CYGNO LIB

middle software tools to handle cygno data, repository, images, ecc.

install the CYGNO library:

full requirements:

Pyroot: https://root.cern/manual/python/ (same function require root IO)
oidc-agent: https://indigo-dc.gitbook.io/oidc-agent/installation (agent needed for repo_tool or S3 python library to get open id token)
boto3sts: https://github.com/DODAS-TS/boto3sts (primitive for S3 python library)
MIDAS: https://github.com/CYGNUS-RD/middleware/tree/master/midas (MIDAS libarary to open and read CYGNO raw data)

install:

      pip install git+https://github.com/CYGNUS-RD/cygno.git -U

CYGNO CLI Tools

cygno_repo

tool to operate on CYGNO backet in S3 exeperiment repository

requirements:

configure oidc-agent on your machine: https://codimd.web.cern.ch/s/SL-cWzDZB (DAQ setup, expert only https://codimd.web.cern.ch/s/_XqFfF_7V)

example for osx

brew tap indigo-dc/oidc-agent
brew install oidc-agent

install the IAM-Profile (not WLCG-Profile token) as reported in the second part of the guide https://codimd.web.cern.ch/s/SL-cWzDZB

install python library (https://github.com/DODAS-TS/boto3sts):

pip install git+https://github.com/DODAS-TS/boto3sts
pip install git+https://github.com/CYGNUS-RD/cygno.git

see https://boto3.amazonaws.com/v1/documentation/api/latest/index.html for S3 documentation

before run the script crate the iam token:

  eval `oidc-agent`
  oidc-gen --flow device --dae https://iam.cloud.infn.it/devicecode infncloud-iam (to generate) 
  oidc-token infncloud-iam (to see your active token)

or refresh the token

  eval `oidc-agent`
  oidc-gen --reauthenticate --flow device infncloud-iam (if you alrady have the token)

you can also add in your bash (or equivalent) profile

echo "CLOUD storage setup: infncloud-iam"
export REFRESH_TOKEN="xxx"
export IAM_CLIENT_SECRET="yyy"
export IAM_CLIENT_ID="zzz"
export IAM_SERVER=https://iam.cloud.infn.it/
unset OIDC_SOCK; unset OIDCD_PID; eval `oidc-keychain`
oidc-gen --client-id $IAM_CLIENT_ID --client-secret $IAM_CLIENT_SECRET --rt $REFRESH_TOKEN --manual --issuer $IAM_SERVER --pw-cmd="echo pwd" --redirect-uri="edu.kit.data.oidc-agent:/redirect

http://localhost:34429 http://localhost:8080 http://localhost:4242" --scope "iam openid email profile offline_access" infncloud-iam

to get setup info, type:

oidc-gen -p infncloud-iam

usage

Usage: cygno_repo	 [-tsv] [ls backet]
			 [put backet filename]
			 [[get backet filein] fileout]
			 [rm backet fileneme]


Options:
  -h, --help            	show this help message and exit
  -t TAG, --tag=TAG     	tag where dir for data;
  -s SESSION, --session=SESSION	token profile [infncloud-iam];
  -v, --verbose         	verbose output;

example:

  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo ls cygno-sim -t test
  2021-10-17 10:03:21  test/s3_list.py
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo put cygno-sim s3_function.py -t test
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo ls cygno-sim -t test
  2021-10-26 16:36:03  test/s3_function.py
  2021-10-17 10:03:21  test/s3_list.py
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo get cygno-sim s3_function.py -t test
  downloading file of 5.82 Kb...
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo ls cygno-sim -t test
  2021-10-26 16:36:03  test/s3_function.py
  2021-10-17 10:03:21  test/s3_list.py
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo rm cygno-sim s3_function.py -t test
  removing file of 5.82 Kb...
  removed file: s3_function.py
  Giovannis-MacBook-Air-2:script mazzitel$ cygno_repo ls cygno-sim -t test
  2021-10-17 10:03:21  test/s3_list.py

Data are also shared in CYGNO CLOUD resources via the CYGNO application: https://notebook.cygno.cloud.infn.it:8888/ (jupyter notebook, python, root and terminal use dodasts/cygno-jupyter:v2.1 image) and availeble via web broser https://minio.cloud.infn.it/

cygno_runs

tool to show SQL runs infromation stored in the logbook

Usage: cygno_runs        [-jsetv] run number

Options:
  -h, --help            show this help message and exit
  -j, --json            json output;
  -g, --google          old google sheet;
  -t TAG, --tag=TAG     tag [lngs](lnf/man)]
  -s START_RUN, --start_run=START_RUN
                        start run [0]
  -e END_RUN, --end_run=END_RUN
                        end run [100000000]
  -v, --verbose         verbose output;

example:

cygno_runs 368 -j (retrive data for run 368 from lngs db in json format)
cygno_runs -s 368 -e 388 -t man (dump info from run 268 to run 388 for mango data in text formt)

HTTP access

sigle run query output: http://lnf.infn.it/~mazzitel/php/cygno_sql_query.php?run=368
full database table: http://lnf.infn.it/~mazzitel/php/cygno_sql_query.php?table=on

cygno_his2root

convert HIS HoKaWo output file in CYGNO root histograms data files

Usage: cygno_his2root	 [-d] DIRECTORY

Options:
  -h, --help     show this help message and exit
  -d, --delete   delete HIS file after conversion;
  -v, --verbose  verbose output;

cygno_mid2root

convert MIDAS output file in CYGNO root histograms data files. Required:

pip install 'https://github.com/CYGNUS-RD/middleware/blob/master/midas/midaslib.tar.gz?raw=true'

tool:

Usage: cygno_mid2root	 <RUN number>

Options:
  -h, --help            show this help message and exit
  -p PATH, --path=PATH  path to file or cache directory
  -v, --verbose         verbose output;

CYGNO library functions

files

1.0.7 open_mid(run, path='/tmp/', cloud=True, tag='LNGS', verbose=False): open/cache MIDAS form cloud in path, return poiner to file (see example)
1.0.7 daq_cam2array(bank, verbose=False): decode daq equipment CAM, return image (2D array) shape_x_image (int), shape_y_image (int)
(obsolete) daq_dgz2header(bank, verbose=False): decode daq equipment header DGZ, return number_events (int), number_channels (int), number_samples (int)
1.0.9 daq_dgz_full2header(bank, verbose=False): decode full daq equipment header DGZ, return number_events, number_channels, number_samples, vertical_resulution, sampling_rate (offset and TTT are not returned up to now)
(obsolete) daq_dgz2array(bank, header, verbose=False): decode daq equipment data DGZ, return waveform array of #number_channels * #number_samples dimesion
1.0.9 daq_dgz_full2array(bank, header, verbose=False): decode fast an slow daq equipment data DGZ, return waveform_f, waveform_s
1.0.8 daq_slow2array(bank, verbose=False): decode daq equipment INPUT
1.0.11 dgtz_header new class for the dgtz header variables. It has array-like indexing to preserve retro compatibility
1.0.11 daq_dgz_full2header(bank, verbose=False) updated, it returns now the header class with: number_events, number_channels, number_samples, vertical_resulution, sampling_rate, channels_offset, channels_ttt, channels_SIC
1.0.11 daq_dgz_full2array(bank, header, verbose=False, corrected=True, ch_offset=[]) now includes the possibillity of correcting fast DGZ waveforms if they are acquired without the DRS4 Correction. Only the first 8 channels can be corrected up to now.

Storage and SQL

1.0.8 daq_sql_cennection(verbose=False): return SQL connection
1.0.8 daq_update_runlog_replica_checksum(connection, run_number, md5sum, verbose=False): return run checksum
1.0.8 daq_update_runlog_replica_tag(connection, run_number, TAG, verbose=False): return run tag
1.0.8 daq_update_runlog_replica_size(connection, run_number, size, verbose=False): return run size
1.0.8 daq_update_runlog_replica_status(connection, run_number, storage, status=-1, verbose=False): update run replica status
1.0.8 daq_read_runlog_replica_status(connection, run_number, storage, verbose=False): return run replica status
1.0.8 daq_not_on_tape_runs(connection, verbose=False): return array of file not on tape
1.0.8 daq_run_info(connection, run, verbose=False): return run info

old api before midas raw data

open_root(run, path='/tmp/', cloud=True, tag='LAB', verbose=False) open/cache ROOT form cloud in path class cfile:

		def __init__(self, file, pic, wfm, max_pic, max_wfm, x_resolution, y_resolution):
			self.file         = file
			self.pic          = pic 
			self.wfm          = wfm
			self.max_pic      = max_pic
			self.max_wfm      = max_wfm
			self.x_resolution = x_resolution
			self.y_resolution = y_resolution

open_(run, tag='LAB', posix=False, verbose=True) - open cygno ROOT/MID file from remote or on cloud posix like access and return cfile class type
read_(f, iTr) - return image array from file poiter
pic_(cfile, iTr=0) - return immage array of track iTr from cfile
wfm_(cfile, iTr=0, iWf=0) - return amplitude and time of iTr track and iWr waveform from cfile
ped_(run, path='./ped/', tag = 'LAB', posix=False, min_image_to_read = 0, max_image_to_read = 0, verbose=False) - cerate (if not exist) root file image of mean and sigma for each pixel and return main and sigma imege of pedestal runs

logbook

1.0.2 read_cygno_logbook(sql=True, tag='lngs', start_run=0, end_run=100000000, verbose=False):ruturn pandas db old google sheet logbook info
1.0.2 run_info_logbook(run, tag='lngs', sql=True, verbose=False):return pandas db google/sql run [int] info

s3 repo

1.0.1 s3.root_file(run, tag='LAB', posix=False, verbose=False): read root file from s3 CYGNO baket
1.0.1 s3.backet_list(tag, bucket='cygno-sim', session="infncloud-iam", verbose=False): list file from s3 CYGNO baket
1.0.1 s3.obj_put(filename, tag, bucket='cygno-sim', session="infncloud-iam", verbose=False): put file in s3 CYGNO baket
1.0.1 s3.obj_get(filein, fileout, tag, bucket='cygno-sim', session="infncloud-iam", verbose=False): get file from s3 CYGNO baket
1.0.1 s3.obj_rm(filename, tag, bucket='cygno-sim', session="infncloud-iam", verbose=False): remouve file from s3 CYGNO baket

images and PMT tools

cluster_par(xc, yc, image): return intesity and dimestion
n_std_rectangle(x, y, ax, image = np.array([]), n_std=3.0, facecolor='none', kwargs): return rettagle confindece level image
confidence_ellipse(x, y, ax, image = np.array([]), n_std=3.0, facecolor='none', kwargs): return ellips confidence level image
confidence_ellipse_par(x, y, image = np.array([]), n_std=3.0, facecolor='none', kwargs): return quantity width, height, pearson, sum, size in the confidence ellips
cluster_elips(points): return points_3d
rebin(a, shape): return rebined shape
smooth(y, box_pts): return smooted array of box_pts dimesion
img_proj(img, vmin, vmax, log=False): retrun plot of image projection
1.0.9 get_pmt_w_by_triggers(waveform, header, number_of_w_readed, trigger) return array of pmt data 0 to number_of_w_readed for a given trigger (int)
1.0.11 correct_waveforms(wfs_in, SIC, nChannels=32, path='./', to_correct=list(range(8))): DSR4 Correction for the fast dgtz. Only the first 8 channels can be corrected for now, returns the waveforms corrected wfs
1.0.11 PeakCorrection(wfs_in, Nch = 8): helper for the correct_waveforms function, returns the waveforms peak-corrected wfsa

NB usefull and primitive UNIX and SQL function are available in the library https://github.com/CYGNUS-RD/cygno/blob/main/cygno/cmd.py

Name		Name	Last commit message	Last commit date
Latest commit History 391 Commits
bin		bin
cygno		cygno
dev		dev
img		img
.gitignore		.gitignore
HoKaWo.md		HoKaWo.md
README.md		README.md
infrastructure.md		infrastructure.md
requirements.txt		requirements.txt
setup.py		setup.py

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Repository files navigation

CYGNO LIB

install the CYGNO library:

CYGNO CLI Tools

cygno_repo

cygno_runs

cygno_his2root

cygno_mid2root

CYGNO library functions

files

Storage and SQL

old api before midas raw data

logbook

s3 repo

images and PMT tools

About

Releases

Packages

Contributors 6

Languages

CYGNUS-RD/cygno

Folders and files

Latest commit

History

Repository files navigation

CYGNO LIB

install the CYGNO library:

CYGNO CLI Tools

cygno_repo

cygno_runs

cygno_his2root

cygno_mid2root

CYGNO library functions

files

Storage and SQL

old api before midas raw data

logbook

s3 repo

images and PMT tools

About

Resources

Stars

Watchers

Forks

Releases

Packages 0

Contributors 6

Languages

Packages