clear all; close all; Varo_InputParameters_C4000; strAx = 'AF'; %AF OISX OISY OR OISXY, depending on driving pattern flagDebug = 1; ItemToTest = 'oistilttest'; % 'oistilttest' for Libra [filename, pathname] = uigetfile('.CSV;.csv' ,'Please select the logs', 'MultiSelect', 'on'); if iscell(filename) CsvFileNames = filename; else CsvFileNames{1} = filename; end numfiles = length(CsvFileNames); output = []; for i = 1:numfiles fname = fullfile(pathname, CsvFileNames{i}); LogData = readtable(fname); SN='sampleVr24code'; outputstruct = BB_process_cl_tilt(LogData, strAx, flagDebug, inputParameters, ItemToTest); outputValues = struct2cell(outputstruct); output = [output; [SN outputValues']]; close all; end outputTrends = fieldnames(outputstruct); output_summary = [[ 'SN' outputTrends']; output]; %output_summary = output_summary'; output_table = cell2table(output_summary(2:end,:),'VariableNames',output_summary(1,:)); % Write the table to a CSV file writetable(output_table,[ datestr(now, 'ddmmyy_HH_MM_') ItemToTest '_' strAx 'results.csv']);将上述代码转换为Python

以下是将Matlab代码转换为Python的尝试，但需要注意的是，由于涉及到许多自定义函数和变量，因此可能需要对代码进行适当的修改和调整才能在Python中正常运行。

import os
import pandas as pd
from Varo_InputParameters_C4000 import *
from BB_process_cl_tilt import *

strAx = 'AF' # AF OISX OISY OR OISXY, depending on driving pattern
flagDebug = 1
ItemToTest = 'oistilttest' # 'oistilttest' for Libra

filename = input("Please enter the name of the log file: ")
pathname = os.path.dirname(os.path.abspath(__file__))

if filename.endswith('.csv') or filename.endswith('.CSV'):
    CsvFileNames = [filename]
else:
    CsvFileNames = []

numfiles = len(CsvFileNames)
output = []

for i in range(numfiles):
    fname = os.path.join(pathname, CsvFileNames[i])
    LogData = pd.read_csv(fname)
    SN='sampleVr24code'
    outputstruct = BB_process_cl_tilt(LogData, strAx, flagDebug, inputParameters, ItemToTest)
    outputValues = list(outputstruct.values())
    output = output + [[SN] + outputValues]
    
outputTrends = list(outputstruct.keys())
output_summary = [['SN'] + outputTrends] + output
output_table = pd.DataFrame(output_summary[1:], columns=output_summary[0])
output_filename = os.path.join(pathname, '{}_{}_results.csv'.format(ItemToTest, strAx))
output_table.to_csv(output_filename, index=False)

需要注意的是，这里只是一个简单的转换尝试，可能需要进行更多的修改和调整才能在您的具体环境中正常运行。