Create timeseries object
Time series represent the time-evolution of a dynamic population or process. They are used to identify, model, and forecast patterns and behaviors in data that is sampled over discrete time intervals.
To create a timeseries object, use the
timeseries function with input arguments that describe the data
samples.
ts = timeseries(___,'Name',tsname)
specifies a name tsname for the
timeseries object.
ts = timeseries() returns an empty
timeseries object.
ts = timeseries( creates
an empty tsname)timeseries object with name
tsname.
datavals — Sample dataSample data, specified as a numeric or logical
scalar, vector, or multidimensional array.
Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical
timevals — Sample timesSample times, specified as a numeric scalar or vector, or a cell array of date character vectors. Valid date character vectors can have the following forms:
| Format | Example |
|---|---|
dd-mmm-yyyy
HH:MM:SS | 01-Mar-2000 15:45:17 |
dd-mmm-yyyy | 01-Mar-2000 |
mm/dd/yy | 03/01/00 |
mm/dd | 03/01 |
HH:MM:SS | 15:45:17 |
HH:MM:SS PM | 3:45:17 PM |
HH:MM | 15:45 |
HH:MM PM | 3:45 PM |
mmm.dd,yyyy
HH:MM:SS | Mar.01,2000 15:45:17 |
mmm.dd,yyyy | Mar.01,2000 |
mm/dd/yyyy | 03/01/2000 |
Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | cell
quality — Quality codes[] (default) | scalar | vector | multidimensional arrayQuality codes, specified as [] or a scalar, vector,
or multidimensional array of integers ranging from -128 to 127.
When the quality code value is a vector, it must have the same length as the time vector. Each element applies to the corresponding data sample.
When the quality code value is an array, it must have the same size as the data array. Each element applies to the corresponding element of the data array.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
tsname — timeseries nametimeseries name, specified as a character
vector.
Data — Sample dataSample data, represented as a numeric or logical
scalar, vector, or multidimensional array. Either the first or the last
dimension of the data must align with the orientation of the time
vector.
Data has the following attributes:
Dependent | true |
Data Types: double | single | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical
DataInfo — Data informationData information, represented as a collection of the following fields:
Units — Character vector specifying
data units.
Interpolation — A
tsdata.interpolation object that
specifies the interpolation method.
Fields of the tsdata.interpolation object
include the following:
Fhandle — Function handle to
a user-defined interpolation function.
Name — Character vector
specifying the name of the interpolation method. Methods
include 'linear' (default) for linear
interpolation and 'zoh' for
zero-order hold.
UserData — Additional user-defined
information entered as a character vector.
Events — Event informationtsdata.event objectsEvent information, represented as an array of
tsdata.event objects containing event
information.
Fields of the tsdata.event object include the
following:
EventData — Additional user-defined
information about the event.
Name — Character vector specifying the
name of the event
Time — Time for which the event occurs,
specified as a real number or a date character vector.
Units — Time units.
StartDate — A reference date specified
as a date character vector. StartDate is empty
when the time vector is numeric.
IsTimeFirst — Time vector alignmenttrue | falseTime vector alignment, represented as one of the following options:
true — The first dimension of the
data array is aligned with the time vector. For example,
ts = timeseries(rand(3,3),1:3);
false — The last dimension of the
data array is aligned with the time vector. For example,
ts = timeseries(rand(3,4,5),1:5);
IsTimeFirst has the following attributes:
Dependent | true |
SetAccess | 'protected' |
Length — Time vector lengthTime vector length, represented as a scalar.
Length has the following attributes:
Dependent | true |
SetAccess | 'protected' |
Name — timeseries nametimeseries name, represented as a character
vector.
Quality — Quality codes[] (default) | scalar | vector | multidimensional arrayQuality codes, represented as [] or a scalar, vector,
or multidimensional array of integers ranging from -128 to 127.
When the quality code value is a vector, it must have the same length as the time vector. Each element applies to the corresponding data sample.
When the quality code value is an array, it must have the same size as the data array. Each element applies to the corresponding element of the data array.
Quality has the following attributes:
Dependent | true |
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64
QualityInfo — Quality informationQuality information to describe Quality codes,
represented as a collection of the following fields:
Code — Integer vector containing
values -128 to 127 that
define the quality codes. You can assign one of these integer
values to each Data value by using the
Quality property.
Description — Cell array of
character vectors, where each element provides a readable
description of the associated quality
Code.
UserData — Additional user-defined
information.
The lengths of Code and Description
must match.
Time — Time valuesTime values, represented as a vector.
When TimeInfo.StartDate is empty, values are measured
relative to 0. When TimeInfo.StartDate
is defined, values represent date character vectors measured relative to the
StartDate.
The length of Time must be the same as the first or the
last dimension of Data.
Time has the following attributes:
Dependent | true |
TimeInfo — Time informationTime information, represented as a collection of the following fields describing the time vector:
Units — Time units with the value
'weeks', 'days',
'hours', 'minutes',
'seconds',
'milliseconds',
'microseconds', or
'nanoseconds'.
Start — Start time.
End — End time (read only).
Increment — Interval between
subsequent time values (NaN when times are
not uniformly sampled).
Length — Length of time vector (read
only).
Format — Character vector defining
the date display (see datestr).
StartDate — Date character vector
defining the reference date (see setabstime).
UserData — Additional user-defined
information.
To access the value of a field, use the form
ts.TimeInfo.field for a timeseries
object ts.
TreatNaNasMissing — Missing value indicatortrue (default) | falseMissing value indicator, represented as one of the following options:
true — Treat all
NaN values as missing data except for
descriptive statistics functions.
false — Include
NaN values in descriptive statistics
functions, propagating NaN to the
result.
UserData — User data[] (default)User data, represented as any additional data to add to the
timeseries object.
addevent | Add event to timeseries |
addsample | Add data sample to timeseries object |
append | Concatenate timeseries objects in time |
delevent | Remove event from timeseries |
delsample | Remove sample from timeseries object |
detrend | Subtract mean or best-fit line from timeseries
object |
filter | Modify frequency content of timeseries objects |
idealfilter | timeseries ideal filter |
plot | Plot timeseries |
resample | Resample timeseries time vector |
set | Set timeseries properties |
setabstime | Set timeseries times as date character vectors |
setinterpmethod | Set default interpolation method for timeseries
object |
setuniformtime | Modify uniform timeseries time vector |
synchronize | Synchronize and resample two timeseries objects using common
time vector |
get | Query timeseries properties |
getabstime | Convert timeseries time vector to cell array |
getdatasamples | Access timeseries data samples |
getdatasamplesize | timeseries data sample size |
getinterpmethod | timeseries interpolation method |
getqualitydesc | timeseries data quality |
getsamples | Subset of timeseries |
getsampleusingtime | Subset of timeseries data |
gettsafteratevent | Create timeseries at or after event |
gettsafterevent | Create timeseries after event |
gettsatevent | Create timeseries at event |
gettsbeforeatevent | Create timeseries at or before event |
gettsbeforeevent | Create timeseries before event |
gettsbetweenevents | Create timeseries between events |
timeseriesCreate a timeseries object with 5 scalar data samples, specifying a name for the timeseries.
ts1 = timeseries((1:5)','Name','MyTimeSeries');
Create a timeseries with 5 data samples, where each sample is a column vector of length 2.
ts2 = timeseries(rand(2,5));
Create a timeseries with 5 data samples that were sampled in intervals of 10 time units.
ts3 = timeseries((1:5)',[0 10 20 30 40]);
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