Methods
(static) exports.changeAbsolute_n_days(featureCollection, targetDate, numberOfDays) → {Map.<string, number>}
computes the new indicator for an absolute change compared to number of previous days internally tests are run, e.g. if a previous day is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfDays |
number | the number of days to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose absolute changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeAbsolute_n_months(featureCollection, targetDate, numberOfMonths) → {Map.<string, number>}
computes the new indicator for an absolute change compared to number of previous months internally tests are run, e.g. if a previous month is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfMonths |
number | the number of months to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose absolute changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeAbsolute_n_years(featureCollection, targetDate, numberOfYears) → {Map.<string, number>}
computes the new indicator for an absolute change compared to number of previous years internally tests are run, e.g. if a previous year is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfYears |
number | the number of years to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose absolute changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeAbsolute_referenceDate(featureCollection, targetDate, referenceDate) → {Map.<string, number>}
computes the new indicator for an absolute change compared to a previous reference date (e.g. prior year or month or day) internally tests are run, e.g. if a previous reference date is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the target date in the string format |
referenceDate |
string | the reference date in the past in the string format |
Returns:
returns the map of all input features that have both timestamps and whose absolute changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeRelative_n_days_percent(featureCollection, targetDate, numberOfDay) → {Map.<string, number>}
computes the new indicator for a relative change in percent compared to number of previous days
internally tests are run, e.g. if a previous day is available or not
if the indicator value for compareDate is '0' then the resulting value will be st as NoData value ('null')
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfDay |
number | the number of days to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose relative changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeRelative_n_months_percent(featureCollection, targetDate, numberOfMonth) → {Map.<string, number>}
computes the new indicator for a relative change in percent compared to number of previous months
internally tests are run, e.g. if a previous month is available or not
if the indicator value for compareDate is '0' then the resulting value will be st as NoData value ('null')
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfMonth |
number | the number of months to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose relative changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeRelative_n_years_percent(featureCollection, targetDate, numberOfYears) → {Map.<string, number>}
computes the new indicator for a relative change in percent compared to number of previous years
internally tests are run, e.g. if a previous year is available or not
if the indicator value for compareDate is '0' then the resulting value will be st as NoData value ('null')
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfYears |
number | the number of years to subtract from the submitted reference date |
Returns:
returns the map of all input features that have both timestamps and whose relative changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.changeRelative_referenceDate_percent(featureCollection, targetDate, referenceDate) → {Map.<string, number>}
computes the new indicator for a relative change in percent compared to a previous reference date (e.g. prior year or month or day) internally tests are run, e.g. if a previous reference date is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the target date in the string format |
referenceDate |
string | the reference date in the past in the string format |
Returns:
returns the map of all input features that have both timestamps and whose relative changeValues in percent were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.computeContinuity(feature, dates) → {number}
Computes the continuity value for the feature considering the submitted array of consecutive dates
Parameters:
| Name | Type | Description |
|---|---|---|
feature |
Feature | a valid GeoJSON Feature, that must contain a |
dates |
Array.<string> | array of dates for which the continuity value shall be computed as string of format |
Returns:
returns the continuity value of the feature considering the concrete consecutive years of dates array. or null if any date of dates array is not included within feature
- Type
- number
(static) exports.computeLinearRegressionSlope(indicatorValueArray, yearsArray) → {number}
Computes the linear regression slope from an indicator value array and a temporal array of consecutive years; both arrays must have the same element length
Parameters:
| Name | Type | Description |
|---|---|---|
indicatorValueArray |
Array.<number> | numeric indicator value array representing the time-series in increasing order |
yearsArray |
Array.<number> | numeric value array containing consecutive years in increasing order, i.e. [2015,2016,2017,2018,2019] |
Returns:
returns the pearson correlation of the two input arrays or null if the input arrays do not have the same length or contain non-numeric values
- Type
- number
(static) exports.computePearsonCorrelation(valueArray_A, valueArray_B) → {number}
Computes the pearson correlation from two numeric input arrays that must have the same element length
Parameters:
| Name | Type | Description |
|---|---|---|
valueArray_A |
Array.<number> | numeric value array |
valueArray_B |
Array.<number> | numeric value array |
Returns:
returns the pearson correlation of the two input arrays or null if the input arrays do not have the same length or contain non-numeric values
- Type
- number
(static) exports.computeTrend(feature, dates) → {number}
Computes the trend value for the feature considering the submitted array of consecutive dates
Parameters:
| Name | Type | Description |
|---|---|---|
feature |
Feature | a valid GeoJSON Feature, that must contain a |
dates |
Array.<string> | array of dates for which the trend value shall be computed as string of format |
Returns:
returns the trend value of the feature considering the concrete consecutive years of dates array. or null if any date of dates array is not included within feature
- Type
- number
(static) exports.continuity_consecutive_n_days(featureCollection, targetDate, numberOfDays) → {Map.<string, number>}
computes the new indicator as continuity for prior consecutive days (Pearson correlation); internally tests are run, e.g. if a previous day is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfDays |
number | the number of prior consecutive days for which the continuity shall be computed |
Returns:
returns the map of all input features whose continuity value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.continuity_consecutive_n_months(featureCollection, targetDate, numberOfMonths) → {Map.<string, number>}
computes the new indicator as continuity for prior consecutive months (Pearson correlation); internally tests are run, e.g. if a previous month is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfMonths |
number | the number of prior consecutive months for which the continuity shall be computed |
Returns:
returns the map of all input features whose continuity value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.continuity_consecutive_n_years(featureCollection, targetDate, numberOfYears) → {Map.<string, number>}
computes the new indicator as continuity for prior consecutive years (Pearson correlation); internally tests are run, e.g. if a previous year is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfYears |
number | the number of prior consecutive years for which the continuity shall be computed |
Returns:
returns the map of all input features whose continuity value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.convertPropertyArrayToNumberArray(propertyArray) → {Array.<number>}
Takes a property array of arbitrary input objects and returns a valueArray of numeric values which have been converted to a number by Number(value).
Any property value of the input array, whose conversion results in Number.NaN using the check Number.isNan(Number(value)) or is boolean will be completely removed from the array
Thus the resulting array may have fewer entries than the original array.
Parameters:
| Name | Type | Description |
|---|---|---|
propertyArray |
Array.<Object> | an array of arbitrary values (can be String, number, boolean, object) |
Returns:
returns the array of all values that were successfully converted to a number. responseArray.length may be smaller than inputArray.length, if inputArray contains boolean items or items whose Number-conversion result in Number.NaN
- Type
- Array.<number>
(static) exports.convertPropertyMapToNumberMap_fromIdValueMap(indicatorIdValueMap) → {Map.<string, number>}
Takes a map of indicator feature id and value pairs and returns a map containing only entries with numeric indicator values which have been converted to a number by Number(value).
Any property value of the input map entries, whose conversion results in Number.NaN using the check Number.isNan(Number(value)) or is boolean will be completely removed from the map
Thus the resulting may may have fewer entries than the original map.
Parameters:
| Name | Type | Description |
|---|---|---|
indicatorIdValueMap |
Map.<string, Object> | a map of indicator ID and value pairs, where key=ID and value=indicatorValue |
Returns:
returns the map of all input map entries whose values were successfully converted to a number. responseMap.size may be smaller than inputMap.size, if inputMap contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.covariance(populationArray_A, populationArray_B) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#covariance to compute the covariance value of the submitted value arrays
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray_A |
Array.<number> | first data array of numeric values (will be piped through function |
populationArray_B |
Array.<number> | second data array of numeric values (will be piped through function |
Returns:
returns the covariance value of the submitted data arrays
- Type
- number
(static) exports.formatDateAsString(date) → {string}
Converts a Javascript Date object into string of pattern 'YYYY-MM-DD'
Parameters:
| Name | Type | Description |
|---|---|---|
date |
* | a Javascript Date object (e.g. initialized by new Date()) |
Returns:
the date in the format YYYY-MM-DD, e.g. 2017-01-01
- Type
- string
(static) exports.geomean(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#geomean to compute the geometric mean value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the mean shall be computed (will be piped through function |
Returns:
returns the geometric mean value of the submitted array of numeric values
- Type
- number
(static) exports.geomean_fromIdValueMap(indicatorIdValueMapArray) → {Map.<string, number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#geomean to compute the geometric mean value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
Parameters:
| Name | Type | Description |
|---|---|---|
indicatorIdValueMapArray |
Array.<Map.<string, number>> | an array of map objects containing indicator feature ID and numeric value pairs (will be piped through function |
Returns:
returns a map containing the indicator feature id and computed geometric mean value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
- Type
- Map.<string, number>
(static) exports.getChange_absolute(featureCollection, targetDate, compareDate) → {Map.<string, number>}
Computes the absolute difference/change of indicator values between the submitted dates (if both are present in the dataset) using
the formula - value[compareDate]
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
compareDate |
string | the compare date in the string format |
Returns:
returns the map of all input features that have both timestamps and whose changeValues were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.getChange_relative_percent(featureCollection, targetDate, compareDate) → {Map.<string, number>}
Computes the relative difference/change in percent of indicator values between the submitted dates (if both are present in the dataset) using
the formula * (( value[targetDate] - value[compareDate] ) / value[compareDate])
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
compareDate |
string | the compare date in the string format |
Returns:
returns the map of all input features that have both timestamps and whose changeValues in percent were successfully converted to a number. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.getSubstractNDaysDate_asString(referenceDateString, numberOfDays) → {string}
Subtracts n days from the reference date
Parameters:
| Name | Type | Description |
|---|---|---|
referenceDateString |
string | the reference date in the string format |
numberOfDays |
number | the number of days to subtract from the submitted reference date |
Returns:
the new date (referenceDate minus numberOfDays) in the format YYYY-MM-DD, e.g. 2017-12-15
- Type
- string
(static) exports.getSubstractNMonthsDate_asString(referenceDateString, numberOfMonths) → {string}
Subtracts n months from the reference date
Parameters:
| Name | Type | Description |
|---|---|---|
referenceDateString |
string | the reference date in the string format |
numberOfMonths |
number | the number of months to subtract from the submitted reference date |
Returns:
the new date (referenceDate minus numberOfMonths) in the format YYYY-MM-DD, e.g. 2017-12-01
- Type
- string
(static) exports.getSubstractNYearsDate_asString(referenceDateString, numberOfYears) → {string}
Subtracts n years from the reference date
Parameters:
| Name | Type | Description |
|---|---|---|
referenceDateString |
string | the reference date in the string format |
numberOfYears |
number | the number of years to subtract from the submitted reference date |
Returns:
the new date (referenceDate minus numberOfYears) in the format YYYY-MM-DD, e.g. 2017-01-01
- Type
- string
(static) exports.max(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#max to compute the max value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the max value shall be computed (will be piped through function |
Returns:
returns the max value of the submitted array of numeric values
- Type
- number
(static) exports.mean(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#mean to compute the mean value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the mean shall be computed (will be piped through function |
Returns:
returns the mean value of the submitted array of numeric values
- Type
- number
(static) exports.mean_fromIdValueMap(indicatorIdValueMapArray) → {Map.<string, number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#mean to compute the mean value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
Parameters:
| Name | Type | Description |
|---|---|---|
indicatorIdValueMapArray |
Array.<Map.<string, number>> | an array of map objects containing indicator feature ID and numeric value pairs (will be piped through function |
Returns:
returns a map containing the indicator feature id and computed mean value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
- Type
- Map.<string, number>
(static) exports.meanSquareError(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#meansqerr to compute the mean square error value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the mean square error value shall be computed (will be piped through function |
Returns:
returns the mean square error value value of the submitted array of numeric values
- Type
- number
(static) exports.median(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#median to compute the median value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the median shall be computed (will be piped through function |
Returns:
returns the median value of the submitted array of numeric values
- Type
- number
(static) exports.min(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#min to compute the min value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the min value shall be computed (will be piped through function |
Returns:
returns the min value of the submitted array of numeric values
- Type
- number
(static) exports.min_fromIdValueMap(indicatorIdValueMapArray) → {Map.<string, number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#min to compute the min value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
Parameters:
| Name | Type | Description |
|---|---|---|
indicatorIdValueMapArray |
Array.<Map.<string, number>> | an array of map objects containing indicator feature ID and numeric value pairs (will be piped through function |
Returns:
returns a map containing the indicator feature id and computed min value of the submitted array of indicator id and value map objects. Only values for those features will be computed, that have an input value for all entries of the input indicatorIdValueMapArray.
- Type
- Map.<string, number>
(static) exports.minMaxNormalization_inverted_singleValue(min, max, value) → {number}
Implements an inverted min max normalization value of the submitted value using the formula - ((value - min) / (max - min));
Parameters:
| Name | Type | Description |
|---|---|---|
min |
Number | the min value used in upper normalization formula |
max |
Number | the max value used in upper normalization formula |
value |
Number | the value to be normalized |
Returns:
returns the inverted normalized value
- Type
- number
(static) exports.minMaxNormalization_inverted_wholeValueArray(populationArray) → {number}
Implements an inverted min max normalization value array of the submitted value array using the formula - ((value - min) / (max - min));
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the min max normalized value array shall be computed (will be piped through function |
Returns:
returns the inverted normalized value array of the submitted value array
- Type
- number
(static) exports.minMaxNormalization_singleValue(min, max, value) → {number}
Implements a min max normalization value of the submitted value using the formula - min) / (max - min);
Parameters:
| Name | Type | Description |
|---|---|---|
min |
Number | the min value used in upper normalization formula |
max |
Number | the max value used in upper normalization formula |
value |
Number | the value to be normalized |
Returns:
returns the normalized value
- Type
- number
(static) exports.minMaxNormalization_wholeValueArray(populationArray) → {number}
Implements a min max normalization value array of the submitted value array using the formula - min) / (max - min);
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the min max normalized value array shall be computed (will be piped through function |
Returns:
returns the normalized value array of the submitted value array
- Type
- number
(static) exports.percentile(populationArray, k) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#percentile to compute the percentile of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | a(will be piped through function |
k |
number | value between |
Returns:
returns the k-th percentile of the submitted array of numeric values
- Type
- number
(static) exports.quantiles(populationArray, quantilesArray) → {Array.<number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#quantiles to compute the quantiles of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the quantiles shall be computed (will be piped through function |
quantilesArray |
Array.<number> | an array of quantile values (i.e. |
Returns:
returns the quantiles of populationArray according to the quantilesArray
- Type
- Array.<number>
(static) exports.quartiles(populationArray) → {Array.<number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#quartiles to compute the quartiles of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the quartiles shall be computed (will be piped through function |
Returns:
returns the quartiles of the submitted array of numeric values
- Type
- Array.<number>
(static) exports.range(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#range to compute the range value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the range value shall be computed (will be piped through function |
Returns:
returns the range value of the submitted array of numeric values - min
- Type
- number
(static) exports.rank(populationArray) → {Array.<number>}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#rank to compute the rank array of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the mean shall be computed (will be piped through function |
Returns:
returns the ranks of the submitted array of numeric values
- Type
- Array.<number>
(static) exports.standardDeviation(values, computeSampledStandardDeviation) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#stdev to compute the standard deviation for an array of values. By defaut, the population standard deviation is returned.
Passing true for the flag parameter returns the sample standard deviation.
Parameters:
| Name | Type | Description |
|---|---|---|
values |
Array.<number> | an array of numeric values for which the standard deviation shall be computed (will be piped through function |
computeSampledStandardDeviation |
boolean | null | OPTIONAL flag.
If set to |
Returns:
returns the standard deviation
- Type
- number
(static) exports.sum(populationArray) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#sum to compute the sum value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the sum value shall be computed (will be piped through function |
Returns:
returns the sum value of the submitted array of numeric values
- Type
- number
(static) exports.trend_consecutive_n_days(featureCollection, targetDate, numberOfDays) → {Map.<string, number>}
computes the new indicator as trend for prior consecutive days; internally tests are run, e.g. if a previous day is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfDays |
number | the number of prior consecutive days for which the trend shall be computed |
Returns:
returns the map of all input features whose trend value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.trend_consecutive_n_months(featureCollection, targetDate, numberOfMonths) → {Map.<string, number>}
computes the new indicator as trend for prior consecutive months; internally tests are run, e.g. if a previous month is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfMonths |
number | the number of prior consecutive months for which the trend shall be computed |
Returns:
returns the map of all input features whose trend value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.trend_consecutive_n_years(featureCollection, targetDate, numberOfYears) → {Map.<string, number>}
computes the new indicator as trend for prior consecutive years; internally tests are run, e.g. if a previous year is available or not
Parameters:
| Name | Type | Description |
|---|---|---|
featureCollection |
FeatureCollection | a valid GeoJSON FeatureCollection, whose features must contain a |
targetDate |
string | the reference/target date in the string format |
numberOfYears |
number | the number of prior consecutive years for which the trend shall be computed |
Returns:
returns the map of all input features whose trend value were successfully computed. responseMap.size may be smaller than featureCollection.features.size, if featureCollection contains boolean value items or items whose Number-conversion result in Number.NaN
- Type
- Map.<string, number>
(static) exports.variance(populationArray, computeSampledVariance) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#variance to compute the variance value of the submitted value array
Parameters:
| Name | Type | Description |
|---|---|---|
populationArray |
Array.<number> | an array of numeric values for which the variance value shall be computed (will be piped through function |
computeSampledVariance |
boolean | null | OPTIONAL flag.
If set to |
Returns:
returns the variance value of the submitted array of numeric values - min
- Type
- number
(static) exports.zScore_byMeanAndStdev(value, mean, stdev) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#jStat.zscore to compute the zScore of the submitted value given the mean and standard deviation of the associated population.
Parameters:
| Name | Type | Description |
|---|---|---|
value |
number | the numeric value for which the zScore shall be computed |
mean |
number | the numeric mean value of the associated population |
stdev |
number | the numeric standard deviation of the associated population |
Returns:
returns the zScore of the submitted value
- Type
- number
(static) exports.zScore_byPopulationArray(value, populationArray, computeSampledStandardDeviation) → {number}
- Source:
- See:
Encapsulates jStat's function https://jstat.github.io/all.html#jStat.zscore to compute the zScore of the submitted value given the mean and standard deviation of the associated population.
Parameters:
| Name | Type | Description |
|---|---|---|
value |
number | the numeric value for which the zScore shall be computed |
populationArray |
Array.<number> | an array of numeric values for which the standard deviation shall be computed (will be piped through function |
computeSampledStandardDeviation |
boolean | null | OPTIONAL flag.
If set to |
Returns:
returns the zScore of the submitted value
- Type
- number