如何对放大的绘图区域进行计算

Question

I have a time series plot along with a scatter plot on top to indicate some points of the series with certain characteristics. On jupyter notebook I am using %matplotlib notebook to get interaction plot and zoom.

Is it possible to calculate all points

EDIT : The following code is a dummy example of ploting radnom data and marking with red dots those point where their value is above a certain threshold.

%matplotlib notebook
# generate random data [0, 10]
random_data = np.random.randint(10, size = 20)
#  implement rule --> i.e. check which data point is > 3
index = np.where([random_data > 3])[1]
value = np.where([random_data > 3])[0]

# plot data and mark data point where rule applies
plt.plot(random_data)
plt.scatter(index, random_data[index], c = 'r') 

This generates the plot below.

Is it possible to to get a result that calculates the red dots every time i zoom in the plot

Answer 1

So after a lot of search I came up with the following solution.

%matplotlib notebook
# generate random data [0, 10]
random_data = np.random.randint(10, size = 20)
#  implement rule --> i.e. check which data point is > 3
index = np.where([random_data > 3])[1]
value = np.where([random_data > 3])[0]

# plot data and mark data point where rule applies
fig, ax = plt.subplots(1,1)
ax.plot(random_data)
ax.scatter(index, random_data[index], c = 'r') 

global scatter_index
scatter_data = index
def on_xlims_change(axes):
    d1, d2 = axes.get_xlim()
    number_of_points = index[np.where((index > d1 )& (index < d2))].shape[0]
    axes.legend([f'{ number_of_points  } numbers of points in area' ])

# use a maplotlib callback to do the calculation
ax.callbacks.connect('xlim_changed', on_xlims_change)

The idea is that you can use a callback to get the new axis limits and filter data based on those limits. Hope