3.3.0Add a spectrum based on the data
(object)
{x, y}}
Spectrum:
Add jcamp By default TITLE from the jcamp will be in the meta information
Add from text By default TITLE from the jcamp will be in the meta information
Manager a large number of spectra with the possibility to normalize the data and skip the original data.
(object
= {})
| Name | Description |
|---|---|
options.maxMemory boolean
(default 64M)
|
|
options.normalization object
(default {})
|
options to normalize the spectra before comparison |
options.normalization.from number?
|
|
options.normalization.to number?
|
|
options.normalization.numberOfPoints number?
|
|
options.normalization.filters Array<object>?
|
|
options.normalization.exclusions Array<object>?
|
Checks if the ID of a spectrum exists in the SpectraProcessor
(string)
Returns an object {x:[], y:[]} containing the autocorrelation for the specified index
Returns a JSGraph chart object for all the spectra
(any)
object:
Returns a JSGraph annotation object for box plot
object:
Returns boxplot information
object:
Returns a JSGraph chart object for all the spectra
(any)
object:
Returns an array of all the ids
Array:
Returns a {x:[], y:[]} containg the average of specified spectra
Returns the metadata for a set of spectra
object:
Returns a JSGraph chart object for all the normalized spectra
object:
We provide the allowed from / to after normalization For the X axis we return the smallest common values For the Y axis we return the largest min / max
Returns an object contains 4 parameters with the normalized data
object:
{ ids:[], matrix:[Array], meta:[object], x:[] }
Returns a tab separated value containing the normalized data
string:
Returns a JSGraph chart object for all the scaled normalized spectra
object:
Returns an object contains 4 parameters with the scaled data
(object
= {})
scale spectra based on various parameters
| Name | Description |
|---|---|
options.range object?
|
from - to |
options.ids Array?
|
ids of selected spectra, by default all |
options.targetID string
(default spectra[0].id)
|
|
options.method string
(default 'max')
|
min, max, range, minMax |
options.relative boolean
(default false)
|
object:
{ ids:[], matrix:[Array], meta:[object], x:[] }
Returns a tab separated value containing the post processed data
(object
= {})
| Name | Description |
|---|---|
options.ids Array?
|
List of spectra ids to export, by default all |
options.fs string
(default '\t')
|
field separator |
options.rs string
(default '\n')
|
record (line) separator |
(object
= {})
string:
Returns an array of spectrum from their ids
(Array)
Returns the index of the spectrum in the spectra array
(string)
number:
Returns the index of the spectrum in the spectra array
(string)
number:
Returns a JSGraph annotation object for the specified index
(any)
object:
Remove all the spectra not present in the list
(Array?)
Array of ids of the spectra to keep
Remove the spectrum from the SpectraProcessor for the specified id
(string)
Recalculate the normalized data using the stored original data if available This will throw an error in the original data is not present
Create SpectraProcessor from normalized TSV
Allows to calculate relative intensity between normalized spectra
(SpectraProcessor)
(object
= {})
scale spectra based on various parameters
| Name | Description |
|---|---|
options.ids Array?
|
ids of selected spectra |
options.filters Array
(default [])
|
Array of object containing {name:'', options:''} |
options.scale object
(default {})
|
object containing the options for rescaling |
options.scale.targetID string
(default spectra[0].id)
|
|
options.scale.method string
(default 'max')
|
min, max, integration, minMax |
options.scale.range Array?
|
from - to to apply the method and rescale |
options.scale.relative boolean
(default false)
|
|
options.ranges Array?
|
Array of object containing {from:'', to:'', label:''} |
options.calculations Array?
|
Array of object containing {label:'', formula:''} |
object:
{ ids:[], matrix:[Array], meta:[object], x:[], ranges:[object] }
Retrieve a chart with autocorrelation color
(SpectraProcessor?)
(number?)
(object
= {})
| Name | Description |
|---|---|
options.autocorrelation Array?
|
precalculated autocorrelation {x,y} |
options.ids Array?
|
ids of the spectra to select, by default all |
options.xFilter object
(default {})
|
|
options.xFilter.from number?
|
|
options.xFilter.to number?
|
|
options.xFilter.exclusions Array
(default [])
|
(Array)
[options.maxDataPoints=]
Retrieve a chart with selected original data
(SpectraProcessor)
(object
= {})
scale spectra based on various parameters
| Name | Description |
|---|---|
options.ids Array?
|
ids of selected spectra |
options.filters Array
(default [])
|
Array of object containing {name:'', options:''} |
options.scale object
(default {})
|
object containing the options for rescaling |
options.scale.targetID string
(default spectra[0].id)
|
|
options.scale.method string
(default 'max')
|
min, max, integration, minMax |
options.scale.range Array?
|
from - to to apply the method and rescale |
options.scale.relative boolean
(default false)
|
could implement a cache if all the options are identical and the normalized data is identical as well in order ot check if the normalized data are identical we should check if the normalized array of all the spectra are identical Because we don't make in-place modification when creating normalized array we can check if the 'pointer' to the object is identical
Create a spectrum from a jcamp
(string)
String containing the JCAMP data
Spectrum:
new instance of Spectrum with the provided data
Creates a g
(string)
String containing the text data
object:
{matrix, data, x, ids}
Create a spectrum from a text file
(string)
String containing the JCAMP data
(any
= {})
Spectrum:
new instance of Spectrum with the provided data
Class allowing manipulate one IR spectrum