NumPy-Maske 2D-Array Salman Mehmood15 Februar 2024 NumPyNumPy Mask Video Player is loading. Current Time0:00 / Duration-:- Loaded:0% Wir lernen mit dieser Erklärung, was die Maske oder das boolesche Array ist. Wir lernen auch, wie man eine 2D-Maske mit logischen P1ython-Operatoren ...
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # 创建一个布尔掩码,这里我们选择所有大于5的元素 mask = arr > 5 print("原始数组:") print(arr) print("布尔掩码:") print(mask) # 使用掩码来获取满足条件的元素 # 注意:这里会返回一个一维数组 filtered_elements = arr[mask] ...
In [33]: mask = np.ones(arr.shape, bool)In [34]: mask[np.arange(10), idxs] = FalseIn [35]: arr[mask]Out[35]: array([ 1, 2, 3, 5, 6, 8, 9, 11, 12, 13, 16, 17, 18, 19, 21, 22, 24, 26, 28, 29]) boolean索引生成一个平面数组,因此我们需要重新整形以获得2d: ...
x = np.zeros((2,5))# create 2D array of zeroes x[0][1:3] =5# replace some values along 1st dimension with 5 mask = (x[0] >0)# create a mask to only deal with the non negative values x[0][mask][1] =10# change one of the values that is non negative printx[0][mask]...
Array Shape...",maskArr.shape) # Get the number of elements of the Masked Array print("Elements in the Masked Array...",maskArr.size) # To mask columns of a 2D array that contain masked values, use the np.ma.mask_cols() method in Numpy print("Result...",np.ma.mask_cols(mask...
#NumPy: Apply a Mask from one 2D Array to another 2D Array This approach also works if you need to apply a mask from one 2D array to another 2D array. main.py importnumpyasnp x =np.array([[1,3],[5,7],[9,12]])y =np.array([[2,4],[6,8],[10,14]])masked_y_array=np...
废弃PyArray_As1D、PyArray_As2D 废弃np.alen 废弃金融函数 numpy.ma.mask_cols 和numpy.ma.mask_row 的axis 参数已废弃 过时的废弃功能 兼容性说明 numpy.lib.recfunctions.drop_fields 不再返回 None numpy.argmin/argmax/min/max 在数组存在 NaT 的情况下返回 NaT np.can_cast(np.uint64, ...
mask= b >=0 plt.plot(a[mask], b[mask],'bo') mask= (b >= 0) & (a <= np.pi / 2) plt.plot(a[mask], b[mask],'go') plt.show() 上面的示例显示了如何进行布尔屏蔽。你所要做的就是将数组传递给涉及数组的条件,它将为你提供一个值的数组,为该条件返回true。
import numpy as np import numpy.ma as ma # Create a 2D NumPy array of shape (5, 5) with random integers array_2d = np.random.randint(0, 100, size=(5, 5)) # Define an initial condition to mask elements less than 20 initial_condition = array_2d < 20 # Create a masked...
importnumpyasnpimportnumpy.maasma# 创建和连接masked arraysarr1=ma.array([1,2,3],mask=[0,0,1])arr2=ma.array([4,5,6],mask=[1,0,0])result=np.concatenate((arr1,arr2))print("numpyarray.com - Concatenated masked arrays:")print(result)print("Mask of the result:",result.mask)...