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我有一个包含 81 个数字的 1D 数组,对应于每 2.5 米深度的 81 个温度,我需要将其插入到一个 3D 数组网格中,该网格在 z-dir 中有 100 个点,在 x-dir 中有 6 个点,在 y-中有 599 个点目录 我创建一维值的功能是:

zz = np.arange(-200,0.1,2.5)
def grid_function(x, ABath=-0.2, BBath=0.1, CBath=50.,DBath=10.):
    """This function creates a theoretical grid"""

    from numpy import tanh, arange


    ans = ABath * (tanh(BBath * (-x - CBath))) + DBath
    return ans

temp = grid_function(zz)

下面是我的网格的横截面 在此处输入图像描述

我不知道我是否清楚我的要求,但如果有人知道一种方法,我将非常感激。

问候,

4

1 回答 1

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您应该能够从现有的temp1D 数组构造一个 3D 数组,如下所示:

zz = np.arange(-200,0.1,2.5)
def grid_function(x, ABath=-0.2, BBath=0.1, CBath=50.,DBath=10.):
    """This function creates a theoretical grid"""

    from numpy import tanh, arange


    ans = ABath * (tanh(BBath * (-x - CBath))) + DBath
    return ans

temp = grid_function(zz)

# Construct 1D 100-element array with z-coordinates
z_new = np.linspace(zz[0], zz[-1], 100)

# Interpolate 1D temperatures at new set of 100 z-coordinates
temp_1d_new = np.interp(z_new, zz, temp)

# Replicate 1D temperatures into two additional dimensions
temp_3d_new = np.tile(temp_1d_new, (6, 599, 1))

但是,您也可以采用更直接的方法,立即从具有所需 100 个元素的 z 坐标一维数组开始(即跳过插值步骤)。像这样:

def grid_function(x, ABath=-0.2, BBath=0.1, CBath=50.,DBath=10.):
    """This function creates a theoretical grid"""

    from numpy import tanh, arange


    ans = ABath * (tanh(BBath * (-x - CBath))) + DBath
    return ans

# Create 1D arrays with x-coordinates, y-coordinates and z-coordinates
x = np.linspace(0., 100., 6)
y = np.linspace(0., 100., 599)
z = np.linspace(-200., 0., 100)

# Create 3D meshgrids for x-coordinates, y-coordinates and z-coordinates
(xx, yy, zz) = np.meshgrid(x, y, z)

# Calculate temperatures 3D array from z-coordinates 3D array
temp = grid_function(zz)

边注

将 import 语句始终放在代码文件的顶部被认为是一种很好的做法。

于 2018-11-05T23:41:40.483 回答