icaoberg

#!/bin/bash

if [ "$#" -ne 1 ]; then
  echo "Usage: $0 <username>" >&2
  exit 1
fi

USERNAME=$1
TEMP=`omero user list | grep "$USERNAME"`
if [ -z "$TEMP" ]; then echo false; else echo true; fi

icaoberg

#!/bin/bash

if [ "$#" -ne 1 ]; then
  echo "Usage: $0 <groupname>" >&2
  exit 1
fi

GROUPNAME=$1
TEMP=`omero group list | grep "$GROUPNAME"`
if [ -z "$TEMP" ]; then echo false; else echo true; fi

icaoberg

#!/bin/bash

sudo apt-get install python-vtk python-wxgtk2.6 python-setuptools python-numpy python-configobj
sudo easy_install pip
sudo pip install mayavi

icaoberg

pbs -Q

icaoberg

#!/bin/bash

for FILE in *
do
    if [ -f "$FILE" ];then
		ID=`uuidgen`
		EXTENSION=${FILE#*.}
	mv -v "$FILE" "$ID"."$EXTENSION"
	fi
done

icaoberg

#the docstrings for the method calculate from pyslid

def calculate( conn, iid, scale=1, set="slf33", field=True, rid=None, pixels=0, channels=[], zslice=0, timepoint=0, threshold=None, debug=False ):
    '''
    Calculates and returns a feature ids vector, a feature vector and the output scale given a valid
    image identification (iid). It currently can calculate SLF33, SLF34, SLF35 and SLF36.

    This method will try to retrieve the resolution of the image from the annotations. 

    If the method is unable to connect to the OMERO.server, then the method will return None.

icaoberg

function out_img = img2projection( img, param )
% IM2GPROJECTION creates a sum or mean projection of the input image
%
% Input:
% img = a 3D binary or realvalued image.
% param = struct with a 'method' field that can be set
% to 'mean' if a mean value projection is desired
% Output:
% out_img = a 2D image that contains a projection
% in each dimension of the original image

icaoberg

#!/bin/bash

#COMMENT: I used brew to install gource and ffmpeg in MacOSX
#To install brew and the two packages in terminal run
#ruby -e "$(curl -fsSL https://raw.github.com/mxcl/homebrew/go)"
#brew install gource
#brew install ffmpeg

OUTPUT=$1

icaoberg

#!/bin/bash

gource --hide dirnames,usernames --title "Protein Subcellular Location Image Database for Python" --seconds-per-day 1 --auto-skip-seconds 1 -1280x720 -o - | ffmpeg -y -r 60 -f image2pipe -vcodec ppm -i - -vcodec libx264 -preset ultrafast -pix_fmt yuv420p -crf 1 -threads 0 -bf 0 ./pyslid.mp4

icaoberg

#!/bin/bash

git clone [email protected]:cjlin1/libsvm.git
cd libsvm
make