numpy 2d直方图的标准偏差

Question

给定一系列 2d 坐标以及每个坐标的加权值，是否有一种方法可以使用 numpy histrogram2d 方法确定每个 bin 中的标准偏差？

Answer 1

Not Sure what are you asking, could you post your code?

I generally plot std on hist drawing verticals lines as follows:

plt.axvline(x=np.mean(data)-np.std(data), ls = "--", color='#2ca02c', alpha=0.7)
plt.axvline(x=np.mean(data)+np.std(data), ls = "--", color='#2ca02c', alpha=0.7)

Where "data" is a dictionary with all the values

Answer 2

It's not directly possible with numpy's histrogram2d but with scipy.stats.binned_statistic_2d it can be done quite easily.

from scipy import stats

x = np.random.rand(10000)
y = np.random.rand(10000)
z = np.random.rand(10000)
binx = np.linspace(0,x.max(), 100)
biny = np.linspace(0,y.max(), 100)
hist = stats.binned_statistic_2d(x, y, z, statistic='std', bins=[binx, biny])
plot_x, plot_y = np.meshgrid(binx, biny)

fig, ax = plt.subplots(figsize=(5,5))
pc = ax.pcolormesh(plot_x, plot_y, hist[0].T, cmap="inferno")
ax.set_aspect('equal')
cbar=fig.colorbar(pc,shrink=0.725)
fig.tight_layout()

The statistic option can also take different things like mean , median or a user-defined function, see the documentation for more details.