使用标准化 x 轴在同一 x 轴上绘制多条线

Question

I have a data frame where one column is my data values (“dFF”) and another column is my timestamps where the data was recorded ("Time). I also have a list of timestamps where events occurred. I want to plot the data 3 seconds before and 5 seconds after each event, with multiple events on the same plot.

df.head()
       Time       dFF
0  0.500267  0.617687
1  0.516673  0.737019
2  0.533079  0.801859
3  0.549485  0.762987
4  0.565891  0.572441

fig, ax0 = plt.subplots()
events = [24.541, 35.193, 45.461, 71.554, 95.954, 108.658, 134.592, 147.914, 163.671]
#Plot trials
for event in events:
     begin = event - 3.0
     end   = event + 5
     in_between = df['Time'].between(begin, end, inclusive=True)
     ax0.plot(df['Time'].loc[in_between], df["dFF"].loc[in_between])
plt.show()

The plots should essentially be on top of each other. But since I am using the time stamps as the x-coordinates, they are instead plotting across the whole time axis. Is there a good way to standardize the x-axis so that I can get the plots on top of each other? There are the same number of data points for each event in the 8 second window.

The desired graph should look something like this: Desired plot output with multiple lines on same x-axis

The two graphs that I currently make (whole trace and subsets) look like this and this .

Answer 1

To answer my question for anyone who comes across this in the future, I made a separate array for the x-values. I created an array using np.linspace from -3 to 5 (3 seconds before to 5 seconds after) using the length of the event array as the number of values.

#Plot trials
fig,ax0 = plt.subplots()
for event in events:
     begin = event - 3.0
     end   = event + 5
     in_between = df['Time'].between(begin, end, inclusive=True)
     tmp = df.loc[in_between]
     event_array = tmp['dFF'].to_numpy()
     x_mask = np.linspace(-3,5,len(event_array))
     ax0.plot(x_mask, df[dff].loc[in_between])
plt.show()

Which resulted in a plot that looks like this: