使跟踪颜色在 Figures/Graphs 中保持一致

Question

假设我有以下代码：

import pandas as pd
import numpy as np
import plotly.express as px
from dash.dependencies import Output, Input
from dash import dcc
from dash import html
import dash


df_a = pd.DataFrame({"time":pd.Series(pd.date_range("1-nov-2021","2-nov-2021", freq="S")).sample(30),
             "bacteria_count":np.random.randint(0,500, 30), "bacteria_type":np.random.choice(list("AB"),30)})

df_a["epoch_time_ms"] = df_a["time"].astype(int) / 1000
df_a = df_a.sort_values("time")
fig_a = px.line(df_a, x="time", y="bacteria_count", line_shape="hv", markers=True, color='bacteria_type')
fig_a.update_traces(mode="markers+lines", hovertemplate=None)
fig_a.update_layout(hovermode='x unified')


df_b = pd.DataFrame({"time":pd.Series(pd.date_range("1-nov-2021","2-nov-2021", freq="S")).sample(30),
             "bacteria_count":np.random.randint(0,500, 30), "bacteria_type":np.random.choice(list("BC"),30)})
df_b["epoch_time_ms"] = df_b["time"].astype(int) / 1000
df_b = df_b.sort_values("time")
fig_b = px.line(df_b, x="epoch_time_ms", y="bacteria_count", line_shape="hv", markers=True, color='bacteria_type')
fig_b.update_traces(mode="markers+lines", hovertemplate=None)
fig_b.update_layout(hovermode='x unified')


app = dash.Dash(__name__)  # call flask server
app.layout = html.Div(children=[
                          html.Div([
                              html.Div([
                                  html.H1(children='G_A'),
                                  dcc.Graph(id='fig_a-graph', figure=fig_a)
                              ], className='six columns'),
                              html.Div([
                                  html.H1(children='G_B'),
                                  dcc.Graph(id='fig_b-graph', figure=fig_b)
                              ], className='six columns')
                          ])])


if __name__ == '__main__':
    app.run_server(debug=True, port=8086)

我想达到：

两个 figures/graphs 中的迹线一致且唯一，因此两个图中迹线 'B' 的颜色相同，迹线 'A' 的颜色不会用作跟踪的颜色 'C'（也不 'B'）。
有时，我在每张图中有 20 条轨迹，如果 plotly 可以 select 所有轨迹的颜色更鲜明，那就太好了，因为有时，很难分辨哪个是哪个，当颜色多笔交易不同但非常相似。

谢谢！

Answer 1

如果我没理解错的话，我想你需要的是这个：https://plotly.com/python/discrete-color/

向下滚动（或搜索）“color_discrete_map”

基本上，您可以创建一个字典，指定“轨迹 A”应使用颜色 1，“轨迹 B”应使用颜色 2，等等

然后在所有相关的figures/graphs中指定使用与color_discrete_map

相同的字典

Answer 2

一种方法是连接数据并使用构面。因此传说是共享和一致的。我在这里使用的技巧是创建一个额外的串联列，可以用作 facet_row

px.line(
    pd.concat([df_a.assign(df="a"), df_b.assign(df="b")]),
    x="epoch_time_ms",
    y="bacteria_count",
    facet_row="df",
    line_shape="hv",
    markers=True,
    color="bacteria_type",
).update_traces(mode="markers+lines", hovertemplate=None).update_layout(
    hovermode="x unified"
)

方法 2

在此示例中定义您自己的颜色映射cmap
确保您查看所有 细菌类型 并使用和方法在 dict comprehension

import pandas as pd
import numpy as np
import plotly.express as px
from dash.dependencies import Output, Input
from dash import dcc
from dash import html
import dash
from jupyter_dash import JupyterDash


df_a = pd.DataFrame(
    {
        "time": pd.Series(pd.date_range("1-nov-2021", "2-nov-2021", freq="S")).sample(
            30
        ),
        "bacteria_count": np.random.randint(0, 500, 30),
        "bacteria_type": np.random.choice(list("AB"), 30),
    }
)

df_a["epoch_time_ms"] = df_a["time"].astype(int) / 1000
df_a = df_a.sort_values("time")
df_b = pd.DataFrame(
    {
        "time": pd.Series(pd.date_range("1-nov-2021", "2-nov-2021", freq="S")).sample(
            30
        ),
        "bacteria_count": np.random.randint(0, 500, 30),
        "bacteria_type": np.random.choice(list("BC"), 30),
    }
)
df_b["epoch_time_ms"] = df_b["time"].astype(int) / 1000
df_b = df_b.sort_values("time")

# use whatever approach you want to assign a color to a bacteria type
# key loop through all bacteria types
cmap = {
    bt: px.colors.qualitative.Plotly[i % len(px.colors.qualitative.Plotly)]
    for i, bt in enumerate(pd.concat([df_a, df_b])["bacteria_type"].unique())
}

fig_a = px.line(
    df_a,
    x="time",
    y="bacteria_count",
    line_shape="hv",
    markers=True,
    color="bacteria_type",
    color_discrete_map=cmap,
)
fig_a.update_traces(mode="markers+lines", hovertemplate=None)
fig_a.update_layout(hovermode="x unified")


fig_b = px.line(
    df_b,
    x="epoch_time_ms",
    y="bacteria_count",
    line_shape="hv",
    markers=True,
    color="bacteria_type",
    color_discrete_map=cmap,
)
fig_b.update_traces(mode="markers+lines", hovertemplate=None)
fig_b.update_layout(hovermode="x unified")

# app = dash.Dash(__name__)  # call flask server
app = JupyterDash(__name__)

app.layout = html.Div(
    children=[
        html.Div(
            [
                html.Div(
                    [
                        html.H1(children="G_A"),
                        dcc.Graph(id="fig_a-graph", figure=fig_a),
                    ],
                    className="six columns",
                ),
                html.Div(
                    [
                        html.H1(children="G_B"),
                        dcc.Graph(id="fig_b-graph", figure=fig_b),
                    ],
                    className="six columns",
                ),
            ]
        )
    ]
)


if __name__ == "__main__":
    # app.run_server(debug=True, port=8086)
    # app.run_server(debug=True, port=8086)
    app.run_server(mode="inline")

使跟踪颜色在 Figures/Graphs 中保持一致

Making Trace Colors Consistency Across Figures/Graphs

python

plotly

plotly-dash

方法 2