复制
收藏
提问
全网

为什么用函数提取文件时，更改了数据时间但提取的文件还是不变，比如def get_once_sampling_data(start_time: datetime, end_time: datetime, io_address: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() group = io_data.groupby('group') i = 0 # start_time = datetime(2024, 5, 5, 20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # get_once_sampling_data(start_time, end_time, io_address) def get_slice_sampling_data(start_time: datetime, end_time: datetime, io_address: int, cut_count: int, cut_index: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() io_data = io_data.groupby('group').filter(lambda x: len(x) == (cut_count + 1) * 2) for _, group in io_data.groupby('group'): if (group['cut'] != 0).sum() >= cut_count: cut_nonzero_indices = group[group['cut'] != 0].index third_cut_nonzero_index = cut_nonzero_indices[cut_index] next_row_index = group.index[group.index.get_loc(third_cut_nonzero_index) + 1] cur_start_time = group.loc[next_row_index - 1, "time"] cur_end_time = group.loc[next_row_index, "time"] source_data = get_np_sampling_data(sampling_path, comm_key, cur_start_time, cur_end_time, [1]) if source_data is None: continue cur_start_time = cur_start_time.astimezone(pytz.timezone('Asia/Shanghai')) file_name = cur_start_time.strftime("%Y%m%d_%H%M%S") cur_path = os.path.join(local_path, '01_slice_sampling_data', file_name + '.csv') os.makedirs(os.path.dirname(cur_path), exist_ok=True) source_data = pd.DataFrame(source_data) # Convert numpy array to pandas DataFrame source_data.to_csv(cur_path) # start_time = datetime(2024, 5, 5,20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # cut_count = 16 # cut_index = 2 # get_slice_sampling_data(start_time, end_time, io_address, cut_count, cut_index)

5月前
全网
文档
学术
百科
知识库
时间不限
自动

理解问题为什么用函数提取文件时，更改了数据时间但提取的文件还是不变，比如def get_once_sampling_data(start_time: datetime, end_time: datetime, io_address: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() group = io_data.groupby('group') i = 0 # start_time = datetime(2024, 5, 5, 20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # get_once_sampling_data(start_time, end_time, io_address) def get_slice_sampling_data(start_time: datetime, end_time: datetime, io_address: int, cut_count: int, cut_index: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() io_data = io_data.groupby('group').filter(lambda x: len(x) == (cut_count + 1) * 2) for _, group in io_data.groupby('group'): if (group['cut'] != 0).sum() >= cut_count: cut_nonzero_indices = group[group['cut'] != 0].index third_cut_nonzero_index = cut_nonzero_indices[cut_index] next_row_index = group.index[group.index.get_loc(third_cut_nonzero_index) + 1] cur_start_time = group.loc[next_row_index - 1, "time"] cur_end_time = group.loc[next_row_index, "time"] source_data = get_np_sampling_data(sampling_path, comm_key, cur_start_time, cur_end_time, [1]) if source_data is None: continue cur_start_time = cur_start_time.astimezone(pytz.timezone('Asia/Shanghai')) file_name = cur_start_time.strftime("%Y%m%d_%H%M%S") cur_path = os.path.join(local_path, '01_slice_sampling_data', file_name + '.csv') os.makedirs(os.path.dirname(cur_path), exist_ok=True) source_data = pd.DataFrame(source_data) # Convert numpy array to pandas DataFrame source_data.to_csv(cur_path) # start_time = datetime(2024, 5, 5,20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # cut_count = 16 # cut_index = 2 # get_slice_sampling_data(start_time, end_time, io_address, cut_count, cut_index)

已完成理解「为什么用函数提取文件时，更改了数据时间但提取的文件还是不变，比如def get_once_sampling_data(start_time: datetime, end_time: datetime, io_address: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() group = io_data.groupby('group') i = 0 # start_time = datetime(2024, 5, 5, 20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # get_once_sampling_data(start_time, end_time, io_address) def get_slice_sampling_data(start_time: datetime, end_time: datetime, io_address: int, cut_count: int, cut_index: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() io_data = io_data.groupby('group').filter(lambda x: len(x) == (cut_count + 1) * 2) for _, group in io_data.groupby('group'): if (group['cut'] != 0).sum() >= cut_count: cut_nonzero_indices = group[group['cut'] != 0].index third_cut_nonzero_index = cut_nonzero_indices[cut_index] next_row_index = group.index[group.index.get_loc(third_cut_nonzero_index) + 1] cur_start_time = group.loc[next_row_index - 1, "time"] cur_end_time = group.loc[next_row_index, "time"] source_data = get_np_sampling_data(sampling_path, comm_key, cur_start_time, cur_end_time, [1]) if source_data is None: continue cur_start_time = cur_start_time.astimezone(pytz.timezone('Asia/Shanghai')) file_name = cur_start_time.strftime("%Y%m%d_%H%M%S") cur_path = os.path.join(local_path, '01_slice_sampling_data', file_name + '.csv') os.makedirs(os.path.dirname(cur_path), exist_ok=True) source_data = pd.DataFrame(source_data) # Convert numpy array to pandas DataFrame source_data.to_csv(cur_path) # start_time = datetime(2024, 5, 5,20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # cut_count = 16 # cut_index = 2 # get_slice_sampling_data(start_time, end_time, io_address, cut_count, cut_index)」

展开阅读网页

在您提供的代码示例中，get_once_sampling_data 和 get_slice_sampling_data 函数用于处理和提取数据。您提到更改了数据时间，但提取的文件内容没有变化。这可能是由于几个原因造成的：

  1. 文件内容的实际修改：文件的修改时间（mtime）和属性修改时间（ctime）是两个不同的概念。mtime 表示文件内容最后一次被修改的时间，而 ctime 表示文件属性或权限最后一次被修改的时间。如果您更改的是文件属性而不是文件内容，那么 mtime 不会改变，因此文件内容也不会更新。57。

  2. 代码逻辑：在 get_once_sampling_data 和 get_slice_sampling_data 函数中，数据的提取和处理逻辑是基于时间范围和特定条件的。如果这些条件没有满足，即使文件的修改时间发生了变化，函数也可能不会提取新的数据。例如，在 get_slice_sampling_data 函数中，只有当 group['cut'] != 0 的数量大于或等于 cut_count 时，才会进行进一步的处理和数据提取7。

  3. 文件系统缓存：操作系统可能会缓存文件的元数据，包括修改时间。即使文件的实际内容已经改变，操作系统的缓存可能还没有更新，导致您看到的修改时间没有变化。这可能需要刷新缓存或重新启动系统来解决。

  4. 文件锁定或权限问题：如果文件被其他进程锁定或您没有足够的权限来修改文件，即使您尝试更改数据时间，文件的实际内容也可能不会更新。

  5. 代码中的逻辑错误：如果代码中存在逻辑错误，比如条件判断错误或循环逻辑错误，也可能导致即使文件内容已更改，提取的文件内容仍然不变。

为了解决这个问题，您需要检查以下几点：

  • 确保您更改的是文件内容，而不仅仅是属性。
  • 检查函数中的条件是否满足，以及是否有逻辑错误。
  • 确认文件没有被其他进程锁定，并且您有足够的权限来修改文件。
  • 如果需要，可以尝试刷新文件系统缓存或重启系统。

请注意，由于您提供的代码片段中没有具体的文件操作代码，以上分析基于代码逻辑和文件系统行为的一般知识。如果需要更具体的帮助，请提供更详细的代码和上下文信息。

更专业一些
转笔记
专业
为什么用函数提取文件时，更改了数据时间但提取的文件还是不变，比如def get_once_sampling_data(start_time: datetime, end_time: datetime, io_address: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() group = io_data.groupby('group') i = 0 # start_time = datetime(2024, 5, 5, 20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # get_once_sampling_data(start_time, end_time, io_address) def get_slice_sampling_data(start_time: datetime, end_time: datetime, io_address: int, cut_count: int, cut_index: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() io_data = io_data.groupby('group').filter(lambda x: len(x) == (cut_count + 1) * 2) for _, group in io_data.groupby('group'): if (group['cut'] != 0).sum() >= cut_count: cut_nonzero_indices = group[group['cut'] != 0].index third_cut_nonzero_index = cut_nonzero_indices[cut_index] next_row_index = group.index[group.index.get_loc(third_cut_nonzero_index) + 1] cur_start_time = group.loc[next_row_index - 1, "time"] cur_end_time = group.loc[next_row_index, "time"] source_data = get_np_sampling_data(sampling_path, comm_key, cur_start_time, cur_end_time, [1]) if source_data is None: continue cur_start_time = cur_start_time.astimezone(pytz.timezone('Asia/Shanghai')) file_name = cur_start_time.strftime("%Y%m%d_%H%M%S") cur_path = os.path.join(local_path, '01_slice_sampling_data', file_name + '.csv') os.makedirs(os.path.dirname(cur_path), exist_ok=True) source_data = pd.DataFrame(source_data) # Convert numpy array to pandas DataFrame source_data.to_csv(cur_path) # start_time = datetime(2024, 5, 5,20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # cut_count = 16 # cut_index = 2 # get_slice_sampling_data(start_time, end_time, io_address, cut_count, cut_index)
不在提醒

更专业内容正在努力生成中
知识树
为什么用函数提取文件时，更改了数据时间但提取的文件还是不变，比如def get_once_sampling_data(start_time: datetime, end_time: datetime, io_address: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() group = io_data.groupby('group') i = 0 # start_time = datetime(2024, 5, 5, 20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # get_once_sampling_data(start_time, end_time, io_address) def get_slice_sampling_data(start_time: datetime, end_time: datetime, io_address: int, cut_count: int, cut_index: int): io_data = get_io_data(io_bin_path, start_time, end_time, io_address) io_data["nor"] = io_data["data"] & 0b01 io_data["cut"] = io_data["data"] & 0b10 io_data['group'] = (io_data['nor'] == 0).cumsum() io_data = io_data.groupby('group').filter(lambda x: len(x) == (cut_count + 1) * 2) for _, group in io_data.groupby('group'): if (group['cut'] != 0).sum() >= cut_count: cut_nonzero_indices = group[group['cut'] != 0].index third_cut_nonzero_index = cut_nonzero_indices[cut_index] next_row_index = group.index[group.index.get_loc(third_cut_nonzero_index) + 1] cur_start_time = group.loc[next_row_index - 1, "time"] cur_end_time = group.loc[next_row_index, "time"] source_data = get_np_sampling_data(sampling_path, comm_key, cur_start_time, cur_end_time, [1]) if source_data is None: continue cur_start_time = cur_start_time.astimezone(pytz.timezone('Asia/Shanghai')) file_name = cur_start_time.strftime("%Y%m%d_%H%M%S") cur_path = os.path.join(local_path, '01_slice_sampling_data', file_name + '.csv') os.makedirs(os.path.dirname(cur_path), exist_ok=True) source_data = pd.DataFrame(source_data) # Convert numpy array to pandas DataFrame source_data.to_csv(cur_path) # start_time = datetime(2024, 5, 5,20,0,tzinfo=pytz.timezone('Asia/Shanghai')) # end_time = datetime(2024, 5, 6,12,0,tzinfo=pytz.timezone('Asia/Shanghai')) # io_address = 5 # cut_count = 16 # cut_index = 2 # get_slice_sampling_data(start_time, end_time, io_address, cut_count, cut_index)
如何确保函数提取文件时数据时间更新？
文件提取函数中数据时间未更新的原因
如何检查文件提取函数的时间参数？
在线客服