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soft:ciao [2024/12/04 05:31] asadsoft:ciao [2024/12/04 06:11] (current) asad
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 ====== CIAO ====== ====== CIAO ======
- 
-===== Quick start ===== 
-  - [[https://cxc.cfa.harvard.edu/ciao/ahelp/blanksky_image.html|blanksky_image]] bkgfile='_background_clean.evt' outroot='_blank' imgfile='_0.5-7_thresh.img' tmpdir=./ clobber=yes 
-  - [[https://cxc.cfa.harvard.edu/ciao/ahelp/merge_obs.html|merge_obs]] 
  
 ===== Install on Ubuntu 24.04 LTS using conda ===== ===== Install on Ubuntu 24.04 LTS using conda =====
-After installing [[https://docs.anaconda.com/anaconda/install/linux/|anaconda3 in Ubuntu]] 18.04 LTS, follow https://cxc.cfa.harvard.edu/ciao/download/conda.html. +<code bash [enable_line_numbers="true"]> 
- +conda create -n ciao-4.16 -c https://cxc.cfa.harvard.edu/conda/ciao -c conda-forge ciao pyciao sherpa ds9 ciao-contrib caldb_main marx python=3.11 
-Here are the steps: +conda activate ciao-4.16 
- +pip uninstall pillow 
-1. Run the following code in a terminal to install ciao and caldb and some associated software in a conda environment named "ciao-4.14". +pip install --no-cache-dir pillow 
- +pip install astropy tqdm 
-<code>conda create -n ciao-4.16 -c https://cxc.cfa.harvard.edu/conda/ciao -c conda-forge ciao pyciao sherpa ds9 ciao-contrib caldb_main marx python=3.11</code> +git clone https://github.com/bcalden/ClusterPyXT 
- +cd ~/ClusterPyXT 
-2. Activate the new conda environment: ''conda activate ciao-4.12'' +python clusterpyxt.py --continue 
- +</code>
-2. Then install ''astropy'', ''jupyter'', ''ipykernel'' inside the ciao environment as: +
- +
-''conda install -n ciao-4.12 jupyter ipykernel astropy'' +
- +
-3. Install git on Ubuntu: ''sudo apt-get install git'' +
- +
-3. Download ClusterPyXT: ''git clone https://github.com/bcalden/ClusterPyXT'' +
- +
-4. Go inside ClusterPyXT: ''cd ~/ClusterPyXT'' +
- +
-5. Initialize the system: run ''python clusterpyxt.py'' and it will ask two things: (1) CIAO installation directory (''~/anaconda3/envs/ciao-4.12''), (2) data output directory. +
- +
-6. Initialize a cluster: run ''python clusterpyxt.py'' again, and answer the questions; type y/n if asked. Give the values of nH (Hydrogen column density), z, metal abundance (use 0.3 for solar abundance), and S/N (signal-to-noise ratio, use 5). +
- +
-7. Download and process the cluster data: <code>python clusterpyxt.py --continue</code>+
- +
  
 +===== Brightness map =====
 +<code bash>
 +blanksky_image bkgfile='_background_clean.evt' outroot='_blank' imgfile='_0.5-7_thresh.img' tmpdir=./ clobber=yes
 +merge_obs
 +</code>
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