txt2xls 0.2.2

安装

使用pip方式：

$ pip install txt2xls

快速使用

假设有几个原始文本数据文件，如：

# Sample1.txt
0 10
1 20
2 30
3 40
4 50
5 60
# Sample2.txt
0 15
1 25
2 35
3 45
4 55
5 65
# Sample3.txt
0 12
1 22
2 32
3 42
4 52
5 62

然后用

% txt2xls -o output Sample*.txt

它将生成output.xls文件。 excel文件有Sample1、Sample2和Sample3张工作表。

用法

usage: txt2xls [-h] [-v] [-p PARSER] [-l LOADER] [-u USING] [--unite]
            [--unite-basecolumn UNITE_BASECOLUMN]
            [--unite-function UNITE_FUNCTION] [--classify]
            [--classify-function CLASSIFY_FUNCTION] [--relative]
            [--relative-origin RELATIVE_ORIGIN]
            [--relative-basecolumn RELATIVE_BASECOLUMN] [--baseline]
            [--baseline-basecolumn BASELINE_BASECOLUMN]
            [--baseline-function BASELINE_FUNCTION]
            [--peakset-method {argmax,argmin}]
            [--peakset-basecolumn PEAKSET_BASECOLUMN]
            [--peakset-where-function PEAKSET_WHERE_FUNCTION]
            [--raise-exception] [-o OUTFILE]
            infiles [infiles ...]

positional arguments:
infiles               Path list of data files or directories which have data
                        files.

optional arguments:
-h, --help            show this help message and exit
-v, --version         show program's version number and exit
--raise-exception     If it is specified, raise exceptions.
-o OUTFILE, --outfile OUTFILE
                        An output filename without extensions. The required
                        filename extension will be automatically determined
                        from an output format.

Reading options:
-p PARSER, --parser PARSER
                        A maidenhair parser name which will be used to parse
                        the raw text data.
-l LOADER, --loader LOADER
                        A maidenhair loader name which will be used to load
                        the raw text data.
-u USING, --using USING
                        A colon (:) separated column indexes. It is used for
                        limiting the reading columns.

Unite options:
--unite               Join the columns of classified dataset with respecting
                        --unite-basecolumn.The dataset is classified with
                        --unite-function.
--unite-basecolumn UNITE_BASECOLUMN
                        An index of columns which will be used as a base
                        column for regulating data point region.
--unite-function UNITE_FUNCTION
                        A python script file path or a content of python
                        lambda expression which will be used for classifing
                        dataset. If it is not spcified, a filename character
                        before period (.) will be used to classify.

Classify options:
--classify            Classify dataset with --classify-function. It will
                        influence the results of --relative and --baseline.
--classify-function CLASSIFY_FUNCTION
                        A python script file path or a content of python
                        lambda expression which will be used for classifing
                        dataset. If it is not specified, a filename character
                        before the last underscore (_) will be used to
                        classify.

Relative options:
--relative            If it is True, the raw data will be converted to
                        relative data from the specified origin, based on the
                        specified column. See `--relative-origin` and
                        `--relative-basecolumn` also.
--relative-origin RELATIVE_ORIGIN
                        A dataset number which will be used as an orign of the
                        relative data. It is used with `--relative` option.
--relative-basecolumn RELATIVE_BASECOLUMN
                        A column number which will be used as a base column to
                        make the data relative. It is used with `--relative`
                        option.

Baseline options:
--baseline            If it is specified, the specified data file is used as
                        a baseline of the dataset. See `--baseline-basecolumn`
                        and `--baseline-function` also.
--baseline-basecolumn BASELINE_BASECOLUMN
                        A column index which will be proceeded for baseline
                        regulation. It is used with `--baseline` option.
--baseline-function BASELINE_FUNCTION
                        A python script file path or a content of python
                        lambda expression which will be used to determine the
                        baseline value from the data. `columns` and `column`
                        variables are available in the lambda expression.

Peakset options:
--peakset-method {argmax,argmin}
                        A method to find peak data point.
--peakset-basecolumn PEAKSET_BASECOLUMN
                        A column index which will be used for finding peak
                        data point.
--peakset-where-function PEAKSET_WHERE_FUNCTION
                        A python script file path or a content of python
                        lambda expression which will be used to limit the
                        range of data points for finding. peak data point.
                        `data` is available in the lambda expression.

首选项

您可以将配置文件创建为~/.config/txt2xls/txt2xls.cfg（Linux）。 ~/.txt2xls.cfg（Mac）或%APPDATA%\txt2xls\txt2xls.cfg（Windows）。

默认首选项等于配置文件，如下所示：

[default]
raise_exception = False

[reader]
parser = 'parsers.PlainParser'
loader = 'loaders.PlainLoader'
using = None

    [[classify]]
    enabled = False
    function = 'builtin:classify_function'

    [[unite]]
    enabled = False
    function = 'builtin:unite_function'
    basecolumn = 0

    [[relative]]
    enabled = False
    origin = 0
    basecolumn = 1

    [[baseline]]
    enabled = False
    function = 'builtin:baseline_function'
    basecolumn = 1

[writer]
default_filename = 'output.xls'

    [[peakset]]
    method = 'argmax'
    basecolumn = -1
    where_function = 'builtin:where_function'

我不使用Microsoft Windows，因此配置文件在Windows中的位置 可能是错的。 如果有什么错误请告诉我。