Plotly:当 scaleanchor = x 时,如何调整带注释的热图的轴标签?
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【中文标题】Plotly:当 scaleanchor = x 时,如何调整带注释的热图的轴标签?【英文标题】:Plotly: How to adjust axis labels for annotated heatmaps when scaleanchor = x? 【发布时间】:2021-05-11 21:19:57 【问题描述】:当您设置scaleanchor=x
和adjusting the aspect ratio 时,例如使用ff.annotated_heatmaps
制作一个完美的正方形热图,您最终会得到与x 轴本身有较大偏移的x 轴标签,如下所示:
如何解决这个问题?
代码:
import numpy as np
import plotly.graph_objs as go
import plotly.figure_factory as ff
# data
z = np.random.randint(0,6, size=(10, 10))
z_text = np.full(z.shape, '', dtype=str)
d = 0:'a', 1:'b', 2:'c', 3:'d', 4:'e', 5:'f'
class_mat = np.vectorize(d.get)(z)
# plotly figure factory annotated heatmap
fig = ff.create_annotated_heatmap(z, annotation_text=z_text,
text=class_mat, hoverinfo='text', colorscale='Viridis',
x = list('ABCDEFGHIJ'),
y = list('ABCDEFGHIJ')
)
fig.layout.title = 'Semantic Segmentation'
fig.data[0]['hoverinfo'] = 'all'
# adjustment 1: scaleanchor => squared figure
fig['layout']['yaxis']['scaleanchor']='x'
# adjustment 2: remove redunant background background
fig.update_layout(plot_bgcolor='rgba(0,0,0,0)')
fig.show()
【问题讨论】:
【参考方案1】:这个解决方案有点神秘,但请确保包含constrain='domain'
:
fig.update_layout(xaxis=dict(scaleanchor='y',constrain='domain'))
情节
完整代码
import numpy as np
import plotly.graph_objs as go
import plotly.figure_factory as ff
# data
z = np.random.randint(0,6, size=(10, 10))
z_text = np.full(z.shape, '', dtype=str)
d = 0:'a', 1:'b', 2:'c', 3:'d', 4:'e', 5:'f'
class_mat = np.vectorize(d.get)(z)
# plotly figure factory annotated heatmap
fig = ff.create_annotated_heatmap(z, annotation_text=z_text,
text=class_mat, hoverinfo='text', colorscale='Viridis',
x = list('ABCDEFGHIJ'),
y = list('ABCDEFGHIJ')
)
fig.layout.title = 'Semantic Segmentation'
fig.data[0]['hoverinfo'] = 'all'
# adjustment 1: scaleanchor => squared figure
fig['layout']['yaxis']['scaleanchor']='x'
# adjustment 2: remove redunant background background
fig.update_layout(plot_bgcolor='rgba(0,0,0,0)')
# adjustment 3: x-axis label offsets
fig.update_layout(xaxis=dict(scaleanchor='y',constrain='domain'))
fig.show()
【讨论】:
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