dta.plot(figsize=(12,8))plt.show() // 在Scala IDE要输入这个命令才能显示图！
f1 = plt.figure(figsize=(12, 8)) ax1 = f1.add_subplot(111) mean_sample = False if len(fig_data[0].shape)==1 else True if mean_sample: fig_data = [ np.mean(fig_data_s, axis=0) for fig_data_s in fig_data] for i in range(len(fig_data)): ax1.plot(epochsInds, fig_...
plot(x,y2,color='green', marker='o', linestyle='dashed', linewidth=1, markersize=6) plot(x,y3,color='#900302',marker='+',linestyle='-') 1. 2. 3. 常见的颜色参数:**Colors** === === character color === === ``'b'`` blue 蓝 ``'g'`` green 绿 ``'r'`` red 红 ``...
fig = PlotUtilities.figure(figsize=(8,12)) IWT_Util.EnergyLandscapePlot(LandscapeObj) PlotUtilities.savefig(fig,OutBase +"IWT.png") 开发者ID:prheenan,项目名称:Research,代码行数:32,代码来源:IWT_Main.py 示例3: run ▲点赞 3▼ # 需要导入模块: from GeneralUtil.python import PlotUtilities [a...
plt.xticks(fontsize=12) plt.yticks(fontsize=12) plt.show 9. 矩阵图 成对图是探索性分析中的最爱,以理解所有可能的数字变量对之间的关系。它是双变量分析的必备工具。 # Load Dataset df = sns.load_dataset('iris') # Plot plt.figure(figsize=(10,8), dpi= 80) ...
plt.figure('tensorflow-手写数字',figsize=(12,6)) plt.scatter(list(range(len(x))),x,c=y,label='source={0}'.format(source)) font_size={'size':15} plt.title('one_hot-label',font_size) plt.xlabel('第i个数字',font_size)
plt.figure(figsize=figsize) date_index = self.index[-h:] predictions = self.predict_is(h) data = self.data[-h:] t_params = self.transform_z() plt.plot(date_index,np.abs(data-t_params[-1]),label='Data') plt.plot(date_index,predictions,label='Predictions',c='black') ...
plt.figure(figsize=(8, 5)) plt.plot(x, y, label="$sin(x)$", color="red", linewidth=2) #label可以使用内嵌Latex引擎,color可以用0到1范围内三个元素的元组表示(1.0,0.0,0.0)也表示红色,linwidth:指定曲线的宽度,可以不是整数,也可以缩写为1w. ...
figure(num=None, figsize=(2.8,1.7), dpi=300)# figsize的2.8和1.7指的是英寸,dpi指定图片分辨率。那么图片就是(2.8*300)*(1.7*300)像素大小plt.plot(test_mean_1000S_n,'royalblue', label='without threshold') plt.plot(test_mean_1000S,'darkorange', label='with threshold')# 画图,并指定颜色plt...
def multiPolygonShow(lst): cmap = plt.cm.get_cmap('RdPu') #'Spectral' https://matplotlib.org/2.0.1/users/colormaps.html fig, axs = plt.subplots(figsize=(20,20)) axs.set_aspect('equal', 'datalim') i=0 for geom in multiSegs.geoms: xs, ys = geom.exterior.xy axs.fill(xs, ys...