在NumPy中沿轴1连接一系列掩码数组
要在特定轴上连接一系列掩码数组,请使用Python NumPy中的**ma.stack()**方法。“**axis**”参数用于设置轴。axis参数指定结果维度中新轴的索引。例如,如果axis=0,它将是第一维;如果axis=-1,它将是最后一维。
如果提供out参数,则将其作为目标位置放置结果。形状必须正确,与未指定out参数时stack返回的形状匹配。
该函数返回的堆叠数组比输入数组多一个维度。它同时应用于_data和_mask(如果有)。
步骤
首先,导入所需的库:
import numpy as np import numpy.ma as ma
创建数组1,一个使用numpy.arange()方法创建的包含整数元素的3x3数组:
arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1)
print("
Array type...
", arr1.dtype)创建掩码数组1:
arr1 = ma.array(arr1)
掩码数组1:
arr1[0, 1] = ma.masked arr1[1, 1] = ma.masked
显示掩码数组1:
print("
Masked Array1...
",arr1)
创建数组2,另一个使用numpy.arange()方法创建的包含整数元素的3x3数组:
arr2 = np.arange(9).reshape((3,3))
print("
Array2...
", arr2)
print("
Array type...
", arr2.dtype)创建掩码数组2:
arr2 = ma.array(arr2)
掩码数组2:
arr2[2, 1] = ma.masked arr2[2, 2] = ma.masked
显示掩码数组2:
print("
Masked Array2...
",arr2)
要在特定轴上连接一系列掩码数组,请使用Python NumPy中的ma.stack()方法。“axis”参数用于设置轴:
print("
Result of joining arrays...
",ma.stack((arr1, arr2), axis = 1))示例
# Python ma.MaskedArray - Join a sequence of masked arrays along axis 1
import numpy as np
import numpy.ma as ma
# Array 1
# Creating a 3x3 array with int elements using the numpy.arange() method
arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1)
print("
Array type...
", arr1.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr1.ndim)
# Get the shape of the Array
print("
Our Array Shape...
",arr1.shape)
# Get the number of elements of the Array
print("
Elements in the Array...
",arr1.size)
# Create a masked array
arr1 = ma.array(arr1)
# Mask Array1
arr1[0, 1] = ma.masked
arr1[1, 1] = ma.masked
# Display Masked Array 1
print("
Masked Array1...
",arr1)
# Array 2
# Creating another 3x3 array with int elements using the numpy.arange() method
arr2 = np.arange(9).reshape((3,3))
print("
Array2...
", arr2)
print("
Array type...
", arr2.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr2.ndim)
# Get the shape of the Array
print("
Our Array Shape...
",arr2.shape)
# Get the number of elements of the Array
print("
Elements in the Array...
",arr2.size)
# Create a masked array
arr2 = ma.array(arr2)
# Mask Array2
arr2[2, 1] = ma.masked
arr2[2, 2] = ma.masked
# Display Masked Array 2
print("
Masked Array2...
",arr2)
# To join a sequence of masked arrays along specific axis, use the ma.stack() method in Python Numpy
# The axis is set using the "axis" parameter
print("
Result of joining arrays...
",ma.stack((arr1, arr2), axis = 1))输出
Array1... [[0 1 2] [3 4 5] [6 7 8]] Array type... int64 Array Dimensions... 2 Our Array Shape... (3, 3) Elements in the Array... 9 Masked Array1... [[0 -- 2] [3 -- 5] [6 7 8]] Array2... [[0 1 2] [3 4 5] [6 7 8]] Array type... int64 Array Dimensions... 2 Our Array Shape... (3, 3) Elements in the Array... 9 Masked Array2... [[0 1 2] [3 4 5] [6 -- --]] Result of joining arrays... [[[0 -- 2] [0 1 2]] [[3 -- 5] [3 4 5]] [[6 7 8] [6 -- --]]]
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