HighResAnalysis
================
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
The current repository is in development and is not guaranteed to work
The working version can be found
https://github.com/diamondIPP/HighResAnalysis
## Prerequisites
- [python](https://www.python.org)\>=3.6
- python=3.10 was used for the development
- [cmake](https://cmake.org)\>=3.7
- optionally [cmake GUI](https://cmake.org/runningcmake/), for example
ccmake
## Installation
- First, install `mamba`. If you do not yet have `conda` install then
getting
[Mambaforge](https://github.com/conda-forge/miniforge#mambaforge) is
the recommended way to get `mamba`. Here is the instruction for Linux.
``` shell
curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh"
bash Mambaforge-Linux-x86_64.sh
```
If this not the case for you. You can follow the instruction on [mamba
install
page](https://mamba.readthedocs.io/en/latest/installation.html#installation "complete mamba installation instructions")
- Next you can install [root](https://root.cern.ch). In the [root
installation instructions](https://root.cern/install/#conda) you need
to replace `conda` with `mamba` and skip the instructions about the
environment, since the `Mambaforge` already created the default `base`
environment.
``` shell
mamba config --set channel_priority strict
mamba install root
mamba install -c conda-forge root
```
- Install the analysis code:
``` shell
pip install HighResAnalysys
```
- Optionally install other useful python packages:
``` shell
mamba install -c conda-forge scikit-learn numpy pandas
mamba install pyarrow openpyxl xlrd pytables requests sqlalchemy
mamba install -c fastai nbdev
mamba install jupyterlab
mamba install jupyternotebook
mamba install ipython
mamba install notebook
mamba install voila
```
- For the installation of the software hosted on the GitHub it is useful
to make a dedicated folder:
``` shell
mkdir software
cd software
```
- And clone all the necessary packages there:
``` shell
git clone git@github.com:diamondIPP/DRS4-v5-shared.git
git clone git@github.com:diamondIPP/proteus.git
git clone git@github.com:diamondIPP/judith.git
git clone git@github.com:diamondIPP/HVClient.git
git clone git@github.com:diamondIPP/eudaq-2.git
```
- generate shh keys and copy them to login.phys.ethz.ch
``` shell
ssh-keygen
ssh-copy-id username@login.phys.ethz.ch
```
- Clone the analysis setup from GitHub. It contains all the necessary
config files:
``` shell
git clone git@github.com:diamondIPP/setup-analysis.git HighResAnalysis
cd HighResAnalysis/
```
- To install the converters follow the instructions on the respective
pages:
- [proteus](https://github.com/diamondIPP/proteus)
- It will need
[Eigen3](https://eigen.tuxfamily.org/index.php?title=Main_Page)
and you will have to tell `cmake` the path to it.
- [judith](https://github.com/diamondIPP/judith) (only for CERN data)
- [eudaq2](https://github.com/diamondIPP/eudaq-2) (only for DESY data)
## Example analysis of the DESY data
the data need to be frist pre-converted:
`>analyse --run=4`
you will need to import a couple of libraries. Most of the tools are in
`src.dut_analysis`. It will load the data and set all the cuts. The
`draw` module from plotting library has some useful functions and
presets that allow plotting histograms and graphs
``` python
from HighResAnalysis.src.dut_analysis import *
from HighResAnalysis.plotting.draw import *
```
Welcome to JupyROOT 6.28/00
Initialize the DUTAnalysis with run number, DUT number, and a string
indicating the year and the month of the beam test
``` python
run4 = DUTAnalysis(4, 0, '201912')
```
--- Palette ------ 55
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
STARTING DUT ANALYSIS of D02, run 4 (Dec 2019), 2.50M ev |
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
************** Initing Converter *****************
*************** Initing PROTEUS ******************
A small function that allows inline plotting of ROOT histograms
``` python
def dc(): get_last_canvas().Draw()
```
Let’s plot a signal distribution
``` python
run4.draw_charge_distribution()
dc()
```
INFO: 10:34:18 --> Creating directory: /Users/hits/Documents/GitHub/HighResAnalysis/HighResAnalysis/results/201912
INFO: 10:34:18 --> saving plot: SignalDist
WARNING: 10:34:19 --> Diamond server is not mounted in /Users/hits/mounts/high-rate
Raw data
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"description": "HighResAnalysis\n================\n\n<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->\n\nThe current repository is in development and is not guaranteed to work\nThe working version can be found\nhttps://github.com/diamondIPP/HighResAnalysis\n\n## Prerequisites\n\n- [python](https://www.python.org)\\>=3.6\n - python=3.10 was used for the development\n- [cmake](https://cmake.org)\\>=3.7\n - optionally [cmake GUI](https://cmake.org/runningcmake/), for example\n ccmake\n\n## Installation\n\n- First, install `mamba`. If you do not yet have `conda` install then\n getting\n [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge) is\n the recommended way to get `mamba`. Here is the instruction for Linux.\n\n``` shell\ncurl -L -O \"https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh\"\nbash Mambaforge-Linux-x86_64.sh \n```\n\nIf this not the case for you. You can follow the instruction on [mamba\ninstall\npage](https://mamba.readthedocs.io/en/latest/installation.html#installation \"complete mamba installation instructions\")\n\n- Next you can install [root](https://root.cern.ch). In the [root\n installation instructions](https://root.cern/install/#conda) you need\n to replace `conda` with `mamba` and skip the instructions about the\n environment, since the `Mambaforge` already created the default `base`\n environment.\n\n``` shell\nmamba config --set channel_priority strict\nmamba install root\nmamba install -c conda-forge root\n```\n\n- Install the analysis code:\n\n``` shell\npip install HighResAnalysys\n```\n\n- Optionally install other useful python packages:\n\n``` shell\nmamba install -c conda-forge scikit-learn numpy pandas \nmamba install pyarrow openpyxl xlrd pytables requests sqlalchemy\nmamba install -c fastai nbdev\nmamba install jupyterlab\nmamba install jupyternotebook\nmamba install ipython\nmamba install notebook\nmamba install voila\n```\n\n- For the installation of the software hosted on the GitHub it is useful\n to make a dedicated folder:\n\n``` shell\nmkdir software\ncd software\n```\n\n - And clone all the necessary packages there:\n\n``` shell\n git clone git@github.com:diamondIPP/DRS4-v5-shared.git\n git clone git@github.com:diamondIPP/proteus.git\n git clone git@github.com:diamondIPP/judith.git\n git clone git@github.com:diamondIPP/HVClient.git\n git clone git@github.com:diamondIPP/eudaq-2.git\n```\n\n- generate shh keys and copy them to login.phys.ethz.ch\n\n``` shell\n ssh-keygen\n ssh-copy-id username@login.phys.ethz.ch\n```\n\n- Clone the analysis setup from GitHub. It contains all the necessary\n config files:\n\n``` shell\ngit clone git@github.com:diamondIPP/setup-analysis.git HighResAnalysis\ncd HighResAnalysis/\n```\n\n- To install the converters follow the instructions on the respective\n pages:\n - [proteus](https://github.com/diamondIPP/proteus)\n - It will need\n [Eigen3](https://eigen.tuxfamily.org/index.php?title=Main_Page)\n and you will have to tell `cmake` the path to it.\n - [judith](https://github.com/diamondIPP/judith) (only for CERN data)\n - [eudaq2](https://github.com/diamondIPP/eudaq-2) (only for DESY data)\n\n## Example analysis of the DESY data\n\nthe data need to be frist pre-converted:\n\n`>analyse --run=4`\n\nyou will need to import a couple of libraries. Most of the tools are in\n`src.dut_analysis`. It will load the data and set all the cuts. The\n`draw` module from plotting library has some useful functions and\npresets that allow plotting histograms and graphs\n\n``` python\nfrom HighResAnalysis.src.dut_analysis import *\nfrom HighResAnalysis.plotting.draw import *\n```\n\n Welcome to JupyROOT 6.28/00\n\nInitialize the DUTAnalysis with run number, DUT number, and a string\nindicating the year and the month of the beam test\n\n``` python\nrun4 = DUTAnalysis(4, 0, '201912')\n```\n\n --- Palette ------ 55\n\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n STARTING DUT ANALYSIS of D02, run 4 (Dec 2019), 2.50M ev |\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n ************** Initing Converter *****************\n *************** Initing PROTEUS ******************\n\nA small function that allows inline plotting of ROOT histograms\n\n``` python\ndef dc(): get_last_canvas().Draw()\n```\n\nLet\u2019s plot a signal distribution\n\n``` python\nrun4.draw_charge_distribution()\ndc()\n```\n\n INFO: 10:34:18 --> Creating directory: /Users/hits/Documents/GitHub/HighResAnalysis/HighResAnalysis/results/201912\n INFO: 10:34:18 --> saving plot: SignalDist\n WARNING: 10:34:19 --> Diamond server is not mounted in /Users/hits/mounts/high-rate\n\n\n",
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