小编oop*_*ops的帖子

我有一个形状为(30,480,640)的numpy ndarray,第1和第2轴代表位置(纬度和长度),第0轴包含实际数据点.我想在每个位置沿第0轴使用最频繁的值,是构造一个形状为(1,480,640).ie的新数组:

>>> data
array([[[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19]],

       [[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19]],

       [[40, 40, 42, 43, 44],
        [45, 46, 47, 48, 49],
        [50, 51, 52, 53, 54],
        [55, 56, 57, 58, 59]]])

(perform calculation)

>>> new_data 
array([[[ 0,  1,  2,  3,  4],
        [ 5, …

是否有另一种方法在numpy中实现scipy.stats.mode函数以获取沿轴的ndarrays中最常见的值？(不导入其他模块)即

import numpy as np
from scipy.stats import mode

a = np.array([[[ 0,  1,  2,  3,  4],
                  [ 5,  6,  7,  8,  9],
                  [10, 11, 12, 13, 14],
                  [15, 16, 17, 18, 19]],

                 [[ 0,  1,  2,  3,  4],
                  [ 5,  6,  7,  8,  9],
                  [10, 11, 12, 13, 14],
                  [15, 16, 17, 18, 19]],

                 [[40, 40, 42, 43, 44],
                  [45, 46, 47, 48, 49],
                  [50, 51, 52, 53, 54],
                  [55, 56, 57, 58, 59]]])

mode= mode(data, axis=0)
mode = …

如何将多个numpy数组写入多个列中的一个csv文件？

import numpy
import csv

arrA = numpy.array(file.root.a)
arrB = numpy.array(file.root.b)
arrC = numpy.array(file.root.c)

for i in range (480):
    for j in range (640):
        (write arrA[i,j] into column1,write arrB[i,j] into column2,write arrC[i,j] into column3)

非常感谢!

我有三个阵列:经度(400,600),纬度(400,600),数据(30,400,60); 我想要做的是根据它的位置(纬度和经度)提取数据数组中的值.

这是我的代码:

    import numpy
    import tables

    hdf = "data.hdf5"
    h5file = tables.openFile(hdf, mode = "r")

    lon = numpy.array(h5file.root.Lonitude)
    lat = numpy.array(h5file.root.Latitude)
    arr = numpy.array(h5file.root.data)

    lon = numpy.array(lon.flat)
    lat = numpy.array(lat.flat)
    arr = numpy.array(arr.flat)

    lonlist=[]
    latlist=[]
    layer=[]
    fre=[]

    for i in range(0,len(lon)):
        for j in range(0,30):
            longi = lon[j]
            lati = lat[j]
            layers=[j]
            frequency= arr[i]

            lonlist.append(longi)
            latlist.append(lati)
            layer.append(layers)
            fre.append(frequency)

    output = numpy.column_stack((lonlist,latlist,layer,fre))

问题是"频率"不是我想要的.我希望数据数组沿着零轴变平,因此"频率"将是一个位置的30个值.这样的函数在numpy中沿着特定的轴展平ndarray？