import math import matplotlib.pyplot as plt import numpy as np if __name__ == '__main__': #获得浮点类型numpy数组 x = np.arange(0.05,3,0.05) #获得函数结果 y1 = [math.log(a,1.5) for a in x] #画图 plt.plot(x, y1, linewidth=2,
问在matplotlib中将直线拟合到log-log曲线EN现在，您可以对它们执行操作。loglog-plot的作用是将a和b的对...
This guide shows how to create a scatterplot with log-transformed axes in Matplotlib. This post uses the object oriented interface and thus uses ax.set_xscale('log'), but this can also be achieved with plt.xscale('log') if you're using plt.plot()...
绘制log()函数图像,并在图上标注选定的两个点 importmathimportmatplotlib.pyplotaspltif__name__ =='__main__': x = [float(i)/200.0foriinrange(1,400)] y = [math.log(i)foriinx] plt.plot(x,y,'r-',linewidth=3, label='log Curve') a = [x[30],x[205]] b = [y[30],y[205]...
plot(d_log['sum'],label='sum') ax2.legend(loc=0) <matplotlib.legend.Legend at 0xcb8d1d0> d_log.corr() countsum count 1.000000 0.512629 sum 0.512629 1.000000 状态码分析 log.head() statusresponse_bytes_clfremote_hostrequest_first_line time_received 2013-03-16 04:00:25 200 0.024916 ...
Matplotlib是一个流行的Python绘图库,可以用于创建各种图表。例如,绘制每小时日志数量的折线图: import matplotlib.pyplot as plt plt.figure(figsize=(10, 6)) plt.plot(hourly_counts.index, hourly_counts.values, marker='o') plt.title('Hourly Log Count') ...
import matplotlib.pyplot as plt df['timestamp'] = pd.to_datetime(df['timestamp']) df.set_index('timestamp', inplace=True) level_counts = df['level'].resample('H').count() plt.figure(figsize=(10, 5)) plt.plot(level_counts.index, level_counts.values) ...
import numpy as np import math import matplotlib.pyplot as plt x=np.arange(0.05,3,0.05) y1=[math.log(a,1.5)for a in x] y2=[math.log(a,2)for a in x] y3=[math.log(a,3)for a in x] plot1=plt.plot(x,y1,'-g',label="log1.5(x)") plot2=plt.plot(x,y2,'-r',label=...
Bug summary I am trying to generate a plot and using log to show relative comparison, the plot is correctly shown however, the saved figure doesn't have any plots, only axis. https://stackoverflow.com/questions/78742649/matplotlib-not-ge...
ax.plot(x, y) #绘制决策边界 plt.title('BestFit') #绘制title plt.xlabel('X1'); plt.ylabel('X2') #绘制坐标轴 plt.show() 1. 2. 3. 4. 5. 6. 7. 8. 分类试验 # -*- coding:UTF-8 -*- import matplotlib.pyplot as plt