Janos Tolgyesi mrtj

## BouncyButtonViewController.h
#import <UIKit/UIKit.h>

@interface BouncyButtonViewController : UIViewController

@end

## TJIntegerArray.h
// Author: janos.tolgyesi@gmail.com
// License: BSD

#import <Foundation/Foundation.h>

@interface TJIntegerArray : NSObject <NSFastEnumeration>
{
    NSInteger* _array;
}

## csv2md.py
from __future__ import print_function
import csv

def print_row(row, maxlen):
    for elem, len in zip (row, maxlen):
        print('| {} '.format(elem.ljust(len)), end='')
    print('|')

def print_hline(maxlen):
    for len in maxlen:

## NSURL+QueryParser.h
#import <Foundation/Foundation.h>

@interface NSURL (QueryParser)

-(NSDictionary*)queryDictionary;

@end


## covid-19-mortality-municipality-table.md

      
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                mrtj
                / covid-19-mortality-municipality-table.md
            
            
              Last active
              April 20, 2020 16:38
            
              
                mortality-covis19 article, municipality table
              
          
municip.
population
start date
expected mortality
actual mortality
excess rate
date of peak
figure


Nembro
11526
2020‑02‑20
15
149
993%
2020‑03‑10


Albino
17805
2020‑02‑21
15
141
940%
2020‑03‑13
![Excess mortality in Albino](https://gist.github.com/mrtj/8daefd0e5f103e5611850ac2cae8bc1b/raw/6a61fb3ea435b34411a88252d19c56ddfef2d063/mortali


## ggcore_enable_sync.py
import boto3
import logging
import json
import re
import uuid
import argparse

'''
This script enables the IoT shadow syncing for your AWS Greengrass Core.

## augmented_image_format.py
import glob
prefix = 's3://my_bucket/dogs_vs_cats/'
with open('manifest.jsonl', 'w') as f:
    for img in glob.glob('*.jpg'):
        lbl = 0 if img.startswith('dog') else 1
        f.write('{{"source-ref":"{}{}", "class":"{}"}}\n'\
                .format(prefix, img, lbl))

## start_step_functions.sh
aws stepfunctions start-execution \
  - state-machine-arn {CrossValidatorStateMachineArn} \
  - input file://my_input.json

## augmented_image_format_s3.py
import boto3
bucket, prefix = 'my_bucket', 'datasets/dogs_vs_cats'
paginator = boto3.client('s3').get_paginator('list_objects')
with open('manifest.jsonl', 'w') as f:
    for page in paginator.paginate(Bucket=bucket, Prefix=prefix):
        for obj in page['Contents']:
            lbl = 0 if 'dog.' in obj['Key'] else 1
            f.write('{{"source-ref":"s3://{}/{}", "class":"{}"}}\n'\
                .format(bucket, obj['Key'], lbl))

## kinetics_actions.sh
#!/usr/bin/env bash
cat train.csv | sed 's/ /_/g' | sed 's/,/ /g' | awk '{print $1}' | grep "$1" | sort | uniq
	#import <UIKit/UIKit.h>

	@interface BouncyButtonViewController : UIViewController

	@end
	// Author: janos.tolgyesi@gmail.com
	// License: BSD

	#import <Foundation/Foundation.h>

	@interface TJIntegerArray : NSObject <NSFastEnumeration>
	{
	NSInteger* _array;
	}
	from __future__ import print_function
	import csv

	def print_row(row, maxlen):
	for elem, len in zip (row, maxlen):
	print('\| {} '.format(elem.ljust(len)), end='')
	print('\|')

	def print_hline(maxlen):
	for len in maxlen:
	#import <Foundation/Foundation.h>

	@interface NSURL (QueryParser)

	-(NSDictionary*)queryDictionary;

	@end
municip.	population	start date	expected mortality	actual mortality	excess rate	date of peak	figure
Nembro	11526	2020‑02‑20	15	149	993%	2020‑03‑10
Albino	17805	2020‑02‑21	15	141	940%	2020‑03‑13	![Excess mortality in Albino](https://gist.github.com/mrtj/8daefd0e5f103e5611850ac2cae8bc1b/raw/6a61fb3ea435b34411a88252d19c56ddfef2d063/mortali
	import boto3
	import logging
	import json
	import re
	import uuid
	import argparse

	'''
	This script enables the IoT shadow syncing for your AWS Greengrass Core.
	import glob
	prefix = 's3://my_bucket/dogs_vs_cats/'
	with open('manifest.jsonl', 'w') as f:
	for img in glob.glob('*.jpg'):
	lbl = 0 if img.startswith('dog') else 1
	f.write('{{"source-ref":"{}{}", "class":"{}"}}\n'\
	.format(prefix, img, lbl))
	aws stepfunctions start-execution \
	- state-machine-arn {CrossValidatorStateMachineArn} \
	- input file://my_input.json
	import boto3
	bucket, prefix = 'my_bucket', 'datasets/dogs_vs_cats'
	paginator = boto3.client('s3').get_paginator('list_objects')
	with open('manifest.jsonl', 'w') as f:
	for page in paginator.paginate(Bucket=bucket, Prefix=prefix):
	for obj in page['Contents']:
	lbl = 0 if 'dog.' in obj['Key'] else 1
	f.write('{{"source-ref":"s3://{}/{}", "class":"{}"}}\n'\
	.format(bucket, obj['Key'], lbl))
	#!/usr/bin/env bash
	cat train.csv \| sed 's/ /_/g' \| sed 's/,/ /g' \| awk '{print $1}' \| grep "$1" \| sort \| uniq