifile2} and @file{ifile3} should be
the result of corresponding @mod{timmin} and @mod{timmax} operations, respectively.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
@EndDescription
@EndModule
......
......@@ -12,7 +12,7 @@ The algorithm uses histograms with minimum and maximum bounds given in @file{ifi
respectively. The default number of histogram bins is 101. The default can be overridden by setting the
environment variable @env{CDO_PCTL_NBINS} to a different value. The files @file{ifile2} and @file{ifile3}
should be the result of corresponding @mod{timselmin} and @mod{timselmax} operations, respectively.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile1}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile1}.
@EndDescription
@EndModule
......@@ -23,15 +23,13 @@ The time stamp in @file{ofile} is from the middle contributing timestep of @file
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = pth percentile {i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
\vspace*{1mm}
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
\vspace*{1mm}
@BeginMath
......
......@@ -11,7 +11,7 @@
This module computes statistical values for a selected number of timesteps. According to
the chosen operator the minimum, maximum, sum, average, variance or standard deviation of
the selected timesteps is written to @file{ofile}.
The time stamp in @file{ofile} is from the middle contributing timestep of @file{ifile}.
The time of @file{ofile} is determined by the time in the middle of all contributing timesteps of @file{ifile}.
@EndDescription
@EndModule
......@@ -22,14 +22,12 @@ The time stamp in @file{ofile} is from the middle contributing timestep of @file
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = min{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -44,14 +42,12 @@ o(t,x) = \mbox{\textbf{min}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = max{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -66,14 +62,12 @@ o(t,x) = \mbox{\textbf{max}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = sum{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -88,14 +82,12 @@ o(t,x) = \mbox{\textbf{sum}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = mean{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -110,14 +102,12 @@ o(t,x) = \mbox{\textbf{mean}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = avg{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -132,14 +122,12 @@ o(t,x) = \mbox{\textbf{avg}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
Normalize by n. For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = var{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -154,14 +142,12 @@ o(t,x) = \mbox{\textbf{var}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
Normalize by (n-1). For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = var1{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -176,14 +162,12 @@ o(t,x) = \mbox{\textbf{var1}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by n. For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
Normalize by n. For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = std{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
Normalize by n. For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......@@ -198,14 +182,12 @@ o(t,x) = \mbox{\textbf{std}}\{i(t',x), t_1 < t' \le t_n\}
@BeginDescription
@IfMan
Normalize by (n-1). For every adjacent sequence t1, ...., tn of timesteps of the same
selected time range it is
Normalize by (n-1). For every adjacent sequence t1, ...., tn of timesteps of the same selected time range it is:
o(t,x) = std1{i(t',x), t1 < t' <= tn}
@EndifMan
@IfDoc
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same
selected time range it is: \\
Normalize by (n-1). For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same selected time range it is: \\
@BeginMath
o(t,x) = \mbox{\textbf{std1}}\{i(t',x), t_1 < t' \le t_n\}
@EndMath
......
......@@ -11,7 +11,7 @@
This module computes statistical values over all timesteps in @file{ifile}. Depending on
the chosen operator the minimum, maximum, sum, average, variance or standard deviation of
all timesteps read from @file{ifile} is written to @file{ofile}.