假设我从一些计算得到一个numpy矩阵。这是我的numpy矩阵'result1'::
result1=
[[ 1. 0. 0. 0.00375 -0.01072 -0. -1000. ]
[ 2. 3. 4. 0. -0.004 750. 0. ]
[ 3. 3. 0. 0. 0. -750. 1000. ]]
现在我想在名为'result.txt'的文本文件中写这个矩阵。为此,我编写了以下代码::
np.savetxt('result.txt', result1, fmt='%.2e')
但是它在一行中给了我矩阵的所有元素。
1.00e+00 0.00e+00 0.00e+00 3.75e-03 -1.07e-02 -1.14e-13 -1.00e+032.00e+00 3.00e+00 4.00e+00 0.00e+00 -4.00e-03 7.50e+02 0.00e+003.00e+00 3.00e+00 0.00e+00 0.00e+00 0.00e+00 -7.50e+02 1.00e+03
我想以正确的矩阵格式在文本文件中编写矩阵。我怎样才能做到这一点?我使用了关键字newline ='\ n'或newline ='',但结果是一样的。
提前致谢...
=======
此编辑部分适用于@Warren
试试这个:
>>> import numpy as np
>>> mat=np.matrix([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
>>> mat
matrix([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>> np.savetxt('text.txt',mat,fmt='%.2f')
在我的text.txt文件中,我得到了:
1.00 2.00 3.004.00 5.00 6.007.00 8.00 9.00
答案 0 :(得分:3)
a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
mat = np.matrix(a)
with open('outfile.txt','wb') as f:
for line in mat:
np.savetxt(f, line, fmt='%.2f')
答案 1 :(得分:1)
要重新创建形状,您需要在保存文件时保存形状。
尝试:
import numpy as np
import re
result=np.array([[1.,0.,0.,0.00375,-0.01072,-0.,-1000.,],
[2.,3.,4.,0.,-0.004,750.,0.],
[3.,3.,0.,0.,0.,-750.,1000.]])
with open('/tmp/test', 'w') as fout:
fout.write(u'#'+'\t'.join(str(e) for e in result.shape)+'\n')
result.tofile(fout)
with open('/tmp/test', 'rb') as f:
line=f.readline().decode('ascii')
if line.startswith('#'):
shape=tuple(map(int, re.findall(r'(\d+)', line)))
else:
raise IOError('Failed to find shape in file')
result2=np.fromfile(f)
result3=result2.reshape(shape)
print(np.array_equal(result, result2))
# False
print(np.array_equal(result, result3))
# True
您可以在oder文件中以某种形式保存形状,以重新创建相同的形状。请确保您不会忘记文件开头的数据,因为与np.loadtxt不同,以#
开头的行仍被视为数据。
答案 2 :(得分:1)
如果您只想使用numpy
:
import numpy as np
mat = np.matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
with open('outfile.txt') as f:
for line in mat:
np.savetxt(f, line, fmt='%.2f')
然后
cat outfile.txt
1.00 2.00 3.00
4.00 5.00 6.00
7.00 8.00 9.00
Pandas有to_csv
方法:
import numpy as np
import pandas as pd
mat = np.matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
dataframe = pd.DataFrame(data=mat.astype(float))
df.to_csv('outfile.csv', sep=' ', header=False, float_format='%.2f', index=False)
它具有相同的输出:
cat outfile.csv
1.00 2.00 3.00
4.00 5.00 6.00
7.00 8.00 9.00