@datagrok/curves
v1.6.0
Published
Curves provides support for fitted curves (such as dose-response curves), including in-grid rendering, storing charts in cells, interactivity, and automatic fitting.
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Curves
Curves provides support for fitted curves (such as dose-response curves), including in-grid rendering, storing charts in cells, interactivity, and automatic fitting.
- Fitting: computing parameters of the specified function to best fit the data
- For dose-response curves, we are typically fitting the sigmoid function
- Ability to dynamically register custom fitting functions
- Automatic fit function determination
- Caching of custom fitting functions
- Ability to get fitting performance characteristics (r-squared, classification, etc.)
- Deep integration with the Datagrok grid
- Either fitting on the fly or using the supplied function + parameters
- Multiple series in one cell
- Candlesticks, confidence intervals, standard deviation and droplines drawing
- Ability to define chart, marker, or fitting options (such as fit function or marker color) on the column level, with the ability to override it on a grid cell or point level
- Clicking a point in a chart within a grid makes it an outlier -> curve is re-fitted on the fly
- Ability to switch curves parameters from the property panel on different levels (dataframe, column, cell)
- Ability to specify a chart as a "reference" so that it is shown on every other chart for comparison
- Ability to overlay curves from multiple grid cells (special viewer)
- Work with series stored in multiple formats (binary for performance, JSON for flexibility, etc.)
Rendering fitted curves using JSON format
To render a fitted curve based on series points, you need to write it in the following JSON format:
{
"series": [
{
"name": "Test series",
"pointColor": "#2ca02c",
"fitLineColor": "#2ca02c",
"confidenceIntervalColor": "#fbec5d",
"outlierColor": "#d62728",
"markerType": "circle",
"outlierMarkerType": "outlier",
"lineStyle": "dashed",
"errorModel": "proportional",
"connectDots": false,
"showFitLine": true,
"showCurveConfidenceInterval": true,
"fitFunction": "sigmoid",
"parameters": [1.7391934768969721, -0.9451759934029763, 4.846020678949615, 0.15841886339211816],
"parameterBounds": [
{"min": 1.739193476892, "max": 1.739193476898},
{"max": -0.9451759934029},
{},
{"min": 0.158418863392114}
],
"showPoints": "points",
"clickToToggle": true,
"droplines": ["IC50"],
"points": [
{ "x": 0.10000000149011612, "y": 0.04152340441942215, "stdev": 0.031523404876, "marker": "square", "outlierMarker": "square" },
{ "x": 0.6000000238418579, "y": 0.11901605129241943, "outlier": true, "outlierColor": "#ff7f0e" },
{ "x": 1.100000023841858, "y": 0.11143334954977036, "outlier": false, "color": "#2ca02c", "size": 5 },
// ...
]
}
],
"chartOptions": {
"showStatistics": ["auc", "rSquared"],
"minX": 0.10000000149011612,
"minY": 0.04152340441942215,
"maxX": 7.099999904632568,
"maxY": 1.7591952085494995,
"title": "Dose-Response curves",
"xAxisName": "Concentration",
"yAxisName": "Activity",
"logX": true,
"logY": false,
"allowXZeroes": true,
"mergeSeries": false,
"showColumnLabel": true
}
}
Each series has its own parameters, such as:
name
- controls the series namepointColor
- overrides the standardized series point colorfitLineColor
- overrides the standardized series fit line colorconfidenceIntervalColor
- overrides the standardized series confidence interval coloroutlierColor
- overrides the standardized series outlier colormarkerType
- defines the series marker type, which could becircle
,asterisk
,square
, etc.outlierMarkerType
- defines the series outlier marker type, which could becircle
,outlier
,square
, etc.lineStyle
- defines the series line style, which could besolid
,dotted
,dashed
ordashdotted
errorModel
- defines the series error model, which could be eitherconstant
,proportional
orcombined
connectDots
- defines whether to connect the points with lines or notshowFitLine
- defines whether to show the fit line or notshowCurveConfidenceInterval
- defines whether to show the confidence intervals or notfitFunction
- controls the series fit function, which could be either a sigmoid, linear, log-linear function or a custom-defined function.parameters
- controls the series parameters, if set explicitly - the fitting process won't be executed. The parameter order of the sigmoid function is:max, tan, IC50, min
.parameterBounds
- defines the acceptable range of each parameter, which is taken into account during the fitting. See alsoparameters
showPoints
- defines the data display mode, which could be eitherpoints
,candlesticks
,both
, or noneclickToToggle
- defines whether clicking on the point toggles its outlier status and causes curve refitting or notdroplines
- defines the droplines that would be shown on the plot (for instance, IC50)points
- an array of objects with each object containingx
andy
coordinates and its own parameters:outlier
- if true, renders as 'x' and gets ignored for curve fittingcolor
- overrides the marker color defined in seriespointColor
marker
- overrides the marker type defined in seriesmarkerType
outlierMarker
- overrides the outlier marker type defined in seriesoutlierMarkerType
size
- overrides the default marker sizestdev
- when defined, renders an error bar candlestick
Each chart has its own parameters as well, such as:
minX
,minY
,maxX
,maxY
- controls the minimum x and y values of the plottitle
- defines the plot title. If the plot size is enough, will render itxAxisName
,yAxisName
- defines the x and y axis names. If the plot size is enough, will render itlogX
,logY
- defines whether the x and y data should be logarithmic or notallowXZeroes
- defines whether x zeroes allowed for logarithmic data or not. If the flag is true, it will calculate the approximate log(0) that will fit the chartmergeSeries
- defines whether to merge series or notshowColumnLabel
- defines whether to show the column label in the legend or notshowStatistics
- defines the statistics that would be shown on the plot (such as the area under the curve (auc
) or the coefficient of determination (rSquared
))
Creating a custom fit function
To render a custom fit function, you need to write in the following JSON format:
"fitFunction": {
"name": "Polynomial",
"function": "([p1, p2, p3, p4], x) => p1 * x * x * x + p2 * x * x + p3 * x + p4",
"getInitialParameters": "(xs, ys) => [0.1, -1, 4, 4]",
"parameterNames": ["Slope", "Intercept", "Parameter 3", "Parameter 4"]
}
Each fitting function has its own name
, which is used to cache the created custom function, enabling
efficient retrieval and reuse, and parameterNames
, which are stored as an array of strings.
Also, there are two functions: getInitialParameters
, which takes arrays of x and y and returns determined
initial parameter values, and function
, which takes the array of parameters and the given x coordinate and
returns the result of the fit function. These functions are written as JavaScript arrow function expressions.
Multi Curve Viewer
You can overlay curves from multiple cells on one chart with the Multi Curve Viewer:
See also: