akimach

## mnpy.py
import ast
import builtins


def make_stmts(exps):
  exps = [simplify(exp) for exp in exps]
  if len(exps) == 1:
    return exps[0]
  else:
    return ["stmts", *exps]

## checkWeeklyReport.js
function checkWeeklyReport() {
  var rootFolder = DriveApp.getFolderById('xxx');
  Logger.log(rootFolder.getName());

  var sheet = SpreadsheetApp.getActive().getSheetByName('シート1');
  sheet.clear();

  var editor_dic = {};
  Logger.log("===");
  var i = 1;

## imagenet1000_clsid_to_human.json
{
  "0" : "tench, Tinca tinca",
  "1" : "goldfish, Carassius auratus",
  "2" : "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
  "3" : "tiger shark, Galeocerdo cuvieri",
  "4" : "hammerhead, hammerhead shark",
  "5" : "electric ray, crampfish, numbfish, torpedo",
  "6" : "stingray",
  "7" : "cock",
  "8" : "hen",

## merge_pdf.sh
"/System/Library/Automator/Combine PDF Pages.action/Contents/Resources/join.py" -o ~/path/to/merged.pdf ~/path/to/merge/*.pdf

## ann-visualizer.ipynb

      
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                akimach
                / ann-visualizer.ipynb
            
            
              Created
              April 3, 2018 10:58
            
          
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## ipynb2docx.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
# Convert .ipynb to .docx

## Dependency

* Jupyter notebook
* Pandoc

## main.go
package main

/*
$ go run main.go
[3 9 2 4 1]
[1 2 3 4 9]
*/

import (
	"fmt"

## generate-react-skelton.py
#!/usr/bin/env python
#!coding: utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import sys
import os, os.path
import subprocess
import json

## file0.txt
$ git clone git@github.com:akimach/note.git

## linear-regression-with-r.ipynb-meta
Title: Linear regression of Boston Housing Dataset using R
Slug: linear-regression-with-r
Date: 2017-11-06 17:00
Category: Notebook
Tags: R
	import ast
	import builtins


	def make_stmts(exps):
	exps = [simplify(exp) for exp in exps]
	if len(exps) == 1:
	return exps[0]
	else:
	return ["stmts", *exps]
	function checkWeeklyReport() {
	var rootFolder = DriveApp.getFolderById('xxx');
	Logger.log(rootFolder.getName());

	var sheet = SpreadsheetApp.getActive().getSheetByName('シート1');
	sheet.clear();

	var editor_dic = {};
	Logger.log("===");
	var i = 1;
	{
	"0" : "tench, Tinca tinca",
	"1" : "goldfish, Carassius auratus",
	"2" : "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
	"3" : "tiger shark, Galeocerdo cuvieri",
	"4" : "hammerhead, hammerhead shark",
	"5" : "electric ray, crampfish, numbfish, torpedo",
	"6" : "stingray",
	"7" : "cock",
	"8" : "hen",
	#!/usr/bin/env python
	# -- coding: utf-8 --
	"""
	# Convert .ipynb to .docx

	## Dependency

	* Jupyter notebook
	* Pandoc
	package main

	/*
	$ go run main.go
	[3 9 2 4 1]
	[1 2 3 4 9]
	*/

	import (
	"fmt"
	#!/usr/bin/env python
	#!coding: utf-8
	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function

	import sys
	import os, os.path
	import subprocess
	import json
	Title: Linear regression of Boston Housing Dataset using R
	Slug: linear-regression-with-r
	Date: 2017-11-06 17:00
	Category: Notebook
	Tags: R