numpy读取txt错误（loadtxt，genfromtxt）

Question

我想在python中阅读下面的文本文件

文本文件的示例

{#  "Column 4-5 Quantity": "Re/Im Pressure"
#   "Column 4-5 Units": ""
#   "Number Rows": 3584879
#}
4.0740740741e-002   -5.0370370370e-002  7.3333333333e-002   9.4443035889e+002   -6.0709484863e+002  
4.1481481481e-002   -5.0370370370e-002  7.3333333333e-002   9.0292657471e+002   -6.2604998779e+002  
4.2222222222e-002   -5.0370370370e-002  7.3333333333e-002   8.2029248047e+002   -6.4528021240e+002  
4.2962962963e-002   -5.0370370370e-002  7.3333333333e-002   7.1829382324e+002   -6.5028546143e+002  
4.3703703704e-002   -5.0370370370e-002  7.3333333333e-002   1.#QNAN00000e+000   0.0000000000e+000   
4.4444444444e-002   -5.0370370370e-002  7.3333333333e-002   1.#QNAN00000e+000   0.0000000000e+000   
4.5185185185e-002   -5.0370370370e-002  7.3333333333e-002   1.#QNAN00000e+000   0.0000000000e+000   
4.5925925926e-002   -5.0370370370e-002  7.3333333333e-002   1.#QNAN00000e+000   0.0000000000e+000
-3.2592592593e-002  -4.9629629630e-002  7.3333333333e-002   4.9716027832e+002   -1.2688856201e+003  
-3.1851851852e-002  -4.9629629630e-002  7.3333333333e-002   5.3677227783e+002   -1.4196939697e+003  
-3.1111111111e-002  -4.9629629630e-002  7.3333333333e-002   6.1588317871e+002   -1.5679577637e+003  
-3.0370370370e-002  -4.9629629630e-002  7.3333333333e-002   7.2673925781e+002   -1.7039268799e+003  
-2.9629629630e-002  -4.9629629630e-002  7.3333333333e-002   8.5946520996e+002   -1.7935989990e+003  
-2.8888888889e-002  -4.9629629630e-002  7.3333333333e-002   1.0030370483e+003   -1.7982950439e+003

因此我使用了numpy的函数loadtxt和genfromtxt

首先我尝试了loadtxt代码

impoty numpy as np

readtxt = np.loadtxt("filename.txt")

我收到如下错误信息

Wrong number of columns at line 5

其次我试过genfromtxt代码是

impoty numpy as np

readtxt = np.genfromtxt("filename.txt")

我收到如下错误信息

Line #5 (got 5 columns instead of 4)

那么，我怎么能弄清楚这个问题呢？我认为问题是“1.＃QNAN00000e + 000”

我想将此值更改为“0”

Answer 1

你可以使用comments和missing_values kwds。 comments我们需要将其设置为默认的#以外的其他内容，以便解析器不会在行中间停止读取。 missing values我们设置为'1.#QNAN0000e+000'，所以他们优雅地处理。这些设置为nan，但nans你可以很容易地用零替换（result[np.isnan(result)] = 0）：

>>> np.genfromtxt(<your_file>, comments='%', missing_values='1.#QNAN0000e+000')
array([[ 4.07407407e-02, -5.03703704e-02,  7.33333333e-02,
         9.44430359e+02, -6.07094849e+02],
       [ 4.14814815e-02, -5.03703704e-02,  7.33333333e-02,
         9.02926575e+02, -6.26049988e+02],
       [ 4.22222222e-02, -5.03703704e-02,  7.33333333e-02,
         8.20292480e+02, -6.45280212e+02],
       [ 4.29629630e-02, -5.03703704e-02,  7.33333333e-02,
         7.18293823e+02, -6.50285461e+02],
       [ 4.37037037e-02, -5.03703704e-02,  7.33333333e-02,
                    nan,  0.00000000e+00],
       [ 4.44444444e-02, -5.03703704e-02,  7.33333333e-02,
                    nan,  0.00000000e+00],
       [ 4.51851852e-02, -5.03703704e-02,  7.33333333e-02,
                    nan,  0.00000000e+00],
       [ 4.59259259e-02, -5.03703704e-02,  7.33333333e-02,
                    nan,  0.00000000e+00],
       [-3.25925926e-02, -4.96296296e-02,  7.33333333e-02,
         4.97160278e+02, -1.26888562e+03],
       [-3.18518519e-02, -4.96296296e-02,  7.33333333e-02,
         5.36772278e+02, -1.41969397e+03],
       [-3.11111111e-02, -4.96296296e-02,  7.33333333e-02,
         6.15883179e+02, -1.56795776e+03],
       [-3.03703704e-02, -4.96296296e-02,  7.33333333e-02,
         7.26739258e+02, -1.70392688e+03],
       [-2.96296296e-02, -4.96296296e-02,  7.33333333e-02,
         8.59465210e+02, -1.79359900e+03],
       [-2.88888889e-02, -4.96296296e-02,  7.33333333e-02,
         1.00303705e+03, -1.79829504e+03]])