Question

我使用asammdf或mdfreader之类的MDF文件。但是我的数据文件也是   大。因此，我想读取特定数据并制作一个数据框。


使用asammdf中的asammdf导入MDF的MDF数据读取器
  mdfreader的情况下，存在很多错误，因为我的mdf文件是相同名称的数据，并且在重采样时遇到了一些麻烦（错误的数据输出）


filename = test_t16.dat”；我的MDF数据文件

yop = MDF（文件名）;使用asammdf的mdf阅读器

whl_rr = yop.get（'WHL_SPD_RR'）;我从mdf中选择一些数据   文件（yop）

whl_rr =

invalidation_bits = {NoneType}无

master_metadata = {tuple}（“ TimeChannel”，1）

name = {str}'WHL_SPD_RR'

raw = {bool}错误

samples = {ndarray} [0。 ... 0。]

source = {NoneType}无

stream_sync = {bool}错误

timestamps = {ndarray} [240.4053 ... 2050.81525]

unit = {str}'km / h'   >   我想要这样的数据框

from asammdf import MDF
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

filename = r"C:\Users\wonyo\PycharmProjects\test\test_t16.dat"
yop = MDF(filename)

signallist = [ "WHL_SPD_RR","WHL_SPD_FR", "WHL_SPD_RL","WHL_SPD_FL"]

df=[]
def group_len(yop, start, stop):             
    for i in range(start, stop):           
        if yop.get_group(i).empty != True:
            if i == start:
                max_len = len(yop.get_group(i).TimeChannel)
                min_time = min(yop.get_group(i).TimeChannel)

            else:
                max_len = min(max_len, len(yop.get_group(i).TimeChannel))
                min_time = max(min_time, min(yop.get_group(i).TimeChannel))

    return max_len-1000, max(242, min_time + 2) 

grlen_time = group_len(yop, 68, 140)
max_len = grlen_time[0]
min_time = grlen_time[1]
time = np.linspace(0, (max_len - 1) * 0.01, max_len)

for i in range(0,5):

    signal = yop.get(signallist[i])
    signal.timestamps = signal.timestamps - min_time
    signal = signal.interp(time)
    data_sg = signal.samples
    name_sg = signal.name
    inex_sg = signal.timestamps
    mydata = pd.DataFrame( data =data_sg , index=index_sg, columns=name_sg)
    print(df)

whl_spd_fl = signal()

我要像这样（数据框）

time    whl_spd_rr    whl_spd_rl   whl_spd_fl    whl_spd_fr
0         0              0            0             0
0.01      1              1            1             1
0.02      2              2            2             2
0.03      4              4            4             4
0.04      10             10           10            10
0.05      15             15           15            15
0.06      20             19           19            19
0.07      21             20           20            20
0.08      22             21           21            21
0.09      24             23           21            22
0.10      10             11           11            11
0.11      8              10           10            10

Answer 1

自API起至少有asammdf版本5.10.3：

已删除熊猫导出选项。您应该改用to_dataframe方法。

from asammdf import MDF

mdf_obj = MDF('file.mf4')
df = mdf_obj.to_dataframe()

Answer 2

yop = MDF(file_name, memory='minimum')

to_keep = ['Channl1', 'Channel2', ('CR_Bms_Soc_Pc', 102) ] # and so on
df = yop.filter(to_keep).cut(start=240, stop=2050).export('pandas', raster=0.01)

Answer 3

df= mdf.filter(signallist).export(fmt='pandas')

我想从MDF文件转换为Dataframe

3 个答案: