PyQtGraph - 获取图像视图的前台角色
下面的文章讨论了我们如何在 PyQTGaph 中获得图像视图对象的前景角色。图像视图中基本上有两种角色,一种是前景,另一种是背景。前景角色定义了用于绘制前景的图像视图调色板的颜色。
PyQtGraph 是一个图形和用户界面Python库,用于设计和科学应用程序中通常需要的功能。它提供了用于显示数据(绘图、视频等)的快速交互式图形。实现许多功能,例如显示 2D 和 3D 图像数据。对于 3D 数据,会显示一个 z 轴滑块,允许用户选择要显示的帧。显示具有定义暗/亮级别和可编辑渐变的可移动区域的图像数据的直方图,提供颜色查找表供参考。
用于创建图像视图 ImageView() 被使用
句法:
imv = pg.ImageView()
为了获取前景角色,我们使用 foregroundRole() 方法和图像视图对象。它不接受任何参数并返回一个 QPalette 对象。
句法 :
imv.foregroundRole()
执行:
Python3
# importing Qt widgets
from PyQt5.QtWidgets import *
# importing system
import sys
# importing numpy as np
import numpy as np
# importing pyqtgraph as pg
import pyqtgraph as pg
from PyQt5.QtGui import *
from PyQt5.QtCore import *
# Image View class
class ImageView(pg.ImageView):
# constructor which inherit original
# ImageView
def __init__(self, *args, **kwargs):
pg.ImageView.__init__(self, *args, **kwargs)
class Window(QMainWindow):
def __init__(self):
super().__init__()
# setting title
self.setWindowTitle("PyQtGraph")
# setting geometry
self.setGeometry(100, 100, 600, 500)
# icon
icon = QIcon("skin.png")
# setting icon to the window
self.setWindowIcon(icon)
# calling method
self.UiComponents()
# showing all the widgets
self.show()
# setting fixed size of window
#self.setFixedSize(QSize(600, 500))
# method for components
def UiComponents(self):
# creating a widget object
widget = QWidget()
# creating a label
label = QLabel("Geeksforgeeks Image View")
# setting minimum width
label.setMinimumWidth(130)
# making label do word wrap
label.setWordWrap(True)
# setting configuration options
pg.setConfigOptions(antialias=True)
# creating image view view object
imv = ImageView()
# Create random 3D data set with noisy signals
img = pg.gaussianFilter(np.random.normal(size=(200, 200)), (5, 5)) * 20 + 100
# setting new axis to image
img = img[np.newaxis, :, :]
# decay data
decay = np.exp(-np.linspace(0, 0.3, 100))[:, np.newaxis, np.newaxis]
# random data
data = np.random.normal(size=(100, 200, 200))
data += img * decay
data += 2
# adding time-varying signal
sig = np.zeros(data.shape[0])
sig[30:] += np.exp(-np.linspace(1, 10, 70))
sig[40:] += np.exp(-np.linspace(1, 10, 60))
sig[70:] += np.exp(-np.linspace(1, 10, 30))
sig = sig[:, np.newaxis, np.newaxis] * 3
data[:, 50:60, 30:40] += sig
# setting image to image view
# Displaying the data and assign each frame a time value from 1.0 to 3.0
imv.setImage(data, xvals=np.linspace(1., 3., data.shape[0]))
## Set a custom color map
colors = [
(0, 0, 0),
(4, 5, 61),
(84, 42, 55),
(15, 87, 60),
(208, 17, 141),
(255, 255, 255)
]
# color map
cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color=colors)
# setting color map to the image view
imv.setColorMap(cmap)
# Creating a grid layout
layout = QGridLayout()
# minimum width value of the label
label.setFixedWidth(130)
# setting this layout to the widget
widget.setLayout(layout)
# adding label in the layout
layout.addWidget(label, 1, 0)
# plot window goes on right side, spanning 3 rows
layout.addWidget(imv, 0, 1, 3, 1)
# setting this widget as central widget of the main widow
self.setCentralWidget(widget)
# getting foreground role of the image view
value = imv.foregroundRole()
# setting text to the label
label.setText("Foreground Role : " + str(value))
# create pyqt5 app
App = QApplication(sys.argv)
# create the instance of our Window
window = Window()
# start the app
sys.exit(App.exec())
输出 :