importmatplotlib.pyplotaspltdefdraw_thick_line(x,y,thickness):foriinrange(1,thickness+1):plt.plot(x,y+i,'k')# 绘制平行线条x=[1,2,3,4,5]y=[2,3,5,7,6]thickness=5plt.plot(x,y,'k')# 绘制原始线条draw_thick_line(x,y,thickness)# 绘制粗线条plt.axis('equal')plt.show() 1. 2...
importcv2importnumpyasnp image=np.zeros((300,300,3),dtype="uint8")start_point=(50,50)end_point=(250,250)color=(0,255,0)thickness=2cv2.line(image,start_point,end_point,color,thickness)cv2.imshow("Line",image)cv2.waitKey(0) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 在...
Sankey( valueformat=".0f", valuesuffix="TWh", # 点 node=dict( pad=15, thickness=15, line=dict(color = "black", width = 0.5), label=data['data'][0]['node']['label'], color=data['data'][0]['node']['color'] ), # 线 link=dict( source=data['data'][0]['link']['...
fig=gr.Figure(data=[gr.Sankey( node=dict(pad=10,thickness=25,line=dict(color="red",width=0.8),label=Depts,), link=dict(source=sending_indices,target=accepting_indices,value=flowvalues ))]) fig.update_layout(title_text="SankeyDiagramofexchangestudentsflowbetweenUniversityDepts",font_size=12) ...
3、calcHist()计算 matplotlib plot()显示 前面介绍了matplotlib hist()方法直接显示直方图,这里利用calHist()计算出直方图,得到的是一个数组,该数组的下标表示像素值代表x轴,数组元素的值表示该下标对应的像素值个数代表y轴,所以也可以利用matplotlib的plot()方法绘制直方图: ...
thickness=20, line=dict(color="black", width=0.5), label=labels ), link=dict( source=source, target=target, value=value ))]) fig.update_layout(title_text="Energy Flow in Model City", font_size=12) fig.show() 1. 2. 3. 4. ...
dept_index=Dept_indices[dept]accepting_indices.append(dept_index)flowvalues=df['FlowValue'].tolist()# Sankey diagramfig=gr.Figure(data=[gr.Sankey(node=dict(pad=10,thickness=25,line=dict(color="red",width=0.8),label=Depts,),link=dict(source=sending_indices,target=accepting_indices,value=flow...
从这个桑基图 (Sankey)可视化中可以明显看出,从England迁移到Wales的居民多于从Scotland或Northern Ireland迁移的居民。 什么是桑基图? 桑基图通常描绘从一个实体(或节点)到另一个实体(或节点)的数据流。 数据流向的实体被称为节点,数据流起源的节点是源节点(例如左侧的England),流结束的节点是目标节点(例如右侧的...
image=np.zeros((500,500,3),dtype=np.uint8)start_point=(100,100)end_point=(400,400)color=(255,0,0)thickness=2cv2.line(image,start_point,end_point,color,thickness)cv2.imshow("Line",image)cv2.waitKey(0)cv2.destroyAllWindows()
append(line) # Set y limit (or first line is cropped because of thickness) ax.set_ylim(-1...