python - 通过选择散点图上的点来更新虚线表

Question

我正在开发一个仪表板。这是我的代码:

# IMPORT SECTION
import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
import pandas as pd
from math import ceil
from matplotlib.cm import Set3


# INPUT DATA
n = 7
d_min = 0.2
d_max = 0.8
d_step = 0.1
N_min = 2000
N_max = 8000
N_step = 1000
D = 40
h = 20
dataframe_file = 'data.xlsx'


# COLOR AND FONT DEFINITION
grey = '#e0e1f5'
black = '#212121'
scatter_colors = ['#' + ''.join(['{:02x}'.format(int(255*Set3(i)[j])) for j in range(3)]) for i in range(n)]
fontsize = 18
fontfamily = 'Arial, sans-serif'


# READ CSV DATA
df = pd.read_excel(dataframe_file)


# CREATE DATA FOR DASH DATATABLE
df_scatter_colors = ceil(len(df) / len(scatter_colors)) * scatter_colors
df_scatter_colors = df_scatter_colors[:len(df)]
df.insert(loc = 0, column = 'COLOR', value = df_scatter_colors)

headers = [{"name": i, "id": i} for i in df.columns]

table = df.to_dict('records')

table_colors = [{'if': {'row_index': i, 'column_id': 'COLOR'},
                 'background-color': df.iloc[i]['COLOR'],
                 'color': df.iloc[i]['COLOR']} for i in range(df.shape[0])]


# CREATE DATA AND LAYOUT FOR THE SCATTERPLOT
x_jitter = 0.05 * N_step * np.random.randn(len(df))
y_jitter = 0.05 * d_step * 1000 * np.random.randn(len(df))
data = [go.Scatter(x = df['NUMBER'] + x_jitter,
                   y = df['DIAMETER'] + y_jitter,
                   text = df['PRODUCT'],
                   mode = 'markers',
                   hoverinfo = 'skip',
                   showlegend = False,
                   marker_color = 'rgba(0, 0, 0, 0)',
                   marker = {'size': 25,
                             'line': {'color': df['COLOR'],
                                      'width': 8}})]

layout = go.Layout(plot_bgcolor = black,
                   hovermode = 'x unified',
                   uirevision = 'value')

figure = go.Figure(data = data, layout = layout)


# DASHBOARD LAYOUT
app = dash.Dash(external_stylesheets = [dbc.themes.BOOTSTRAP])

app.layout = html.Div(id = 'general_div',
                      children = [html.Div(id = 'first_row',
                                           children = [dcc.Graph(id = 'main_graph',
                                                                 figure = figure,
                                                                 style = {'height': 800,
                                                                          'width': 1400})],

                                           className = 'row'),

                                  html.Div(id = 'second_row',
                                           children = [dash_table.DataTable(id = 'main_table',
                                                                            columns = headers,
                                                                            data = table,
                                                                            style_data_conditional = table_colors,
                                                                            style_table = {'margin-left': '3vw',
                                                                                           'margin-top': '3vw'},
                                                                            style_cell = {'font-family': fontfamily,
                                                                                          'fontSize': fontsize},
                                                                            style_header = {'backgroundColor': 'rgb(230, 230, 230)',
                                                                                            'fontWeight': 'bold'})],

                                           className = 'row')])


# CALLBACK DEFINITION
@app.callback(Output('main_table', 'style_data_conditional'),
              [Input('main_graph', 'selectedData'),
               Input('main_table', 'style_data_conditional')])
def display_selected_data(selectedData, style_data_conditional):
    # what to do here and how to run this callback?
    return style_data_conditional


if __name__ == "__main__":
    app.run_server()

在仪表板中存在散点图( dcc.Graph)和表格( dash_table.DataTable)。散点图的每个点对应于表格的特定行，我从 excel 文件中读取这些数据。
excel文件中的数据格式如下:

PRODUCT CODE    NUMBER  DIAMETER
AAAAA   1412    8000    0.049
BBBBB   1418    3900    0.08
CCCCC   1420    7600    0.06
DDDDD   1426    8500    0.049
EEEEE   1430    3900    0.08
FFFFF   1442    3900    0.08
GGGGG   1490    8500    0.049
HHHHH   1504    9000    0.18
IIIII   1514    5500    0.224
JJJJJ   1584    7600    0.06
KKKKK   1606    8500    0.049
LLLLL   1618    7600    0.06
MMMMM   1638    7600    0.06
NNNNN   1640    7600    0.06
OOOOO   1666    3900    0.08
PPPPP   1670    8000    0.049
QQQQQ   1672    8000    0.049
RRRRR   1674    7600    0.06
SSSSS   1700    7100    0.071
TTTTT   1704    8500    0.049
UUUUU   1712    7600    0.06
VVVVV   1718    7600    0.06
WWWWW   1722    8000    0.065

我想实现这个功能:当用户选择散点图中的某个点时，代码突出显示表中的相应行(例如将这些行中单元格的背景颜色更改为 'pink' ，除了 'COLOR' 列，保持其颜色)。
检查了这些来源:

dash-datatable-individual-highlight-using-style-data-conditionals-works-unusual

dash-datatable-style-data-conditional-row-vice

interactive-graphing

我试图绘制这样的回调，但没有成功:

@app.callback(Output('selected_data', 'children'),
              [Input('main_graph', 'selectedData'),
               Input('main_table', 'style_data_conditional')])
def display_selected_data(selectedData, style_data_conditional):
    selected_points = []
    for point in selectedData['points']:
        selected_points.append(point['marker.line.color'])
    selected = [{'if': {'filter': '{COLOR} eq ' + f'"{color}"',
                        'column_id': 'PRODUCT'},
                 'backgroundColor': 'pink'} for color in selected_points]
    style_data_conditional.extend(selected)

    return style_data_conditional

提前致谢。
版本信息

Python                       3.7.0
dash                         1.12.0
dash-bootstrap-components    0.10.1
dash-core-components         1.10.0
dash-html-components         1.0.3
matplotlib                   3.0.2
numpy                        1.15.4
plotly                       4.7.0

Answer 1

我设法通过 selectedData 解决了这个问题作为来自 main_graph 的输入和加工main_table的 style_data_conditional作为通过函数 update_table_style 的输出.
在这里，我用深灰色为奇数行着色，以提高表格的可见性，然后我通过样式条件设置所选行的背景颜色。最后，我根据每行的颜色(在每行的第一列上报告的颜色)更改第一列的背景。
代码:

# IMPORT SECTION
import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
import pandas as pd
from math import ceil
from matplotlib.cm import Set3


# INPUT DATA
n = 7
d_min = 0.2
d_max = 0.8
d_step = 0.1
N_min = 2000
N_max = 8000
N_step = 1000
D = 40
h = 20
dataframe_file = 'data.xlsx'


# COLOR AND FONT DEFINITION
grey = '#e0e1f5'
black = '#212121'
scatter_colors = ['#' + ''.join(['{:02x}'.format(int(255*Set3(i)[j])) for j in range(3)]) for i in range(n)]
fontsize = 18
fontfamily = 'Arial, sans-serif'


# READ CSV DATA
df = pd.read_excel(dataframe_file)


# CREATE DATA FOR DASH DATATABLE
df_scatter_colors = ceil(len(df) / len(scatter_colors)) * scatter_colors
df_scatter_colors = df_scatter_colors[:len(df)]
df.insert(loc = 0, column = 'COLOR', value = df_scatter_colors)

headers = [{"name": i, "id": i} for i in df.columns]

table = df.to_dict('records')


# CREATE DATA AND LAYOUT FOR THE SCATTERPLOT
x_jitter = 0.05 * N_step * np.random.randn(len(df))
y_jitter = 0.05 * d_step * 1000 * np.random.randn(len(df))
data = [go.Scatter(x = df['NUMBER'] + x_jitter,
                   y = df['DIAMETER'] + y_jitter,
                   text = df['PRODUCT'],
                   mode = 'markers',
                   hoverinfo = 'skip',
                   showlegend = False,
                   marker_color = 'rgba(0, 0, 0, 0)',
                   marker = {'size': 25,
                             'line': {'color': df['COLOR'],
                                      'width': 8}})]

layout = go.Layout(plot_bgcolor = black,
                   hovermode = 'x unified',
                   uirevision = 'value')

figure = go.Figure(data = data, layout = layout)

def update_table_style(selectedData):
    table_style_conditions = [{'if': {'row_index': 'odd'},
                               'backgroundColor': 'rgb(240, 240, 240)'}]

    if selectedData != None:
        points_selected = []
        for point in selectedData['points']:
            points_selected.append(point['pointIndex'])
        selected_styles = [{'if': {'row_index': i},
                            'backgroundColor': 'pink'} for i in points_selected]
        table_style_conditions.extend(selected_styles)

    table_style_conditions.extend([{'if': {'row_index': i, 'column_id': 'COLOR'},
                                    'background-color': df.iloc[i]['COLOR'],
                                    'color': df.iloc[i]['COLOR']} for i in range(df.shape[0])])

    return table_style_conditions


# DASHBOARD LAYOUT
app = dash.Dash(external_stylesheets = [dbc.themes.BOOTSTRAP])

app.layout = html.Div(id = 'general_div',
                      children = [html.Div(id = 'first_row',
                                           children = [dcc.Graph(id = 'main_graph',
                                                                 figure = figure,
                                                                 style = {'height': 800,
                                                                          'width': 1400})],

                                           className = 'row'),

                                  html.Div(id = 'second_row',
                                           children = [dash_table.DataTable(id = 'main_table',
                                                                            columns = headers,
                                                                            data = table,
                                                                            # style_data_conditional = table_colors,
                                                                            style_table = {'margin-left': '3vw',
                                                                                           'margin-top': '3vw'},
                                                                            style_cell = {'font-family': fontfamily,
                                                                                          'fontSize': fontsize},
                                                                            style_header = {'backgroundColor': 'rgb(230, 230, 230)',
                                                                                            'fontWeight': 'bold'})],

                                           className = 'row')])


# CALLBACK DEFINITION
@app.callback(Output('main_table', 'style_data_conditional'),
              [Input('main_graph', 'selectedData')])
def display_selected_data(selectedData):
    table_style_conditions = update_table_style(selectedData)
    return table_style_conditions


if __name__ == "__main__":
    app.run_server()

上色部分是这样的:

table_style_conditions = [{'if': {'row_index': 'odd'},
                           'backgroundColor': 'rgb(240, 240, 240)'}]

if selectedData != None:
    points_selected = []
    for point in selectedData['points']:
        points_selected.append(point['pointIndex'])
    selected_styles = [{'if': {'row_index': i},
                        'backgroundColor': 'pink'} for i in points_selected]
    table_style_conditions.extend(selected_styles)

table_style_conditions.extend([{'if': {'row_index': i, 'column_id': 'COLOR'},
                                'background-color': df.iloc[i]['COLOR'],
                                'color': df.iloc[i]['COLOR']} for i in range(df.shape[0])])

这是我得到的结果: