Matteo Visconti di Oleggio Castello mvdoc

## rsync-retry.sh
#!/bin/bash

### ABOUT: See: http://gist.github.com/366269
### Runs rsync, retrying on errors up to a maximum number of tries.
### On failure script waits for internect connection to come back up by pinging google.com before continuing.
###
### Usage: $ ./rsync-retry.sh source destination
### Example: $ ./rsync-retry.sh user@server.example.com:~/* ~/destination/path/
###
### INPORTANT:

## cart2pol
def appendSpherical_np(xyz):
    ptsnew = np.hstack((xyz, np.zeros(xyz.shape)))
    xy = xyz[:,0]**2 + xyz[:,1]**2
    ptsnew[:,3] = np.sqrt(xy + xyz[:,2]**2)
    ptsnew[:,4] = np.arctan2(np.sqrt(xy), xyz[:,2]) # for elevation angle defined from Z-axis down
    #ptsnew[:,4] = np.arctan2(xyz[:,2], np.sqrt(xy)) # for elevation angle defined from XY-plane up
    ptsnew[:,5] = np.arctan2(xyz[:,1], xyz[:,0])
    return ptsnew

## README.md

      
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                mvdoc
                / README.md
            
            
              Created
              January 25, 2017 22:07
                — forked from hofmannsven/README.md
            
              
                My simply MySQL Command Line Cheatsheet
              
          
    MySQL

Getting started:

http://www.sqlteaching.com/
https://www.codecademy.com/courses/learn-sql

Related tutorials:

MySQL-CLI: https://www.youtube.com/playlist?list=PLfdtiltiRHWEw4-kRrh1ZZy_3OcQxTn7P
Analyzing Business Metrics: https://www.codecademy.com/learn/sql-analyzing-business-metrics


## nested_cv_parallel.py
from mvpa2.suite import *
# increase verbosity a bit for now
verbose.level = 3
# pre-seed RNG if you want to investigate the effects, thus
# needing reproducible results
#mvpa2.seed(3)
# we import Parallel and delayed from joblib to run in parallel
from joblib import Parallel, delayed

"""

## jupyter_notebook_config.py
# This file should be put in ~/.jupyter/
# New notebooks will be renamed to YYYY-MM-DD_untitled-N.ipynb instead of Untitled.ipynb
# Please be aware that this code has **NOT** been tested extensively, I wrote it rather quickly,
# and thus your notebook might be deleted by accident.
#
# USE THIS CODE AT YOUR OWN RISK
#

import os
import re

## get_size_localcopy_annex.py
# This script computes the total size of git-annex files with only a single local copy.
# It's useful to figure out how much data will be used if all the files were to be archived.
import subprocess
from tqdm import tqdm
import json
import os

def get_files_with_one_copy():
    try:
        result = subprocess.run(['git-annex', 'find', '--copies=1', '--and', '--not', '--copies=2', '--and', '--in=here'], capture_output=True, text=True, check=True)
	#!/bin/bash

	### ABOUT: See: http://gist.github.com/366269
	### Runs rsync, retrying on errors up to a maximum number of tries.
	### On failure script waits for internect connection to come back up by pinging google.com before continuing.
	###
	### Usage: $ ./rsync-retry.sh source destination
	### Example: $ ./rsync-retry.sh user@server.example.com:~/* ~/destination/path/
	###
	### INPORTANT:
	def appendSpherical_np(xyz):
	ptsnew = np.hstack((xyz, np.zeros(xyz.shape)))
	xy = xyz[:,0]2 + xyz[:,1]2
	ptsnew[:,3] = np.sqrt(xy + xyz[:,2]**2)
	ptsnew[:,4] = np.arctan2(np.sqrt(xy), xyz[:,2]) # for elevation angle defined from Z-axis down
	#ptsnew[:,4] = np.arctan2(xyz[:,2], np.sqrt(xy)) # for elevation angle defined from XY-plane up
	ptsnew[:,5] = np.arctan2(xyz[:,1], xyz[:,0])
	return ptsnew
	from mvpa2.suite import *
	# increase verbosity a bit for now
	verbose.level = 3
	# pre-seed RNG if you want to investigate the effects, thus
	# needing reproducible results
	#mvpa2.seed(3)
	# we import Parallel and delayed from joblib to run in parallel
	from joblib import Parallel, delayed

	"""
	# This file should be put in ~/.jupyter/
	# New notebooks will be renamed to YYYY-MM-DD_untitled-N.ipynb instead of Untitled.ipynb
	# Please be aware that this code has NOT been tested extensively, I wrote it rather quickly,
	# and thus your notebook might be deleted by accident.
	#
	# USE THIS CODE AT YOUR OWN RISK
	#

	import os
	import re
	# This script computes the total size of git-annex files with only a single local copy.
	# It's useful to figure out how much data will be used if all the files were to be archived.
	import subprocess
	from tqdm import tqdm
	import json
	import os

	def get_files_with_one_copy():
	try:
	result = subprocess.run(['git-annex', 'find', '--copies=1', '--and', '--not', '--copies=2', '--and', '--in=here'], capture_output=True, text=True, check=True)