NumPy中沿指定轴返回掩码数组的值范围
要返回掩码数组的值范围,请在NumPy中使用**ma.MaskedArray.ptp()**方法。峰峰值(最大值 - 最小值)沿给定轴。轴使用**axis**参数设置。ptp()方法返回一个包含结果的新数组,除非指定了out,在这种情况下,将返回对out的引用。
axis参数是查找峰值的轴。如果为None(默认值),则使用扁平化数组。out是一个参数,一个替代输出数组,用于放置结果。它必须与预期输出具有相同的形状和缓冲区长度,但如果需要,类型将被转换。
如果keepdims参数设置为True,则减少的轴将作为大小为一的维度保留在结果中。使用此选项,结果将针对数组正确广播。
步骤
首先,导入所需的库:
import numpy as np import numpy.ma as ma
使用numpy.array()方法创建一个包含整型元素的数组:
arr = np.array([[55, 85, 68, 84], [67, 33, 39, 53], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)获取数组的维度:
print("Array Dimensions...
",arr.ndim)
创建一个掩码数组并将其中的某些元素标记为无效:
maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)获取掩码数组的维度:
print("
Our Masked Array Dimensions...
",maskArr.ndim)
获取掩码数组的形状:
print("
Our Masked Array Shape...
",maskArr.shape)获取掩码数组的元素个数:
print("
Elements in the Masked Array...
",maskArr.size)
要返回掩码数组的值范围,请在NumPy中使用ma.MaskedArray.ptp()方法。峰峰值(最大值 - 最小值)沿给定轴。轴使用axis参数设置:
print("
Peak to peak value (max - min)...
",
np.ptp(maskArr, axis=1))示例
import numpy as np
import numpy.ma as ma
# Create an array with int elements using the numpy.array() method
arr = np.array([[55, 85, 68, 84], [67, 33, 39, 53], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)
# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)
# Get the dimensions of the Masked Array
print("
Our Masked Array Dimensions...
",maskArr.ndim)
# Get the shape of the Masked Array
print("
Our Masked Array Shape...
",maskArr.shape)
# Get the number of elements of the Masked Array
print("
Elements in the Masked Array...
",maskArr.size)
# To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy.
# Peak to peak (maximum - minimum) value along a given axis.
# The axis is set using the axis parameter
print("
Peak to peak value (max - min)...
", np.ptp(maskArr, axis=1))输出
Array... [[55 85 68 84] [67 33 39 53] [29 88 51 37] [56 45 99 85]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 68 84] [67 33 -- 53] [29 88 51 --] [56 -- 99 85]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 4) Elements in the Masked Array... 16 Peak to peak value (max - min)... [16 34 59 43]
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