Matplotlib作為Python中著名的數據可視化工具，其官網也提供了在PyQt4中使用的源碼，這裡舉一個應用實例，以備不時之需。
1) 利用Qt Designer創建GUI界面
Demo的GUI界面，如圖1所示，其中利用QFrame作為放置Matplotlib界面的容器。然後調用pyuic4.bat -o ui_maindialog.py maindialog.ui編譯UI界面。
圖1 GUI設計界面
2) maindialog.py程序代碼
#!/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對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()
# 創建Matplotlib的畫布
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) # 四周Margin
self._canvas = FigureCanvas(self._fig) # 畫布
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()
初始界面如圖2所示：
圖2 GUI初始界面
3) 點擊plot按鍵後
界面顯示見圖3：
圖3 點擊Plot按鍵後界面