示例

以下是一些当前支持的图表示例。

垂直柱状图

以下是示例代码

use charts::{Chart, VerticalBarView, ScaleBand, ScaleLinear};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that maps ["A", "B", "C"] categories to values in the [0, availableWidth]
    // range (the width of the chart without the margins).
    let x = ScaleBand::new()
        .set_domain(vec![String::from("A"), String::from("B"), String::from("C")])
        .set_range(vec![0, width - left - right])
        .set_inner_padding(0.1)
        .set_outer_padding(0.1);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0, 100])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `BarDatum` trait.
    let data = vec![("A", 90), ("B", 10), ("C", 30)];

    // Create VerticalBar view that is going to represent the data as vertical bars.
    let view = VerticalBarView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .load_data(&data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Bar Chart"))
        .add_view(&view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Units of Measurement")
        .add_bottom_axis_label("Categories")
        .save("vertical-bar-chart.svg").unwrap();
}

以下是结果

类别显示顺序由传递给set_domain方法的向量定义。如果您将此顺序更改为"A, C, B"，则结果顺序也会相应调整。

您可以通过调整set_inner_padding和set_outer_padding的值来自定义图表的外观。

垂直堆积柱状图

简单的柱状图（如上面所示）是堆叠柱状图的一个特例，其中只有一个值类型。在底层，charts对这两种类型处理得几乎一样，这就是为什么代码几乎相同，唯一的区别是输入数据必须提供一个key，以便按此键分组和堆叠值。

use charts::{Chart, VerticalBarView, ScaleBand, ScaleLinear, BarLabelPosition};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that maps ["A", "B", "C"] categories to values in [0, availableWidth]
    // range (the width of the chart without the margins).
    let x = ScaleBand::new()
        .set_domain(vec![String::from("A"), String::from("B"), String::from("C")])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in the top left corner, while chart's origin is in bottom left corner, hence we need to
    // invert the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0, 100])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `BarDatum` trait.
    let data = vec![("A", 70, "foo"), ("B", 10, "foo"), ("C", 30, "foo"), ("A", 20, "bar"), ("A", 5, "baz")];

    // Create VerticalBar view that is going to represent the data as vertical bars.
    let view = VerticalBarView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        // .set_label_visibility(false)  // <-- uncomment this line to hide bar value labels
        .set_label_position(BarLabelPosition::Center)
        .load_data(&data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Stacked Bar Chart"))
        .add_view(&view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Units of Measurement")
        .add_bottom_axis_label("Categories")
        .save("stacked-vertical-bar-chart.svg").unwrap();
}

结果

默认情况下，输入数据中键的顺序决定了堆叠顺序。然而，您可以通过在调用 load_data() 方法之前，在 VerticalBarDataset 结构体上指定不同的顺序来调整它，使用 set_keys() 方法。

// Create VerticalBar view that is going to represent the data as vertical bars.
let view = VerticalBarView::new()
    .set_x_scale(&x)
    .set_y_scale(&y)
    .set_keys(vec![String::from("foo"), String::from("baz"), String::from("bar")])
    // .set_label_visibility(false)  // <-- uncomment this line to hide bar value labels
    .set_label_position(BarLabelPosition::Center)
    .load_data(&data).unwrap();

结果是如下所示（注意第一个柱状图中顺序的变化）

散点图

use charts::{Chart, ScaleLinear, ScatterView, MarkerType, PointLabelPosition};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that will interpolate values in [0, 200] to values in the
    // [0, availableWidth] range (the width of the chart without the margins).
    let x = ScaleLinear::new()
        .set_domain(vec![0, 200])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0, 100])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let scatter_data = vec![(120, 90), (12, 54), (100, 40), (180, 10)];

    // Create Scatter view that is going to represent the data as points.
    let scatter_view = ScatterView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_label_position(PointLabelPosition::E)
        .set_marker_type(MarkerType::Square)
        .load_data(&scatter_data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Scatter Chart"))
        .add_view(&scatter_view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Custom X Axis Label")
        .add_bottom_axis_label("Custom Y Axis Label")
        .save("scatter-chart.svg").unwrap();
}

结果

您可以按照以下方式自定义外观和布局

选择标签相对于标记的显示方式。可用选项：N, NE, E, SE, S, SW, W, NW

选择点的标记类型。可用选项：方形，圆形，X

如果数据集有一个区分点的 key，您还可以使用 ScatterView 来显示它。

use charts::{Chart, ScaleLinear, ScatterView, MarkerType, Color, PointLabelPosition};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that will interpolate values in [0, 200] to values in the
    // [0, availableWidth] range (the width of the chart without the margins).
    let x = ScaleLinear::new()
        .set_domain(vec![0, 200])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0, 100])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let scatter_data = vec![(120, 90, "foo"), (12, 54, "foo"), (100, 40, "bar"), (180, 10, "baz")];

    // Create Scatter view that is going to represent the data as points.
    let scatter_view = ScatterView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_label_position(PointLabelPosition::E)
        .set_marker_type(MarkerType::Circle)
        .set_colors(Color::color_scheme_dark())
        .load_data(&scatter_data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Scatter Chart"))
        .add_view(&scatter_view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Custom X Axis Label")
        .add_bottom_axis_label("Custom Y Axis Label")
        .save("scatter-chart-multiple-keys.svg").unwrap();
}

线系列

线系列支持散点图相同的函数。

use charts::{Chart, ScaleLinear, MarkerType, PointLabelPosition, LineSeriesView};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that will interpolate values in [0, 200] to values in the
    // [0, availableWidth] range (the width of the chart without the margins).
    let x = ScaleLinear::new()
        .set_domain(vec![0_f32, 200_f32])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0_f32, 100_f32])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let line_data = vec![(12, 54), (100, 40), (120, 50), (180, 70)];

    // Create Line series view that is going to represent the data.
    let line_view = LineSeriesView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_marker_type(MarkerType::Circle)
        .set_label_position(PointLabelPosition::N)
        .load_data(&line_data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Line Chart"))
        .add_view(&line_view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Custom Y Axis Label")
        .add_bottom_axis_label("Custom X Axis Label")
        .save("line-chart.svg").unwrap();
}

面积系列

目前，AreaSeriesView 不支持具有多个键的数据集，因此无法显示堆叠面积图。

use charts::{Chart, ScaleLinear, MarkerType, PointLabelPosition, AreaSeriesView};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that will interpolate values in [0, 200] to values in the
    // [0, availableWidth] range (the width of the chart without the margins).
    let x = ScaleLinear::new()
        .set_domain(vec![12_f32, 180_f32])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0_f32, 100_f32])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let area_data = vec![(12, 54), (100, 40), (120, 50), (180, 70)];

    // Create Area series view that is going to represent the data.
    let area_view = AreaSeriesView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_marker_type(MarkerType::Circle)
        .set_label_position(PointLabelPosition::N)
        .load_data(&area_data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Area Chart"))
        .add_view(&area_view)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Custom Y Axis Label")
        .add_bottom_axis_label("Custom X Axis Label")
        .save("area-chart.svg").unwrap();
}

图表组成

一旦您了解了基本构建块（主要是 刻度 和 视图），那么您可以使用 charts 实现的内容就几乎是无限的（目前有可用的实现视图，:)）。

主要思想是使用常见的刻度实例，这些实例作为不同数据集和视图之间的共同上下文。

一个例子是将柱状图和散点图结合起来

use charts::{Chart, VerticalBarView, ScaleBand, ScaleLinear, ScatterView, MarkerType, Color, PointLabelPosition};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 50, 60);

    // Create a band scale that maps ["A", "B", "C"] categories to values in the [0, availableWidth]
    // range (the width of the chart without the margins).
    let x = ScaleBand::new()
        .set_domain(vec![String::from("A"), String::from("B"), String::from("C")])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0, 100])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `BarDatum` trait.
    let bar_data = vec![("A", 70), ("B", 10), ("C", 30)];

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let scatter_data = vec![(String::from("A"), 90.3), (String::from("B"), 20.1), (String::from("C"), 10.8)];

    // Create VerticalBar view that is going to represent the data as vertical bars.
    let bar_view = VerticalBarView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .load_data(&bar_data).unwrap();

    // Create Scatter view that is going to represent the data as points.
    let scatter_view = ScatterView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_label_position(PointLabelPosition::NE)
        .set_marker_type(MarkerType::Circle)
        .set_colors(Color::from_vec_of_hex_strings(vec!["#FF4700"]))
        .load_data(&scatter_data).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Composite Bar + Scatter Chart"))
        .add_view(&bar_view)                            // <-- add bar view
        .add_view(&scatter_view)                        // <-- add scatter view
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Units of Measurement")
        .add_bottom_axis_label("Categories")
        .save("composite-bar-and-scatter-chart.svg").unwrap();
}

结果如下所示

另一个例子是将不同的数据集结合起来。例如，我们可以定义覆盖两个数据集域的刻度，并查看它们之间的关系。

use charts::{Chart, ScaleLinear, ScatterView, MarkerType, PointLabelPosition, Color, AxisPosition};

fn main() {
    // Define chart related sizes.
    let width = 800;
    let height = 600;
    let (top, right, bottom, left) = (90, 40, 80, 60);

    // Create a band scale that will interpolate values in [0, 200] to values in the
    // [0, availableWidth] range (the width of the chart without the margins).
    let x = ScaleLinear::new()
        .set_domain(vec![0_f32, 200_f32])
        .set_range(vec![0, width - left - right]);

    // Create a linear scale that will interpolate values in [0, 100] range to corresponding
    // values in [availableHeight, 0] range (the height of the chart without the margins).
    // The [availableHeight, 0] range is inverted because SVGs coordinate system's origin is
    // in top left corner, while chart's origin is in bottom left corner, hence we need to invert
    // the range on Y axis for the chart to display as though its origin is at bottom left.
    let y = ScaleLinear::new()
        .set_domain(vec![0_f32, 100_f32])
        .set_range(vec![height - top - bottom, 0]);

    // You can use your own iterable as data as long as its items implement the `PointDatum` trait.
    let scatter_data_1 = vec![(20, 90), (12, 54), (25, 70), (33, 40)];
    let scatter_data_2 = vec![(120, 10), (143, 34), (170, 14), (190, 13)];

    // Create Scatter view that is going to represent the data as points.
    let scatter_view_1 = ScatterView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_marker_type(MarkerType::Circle)
        .set_label_position(PointLabelPosition::N)
        .set_custom_data_label("Apples".to_owned())
        .load_data(&scatter_data_1).unwrap();

    // Create Scatter view that is going to represent the data as points.
    let scatter_view_2 = ScatterView::new()
        .set_x_scale(&x)
        .set_y_scale(&y)
        .set_marker_type(MarkerType::Square)
        .set_label_position(PointLabelPosition::N)
        .set_custom_data_label("Oranges".to_owned())
        .set_colors(Color::from_vec_of_hex_strings(vec!["#aa0000"]))
        .load_data(&scatter_data_2).unwrap();

    // Generate and save the chart.
    Chart::new()
        .set_width(width)
        .set_height(height)
        .set_margins(top, right, bottom, left)
        .add_title(String::from("Scatter Chart"))
        .add_view(&scatter_view_1)
        .add_view(&scatter_view_2)
        .add_axis_bottom(&x)
        .add_axis_left(&y)
        .add_left_axis_label("Custom X Axis Label")
        .add_bottom_axis_label("Custom Y Axis Label")
        .add_legend_at(AxisPosition::Bottom)
        .save("scatter-chart-two-datasets.svg").unwrap();
}

下一步

这仍然是一个正在进行中的项目，所以下一步将是实现更多的视图和改进现有功能。