Commit 35685750 authored by Uwe Schulzweida's avatar Uwe Schulzweida
Browse files

ECA: docu update

parent 2741a297
......@@ -10,7 +10,7 @@
@BeginDescription
This module performs simple arithmetic of two datasets.
The number of fields in @file{ifile1} should be the same as in @file{ifile2}.
One of the input files can contain only one time step or one field.
One of the input files can contain only one timestep or one field.
The fields in @file{ofile} inherit the meta data from @file{ifile1} or @file{ifile2}.
@EndDescription
@EndModule
......
......@@ -8,7 +8,7 @@
@Operators = muldpm divdpm muldpy divdpy
@BeginDescription
This module multiplies or divides each time step of a dataset with the corresponding
This module multiplies or divides each timestep of a dataset with the corresponding
days per month or days per year. The result of these functions depends on the used
calendar of the input data.
@EndDescription
......
......@@ -11,7 +11,7 @@
This module compares two datasets field by field. The resulting
field is a mask containing 1 if the comparison is true and 0 if not.
The number of fields in @file{ifile1} should be the same as in @file{ifile2}.
One of the input files can contain only one time step or one field.
One of the input files can contain only one timestep or one field.
The fields in @file{ofile} inherit the meta data from @file{ifile1} or @file{ifile2}.
The type of comparison depends on the chosen operator.
@EndDescription
......
......@@ -11,7 +11,7 @@ This module selects field elements from @file{ifile2} with respect to @file{ifil
to @file{ofile}. The fields in @file{ifile1} are handled as a mask. A value
not equal to zero is treated as "true", zero is treated as "false".
The number of fields in @file{ifile1} has either to be the same as in @file{ifile2} or the
same as in one time step of @file{ifile2} or only one.
same as in one timestep of @file{ifile2} or only one.
The fields in @file{ofile} inherit the meta data from @file{ifile2}.
@EndDescription
@EndModule
......
......@@ -10,7 +10,7 @@ This operator selects field elements from @file{ifile2} or @file{ifile3} with re
@file{ifile1} and writes them to @file{ofile}. The fields in @file{ifile1} are handled as a mask.
A value not equal to zero is treated as "true", zero is treated as "false".
The number of fields in @file{ifile1} has either to be the same as in @file{ifile2} or the
same as in one time step of @file{ifile2} or only one.
same as in one timestep of @file{ifile2} or only one.
@file{ifile2} and @file{ifile3} need to have the same number of fields.
The fields in @file{ofile} inherit the meta data from @file{ifile2}.
@EndDescription
......
......@@ -8,7 +8,7 @@
@Operators = consecsum consects
@BeginDescription
This module computes periods over all time steps in @file{ifile} where a
This module computes periods over all timesteps in @file{ifile} where a
certain property is valid. The propery can be chosen by creating a mask from
the original data, which is the expected input format for operators of this
module. Depending on the operator full information about each period or
......
......@@ -10,7 +10,7 @@
@BeginDescription
This module contains operators to copy or concatenate datasets.
@file{ifiles} is an unlimited number of input files. All input files need to have
the same structure with the same variables on different time steps.
the same structure with the same variables on different timesteps.
@EndDescription
@EndModule
......@@ -43,12 +43,12 @@ as is required for proper recognition by GrADS or Ferret:
@BeginVerbatim
cdo -r -f nc copy ifile ofile.nc
@EndVerbatim
To concatenate 3 datasets with different time steps of the same variables use:
To concatenate 3 datasets with different timesteps of the same variables use:
@BeginVerbatim
cdo copy ifile1 ifile2 ifile3 ofile
@EndVerbatim
If the output dataset already exists and you wish to extend it
with more time steps use:
with more timesteps use:
@BeginVerbatim
cdo cat ifile1 ifile2 ifile3 ofile
@EndVerbatim
......
......@@ -8,15 +8,15 @@
@Operators = daypctl
@BeginDescription
This operator computes percentiles over all time steps of the same day in @file{ifile1}.
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 date information of a time step in @file{ofile} is the date of the
last contributing time step in @file{ifile1}.
The date information of a timestep in @file{ofile} is the date of the
last contributing timestep in @file{ifile1}.
@EndDescription
@EndModule
......@@ -27,13 +27,13 @@ last contributing time step in @file{ifile1}.
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
\vspace*{1mm}
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
\vspace*{1mm}
@BeginMath
......
......@@ -8,11 +8,11 @@
@Operators = daymin daymax daysum daymean dayavg dayvar daystd
@BeginDescription
This module computes statistical values over time steps of the same day.
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 time steps of the same day is written to @file{ofile}.
The date information of a time step in @file{ofile} is the date of the last
contributing time step in @file{ifile}.
or standard deviation of timesteps of the same day is written to @file{ofile}.
The date information of a timestep in @file{ofile} is the date of the last
contributing timestep in @file{ifile}.
@EndDescription
@EndModule
......@@ -22,12 +22,12 @@ contributing time step in @file{ifile}.
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf min}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -41,12 +41,12 @@ o(t,x) = \mbox{\bf min}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf max}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -60,12 +60,12 @@ o(t,x) = \mbox{\bf max}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf sum}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -79,12 +79,12 @@ o(t,x) = \mbox{\bf sum}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf mean}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -98,12 +98,12 @@ o(t,x) = \mbox{\bf mean}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf avg}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -117,12 +117,12 @@ o(t,x) = \mbox{\bf avg}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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) = var{i(t',x), t_1<t'<=t_n}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf var}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......@@ -136,12 +136,12 @@ o(t,x) = \mbox{\bf var}\{i(t',x), t_1 < t' \leq t_n\}
@BeginDescription
@IfMan
For every adjacent sequence t_1, ...,t_n of time steps 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) = std{i(t',x), t_1<t'<=t_n}
@EndifMan
@IfDoc
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of time steps of the same day it is: \\
For every adjacent sequence \begin{math}t_1, ...,t_n\end{math} of timesteps of the same day it is: \\
@BeginMath
o(t,x) = \mbox{\bf std}\{i(t',x), t_1 < t' \leq t_n\}
@EndMath
......
......@@ -14,11 +14,11 @@
@BeginDescription
@IfMan
Every time series in @file{ifile} is linearly detrended. For every field element x
only those time steps t belong to the sample S(x), which have i(t,x) NE miss.
only those timesteps t belong to the sample S(x), which have i(t,x) NE miss.
@EndifMan
@IfDoc
Every time series in @file{ifile} is linearly detrended.
For every field element \begin{math}x\end{math} only those time steps \begin{math}t\end{math} belong to the sample
For every field element \begin{math}x\end{math} only those timesteps \begin{math}t\end{math} belong to the sample
\begin{math}S(x)\end{math}, which have \begin{math}i(t,x) \neq \mbox{miss}\end{math}.
With
@BeginDisplayMath
......@@ -40,7 +40,7 @@ o(t,x) = i(t,x) - (a(x) + b(x)t)
@BeginNote
This operator has to keep the fields of all time steps concurrently in the memory.
This operator has to keep the fields of all timesteps concurrently in the memory.
If not enough memory is available use the operators @mod{trend} and @mod{subtrend}.
@EndNote
......
......@@ -57,7 +57,7 @@ To print the difference for each field of two datasets use:
@BeginVerbatim
cdo diffn ifile1 ifile2
@EndVerbatim
This is an example result of two datasets with one 2D parameter over 12 time steps:
This is an example result of two datasets with one 2D parameter over 12 timesteps:
@BeginListing
Date Time Name Level Size Miss : S Z Max_Absdiff Max_Reldiff
1 : 1987-01-31 12:00:00 SST 0 2048 1361 : F F 0.00010681 4.1660e-07
......
......@@ -18,7 +18,7 @@ If operator @mod{eof} is chosen, the EOFs are computed in either time or spatial
space, whichever is the fastest. If the user already knows, which computation
is faster, the module can be forced to perform a computation in time- or gridspace
by using the operators @mod{eoftime} or @mod{eofspatial}, respectively. This can enhance
performance, especially for very long time series, where the number of time steps
performance, especially for very long time series, where the number of timesteps
is larger than the number of grid-points. Data in @file{ifile} are assumed to be anomalies.
If they are not, the behavior of this module is @bold{not well defined}.
After execution @file{ofile1} will contain all eigen-values and @file{ofile2} the
......
......@@ -8,11 +8,11 @@
@Operators = eca_cdd
@BeginDescription
Let @file{ifile} be a time series of daily precipitation amounts @math{RR}, then counted is the
largest number of consecutive days where @math{RR} is less than @math{R}. @math{R} is an optional parameter with
Let @file{ifile} be a time series of daily precipitation amounts @math{RR}, then the largest number
of consecutive days where @math{RR} is less than @math{R} is counted. @math{R} is an optional parameter with
default @math{R = 1 mm}. A further output variable is the number of dry periods of more than 5 days.
The date information of a time step in @file{ofile} is the date of the last contributing
time step in @file{ifile}.
The date information of a timestep in @file{ofile} is the date of the last contributing
timestep in @file{ifile}.
@EndDescription
@EndModule
......
......@@ -8,10 +8,10 @@
@BeginDescription
Let @file{ifile} be a time series of daily minimum temperatures TN,
then counted is the largest number of consecutive days where
TN < 0 @celsius. Note that TN have to be given in units of Kelvin.
The date information of a time step in @file{ofile} is the date of
the last contributing time step in @file{ifile}.
then the largest number of consecutive days whereTN < 0 @celsius
is counted. Note that TN have to be given in units of Kelvin.
The date information of a timestep in @file{ofile} is the date of
the last contributing timestep in @file{ifile}.
@EndDescription
@EndModule
......
......@@ -9,12 +9,12 @@
@BeginDescription
Let @file{ifile} be a time series of daily maximum temperatures TX,
then counted is the largest number of consecutive days where TX > T.
then the largest number of consecutive days where TX > T is counted.
The number T is an optional parameter with default T = 25 @celsius.
Note that TN have to be given in units of Kelvin, whereas T have to be given
in degrees Celsius.
The date information of a time step in @file{ofile} is the date of
the last contributing time step in @file{ifile}.
The date information of a timestep in @file{ofile} is the date of
the last contributing timestep in @file{ifile}.
@EndDescription
@EndModule
......
......@@ -7,11 +7,11 @@
@Operators = eca_cwd
@BeginDescription
Let @file{ifile} be a time series of daily precipitation amounts @math{RR}, then counted is the
largest number of consecutive days where @math{RR} is at least @math{R}. @math{R} is an optional parameter with
Let @file{ifile} be a time series of daily precipitation amounts @math{RR}, then the largest number
of consecutive days where @math{RR} is at least @math{R} is counted. @math{R} is an optional parameter with
default @math{R = 1 mm}. A further output variable is the number of wet periods of more than 5 days.
The date information of a time step in @file{ofile} is the date of the last contributing
time step in @file{ifile}.
The date information of a timestep in @file{ofile} is the date of the last contributing
timestep in @file{ifile}.
@EndDescription
@EndModule
......
......@@ -18,8 +18,8 @@ waves longer than or equal to nday days.
TNnorm is calculated as the mean of minimum temperatures of a five day
window centred on each calendar day of a given climate reference period.
Note that both TN and TNnorm have to be given in the same units.
The date information of a time step in @file{ofile} is the date of
the last contributing time step in @file{ifile1}.
The date information of a timestep in @file{ofile} is the date of
the last contributing timestep in @file{ifile1}.
@EndDescription
@EndModule
......
......@@ -17,8 +17,8 @@ equal to nday days.
TGn10 is calculated as the 10th percentile of daily mean temperatures of a five
day window centred on each calendar day of a given climate reference period.
Note that both TG and TGn10 have to be given in the same units.
The date information of a time step in @file{ofile} is the date of
the last contributing time step in @file{ifile1}.
The date information of a timestep in @file{ofile} is the date of
the last contributing timestep in @file{ifile1}.
@EndDescription
@EndModule
......
......@@ -12,8 +12,8 @@ Let @file{ifile1} and @file{ifile2} be time series of maximum and minimum
temperatures TX and TN, respectively. Then the extreme temperature
range is the difference of the maximum of TX and the minimum of TN.
Note that TX and TN have to be given in the same units.
The date information of a time step in @file{ofile} is the date of
the last contributing time steps in @file{ifile1} and @file{ifile2}.
The date information of a timestep in @file{ofile} is the date of
the last contributing timesteps in @file{ifile1} and @file{ifile2}.
@EndDescription
@EndModule
......
......@@ -8,10 +8,10 @@
@BeginDescription
Let @file{ifile} be a time series of daily minimum temperatures TN,
then counted is the number of days where TN < 0 @celsius. Note
then the number of days where TN < 0 @celsius is counted. Note
that TN have to be given in units of Kelvin.
The date information of a time step in @file{ofile} is the date of
the last contributing time step in @file{ifile}.
The date information of a timestep in @file{ofile} is the date of
the last contributing timestep in @file{ifile}.
@EndDescription
@EndModule
......
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