View app.py
from bottledaemon import daemon_run
from bottle import route, run, get
from talk_weather import talk_weather, talk_datetime
@get('/test')
def test():
return 'Hello Raspbery Pi!'
View clustering_based_elm.py
#!/usr/bin/env python
from elm import ELM
from sklearn.cluster import KMeans
import numpy as np
class ClusteringBasedELM(ELM):
"""
This script is clustering based extreme learning machine(CBELM),
View bagging.py
#!/usr/bin/env python
import copy
import numpy as np
from sklearn.base import BaseEstimator, ClassifierMixin
class Bagging(BaseEstimator, ClassifierMixin):
def __init__(self, estimator, n_ensemble, max_samples=1.0):
View CMakeLists.txt
cmake_minimum_required (VERSION 3.7)
project (matrix_calc_ndk)
add_executable(matrix_calc_ndk matrix_calc_ndk.cpp)
View github-pandoc.css
/*! normalize.css v2.1.3 | MIT License | git.io/normalize */
/* ==========================================================================
HTML5 display definitions
========================================================================== */
/**
* Correct `block` display not defined in IE 8/9.
*/
View numpy.hpp
/*
* Copyright (c) 2012 Masaki Saito
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
View input_array.cpp
#include <iostream>
#include "numpy.hpp"
int main(void) {
std::vector<int> s; // Vetor for matrix size
std::vector<int> int_data; // Vector for matrix element
aoba::LoadArrayFromNumpy("int_array.npy", s, int_data);
View graph.py
#!/usr/bin/env python
import numpy as np
from matplotlib import pylab as plt
import pandas as pd
import sys
def main():
View tabulate_sample.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
from tabulate import tabulate
from sklearn.preprocessing import normalize
from sklearn.datasets import fetch_mldata
from sklearn.model_selection import cross_val_score, KFold
from elm import ELM
View README.md

systemdによる定期実行

$HOME/.config/systemd/user/ofls-bot.serviceに以下を書く

[Unit]
Description=ofls-bot-service

[Service]
Type=simple
ExecStart=/home/s1200107/.pyenv/shims/python /home/s1200107/Dropbox/Works/ofls-bot/ofls_bot.py