Supervisely
About SuperviselyEcosystemContact usSlack
  • 💻Supervisely Developer Portal
  • 🎉Getting Started
    • Installation
    • Basics of authentication
    • Intro to Python SDK
    • Environment variables
    • Supervisely annotation format
      • Project Structure
      • Project Meta: Classes, Tags, Settings
      • Objects
      • Tags
      • Image Annotation
      • Video Annotation
      • Point Clouds Annotation
      • Point Cloud Episode Annotation
      • Volumes Annotation
    • Python SDK tutorials
      • Images
        • Images
        • Image and object tags
        • Spatial labels on images
        • Keypoints (skeletons)
        • Multispectral images
        • Multiview images
        • Advanced: Optimized Import
        • Advanced: Export
      • Videos
        • Videos
        • Video and object tags
        • Spatial labels on videos
      • Point Clouds
        • Point Clouds (LiDAR)
        • Point Cloud Episodes and object tags
        • 3D point cloud object segmentation based on sensor fusion and 2D mask guidance
        • 3D segmentation masks projection on 2D photo context image
      • Volumes
        • Volumes (DICOM)
        • Spatial labels on volumes
      • Common
        • Iterate over a project
        • Iterate over a local project
        • Progress Bar tqdm
        • Cloning projects for development
    • Command Line Interface (CLI)
      • Enterprise CLI Tool
        • Instance administration
        • Workflow automation
      • Supervisely SDK CLI
    • Connect your computer
      • Linux
      • Windows WSL
      • Troubleshooting
  • 🔥App development
    • Basics
      • Create app from any py-script
      • Configuration file
        • config.json
        • Example 1. Headless
        • Example 2. App with GUI
        • v1 - Legacy
          • Example 1. v1 Modal Window
          • Example 2. v1 app with GUI
      • Add private app
      • Add public app
      • App Compatibility
    • Apps with GUI
      • Hello World!
      • App in the Image Labeling Tool
      • App in the Video Labeling Tool
      • In-browser app in the Labeling Tool
    • Custom import app
      • Overview
      • From template - simple
      • From scratch - simple
      • From scratch GUI - advanced
      • Finding directories with specific markers
    • Custom export app
      • Overview
      • From template - simple
      • From scratch - advanced
    • Neural Network integration
      • Overview
      • Serving App
        • Introduction
        • Instance segmentation
        • Object detection
        • Semantic segmentation
        • Pose estimation
        • Point tracking
        • Object tracking
        • Mask tracking
        • Image matting
        • How to customize model inference
        • Example: Custom model inference with probability maps
      • Serving App with GUI
        • Introduction
        • How to use default GUI template
        • Default GUI template customization
        • How to create custom user interface
      • Inference API
      • Training App
        • Overview
        • Tensorboard template
        • Object detection
      • High level scheme
      • Custom inference pipeline
      • Train and predict automation model pipeline
    • Advanced
      • Advanced debugging
      • How to make your own widget
      • Tutorial - App Engine v1
        • Chapter 1 Headless
          • Part 1 — Hello world! [From your Python script to Supervisely APP]
          • Part 2 — Errors handling [Catching all bugs]
          • Part 3 — Site Packages [Customize your app]
          • Part 4 — SDK Preview [Lemons counter app]
          • Part 5 — Integrate custom tracker into Videos Annotator tool [OpenCV Tracker]
        • Chapter 2 Modal Window
          • Part 1 — Modal window [What is it?]
          • Part 2 — States and Widgets [Customize modal window]
        • Chapter 3 UI
          • Part 1 — While True Script [It's all what you need]
          • Part 2 — UI Rendering [Simplest UI Application]
          • Part 3 — APP Handlers [Handle Events and Errors]
          • Part 4 — State and Data [Mutable Fields]
          • Part 5 — Styling your app [Customizing the UI]
        • Chapter 4 Additionals
          • Part 1 — Remote Developing with PyCharm [Docker SSH Server]
      • Custom Configuration
        • Fixing SSL Certificate Errors in Supervisely
        • Fixing 400 HTTP errors when using HTTP instead of HTTPS
      • Autostart
      • Coordinate System
      • MLOps Workflow integration
    • Widgets
      • Input
        • Input
        • InputNumber
        • InputTag
        • BindedInputNumber
        • DatePicker
        • DateTimePicker
        • ColorPicker
        • TimePicker
        • ClassesMapping
        • ClassesColorMapping
      • Controls
        • Button
        • Checkbox
        • RadioGroup
        • Switch
        • Slider
        • TrainValSplits
        • FileStorageUpload
        • Timeline
        • Pagination
      • Text Elements
        • Text
        • TextArea
        • Editor
        • Copy to Clipboard
        • Markdown
        • Tooltip
        • ElementTag
        • ElementTagsList
      • Media
        • Image
        • LabeledImage
        • GridGallery
        • Video
        • VideoPlayer
        • ImagePairSequence
        • Icons
        • ObjectClassView
        • ObjectClassesList
        • ImageSlider
        • Carousel
        • TagMetaView
        • TagMetasList
        • ImageAnnotationPreview
        • ClassesMappingPreview
        • ClassesListPreview
        • TagsListPreview
        • MembersListPreview
      • Selection
        • Select
        • SelectTeam
        • SelectWorkspace
        • SelectProject
        • SelectDataset
        • SelectItem
        • SelectTagMeta
        • SelectAppSession
        • SelectString
        • Transfer
        • DestinationProject
        • TeamFilesSelector
        • FileViewer
        • Dropdown
        • Cascader
        • ClassesListSelector
        • TagsListSelector
        • MembersListSelector
        • TreeSelect
        • SelectCudaDevice
      • Thumbnails
        • ProjectThumbnail
        • DatasetThumbnail
        • VideoThumbnail
        • FolderThumbnail
        • FileThumbnail
      • Status Elements
        • Progress
        • NotificationBox
        • DoneLabel
        • DialogMessage
        • TaskLogs
        • Badge
        • ModelInfo
        • Rate
        • CircleProgress
      • Layouts and Containers
        • Card
        • Container
        • Empty
        • Field
        • Flexbox
        • Grid
        • Menu
        • OneOf
        • Sidebar
        • Stepper
        • RadioTabs
        • Tabs
        • TabsDynamic
        • ReloadableArea
        • Collapse
        • Dialog
        • IFrame
      • Tables
        • Table
        • ClassicTable
        • RadioTable
        • ClassesTable
        • RandomSplitsTable
        • FastTable
      • Charts and Plots
        • LineChart
        • GridChart
        • HeatmapChart
        • ApexChart
        • ConfusionMatrix
        • LinePlot
        • GridPlot
        • ScatterChart
        • TreemapChart
        • PieChart
      • Compare Data
        • MatchDatasets
        • MatchTagMetas
        • MatchObjClasses
        • ClassBalance
        • CompareAnnotations
      • Widgets demos on github
  • 😎Advanced user guide
    • Objects binding
    • Automate with Python SDK & API
      • Start and stop app
      • User management
      • Labeling Jobs
  • 🖥️UI widgets
    • Element UI library
    • Supervisely UI widgets
    • Apexcharts - modern & interactive charts
    • Plotly graphing library
  • 📚API References
    • REST API Reference
    • Python SDK Reference
Powered by GitBook
On this page
  • Introduction
  • Function signature
  • Parameters
  • series
  • options
  • type
  • height
  • sly_options
  • Methods and attributes
  • Mini App Example
  • Import libraries
  • Init API client
  • Prepare series for chart
  • Initialize Apexchart widget
  • Create app layout
  • Create app using layout
  • Add functions to control widgets from python code

Was this helpful?

Edit on GitHub
  1. App development
  2. Widgets
  3. Charts and Plots

ApexChart

Introduction

Apexchart is a widget in Supervisely that allows for displaying interactive charts on the UI. It supports various chart types such as line, area, and bar. Users can customize the chart by changing the chart type, color schemes, and legend location.

It also provides functionality for data streaming and dynamic updates, allowing the chart to display real-time data. The data can be passed to the chart in the form of a pandas dataframe or a Python list of dictionaries. Additionally, users can control the chart through Python code by detecting events such as clicking on a data point or hovering over a chart element.

Function signature

size1 = 10
x1 = list(range(size1))
y1 = np.random.randint(low=10, high=148, size=size1).tolist()
s1 = [{"x": x, "y": y} for x, y in zip(x1, y1)]

size2 = 30
x2 = list(range(size2))
y2 = np.random.randint(low=0, high=300, size=size2).tolist()
s2 = [{"x": x, "y": y} for x, y in zip(x2, y2)]

apexchart = Apexchart(
    series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}],
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product Trends by Month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    type="line",
)

Parameters

Parameters
Type
Description

series

list

List of series including names and lists of X, Y coordinates

options

dict

Chart options for customizing styles

type

str

Type of chart (line, bar, area)

height

Union[int, str]

Widget height

sly_options

dict

Additional options used in supervisely component

series

List of series including names and lists of X, Y coordinates

type: list

apexchart = Apexchart(
    series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}],
    # options=...
    # type=...
)

options

Chart options for customizing styles

type: dict

apexchart = Apexchart(
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product Trends by Month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    # series=...,
    # type=...
)

type

Type of chart. It supports following chart types: line, area, bar.

type: str

apexchart = Apexchart(
    series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}],
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product Trends by Month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    type="line",
)
apexchart = Apexchart(
    series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}],
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product Trends by Month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    type="area",
)
apexchart = Apexchart(
    series=[{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}],
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product Trends by Month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    type="bar",
)

height

Widget height

type: Union[int, str]

default value: "300"

apexchart = Apexchart(
    # series=...,
    # options=...,
    # type=...,
    height="500"
)

sly_options

Additional options used in supervisely component.

type: dict

Methods and attributes

Attributes and Methods
Description

get_clicked_value()

Get value of clicked datapoint.

get_clicked_datapoint()

Get clicked datapoint.

set_title(title: str, send_changes: bool = True)

Set chart title.

add_series(name: str, x: list, y: list, send_changes: bool = True)

Add new series to chart.

set_series(series: list, send_changes: bool = True)

Set series to chart.

set_colors(colors: List[str or List[int]], send_changes: bool = True)

Set colors for series in chart (str, RGB or HEX).

add_to_series(name_or_id: str or int, data: List[tuple] or List[dict] or tuple or dict], send_changes: bool = True)

Add data to exist series.

get_series_by_name(name: str)

Return series data by name.

@click

Decorator function to handle chart click.

Mini App Example

You can find this example in our GitHub repository:

Import libraries

import os

import numpy as np
import supervisely as sly
from dotenv import load_dotenv
from supervisely.app.widgets import Apexchart, Card

Init API client

First, we load environment variables with credentials and init API for communicating with Supervisely Instance:

load_dotenv("local.env")
load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api()

Prepare series for chart

size1 = 22
x1 = list(range(size1))
y1 = np.random.randint(low=10, high=180, size=size1).tolist()
s1 = [{"x": x, "y": y} for x, y in zip(x1, y1)]

size2 = 30
x2 = list(range(size2))
y2 = np.random.randint(low=0, high=300, size=size2).tolist()
s2 = [{"x": x, "y": y} for x, y in zip(x2, y2)]

Initialize Apexchart widget

apexchart = Apexchart(
    series=[{"name": "Fred", "data": s1}, {"name": "Harry", "data": s2}],
    options={
        "chart": {"type": "line", "zoom": {"enabled": False}},
        "dataLabels": {"enabled": False},
        "stroke": {"curve": "smooth", "width": 2},
        "title": {"text": "Product sales by month", "align": "left"},
        "grid": {"row": {"colors": ["#f3f3f3", "transparent"], "opacity": 0.5}},
        "xaxis": {"type": "category"},
    },
    type="line",
)

Create app layout

Prepare a layout for app using Card widget with the content parameter.

info_text = Text(status="info")
card = Card(title="Apexchart", content=Container([apexchart, info_text]))

Create app using layout

Create an app object with layout parameter.

app = sly.Application(layout=card)

Add functions to control widgets from python code

@apexchart.click
def show_info(datapoint: sly.app.widgets.Apexchart.ClickedDataPoint):
    x = datapoint.x
    y = datapoint.y
    name = datapoint.series_name
    info_text.text = f"On May {x}, {name} has sold {y} units of the product."
    if int(y) > 160:
        info_text.status = "success"
    elif int(y) < 50:
        info_text.status = "error"
    else:
        info_text.status = "info"
PreviousHeatmapChartNextConfusionMatrix

Last updated 1 year ago

Was this helpful?

🔥
ui-widgets-demos/charts and plots/003_apex_chart/src/main.py