以数组作为参数的条件函数的形成

Question

我有三个2D数组-- SandArray、ClayArray和SiltArray。我还有一个描述这里的函数。下面是我的代码，当我运行脚本时，我会得到一个ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

def TextureClass(sand, clay, silt):
    
        #if sand + clay > 100 or sand < 0 or clay < 0:
        #    raise Exception('Inputs adds over 100% or are negative')

    if silt + 1.5*clay < 15:
        textural_class = 'sand'

    elif silt + 1.5*clay >= 15 and silt + 2*clay < 30:
        textural_class = 'loamy sand'

    elif (clay >= 7 and clay < 20 and sand > 52 and silt + 2*clay >= 30) or (clay < 7 and silt < 50 and silt + 2*clay >= 30):
        textural_class = 'sandy loam'

    elif clay >= 7 and clay < 27 and silt >= 28 and silt < 50 and sand <= 52:
        textural_class = 'loam'

    elif (silt >= 50 and clay >= 12 and clay < 27) or (silt >= 50 and silt < 80 and clay < 12):
        textural_class = 'silt loam'

    elif silt >= 80 and clay < 12:
        textural_class = 'silt'

    elif clay >= 20 and clay < 35 and silt < 28 and sand > 45:
        textural_class = 'sandy clay loam'

    elif clay >= 27 and clay < 40 and sand > 20 and sand <= 45:
        textural_class = 'clay loam'

    elif clay >= 27 and clay < 40 and sand <= 20:
        textural_class = 'silty clay loam'

    elif clay >= 35 and sand > 45:
        textural_class = 'sandy clay'

    elif clay >= 40 and silt >= 40:
        textural_class = 'silty clay'

    elif clay >= 40 and sand <= 45 and silt < 40:
        textural_class = 'clay'

    else:
        textural_class = 'na'

    return textural_class

Texture = TextureClass(SandArray,ClayArray,SiltArray)

纹理应该是一个与SandArray、ClayArray和SiltArray具有相同形状的数组，但以textural_class str作为其值。

是否可能有一个具有条件的函数的文本输出数组，并使用数组作为它的输入参数，如果有，我遗漏了什么？

编辑:尝试了texture = np.array(list(map(TextureClass,SandArray,ClayArray,SiltArray)))之后，我仍然得到了相同的ValueError

Answer 1

我对numpy不太了解，但是，从我在其他问题中搜索的内容来看，您可以使用矢量化来包装您的函数。

下面是一个例子：如何应用2d numpy数组/矩阵中每个元素的函数/映射值？

使用我之前使用的主要是内置python代码的方法：

您可以zip这三个数组(无论是在函数内部还是外部，但我会在外部执行)，然后在压缩的数组上循环。

zip()函数返回一个zip对象，它是一个元组的迭代器，其中每个传递的迭代器中的第一个项是对的，然后每个传递的迭代器中的第二个项是配对的，等等。 如果传递的迭代器具有不同的长度，则具有最少项的迭代器将决定新迭代器的长度。

强调的是，假定这三个数组的长度相同。而且，在这种情况下，您需要双向压缩：

因此，与Texture = TextureClass(SandArray,ClayArray,SiltArray)不同，您可以使用：

soilCompositions = (zip(sands, clays, silts) for sands, clays, silts in zip(SandArray, ClayArray, SiltArray))
Textures = ((TextureClass(sand, clay, silt) for sand, clay, silt in soilCompositionRow) for soilCompositionRow in soilCompositions)

请注意，我使用了生成器理解，但您也可以轻松地使用列表理解：

soilCompositions = (zip(sands, clays, silts) for sands, clays, silts in zip(SandArray, ClayArray, SiltArray))
Textures = [[TextureClass(sand, clay, silt) for sand, clay, silt in soilCompositionRow] for soilCompositionRow in soilCompositions]

Answer 2

将函数应用于矩阵的每个元素需要np.vectorize。文档是可用的这里。，类似问题的一个例子可以在这里找到：如何应用2d numpy数组/矩阵中每个元素的函数/映射值？。

我认为这个问题是独一无二的，因为它显示了np.vectorize工作的函数的范围。我最初的问题是，np.vectorize是否会像我问题中的条件函数那样工作。

def TextureClass(sand, clay, silt):
    
        #if sand + clay > 100 or sand < 0 or clay < 0:
        #    raise Exception('Inputs adds over 100% or are negative')

    if silt + 1.5*clay < 15:
        textural_class = 'sand'

    elif silt + 1.5*clay >= 15 and silt + 2*clay < 30:
        textural_class = 'loamy sand'

    elif (clay >= 7 and clay < 20 and sand > 52 and silt + 2*clay >= 30) or (clay < 7 and silt < 50 and silt + 2*clay >= 30):
        textural_class = 'sandy loam'

    elif clay >= 7 and clay < 27 and silt >= 28 and silt < 50 and sand <= 52:
        textural_class = 'loam'

    elif (silt >= 50 and clay >= 12 and clay < 27) or (silt >= 50 and silt < 80 and clay < 12):
        textural_class = 'silt loam'

    elif silt >= 80 and clay < 12:
        textural_class = 'silt'

    elif clay >= 20 and clay < 35 and silt < 28 and sand > 45:
        textural_class = 'sandy clay loam'

    elif clay >= 27 and clay < 40 and sand > 20 and sand <= 45:
        textural_class = 'clay loam'

    elif clay >= 27 and clay < 40 and sand <= 20:
        textural_class = 'silty clay loam'

    elif clay >= 35 and sand > 45:
        textural_class = 'sandy clay'

    elif clay >= 40 and silt >= 40:
        textural_class = 'silty clay'

    elif clay >= 40 and sand <= 45 and silt < 40:
        textural_class = 'clay'

    else:
        textural_class = 'na'

    return textural_class

vector_func = np.vectorize(TextureClass)
textures = vector_func(SandArray, ClayArray, SiltArray)