我想从文件中读取数字并将其存储到二维数组中。
文件内容:
- 包含w,h的行
- h行,每行包含w个以空格分隔的整数
例如:
4 3
1 2 3 4
2 3 4 5
6 7 8 9
我想从文件中读取数字并将其存储到二维数组中。
文件内容:
例如:
4 3
1 2 3 4
2 3 4 5
6 7 8 9
with open('file') as f:
w, h = [int(x) for x in next(f).split()] # read first line
array = []
for line in f: # read rest of lines
array.append([int(x) for x in line.split()])
你可以将最后的for循环压缩成一个嵌套的列表推导式:
with open('file') as f:
w, h = [int(x) for x in next(f).split()]
array = [[int(x) for x in line.split()] for line in f]
readline
和line in f
,我对此给予高度评价。干杯。 - machine yearningnext(f)
和f.readline()
,因为next()
实际上是使用readline()
实现的,并且缓冲区被移动到一个单独的类中,该类用于从文件读取的所有机制。感谢您指出这一点。我现在记得几年前读过它,但当我写下先前的评论时,它已经从我的脑海中滑落了。 - Sven Marnachopen(name, mode)
, myfile.readlines()
, mystring.split()
, int(myval)
, 然后你可能想以Pythonic的方式将它们组合起来使用一些生成器。# This opens a handle to your file, in 'r' read mode
file_handle = open('mynumbers.txt', 'r')
# Read in all the lines of your file into a list of lines
lines_list = file_handle.readlines()
# Extract dimensions from first line. Cast values to integers from strings.
cols, rows = (int(val) for val in lines_list[0].split())
# Do a double-nested list comprehension to get the rest of the data into your matrix
my_data = [[int(val) for val in line.split()] for line in lines_list[1:]]
在这里查找生成器表达式。它们可以将您的代码简化为离散的功能单元!想象一下在C++中用4行做同样的事情...它会是一个怪物。特别是列表生成器,当我还是C ++用户时,我总是希望有像那样的东西,并经常最终构建自定义函数来构造我想要的每种类型的数组。
cols, rows = (int(val) for val in '4 3\n')
不会达到你想要的效果。同样,对于 [int(val) for val in line]
也是一样的,因为 line
将会是类似 '1 2 3 4\n'
的东西。 - Jason R. Coombs不确定为什么需要w,h。如果这些值确实是必需的,并且意味着只应读取指定数量的行和列,则可以尝试以下操作:
output = []
with open(r'c:\file.txt', 'r') as f:
w, h = map(int, f.readline().split())
tmp = []
for i, line in enumerate(f):
if i == h:
break
tmp.append(map(int, line.split()[:w]))
output.append(tmp)
可以同时使用Python2(例如Python 2.7.10)和Python3(例如Python 3.6.4)。
with open('in.txt') as f:
rows,cols=np.fromfile(f, dtype=int, count=2, sep=" ")
data = np.fromfile(f, dtype=int, count=cols*rows, sep=" ").reshape((rows,cols))
另一种方法是同时使用Python2(例如Python 2.7.10)和Python3(例如Python 3.6.4),对于复杂矩阵,请参见下面的示例(只需将int
更改为complex
)。
with open('in.txt') as f:
data = []
cols,rows=list(map(int, f.readline().split()))
for i in range(0, rows):
data.append(list(map(int, f.readline().split()[:cols])))
print (data)
我更新了代码,这种方法适用于任意数量和任何类型的矩阵(int
,complex
,float
),在初始的in.txt
文件中。
该程序作为一个应用程序产生矩阵乘法。可以在python2中使用,如果要在python3中使用,请进行以下更改。
print to print()
并且
print "%7g" %a[i,j], to print ("%7g" %a[i,j],end="")
脚本:
import numpy as np
def printMatrix(a):
print ("Matrix["+("%d" %a.shape[0])+"]["+("%d" %a.shape[1])+"]")
rows = a.shape[0]
cols = a.shape[1]
for i in range(0,rows):
for j in range(0,cols):
print "%7g" %a[i,j],
print
print
def readMatrixFile(FileName):
rows,cols=np.fromfile(FileName, dtype=int, count=2, sep=" ")
a = np.fromfile(FileName, dtype=float, count=rows*cols, sep=" ").reshape((rows,cols))
return a
def readMatrixFileComplex(FileName):
data = []
rows,cols=list(map(int, FileName.readline().split()))
for i in range(0, rows):
data.append(list(map(complex, FileName.readline().split()[:cols])))
a = np.array(data)
return a
f = open('in.txt')
a=readMatrixFile(f)
printMatrix(a)
b=readMatrixFile(f)
printMatrix(b)
a1=readMatrixFile(f)
printMatrix(a1)
b1=readMatrixFile(f)
printMatrix(b1)
f.close()
print ("matrix multiplication")
c = np.dot(a,b)
printMatrix(c)
c1 = np.dot(a1,b1)
printMatrix(c1)
with open('complex_in.txt') as fid:
a2=readMatrixFileComplex(fid)
print(a2)
b2=readMatrixFileComplex(fid)
print(b2)
print ("complex matrix multiplication")
c2 = np.dot(a2,b2)
print(c2)
print ("real part of complex matrix")
printMatrix(c2.real)
print ("imaginary part of complex matrix")
printMatrix(c2.imag)
我将采用作为输入文件的 in.txt
:
4 4
1 1 1 1
2 4 8 16
3 9 27 81
4 16 64 256
4 3
4.02 -3.0 4.0
-13.0 19.0 -7.0
3.0 -2.0 7.0
-1.0 1.0 -1.0
3 4
1 2 -2 0
-3 4 7 2
6 0 3 1
4 2
-1 3
0 9
1 -11
4 -5
以及 complex_in.txt
3 4
1+1j 2+2j -2-2j 0+0j
-3-3j 4+4j 7+7j 2+2j
6+6j 0+0j 3+3j 1+1j
4 2
-1-1j 3+3j
0+0j 9+9j
1+1j -11-11j
4+4j -5-5j
输出结果如下:
Matrix[4][4]
1 1 1 1
2 4 8 16
3 9 27 81
4 16 64 256
Matrix[4][3]
4.02 -3 4
-13 19 -7
3 -2 7
-1 1 -1
Matrix[3][4]
1 2 -2 0
-3 4 7 2
6 0 3 1
Matrix[4][2]
-1 3
0 9
1 -11
4 -5
matrix multiplication
Matrix[4][3]
-6.98 15 3
-35.96 70 20
-104.94 189 57
-255.92 420 96
Matrix[3][2]
-3 43
18 -60
1 -20
[[ 1.+1.j 2.+2.j -2.-2.j 0.+0.j]
[-3.-3.j 4.+4.j 7.+7.j 2.+2.j]
[ 6.+6.j 0.+0.j 3.+3.j 1.+1.j]]
[[ -1. -1.j 3. +3.j]
[ 0. +0.j 9. +9.j]
[ 1. +1.j -11.-11.j]
[ 4. +4.j -5. -5.j]]
complex matrix multiplication
[[ 0. -6.j 0. +86.j]
[ 0. +36.j 0.-120.j]
[ 0. +2.j 0. -40.j]]
real part of complex matrix
Matrix[3][2]
0 0
0 0
0 0
imaginary part of complex matrix
Matrix[3][2]
-6 86
36 -120
2 -40
f = open("input.txt", 'r')
nums = f.readlines()
nums = [int(i) for i in nums]
读取文件的每一行,将每个字符串转换为数字
nums.sort()
排序数字
f.close()
f = open("input.txt", 'w')
for num in nums:
f.write("%d\n" %num)
f.close()
。
with open("file") as f:
(w, h), data = [int(x) for x in f.readline().split()], [int(x) for x in f.read().split()]