Introduction
GridChart
widget is used to create a grid of LineChart
subplots with a given data. Users can add plots in real-time making it useful for interactive data exploration and analysis. This widget could be considered as an advanced version of a GridPlot
widget with the support of library.
Function signature
Copy data_1 = {
"title": "Line 1",
"series": [{"name": "Line 1", "data": s1}],
}
data_2 = {
"title": "Line 2",
"series": [{"name": "Line 2", "data": s2}],
}
data_all = {
"title": "All lines",
"series": [{"name": "Line 1", "data": s1}, {"name": "Line 2", "data": s2}],
}
grid_chart = GridChart(data=[data_1, data_2, data_all], columns=3)
Parameters
Parameters
Type
Description
List of data to display. str
inputs will be recognized as a titles for empty widgets.
Gap between widgets inside GridChart
.
data
List of data to display on GridPlot
.
type: List[Dict or str]
Copy data_max = {"title": "Max", "series": [{"name": "Max", "data": s1}]}
data_denis = {"title": "Denis", "series": [{"name": "Denis", "data": s2}]}
grid_chart = GridChart(data=[data_max, data_denis])
columns
Determine the number of columns on GridChart
.
type: int
default value: 1
Copy data_max = {"title": "Max", "series": [{"name": "Max", "data": s1}]}
data_denis = {"title": "Denis", "series": [{"name": "Denis", "data": s2}]}
grid_chart = GridChart(data=[data_max, data_denis], columns=2)
gap
Determine the gap between widgets on GridChart
.
type: int
default value: 10
Copy data_max = {"title": "Max", "series": [{"name": "Max", "data": s1}]}
data_denis = {"title": "Denis", "series": [{"name": "Denis", "data": s2}]}
grid_chart = GridChart(data=[data_max, data_denis], columns=2, gap=100)
ID of the widget.
type: str
default value: None
Methods and attributes
Attributes and Methods
Description
add_scalar(identifier: str, y, x)
add_scalars(plot_title: str, new_values: dict, x)
Add series of data in GridChart
.
Mini App Example
You can find this example in our GitHub repository:
Import libraries
Copy import os
import supervisely as sly
from supervisely.app.widgets import Card, Container, GridChart
from dotenv import load_dotenv
import numpy as np
Init API client
First, we load environment variables with credentials and init API for communicating with Supervisely Instance:
Copy load_dotenv("local.env")
load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api()
Prepare series for plot
Copy 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, y) for x, y in zip(x2, y2)]
data_max = {"title": "Max", "series": [{"name": "Max", "data": s1}]}
data_denis = {"title": "Denis", "series": [{"name": "Denis", "data": s2}]}
data_all = {
"title": "Max vs Denis",
"series": [{"name": "Max", "data": s1}, {"name": "Denis", "data": s2}]
}
Copy grid_chart = GridChart(data=[data_max, data_denis, data_all], columns=2)
Create app layout
Prepare a layout for an app using a Card
widget with the content
parameter and place widget that we've just created in the Container
widget.
Copy card = Card(
title="GridChart",
content=grid_chart,
)
layout = Container(widgets=[card], direction="vertical")
Create an app using a layout
Create an app object with a layout parameter.
Copy app = sly.Application(layout=layout)