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271 lines
11 KiB
271 lines
11 KiB
// Copyright 2018 the Charts project authors. Please see the AUTHORS file
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// for details.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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/// Example of using disjoint measure axes to render 4 series of lines with
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/// separate scales. The general use case for this type of chart is to show
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/// differences in the trends of the data, without comparing their absolute
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/// values.
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///
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/// Disjoint measure axes will be used to scale the series associated with them,
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/// but they will not render any tick elements on either side of the chart.
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// EXCLUDE_FROM_GALLERY_DOCS_START
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import 'dart:collection' show LinkedHashMap;
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import 'dart:math';
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import 'package:charts_flutter/flutter.dart' as charts;
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import 'package:flutter/material.dart';
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class DisjointMeasureAxisLineChart extends StatelessWidget {
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final List<charts.Series> seriesList;
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final bool animate;
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const DisjointMeasureAxisLineChart(this.seriesList, {this.animate, Key key})
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: super(key: key);
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/// Creates a [LineChart] with sample data and no transition.
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factory DisjointMeasureAxisLineChart.withSampleData() {
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return DisjointMeasureAxisLineChart(
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_createSampleData(),
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// Disable animations for image tests.
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animate: false,
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);
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}
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// EXCLUDE_FROM_GALLERY_DOCS_START
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// This section is excluded from being copied to the gallery.
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// It is used for creating random series data to demonstrate animation in
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// the example app only.
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factory DisjointMeasureAxisLineChart.withRandomData() {
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return DisjointMeasureAxisLineChart(_createRandomData());
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}
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/// Create random data.
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static List<charts.Series<LinearClicks, num>> _createRandomData() {
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final random = Random();
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// The first three series contain similar data with different magnitudes.
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// This demonstrates the ability to graph the trends in each series relative
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// to each other, without the largest magnitude series compressing the
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// smallest.
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final myFakeDesktopData = [
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LinearClicks(0, clickCount: random.nextInt(100)),
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LinearClicks(1, clickCount: random.nextInt(100)),
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LinearClicks(2, clickCount: random.nextInt(100)),
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LinearClicks(3, clickCount: random.nextInt(100)),
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];
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final myFakeTabletData = [
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LinearClicks(0, clickCount: random.nextInt(100) * 100),
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LinearClicks(1, clickCount: random.nextInt(100) * 100),
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LinearClicks(2, clickCount: random.nextInt(100) * 100),
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LinearClicks(3, clickCount: random.nextInt(100) * 100),
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];
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final myFakeMobileData = [
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LinearClicks(0, clickCount: random.nextInt(100) * 1000),
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LinearClicks(1, clickCount: random.nextInt(100) * 1000),
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LinearClicks(2, clickCount: random.nextInt(100) * 1000),
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LinearClicks(3, clickCount: random.nextInt(100) * 1000),
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];
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// The fourth series renders with decimal values, representing a very
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// different sort ratio-based data. If this was on the same axis as any of
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// the other series, it would be squashed near zero.
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final myFakeClickRateData = [
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LinearClicks(0, clickRate: .25),
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LinearClicks(1, clickRate: .65),
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LinearClicks(2, clickRate: .50),
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LinearClicks(3, clickRate: .30),
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];
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return [
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// We render an empty series on the primary measure axis to ensure that
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// the axis itself gets rendered. This helps us draw the gridlines on the
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// chart.
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charts.Series<LinearClicks, int>(
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id: 'Fake Series',
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: []),
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charts.Series<LinearClicks, int>(
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id: 'Desktop',
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colorFn: (_, __) => charts.MaterialPalette.blue.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeDesktopData,
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)
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// Set the 'Desktop' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 1'),
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charts.Series<LinearClicks, int>(
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id: 'Tablet',
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colorFn: (_, __) => charts.MaterialPalette.red.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeTabletData,
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)
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// Set the 'Tablet' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 2'),
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charts.Series<LinearClicks, int>(
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id: 'Mobile',
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colorFn: (_, __) => charts.MaterialPalette.green.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeMobileData,
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)
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// Set the 'Mobile' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 3'),
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charts.Series<LinearClicks, int>(
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id: 'Click Rate',
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colorFn: (_, __) => charts.MaterialPalette.purple.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeClickRateData,
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)
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// Set the 'Click Rate' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 4'),
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];
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}
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// EXCLUDE_FROM_GALLERY_DOCS_END
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@override
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Widget build(BuildContext context) {
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return charts.LineChart(seriesList,
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animate: animate,
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// Configure a primary measure axis that will render gridlines across
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// the chart. This axis uses fake ticks with no labels to ensure that we
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// get 5 grid lines.
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//
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// We do this because disjoint measure axes do not draw any tick
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// elements on the chart.
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primaryMeasureAxis: const charts.NumericAxisSpec(
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tickProviderSpec: charts.StaticNumericTickProviderSpec(
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// Create the ticks to be used the domain axis.
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<charts.TickSpec<num>>[
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charts.TickSpec(0, label: ''),
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charts.TickSpec(1, label: ''),
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charts.TickSpec(2, label: ''),
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charts.TickSpec(3, label: ''),
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charts.TickSpec(4, label: ''),
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],
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)),
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// Create one disjoint measure axis per series on the chart.
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//
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// Disjoint measure axes will be used to scale the rendered data,
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// without drawing any tick elements on either side of the chart.
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disjointMeasureAxes:
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LinkedHashMap<String, charts.NumericAxisSpec>.from({
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'axis 1': const charts.NumericAxisSpec(),
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'axis 2': const charts.NumericAxisSpec(),
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'axis 3': const charts.NumericAxisSpec(),
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'axis 4': const charts.NumericAxisSpec(),
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}));
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}
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/// Create one series with sample hard coded data.
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static List<charts.Series<LinearClicks, int>> _createSampleData() {
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// The first three series contain similar data with different magnitudes.
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// This demonstrates the ability to graph the trends in each series relative
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// to each other, without the largest magnitude series compressing the
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// smallest.
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final myFakeDesktopData = [
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LinearClicks(0, clickCount: 25),
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LinearClicks(1, clickCount: 125),
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LinearClicks(2, clickCount: 920),
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LinearClicks(3, clickCount: 375),
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];
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final myFakeTabletData = [
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LinearClicks(0, clickCount: 375),
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LinearClicks(1, clickCount: 1850),
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LinearClicks(2, clickCount: 9700),
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LinearClicks(3, clickCount: 5000),
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];
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final myFakeMobileData = [
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LinearClicks(0, clickCount: 5000),
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LinearClicks(1, clickCount: 25000),
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LinearClicks(2, clickCount: 100000),
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LinearClicks(3, clickCount: 75000),
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];
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// The fourth series renders with decimal values, representing a very
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// different sort ratio-based data. If this was on the same axis as any of
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// the other series, it would be squashed near zero.
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final myFakeClickRateData = [
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LinearClicks(0, clickRate: .25),
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LinearClicks(1, clickRate: .65),
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LinearClicks(2, clickRate: .50),
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LinearClicks(3, clickRate: .30),
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];
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return [
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// We render an empty series on the primary measure axis to ensure that
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// the axis itself gets rendered. This helps us draw the gridlines on the
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// chart.
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charts.Series<LinearClicks, int>(
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id: 'Fake Series',
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: []),
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charts.Series<LinearClicks, int>(
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id: 'Desktop',
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colorFn: (_, __) => charts.MaterialPalette.blue.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeDesktopData,
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)
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// Set the 'Desktop' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 1'),
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charts.Series<LinearClicks, int>(
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id: 'Tablet',
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colorFn: (_, __) => charts.MaterialPalette.red.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeTabletData,
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)
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// Set the 'Tablet' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 2'),
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charts.Series<LinearClicks, int>(
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id: 'Mobile',
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colorFn: (_, __) => charts.MaterialPalette.green.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickCount,
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data: myFakeMobileData,
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)
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// Set the 'Mobile' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 3'),
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charts.Series<LinearClicks, int>(
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id: 'Click Rate',
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colorFn: (_, __) => charts.MaterialPalette.purple.shadeDefault,
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domainFn: (LinearClicks clickCount, _) => clickCount.year,
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measureFn: (LinearClicks clickCount, _) => clickCount.clickRate,
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data: myFakeClickRateData,
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)
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// Set the 'Click Rate' series to use a disjoint axis.
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..setAttribute(charts.measureAxisIdKey, 'axis 4'),
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];
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}
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}
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/// Sample linear data type.
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class LinearClicks {
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final int year;
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final int clickCount;
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final double clickRate;
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LinearClicks(this.year, {this.clickCount, this.clickRate});
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}
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