代码如下所示: color_name=input("请输入颜色名称:")color_code=color_codes.get(color_name)ifcolor_code:print(f"您选择的颜色代码是:{color_code}")else:print("您输入的颜色名称不存在,请重新输入。") 1. 2. 3. 4. 5. 6. 这段代码使用了input()函数,用户可以通过输入颜色名称来获取对应的颜色代码...
def qrcode_detect(image): gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) codes = decode(gray_image) results = [] for code in codes: x, y, w, h = code.rect.left, code.rect.top, code.rect.width, code.rect.height results.append([x, y, w, h]) return image codes 中包...
colors=[c2[i]foriincodes]# 使用「面向对象」的方法画图fig,ax=plt.subplots(figsize=(8,6))# 设置标题ax.set_title('\n 2017年1月份河南省各地市AQI排名\n',fontsize=28,loc='left',color=c['深灰色'])# 画柱形图ax.bar(x,y,width=0.5,color=colors)#均值线ax.hlines(y.mean(),x[0],x[-...
cbar = plt.colorbar(cs,shrink=0.99,aspect=30,fraction=0.3,pad=0.01) cbar.set_ticks(np.arange(0,2600,400)) draw_maps(get_adm_maps(province='云南省', level='市'), color='black', linewidth=0.8) #绘制省内各区边界 map_polygon = get_adm_maps(province='云南省', level='市', only_p...
attribute_color: 点符号的颜色 verbose: 是否打印信息 OUTPUT: 没有,但是会有地图 """ _, ax = plt.subplots(figsize=figsize) # 初始化要添加到Path对象的点 multiverts = [] multicodes = [] # 在多边形和组合多边形中逐个添加点 for polygon in polygons: ...
[0]), s=10, color='black', alpha=0.7) # Line Segmentsand Annotation for p1, p2, c in zip(df['1952'], df['1957'], df['continent']): newline([1,p1],[3,p2]) ax.text(1-0.05, p1, c +', '+ str(round(p1)), horizontalalignment='right', verticalalignment='center', ...
(chart, canvas): text_width = canvas.stringWidth(chart['title'], "Helvetica", 24) text_height = 24 * 1.2 left = CHART_WIDTH/2 - text_width/2 bottom = CHART_HEIGHT - TITLE_HEIGHT/2 + text_height/2 canvas.setFont("Helvetica", 24) canvas.setFillColorRGB(0.25, 0.25, 0.625) canvas...
set(palette="muted",color_codes=True) rs = np.random.RandomState(10) d = rs.normal(size=100) sns.distplot(d,kde=False,color='b') plt.show() f,axes = plt.subplots(2,2,figsize=(7,7),sharex=True) sns.distplot(d,kde=False,color='b',ax=axes[0,0]) sns.distplot(d,hist=False...
preceding example, we used theinit() function to enable automatic reset to default colors after each print(), but even when not required, init() should always be called (when your code runs on Windows, the init() call enables the mapping from ANSI color codes to the Windows color system...
ax_main.scatter('displ','hwy', s=df.cty*4, c=df.manufacturer.astype('category').cat.codes, alpha=.9, data=df, cmap="tab10", edgecolors='gray', linewidths=.5) # histogram on the right ax_bottom.hist(df.displ,40, histtype...