Slider in `scatter_3d` and `scatter` makes some data points go missing

執行 plot_scatter_3d_mwe 中提供的 Python MWE，並比較動畫 2D 與 3D 散佈圖在各個閾值影格之間的行為。追蹤 animation_frame 和 animation_group 在產生的圖形中的表示方式；當四個類別及其資料點在滑桿的每個位置都仍然可用時，即表示完成。

Only 2 out of 4 categories are plotted when I use a slider. Other data points do not appear at all. When I slide the slider, different categories are plotted. E.g. in the MWE below, only TP and FP show up when the slider is below 0.9. At 0.9 only TN and FN show up.

This behavior also happens for both 2d and 3d scatter plots. See the MWE below for 3d.

import numpy as np
import pandas as pd
import plotly.express as px

def plot_scatter_3d_mwe():
    # Create a small DataFrame with fake data
    data = {
        'Dim1': np.random.rand(10),
        'Dim2': np.random.rand(10),
        'Dim3': np.random.rand(10),
        'due': [1, 0, 1, 0, 1, 0, 1, 0, 1, 0],
        'serial_number': range(10),
        'predicted_probabilities': [0.9, 0.8, 0.4, 0.2, 0.6, 0.7, 0.1, 0.5, 0.3, 0.95]
    }

    df = pd.DataFrame(data)
    thresholds = np.arange(0, 1.1, 0.1)
    all_frames = []

    for threshold in thresholds:
        # Recalculate predictions based on the threshold
        predicted = (df['predicted_probabilities'] >= threshold).astype(int)
        
        # Create the 4 categories for coloring: TP, TN, FP, FN
        conditions = [
            (df['due'] == 1) & (predicted == 1),  # TP
            (df['due'] == 0) & (predicted == 0),  # TN
            (df['due'] == 0) & (predicted == 1),  # FP
            (df['due'] == 1) & (predicted == 0),  # FN
        ]
        categories = ['TP', 'TN', 'FP', 'FN']
        
        # Assign the categories to a new column
        df['category'] = np.select(conditions, categories, default='Unknown')
        df['threshold'] = threshold  # Add threshold as a column for animation frame
        
        all_frames.append(df.copy())

    # Concatenate all frames for animation
    df_all_frames = pd.concat(all_frames)

    # Plot the scatter 3D with the categories as color and animate over thresholds
    fig = px.scatter_3d(df_all_frames,
                        x='Dim1', y='Dim2', z='Dim3',
                        color='category',
                        animation_frame='threshold',
                        animation_group='serial_number')

    fig.show()

# Call the function
plot_scatter_3d_mwe()