Bokeh interactively changing the columns being plotted
我有一个大型数据集想要探索。但是我不想创建多个图。我只想要一个图，我可以在其中交互地更改用于 x 和 y 轴的列，并且图会自行更新。
我正在尝试通过 Python/Bokeh 使用 Bokeh 将我的脚本提供给浏览器来执行此操作。但是我不清楚如何让情节更新。我看到很多更改基础数据源的示例，但我不想这样做，我只想更改正在绘制的列。
我在下面做了一个简单的例子来说明我想做什么。它使用两个"选择"小部件来选择数据源的 x 和 y 列。这些具有尝试更改"行"字形所指列的回调。然而，这似乎不起作用。欢迎提供任何建议。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | import numpy as np from bokeh.models import ColumnDataSource from bokeh.plotting import Figure from bokeh.models.widgets import Select,TextInput from bokeh.models.glyphs import Line from bokeh.models.layouts import HBox, VBox from bokeh.io import curdoc #============================================================================== #%% Define some Data #============================================================================== N = 200 # Define the data to be used x = np.linspace(0,4.*np.pi,N) y = 3*np.cos(2*np.pi*x + np.pi*0.2) z = 0.5*np.sin(2*np.pi*0.8*x + np.pi*0.4) source = ColumnDataSource({'x':x,'cos':y,'sin':z}) #============================================================================== #%% Layout #============================================================================== TOOLS ="box_select,lasso_select,help" # create a new plot plot = Figure(tools=TOOLS, title=None) # Make a line and connect to data source glyph = Line(x="x", y="cos", line_color="#F46D43", line_width=6, line_alpha=0.6) plot.add_glyph(source, glyph) # Add list boxes for selecting which columns to plot on the x and y axis yaxis_select = Select(title="Y axis:", value="cos", options=['x','cos','sin']) xaxis_select = Select(title="X axis:", value="x", options=['x','cos','sin']) # Text input as a title text = TextInput(title="title", value='my sine wave plotter') # Layout widgets next to the plot controls = VBox(text,yaxis_select,xaxis_select) layout = HBox(controls,plot,width=800) #============================================================================== #%% Callbacks #============================================================================== # Put callbacks on the list boxes so that when they are changed the columns being # plotted get changed. def update_x_axis(attr, old, new): # Change the column used for the x axis glyph.x = xaxis_select.value def update_y_axis(attr, old, new): # Change the column used for the y axis glyph.y = yaxis_select.value yaxis_select.on_change('value', update_y_axis) xaxis_select.on_change('value', update_x_axis) #============================================================================== #%% Add to document root #============================================================================== curdoc().add_root(layout) curdoc().title ="Plotting app" |
要编辑字形获取其坐标的实际源字段，您需要修改此问题中的代码。 ImportanceOfBeingErnest\\'s 代码的修订版产生正确的结果，无需更改原始 ColumnDataSource 或隐藏 Select 小部件中的任何键：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | import numpy as np from bokeh.models import ColumnDataSource from bokeh.plotting import Figure from bokeh.models.widgets import Select, TextInput from bokeh.models.layouts import HBox, VBox import bokeh.io from bokeh.io import curdoc from bokeh.models import CustomJS N = 200 # Define the data to be used x = np.linspace(0, 4. * np.pi, N) y = 3 * np.cos(2 * np.pi * x + np.pi * 0.2) z = 0.5 * np.sin(2 * np.pi * 0.8 * x + np.pi * 0.4) data = {'x': x, 'cos': y, 'sin': z} source = ColumnDataSource(data=data) codex =""" var column = cb_obj.value; line1.glyph.x.field = column; source.trigger('change') """ codey =""" var column = cb_obj.value; line1.glyph.y.field = column; source.trigger('change') """ # create a new plot plot = Figure(title=None) # Make a line and connect to data source line1 = plot.line(x="x", y="cos", line_color="#F46D43", line_width=6, line_alpha=0.6, source=source) callbackx = CustomJS(args=dict(line1=line1, source=source), code=codex) callbacky = CustomJS(args=dict(line1=line1, source=source), code=codey) # Add list boxes for selecting which columns to plot on the x and y axis yaxis_select = Select(title="Y axis:", value="cos", options=data.keys(), callback=callbacky ) xaxis_select = Select(title="X axis:", value="x", options=data.keys(), callback=callbackx ) # Text input as a title text = TextInput(title="title", value='my sine wave plotter') # Layout widgets next to the plot controls = VBox(text, yaxis_select, xaxis_select) layout = HBox(controls, plot, width=800) # bokeh.io.show(layout) curdoc().add_root(layout) curdoc().title ="Sliders" |
为了清晰起见，我将代码字符串分开，但 ImportanceOfBeingErnest\\ 的 string.format() 使用非常简洁。
不幸的是，我无法获得用于编辑这些特定字段的完整 Python 解决方案，尽管 ImportanceOfBeingErnest\\ 的解决方案实际上根本不需要 JavaScript(但确实更改了数据源)
以下脚本似乎工作正常。它不使用 Bokeh 服务器，而是使用 CustomJS 客户端样式。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | import numpy as np from bokeh.models import ColumnDataSource from bokeh.plotting import Figure from bokeh.models.widgets import Select,TextInput from bokeh.models.layouts import HBox, VBox import bokeh.io from bokeh.models import CustomJS N = 200 # Define the data to be used x = np.linspace(0,4.*np.pi,N) y = 3*np.cos(2*np.pi*x + np.pi*0.2) z = 0.5*np.sin(2*np.pi*0.8*x + np.pi*0.4) source = ColumnDataSource(data={'x':x,'y':y, 'X': x, 'cos':y,'sin':z}) code=""" var data = source.get('data'); var r = data[cb_obj.get('value')]; var {var} = data[cb_obj.get('value')]; //window.alert("{var}" + cb_obj.get('value') + {var} ); for (i = 0; i < r.length; i++) {{ {var}[i] = r[i] ; data['{var}'][i] = r[i]; }} source.trigger('change'); """ callbackx = CustomJS(args=dict(source=source), code=code.format(var="x")) callbacky = CustomJS(args=dict(source=source), code=code.format(var="y")) # create a new plot plot = Figure(title=None) # Make a line and connect to data source plot.line(x="x", y="y", line_color="#F46D43", line_width=6, line_alpha=0.6, source=source) # Add list boxes for selecting which columns to plot on the x and y axis yaxis_select = Select(title="Y axis:", value="cos", options=['X','cos','sin'], callback=callbacky) xaxis_select = Select(title="X axis:", value="x", options=['X','cos','sin'], callback=callbackx) # Text input as a title text = TextInput(title="title", value='my sine wave plotter') # Layout widgets next to the plot controls = VBox(text,yaxis_select,xaxis_select) layout = HBox(controls,plot,width=800) bokeh.io.show(layout) |
然而，我对它进行了修补，直到它完成了它应该做的事情。而且我不确定为什么 CustomJS 代码中的部分需要如此复杂。
特别是在 JS 部分 for 循环内的这两行似乎实际上都是需要的，尽管它们似乎做同样的事情。
因此，除非有人真正想出可以解释的东西，否则我不会称这个问题为已回答。
我无法在 Bokeh 2.02 上获得上述答案。在对答案进行一些修改后，产生了以下适用于 BOKEH 2.02 的代码。
您还可以在页面底部尝试"运行代码片段"以查看此示例的实际效果。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | import numpy as np from bokeh.models import ColumnDataSource from bokeh.plotting import Figure from bokeh.models.widgets import Select,TextInput from bokeh.models.layouts import Column, Row import bokeh.io from bokeh.models import CustomJS N = 200 # Define the data to be used x = np.linspace(0,4.*np.pi,N) y = 3*np.cos(2*np.pi*x + np.pi*0.2) z = 0.5*np.sin(2*np.pi*0.8*x + np.pi*0.4) source = ColumnDataSource(data={'x':x,'y':y, 'X': x, 'cos':y,'sin':z}) code=""" var column = cb_obj.value; line.glyph.{var}.field = column; source.change.emit(); """ # create a new plot plot = Figure(title=None) # Make a line and connect to data source line = plot.line(x="x", y="y", line_color="#F46D43", line_width=6, line_alpha=0.6, source=source) #Make a callbacks callbackx = CustomJS(args=dict(source=source, line=line), code=code.format(var="x")) callbacky = CustomJS(args=dict(source=source, line =line), code=code.format(var="y")) # Add list boxes for selecting which columns to plot on the x and y axis yaxis_select = Select(title="Y axis:", value="cos", options=['X','cos','sin']) yaxis_select.js_on_change('value', callbacky) xaxis_select = Select(title="X axis:", value="x", options=['X','cos','sin']) xaxis_select.js_on_change('value', callbackx) # Text input as a title text = TextInput(title="title", value='my sine wave plotter for Bokeh 2.02') # Layout widgets next to the plot controls = Row(text,yaxis_select,xaxis_select) layout = Column(controls,plot,width=800) bokeh.io.show(layout) # Generate standlone html documents to put into stackoverflow"RUN SNIPPET" #from bokeh.resources import CDN #from bokeh.embed import file_html #with open('callbacks_example.html','w') as f: #f.write(file_html(layout, CDN)) # Copy and pas the html contents into stackover flow |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 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