pyqtgraph只使用image view进行热图的可视化展示 (一个脚本)创建一个窗口
pyqtgraph只使用image view进行热图的可视化展示
"""
import scipy.io as scio
import numpy as np
import pyqtgraph as pg
from PyQt5 import QtCore, QtGui
from PyQt5.QtWidgets import *
from PyQt5 import uic
if __name__ == '__main__':
#
import sys
app = QApplication(sys.argv)
print("对参与同步簇点火的神经元进行Sorting")
data = np.array([[i for i in range(255)] for _ in range(255)])
# 可视化
winHeatmap = uic.loadUi(r'../GUI/Empty.ui')
winHeatmap.setFixedSize(2000, 400)
ivHeatmap = pg.ImageView()
winHeatmap.verticalLayout_2.addWidget(ivHeatmap)
ivHeatmap.setImage(data)
colors = [(48, 18, 59), (62, 155, 254), (70, 247, 131), (225, 220, 55), (239, 90, 17), (122, 4, 3), ]
cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color=colors)
ivHeatmap.setColorMap(cmap)
winHeatmap.setWindowTitle("The heatmap of neurons.\t{}".format("traceMatPath"))
winHeatmap.show()
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()

---------
和人家提供的exapmle类似
# -*- coding: utf-8 -*-
"""
This example demonstrates the use of ImageView, which is a high-level widget for
displaying and analyzing 2D and 3D data. ImageView provides:
1. A zoomable region (ViewBox) for displaying the image
2. A combination histogram and gradient editor (HistogramLUTItem) for
controlling the visual appearance of the image
3. A timeline for selecting the currently displayed frame (for 3D data only).
4. Tools for very basic analysis of image data (see ROI and Norm buttons)
"""
## Add path to library (just for examples; you do not need this)
import initExample
import numpy as np
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph as pg
# Interpret image data as row-major instead of col-major
pg.setConfigOptions(imageAxisOrder='row-major')
app = QtGui.QApplication([])
## Create window with ImageView widget
win = QtGui.QMainWindow()
win.resize(800,800)
imv = pg.ImageView()
win.setCentralWidget(imv)
win.show()
win.setWindowTitle('pyqtgraph example: ImageView')
## Create random 3D data set with noisy signals
img = pg.gaussianFilter(np.random.normal(size=(200, 200)), (5, 5)) * 20 + 100
img = img[np.newaxis,:,:]
decay = np.exp(-np.linspace(0,0.3,100))[:,np.newaxis,np.newaxis]
data = np.random.normal(size=(100, 200, 200))
data += img * decay
data += 2
## Add 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
## Display 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),
(45, 5, 61),
(84, 42, 55),
(150, 87, 60),
(208, 171, 141),
(255, 255, 255)
]
cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color=colors)
imv.setColorMap(cmap)
## Start Qt event loop unless running in interactive mode.
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
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