Plotly：當 scaleanchor = x 時，如何調整帶注釋的熱圖的軸標簽？

Question

當您在調整縱橫比時設置scaleanchor=x時，例如使用ff.annotated_heatmaps制作完美的正方形熱圖，您最終會得到與 x 軸本身有較大偏移的 x 軸標簽，如下所示：

你怎么能解決這個問題？

代碼：

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()

Answer 1

這個解決方案有點神秘，但只要確保包含constrain='domain' ：

fig.update_layout(xaxis=dict(scaleanchor='y',constrain='domain'))

Plot

完整代碼

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()