numpy.where(condition, [x, y, ]/) condition:匹配的条件。如果true则返回x,否则y。 a = np.arange(12).reshape(4,3) a array([[ 0, 1, 2], [ 3, 4, 5], [ 6, 7, 8], [ 9, 10, 11]]) np.where(a>5) ## Get The Index --- (array([2, 2, 2, 3, 3, 3], dtype=int...
np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of elements np.any N/A Evaluate whether any elements are true np.all N/A Evaluate whether all elements are true np.power 幂运算 ...
代码语言:javascript 复制 >>> # Create an empty array with 2 elements >>> np.empty(2) array([3.14, 42\. ]) # may vary 您可以创建一个具有元素范围的数组: 代码语言:javascript 复制 >>> np.arange(4) array([0, 1, 2, 3]) 甚至可以创建一个包含一系列均匀间隔的区间的数组。为此,您需...
# Input np.random.seed(100) a = np.random.randint(0, 5, 10) ## Solution # There is no direct function to do this as of 1.13.3 # Create an all True array out = np.full(a.shape[0], True) # Find the index positions of unique elements unique_positions = np.unique(a, return_...
–Elements fromywhen the condition isFalse. Therefore, chaining thenp.max()andnp.where()functions, we can find the maximum element, followed by the index at which it occurs. Instead of the above two-step process, you can use the NumPy argmax() function to get the index of the maximum...
The test is equivalent to abs(desired-actual) < 0.5 * 10**(-decimal) Given two objects (numbers or ndarrays), check that all elements of these objects are almost equal. An exception is raised at conflicting values. For ndarrays this delegates to assert_array_almost_equal Parameters --- ...
def maxx(x, y): """Get the maximum of two items""" if x >= y: return x else: return y pair_max = np.vectorize(maxx, otypes=[float]) a = np.array([5, 7, 9, 8, 6, 4, 5]) b = np.array([6, 3, 4, 8, 9, 7, 1]) pair_max(a, b) array([6., 7., 9., ...
import numpy as np x = np.array([[1,2], [3,4]]) print(np.sum(x)) # Compute sum of all elements; prints "10" print(np.sum(x, axis=0)) # Compute sum of each column; prints "[4 6]" print(np.sum(x, axis=1)) # Compute sum of each row; prints "[3 7]"tile...
If there are no elements, the if condition will become true and it will print the empty message. If our array is equal to: a = numpy.array([]) The output of the above code will be as below: Find the index of a value To find the index of value, we can use the where() method...
np.where(condition): 输出满足条件 (即非0) 元素的坐标 a = np.array([2,4,6,8,10,3]).reshape(2,3) c = np.where(a > 5) # 返回索引 out : (array([0, 1, 1], dtype=int64), array([2, 0, 1], dtype=int64)) a[c] # 获得元素 2.2.6 元素删除 np.delete(arr, obj, axis=...