QwtPyPlot — Matplotlib-Style Plotting Interface¶

QwtPyPlot is a high-level wrapper class in Qwt 7 that provides a pyplot-like plotting interface for C++ users familiar with matplotlib. It delegates internally to QwtFigure, QwtPlot, QwtPlotFactory, QwtPlotStyling, and other existing classes without modifying any underlying implementation.

Overview¶

classDiagram
    class QwtPyPlot {
        +QwtPyPlot(QwtFigure*)
        +QwtPyPlot(QwtPlot*)
        +gcf() QwtFigure*
        +gca() QwtPlot*
        +sca(QwtPlot*)
        +subplot(rows, cols, index)
        +plot(x, y, fmt)
        +scatter(x, y, size, color)
        +bar(values, color)
        +hist(data, bins, color)
        +imshow(data, cmap)
        +contour(data, levels)
        +fillBetween(x, y1, y2)
        +setTitle(title)
        +setXLim(min, max)
        +grid(show)
        +legend()
        +savefig(filename, dpi)
        +show()
    }

    class QwtFormatString {
        +parse(fmt) QwtFormatString
        +color
        +marker
        +lineStyle
        +noLine
    }

    QwtPyPlot ..> QwtFigure : wraps
    QwtPyPlot ..> QwtPlot : operates on
    QwtPyPlot ..> QwtPlotFactory : delegates
    QwtPyPlot ..> QwtPlotStyling : delegates
    QwtPyPlot ..> QwtFormatString : parses

Class	Responsibility	Header
`QwtPyPlot`	Matplotlib pyplot-style plotting interface	`<QwtPyPlot>`
`QwtFormatString`	Matplotlib format string parser	`<QwtPyPlot>`

Core Concepts¶

QwtPyPlot maintains a "current axes" pointer (similar to matplotlib's gca()), so all plotting methods operate on the current axes:

matplotlib Concept	QwtPyPlot / Qwt Equivalent
`matplotlib.figure.Figure`	`QwtFigure`
`matplotlib.axes.Axes`	`QwtPlot`
`pyplot` module	`QwtPyPlot` class
`plt.gcf()` / `plt.gca()`	`QwtPyPlot::gcf()` / `gca()`
`plt.subplot()`	`QwtPyPlot::subplot(rows, cols, index)`
`fig.savefig()`	`QwtPyPlot::savefig(filename, dpi)`

Two Usage Modes¶

Mode 1: QwtFigure Multi-Subplot Mode¶

#include <QwtFigure>
#include <QwtPyPlot>

QwtFigure* fig = new QwtFigure;
QwtPyPlot plt(fig);

// Create subplot 1 in a 2×1 grid
plt.subplot(2, 1, 1);
plt.plot(x, y, "r-o", "Temperature");
plt.setTitle("Sensor Data");
plt.grid(true);
plt.legend();

// Create subplot 2
plt.subplot(2, 1, 2);
plt.bar({10, 20, 30, 40}, "b", "Sales");
plt.setYLabel("Value");

plt.savefig("output.png", 300);
fig->show();

Mode 2: QwtPlot Single-Plot Mode¶

#include <QwtPlot>
#include <QwtPyPlot>

QwtPlot* plot = new QwtPlot;
QwtPyPlot plt(plot);

plt.plot(x, y, "b--");
plt.scatter(x2, y2, 50, "r");
plt.setTitle("Quick Plot");

plot->show();

Format Strings¶

QwtFormatString parses matplotlib-style format strings, supporting combinations of color, marker, and line style:

Format: [color][line_style][marker]
Examples: "r-o"  → red solid line + circle marker
          "b--"  → blue dashed line
          "g^:"  → green dotted line + upward triangle
          "ko"   → black circles (no line)

Color Characters¶

Char	Color	Char	Color
`b`	Blue	`m`	Magenta
`g`	Green	`y`	Yellow
`r`	Red	`k`	Black
`c`	Cyan	`w`	White

Marker Characters¶

Char	Marker	Char	Marker
`o`	Circle	`x`	Cross (×)
`s`	Square	`+`	Plus (+)
`^`	Triangle up	`*`	Star
`v`	Triangle down	`.`	Dot
`D`	Diamond

Line Styles¶

Symbol	Style
`-`	Solid
`--`	Dashed
`-.`	Dash-dot
`:`	Dotted

Matplotlib Behavior

When only a marker is specified without a line style (e.g. "ro"), the line is automatically hidden, showing only marker points. This matches matplotlib behavior.

Plotting Methods¶

Basic Plots¶

plot() — Line Plot¶

// y-only (x auto-generated as 0, 1, 2, ...)
plt.plot({1, 4, 2, 5}, "r-o");

// x-y data
plt.plot(x, y, "b--", "Label");

// QPointF data
QVector<QPointF> data = {{0,1}, {1,3}, {2,2}};
plt.plot(data, "g^:");

scatter() — Scatter Plot¶

// Parameters: x, y, marker size, color, label
plt.scatter(x1, y1, 30, "r", "Group A");
plt.scatter(x2, y2, 50, "b", "Group B");

bar() — Bar Chart¶

// y-only values (x = index)
plt.bar({10, 20, 30, 40}, "c");

// x-y data with width
plt.bar(x, values, 0.8, "b", "Sales");

hist() — Histogram¶

// Automatic binning (default 10 bins)
plt.hist(data, 20, "m", "Distribution");

imshow() — Heatmap¶

// 2D matrix data with various colormaps
QVector<QVector<double>> matrix = ...;
plt.imshow(matrix, "viridis");

Supported colormaps: "viridis", "hot", "cool", "jet", "gray"

contour() — Contour Lines¶

// Auto-generate 10 contour levels
plt.contour(data);

// Custom contour levels
plt.contour(data, {0.2, 0.4, 0.6, 0.8}, "hot");

fillBetween() — Filled Area¶

// Parameters: x, y1, y2, color, alpha
plt.fillBetween(x, yLower, yUpper, "blue", 0.3);

errorbar() — Error Bars¶

plt.errorbar(x, y, yerr, "r-", "Measurement");

quiver() — Vector Field¶

plt.quiver(x, y, u, v, "k");

candlestick() — OHLC Chart¶

QVector<QwtOHLCSample> ohlcData = ...;
plt.candlestick(ohlcData, "Stock");

Decorative Elements¶

Method	Description	Example
`grid(show, minor)`	Grid lines	`plt.grid(true, true)`
`axhline(y, fmt)`	Horizontal reference line	`plt.axhline(0, "k--")`
`axvline(x, fmt)`	Vertical reference line	`plt.axvline(5, "r:")`
`axhspan(y1, y2, color, alpha)`	Horizontal zone highlight	`plt.axhspan(2, 4, "yellow", 0.2)`
`axvspan(x1, x2, color, alpha)`	Vertical zone highlight	`plt.axvspan(3, 7, "blue", 0.1)`
`legend(loc)`	Legend	`plt.legend()`
`annotate(text, xy, xytext)`	Arrow annotation	`plt.annotate("Peak", peak, label)`

Axis Configuration¶

Titles and Labels¶

plt.setTitle("My Plot");
plt.setXLabel("Time (s)");
plt.setYLabel("Amplitude");

Axis Limits and Scale¶

// Set axis limits
plt.setXLim(0, 100);
plt.setYLim(-5, 5);

// Logarithmic scale
plt.setXScale("log");
plt.setYScale("log");

// Back to linear
plt.setXScale("linear");

Ticks¶

// Custom tick positions
plt.setXTicks({0, 2.5, 5, 7.5, 10});
plt.setYTicks({-1, 0, 1});

// Invert axis direction
plt.invertXAxis();
plt.invertYAxis();

Figure Operations¶

Subplot Layout¶

QwtFigure* fig = new QwtFigure;
QwtPyPlot plt(fig);

// subplot(rows, cols, index) — 1-based index
plt.subplot(2, 2, 1);  // Row 1, Column 1
plt.subplot(2, 2, 2);  // Row 1, Column 2
plt.subplot(2, 1, 2);  // Row 2, spans 2 columns

Twin Axes (Dual Y/X)¶

plt.subplot(1, 1, 1);
plt.plot(x, temp, "r-", "Temperature");
plt.setYLabel("°C");

// Create twin Y-axis on right
QwtPlot* ax2 = plt.twinx();
plt.sca(ax2);  // Switch to new axes
plt.plot(x, humidity, "b--", "Humidity");
plt.setYLabel("%");

Tight Layout¶

plt.tightLayout();  // Align Y-axes across all subplots

Appearance¶

// Set figure background color
plt.setFaceColor("lightgray");

// Set canvas background color
plt.setAxesColor("white");

Output and Interaction¶

Save to File¶

plt.savefig("output.png");        // Default DPI
plt.savefig("output.png", 300);   // 300 DPI

Show Window¶

plt.show();

Interaction Controls¶

plt.enablePan(true);   // Enable drag panning
plt.enableZoom(true);  // Enable rubber-band zoom

Complete Example¶

The following example demonstrates a multi-subplot application with line plots, scatter plots, and histograms:

#include <QApplication>
#include <QwtFigure>
#include <QwtPyPlot>
#include <cmath>

int main(int argc, char* argv[])
{
    QApplication app(argc, argv);

    QwtFigure* fig = new QwtFigure;
    QwtPyPlot plt(fig);

    // Generate data
    QVector<double> x, sinY, cosY;
    for (int i = 0; i <= 100; i++) {
        double t = i * 0.1;
        x.append(t);
        sinY.append(std::sin(t));
        cosY.append(std::cos(t));
    }

    // Subplot 1: Line plot
    plt.subplot(2, 1, 1);
    plt.plot(x, sinY, "r-", "sin(x)");
    plt.plot(x, cosY, "b--", "cos(x)");
    plt.setTitle("Trigonometric Functions");
    plt.grid(true);
    plt.legend();

    // Subplot 2: Histogram
    plt.subplot(2, 1, 2);
    QVector<double> randomData;
    for (int i = 0; i < 500; i++) {
        randomData.append(std::sin(i * 0.1) * 10 + (i % 7));
    }
    plt.hist(randomData, 20, "c");
    plt.setTitle("Distribution");

    plt.tightLayout();
    plt.savefig("demo.png", 300);
    fig->resize(800, 600);
    fig->show();

    return app.exec();
}

API Reference¶

Construction and State¶

Method	Description
`QwtPyPlot(QwtFigure*)`	Construct: multi-subplot mode
`QwtPyPlot(QwtPlot*)`	Construct: single-plot mode
`gcf()`	Get current Figure
`gca()`	Get current axes
`sca(QwtPlot*)`	Set current axes

Plotting Methods¶

Method	Return Type	Description
`plot(y, fmt, label)`	`QwtPlotCurve*`	Y-only line plot
`plot(x, y, fmt, label)`	`QwtPlotCurve*`	X-Y line plot
`plot(data, fmt, label)`	`QwtPlotCurve*`	QPointF line plot
`scatter(x, y, size, color, label)`	`QwtPlotCurve*`	Scatter plot
`bar(values, color, label)`	`QwtPlotBarChart*`	Bar chart
`bar(x, values, width, color, label)`	`QwtPlotBarChart*`	X-Y bar chart
`hist(data, bins, color, label)`	`QwtPlotHistogram*`	Histogram
`boxplot(data, label)`	`QwtPlotBoxChart*`	Box plot
`fillBetween(x, y1, y2, color, alpha)`	`QwtPlotIntervalCurve*`	Filled area
`errorbar(x, y, yerr, fmt, label)`	`QwtPlotIntervalCurve*`	Error bars
`imshow(data, cmap, vmin, vmax)`	`QwtPlotSpectrogram*`	Heatmap
`contour(data, levels, cmap)`	`QwtPlotSpectrogram*`	Contour lines
`quiver(x, y, u, v, color)`	`QwtPlotVectorField*`	Vector field
`candlestick(data, label)`	`QwtPlotTradingCurve*`	OHLC chart

Axis Configuration¶

Method	Description
`setTitle(title)`	Set plot title
`setXLabel(label)`	Set X-axis label
`setYLabel(label)`	Set Y-axis label
`setXLim(min, max)`	Set X-axis limits
`setYLim(min, max)`	Set Y-axis limits
`setXScale(scale)`	Set X-axis scale (`"linear"` / `"log"`)
`setYScale(scale)`	Set Y-axis scale
`setXTicks(ticks, labels)`	Set X-axis ticks
`setYTicks(ticks, labels)`	Set Y-axis ticks
`invertXAxis()`	Invert X-axis
`invertYAxis()`	Invert Y-axis

Figure Operations¶

Method	Description
`subplot(rows, cols, index)`	Create subplot (1-based index)
`addAxes(rect)`	Add axes at normalized position
`twinx(host)`	Create twin Y-axis
`twiny(host)`	Create twin X-axis
`tightLayout()`	Apply tight layout

Output and Interaction¶

Method	Description
`savefig(filename, dpi)`	Save figure to file
`show()`	Show widget window
`enablePan(enable)`	Enable/disable panning
`enableZoom(enable)`	Enable/disable zooming

Related Examples

A complete example is located in examples/2D/pyplot/, containing 8 tabs demonstrating various QwtPyPlot features.

Screenshot of the PyPlot example:

PyPlot