0.2.4 • Published 1 year ago
riskfix v0.2.4
RiskFix: A Modular Package for Visual-Interactive Validation of Risk-Prediction Machine Learning Models
This is a React component library that provides reusable UI components for building web applications.
Installation
You can install this library via NPM by running the following command:
npm install riskfix
Usage
To use this component library in your project, you can import individual components like so:
import { PreBias } from "riskfix"
function MyComponent() {
const [count, setCount] = useState(0)
return (<PreBias setPrebiasValue={setCount} />);
}
Available Components
PreBias: A pre-bias component
setPrebiasValue
: (value: number) => void;
QRReader: A QR code reader component
bedside_info
: string;- A string representing the information about the bedside monitoring device.
bedside_devices
: string | null;- A string or null value representing the list of devices connected to the bedside monitoring system.
setBedsideDevices
: React.Dispatch<React.SetStateAction<string | null>>;- A React state hook function that takes a string or null value and sets the bedside devices.
setBedsideInfo
: React.Dispatch<React.SetStateAction>;- A React state hook function that takes a string value and sets the bedside info.
handleScan
: (data: any) => void;- A function that takes a data object as an argument and is called when a QR code is successfully scanned.
handleError
: (err: any) => void;- A function that takes an error object as an argument and is called when there is an error with the QR code scan.
PredictionTimeline: A prediction timeline component to show model validated results.
prebiasValue
: number | undefined; - An optional number value representing the pre-bias value for the risk prediction model.bedsideDevices
: string | null; - A string or null value representing the list of devices connected to the bedside monitoring system.bedsideInfo
: string; - A string value representing the information about the bedside monitoring device.user
: { email: string } | undefined; - An optional object with an email property representing the user information.recordValidation
: (val: IValidation) => Promise<number | undefined> - A function that takes a validation object as an argument and returns a promise that resolves to a number or undefined value.fetchAnnotation
: (user: string, devid: number, start_time: number, end_time: number) => Promise - A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to an annotation object.recordAnnotation
: (val: IRecordAnnotation) => Promise<number | undefined> - A function that takes an annotation object as an argument and returns a promise that resolves to a number or undefined value.fetchPrediction
: (devid: number, limit: number, start_time: number, end_time: number) => Promise - A function that takes devid, limit, start_time, and end_time as arguments and returns a promise that resolves to a prediction scores object.fetchValidation
: (user: string, devid: number, start_time: number, end_time: number) => Promise - A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to a validated scores object.
Timeline: The timeline visualization component used within the PredictionTimeline component.
devid
: number; - A number value representing the ID of the monitoring device.prebias
: number; - A number value representing the pre-bias value for the risk prediction model.modelPause
: boolean; - A boolean value indicating whether the model is paused or not.user
: string; - A string value representing the user information.fetchInterval
- The time of the interval between points, in milliseconds. An example value would be: 30000 for 30 second intervals.timeWindow
- The size of display window in terms of time, in milliseconds. For example, if we wanted to show the last 5 mins. we would put in: (5 60 1000).rollbackTime
- If a time rollback is required from the latest set of points, use this to start after a certain number of milliseconds before the current time within the model values.fetchPrediction
: (devid: number, limit: number, start_time: number, end_time: number) => Promise - A function that takes devid, limit, start_time, and end_time as arguments and returns a promise that resolves to a prediction scores object.fetchValidation
: (user: string, devid: number, start_time: number, end_time: number) => Promise - A function that takes user, devid, start_time, and end_time as arguments and returns a promise that resolves to a validated scores object.recordValidation
: (val: IValidation) => Promise<number | undefined> - A function that takes a validation object as an argument and returns a promise that resolves to a number or undefined value.
Contributing
To contribute to this project, please follow these steps:
Fork the repo Create a new branch (git checkout -b my-new-feature) Make changes and commit (git commit -am 'Add some feature') Push to the branch (git push origin my-new-feature) Create a new pull request
License
This project is licensed under the MIT License. See the LICENSE file for more details.