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TemporalRegularity

is an option for TimeSeries, EventSeries and TemporalData that controls whether the paths are assumed to be uniformly spaced in time.

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Examples  
Basic Examples  
Scope  
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TemporalRegularity

TemporalRegularity

is an option for TimeSeries, EventSeries and TemporalData that controls whether the paths are assumed to be uniformly spaced in time.

Details

  • Possible settings include:
  • Automaticautomatically detect regularity (default)
    Trueexplicitly assume regularity
    Falseexplicitly assume irregularity
  • Setting TemporalRegularityTrue will make the series be treated as regular even if the timestamps are not equally spaced.

Examples

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Basic Examples  (2)

By default, regularity is determined from the data:

Wolfram Language code: t = {0, 2.5, 3, 4, 5.5};
Wolfram Language code: TemporalData[Range[5], {t}]//RegularlySampledQ

Explicitly assume regularity:

Wolfram Language code: TemporalData[Range[5], {t}, TemporalRegularity -> True]//RegularlySampledQ

Construct a time series for business days:

Wolfram Language code: dates = DayRange[{2026, 1, 1}, {2026, 1, 10}, "BusinessDay"] values = Range[Length[dates]]

By default, TimeSeries does not detect the regularity in the list of business days:

Wolfram Language code: TimeSeries[values, {dates}]//RegularlySampledQ

Force the time series to be regular in those dates:

Wolfram Language code: TimeSeries[values, {dates}, TemporalRegularity -> True]//RegularlySampledQ

Scope  (1)

Take lists of dates and values of the same length:

Wolfram Language code: dates = DayRange[{2024, 1, 1}, {2025, 12, 31}, "BusinessDay"]; values = Accumulate@RandomReal[{-1, 1}, Length[dates]];

By default, TimeSeries does not check for date regularity of any special day type:

Wolfram Language code: ts1 = TimeSeries[values, {dates}];
Wolfram Language code: RegularlySampledQ[ts1]

The iterator notation {tmin,tmax,dt} allows setting regularity for nontrivial day types:

Wolfram Language code: ts2 = TimeSeries[values, {{2024, 1, 1}, {2025, 12, 31}, "BusinessDay"}];
Wolfram Language code: RegularlySampledQ[ts2]

Use the TemporalRegularity option to force regularity in a time series:

Wolfram Language code: ts3 = TimeSeries[values, {dates}, TemporalRegularity -> True];
Wolfram Language code: RegularlySampledQ[ts3]

All three time series contain the same data:

Wolfram Language code: Normal[ts1] === Normal[ts2] === Normal[ts3]
Wolfram Research (2014), TemporalRegularity, Wolfram Language function, https://reference.wolfram.com/language/ref/TemporalRegularity.html.

Text

Wolfram Research (2014), TemporalRegularity, Wolfram Language function, https://reference.wolfram.com/language/ref/TemporalRegularity.html.

CMS

Wolfram Language. 2014. "TemporalRegularity." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/TemporalRegularity.html.

APA

Wolfram Language. (2014). TemporalRegularity. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/TemporalRegularity.html

BibTeX

@misc{reference.wolfram_2026_temporalregularity, author="Wolfram Research", title="{TemporalRegularity}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/TemporalRegularity.html}", note=[Accessed: 15-June-2026]}

BibLaTeX

@online{reference.wolfram_2026_temporalregularity, organization={Wolfram Research}, title={TemporalRegularity}, year={2014}, url={https://reference.wolfram.com/language/ref/TemporalRegularity.html}, note=[Accessed: 15-June-2026]}