Python NumPy maximum() or max() function is used to get the maximum value (greatest value) of a given array, or compare the two arrays
Python code for running maximum of NumPy array values # Import numpyimportnumpyasnp# Creating a numpy arrayarr=[4,2,1,3,1,2,3,4]# Display original dataprint("Original data:\n",arr,"\n")# Using maximum accumulateres=np.maximum.accumulate(arr)# Display resultprint("Result:\n",res) ...
maximum() Return Value Themaximum()function returns an array containing element-wise maximum of two arrays. Example 1: maximum() With 2-D Array importnumpyasnp# create two 2-D arraysarray1 = np.array([[1,2,3], [4,5,6]]) array2 = np.array([[2,4,1], [5,3,2]]) # find t...
Arrays Arrays in numpy have elements all of the same type and occupy the same amount of storage, an element can be composed of other simple types, have a fixed size (cannot grow like lists), have a shape specified with a tuple, the tuple gives the size of each dimension, are inde...
maximum和minimum不再发出警告 Umath 和 multiarray c-extension 模块合并为单一模块 getfield有效性检查扩展 NumPy 函数现在支持__array_function__重载 基于只读缓冲区的数组不可设置writeable 1.15.4 兼容性说明 贡献者 合并的 Pull 请求 1.15.3 兼容性说明 贡献者 合并的 Pull 请求 1.15.2 ...
ch04:NumPy 基础: Arrays(数组) 和 Vectorized(矢量) 计算 NumPy 基础: Arrays(数组) 和 Vectorized(矢量) 计算¶ In [2]: %matplotlibinline In [1]: from__future__importdivisionfromnumpy.randomimportrandnimportnumpyasnpnp.set_printoptions(precision=4,suppress=True) ...
np.maximum(x, y) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 array([ 0.3313, 1.3497, 0.0699, 0.2467, -0.0119, 1.0048, 1.3272, -0.7539]) 返 回浮点数数组的小数和整数部分: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 arr = np.random.randn(7) * 5 代码语言:javascript 代...
ediff1d(ary[, to_end, to_begin])The differences between consecutive elements of an array. gradient(f, *varargs, **kwargs)Return the gradient of an N-dimensional array. cross(a, b[, axisa, axisb, axisc, axis])Return the cross product of two (arrays of) vectors. trapz(y[, x, dx...
Thenumpy.max()method returns the maximum of an array along the given axis. Conversely, thenumpy.min()method returns the minimum of an array along the given axis. Note that the methods don't ignore theNaNvalues. If you need to ignore theNaNvalues, use thenumpy.nanmax()andnumpy.nanmin()...
>>> np.amax(a) # Maximum of the flattened array 3 >>> np.amax(a, axis=0) # Maxima along the first axis array([2, 3]) >>> np.amax(a, axis=1) # Maxima along the second axis array([1, 3]) >>> np.amax(a, where=[False, True], initial=-1, axis=0) ...