np.delete(data,index2,axis=0)
时间: 2024-05-21 21:11:30 浏览: 9
This function removes the rows specified by the index2 parameter from the data array along the axis specified by the axis parameter (axis=0 means removing rows, axis=1 means removing columns). The modified data array is returned.
相关问题
请问应该在python中导入什么库运行下列代码:def createSpec(data): fs=256 lowcut=117 highcut=123 y=butter_bandstop_filter(data, lowcut, highcut, fs, order=6) lowcut=57 highcut=63 y=butter_bandstop_filter(y, lowcut, highcut, fs, order=6) cutoff=1 y=butter_highpass_filter(y, cutoff, fs, order=6) Pxx=signal.spectrogram(y, nfft=256, fs=256, return_onesided=True, noverlap=128)[2] Pxx = np.delete(Pxx, np.s_[117:123+1], axis=0) Pxx = np.delete(Pxx, np.s_[57:63+1], axis=0) Pxx = np.delete(Pxx, 0, axis=0) result=(10*np.log10(np.transpose(Pxx))-(10*np.log10(np.transpose(Pxx))).min())/(10*np.log10(np.transpose(Pxx))).ptp() return result
您需要导入以下库:
import numpy as np
from scipy import signal
并且需要使用如下代码来定义butter_bandstop_filter和butter_highpass_filter两个函数:
def butter_bandstop_filter(data, lowcut, highcut, fs, order=5):
nyq = 0.5 * fs
low = lowcut / nyq
high = highcut / nyq
b, a = signal.butter(order, [low, high], btype='bandstop')
y = signal.filtfilt(b, a, data)
return y
def butter_highpass_filter(data, cutoff, fs, order=5):
nyq = 0.5 * fs
normal_cutoff = cutoff / nyq
b, a = signal.butter(order, normal_cutoff, btype='highpass')
y = signal.filtfilt(b, a, data)
return y
接下来,您可以直接使用上述代码中的createSpec函数。
for i in range(len(data)): if data[i,-1] == 2: clear_arr = np.delete(data,i,axis=0) print(clear_arr)
This code iterates through each row in the "data" array using a for loop with the range function.
For each row, it checks if the last element (indicated by "-1") is equal to 2.
If the last element is 2, it uses the numpy "delete" function to remove that entire row from the "data" array, creating a new array called "clear_arr".
Finally, it prints the "clear_arr" array.
Overall, this code appears to be removing any rows from the "data" array where the last element is equal to 2.
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