首先导入scipy的包 from scipy.io import loadmat
然后读取 m = loadmat("F:/__identity/activity/论文/data/D001.mat")
注意这里m是一个dict数据结构
>>> m {‘__header__‘: b‘MATLAB 5.0 MAT-file, Platform: PCWIN, Created on: Mon Aug 15 22:16:43 2011‘, ‘__globals__‘: [], ‘labels‘: array([[1], [3], [4], ..., [4], [3], [4]], dtype=uint8), ‘data‘: array([[ 1. , 0.35 , 0.265 , ..., 0.0995, 0.0485, 0.07 ], [ 2. , 0.53 , 0.42 , ..., 0.2565, 0.1415, 0.21 ], [ 1. , 0.44 , 0.365 , ..., 0.2155, 0.114 , 0.155 ], ..., [ 1. , 0.59 , 0.44 , ..., 0.439 , 0.2145, 0.2605], [ 1. , 0.6 , 0.475 , ..., 0.5255, 0.2875, 0.308 ], [ 2. , 0.625 , 0.485 , ..., 0.531 , 0.261 , 0.296 ]]), ‘__version__‘: ‘1.0‘}
>>> m.keys() dict_keys([‘__header__‘, ‘__globals__‘, ‘labels‘, ‘data‘, ‘__version__‘])
>>> m["labels"] array([[1], [3], [4], ..., [4], [3], [4]], dtype=uint8)
>>> m["data"] array([[ 1. , 0.35 , 0.265 , ..., 0.0995, 0.0485, 0.07 ], [ 2. , 0.53 , 0.42 , ..., 0.2565, 0.1415, 0.21 ], [ 1. , 0.44 , 0.365 , ..., 0.2155, 0.114 , 0.155 ], ..., [ 1. , 0.59 , 0.44 , ..., 0.439 , 0.2145, 0.2605], [ 1. , 0.6 , 0.475 , ..., 0.5255, 0.2875, 0.308 ], [ 2. , 0.625 , 0.485 , ..., 0.531 , 0.261 , 0.296 ]])
有点不太懂这个“uint8”
>>> m["labels"][0] array([1], dtype=uint8) >>> m["labels"][0][0] 1 >>> m["labels"][0][0] + 1 2 >>> m["labels"][0].as_type("int") Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: ‘numpy.ndarray‘ object has no attribute ‘as_type‘ # 注意时astype不是as_type >>> m["labels"][0].dtype dtype(‘uint8‘) >>> m["labels"][0].astype("int") array([1])
这个数据类型真是醉了：
>>> type(m["labels"][0][0] + 1)
<class ‘numpy.int32‘>
如果要把它变成dataframe，导入pandas后
>>> df = pd.DataFrame(m["data"]) >>> df.head() 0 1 2 3 4 5 6 7 0 1.0 0.350 0.265 0.090 0.2255 0.0995 0.0485 0.070 1 2.0 0.530 0.420 0.135 0.6770 0.2565 0.1415 0.210 2 1.0 0.440 0.365 0.125 0.5160 0.2155 0.1140 0.155 3 3.0 0.330 0.255 0.080 0.2050 0.0895 0.0395 0.055 4 3.0 0.425 0.300 0.095 0.3515 0.1410 0.0775 0.120
