Metadata-Version: 1.0
Name: toolman
Version: 0.1.10b0
Summary: Python utility tools for research
Home-page: https://github.com/bohaohuang/toolman
Author: bohaohuang
Author-email: hbhzhuce@gmail.com
License: MIT
Description: *****************************************
        ToolMan: Python utility functions for R&D
        *****************************************
        
        .. image:: https://img.shields.io/pypi/v/toolman.svg
           :target: https://pypi.python.org/pypi/toolman/
        
        .. image:: https://travis-ci.com/bohaohuang/toolman.svg?branch=master
          :target: https://travis-ci.com/bohaohuang/toolman
        
        .. image:: https://codecov.io/gh/bohaohuang/toolman/branch/master/graph/badge.svg
          :target: https://codecov.io/gh/bohaohuang/toolman
        
        See the source for this project on our `GitHub page <https://github.com/bohaohuang/toolman>`_
        
        Install
        #######
        .. code-block:: bash
        
            pip install toolman
        
        Modules
        #######
        `mist_utils.py <./toolman/misc_utils.py>`_
        *******************************************
        miscellaneous utility functions including data I/O and processing
        
        a) Read/write different formats of files in one function:
        
        .. code-block:: python
        
            import toolman as tm
            data = tm.misc_utils.load_file(file_name)
            tm.misc_utils.save_file(file_name, data)
        
        Currently support extensions including: `.npy`, `.pkl`, `.txt`, `.csv`, `.json` and commonly used image formats.
        
        b) Argument parser, parse nested argument list:
        
        .. code-block:: python
        
            import sys
            import argparse
            import toolman as tm
            parser = argparse.ArgumentParser()
            args, extras = parser.parse_known_args(sys.argv[1:])
            cfg_dict = tm.misc_utils.parse_args(extras)
        
        `vis_utils.py <./toolman/vis_utils.py>`_
        *******************************************
        Matplotlib utility functions for visualization
        
        a) Display images in side by side with axis linked
        
        .. code-block:: python
        
            import toolman as tm
            fig1 = tm.misc_utils.load_file(img_name_1)
            fig2 = tm.misc_utils.load_file(img_name_1)
            tm.vis_utils.compare_figures([fig1, fig2], (1, 2), fig_size=(12, 5))
        
        b) Display barplots
        
        .. code-block:: python
        
            import toolman as tm
            data = np.random.random((3, 4))
            labels = ['group 1', 'group 2', 'group 3']
            xticks = ['cluster 1', 'cluster 2', 'cluster 3', 'cluster 4']
            tm.vis_utils.compare_bars(data, labels, xticks)
        
        
        `img_utils <./toolman/img_utils.py>`_
        *******************************************
        image specific utility functions
        
        `pytorch_utils <./toolman/pytorch_utils.py>`_
        **************************************************
        pytorch specific utility functions
        
        `process_block <./toolman/process_block.py>`_
        *************************************************
        A processing unit that do certain operations only if it has never done before. This is helpful avoid duplicate
        executing time consuming jobs.
        
        .. code-block:: python
        
            import toolman as tm
            def foo(cnt_len):
                cnt = 0
                for i in range(cnt_len):
                    cnt += 1
                return cnt
        
            pb = tm.process_block.ProcessBlock(foo, file_dir)
            pb.run(force_run=False, cnt_len=100)
        
Platform: UNKNOWN
