Question

我有一些.csv文件，其数据长度不同。我需要加载一些已定义的色谱柱，对它们进行排序并重新采样为相同的长度（100％）。

我已经编写了som定义的嵌套循环来对数据进行排序，但最终重采样功能无法正常工作。

subjects   = ['S01_']
conditions = ['Shoe1_', 'Shoe2_']
trials     = ['Run_1', 'Run_2','Run_3']

results_GRF_AP = np.empty(shape=(100,6))*np.NaN
results_GRF_ML = np.empty(shape=(100,6))*np.NaN
results_GRF_VERT = np.empty(shape=(100,6))*np.NaN

results_AnkPower = np.empty(shape=(100,6))*np.NaN


ind = 0
for s, subject in enumerate(subjects):
    for c, condition in enumerate(conditions):
        for t, trial in enumerate(trials):
            ind += 1
            filename = path + subject + condition + trial + extension
            try:
                data2 = pd.read_csv(filename,delimiter = ';')
                data2=np.array(data2)



            except Exception as err:
                print(filename, err)          
                continue
            else:
                print(filename, 'loaded')
                pass


            threshold = 30 ## defined threshold value in Newton from vertical GRF
            signal = np.array(data2[:,4])
            indices_bigger_than_threshold = np.where(signal > threshold)[0] # get item
            non_consecutive = np.where(np.diff(indices_bigger_than_threshold) != 1)[0]+1 # +1 for selecting the next
            first_bigger_than_threshold1 = np.zeros_like(signal, dtype=np.bool)
            first_bigger_than_threshold1[indices_bigger_than_threshold[0]] = True # retain the first
            first_bigger_than_threshold1[indices_bigger_than_threshold[non_consecutive]] = True
            indices_bigger_than_threshold = np.array(indices_bigger_than_threshold)

            GRF_AP = (data2[indices_bigger_than_threshold,2])
            GRF_ML = (data2[indices_bigger_than_threshold,3])
            GRF_VERT= (data2[indices_bigger_than_threshold,4])
            Ank_Power = (data2[indices_bigger_than_threshold,28])



            GRF_AP_Norm = signal.resample(GRF_AP,100)
            GRF_ML_Norm = signal.resample(GRF_ML,100)
            GRF_VERT_Norm= signal.resample(GRF_VERT,100)
            Ank_Power_Norm = signal.resample(Ank_Power,100)


            # talking one coloum from the loaded .csv file to store in the results parameter.  
            results_GRF_AP[:,ind-1] = GRF_AP_Norm
            results_GRF_ML[:,ind-1] = GRF_ML_Norm
            results_GRF_VERT[:,ind-1] = GRF_VERT_Norm

            results_AnkPower[:,ind-1] = Ank_Power_Norm

所有零件都单独工作，但是在循环中我遇到一个错误 AttributeError：'numpy.ndarry'对象没有属性'resample'

如果我从scipy导入信号运行，然后对加载的主题，条件和试用版使用重新采样，则该效果正常。

Answer 1

我认为您的问题在于，您正在使用调用signal的变量覆盖scipy中的signal函数：

signal = np.array(data2[:,4])

如果重命名变量，则应将其修复。

我需要使用信号重采样对np数组进行重采样

1 个答案: