Metadata-Version: 2.1
Name: mngs
Version: 0.0.29
Summary: For lazy python users (monogusa people in Japanse), especially in ML/DSP fields
Home-page: https://github.com/ywatanabe1989/mngs
Author: ywatanabe1989
Author-email: ywata1989@gmail.com
License: GPL3.0
Description: ## Requirements
        ```
        chardet
        GitPython
        h5py
        joblib
        matplotlib
        natsort
        numpy
        pandas
        pymatreader
        PyYAML
        scipy
        seaborn
        sklearn
        statsmodels
        torch
        xmltodict
        ```
        
        ## Installation
        ``` bash
        $ pip install -y mngs
        ```
        
        
        ## mngs.general.save
        ``` python
        import mngs
        import numpy as np
        import matplotlib.pyplot as plt
        import pandas as pd
        
        ## numpy
        arr = np.arange(10)
        mngs.general.save(arr, 'spath.npy')
        
        ## pandas
        df = pd.DataFrame(arr)
        mngs.general.save(df, 'spath.csv')
        
        ## matplotlib
        fig, ax = plt.subplots()
        ax.plot(arr)
        mngs.general.save(fig, 'spath.png)
        ```
        
        ## mngs.general.load
        ``` python
        import mngs
        arr = mngs.general.load('spath.npy')
        arr = mngs.general.load('spath.mat')
        df = mngs.general.load('spath.npy')
        yaml_dict = mngs.general.load('spath.yaml')
        hdf5_dict = mngs.general.load('spath.hdf5')
        ```
        
        ## mngs.general.fix_seeds
        
        ``` python
        import mngs
        import os
        import random
        import numpy as np
        import torch
        
        mngs.general.fix_seeds(os=os, random=random, np=np, torch=torch, tf=None, seed=42)
        ```
        
        ## mngs.general.tee
        ``` python
        import sys
        sys.stdout, sys.stderr = tee(sys)
        print("abc")  # also wrriten in stdout
        print(1 / 0)  # also wrriten in stderr
        ```
        
        ## mngs.plt.configure_mpl
        ``` python
        configure_mpl(
            plt,
            dpi=100,
            figsize=(16.2, 10),
            figscale=1.0,
            fontsize=16,
            labelsize="same",
            legendfontsize="xx-small",
            tick_size="auto",
            tick_width="auto",
            hide_spines=False,
        )
        ```
        
        ## mngs.plt.ax_*
        - mngs.plt.ax_extend
        - mngs.plt.ax_scientific_notation
        - mngs.plt.ax_set_position
        
        ## mngs.ml.Reporter
        Now, classification task is available.
        ``` python
        reporter = mngs.ml.Reporter(sdir=log_dir)
        for i_fold in range(N_FOLDS):
            ...
            print("\n--- Metrics ---\n")
            reporter.calc_metrics(
                T_tes,
                pred_class_tes,
                pred_proba_tes,
                labels=[class_0, class_1, class_2],
                i_fold=i_fold,
            )
            print("\n---------------\n")
        
        reporter.summarize()
        reporter.save()
        ```
        
        The above lines makes reportes and figures.
        ``` bash
        $ tree $log_dir
        ├── aucs.csv
        ├── bACCs.csv
        ├── balanced_accs.csv
        ├── clf_reports.csv
        ├── conf_mat
        │   ├── conf_mats.csv
        │   ├── fold#0.png
        │   ├── fold#1.png
        │   ├── fold#2.png
        │   └── overall_sum.png
        ├── mccs.csv
        ├── pre_rec_curves
        │   ├── fold#0.png
        │   ├── fold#1.png
        │   └── fold#2.png
        └── roc_curves
            ├── fold#0.png
            ├── fold#1.png
            └── fold#2.png
        ```
        
Keywords: utils,utilities,python,machine learning
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
