Matplotlib - 两个问题:共享色条/标签不显示
我终于把我想要的三个图放到一个图里,做成了三个子图……现在我需要加一个公共的颜色条,最好是横着的。而且,因为我把它们做成了子图,之前的标签也没了。
看起来例子里建议我 添加一个坐标轴,但我不太明白参数里的数字是什么意思。
def plot_that_2(x_vals, y_vals, z_1_vals, z_2_vals, z_3_vals, figname, units, efficiency_or_not):
global letter_pic_width
plt.close() #I moved this up from the end of the file because it solved my QTagg problem
UI = [uniformity_calc(z_1_vals), uniformity_calc(z_2_vals), uniformity_calc(z_3_vals)]
ranges = [ str(int(np.max(z_1_vals) - np.min(z_1_vals))), str(int(np.max(z_2_vals) - np.min(z_2_vals))), str(int(np.max(z_3_vals) - np.min(z_3_vals)))]
z_vals = [z_1_vals, z_2_vals, z_3_vals]
fig = plt.figure(figsize = (letter_pic_width, letter_pic_width/3 ))
ax0 = fig.add_subplot(1,3,1, aspect = 1)
ax1 = fig.add_subplot(1,3,2, aspect = 1)
ax2 = fig.add_subplot(1,3,3, aspect = 1)
axenames = [ax0, ax1, ax2]
for z_val, unif, rangenum, ax in zip(z_vals, UI, ranges, axenames):
ax.scatter(x_vals, y_vals, c = z_val, s = 100, cmap = 'rainbow')
if efficiency_or_not:
ax.vmin = 0
ax.vmax = 1
ax.xlabel = 'Uniformity: ' + unif
else:
ax.xlabel = 'Uniformity: ' + unif + ' ' + rangenum + ' ppm'
plt.savefig('./'+ figname + '.jpg', dpi = 100)
2 个回答
2
关于你问的颜色条轴,数字代表的是
[bottom_left_x_coord, bottom_left_y_coord, width, height]
一个合适的颜色条可能是
# x y w h
[0.2, 0.1, 0.6, 0.05]
这是你的代码,稍微修改了一下,增加了颜色条:
import numpy as np
import matplotlib.pyplot as plt
WIDTH = 9
def uniformity_calc(x):
return x.mean()
def plotter(x, y, zs, name, units, efficiency=True):
fig, axarr = plt.subplots(1, 3, figsize=(WIDTH, WIDTH/3),
subplot_kw={'aspect':1})
fig.suptitle(name)
UI = map(uniformity_calc, zs)
ranges = map(lambda x: int(np.max(x)-np.min(x)), zs)
for ax, z, unif, rangenum in zip(axarr, zs, UI, ranges):
scat = ax.scatter(x, y, c=z, s=100, cmap='rainbow')
label = 'Uniformity: %i'%unif
if not efficiency:
label += ' %i ppm'%rangenum
ax.set_xlabel(label)
# Colorbar [left, bottom, width, height
cax = fig.add_axes([0.2, 0.1, 0.6, 0.05])
cbar = fig.colorbar(scat, cax, orientation='horizontal')
cbar.set_label('This is a colorbar')
plt.show()
def main():
x, y = np.meshgrid(np.arange(10), np.arange(10))
zs = [np.random.rand(*y.shape) for _ in range(3)]
plotter(x.flatten(), y.flatten(), zs, 'name', None)
if __name__ == "__main__":
main()