Question

我正在尝试排列大小（1425 x 15）的特征矩阵，其中每一列代表每个传感器的固有频率，每一行代表一个数据文件。但是，我继续在每一列中获得相同的值，并且下一个值打印到下一行。我将如何重新排列特征矩阵？

我试图形成一个可以在下面找到的代码，但是，我不知道代码中的错误。我形成了不同的代码，但结果仍然相同。请在下面找到形成的代码：

代码1：

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代码2：

# Matrix array:
DataSizerow=0
DataSizecolumn=0
Data = np.zeros((1425,15))

# Forming a feature matrix from frequency, PSD and AutoCorrelation values:
        # Dataset.shape[1] represesnt the acceleration dataset column
        # List_Of_DataFrame_Feature = []
        # List_Of_DataFrame_Label = []
        Length_PSD_mean = len(x_axis_list_psd_filtered)
        print('Length of PSD values: ', Length_PSD_mean)
        if Length_PSD_mean > 1:
            for PSD_Mean in range(Length_PSD_mean):
                X_axis_values_psd_mean = mean(x_axis_list_psd_filtered)
        else:
            X_axis_values_psd_mean = x_axis_list_psd_filtered
        DataFrame_Feature = np.array(X_axis_values_psd_mean)
        DataFrame_Feature1 = np.array(x_axis_list_filtered)
        DataSizecolumn = DataSizecolumn + 1
        print('Data Size column: ',DataSizecolumn)
        Data[DataSizecolumn - 1] = DataFrame_Feature
        if DataSizecolumn in range(1, dataset.shape[1]):
            DataSizerow = DataSizerow + 1
            print('Data Size row: ', DataSizerow)
            Data[DataSizerow - 1] = DataFrame_Feature
        print('Sensor {0}'.format(k))
        print('Data Frame: ', Data)

代码3：

        # Dataset.shape[0] represesnt the acceleration dataset row
        # Dataset.shape[1] represesnt the acceleration dataset column
        DataSizecolumn1 = 0
        DataSizerow1 = 0
        DataFrame1 = np.zeros((1426, 16))
        for DataSizecolumn1 in range(1, dataset.shape[1]):
            print('Data Size column: ', DataSizecolumn1)
            for DataSizerow1 in range(1, dataset.shape[0]):
                print('Data Size row: ', DataSizerow1)
                DataFrame1[DataSizerow1][DataSizecolumn1] = DataFrame_Feature
        print('Sensor {0}'.format(k))
        print('DataFrame: ', DataFrame1)

预期结果应类似于单行下面的矩阵：

        # Dataset.shape[0] represesnt the acceleration dataset row
        # Dataset.shape[1] represesnt the acceleration dataset column
        DataSizecolumn2 = 0
        DataSizerow2 = 0
        DataFrame2 = np.zeros((1426, 16))
        for DataSizecolumn2 in range(1, dataset.shape[1]):
            print('Data Size column: ', DataSizecolumn2)
            DataFrame2[DataSizecolumn2] = DataFrame_Feature
            if DataSizecolumn2 == dataset.shape[1]:
                DataSizerow2 = DataSizerow2 + 1
                print('Data Size row: ', DataSizerow2)
                DataFrame2[DataSizerow2] = DataFrame_Feature
                if DataSizerow2 == dataset.shape[0]:
                    break
        print('Sensor {0}'.format(k))
        print('DataFrame: ', DataFrame2)

但是实际结果如下：

          Sensor 1 | Sensor 2 | Sensor 3 | Sensor 4 | Sensor 5 | Sensor 6 | 
Data file     13   |   51.5   |    13    |   13     |    13    |    13    |
          Sensor 7 | Sensor 8 | Sensor 9 | Sensor 10 | Sensor 11 | Sensor 12 | 
Data file     8.5  |    14    |    20    |   18.6    |   9.5     |   39    |
          Sensor 13 | Sensor 14 | Sensor 15 | 
Data file     8.5   |    8.5    |    8.5    |

Actual Feature matirx text file

请在下面找到整个代码：

          Sensor 1 | Sensor 2 | Sensor 3 | Sensor 4 | Sensor 5 | Sensor 6 | 
Data file     13   |   13     |    13    |   13     |    13    |    13    |
          Sensor 7 | Sensor 8 | Sensor 9 | Sensor 10 | Sensor 11 | Sensor 12 | 
Data file     13   |    13    |    13    |    13     |    13     |    13     |
          Sensor 13 | Sensor 14 | Sensor 15 | 
Data file     13    |    13     |    13     |

数据集来自网站链接。链接：http://users.metropolia.fi/~kullj/JrkwXyZGkhF/wooden_bridge_time_histories/

谢谢您的帮助。

如何排列特征矩阵？

0 个答案: