pyqtgraph heapmap 热图 伪彩色

如何设置？

核心代码：

self.IVNetwork = pg.ImageView()
self.IVNetwork.ui.menuBtn.setVisible(False)
self.IVNetwork.ui.roiBtn.setVisible(False)
# self.IVNetwork.ui.histogram.setVisible(False)


self.winDDD.verticalLayout_11.addWidget(self.IVNetwork)

self.IVNetwork.setImage(dynamicMI)
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)
self.IVNetwork.setColorMap(cmap)

示例代码：

def slotCreateDDD(self):
    # "创建Dynamics Degree Distribution Windows"
    # 默认 Dynamic of MI 的matlab矩阵已经算好了
    self.winDDD = uic.loadUi(r'./GUI/DynamiceDegreeDistribution.ui')
    self.winDDD.setWindowTitle("Dynamic of degree distribution")

    self.IVDistribution = pg.ImageView()
    self.IVDistribution.ui.menuBtn.setVisible(False)
    self.IVDistribution.ui.roiBtn.setVisible(False)
    self.IVDistribution.ui.histogram.setVisible(False)

    self.IVNetwork = pg.ImageView()
    self.IVNetwork.ui.menuBtn.setVisible(False)
    self.IVNetwork.ui.roiBtn.setVisible(False)
    # self.IVNetwork.ui.histogram.setVisible(False)

    self.winDDD.verticalLayout_4.addWidget(self.IVDistribution)
    self.winDDD.verticalLayout_11.addWidget(self.IVNetwork)

    # 加载提前计算好的Dynamics of MI array
    dynamicMatrixDataPath = r'D:\PythonProject\QTNLS\TNCalciumAnalysis\dynamicMI.mat'
    mat = scio.loadmat(dynamicMatrixDataPath)
    dynamicMI = mat['dynamicMI']

    #设置成热图  有些问题，不好好搞。pyqtGraph的API设计得不行。
    self.IVNetwork.setImage(dynamicMI)
    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)
    self.IVNetwork.setColorMap(cmap)

    #请把distribution也渲染出来；
    dynamicDistribution = None
    #先打印出来把

    frames = dynamicMI.shape[0]
    numNeurons = dynamicMI.shape[1]
    thres = 3.1

    dynamicDistribution = np.ones((frames, 512, 512, 4))
    dynamicDistributionDataPath = r'D:\PythonProject\QTNLS\resources\dynamicDistribution.npy'
    if os.path.exists(dynamicDistributionDataPath):
        dynamicDistribution = np.load(dynamicDistributionDataPath)
    else:
        for t in range(frames):
            print(t)
            G = nx.Graph()
            for i in range(numNeurons):
                for j in range(i, numNeurons):
                    if dynamicMI[t,i,j] > thres:
                        G.add_edge(i,j)
            # print(G.degree())
            degree_sequence = sorted([d for n, d in G.degree()], reverse=True)
            fig, ax = plt.subplots(figsize=(4, 4), dpi=128)
            ax.bar(*np.unique(degree_sequence, return_counts=True))
            ax.set_xlim(xmin = 0, xmax = numNeurons)#度分布，最大的度就是所有人都连上了
            ax.set_ylim(ymin = 0, ymax = 15)#度分布，最大的度就是所有人都连上了
            ax.set_title("Degree histogram")
            ax.set_xlabel("Degree")
            ax.set_ylabel("# of Nodes")

            buf = io.BytesIO()
            fig.savefig(buf, format='raw', dpi=128)
            buf.seek(0)
            img_arr = np.frombuffer(buf.getvalue(), dtype=np.uint8)
            buf.close()

            plt.cla()
            plt.close("all")

            w, h = fig.canvas.get_width_height()
            im = img_arr.reshape((int(h), int(w), -1))
            im = im.transpose((1, 0, 2))
            dynamicDistribution[t,:,:,:] = im
        np.save(dynamicDistributionDataPath,dynamicDistribution)
    self.IVDistribution.setImage(dynamicDistribution)
    self.winDDD.show()