# 随机热力图：imshow
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']
'''
# ===========随机热力图==========
x = np.random.rand(10)
y = np.random.rand(10)
z = (np.random.rand(9000000) + np.linspace(0, 1, 9000000)
).reshape(3000, 3000) # reshape函数将原矩阵A，重组为新矩阵B
im = plt.imshow(z, interpolation='nearest', cmap='hot',
extent=(np.amin(x), np.amax(x), np.amin(
y), np.amax(y)) # 设置坐标轴范围
)
plt.colorbar(im, shrink=0.5) # 设置Bar
plt.show() '''
def Imshow_heatmap(data, xlabel, ylabel): # imshow绘制矩阵随机热力图
# 使用figure
# plt.figure(facecolor='w')
#plt.subplot(111, position=[0.1, 0.15, 0.8, 0.8])
plt.yticks(range(len(ylabel)), ylabel)
plt.xticks(range(len(xlabel)), xlabel)
'''
# 使用Figure显式的创建Axes
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, position=[0.1, 0.15, 0.8, 0.8])
ax.set_yticks(range(len(ylabel)))
ax.set_yticklabels(ylabel) # 用ylabel替代y坐标值
ax.set_xticks(range(len(xlabel)))
ax.set_xticklabels(xlabel) # 用xlabel替代x坐标值'''
# 求data数组的最小值和最大值
vmax, vmin = data[0][0], data[0][0]
for i in data:
if min(i) < vmin:
vmin = min(i)
if max(i) > vmax:
vmax = max(i)
map = plt.imshow(data, interpolation='nearest',
cmap='summer', vmin=vmin, vmax=vmax)
plt.colorbar(map, shrink=0.5)
plt.show()
if __name__ == "__main__":
data = np.random.rand(10, 10)
xlabel = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J']
ylabel = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
Imshow_heatmap(data, xlabel, ylabel)
