@@ -40,7 +46,8 @@
If you have ever used a traditional HP calculator you already know -RPN. The idea behind RPN is that you have a stack and push +RPN (Reverse Polish Notation). +The idea behind RPN is that you have a stack and push your data onto this stack. Whenever you execute an operation, it takes as many elements from the stack as needed. Pushing is done implicitly, so whenever you specify a number or a variable, it gets @@ -52,7 +59,7 @@ data point on the graph. VDEF instructions work on an entire da one run. Note, that currently VDEF instructions only support a limited list of functions.
Example: VDEF:maximum=mydata,MAXIMUM
This will set variable ``maximum'' which you now can use in the rest +
This will set variable "maximum" which you now can use in the rest of your RRD script.
Example: CDEF:mydatabits=mydata,8,*
This means: push variable mydata, push the number 8, execute
@@ -70,7 +77,7 @@ would do a = b, 3, +, 5, * without the need for parentheses.
LT, LE, GT, GE, EQ, NE
@@ -88,7 +95,7 @@ mean that any value other than 0 is considered to be true.Example: A,B,C,IF should be read as if (A) then (B) else (C)
MIN, MAX
@@ -108,7 +115,7 @@ will always return an unknown alpha is lower than 0 or if it is higher than 100.+, -, *, /, %
@@ -136,7 +143,7 @@ components into an angle in degrees.ABS
Take the absolute value.
SORT, REV
@@ -151,7 +158,7 @@ largest. average, ignoring all UNKNOWN values in the process.Example: CDEF:x=a,b,c,d,4,AVG
TREND, TRENDNAN
-Create a ``sliding window'' average of another data series.
+Create a "sliding window" average of another data series.
Usage: CDEF:smoothed=x,1800,TREND
This will create a half-hour (1800 second) sliding window average of x. The @@ -173,8 +180,69 @@ average is essentially computed as shown here:
source value is NAN the complete sliding window is affected. The TRENDNAN operation ignores all NAN-values in a sliding window and computes the average of the remaining values. +PREDICT, PREDICTSIGMA
+Create a "sliding window" average/sigma of another data series, that also +shifts the data series by given amounts of of time as well
+Usage - explicit stating shifts: +CDEF:predict=<shift n>,...,<shift 1>,n,<window>,x,PREDICT +CDEF:sigma=<shift n>,...,<shift 1>,n,<window>,x,PREDICTSIGMA
+Usage - shifts defined as a base shift and a number of time this is applied +CDEF:predict=<shift multiplier>,-n,<window>,x,PREDICT +CDEF:sigma=<shift multiplier>,-n,<window>,x,PREDICTSIGMA
+Example: +CDEF:predict=172800,86400,2,1800,x,PREDICT
+This will create a half-hour (1800 second) sliding window average/sigma of x, that +average is essentially computed as shown here:
++ +---!---!---!---!---!---!---!---!---!---!---!---!---!---!---!---!---!---> + now + shift 1 t0 + <-----------------------> + window + <---------------> + shift 2 + <-----------------------------------------------> + window + <---------------> + shift 1 t1 + <-----------------------> + window + <---------------> + shift 2 + <-----------------------------------------------> + window + <--------------->+
+ Value at sample (t0) will be the average between (t0-shift1-window) and (t0-shift1) + and between (t0-shift2-window) and (t0-shift2) + Value at sample (t1) will be the average between (t1-shift1-window) and (t1-shift1) + and between (t1-shift2-window) and (t1-shift2)+
The function is by design NAN-safe. +This also allows for extrapolation into the future (say a few days) +- you may need to define the data series whit the optional start= parameter, so that +the source data series has enough data to provide prediction also at the beginning of a graph...
+Here an example, that will create a 10 day graph that also shows the +prediction 3 days into the future with its uncertainty value (as defined by avg+-4*sigma) +This also shows if the prediction is exceeded at a certain point.
+rrdtool graph image.png --imgformat=PNG \ + --start=-7days --end=+3days --width=1000 --height=200 --alt-autoscale-max \ + DEF:value=value.rrd:value:AVERAGE:start=-14days \ + LINE1:value#ff0000:value \ + CDEF:predict=86400,-7,1800,value,PREDICT \ + CDEF:sigma=86400,-7,1800,value,PREDICTSIGMA \ + CDEF:upper=predict,sigma,3,*,+ \ + CDEF:lower=predict,sigma,3,*,- \ + LINE1:predict#00ff00:prediction \ + LINE1:upper#0000ff:upper\ certainty\ limit \ + LINE1:lower#0000ff:lower\ certainty\ limit \ + CDEF:exceeds=value,UN,0,value,lower,upper,LIMIT,UN,IF \ + TICK:exceeds#aa000080:1
+Note: Experience has shown that a factor between 3 and 5 to scale sigma is a good +discriminator to detect abnormal behaviour. This obviously depends also on the type +of data and how "noisy" the data series is.
+This prediction can only be used for short term extrapolations - say a few days into the future-
UNKN
@@ -199,7 +267,7 @@ number 2 if it is the second, and so on. This special value allows you to make calculations based on the position of the value within the data set. This function cannot be used in VDEF instructions.Time inside RRDtool is measured in seconds since the epoch. The @@ -214,7 +282,7 @@ valid at that time including daylight saving time if your OS supports it, and pushes the result on the stack. There is an elaborate example in the examples section below on how to use this.
DUP, POP, EXC
@@ -229,20 +297,20 @@ top elements.These operators work only on VDEF statements. Note that currently ONLY these work for VDEF.
Return the corresponding value, MAXIMUM and MINIMUM also return the first occurrence of that value in the time component.
Example: VDEF:avg=mydata,AVERAGE
Returns the standard deviation of the values.
Example: VDEF:stdev=mydata,STDEV
Return the last/first value including its time. The time for @@ -250,7 +318,7 @@ FIRST is actually the start of the corresponding interval, whereas LAST returns the end of the corresponding interval.
Example: VDEF:first=mydata,FIRST
Returns the rate from each defined time slot multiplied with the @@ -259,21 +327,23 @@ when you have logged bytes per second. The time component returns the number of seconds.
Example: VDEF:total=mydata,TOTAL
This should follow a DEF or CDEF vname. The vname is popped, another number is popped which is a certain percentage (0..100). The data set is then sorted and the value returned is chosen such that percentage percent of the values is lower or equal than the result. +For PERCENTNAN Unknown values are ignored, but for PERCENT Unknown values are considered lower than any finite number for this purpose so if this operator returns an unknown you have quite a lot of them in your data. Infinite numbers are lesser, or more, than the finite numbers and are always more than the Unknown numbers. (NaN < -INF < finite values < INF)
-Example: VDEF:perc95=mydata,95,PERCENT
Example: VDEF:perc95=mydata,95,PERCENT
+ VDEF:percnan95=mydata,95,PERCENTNAN
Return the parameters for a Least Squares Line (y = mx +b) @@ -300,7 +370,8 @@ and represents the quality of fit for the approximation.
Program by Tobias Oetiker <tobi@oetiker.ch>
-This manual page by Alex van den Bogaerdt <alex@ergens.op.het.net>
+This manual page by Alex van den Bogaerdt <alex@vandenbogaerdt.nl> +with corrections and/or additions by several people