下面是一个使用PIL进行线条加粗的例子: fromPILimportImage,ImageDraw# 读取图像image=Image.open('image.jpg')# 创建一个新的图像副本new_image=image.copy()# 创建一个绘图对象draw=ImageDraw.Draw(new_image)# 设置线条宽度line_width=5# 绘制线条draw.line([(0,0),(100,100)],fill='black',width=line...
#若figure大小为10*10,则大图(1,1)为起点,高8,宽8 left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 # 将大图坐标系添加到figure中 ax1 = fig.add_axes([left, bottom, width, height]) ax1.plot(x,y,'r') ax1.set_xlabel('x') ax1.set_ylabel('y') ax1.set_title('big') 1. 2...
update_traces(marker={ "size": 8, "opacity": opacity, "line":{"width": width_line, "color":"black"} }) # layout更新 fig.update_layout( width=800, # 长宽 height=700, autosize=False, showlegend = True, legend=dict(title_font_family="Times New Roman", font=dict(size= 20)), ...
import matplotlib.lines as mlines # Import Data df = pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/health.csv") df.sort_values('pct_2014', inplace=True) df.reset_index(inplace=True) # Func to draw line segment def newline(p1, p2, color='black'): ax = ...
传入一个四元列表参数：[x,y,width,height]，用来表示这个子图坐标轴原点的x坐标、y坐标，以及宽和高...
line_join (:class:`~bokeh.core.enums.LineJoin` ) : (default: 'bevel') line_width (:class:`~bokeh.core.properties.NumberSpec` ) : (default: 1) 线宽,默认:1另外,Bokeh中的一些属性,如`~bokeh.core.properties.NumberSpec `、`...
plt.annotate('Important Point', xy=(2, 3), xytext=(3, 4), fontsize=12, arrowprops=dict(facecolor='black', shrink=0.05, width=1.5, headwidth=8)) 3.8更改坐标轴范围 xlim和ylim: 设置X轴和Y轴的范围。 plt.xlim(0, 10)plt.ylim(-1, 1) ...
( 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']['source'], target=data['data'][0]['link']['target'], value=data[...
textprops={'fontsize':15,'color':'black'},startangle=90) plt.title('水果销量占比图',pad=30,size=20) plt.axis('equal') plt.show() 注意:plt.axis('equal') 用于将饼图显示为正圆 四、条形图 plt.bar(x, height,width,bottom,color,linewidth,tick_label,align) ...
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. 5. 6. 7. ...