automatic import of python-mngs

3 files changed, 541 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..5afa4a2 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/mngs-0.4.0.tar.gz
diff --git a/python-mngs.spec b/python-mngs.spec
new file mode 100644
index 0000000..febefa6
--- /dev/null
+++ b/python-mngs.spec
@@ -0,0 +1,539 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-mngs
+Version:	0.4.0
+Release:	1
+Summary:	For lazy python users (monogusa people in Japanse), especially in ML/DSP fields
+License:	GPL3.0
+URL:		https://github.com/ywatanabe1989/mngs
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/f2/95/0bc28b15ac436c49c9becb10049eddf3c0c94860908fbe74e94ca3d20afc/mngs-0.4.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-chardet
+Requires:	python3-GitPython
+Requires:	python3-h5py
+Requires:	python3-joblib
+Requires:	python3-matplotlib
+Requires:	python3-natsort
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-pymatreader
+Requires:	python3-PyYAML
+Requires:	python3-scipy
+Requires:	python3-seaborn
+Requires:	python3-sklearn
+Requires:	python3-statsmodels
+Requires:	python3-torch
+Requires:	python3-xmltodict
+Requires:	python3-openpyxl
+Requires:	python3-obspy
+Requires:	python3-pyro-ppl
+Requires:	python3-torchaudio
+Requires:	python3-scikit-learn
+Requires:	python3-psutil
+Requires:	python3-pyedflib
+
+%description
+## Requirements
+```
+chardet
+GitPython
+h5py
+joblib
+matplotlib
+natsort
+numpy
+pandas
+pymatreader
+PyYAML
+scipy
+seaborn
+sklearn
+statsmodels
+torch
+xmltodict
+```
+
+## Installation
+``` bash
+$ pip install mngs
+
+or
+
+$ pip install git+https://github.com/ywatanabe1989/mngs.git@develop
+```
+
+
+
+## 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 $log_dir
+├── aucs.csv
+├── bACCs.csv
+├── balanced_accs.csv
+├── clf_reports.csv
+├── conf_mat
+│   ├── conf_mats.csv
+│   ├── fold#0.png
+│   ├── fold#1.png
+│   ├── fold#2.png
+│   └── overall_sum.png
+├── mccs.csv
+├── pre_rec_curves
+│   ├── fold#0.png
+│   ├── fold#1.png
+│   └── fold#2.png
+└── roc_curves
+    ├── fold#0.png
+    ├── fold#1.png
+    └── fold#2.png
+```
+
+
+
+
+%package -n python3-mngs
+Summary:	For lazy python users (monogusa people in Japanse), especially in ML/DSP fields
+Provides:	python-mngs
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-mngs
+## Requirements
+```
+chardet
+GitPython
+h5py
+joblib
+matplotlib
+natsort
+numpy
+pandas
+pymatreader
+PyYAML
+scipy
+seaborn
+sklearn
+statsmodels
+torch
+xmltodict
+```
+
+## Installation
+``` bash
+$ pip install mngs
+
+or
+
+$ pip install git+https://github.com/ywatanabe1989/mngs.git@develop
+```
+
+
+
+## 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 $log_dir
+├── aucs.csv
+├── bACCs.csv
+├── balanced_accs.csv
+├── clf_reports.csv
+├── conf_mat
+│   ├── conf_mats.csv
+│   ├── fold#0.png
+│   ├── fold#1.png
+│   ├── fold#2.png
+│   └── overall_sum.png
+├── mccs.csv
+├── pre_rec_curves
+│   ├── fold#0.png
+│   ├── fold#1.png
+│   └── fold#2.png
+└── roc_curves
+    ├── fold#0.png
+    ├── fold#1.png
+    └── fold#2.png
+```
+
+
+
+
+%package help
+Summary:	Development documents and examples for mngs
+Provides:	python3-mngs-doc
+%description help
+## Requirements
+```
+chardet
+GitPython
+h5py
+joblib
+matplotlib
+natsort
+numpy
+pandas
+pymatreader
+PyYAML
+scipy
+seaborn
+sklearn
+statsmodels
+torch
+xmltodict
+```
+
+## Installation
+``` bash
+$ pip install mngs
+
+or
+
+$ pip install git+https://github.com/ywatanabe1989/mngs.git@develop
+```
+
+
+
+## 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
+```
+
+
+
+
+%prep
+%autosetup -n mngs-0.4.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-mngs -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..30d83de
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+e2226fff65b1e9a1b44e233c9db252f9  mngs-0.4.0.tar.gz