为啥我的 3D Plotly Scatterplot 的大小会随机变化？

Posted 2023-02-18

【中文标题】为啥我的 3D Plotly Scatterplot 的大小会随机变化？

【英文标题】：Why does the size of my 3D Plotly Scatterplot randomly change?为什么我的 3D Plotly Scatterplot 的大小会随机变化？

【发布时间】：2021-11-20 17:24:30

【问题描述】：

我正在尝试创建一个动画 3D 散点图来表示在 3D 空间中游泳的鱼。我有 8 条鱼，每条鱼我有 4 分。我能够制作图表并为其设置动画，但是图表的大小在时间点之间随机变化。我已经设置了轴的最小值和最大值，但它们之间的距离似乎发生了变化。为了保持稳定，我需要改变情节的哪些方面？

这是我正在使用的 plotly express 命令：

fig = px.scatter_3d(df,x="x", y="y", z="z",
                       color="Fish", animation_frame="Frame", hover_data = ["BodyPart"],
                       range_x=[-0.25,0.25], range_y=[-0.15,0.15], range_z=[-0.15,0.15], 
                       color_continuous_scale = "rainbow")

这两张图片显示的图表彼此相隔一帧。绿色方块显示某一点的统计数据，表明它没有发生剧烈变化：

我还包括this video 以获得更清晰的示例。

已编辑：

最少的绘图代码：

import pandas as pd
import plotly.express as px

data_dict = 'Fish': 0: 0, 1: 0, 2: 0, 3: 0, 4: 1, 5: 1, 6: 1, 7: 1, 8: 2, 9: 2, 10: 2, 11: 2, 12: 3, 13: 3, 14: 3, 15: 3, 16: 4, 17: 4, 18: 4, 19: 4, 20: 5, 21: 5, 22: 5, 23: 5, 24: 6, 25: 6, 26: 6, 27: 6, 28: 7, 29: 7, 30: 7, 31: 7, 32: 0, 33: 0, 34: 0, 35: 0, 36: 1, 37: 1, 38: 1, 39: 1, 40: 2, 41: 2, 42: 2, 43: 2, 44: 3, 45: 3, 46: 3, 47: 3, 48: 4, 49: 4, 50: 4, 51: 4, 52: 5, 53: 5, 54: 5, 55: 5, 56: 6, 57: 6, 58: 6, 59: 6, 60: 7, 61: 7, 62: 7, 63: 7, 'BodyPart': 0: 'head', 1: 'midline2', 2: 'tailbase', 3: 'tailtip', 4: 'head', 5: 'midline2', 6: 'tailbase', 7: 'tailtip', 8: 'head', 9: 'midline2', 10: 'tailbase', 11: 'tailtip', 12: 'head', 13: 'midline2', 14: 'tailbase', 15: 'tailtip', 16: 'head', 17: 'midline2', 18: 'tailbase', 19: 'tailtip', 20: 'head', 21: 'midline2', 22: 'tailbase', 23: 'tailtip', 24: 'head', 25: 'midline2', 26: 'tailbase', 27: 'tailtip', 28: 'head', 29: 'midline2', 30: 'tailbase', 31: 'tailtip', 32: 'head', 33: 'midline2', 34: 'tailbase', 35: 'tailtip', 36: 'head', 37: 'midline2', 38: 'tailbase', 39: 'tailtip', 40: 'head', 41: 'midline2', 42: 'tailbase', 43: 'tailtip', 44: 'head', 45: 'midline2', 46: 'tailbase', 47: 'tailtip', 48: 'head', 49: 'midline2', 50: 'tailbase', 51: 'tailtip', 52: 'head', 53: 'midline2', 54: 'tailbase', 55: 'tailtip', 56: 'head', 57: 'midline2', 58: 'tailbase', 59: 'tailtip', 60: 'head', 61: 'midline2', 62: 'tailbase', 63: 'tailtip', 'x': 0: 0.121283071, 1: 0.074230535, 2: 0.096664814, 3: 0.063435668, 4: -0.11843468, 5: -0.133776416, 6: -0.12698166, 7: -0.133996648, 8: 0.154499401, 9: 0.099541555, 10: 0.126525899, 11: 0.086448979, 12: -0.001723707, 13: -0.064203743, 14: -0.033163578, 15: -0.077987938, 16: 0.160456072, 17: 0.175340028, 18: 0.178537856, 19: 0.16438273, 20: -0.151890354, 21: -0.099510254, 22: -0.123827166, 23: -0.08765671, 24: 0.052741099, 25: -0.003778201, 26: 0.022010701, 27: -0.014747641, 28: -0.137528989, 29: -0.078632593, 30: -0.106688178, 31: -0.065274018, 32: 0.12128202, 33: 0.074230379, 34: 0.096662597, 35: 0.063435699, 36: -0.118412987, 37: -0.133729238, 38: -0.12729935, 39: -0.134238167, 40: 0.154498856, 41: 0.099541572, 42: 0.126525899, 43: 0.086450612, 44: -0.001719156, 45: -0.064209291, 46: -0.033163578, 47: -0.07796947, 48: 0.157094899, 49: 0.175288008, 50: 0.178383788, 51: 0.1643551, 52: -0.153086656, 53: -0.100645272, 54: -0.125700666, 55: -0.089248865, 56: 0.052731775, 57: -0.003778201, 58: 0.022011924, 59: -0.014749184, 60: -0.138954183, 61: -0.079588201, 62: -0.107413558, 63: -0.06588028, 'y': 0: -0.018777537, 1: -0.017936625, 2: -0.019031854, 3: -0.018688299, 4: 0.031655295, 5: 0.089278103, 6: 0.060434868, 7: 0.102354879, 8: 0.012448659, 9: 0.005374916, 10: 0.008431857, 11: 0.010384436, 12: 0.007394437, 13: 0.002657548, 14: 0.0047918, 15: 0.004216939, 16: -0.061691249, 17: -0.022574622, 18: -0.044862196, 19: -0.015288812, 20: 0.126254494, 21: 0.125420316, 22: 0.127216595, 23: 0.122366769, 24: -0.018798237, 25: -0.026209512, 26: -0.020654802, 27: -0.030922742, 28: 0.100460973, 29: 0.091726762, 30: 0.095608508, 31: 0.089022071, 32: -0.018930378, 33: -0.018313362, 34: -0.019121954, 35: -0.018839649, 36: 0.030465513, 37: 0.087966041, 38: 0.058855924, 39: 0.100617287, 40: 0.012372615, 41: 0.00530059, 42: 0.008431857, 43: 0.009864426, 44: 0.007169236, 45: 0.002524294, 46: 0.0047918, 47: 0.002813216, 48: -0.061409007, 49: -0.024774863, 50: -0.045825365, 51: -0.017002469, 52: 0.125813664, 53: 0.125533354, 54: 0.126988948, 55: 0.121414741, 56: -0.019165739, 57: -0.026209512, 58: -0.020802186, 59: -0.031842627, 60: 0.100213119, 61: 0.091677506, 62: 0.095490242, 63: 0.08724155, 'z': 0: -0.011584533, 1: -0.005671144, 2: -0.004720913, 3: -0.007099159, 4: 0.048633092, 5: 0.044680886, 6: 0.047755313, 7: 0.047602698, 8: 0.005219131, 9: 0.020195691, 10: 0.013766486, 11: 0.019271016, 12: -0.009086866, 13: 0.005213358, 14: -0.003552202, 15: 0.001820855, 16: -0.039992723, 17: 0.041166976, 18: -0.013040119, 19: 0.048827692, 20: 0.044577227, 21: 0.043492943, 22: 0.045104437, 23: 0.0399218, 24: 0.007934858, 25: 0.007980119, 26: 0.010593472, 27: 0.006390279, 28: 0.070277892, 29: 0.066889416, 30: 0.070485941, 31: 0.054907996, 32: -0.011559485, 33: -0.005583401, 34: -0.004725084, 35: -0.007089815, 36: 0.048823811, 37: 0.04574317, 38: 0.047201689, 39: 0.043995531, 40: 0.005234299, 41: 0.020211407, 42: 0.013766486, 43: 0.019405438, 44: -0.009034049, 45: 0.005200504, 46: -0.003552202, 47: 0.002061042, 48: -0.035258171, 49: 0.041424053, 50: -0.013317812, 51: 0.048629332, 52: 0.043972705, 53: 0.042581942, 54: 0.046299595, 55: 0.040028712, 56: 0.007931264, 57: 0.007980119, 58: 0.010624531, 59: 0.006616644, 60: 0.068992196, 61: 0.064455916, 62: 0.07226277, 63: 0.056393304, 'Frame': 0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0, 8: 0, 9: 0, 10: 0, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 0, 18: 0, 19: 0, 20: 0, 21: 0, 22: 0, 23: 0, 24: 0, 25: 0, 26: 0, 27: 0, 28: 0, 29: 0, 30: 0, 31: 0, 32: 1, 33: 1, 34: 1, 35: 1, 36: 1, 37: 1, 38: 1, 39: 1, 40: 1, 41: 1, 42: 1, 43: 1, 44: 1, 45: 1, 46: 1, 47: 1, 48: 1, 49: 1, 50: 1, 51: 1, 52: 1, 53: 1, 54: 1, 55: 1, 56: 1, 57: 1, 58: 1, 59: 1, 60: 1, 61: 1, 62: 1, 63: 1

df = pd.DataFrame(data_dict)

fig = px.scatter_3d(df,x="x", y="y", z="z", color="Fish", animation_frame="Frame", hover_data = ["BodyPart"],
                        range_x=[-0.25,0.25], range_y=[-0.15,0.15], range_z=[-0.15,0.15], color_continuous_scale = "rainbow")

fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))

fig.show()

【问题讨论】：

@Squidswll 似乎px.scatter3D 试图通过根据特定帧的数据结构调整轴的长度来使动画中的每一帧在视觉上更令人愉悦。如果您与sample of your data 共享完整的代码sn-p 来重现您的身材，那么我相信您会很快得到您寻求的帮助。

感谢您的反馈。我添加了更多代码和前两帧数据

【参考方案1】：

这似乎与fig.layout.scene中的纵横比有关：

layout.Scene(
    'aspectmode': 'auto',
    'aspectratio': 'x': 1.7359689116422856, 'y': 0.9924641251101735, 'z':0.5804211635071164,

如果您在上面的字典中手动将x, y and z 设置为特定的东西，动画帧之间的图形退缩似乎消失了。

我试过了：

fig.layout.scene.aspectratio = 'x':1, 'y':1, 'z':1
fig.show()

而且结果很有希望。试一试，告诉我它对你有什么影响。

---

正如您已经发现的那样，与为x_range, y_range, z_range 设置定义的范围一起使用似乎效果最好。由于您的数据样本有点有限，我一直在搞乱px.data.gapminder()。

情节

完整代码

import plotly.express as px
df = px.data.gapminder()
# df
fig = px.scatter_3d(df, x = 'pop', y='lifeExp', z = 'gdpPercap', animation_frame='year',
                    range_x=[int(df['pop'].min()*0.5),int(df['pop'].max()*1.5)],
                    range_y=[int(df.lifeExp.min()*0.5),int(df.lifeExp.max()*1.5)],
                    range_z=[int(df['gdpPercap'].min()*0.5),int(df['gdpPercap'].max()*1.5)]
                   )
fig.layout.scene.aspectratio = 'x':1, 'y':1, 'z':1
fig.show()

【讨论】：

这对我来说非常有效，谢谢你的帮助！

@Squidswell 不客气！