I'd like to read numbers from file into two dimensional array.
我想从文件中读取数据到二维数组中。
File contents:
文件内容:
- line containing w, h
- 行包含w h
- h lines containing w integers separated with space
- 包含与空间分隔的w整数的h行。
For example:
例如:
4 3
1 2 3 4
2 3 4 5
6 7 8 9
4 个解决方案
#1
65
Assuming you don't have extraneous whitespace:
假设你没有多余的空白:
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()])
You could condense the last for loop into a nested list comprehension:
您可以将最后一个循环压缩为嵌套列表理解:
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]
#2
12
To me this kind of seemingly simple problem is what Python is all about. Especially if you're coming from a language like C++, where simple text parsing can be a pain in the butt, you'll really appreciate the functionally unit-wise solution that python can give you. I'd keep it really simple with a couple of built-in functions and some generator expressions.
对我来说，这类看似简单的问题是Python的全部内容。特别是，如果您使用的是像c++这样的语言，在这里简单的文本解析可能会让您感到痛苦，您将非常感激python能够给您的功能上的单元解决方案。我将使用一些内置函数和一些生成器表达式来保持它的简单性。
You'll need open(name, mode), myfile.readlines(), mystring.split(), int(myval), and then you'll probably want to use a couple of generators to put them all together in a pythonic way.
您需要打开(名称、模式)、myfile.readlines()、mystring.split()、int(myval)，然后您可能需要使用几个生成器以python的方式将它们组合在一起。
# 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:]]
Look up generator expressions here. They can really simplify your code into discrete functional units! Imagine doing the same thing in 4 lines in C++... It would be a monster. Especially the list generators, when I was I C++ guy I always wished I had something like that, and I'd often end up building custom functions to construct each kind of array I wanted.
在这里查找生成器表达式。他们可以将你的代码简化成离散的功能单元!想象一下在c++中做同样的事情。那将是一个怪物。特别是列表生成器，当我是c++的时候，我总是希望我有这样的东西，我经常会构建自定义函数来构造我想要的每一种数组。
#3
3
Not sure why do you need w,h. If these values are actually required and mean that only specified number of rows and cols should be read than you can try the following:
不知道为什么你需要w,h。如果这些值实际上是必需的，并且意味着只需要读取指定的行数和cols数，那么您可以尝试以下步骤:
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)
#4
-2
is working with both python2(e.g. Python 2.7.10) and python3(e.g. Python 3.6.4)
和python2一起工作(例如:Python 2.7.10)和python3(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))
another way: is working with both python2(e.g. Python 2.7.10) and python3(e.g. Python 3.6.4), as well for complex matrices see the example below (only change int to complex)
另一种方法是使用python2(例如:Python 2.7.10)和python3(如。对于复杂的矩阵，也可以看到下面的例子(只对复数进行修改)
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)
I updated the code, this method is working for any number of matrices and any kind of matrices(int,complex,float) in the initial in.txt file.
我更新了代码，这个方法适用于任意数量的矩阵和任何类型的矩阵(int,complex,float)。txt文件。
This program yields matrix multiplication as an application. Is working with python2, in order to work with python3 make the following changes
这个程序将矩阵乘法作为一个应用程序。与python2一起工作，为了与python3合作，做出以下改变?
print to print()
and
和
print "%7g" %a[i,j], to print ("%7g" %a[i,j],end="")
the script:
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)
as input file I take in.txt:
作为输入文件，我接受。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
and complex_in.txt
和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
and the output look like:
输出是这样的
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
#1
65
Assuming you don't have extraneous whitespace:
假设你没有多余的空白:
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()])
You could condense the last for loop into a nested list comprehension:
您可以将最后一个循环压缩为嵌套列表理解:
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]
#2
12
To me this kind of seemingly simple problem is what Python is all about. Especially if you're coming from a language like C++, where simple text parsing can be a pain in the butt, you'll really appreciate the functionally unit-wise solution that python can give you. I'd keep it really simple with a couple of built-in functions and some generator expressions.
对我来说，这类看似简单的问题是Python的全部内容。特别是，如果您使用的是像c++这样的语言，在这里简单的文本解析可能会让您感到痛苦，您将非常感激python能够给您的功能上的单元解决方案。我将使用一些内置函数和一些生成器表达式来保持它的简单性。
You'll need open(name, mode), myfile.readlines(), mystring.split(), int(myval), and then you'll probably want to use a couple of generators to put them all together in a pythonic way.
您需要打开(名称、模式)、myfile.readlines()、mystring.split()、int(myval)，然后您可能需要使用几个生成器以python的方式将它们组合在一起。
# 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:]]
Look up generator expressions here. They can really simplify your code into discrete functional units! Imagine doing the same thing in 4 lines in C++... It would be a monster. Especially the list generators, when I was I C++ guy I always wished I had something like that, and I'd often end up building custom functions to construct each kind of array I wanted.
在这里查找生成器表达式。他们可以将你的代码简化成离散的功能单元!想象一下在c++中做同样的事情。那将是一个怪物。特别是列表生成器，当我是c++的时候，我总是希望我有这样的东西，我经常会构建自定义函数来构造我想要的每一种数组。
#3
3
Not sure why do you need w,h. If these values are actually required and mean that only specified number of rows and cols should be read than you can try the following:
不知道为什么你需要w,h。如果这些值实际上是必需的，并且意味着只需要读取指定的行数和cols数，那么您可以尝试以下步骤:
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)
#4
-2
is working with both python2(e.g. Python 2.7.10) and python3(e.g. Python 3.6.4)
和python2一起工作(例如:Python 2.7.10)和python3(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))
another way: is working with both python2(e.g. Python 2.7.10) and python3(e.g. Python 3.6.4), as well for complex matrices see the example below (only change int to complex)
另一种方法是使用python2(例如:Python 2.7.10)和python3(如。对于复杂的矩阵，也可以看到下面的例子(只对复数进行修改)
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)
I updated the code, this method is working for any number of matrices and any kind of matrices(int,complex,float) in the initial in.txt file.
我更新了代码，这个方法适用于任意数量的矩阵和任何类型的矩阵(int,complex,float)。txt文件。
This program yields matrix multiplication as an application. Is working with python2, in order to work with python3 make the following changes
这个程序将矩阵乘法作为一个应用程序。与python2一起工作，为了与python3合作，做出以下改变?
print to print()
and
和
print "%7g" %a[i,j], to print ("%7g" %a[i,j],end="")
the script:
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)
as input file I take in.txt:
作为输入文件，我接受。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
and complex_in.txt
和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
and the output look like:
输出是这样的
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