我正在编写一个简单的数字图像处理程序。为此，我在我的 qt 应用程序中嵌入了一个 mpl 小部件。用户可以对图像执行一些简单的分析，例如 box car filter、FFT 等。在我想从显示图像切换到显示绘图之前，一切都运行良好。
如果我先显示一个图，则轴很好(请参见图像中的底部图)。但是，如果我先显示图像，然后显示绘图(图像中的顶部绘图)，则比例会压缩。
https://picasaweb.google.com/105163945296073520628/Temp <-- 抱歉我还不能发布图片
代码托管在这里 https://code.launchpad.net/~marrabld/pymi/trunk
我正在使用 imshow() 来显示图像。和 plot(x,y) 用于绘图。
这是主要的更新方法
def updateImage(self):
self.ui.mplWidget.canvas.PlotTitle = self.plotTitle
self.ui.mplWidget.canvas.xtitle = self.xTitle
self.ui.mplWidget.canvas.ytitle = self.yTitle
#self.ui.mplWidget.canvas.ax.visible(False)
self.ui.mplWidget.canvas.format_labels()
if self.projectProperty == globals.IMAGE:
if self.lastProjectProperty == globals.PLOT:
self.myImage = imageFuncs.basic(self.imageFileName)
self.imPlot = self.ui.mplWidget.canvas.ax.imshow(self.myImage.image,cmap=matplotlib.cm.gray,origin='upper')
elif self.projectProperty == globals.PLOT:
if self.lastProjectProperty == globals.IMAGE: # we need to reload the GUI
self.ui.mplWidget.canvas.ax.hold(False)
self.ui.mplWidget.canvas.ax.plot(self.xData,self.yData)
self.ui.mplWidget.canvas.draw()
还有我正在使用的mpl小部件
#!/usr/bin/env python
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
#from matplotlib.backends.backend_qt4 import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backend_bases import NavigationToolbar2
from matplotlib.figure import Figure
from matplotlib import rc
import numpy as N
class MyMplCanvas(FigureCanvas):
def __init__(self, parent=None, width = 10, height = 12, dpi = 125, sharex = None, sharey = None):
rc('text', usetex=True)
rc('font', family='sans-serif')
rc('legend',fontsize='small' )
rc('legend',shadow='true')
self.fig = Figure(figsize = (width, height), dpi=dpi, facecolor = '#FFFFFF')
self.ax = self.fig.add_subplot(111, sharex = sharex, sharey = sharey)
self.fig.subplots_adjust(left=0.15, bottom=0.15, right=0.9, top=0.9)
self.fig.add_axes(yscale='symlog')
self.xtitle=r"x-Axis"
self.ytitle=r"y-Axis"
self.PlotTitle = r"Title"
self.grid_status = True
self.xaxis_style = 'linear'
self.yaxis_style = 'linear'
#self.fig.yscale = 'log'
self.format_labels()
self.ax.hold(True)
FigureCanvas.__init__(self, self.fig)
#self.fc = FigureCanvas(self.fig)
#FigureCanvas.setSizePolicy(self,
# QSizePolicy.Expanding,
# QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
def format_labels(self):
self.ax.set_title(self.PlotTitle)
self.ax.title.set_fontsize(5)
self.ax.set_xlabel(self.xtitle, fontsize = 4)
self.ax.set_ylabel(self.ytitle, fontsize = 4)
labels_x = self.ax.get_xticklabels()
labels_y = self.ax.get_yticklabels()
for xlabel in labels_x:
xlabel.set_fontsize(4)
for ylabel in labels_y:
ylabel.set_fontsize(4)
ylabel.set_color('b')
def sizeHint(self):
w, h = self.get_width_height()
return QSize(w, h)
def minimumSizeHint(self):
return QSize(10, 10)
def sizeHint(self):
w, h = self.get_width_height()
return QSize(w, h)
def minimumSizeHint(self):
return QSize(10, 10)
#mouseClick = pyqtProperty("QPoint",mouseClick,click)
class mplWidget(QWidget):
def __init__(self, parent = None):
QWidget.__init__(self, parent)
self.canvas = MyMplCanvas()
#self.toolbar = MyNavigationToolbar(self.canvas, self.canvas, direction = 'v')
self.hbox = QHBoxLayout()
#self.hbox.addWidget(self.toolbar)
self.hbox.addWidget(self.canvas)
self.setLayout(self.hbox)
def savePlot(self,filePath):
self.canvas.fig.savefig(filePath)
def setLegend(self,handle, label):
self.canvas.fig.legend(handle,label,'upper right')
def clearPlot(self):
self.canvas.fig.clear()
width = 10
height = 12
dpi = 125
sharex = None
sharey = None
self.canvas.fig = Figure(figsize = (width, height), dpi=dpi, facecolor = '#FFFFFF')
self.canvas.ax = self.canvas.fig.add_subplot(111, sharex = sharex, sharey = sharey)
self.canvas.fig.subplots_adjust(left=0.15, bottom=0.15, right=0.9, top=0.9)
self.canvas.fig.add_axes(yscale='symlog')
self.canvas.xtitle=r"x-Axis"
self.canvas.ytitle=r"y-Axis"
self.canvas.PlotTitle = r"Title"
self.canvas.grid_status = True
self.canvas.xaxis_style = 'linear'
self.canvas.yaxis_style = 'linear'
#self.fig.yscale = 'log'
self.canvas.format_labels()
self.canvas.ax.hold(True)
FigureCanvas.__init__(self.canvas, self.canvas.fig)
#self.fc = FigureCanvas(self.fig)
FigureCanvas.setSizePolicy(self,
QSizePolicy.Expanding,
QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
任何帮助将不胜感激。
请您参考如下方法:
您可以使用 imshow() 的 aspect 参数来调整高度和重量之间的比例:
from pylab import *
a = np.zeros((100,10)) # height=100, weight=10
subplot(211)
imshow(a) # ratio = 10
subplot(212)
imshow(a, aspect=0.1) # ratio = 1
show()
但它会拉伸(stretch)图像。
或者你可以使用 xlim(), ylim() 来设置 x-y 轴的范围。
imshow(a)
xlim(-50,50)
编辑:
imshow() 会将 ax 的 aspect 属性设置为“equal”。你需要在调用 plot() 之前重置它:
self.ui.mplWidget.canvas.ax.set_aspect("auto")
self.ui.mplWidget.canvas.ax.plot(self.xData,self.yData)
