Constructor
new DataAdapter(projects, aggrMeta)
- Source:
- Copyright:
- (c) 2024 TLF Research Ltd.
Constructs a DataAdapter instance.
Parameters:
| Name | Type | Description |
|---|---|---|
projects |
Array | Array of available projects for the current user. |
aggrMeta |
Array | Metadata about aggregators supported by the system. |
Members
calculateHighValuePercentages
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calculateHighValuePercentages returns the percentage of high values as a proportion of the total responses.
convertToDelta
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Gets the difference between the two sets of data.
convertVerbalScaleToLevels
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convertVerbalScaleToLevels converts all the different verbal scale responses into L1 - L5 categories
data
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Gets the normalized data store.
groupIntoHightNeutralLow
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Groups the given data into High/Neutral/Low categories.
omitted
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Gets the omitted data series.
output
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Gets the output of the adapter after transforming the data.
response
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Gets the API response data in the adapter.
response
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Sets the API response data in the adapter. Normalizes the data based on the aggregator metadata.
transposeVerbalScaleResponses
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Converts verbal scale responses into a format for presentation in charts.
Methods
(static) deepClone(orig) → {*}
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Returns a deep clone of the given object.
Parameters:
| Name | Type | Description |
|---|---|---|
orig |
* | The object to be cloned |
Returns:
A clone of the given object
- Type
- *
(static) deepMerge(obj1, obj2) → {*}
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Returns a deep merge of the second object into the first and reurns the result.
Parameters:
| Name | Type | Description |
|---|---|---|
obj1 |
* | The base object (that is changed in place) |
obj2 |
* | The object to be merged |
Returns:
A deep merge of the given objects aka obj1
- Type
- *
(static) getTSMSubmissionTable(ds, data)
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getTSMSubmissionTable returns data for a table of TSM submissions.
Parameters:
| Name | Type | Description |
|---|---|---|
ds |
Object | Data source object. |
data |
Array | Array of data series containing TSM responses. |
(static) getVsatTopBoxPercent(ds, data) → {Number}
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Returns the top box score for the given satisfaction scale data.
Parameters:
| Name | Type | Description |
|---|---|---|
ds |
Object | Dataset object. |
data |
Object | Data object containing satisfaction scores. |
Returns:
- Top box percentage as a float.
- Type
- Number
(static) multiplyBy(multiplier) → {function}
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multiplyBy is a higher-order function that returns a function that mutiplies all the data values by the given multiplier.
Parameters:
| Name | Type | Description |
|---|---|---|
multiplier |
number | The multiplier to be applied to the data values |
Returns:
- A function that mutiplies all the data values by the given multiplier
- Type
- function
(static) sortUsingSeries(ds, data, seriesName, orderopt) → {Array}
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Sorts all data series using the specified series as the reference.
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
ds |
Object | Dataset object containing metadata. |
||
data |
Array | Array of data series to be sorted. |
||
seriesName |
string | The name of the series to be used for sorting. |
||
order |
string |
<optional> |
'ASC'
|
The order of sorting, either 'ASC' or 'DESC'. |
Returns:
- Sorted data series array.
- Type
- Array
(static) zTest(sample1, sample2) → {number}
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Performs a z-test on two independent samples.
Parameters:
| Name | Type | Description |
|---|---|---|
sample1 |
Object | First sample with |
sample2 |
Object | Second sample with |
Returns:
- Returns 1 if the difference is significant, -1 if inverse, and 0 if not significant.
- Type
- number
(static) zTestOverall(overall, subset) → {number}
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Performs a z-test where the second sample is a subset of the first.
Parameters:
| Name | Type | Description |
|---|---|---|
overall |
Object | Overall sample with |
subset |
Object | Subset sample with |
Returns:
- Returns 1 if the difference is significant, -1 if inverse, and 0 if not significant.
- Type
- number
calculateImpact(ds, data) → {Array}
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Calculates the impact of independent variables on the dependent variable.
Parameters:
| Name | Type | Description |
|---|---|---|
ds |
Object | Dataset information object. |
data |
Object | Raw data used for calculation. |
Returns:
- Array of calculated impact results.
- Type
- Array
processComprehendTextAnalysis(ds, data, seriesIdx, thresholds) → {Array}
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Processes text analysis data from Amazon Comprehend for the given dataset.
Parameters:
| Name | Type | Description |
|---|---|---|
ds |
Object | Dataset information object. |
data |
Array | Raw data array for text analysis. |
seriesIdx |
number | Index of the series in the dataset. |
thresholds |
Array.<number> | Array of thresholds used for filtering themes. |
Returns:
- Processed text analysis result for presentation.
- Type
- Array