matplotlib作为Python中著名的数据可视化工具，其官网也提供了在PyQt4中使用的源码，这里举一个应用实例，以备不时之需。
1) 利用Qt Designer创建GUI界面
Demo的GUI界面，如图1所示，其中利用QFrame作为放置matplotlib界面的容器。然后调用pyuic4.bat -o ui_maindialog.py maindialog.ui编译UI界面。
图1 GUI设计界面
2) maindialog.py程序代码
#!/usr/bin/env python
#-*- coding: utf-8 -*- import numpy as np
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from ui_maindialog import Ui_MainDialog
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas # matplotlib对PyQt4的支持
from matplotlib.figure import Figure class MainDialog(QDialog, Ui_MainDialog):
def __init__(self, parent=None):
super(MainDialog, self).__init__(parent)
self.setupUi(self)
self._createFigures()
self._createLayouts()
# 创建matplotlib的画布
def _createFigures(self):
self._fig = Figure(figsize=(8, 6), dpi=100, tight_layout=True)
self._fig.set_facecolor("#F5F5F5") # 背景色
self._fig.subplots_adjust(left=0.08, top=0.92, right=0.95, bottom=0.1) # Margins
self._canvas = FigureCanvas(self._fig) # 画布
self._ax = self._fig.add_subplot(111) # 增加subplot
self._ax.hold(True)
self._initializeFigure() def _createLayouts(self):
layout = QHBoxLayout(self.frame)
layout.setContentsMargins(0, 0, 0, 0)
layout.addWidget(self._canvas) # Add Matplotli def _initializeFigure(self):
Font = {'family': 'Tahoma',
'weight': 'bold',
'size': 10}
# Abscissa
self._ax.set_xlim([380, 780])
self._ax.set_xticks([380, 460, 540, 620, 700, 780])
self._ax.set_xticklabels([380, 460, 540, 620, 700, 780], fontdict=Font)
self._ax.set_xlabel("Wavelength (nm)", fontdict=Font)
# Ordinate
self._ax.set_ylim([0.0, 1.0])
self._ax.set_yticks(np.arange(0.0, 1.1, 0.2))
self._ax.set_yticklabels(np.arange(0.0, 1.1, 0.2), fontdict=Font)
self._ax.set_ylabel("Spectral Radiance (W/(m$^2$*sr*nm))", fontdict=Font) self._ax.grid(True) # Grid On def _updateFigures(self):
Font = {'family': 'Tahoma',
'weight': 'bold',
'size': 10} self._ax.clear() maxY = 0.0 x = np.arange(380, 781)
y = np.random.rand(401) self._ax.plot(x, y, 'r', label="Data")
maxY = max(y)
if maxY <= 0:
self._initializeFigure()
else:
self._fig.subplots_adjust(left=0.11, top=0.92, right=0.95, bottom=0.1)
# Abscissa
self._ax.set_xlim([380, 780])
self._ax.set_xticks([380, 460, 540, 620, 700, 780])
self._ax.set_xticklabels([380, 460, 540, 620, 700, 780], fontdict=Font)
self._ax.set_xlabel("Wavelength (nm)", fontdict=Font)
# Ordinate
self._ax.set_ylim([0.0, maxY])
self._ax.set_yticks([0.0, maxY / 4.0, maxY / 2.0, maxY * 3 / 4.0, maxY])
self._ax.set_yticklabels(
["%.1e" % 0.0, "%.1e" % (maxY / 4.0), "%.1e" % (maxY / 2.0), "%.1e" % (maxY * 3.0 / 4.0),
"%.1e" % maxY], fontdict=Font)
self._ax.set_ylabel("Spectral Radiance (W/(m$^2$*sr*nm))", fontdict=Font) self._ax.grid(True)
self._ax.legend(loc="best", fontsize="small").draggable(state=True) # Legend
self._canvas.draw() @pyqtSlot()
def on_plotPushButton_clicked(self):
self._updateFigures()
初始界面如图2所示：
图2 GUI初始界面
3) 点击plot按键后
界面显示见图3：
图3 点击Plot按键后界面