npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

@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.

Downloads

39

Readme

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 name
  • pointColor - overrides the standardized series point color
  • fitLineColor - overrides the standardized series fit line color
  • confidenceIntervalColor - overrides the standardized series confidence interval color
  • outlierColor - overrides the standardized series outlier color
  • markerType - defines the series marker type, which could be circle, asterisk, square, etc.
  • outlierMarkerType - defines the series outlier marker type, which could be circle, outlier, square, etc.
  • lineStyle - defines the series line style, which could be solid, dotted, dashed or dashdotted
  • errorModel - defines the series error model, which could be either constant, proportional or combined
  • connectDots - defines whether to connect the points with lines or not
  • showFitLine - defines whether to show the fit line or not
  • showCurveConfidenceInterval - defines whether to show the confidence intervals or not
  • fitFunction - 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 also parameters
  • showPoints - defines the data display mode, which could be either points, candlesticks, both, or none
  • clickToToggle - defines whether clicking on the point toggles its outlier status and causes curve refitting or not
  • droplines - defines the droplines that would be shown on the plot (for instance, IC50)
  • points - an array of objects with each object containing x and y coordinates and its own parameters:
    • outlier - if true, renders as 'x' and gets ignored for curve fitting
    • color - overrides the marker color defined in series pointColor
    • marker - overrides the marker type defined in series markerType
    • outlierMarker - overrides the outlier marker type defined in series outlierMarkerType
    • size - overrides the default marker size
    • stdev - 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 plot
  • title - defines the plot title. If the plot size is enough, will render it
  • xAxisName, yAxisName - defines the x and y axis names. If the plot size is enough, will render it
  • logX, logY - defines whether the x and y data should be logarithmic or not
  • allowXZeroes - 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 chart
  • mergeSeries - defines whether to merge series or not
  • showColumnLabel - defines whether to show the column label in the legend or not
  • showStatistics - defines the statistics that would be shown on the plot (such as the area under the curve (auc) or the coefficient of determination (rSquared))

curves

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.

custom-fit-function

Multi Curve Viewer

You can overlay curves from multiple cells on one chart with the Multi Curve Viewer:

See also: