Question

我的数据如下。

dim3 threadsPerBlock(8, 8); 
dim3 grid(targetAreaRect_px._uiWidth / threadsPerBlock.x, targetAreaRect_px._uiHeight / threadsPerBlock.y);
CudaTransformAndAverageImage << < grid, threadsPerBlock >> > (pcPreRasteredImage_dyn, resultArray );

代码是

3.错误消息

   def Simplify(G_x,data):
       data['dx'] = data*G_x 
       data['dy'] = data - data.shift(1)
       data = data.fillna(0)
       data['G_mag'] = np.sqrt((data['dx']+data['dy'])*(data['dx']+data['dy'])-2*data['dx']*data['dy']) 
       data['Theta'] = np.arctan(data['dy']/data['dx'])
       data = data.fillna(0) 
       data['Theta']=0
       data.loc[data['Theta']<0,'Theta'] = data['Theta']+2*np.pi
       data.loc[(data['Theta']<=np.pi/8) & (data['Theta']>=0), 'Theta'] = np.arctan(0)
       data.loc[(data['Theta']<=3*np.pi/8) & (data['Theta']>1*np.pi/8), 'Theta'] = np.arctan(1)
       data.loc[(data['Theta']<=np.pi) & (data['Theta']>3*np.pi/8), 'Theta'] = np.arctan(2)
       data.loc[(data['Theta']<=13*np.pi/8) & (data['Theta']>np.pi), 'Theta'] = np.arctan(-2)
       data.loc[(data['Theta']<=15*np.pi/8) & (data['Theta']>13*np.pi/8), 'Theta'] = np.arctan(-1)
       data.loc[(data['Theta']>15*np.pi/8) & (data['Theta']<=2*np.pi), 'Theta'] = np.arctan(0)
       data['New_dy'] = data['dx']*np.tan(data['Theta'])
       data['N_AC']=data['New_dy'].cumsum()+data['Adj Close'][0]
       return data['N_AC']

4。当我直接运行此代码时，不使用函数。它运作良好。有没有什么好方法可以解决这个问题。谢谢！

Answer 1

您可能已经在某处创建了一个名为np的全局变量，因此当您编写np.sqrt或np.arctan时，它会尝试查找对象np的相应方法调用numpy函数。

或者当你不将它用作函数时，它必须是因为它在函数中不理解np表示包numpy。如果您正在处理笔记本电脑，例如jupyter，只需在您正在使用的笔记本中添加import numpy as np。如果您只在您调用该功能的笔记本中加载numpy，它将无法理解np指的是什么。

'float'对象没有属性'arctan'

1 个答案: